by Judith Curry
Part IV of the Climate Etc. series on sea level rise focuses on the satellite era (since 1993), including the recent causes of sea level variations and arguments regarding the acceleration (or not) of recent sea level rise.
Part III considered historical sea level rise in the 19th and 20th centuries and Part II provided an overview of the ‘relatively’ recent geological evidence for sea level variability and rise.
Satellite altimetry
Since 1992, measurements of global satellite sea level have been obtained from satellites. Satellite altimeters measure the time taken by a radar pulse to travel from the satellite antenna to the sea surface and back to the satellite receiver. Converting the signal received by the satellite altimeter to global sea level heights is a complex undertaking.
As described by Ablain et al. (2016), the following corrections need to be applied to the SSH measurement from satellite altimeters: propagation corrections as the altimeter radar wave is delayed during atmosphere travel (ionospheric correction, wet tropospheric correction, dry tropospheric correction), and ocean surface correction for the sea state which directly affects the radar wave (electromagnetic bias). After making these corrections for interferences of the radar signal, the travelling time of the radar signal time is transformed into a distance, or ‘range’. Additional corrections are made for tides, and the ocean response to atmospheric pressure variations.
Determination of sea level height (SSH) from the altimeter range requires a reference to the mean sea surface at rest. To accomplish this, satellite altimetry datasets are complemented by satellite data that provides gravimetric measures — measures of the distribution of mass on the Earth and oceans. The force of gravity is affected by density anomalies in Earth’s interior, the rotation of Earth and topographic features. The Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite missions are used to map the Earth’s gravity field and its changes through time. This gravity field provides the basis for calculating the height of the geoid that corresponds to the mean sea surface at rest. Subtracting from the measured SSH from a reference mean sea surface provides a ‘SSH anomaly’. Calculation of the SSH anomaly at each point in the ocean is repeated very 10 days – the satellite track repeat cycle.
Ablain et al. (2016) has assessed the errors in global mean sea level (GMSL) determined from satellites. Regarding the GMSL trend, an uncertainty of 0.5 mm/year was estimated over the whole altimetry era (1993–2015) within a confidence interval of 95%. The main source of error is the radiometer wet tropospheric correction with a drift uncertainty in the range of 0.2– 0.3 mm/year. Orbit error and the altimeter parameters instabilities add additional uncertainty, of the order of 0.1 mm/year. The uncertainties are higher in the first altimetry decade (1993– 2002). Differences between TOPEX-A and TOPEX-B (February 1999), TOPEX- B and Jason-1 (April 2003), Jason-1 and Jason-2 (October 2008) lead to errors of 2, 1 and 0.5 mm, respectively, result in a GMSL trend uncertainty of about 0.1 mm/year over the 1993–2014 period.
Significant work has been done to devise methods to accurately calibrate altimeter measurements against a global network of tide gauges. As a result, a number of drifts and bias changes have been discovered and corrected, including an early software error that caused the estimate to be nearly 7 mm yr-1 too high, drifts in the water vapor correction from the microwave radiometer, and changes in the sea state bias model. Calibration efforts are ongoing, which is essential for obtaining an accurate climate record from satellite altimetry.
Summary. Satellite measurements of global sea level have been available since 1992, and the technology is under continuing development. Complex analysis methods are required to transform raw satellite measurements into sea level variations, including the correction and piecing together of records collected over many years by ageing and changing satellites. Estimates of sea level change made using satellite-collected data are associated with many uncertainties in the data processing; with time, the uncertainty in current analysis methods and datasets may be revised as addition errors are uncovered. There is some inconsistency between the results derived by different research groups for the interannual variability, owing to differences in making the complex adjustments. These uncertainties underscore the need for continual scrutiny of the satellite and in situ tide gauge data, plus the need for independent observing systems such as multiple satellite altimeters with differing instrument designs, the tide gauge network, in situ ocean temperature observing system, and gravimetric satellites.
Satellite observations of SLR since 1993
From the IPCC AR5, Chapter 3:
The rate of GMSL rise from 1993–2010 is 3.2 [2.8 to 3.6] mm yr-1 based on the average of altimeter time series published by multiple groups. As noted in AR4, this rate continues to be statistically higher than that for the 20th century. There is high confidence that this change is real and not an artefact of the different sampling or change in instrumentation, as the trends estimated over the same period from tide gauges and altimetry are consistent. Although the rate of GMSL rise has a slightly lower trend between 2005 and 2010, this variation is consistent with earlier interannual fluctuations in the record (e.g., 1993–1997), mostly attributable to El Niño/La Niña cycles.
Products from six processing groups are available for the altimetry-based sea level data, based on TOPEX/Poseidon, Jason-1 and Jason-2:
Figure 1 shows the GMSL time series from CU, which is current to 2/12/18
Figure 1. From University of Colorado,downloaded 2/12/18
Substantial interannual variations are seen, which are associated primarily with ENSO. The large trend between 2011 and 2016 is associated with a very strong LaNina (2011) and a very strong El Nino (2016).
Ablain et al. (2016) compared the Multivariate ENSO Index (MEI) with the global sea level time series after removing the mean trend (Figure 2). Recent studies have shown that the short-term fluctuations in the altimetry-based GMSL are mainly due to variations in global land water storage (mostly in the tropics), with a tendency for land water deficit (and temporary increase of the GMSL) during El Nino events [LINK] and the opposite during La Nina [LINK].
Figure 2. From Ablain et al. (2016)
A recent update to the altimeter sea level dataset is associated with a correction to the TOPEX altimeter data in the way that satellite drift is treated. Beckley et al. (2017) and Watson et al. (2015) have argued for adjusting the TOPEX sea level data downwards during the period 1993-1999. This adjustment is included in Figure 1 above.
Spatial variability of sea level rise
Arguably the most important contribution from the satellite altimeters to our understanding of sea level is associated with the spatial variability of sea level rise. Over the globe, significant regional variations occur in the rate of sea-level change. These variations are partly due to variations in the rate of warming and salinity changes between different regions, and the proximity to discharges of meltwater. But primarily these variations reflect the influence of major ocean circulation systems that redistribute heat and mass through the oceans. As a result, at any location around or within the oceans, the observed sea level behavior can differ significantly from the global average. Additionally, this understanding of the spatial variability of sea level rise is very important for interpreting the tide guage record of sea level rise.
Ablain et al. (2016) provides a map of sea level trends over the period 1993-2014. Regional trend errors generally range from 1 to 3 mm/yr. Trends are not significant in areas of high oceanic variability. Note the very large sea level rise anomalies in the tropical west Pacific and the South Pacific and Indian Oceans.
Figure 3. From Ablain et al. (2016)
Reconciliation with tide gauges
The IPCC AR5 states:
It is very likely that the mean rate was 1.7 [1.5 to 1.9] mm yr-1 between 1901 and 2010 and increased to 3.2 [2.8 to 3.6] mm yr-1 between 1993 and 2010.
Rates of GMSL rise during the altimeter period (since 1993) are about twice as large as the rates of GMSL rise during the period 1900-1993 (1.5 ± 0.2 mm/yr). Is this increase in the rate of sea level rise real, or does this reflect an apples-to-oranges comparison using fundamentally different measuring technologies and assumptions?
There have been numerous studies that compare the tide guage with altimeter values during the period since 1993:
Merrifield et al. (2009): After 1990, the global trend increases to the most recent rate of 3.2 ± 0.4 mm yr-1, matching estimates obtained from satellite altimetry.
Jevrejeva et al. (2014): There is a good agreement between the rate of sea level rise (3.2 ± 0.4 mm· yr-1) calculated from satellite altimetry and the rate of 3.1 ± 0.6 mm·yr-1 from tide gauge based reconstruction for the overlapping time period (1993–2009).
Hay et al. (2015): Our analysis, which combines tide gauge records with physics-based and model-derived geometries of the various contributing signals, also indicates that GMSL rose at a rate of 3.0 ± 0.7 millimetres per year between 1993 and 2010 . . . is also consistent with the estimate based on TOPEX and Jason altimeter measurements (3.2 ± 0.4 mm yr-1 for the period 1993–2010.)
Dangendorf et al. 2016: our estimate of 3.1 ± 1.4 mm⋅y−1 from 1993 to 2012 is consistent with independent estimates from satellite altimetry.
Figure 4 shows that there is some sort of SLR acceleration that occurred in the 1990s, and that this increase is evident in the tide guage record. Merrifield et al. (2009) examined the tide guage data from 1965 to 2000 for an interpretation. Prior to the late-1980s or so, the global trend is relatively steady. After 1989, there is a sharp increase in the rate of sea level that continues through the 1990’s.
Figure 4. From Merrifield et al. (2009)
Merrifield et al. (2009) note that the Northern Hemisphere oceans play a surprisingly small role in the acceleration. Dangendorf et al. (2016) found that this sharp increase was geographically dominated by the Indian Ocean–Southern Pacific region, marking a transition from lower-than-average rates before 1990 toward unprecedented high rates in recent decades. Merrifield et al. (2009) identified a covariation of regional sea level in the tropics and southern oceans that represents a shift from a state where the two regions once varied out of phase to now apparently varying more in phase. These ‘hot spot’ regions are clearly visible in the spatial map of rates of sea level rise (Figure 3, preceding section).
Note: the recent values of sea level rise of 1.1 or 1.2 mm/yr between 1900 and 1990 imply a greater acceleration in the 1990’s.
The ‘acceleration’ debate
The important question is not ‘is the long-term rate of sea-level rising’, since the geological, tide-gauge and satellite record all agree that it is and, all other things being equal, will continue to do so. Rather, in context of detecting a human influence on sea level rise, the key question is: ‘is the rate of sea-level rise accelerating?’
Recent headlines (February 2018) proclaim:
- CNN: Satellite observations show sea levels rising, and climate change is accelerating it
- USA Today: Miami could be underwater in your kid’s lifetimes as sea level rise accelerates
- The Weather Network: Global sea level rise on faster pace than expected.
Before delving into the recent Nerem et al. paper that is subject of these articles, I provide some context for interpreting acceleration or deceleration over the relatively short time period since 1993.
The IPCC AR5 Chapter 3 acknowledges that a long time series is needed to detect acceleration in sea level rise from human caused climate change. “While technically correct that these multidecadal changes represent acceleration/deceleration of sea level, they should not be interpreted as change in the longer-term rate of sea level rise, as a time series longer than the variability is required to detect those trends.”
Nevertheless, there have been several recent papers addressing acceleration/deceleration in sea level rise over the short time period (since 1993) of the satellite altimeter record, searching for a human fingerprint:
From Cazenave et al (2014) The rate of sea level rise.
Since the early 1990’s, sea level rose at a mean rate of ~3.1 mm/yr. However, over the last decade a showdown of this rate of about 30% has been recorded. It coincides with a plateau in Earth’s mean surface temperature, known as the recent pause in warming. Here we present an analysis that separates interannual natural variability in sea level from the longer-term change probably related to anthropogenic global warming. We find that when correcting for interannual variability, the past decade’s slowdown of global mean sea level disappears.
Fasullo, Nerem & Hamlington (2016), Is the detection of accelerated sea level rise imminent?
“Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time. In stark contrast to this expectation however, current altimeter products show the rate of sea level rise to have decreased from the first to second decades of the altimeter era. Here, a combined analysis of altimeter data and specially designed climate model simulations shows the 1991 eruption of Mt Pinatubo to likely have masked the acceleration that would have otherwise occurred. This masking arose largely from a recovery in ocean heat content through the mid to late 1990 s subsequent to major heat content reductions in the years following the eruption. A consequence of this finding is that barring another major volcanic eruption, a detectable acceleration is likely to emerge from the noise of internal climate variability in the coming decade.
Nerem et al. recently published a paper entitled Climate-change-driven acceleration detected in the altimeter era. The punchline conclusion:
Using a 25-y time series of precision satellite altimeter data from TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3, we estimate the climate-change–driven acceleration of global mean sea level over the last 25 y to be 0.084 ± 0.025 mm/y2.
This follows recent publications by Cazenave et al. (2014) and Fasullo et al. (2016) that found no acceleration, or even found deceleration. What changed?
Apart from several additional years of data, the acceleration hinges on the new adjustment to the TOPEX record during the period 1993-1999 recommended by Beckley et al. (2017) and Watson et al. (2015). Nerem et al. (2018) use this revised data set as the basis for statistically ‘eliminating’ the effects of ENSO and the 1992 Pinatubo eruption. Using a simple quadratic fit the residual time series, they identify an acceleration that the attribute to ‘climate change’, without actually stating whether or why this climate change can be attributed to humans (instead of e.g. multi-decadal ocean oscillations). The implication that this is associated with human-caused climate change comes from this statement:
Coupled with the average climate-change–driven rate of sea level rise over these same 25 y of 2.9 mm/y, simple extrapolation of the quadratic implies global mean sea level could rise 65 ± 12 cm by 2100 compared with 2005, roughly in agreement with the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5) model projections.
The flip from deceleration to acceleration hinges on a substantial adjustment to the first 6 years of the TOPEX record, which is associated with much greater uncertainty than the later JASON data. And this is not to mention the questionable statistical methods used to ‘eliminate’ the impact of Pinatubo and ENSO, and to determine an acceleration (these issues will be addressed in Part V).
UPDATE from frankclimate in the comments:
Re Nerem et al 2017: I think that the application of a quadratic fit is not justified at all. I digitized the Fig.1 of this paper http://www.pnas.org/content/pnas/early/2018/02/06/1717312115.full.pdf
for the years after 2000 to avoid the TOPEX and/or the Pinatubo issues. Thereafter I calculated the linear trends 2000…2016 ( for Nerem et al) and 2000…2017 for the “Colorado” data. The residuals in annual resolution:
https://i.imgur.com/X6HGci6.jpg
The “ENSO removal” didn’t work. IMO they didn’t remove the ENSO index but reduced the impacts by about a half. See 2011 and 2016. In the raw data the ENSO blop is reduced in 2017 but not in the paper whrere the data end in the end of 2016. The relation stands and in the end they have a ENSO-blop which influences a trend very much. Together with the data before 2000 this gives only a plea to estimate a quadratic trend. This could have been seen also in their Figure 2:
https://i.imgur.com/fGHsFUz.jpg
The monthly datapoints inscribe much noise but the not succesful removal of the 2015/16 ENSO-impacts are clearly visible and also the suspicious behaviour in the late 90s. As a reviewer I would have asked for an annual resolved record and would have pointed to the ElNino in the end of the record.
In my opinion, the value of the altimeter data is in understanding regional and interannual variability, and that the first 6 years of altimeter data should be pretty much ignored in climate change arguments. In any event, the altimeter data set is not useful by itself (owing to its short length) for detecting long-term accelerations that could be attributed to human-caused climate change.
The bigger issue of whether there is a detectable signal from humans in the record of sea level rise will be addressed in Part V.
Controversies surrounding the altimeter-derived SLR data
The controversies surrounding the altimeter SLR data set are associated with the myriad corrections/adjustments that are made to the data set.
A recent paper by Chen et al. (2017) illustrates the difference between the unadjusted and adjusted SLR data, where the red and orange curves are adjusted (CSIRO), and the blue-gray colors correspond to unadjusted measurements from three different teams:
Figure 5: From Chen et al (2017).
Specifically, the unadjusted data refers to omitting the glacial isostatic adjustment (GIA) or Global Positioning System (GPS) data set to correct for the effects of vertical land motion. Figure 5 shows a deceleration using the unadjusted rates of SLR. With regards to the sea level rate figure (bottom), details are not given regarding exactly what it represents, but it appears to be calculated from 10 year averages.
The implication is that any acceleration in rates is largely associated with the VLM adjustments. The generally recognized uncertainty in the GIA/VLM adjustments is ±0.3 mm/yr.
In (2004), Nils Axel Morner published a paper that points out that the raw satellite data shows barely any rise:
The raw data from the TOPEX/POSEIDON sea-level satellites, which operated from 1993-2000, shows a slight uptrend in sea level. However, after exclusion of the distorting effects of the Great El Niño Southern Oscillation of 1997/1998, a naturally-occurring event, the sea-level trend is zero.
Nerem et al. (2007) published a rebuttal to Morner, stating that Mörner’s claim that sea levels are not rising has been criticised for ignoring correctly calibrated satellite altimeter records all of which show that sea levels are rising.”
The rebuttal systematically goes through all the adjustments and corrections ignored by Morner:
Satellite altimetry is somewhat unique in that many adjustments must be made to the raw range measurements to account for atmospheric delays (ionosphere, troposphere), ocean tides, variations in wave height (which can bias how the altimeter measures sea level), and a variety of other effects. In addition, the sea level measurements can be affected by the method used to process the altimeter waveforms, and by the techniques and data used to compute the orbit of the satellite.
One of the errors is caused by a drift in the TOPEX Microwave Radiometer (TMR). It was first observed in sea level via a comparison to tide gauges, and was verified to be caused by the TMR via comparisons to other orbiting microwave radiometers and radio- sondes. It caused a drift of nearly −1.2 mm/year in measured GMSL until early 1998, and then a bias of −5 mm. A second major error was introduced when the redundant TOPEX altimeter was turned on in early 1999 due to degradation in the original instrument. Since the electronics of the redundant altimeter were different, it caused an apparent bias in the GMSL measurement related to the Sea State Bias (SSB). The sense of the bias was such to cause an incorrect sudden drop in GMSL from the end of 1998 to the beginning of 1999 of nearly 10 mm. This error is removed when an updated SSB model is applied.
The net result of this exchange is that this does not inspire confidence in the altimetry data, and makes me wonder whether their uncertainty/error assessment is reasonable.
A note on why I prefer blog dialogue to attempting to conduct this via journal publications. Morner’s 2004 publication was submitted in 2001. The Nerem et al rebuttal is published in 2007, and Morner’s response is published in 2013!
In his (2013) response to Nerem et al., Morner states:
“It is because of the introduction of additional calibrations — and those “calibrations” are subjective interpretations; not objective readings. Consequently, they are opinion-dependent. “We adopt the rate given by Douglas (1991,1995) of 1.8±0.1 mm/yr” [for long-term sea level rise], Mitchum (2000) states. This rate, however, is widely debated and far from generally accepted.
Wait a minute. The latest/greatest estimates for long term sea level rise is 1.1 or 1.2 ± 0.2 or .03 mm/yr. How would incorporating these lower long-term rates of sea level rise influence the interpretation of altimeter measurements? I haven’t yet dug into the weeds sufficiently on this, would appreciate any insights on this.
The JASON Products Handbook provides a very detailed technical reference on processing and interpretation of the raw satellite data. The errors in many of the processing steps are measured in centimeters; I have no idea how to reconcile these numbers with reported confidence intervals in sea level rise numbers. Apparently spatial averaging reduces these errors to millimeters.
The accuracy of Jason series altimetry is limited to +/- 3.4 centimeters (possibly as good as +/- 2 cm). Many of the uncertainties in the data processing are even larger than the inherent measurement uncertainty. The assessment of errors in the altimetry sea level data set seem to come more from the differences between ‘independent’ analyses of the dataset, rather than careful consideration of all of the uncertainties involved. The end result is that the ‘calibrations’ are far larger than the derived changes in global mean sea level. I have no doubt that many errors and sources of uncertainty in the altimeter data set have yet to be identified and understood. The recent error highlighted by Nerem et al. (2018) is a case in point.
Sea level rise budgets during the satellite era can in principle be used as a check on the altimeter-derived sea level rise. There is a plethora of such studies that will be explored in more detail in in Part V on attribution. Here I provide the budget from Chen et al. (2017) that includes both adjusted and unadjusted rates of sea level rise:
Figure 6. From Chen et al. (2017)
The components of the SLR budget reasonably match the adjusted altimeter record (not the unadjusted record). Notice that the sum of steric and glacier components follow the slope (but not magnitude) of the unadjusted SLR rates. Greenland melting is primarily responsible for increase in sea level rates. The ice sheet melting is determined from GRACE satellite using many adjustments, including the GIA adjustment. I haven’t deeply dug into exactly what is done for determining ice sheet contribution to SLR, but there may be some circular reasoning involved in the adjustments that promote a balance with the adjusted SLR rates determined from satellite altimetry — I would appreciate any insights on this (note I will be digging deeper into this issue for Part V).
As concluded by Wunsch et al. (2007) with respect to the satellite measurements:
At best, the determination and attribution of global-mean sea-level change lies at the very edge of knowledge and technology. Both systematic and random errors are of concern, the former particularly, because of the changes in technology and sampling methods over the many decades, the latter from the very great spatial and temporal variability. It remains possible that the database is insufficient to compute mean sea-level trends with the accuracy necessary to discuss the impact of global warming – as disappointing as this conclusion may be. The priority has to be to make such calculations possible in the future.
Forthcoming Part V: Attribution addresses arguments for the causes of sea level rise since the 19th century, with a focus on the period since 1950. In particular, we assess the arguments for attributing any of the recent sea level rise to human caused global warming.
JC note: I am continuing to update Parts I-III, based on your comments and additional information that I come across. Your emails and blog comments have been extremely useful to me in this endeavor. Keep the comments and emails coming!
Dr. Curry ==> (I am commenting as I go through your post) ” the first 6 years of altimeter data should be pretty much ignored in climate change arguments. In any event, the altimeter data set is not useful by itself (owing to its short length) for dectecting long-term accelerations that could be attributed to human-caused climate change.” That was my first impression after reading Nerem’s latest paper. I created this version of his graph to illustrate:
https://i0.wp.com/wattsupwiththat.files.wordpress.com/2018/02/gmsl_no_topexa1.jpg
JC ==> “In any event, the altimeter data set is not useful by itself (owing to its short length) for dectecting [typo] long-term accelerations that could be attributed to human-caused climate change.”
Yes, we are looking at the wiggles in this short a time-series.
fixed, thx!
In the section comparing altimetric results to tide gauges, the summary for Dangendorf et al. (2016) accidentally repeats that of Jevrejeva et al. (2014). It should read, “our estimate of 3.1 ± 1.4 mm⋅y−1 from 1993 to 2012 is consistent with independent estimates from satellite altimetry.”
fixed, thx!
JC ==> From Mörner (2008) “…the rate given by Douglas…of 1.8±0.1mm/yr”. This rate has been the “gold standard” on long-term SLR rate pre-satellite for a long time….I have used it in all my essays as a pretty-good assumption based on tide gauges (known to be dubious), but with a cm scale uncertainty bar.
The deal is, as I see it, is that we don’t really know — with real accuracy or precision — what the rate of SLR was between 1890s and 1990s. The Battery in NY (secured in Manhattan bedrock) saw 1.3 mm/yr subsidence (GIA in this case) — 1/3 of the recorded SLR there — in the end, “The correct result for Absolute Sea Level Rise at The Battery is 3.34 inches over 50 years 1963-2013,” equivalent to 1.7 mm/yr for that same period. [ see here ] But that could be just a regional phenomena.
JC ==> I’m a journalist, not a sea level specialist, but from my rather extensive study over the last few years, I believe that what Wunsch et al. (2007) said with respect to the satellite measurements is as true today as it was ten years ago.
Subjective uncertainties requiring corrections one and two orders of magnitude greater than the annual/decadal delta in sea surface height, as well as outright “additions” based on calculated “ought to be”s (not actually manifested in changes to physical sea surface height) shake my confidence in the satellite SL calculations, from all groups.
This follows recent publications by Cazenave et al. (2014) and Fasullo et al. (2016) that found deceleration. What changed? – Professor Curry
Cazenave compared two periods within the satellite data that roughly compare to these two graphs:
https://i.imgur.com/IBuG4ht.png
https://i.imgur.com/CPAq4ec.png
When she a accounted for natural variation, the deceleration disappeared. No surprise, the 2nd period includes the huge La Niña drop.
As for Fasullo 2016, the word “deceleration” does not appear in his paper. He found that on an acceleration was imminent.
” I have no idea how to reconcile these numbers with reported confidence intervals in sea level rise numbers. Apparently spatial averaging reduces these errors to millimeters.”
Neither do I!!!
Spatial averaging is inappropriate in this environment. The problem with the satellites is that they are not measuring the same thing (as required by spatial averaging), as each orbit shifts the satellite’s location geographically, and Sea State status, barometric pressure, current movement and a host of other factors change what the satellites measure!
A satellite altimetry would be very precise on a flat sea surface. Unfortunately, that is not the case. Due to the presence of waves, the returned signal is spread in time – some part is reflected from a top of waves, some from the trough, some may be even reflected from a 45 degree slope and then again from an opposite 45 degree slope. Altimetrists say that we have sufficient statistical knowledge about waves, but I doubt that we do: “The rig was built to withstand a calculated 1 in 10,000 years wave with a predicted height of 64 feet (19.5 m) and was also fitted with state-of-the-art laser wave recorder on the platform’s underside. At 3 p.m. on 1 January 1995 it recorded an 85 feet (25.9 m) rogue wave (i.e. 21 feet [6.4 m] taller than the predicted 10,000 year wave) that hit the rig at 45 miles per hour (72.4 km/h). ” [Wikipedia, Rogue wave]
I am sorry. I fail to see the importance of all this. Sea levels rise and fall and there are natural reasons for that behavior. What is unclear in the debate is what benchmark(s) we are referring to? Nowhere in the available literature can we establish how earth’s water is divided up.
Taken that all water, with that I mean the sum of water vapor, liquid, ice and ground water, equals 1. What says that a% = liquid,b% = ice, etc.? There is a continuous exchange going on in the atmosphere and on the ground, but this exchange cannot be quantified (except theoretically) exactly.
To include climate change in the work muddies the water further as water (in any form) is not part of its definition.
If we did not have thermometers we would not have climate change. It is the important activities that goes on around all the thermometers that is either overlooked or just ignored. The full picture of any global warming is found there, not in the casual observance of carbon dioxide.
If we did not have thermometers we would not have climate change. NOT TRUE!
The Vikings moved to Greenland and then left, all due to climate change. We have history books. Climate change is well known without using thermometers.
Since the 1990’s, the contribution of melting Greenland and Antarctica (70% Greenland) have increased from essentially zero to 400 Gt/yr which translates to 1 mm/yr of sea-level rise, so that is one major source of the acceleration since the 1990’s.
https://globalchange.umich.edu/globalchange1/current/lectures/dangerous_climate/Greenland_Antarctica.jpg
The doubling time of this contribution is about a decade, possibly less, so in a decade or so melting ice will be the dominant contributor to sea-level rise. Continuation of that 10-year exponential trend gives over 3 meters between now and 2100.
Exponential acceleration? 3 meters in 82 years? That’s a wee bit higher than AR5 suggests is the plausible range. 3 meters represents about 40% of Greenland’s total ice mass, while the current rate of loss is equal to about 0.01% per year. Your projection is ridiculous. I do wonder sometimes if you make your wild eyed “prorections” with a straight face.
3 meters represents 4% of Greenland + Antarctica. Ten year doubling times are also used by Hansen in his 2016 melt, sea-level rise paper because that is what is indicated in the last 20 years of ice mass data. It reached 1 mm/yr’s worth in a remarkably short time. The IPCC realize that this is an uncertainty factor for their upper limit.
JimD
Antarctica snow accumulations over the last 1000 years Thomas et al 2017
“Our results show that SMB for the total Antarctic Ice Sheet (including
ice shelves) has increased at a rate of 7 ± 0.13 Gt decade−1 since 1800 AD, representing a net reduction in sea level of ∼ 0.02 mm decade−1 since 1800 and ∼ 0.04 mm decade−1 since 1900 AD. The largest contribution is from the Antarc- tic Peninsula (∼ 75 %) where the annual average SMB dur- ing the most recent decade (2001–2010) is 123 ± 44 Gt yr−1 higher than the annual average during the first decade of the 19th century”
JimD
https://www.clim-past.net/13/1491/2017/cp-13-1491-2017.pdf
James Hansen, not the AR5 consensus? That’s an extra-special super-convincing argument. Hansen seems to be a rather cranky old man who likes zooming about the world in private jets to hector people about fossil fuels. When he starts to walk the walk he can start to talk the talk. Until then, not so much.
AR5 says the likely range of sea level rise (thermal expansion plus land supported ice loss) under the RCP 8.5 scenario is 53 to 100 cm, not multiple meters from ice melt alone. The 8.5 scenario is not itself plausible, since it is based on an unrealistic use of coal and other unlikely assumptions. The actual sea level rise will almost certainly be less. Your projection is utterly ridiculous.
Snow accumulation is one side of the equation and the net mass balance in the graph indicates that the other side is getting more important with time.
As Hansen has mentioned, meltwater pulses have occurred several times since the last Ice Age and these are several meters per century when they happen. Under our particularly fast climate change, these tipping points become more likely, and may have already started since 1990.
As usual JimD, your nonsensical scare stories are both endless and not supported by science. They are just silly.
JimD
The change in SMB is affecting SLR as evidence of reducing contribution by .02mm per decade. The study contradicts your graph. Reconcile your graph with this very impressive peer reviewed study with many co-authors. Increasing 7Gt as the study says destroys your graph.
You can check what Hansen has to say for yourself.
https://www.atmos-chem-phys.net/16/3761/2016/acp-16-3761-2016.pdf
I am not trying to scare you, only to prepare you. If a decade from now, the sea-level rise rate is 4 mm/yr, it will be on track with this acceleration cause that should not be just written off.
And if the rate is not 0.4 mm per year in 2028, or not 0.6 mm per year in 2038, or not 1 cm per year in 2048, or not 1.8 cm per year in 2058 and 3.4 cm per year in 2068, etc. then you will be wrong. Not trying to scare you Jim D, just preparing you for the inevitable disappointment.
Yes, sea-level rise wouldn’t reach its first meter until about 2080 with a 10-year doubling rate, and the annual rate would be over 60 mm/yr at that time. It’s just wait and see at this point.
JimD
More than a little hilarious that as a source you use a guy who completely blew a prediction that Manhattan would be underwater by now. If he has a worldview so completely off to miss that, why do you think he knows anything about 2050 or 2100.
You still haven’t acknowledged that the Thomas et al 2017 paper above has discredited your entire Schtick.
Jim D,
The great things about crazy predictions (like endless exponential growth of melt rates), are that they need no physical justification, they are usually so far in the future that actual data can never be used to refute them, and they can be super scary. Sort of like the Club of Rome and crazy 1970’s predictions of civilizational collapse (by decades ago!) due to famine, raw material depletion, etc. Like their arguments, your arguments are unsupported by evidence, not remotely related to science (or even reality), and so just politically motivated rubbish.
Here is the most recent actual Greenland data: http://sciencenordic.com/sites/default/files/imagecache/620x/Grace_curve_La_EN_20170100-1024×588.png
Looks very much NOT continuous exponential increase in melt rate. But of course, you have to actually look at the data to see that. Exponential growth in Greenland mass loss is absurd, wild eyed lunacy.
I gave you the Hansen reference for the consequences of exponential acceleration. It is published work with 18 coauthors. Does he say it will happen? No. Does he say it can happen and has in the past? Yes. You want to suppress any such concerns in your own mind. Fine.
Per Jim D,
“I am not trying to scare you, only to prepare you.”
As in prepare you to don your hip waders, as we know how deep it gets when Jim D starts in with his “data”.
Jim D,
Quite honestly, you are lost. Will sea level continue to rise? Of course. Will that rise be huge, rapid, freightening etc? (Melt-pulse!) Of course not. The plausible rise through 2100 is in the range of 18 -24 inches, and could be less. Where my boat sits in the sea in Florida, 20 inches will make zero difference. There are a dozen more pressing issues for humanity to address, and it is a shame you and your sorry ilk focus on the very least important issues humanity faces. Your comments on sea level, like most of your comments, convey more about your leftist political inclinations than about physical reality or the plausible future. Get a grip on reality if you actually care about the future of humanity. But I very much doubt you do.
steve, this blog has had 4 going on 5 threads on sea level, plus many mentions in the past. Clearly this is a priority for the skeptics because it is already happening and its cause is clear. Downplaying it therefore is an important mission for them because the general public notices things like this and associates it with global warming and therefore CO2 emissions. So I can see why this blog makes it such a focus. The melting acceleration I mention is only 7% per year, slow at first, faster later, and is based on the last couple of decades. It gives 15 cm by 2050. Six inches between now and 2050 is within the range Judith projects on behalf of CFAN. We can’t just dismiss it. People have to be prepared.
https://curryja.files.wordpress.com/2017/11/sea-level-ins.pdf
The issues are this:
• Are the more alarming scenarios probable or even possible?
• Are oil companies to blame for sea level rise (e.g. the growing number of lawsuits)
Jim D,
Yes, by far the most credible negative consequence of GHG driven warming is sea level rise. If this comes as a surprise to you, then you have been for a couple of decades or more.
So, it is not a big suprise that Judith would focus on sea level rise as a subject for multiple blog posts. I have a photo of myself in diapers, sitting next to the sea with my parents (in the summer of 1951). I can see in the photo the very same granite rocks, waves washing over them, that I walked on last summer, waves once again washing over them. Any suggestion that sea level rise is rapid and disruptive is false.
More importantly, whatever the rate of sea level rise will be in the next few decades, it most certainly will not be disruptive. What will be disruptive is the insistance by you and your sorry ilk that the world’s poorest people should remain empoverished, in the hope that atmospheric CO2 rises a bit more slowly. It is worse than a deal with the devil… it is adopting the devil’s goals as your very own.
Jim D,
Yes, by far the most credible negative consequence of GHG driven warming is sea level rise. If this comes as a surprise to you, then you have been for a couple of decades or more.
So, it is not a big suprise that Judith would focus on sea level rise as a subject for multiple blog posts. I have a photo of myself in diapers, sitting next to the sea with my parents (in the summer of 1951). I can see in the photo the very same granite rocks, waves washing over them, that I walked on last summer, waves once again washing over them. Any suggestion that sea level rise is rapid and disruptive is false.
More importantly, whatever the rate of sea level rise will be in the next few decades, it most certainly will not be disruptive. What will be disruptive is the insistance by you and your sorry ilk that the world’s poorest people should remain empoverished, in the hope that atmospheric CO2 rises a bit more slowly. It is worse than a deal with the devil… it is adopting the devil’s goals as your very own.
Judith, can’t you see that little yimmy is accusing you of being a deliberate serial dis-informer on the climate science? Your object being to deceive the public by downplaying the danger from sea level rise. Do you want people to drown? He says it’s your mission, your focus. Why do you put up with that insulting libelous BS?
steve, I was responding to where you said it was the least important issue humanity faces. It now appears that is not what you meant it to sound like. The CFAN estimate does allow for melt accelerations of the type I mentioned at least through 2050, and it is good that there is that realization.
Are oil companies to blame, Judith asks? Coal too, and maybe Republicans, I guess. As I mentioned somewhere else here, the last time we were above 400 ppm over 5 million years ago, Greenland was not glaciated. Values far above 400 ppm are inconsistent with Greenland’s glacier persisting. It is only as we approached 400 ppm that Greenland’s melt rate became a noticeable contribution to sea-level rise. This looks directly tied through the rapidly rising Arctic temperatures. Of course CO2 levels are directly tied to emissions, and that ties it to Greenland’s melt rate. The question was political, so I have to say this. What happened prior to Kyoto, maybe they can plead ignorance, but since then the problem has become known and quantified more and more, so there could be blame for a failure to slow emission rates if that happens via purely political pressures to keep emitting in favor of oil and coal companies that directly fund the politicians, and abandon new technologies that would have helped. It’s not hard to untangle that.
Don, on the contrary, I referenced the CFAN estimate as somewhat credible with its 2050 projection range. In fact their projection is more likely to upset the skeptics as acceleration has to continue for it to be right.
Jim D,
No, the evil Republicans and evil oil companies (or whatever other boogey-men you want to attack) are not “to blame” for the continuing rise in atmospheric CO2. The blame is with all of the billions of people around the world who benefit, personally and directly, from having access to fossil fuel energy, including both you and especially James ‘Private Jet’ Hansen. Whatever policy you want to adopt to restrict access to fossil fuels will immediately and directly hurt billions of people, most of whom are far poorer that you Jim D. Drop the righteousness about fossile fuels and address the reality of poor people who burn dung or charcoal in a paint can to cook their dinner, and for whom a propane stove would be a major improvement in quality of life.
You know, places like Haiti and sub-sahara Africa, where people live on a couple of dollars a day, and where access to reliable electric power is as far away from their day to day reality as your dreams of restricting everyone’s access to fossil fuels and nuclear power are from your’s.
Judith asked who to sue for sea-level rise. I gave an answer in the spirit of the question. For Greenland the difference between 400 ppm and wherever we end up is rather important, requiring the success of efforts like Paris, rather than doing the exact opposite.
Judith,
“• Are the more alarming scenarios probable or even possible?
• Are oil companies to blame for sea level rise (e.g. the growing number of lawsuits”
.
Are the more alarming scenarios probable? Heck no! Possible? Only barely. In spite of James Hansen’s raging about the West Side highway being under water by now, New York is safe from flooding. DeBlasio on the other hand is doing real damage every day
Oil companies? Are ladies of the night to blame for having customers? The suggestion that any oil company is “to blame” is absurd. They sell products people want and need. The lawsuits will fail.
In a just world, the blame goes to the elected politicians who put their own funders’ interests ahead of human interests (on more than one issue now), and a President whose main motivation is to undo Obama in every way possible aided by EPA and Energy chiefs whose least interests are a clean environment and modernizing energy. Yes, you can’t blame the oil and coal companies for trying, but you can blame the politicians for them succeeding so easily in overriding the interests of the people. That’s the part where the system is broken. The swamp in action.
We know what you said, yimmy. Again, the question is:”Why does Judith put up with little fanatic CAGW alarmists coming on her blog and accusing her of being a serial dis-informer.
wow, the shift to the warm phase of the AMO in 1995 had quite an impact!
No ordinary AMO but supercharged by a factor of several by the climate change background trend.
A more valid perspective IMO is that the AMO (and PDO etc) are the fundamental modes of climate variability, with external forcing projecting onto these modes to modify slightly the frequency, phasing and amplitude of these modes.
The size of these oscillations is +/-0.1 C as a global average, while climate change is 1 C already at +0.2 C per decade. This is the driving part. Each AMO/PDO minimum is warmer than the previous maximum 30 years earlier if you think about it. The next minimum will be warmer than this maximum, and not by a little.
Numbers and references Jimbo?
Knudsen et al 2012
“ A key aspect concerns the enigmatic Atlantic Multidecadal Oscillation (AMO), a feature defined by a 60- to 90-year variability in North Atlantic sea-surface temperatures. The nature and origin of the AMO is uncertain, and it remains unknown whether it represents a persistent periodic driver in the climate system, or merely a transient feature. Here, we show that distinct, ∼55- to 70-year oscillations characterized the North Atlantic ocean-atmosphere variability over the past 8,000 years. We test and reject the hypothesis that this climate oscillation was directly forced by periodic changes in solar activity. We therefore conjecture that a quasi-persistent ∼55- to 70-year AMO, linked to internal ocean-atmosphere variability, existed during large parts of the Holocene. “
AMO, the Big Mo for 8,000 years.
RIE, many references. Mann (2014) for example.
http://www.meteo.psu.edu/holocene/public_html/Mann/articles/articles/MannEtAlGRL14.pdf
Insights into Atlantic multidecadal variability using the Last Millennium Reanalysis framework
https://i.imgur.com/kFQBIfd.png
That was Mann’s anti stadium wave paper – something that is patently absurd. The Earth is a globally coupled, chaotic system with leads and lags. Failing to understand that is no confirmation of Mann’s scientific perspicacity. Nor does it remotely support Jimbo’s wild fantasies. “No ordinary AMO but supercharged by a factor of several by the climate change background trend.” If there is something here that confirms that – by all means share.
“Previous studies have shown that seasonal and interannual changes in the subtropical AMOC are forced primarily by changing wind stress mediated by Rossby waves (Zhao & Johns, 2014a, 2014b). There is growing evidence (Delworth et al., 2016; Jackson et al., 2016) that the longer-term changes of the AMOC over the last decade are also associated with thermohaline forcing and that the changed circulation alters the pattern of ocean-atmosphere heat exchange (Gulev et al., 2013). The role of ocean circulation in decadal climate variability has been challenged in recent years with authors suggesting that external, atmospheric-driven changes could produce the observed variability in Atlantic SSTs (Clement et al., 2015). However, the direct observation of a weakened AMOC supports a role for ocean circulation in decadal Atlantic climate variability.” http://onlinelibrary.wiley.com/doi/10.1002/2017GL076350/full
The Clement et al 2015 may have been a better reference for Jimbo.
“Here we show that the main features of the observed AMO are reproduced in models where the ocean heat transport is prescribed and thus cannot be the driver. Allowing the ocean circulation to interact with the atmosphere does not significantly alter the characteristics of the AMO in the current generation of climate models. These results suggest that the AMO is the response to stochastic forcing from the mid-latitude atmospheric circulation, with thermal coupling playing a role in the tropics. In this view, the AMOC and other ocean circulation changes would be largely a response to, not a cause of, the AMO.” Although this would seem to suggest that the AMO is a response to rather than a cause of broad ranging NH climate variability.
JCH waves yet again his AMO standard. “Try to keep up. The AMO is for the gullible.” He seems to imagine that the lack of a 60-80 year spectral signal in LMR data implies that NH climate variability has been eliminated. The LMR data itself would suggest otherwise. There may be another explanation the lack of a spectral signature – at any rate it far from the first and unlikely to be the last word on this.
https://judithcurry.com/2018/02/11/week-in-review-science-edition-76/#comment-866346
The stadium wave has come and gone. Not even its authors noticed it.
RIE, you failed to show any other number than +/-0.1 C for 60-year ocean oscillations in any of those quotes. Try again.
Who to believe?
http://onlinelibrary.wiley.com/doi/10.1002/2014GL061416/pdf
They agree with Mann on variance for 60 years, which is their 30-year window where 0.01 translates to +/-0.1 C. Got anything else?
They all agree on plus +/- 0.1K do they? I think I finally figured out that you are talking sea surface temperature changes – that are a little larger than you suggest. The atmospheric temperature changes in the northern Eurasia region are much larger responding to other atmospheric changes. Much more about polar blocking patterns than energy transfer between ocean and atmosphere in those high latitudes.
It is all rather about timing and leads and lags in a range of indices in the NH. Mann used models, Wyat and Curry used data, Kravtsov et al used both models and data. Data shows the propagation of climate signals through NH indices – the stadium wave – models do not. But no one claims to be able to disentangle intrinsic from forced variability.
On this ‘supercharged’ AMO warming, if rising CO2 forcing increases positive AO/NAO conditions as the IPCC models suggest, that would tend to inhibit AMO warming, as warm AMO states are negative AO/NAO driven.
http://www.woodfortrees.org/graph/esrl-amo/from:1920/plot/esrl-amo/from:1923/to:1935/trend/plot/esrl-amo/from:1993/to:2005/trend
This study shows the North Atlantic since 1850 was the warmest in the peak of the last solar minimum, between 1885 and 1895, because weak solar wind states increase negative AO/NAO conditions.
http://notrickszone.com/wp-content/uploads/2016/12/Holocene-Cooling-Irminger-Sea-North-Atlantic-de-Jong-16.jpg
JimD,
IPCC had suggested Greenland’s contribution was zero or slightly decreased sea level from 1960 to the 1990s. From 1990 to 2012 increased surface melting suggested Greenland was adding up to 1.5 mm/year to sea level. That increase in surface melting has been attributed to a decrease in cloudiness in association with the the North Atlantic Oscillation, so that increased insolation had caused the increased melting.
After 2012, the rate of surface melt decreased and by the end of the 2017 melt season the DMI suggests Greenland gained about 50 billion tons of ice, which would decrease sea level.
You have made an extrapolation for an ever increasing Greenland meltwater contribution into the future that is not supported in reality.
And regards Antarctica there is absolutely no consensus within the research community regards any Antarctic contribution to sea level that would either raise or lower sea level and if anthropogenic causes ever played a part
It has been common to fit exponentials to the ice mass loss because that has been the appearance.
https://media.nature.com/m685/nature-assets/ncomms/2016/160122/ncomms10525/images/ncomms10525-f2.jpg
Easy snow; easy go:
https://i.imgur.com/fkT4qCZ.png
JimD –
The curve fit in your post is a quadratic with vertex assigned to 1996. It is not an exponential.
Extrapolating a quadratic for several times the length of the curve fit, without physical justification, is fraught enough. Extrapolating an exponential under the same circumstances ventures well into the speculative regime.
Harold, thanks for that info. A linear acceleration implied by a quadratic gives 40-50 cm by 2100. The functional form is important. Hansen used an exponential with various time scales for his paper.
As an example of the dangers of simple extrapolation, take the World Bank global population data from 1960-2016. A linear fit, with R^2=0.999, projects to around 14 billion persons in 2100. An exponential fit, with R^2=0.992, predicts over 30 billion. Measured by R^2, both curves are excellent fits to the data set, but there is a huge difference when extrapolated so far. Then there’s reality: most (all?) projections of population in 2100, incorporating observations on the trend of fertility rates, lie well below the lower of those two figures.
Getting back to Greenland: due to topography, it seems implausible that the sea level contribution of Greenland should continue to increase in either a quadratic or exponential manner for the remainder of the century.
Harold, Hansen has quite a lot of discussion on Greenland in his ACP paper including this
“We argue that such a rapid increase in meltwater is plausible
if GHGs keep growing rapidly. Greenland and Antarctica
have outlet glaciers in canyons with bedrock below sea level
well back into the ice sheet (Fretwell et al., 2013; Morlighem
et al., 2014; Pollard et al., 2015). Feedbacks, including ice
sheet darkening due to surface melt (Hansen et al., 2007b;
Robinson et al., 2012; Tedesco et al., 2013; Box et al., 2012)
and lowering and thus warming of the near-coastal ice sheet
surface, make increasing ice melt likely.”
Jim D,
Thanks for the reply. Yes, I have read the Hansen et al. paper which you cite.
“Our approach is to postulate existence of feedbacks that can rapidly accelerate ice melt, impose such rapidly growing freshwater injection on a climate model, and look for a climate response that supports such acceleration. Our imposed ice melt grows nonlinearly in time, specifically exponentially…”
[On Greenland ice melt] “We conclude that empirical data are too brief to imply a characteristic time for ice sheet mass loss or to confirm our hypothesis that continued high fossil fuel emissions leading to CO2 ~600–900 ppm will cause exponential ice mass loss up to several meters of sea level. The empirical data are consistent with a doubling time of the order of a decade, but they cannot exclude slower responses.”
Nor, I will add, functionally different (non-exponential) forms.
Yes, if one *posits* a functional form such as exponential growth, one can arrive at with extreme predictions. See my example on world population, above: an exponential curve fit projects double the population in 2100, compared to a linear extrapolation. The graphs of the Hansen et al. paper show 1m of SLR by approx. 2050, 2070, and 2110 respectively for doubling times of 5, 10, and 20 years. [They note that 5 years is implausible, including it only because it allows them to see a response with less computing time.] In an earlier comment, you calculated that a quadratic form results in around 0.5 m by 2100, much less than either exponential form.
Harold, the exponential form is characteristic of the growth of an instability in a system. Very few natural systems follow a quadratic growth. If the glaciers are beyond their stable temperature, they would be unstable, and so this is how a tipping point would operate. It may look slow now, and at the beginning an exponential can’t be distinguished from a quadratic, but the 10-year doubling time scale is a 7% annual growth rate which after a while becomes the dominant process. If the melting event of 2012 repeats more often, that is another mode of mass loss separate from calving that would allow acceleration.
“After more than 15 productive years in orbit, the U.S./German GRACE (Gravity Recovery and Climate Experiment) satellite mission has ended science operations”
Does this mean the current and future measurements are now running blind?
2018:
The budget proposes $1.78 billion for Earth science, a cut of 6%. It includes missions to launch this year such as the next set of GRACE gravity-measuring satellites, and ICESat-2 to measure polar ice.
Maybe you could ask those paragons of climate purity in China to step up and fund the mission.
Angech,
The replacement Grace mission is funded and will launch in April this year from Vandenberg AFB on a Falcon 9 rocket (a communications satellite will share the rocket). No satellite missions have been canceled AFAIK.
But if you want scream “Oh my God, Trump is destroying science, humanity’s future, and Earth itself!”, as you run down the street weeping, that will affirm the crazy beliefs of some regular commenters on this blog.
“The Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite missions are used to map the Earth’s gravity field and its changes through time. This gravity field provides the basis for calculating the height of the geoid that corresponds to the mean sea surface at rest. Subtracting from the measured SSH from a reference mean sea surface provides a ‘SSH anomaly’. Calculation of the SSH anomaly at each point in the ocean is repeated very 10 days – the satellite track repeat cycle.”
Means all the recent calculations are being done without GRACE direct input since October hence not relianble
From Chambers et al 2012
. “Until we understand whether the multi decadal variations in sea level reflect distinct inflexion points or a 60-year oscillation and whether there is a GMSL signature, one should be cautious about computations of acceleration in sea level records unless they are longer than two cycles of the oscillation or at least account for the possibility of a 60-year oscillation in their model. This especially applies to interpretation of acceleration in GMSL using only the 20-year record of from satellite altimetry and to evaluations of short records of mean sea level from individual gauges.”
Is there a 60-year oscillation in global mean sea level?
Authors
Don P. Chambers,
Mark A. Merrifield,
R. Steven Nerem
========
Climate-change–driven accelerated sea-level rise detected in the altimeter era
R. S. Nerema, B. D. Beckley, J. T. Fasullo, B. D. Hamlington, D. Masters, and G. T. Mitchum
Edited by Anny Cazenave, Centre National d’Etudes Spatiales, Toulouse, France, and approved January 9, 2018 (received for review October 2, 2017)
ACKNOWLEDGMENTS. M. Merrifield and P. Thompson provided feedback on an initial draft of the paper.
=========
Quantifying recent acceleration in sea level unrelated to internal climate variability
Calafat, F.M.; Chambers, D.P 2013
Wenzel et al 2014
“Although the acceleration (+0.0042+-0.0092mm/yr) found for the global mean sea level rise is not significant….”
With error bars like that, it doesn’t engender much confidence.
Is there a 60-year oscillation in global mean sea level?
–
Is there a simple mathematical model that predicts the appearance of quasi 60 year cycles?
For instance if the average yearly variance is 0.3 mm will this tend, in a naturally varying chaotic state, to give buildups or down of 1 – 2 mm mimicking a 60 year variance purely by the maths?
–
Any statisticians out there.
Gauges will tell: https://tidesandcurrents.noaa.gov/sltrends/global_50yr.htm?stnid=190-091
It is evident!
angech
I wasn’t sure if you were looking for papers that concluded there was a 60 year cycle, there are many, or just looking at a statistical method for discovery. But as oppti says the tidal gauges tell the story better than anything else.
angech,
Is there a simple mathematical model that predicts the appearance of quasi 60 year cycles?
Yes, a quasi-60 year cycle since the 19th Century is a simple expectation due to the timing of major volcanic eruptions. The volcanically-active late-19th/early-20th Century periods gave way to the quiet mid-20th Century, which was then followed by the active late-20th Century. Here’s a plot showing volcanic forcing smoothed with a 15-year running mean in order to demonstrate the multi-decadal influence. As you can see, it suggests we should see a 60-year climate “cycle” with timing very similar to that indicated by sea level reconstructions.
The appearance of the trough part of the “cycle” from ~1960-1990 is also very likely enhanced by the sharp post-WW2 increase in anthropogenic aerosol forcing, while the increased rate up to the mid-20th Century was probably enhanced by increases in high-latitude anthropogenic black carbon emissions affecting glaciers.
This of course means there is no real “cycle”, unless we suggest that major volcanic eruptions follow quasi-cyclical behaviour.
The troughs in your volcanic forcing “cycle” are 100+ years apart, not 60 years!
It would be pointlessly academic to argue what sea level rate periodicity volcanic forcing would imply, particularly since there isn’t a true periodicity. Instead I’ll simply point to Figure 1 A and B from Dangendorf et al. 2017 (a similar plot was produced for AR5 Chapter 13), which shows that a multi-decadal “cycle” appears as a consequence of known, well-understood natural and anthropogenic forcing variability. The apparent periodicity of this “cycle” can certainly be described as quasi-60 year.
This forced oscillation also explains much of the apparent “cycle” in the observed tide gauge sea level reconstructions. Of course the fit isn’t perfect, we wouldn’t expect it to be for two primary reasons:
1) There is internal variability influence on multiple timescales. Particularly important seems to be decadal variability, over 10-15 year periods. In concert with the multi-decadal forced response, these fluctuations are very likely to modulate apparent multi-decadal periodicities for anyone looking to construct cycles in global sea level trends.
2) The historical data is far from perfect. Since we have altimeter data with near-global coverage, it’s plain to see that the high-frequency variability in tide gauge reconstructions does not reflect real variability in global mean sea level. The amplitude of that variability increases further back in time, which is expected given the decrease in tide gauge sites and heterogeneity of geographical coverage. Therefore the variability in rates depicted, particularly over the early 20th Century (and late 19th Century) has to be considered somewhat suspect.
All in all, observed sea level variability over the 20th Century can be amply explained as a consequence of known forced, and less-known unforced, variability in context of imperfect observational records.
On the other hand, those seeking to promote the idea that observed multi-decadal variability in SLR rates simply (and accurately) reflects entirely secular unforced oscillations need to explain why the well-understood physics of e.g. volcanic forcing somehow does not influence this aspect of climate.
There is this informative recent letter on this topic:
From Reply from Nils-Axel Mörner on the problems of estimating Future Sea Level Changes as asked by Albert Parker in letter of January 2, 2018
“There are physical frames to consider. Ice melting requires time and heating, strictly bounded by physical laws. At the largest climatic jump in the last 20,000 years – viz. at the Pleistocene/Holocene boundary about 11,000 years BP – ice melted under extreme temperature forcing; still sea level only rose at a rate of about 10 mm/yr (or just a little more if one would consider more extreme eustatic reconstructions). Today, under interglacial climatic conditions with all the glacial ice caps gone climate forcing can only rise global sea level by a fraction of the 11,000 BP rate, which in comparison with the values of Garner et al. [1] would imply:
well below 0.4 m at 2050 instead of +0.6 m
well below 0.9 m at 2100 instead of +2.6 m
well below 2.9 m at 2300 instead of +17.5 m
Consequently, the values given by Garner et al. [1] violate physical laws and common glaciological knowledge. Therefore, their values must not be set as standard in coastal planning (point 2 above).
The mean sea level rise over the last 125 years is +0.81 ±0.18 mm/yr. At Stockholm in Sweden, the absolute uplift over the last 3000 years is strictly measured at +4.9 mm/yr. The mean tide-gauge change is -3.8 mm/yr, giving a eustatic component of +1.1 mm/yr for the last 150 years. In Amsterdam, the long-term subsidence is known as +0.4 mm/yr. The Amsterdam/Ijmuiden stations record a relative rise of +1.5 mm/yr, which give a eustatic component of +1.1 mm/yr.
Global Loading Adjustment has been widely used in order to estimate global sea level changes. Obviously, the globe must adjust its rate of rotation and geoid relief in close agreement with the glacial eustatic rise in sea level after the last Ice Age. The possible internal glacial loading adjustment is much more complicated, and even questionable, however.
Direct coastal analysis of morphology, stratigraphy, biological criteria, coastal dynamics, etc usually offers the far best means of recording the on-going sea level variations in a correct and meaningful way. It calls for hard work in the field and deep knowledge in a number of subjects. We have, very successfully, applied it in the Maldives, in Bangladesh, in Goa in southern India, and now also in the Fiji Islands. In all these sites, direct coastal analyses indicate full eustatic stability over the last 50-70 years, and long-term variations over the last 500 years that are consistent with “rotational eustasy” or “Global Solar Cycle Oscillations” (GSCO).”
https://www.researchgate.net/publication/322256322_Reply_from_Nils-Axel_Morner_on_the_problems_of_estimating_Future_Sea_Level_Changes_as_asked_by_Albert_Parker_in_letter_of_January_2_2018
While we wait for better data and methods, it is usually best to go with the available evidence, keeping in mind that its uncertainty limits the conclusions.
-Both tide gauges and satellite altimetry agree that SLR rate has increased from the 20th century average to the 21st century average. There is long term acceleration.
-Over the past 25 years the acceleration is not seen in the data. The last 20 years show zero acceleration. There is short term lack of acceleration.
The evidence indicates the acceleration in SLR is due to two processes:
1. A 60-year oscillation that dominates over periods of a few decades. This oscillation is likely responsible for the recent lack of acceleration.
2. A long term trend that probably started about 2 centuries ago, coinciding with the increased melting of glaciers ~ 1850. This accelerating trend is responsible for 21st century SLR being higher than its 20th century average.
Anthropogenic forcing should affect the long term trend, but there is no evidence for that. A much longer period of observation is required to confirm or reject such effect, but considering the increase in CO₂, that the effect is not detectable is surprising and does not support catastrophic outcomes over the next 100 years.
We have to keep in mind that if SLR measurements were so dominated by errors that could not be trusted, they would not agree so well with ENSO, unless we want to defend that they are being adjusted to fit ENSO values.
The seem to capture interannual and spatial variability in a reasonable way, although the interannual budgets don’t balance and different datasets show different values for interannual variability. The issue is absolute values of rates of sea level rise
The budget doesn’t balance because it is a single equation with several unknowns.
The long term acceleration in SLR is hard to set because it is very small, constrained by most authors to a value ~ 0.01 mm/yr², requiring records of a century or longer.
In most disciplines this issue would be considered uncontroversial. Although exact values are not known, there is general agreement between researchers on the magnitude and direction of the changes.
The controversy really is about the projections, meaning that it is not in the data, but in the models. As is usually the case with forecasting, models that are not conservative enough, have a very high chance of being wrong. But in terms of publishing, it is the present that matters, and a highly unlikely projection that attracts more attention is preferred. Many journals are not neutral in the climate wars.
And let’s not forget that your own supported “Stadium wave” hypothesis projects a deceleration of SLR over the next couple of decades, if I have interpreted it correctly. That ought to be fun.
The stadium wave reflects the multi-decadal variability, on top of a longer term secular trend. The stadium wave says nothing about the secular trend. The stadium wave posits that we could see a dip in rates of sea level rise, comparable to what we saw in 1960-1980 (i’ve added a new figure illustrating this in Part III). 21st century projections will be topic of ~Part VIII
“Many journals are not neutral in the climate wars.”
Oddly enough, I had noticed that too.
1. A 60-year oscillation that dominates over periods of a few decades. This oscillation is likely responsible for the recent lack of acceleration.
Which oscillation?
The oscillation found by several authors on sea level data, including:
Jevrejeva, S., Moore, J. C., Grinsted, A., & Woodworth, P. L. (2008). Recent global sea level acceleration started over 200 years ago?. Geophysical Research Letters, 35(8).
“The multi-decadal variability in global sea level for the past 300 years shows the same pattern as previously found in the climate system [Delworth and Mann, 2000], including a 60–70 years variability in sea surface temperature (SST) and sea level pressure (SLP). Similar 60-year cycles exist in early instrumental European records of air temperature (1761–1980) and longer paleo proxies from different locations around the world [Shabalova and Weber, 1998, 1999], suggesting a global pattern of 60-year variability.”
You can read my last article on Climate Change mechanisms here. It is described and referenced there.
So it’s a religious oscillation.
Thankyou, Javier, for being the only person here to put units on the acceleration term. The terms rate and acceleration are used carelessly and the inclusion of units helps.
“The long term acceleration in SLR is hard to set because it is very small, constrained by most authors to a value ~ 0.01 mm/yr², requiring records of a century or longer.”
With the ground based temperature series, the argument is made that it’s better than the satellites. It might be. Using a many samples argument, I think it’s likely there are enough samples, be it 800 stations or 1500 or 400.
With tide gauges, the problem seems more tractable and more understandable, and yes the available sample size is large enough.
With tide gauges it takes some money to make a good one, and a GPS. And tide gauge are used to verify the satellites. A tangible link to a bunch of math equations for a deal orbiting the Earth which be its nature has a limited life and whose replacement may not get funded.
When we get into the satellite adjustments, the climate scientists can convince each other that this means something, but they might as well be speaking in a language most people can’t understand.
The message is 3 cm/decade. Who cares? It might get worse but who knows? And if this is their bread and butter message, I don’t live near the coast. If I did, I’d expect there to be costs of doing so.
Democrats don’t like rich people and guess who lives on the coasts? Rich people. So they had to find some poor people living on the coasts so they have non-rich people that needed saving too.
And all the people living on coasts need wind turbines in Iowa to save them, so the pain can be spread around some. So Iowa’s message can be, hang on, we’re putting up more windmills, but we are not sending aid money to Florida. We did our part. We are going Green, and if that doesn’t keep you from being under water, perhaps you ought to go to plan B.
The satirical appears to be the rational response to any of this. The moral is that the more earnest the tone the less their credibility. If Trump were talking sea level – he would be the wisest man alive. On economics the ongoing debt spree might be a worry. You might have to hock the silverware.
As a sometime engineer in charge of beaches – I knew enough to build above the level of any halfway decent tsunami. I am in 2 minds on sea level rise. On the one hand I look forward to the plebs on the mangrove fringe being washed away and me ending up with ocean frontage. On the other – this might involve opening my house to refugees.
Judith,
Have you examined the effects of natural groundwater discharge on the steady, linear increase in 20th century sea level that Munk suggested was tooo linear?
Groundwater stored during the last Ice Age has yet to reach equilibrium with our current climate state. The total freshwater volume of stored groundwater, if discharged to the ocean could raise sea level by ~203 feet, yet most studies seem to ignore natural groundwater discharge in their sea level rise budgets.
An accurate accounting of natural groundwater discharge could readily account for the “unaccounted” contributions reported in earlier IPCC studies that amount to about 25% of estimated sea level rise. An accurate accounting would also constrain the wide ranging contributions from meltwater and thermal expansion.
Jim, I did some research into this and concluded the groundwater contribution to SLR is likely deminimus. Three separate classes of observations. 1. Most places, groundwater is seasonally or multiannually replenished, proven by well water levels over time. 2.The places that are depleting provable by well levels—in the US, the largest is the Ogallala aquifer storing paleowater from the Holocene melt. About 24 cubic km per year. Essentially nothing compared to the oceans. Second largest depletion is in north central India, but in an area smaller than the Ogallala. 3. Groundwater storage/recharge was used in two papers to explain the possible slowdown in SLR ~2007-2012 supposedly detected by Jason 2. I dissected both papers (laughably bad) in essay PseudoPrecision (which is about SLR). Their groundwater storage claims (interior of Australia, Amazon, Congo river basins) are provably bogus. The SLR ‘slowdown’ was likely just Jason 2 instrument drift. Hence the essay title.
Steric sea level rise shows the inexorable increase in ocean heat content.
https://watertechbyrie.files.wordpress.com/2018/02/steric-sea-level.jpg
https://sealevel.nasa.gov/understanding-sea-level/key-indicators/steric-height
Frankly I am expecting the natural climate state to revert to a cooler mean this century. Emissions of greenhouse gases and aerosols are almost entirely under human control. I expect sea level rise to be a non-problem within decades. Oh wait – it already is a non-problem.
Gosh, the cool thing is that we actual have the raw data for
1. Tide gauges
2. Satellite altrimetry
3. SST
4. SAT
And we can all see the raw and see the adjusted. we can look for ourselves at all the adjustments.
There is one record for which we have no access to the raw:
we only get to see the adjusted.
Its filled with uncertainties as great if not greater than the SLR record.
Guess what record this is?
Its the record skeptics put their most faith in
If sea level is rising, why isn’t the level of the sea getting any higher?
I assume that is a rhetorical question, but if SLR doesn’t fit the models it doesn’t necessarily mean there is no more Warming, or that the volume of water isn’t greater, or the ice sheets are not contributing to SLR. It could be the ocean basins are increasing and there is growing deformation of the sea floor. The capacity of the ocean basins may simply be getting larger. Who knows?
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Since the media will create headlines and taglines to summarize this complex report, I would like to read the author’s and others propose accurate headlines and short short summaries. This may sound preposterous but better to state our own than be coopted by ideology and foolishness.
A quick summary of a previous guest post on seal level rise, acceleration, and closure. In PSMSL there are about 70 tide gauges with sufficiently proximate diff GPS to correct for vertical land motion and sufficiently long 60 year+ records to establish a trend. These show about 2.2mm/year and no acceleration. The 2.2 may be globally biased because the sample is heavily northern hemisphere and then Atlantic basin biased. But it does close with two estimates of ice sheet mass loss plus steric rise: Cazenove 2014 (2.2mm/yr), and the one derived in the post from various sources (2.3mm/y).
All of this says the satellite altimetry is just way off, making Nerem’s Topex correction to create acceleration even less credible than the post points out.
A big correction factor perhaps insufficiently emphasized is sea state. Crests and troughs of waves reflect differently, and the corrections assume 2 meter waves. I have lived directly on the Atlantic Ocean for 17 years with a great balcony view of the beach, the surf, and waves flowing over or breaking on the reef system off Fort Lauderdale. Seldom is the sea state 2 meters. Right now it is under a meter, and for three days last week it was about 3 meters.
Nice write up. (Not that I would be an adequate judge).
“VLM adjustments” doesn’t seem to have been explained (if I didn’t miss something obvious).
Oops, discussed in part III VLM=Vertical Land Movement
Dear Dr. Curry, I have been following the climate since I retired as a chemical engineer in 1992 and really enjoy your very precise coverage and method of operation. On sea level change I find very little mention of the Influence of wind velocity change over time as covered by Dr. Joseph O. Fletcher in his 2000 lecture at CSUMB. He was 80 years old at the time and seven years after retirement from 30 years directing climate studies at NOAA relating to wind changes and world climate. At the very end he makes some statements about sea level with the most profound being the winds circling Antarctica being of such force that the sea level is over four feet lower than if no wind. The amount of water in the Southern Hemisphere is very significant thus wind velocity changes over time can have a significant influence since he demonstrated velocity change of over 25% on cycles of 170 years. Shorter cycles but of lower ranges of velocities. His hope was that the satellite level measurements over time would fill in the gap of level data sorely missing in the Southern Hemisphere. If you know of any studies covering wind changes could you please enlighten me. Larry Wilhelmsen, Longview WA.
Sent from my iPad
>
Larry
This might be what you are after. Several citations in Section 2.3.
https://link.springer.com/article/10.1007/s10712-016-9386-y
McVicar, T. R., & Roderick, M. L. (2010). Atmospheric science: winds of change. Nature Geoscience, 3(11), 747.
Vautard, R., Cattiaux, J., Yiou, P., Thépaut, J. N., & Ciais, P. (2010). Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nature Geoscience, 3(11), 756.
Watson, S. J., Kritharas, P., & Hodgson, G. J. (2015). Wind speed variability across the UK between 1957 and 2011. Wind Energy, 18(1), 21-42.
Azorin-Molina, C., Vicente-Serrano, S. M., McVicar, T. R., Jerez, S., Sanchez-Lorenzo, A., López-Moreno, J. I., … & Espírito-Santo, F. (2014). Homogenization and assessment of observed near-surface wind speed trends over Spain and Portugal, 1961–2011. Journal of Climate, 27(10), 3692-3712.
Minola, L., Azorin-Molina, C., & Chen, D. (2016). Homogenization and assessment of observed near-surface wind speed trends across Sweden, 1956–2013. Journal of Climate, 29(20), 7397-7415.
I’m not a scientist so perhaps someone here can put me right:
It seems from what I have read here and elsewhere that measuring the height of active bodies of water is difficult from a distance and changes in height even more so.
Why don’t we use satellite altimetry to measure the land and use more physically proximate means to measure what’s happening to the water nearby? We can account for subsidence and tectonic changes from a distance and use tidal gauges for the water?
Thomas
Both are done. If you were an agency tasked with building a physical sea wall or other defence on or next to the beach you would generally use a tide gauge as that shows what is actually happening on site and normally over a long time scale. Your ‘average’ annual change might be wildly different to the global average.
Any calculation locally needs to take into account the expected sea level rise. With Kyoto, those signing up to it had to add 30CM to any estimated height necessary to last the life of the structure. I guess Paris has the same criteria neither of Which the States signed up to, so you would have your own criteria, which might vary from state to state.
Mind you in the States and Canada there are some very high levels of sea level change (up and down) due to movements of land and those would also need to be taken into account.
For every foot of sea wall in height, different load factors have to be taken into account, which raises its costs considerably, so generally you don’t want to build a wall 6 foot higher than necessary ‘just in case.’
tonyb
SLR is a local affair.
Ideally you’ve give the locals two estimates.
1. A purely statistical extrapolation from historical data
2. A physics informed estimate.
Next stop subizing the insurance rates of those who do not take account
of the worse of those two estimates. FEMA can step in for events that occur outside the range of what the best science tells us is the worst case.
acts of god– basically the tail
wanna live at the beach? fine. pay an unsubsidized rate.
Seems like a reasonable approach. Of course the devil is in the details – “a physics informed estimate”. North Carolina’s decision was to plan on 6-8 inches of slr by 2045, with updates for 20 year intervals after that. They backed off an earlier estimate of about 3 feet by 2100.
“Seems like a reasonable approach. Of course the devil is in the details – “a physics informed estimate”
for Physics informed estimate use the IPCC.
if north carolina is on notice that a statistical approach is 6-8 inches
and a physics informed estimate is 2 feet, FEMA does not own
the risk between 8 inches and 2 feet. the locals own that risk.
Re Nerem et al 2017: I think that the application of a quadratic fit is not justified at all. I digitized the Fig.1 of this paper http://www.pnas.org/content/pnas/early/2018/02/06/1717312115.full.pdf for the years after 2000 to avoid the TOPEX and/or the Pinatubo issues. Thereafter I calculated the linerar Trends 2000…2016 ( for Nerem et al) and 2000…2017 for the “Colorado” data. The residuals in annual resolution:
https://i.imgur.com/X6HGci6.jpg
The “ENSO removal” didn’t work. IMO they didn’t remove the ENSO index but reduced the impacts by about a half. See 2011 and 2016. In the raw data the ENSO blop is reduced in 2017 but not in the paper whrere the data end in the end of 2016. The relation stands and in the end they have a ENSO-blop which influences a trend very much. Together with the data before 2000 this gives only a plea to estimate a quadratic trend. This could have been seen also in their Figure 2:
https://i.imgur.com/fGHsFUz.jpg
The monthly datapoints inscribe much noise but the not succesful removal of the 2015/16 ENSO-impacts are clearly visible and also the suspicious behaviour in the late 90s. As a reviewer I would have asked for an annual resolved record and would have pointed to the ElNino in the end of the record. It’s always the same: take care!
very helpful thx. I’ve added this to the main post
And see the “ENSO correction” of the 1997/98 ElNino! This paper was reviewed by some blind guys I’m afraid.
Judith: I’m not franktoo but this is not a problem for me :-)
sorry i fixed that!
Frankclimate, my complements. A clear and simple way to show Nerem did not do what he claimed to have done, so his result is bogus.
yes, the results are very questionable indeed. What makes me sad is that the paper was published despite a “review”. What have done the peers? It took me about one hour to show the bogus “ENSO adjustment”. In the end there is one ElNino in the beginning and one in the end of the record, in between a strong LaNina. This must give a quadratic trend in every case. Not due to CAGW but due to internal variability.
Could you explain what you mean by “digitize”? It reads like your results are based on a scan of the figure? Did you not have access to the original data? I thought most data these days should be posted as “supplementary”.
No data posted in the supps or I wansn’t able to find them. Anyway: Don’t worry, the digitizing is very sophisticated and the uncertainty is very small, see https://automeris.io/WebPlotDigitizer/.
Thanks. I was reminded of a huge table with measurements I had made and someone tried to scan it and decipher it. She could have just asked me for the table. I have respect for scientists who publish their data and code. No one is perfect. Errors can be acknowledged and fixed. I still have doubts about the Digitizer but perhaps you are right. I just wish it was not necessary.
I want to add a more constructive comment. In Nerem et.al they do not describe in detail how they made the ENSO remove. I suggest the following procedure: Following this paper http://onlinelibrary.wiley.com/doi/10.1002/2017GL072908/abstract I used the SST 5N-5S; 160E-90W ( record: NCEP OI v2 SST). This suggested monthly record describes, following Hu et.al, the impact of the released heat better than other indexes , i.e. Nino3,4 or MEI ( which should be not the best choice ,in this case, it’s a mixed index and the most important influence of SSH comes from pure ocean indexes). I optimised the relation between the trend residuals of SSH and SST including a time delay of 3 month of the SSH. After reclaculating annual averages this gives this picture:
https://i.imgur.com/Qf8ezDC.jpg
It’s clearly visible that the ENSO removal of the black line ( my proposal to Nerem et.al for this operation) works much better to remove the ElNino blobs and LaNina dips. With the monthly data and recalculating the Figure 1 of Nerem et al. there is no difference between the linear trend and the quadratic. I’m not sure if my proposal is welcome…
Perhaps someone can help me with something. In Ragnaar’s world of flowcharts and cartoons, sufficient El Nino conditions transfer more joules from the Pacific into the atmosphere cooling the Pacific more than before. The Pacific now being a bit cooler contracts and SLR slows. Sufficient La Nina conditions soak up joules as the cooler water evaporates less and being cooler, steals atmospheric joules more than before. With more joules, the Pacific expands and SLR is faster.
Figure 1. in the article:
“The large trend between 2011 and 2016 is associated with a very strong LaNina (2011) and a very strong El Nino (2016).”
Then we have this:
“The key to these sea level effects is water storage on land. The warmer phase, El Niño, can raise sea level because of increased rainfall over the oceans; the cooler phase, La Niña, can lower sea level because of increased rainfall over land, where the water is temporarily stored before draining back into the sea. These effects are magnified in the tropics [Llovel et al., 2011].”
https://sealevel.nasa.gov/understanding-sea-level/causes/regional-sea-level-change
The second explanation makes some sense. The IPWP is near land that can be rained on. An El Nino moves this to the middle of the Pacific which is just ocean.
So, which explanation is correct? Argue that the 21st century shows acceleration. That 90% of the joule gain is in the oceans until their vengeful return. Argue that there was no pause. A SLR acceleration for the 21st century questions Karl. Yes CO2 can accelerate SLR by putting joules not in the atmosphere. So to argue for SLR acceleration is to argue for the pause. To say the pause was a mind trick is to argue SLR did not accelerate.
I prefer the first explanation above. Rain will flow to the sea and evaporated, if it came from the Pacific, there’s a chance it will return to the Pacific in the short term.
Because CO2 traps heat, we will get worrisome SLR or GMST rise. To the extent we get one, we will get less of the other. Should the books balance? Do they have to?
To tell a story, what shall we do? If GMST rise is not worrisome what shall we do? Say SLR is the problem.
As I posted earlier, a key is that since the 1990’s the Greenland and Antarctic net mass loss rates have grown to where they significantly contribute to sea-level rise. Now they are contributing ~1 mm/yr (70% from Greenland) which is about the size of the acceleration since the 1990’s, and this factor is growing faster than the warming effect. In another decade it could contribute to half the rise rate.
Oceans and atmosphere reach equilibrium much quicker than ice on Greenland and Antarctica. With both huge piles of ice, there will be collapses, large and small on all time scales. Water and air is some high school lab experiment compared to figuring out that ice.
Past climates did not have a Greenland glacier at above 400 ppm, so it is on borrowed time as long as we keep it that way. It’s no coincidence that it only started contributing to sea-level rise as we approached 400 ppm. These things are connected rather directly via the Arctic temperatures that are changing faster than anywhere.
Citation?
One example is here.
https://globalcryospherewatch.org/assessments/icesheets/
400 Gt/yr would be ~1 mm/yr added sea level.
bernie, or if referring to 400 ppm, this s one reference, but there are many CO2 paleo reconstructions which you can compare with the formation time of Greenland’s glacier 5 million years ago.
https://robertscribbler.com/tag/climate-thresholds/
Jim D, there are two factual responses to your evident concern.
First, your own ice mass losses plus the Argo estimated thermosteric rise yields about 2.0-2.1 mm/yr, with significant uncertainties. Nothing to be alarmed about. Warmunist alarm comes from acceleration of that rate, for which there is no meaningful observational evidence, only easily falsified model projections.
Second, per a long ago previous guest post here on Tipping Points, the previous Eemian highstand did indeed reach about 6.5 meters above present MSL, and at a temperature estimated from proxies to be 1-2C higher generally, and up to 6-8C higher in Greenland based on the Neem ice core. Now, this highstand took roughly three millennia to reach, which translates to about 2.1-2.2mm/yr of SLR and no acceleration. No cause for CAGW alarm—Earth has been there and done that before.
All the warmunist alarm comes either from thermodynamically impossible ice sheet melting rates, or geologically impossible ice sheet ‘slide off’ tipping points. With respect to both, you might find essay Tipping Points in ebook Blowing Smoke, or my previous guest post here of same name from which it derived, edifying.
Sure Greenland with 2.85 million cubic kilometers of ice. Antarctica has 30 million. We’d really be in trouble if since it has 10 times the mass, it reacted to CO2 as Greenland does. But the Southern Hemisphere didn’t get the memo. Yes, like the Wicked Witch, it’s melting. But how good is your steric information? We’ve nailed down sea level? Good, we can balance the books now.
ristvan, if you are looking for examples in paleoclimate you need look no further back than what is now known as meltwater pulse 1A that had sea-level rises of several meters per century as a former large glacier, thought to be in eastern Canada, collapsed after the last Ice Age. Parts of Greenland and parts of Antarctica are at risk of doing likewise.
There are huge variations in Greenland melting. The greatest melting period was in the first half of the 20th century. (natural variation) The inland ice is growing, as it is in Antarctica too. Over these high landscapes the greenhouse effect is reversed, according to theory.
Greenland has been melting more hugely more lately. Prior to 2000, not that much, after 2010, some really large amounts. There was a major melt episode that compounded the melting in 2012. These may occur more often in the future.
A SLR acceleration for the 21st century questions Karl.
No.
I am suggesting one can’t have it both ways. More of one is less of the other. Record apocalyptic temperatures and a crack fueled PDO mean less SLR, full stop.
SLR is caused by thermal expansion due to a net accumulation of energy in the oceans and a net transfer of water/ice from land to oceans.
Jch
How are the ocean temperatures doing?
Tonyb
Net transfer of water/ice from land is drumroll please……..
Let’s ask Zwally. Let’s mix it with steric SLR and say, it’s some of both. Here’s the cool accounting thing with a big pile of stuff far away. If you can’t find something, say it’s there. No one wants to go to Antarctica to verify it and to attempt it, costs millions of dollars. Hide it in the most difficult thing to audit. I am not saying anyone did anything. Some things are kind of universal though. Why do we even need auditors?
But Zwally!
Try this:
Ask Zwally if he thinks his result calls into question in anyway at all the accuracy of satellite-era sea data. His result turn Antarctica from a source of sea level rise to an offset of sea level rise. My bet, he says absolutely not.
…may be revised as addition errors are uncovered.
The key point is careful thought and analysis – what is the uncertainty in a given approach, what can we do about it, what is the overall weight of evidence, does one part of the evidence constrain another?
Yes, sea levels are rising and the evidence is accumulating that there is an acceleration – glacial and ice cap loss and thermal expansion are basically consistent with the sea level rise – and all are consistent with AGW.
We know the process is slow – but reasonable parties know that the process cannot be “stopped on a dime” it has inertia. So a time frame going to a couple of centuries – shows a pretty high risk for coastal cities and agriculture. Given those risks, analyzing “it” to death and as a result hesitating – doesn’t seem altogether wise. And the evidence continues to gather weight and strength – the basic direction in the overall science is the risk is indeed there and not diminishing.
No doubt sea levels have been rising since end of LIA. Substantial doubt as to whether there has been any acceleration. Great doubt about whether any acceleration would ever become significant enough to warrant mitigation. Alarmists Hansen and Rahmstorf think yes, but their observational evidence is zero and their models provably wrong. Worrisome SLR acceleration is another warmunist unsubstantiated belief.
And then one must also be regionally specific. Bangkok has a huge present problem because the river delta it is built on is subsiding. Itnwill need dykes by 2030. New York, nothing if they would just build for the inevitable occasional storm surge. LA and Tokyo have earthquake issues, not SLR issues. Miami South Beach was built improperly low in the 1920s and is also subsiding. Answer is storm drain check valves like were installed on also improperly built Las Olas Isles in Fort Lauderdale. (Dredged spoil from converting mangrove swamp to waterfront housing on the Fort Lauderdale harbor waterway in the 1950s). Miami has been too cheap to install them, so portions of Miami Beach get light flooding on king tides while the Las Olas Isles don’t.
Stick with the data, not generalized beliefs.
I’d suggest Kemp et al Climate related sea-level variations over the last two millennia PNAS 108:11017-11022 2011 Their Figure 3 is a bit of a mini-review of other studies. A search of who has cited this would probably yield more recent paleoclimate work on sea level rise.
For recent times, including very recent – there’s a host of papers. A short list of examples, emphasis on more recent where again, the use of their citations may be helpful:
Ablain et al Satellite Altimetry-Based Sea Level at Global and Regional Scales Surv Geophys 38:7-31 2017
Church & White Sea-Level Rise from the Late 19th to the Early 21st Century Surv Geophys 32:585–602 2011
Dangendorf et al Reassessment of 20th century global mean sea level rise PNAS 114:5946-5951 2017
Gehrels et al Onset of recent rapid sea-level rise in the western Atlantic Ocean Quat Sci Rev 24:2083–2100 2005
Hay et al Probabilistic reanalysis of twentieth-century sea-level rise Nature 517:481-484 2015
Jevrejeva et al Recent global sea level acceleration started over 200 years ago Geophys Res Lett vol35 L08715 2008
Jevrejeva et al Trends and acceleration in global and regional sea levels since 1807 Global Plant Change 113:11–22 2014
Kopp et al Temperature-driven global sea-level variability in the Common Era PNAS 113:E1434-E1441 2016
Meyssignac & Cazenave Sea level: a review of present-day and recent-past changes and variability J Geodynamics 58:96-109 2012
I don’t buy Hansen’s models, but that doesn’t disprove the other, physical models that predict increased sea level rise.
The IPCC admitted problems with the ice sheet models we had in the ’00s. They didn’t account for a lot of things — bedrock lubrication, downward-sloping seabeds, ice cliff instability. So the IPCC reported predictions of 1-3 feet of SLR by the end of the century, but with a lot of caveats about unaddressed uncertainties, almost all of which would increase the rate.
And what’s more, since then, the paleo data we find keeps suggesting that SLR can accelerate quite substantially. Study after study shows that a small bit of warming causes large increases in sea level. And now we have the physics that explains why; those previously-unaccounted for factors. Ice sheets are relatively unstable to temperature perturbations.
The timescale is still unclear — is it decades, or centuries? But at this point, you have to blow off a helluva lot of scientific evidence to blow off the possibility of SLR acceleration. The data says it’s more and more likely.
Should we also come up with additional parameters to make a statistical adjustments for Eyjafjallajökull and other volcanic activity taking place beneath the surface of the ocean?
Only if you can measure it, I’d think.
An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative
https://i.imgur.com/3Y6qwSj.png
thx, i can use this in Part V
Then compare it to the tide guages to see if it’s actually happening.
If you want to know.
As the Mean Sea Level (neither calculated from satellite data nor from tide gauges) is not (and is not trying to be) a measure of the physical sea level, where are the studies using SSH (Sea Surface Height) or RSL (Relative Sae Level)? What’s the idea trying to figure out if some beach will be underground using a measure which isn’t ment to measure that?
Tuvalu main island, as an example, has grown 3,6ha while the unreal MSL number rose by 3.6mm/y. Of all the Tuvalu Islands, 76% gained in size. Nature published a study on this about a week ago. Relative Sea Level growth must have been negative there, but where’s the data? (e.g. PNMSL is just another MSL number.)
One thing that no one seems to have done is take a small segment of an ocean, like around one of the Pacific islands, and compared the satellite data to the island’s tide gauge. Doing it visually indicates there large differences. To take an example, The Area east of PNG from AVISO is shown as about 7mm/yr
https://www.aviso.altimetry.fr/fileadmin/images/data/Products/indic/msl/MSL_Map_MERGED_Global_AVISO_NoGIA_Adjust.png
but the tide gauge for Honiara in the centre of the red shows little change
http://www.psmsl.org/data/obtaining/rlr.monthly.data/1861.rlrdata
One can do the same for other places and show it isn’t just the Solomons are being uplifted. Look at the red spot off the coast of NSW that isn’t affecting Sydney or Chatham Island east of New Zealand
The believers have talked about averaging, or do an appeal to authority, but if the detail isn’t right, then how can one have any faith in derivatives?
Mathematically, the error bars in the derivatives follow pretty straightforwardly from errors in the base series.
So, properly calculated, the derivatives tell you how much you should trust them.
I think you are going to sea a pronounced ebb and flow in the Solomons due to ENSO. With La Niña and negative PDO dominating much of the satellite era, that area sees ocean mounding.
The bow, 137′ of boat, was blown off my father’s heavy cruiser just off the area where that tide gauge is located.
There are two problems with your reasoning JCH. The first is that the sea level trends show a high rate of change across the Solomon Sea, which is surounded by islands. The second is that Honiara faces into Iron Bottom Sound which is a relatively narrow passage of water. Both of those mean it is not credible that mounding would affect the ocean and not the tide gauges. The maps don’t show a yellow ring around any of the islands indicating areas of low sea level rise. Thirdly, if the sea level changes are domination by ENSO, PDO and La Nina; none of those have anything to do with oceans getting warmer from climate change.
Sounds like you’re asking a computer graphic to do the impossible.
The resolution on the computer graphic appears to have pixels less than about 30-40km at the equator JCH so if big sea level rises are only in deeper ocean away from land masses, then it shouldn’t show them in archipelagos, which it does. Your guess also means they can’t be correlating the satellite with tide gauges, which was my original point.
And I note you haven’t commented about the non-climate change effects being the cause, so we can take your agreement from the silence.
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The stated accuracy of the satellite altimeters is 34 mm, and they hope to get down to 24 mm.
https://sealevel.jpl.nasa.gov/technology/
The Science behind this limitation is that a single receiver
dish cannot resolve below one wavelength of the frequency used.
The highest frequency used is 13.6 Ghz, or 3^8/13.6^9= .022 meters,
or 22 mm. Discussions of what the actual measurement is smaller
than one wavelength is very subjective.
Another large area of error is tides, they state that the sea level is corrected
for tides, but the tide predictions for any given location can be off by
100 mm or more. Sea state, fetch, storms, ect, all can radically affect,
the predicted tide.
We have a few, century plus tide gauges, that show us the sea level
is indeed increasing, but the data is noisy, and finding and acceleration
within such noise to any certainty would be difficult to prove.
Sometimes it’s a good idea to pull back from a detailed study of the trees to concentrate on the forest as a whole. When we consider the big picture we do in fact see what looks like a very strong correlation between sea level rise and CO2 concentrations over the last 120 years or more. Regardless of the many details and all the many ways of interpreting them, we see a steady rise in sea level accompanied by a steady rise in atmospheric CO2, strongly suggesting a cause-effect relation.
However, as is well known, correlation cannot always be interpreted as causation. Looking more closely at the long range statistics we do NOT in fact see a correlation between global temperatures and either CO2 or sea level. From ca. 1940 to ca, 1979, a period of roughly 40 years, temperatures either declined or remained more or less steady, while both CO2 and sea levels continued to rise. The lack of correlation between temperatures and CO2 has created problems for supporters of the “climate change” meme, many of whom have attempted to explain it away by invoking the cooling effects of aerosols produced by industrial pollution.
Be that as it may, such an explanation can have no bearing on the lack of correlation between global temperatures and sea level rise during this period. And since one would expect sea level rise to be caused largely by ocean heating, one is forced to wonder about the accuracy of the various methods used to measure either temperature or sea level, or both, on a global scale. I’m wondering what you make of this apparent contradiction.
thx, this very well states something I am working on for part V, stay tuned
just curious.. are there no graphs available that combine atmospheric CO2 levels with global temperatures and GSLR ?
The pause fooled a lot of really smart people. Maybe all pauses do that.
Bingo!!
There is no contradiction – global temperature and sea level rise rate do correlate.
http://www.realclimate.org/images//sea_level_rise_vs_temperature.png
Sea level rise is caused largely by melting of land ice (consensus is roughly 2/3) and not by ocean heating.
I agree about the accuracy.
What you have there is the PDO. Mid-century atmospheric CO2 levels were fairly low, so the negative phase off the PDO clobbered the rate of SLR and surface warming. The PDO went negative again in the first decades of the 21st century. Atmospheric CO2 levels were much higher, and there was both an insignificant slowdown of the GMST and the rate of SLR. The PDO went positive in 2015, and there has been a pronounced increase in the GMST and the rate of SLR.
And strongly disagree about CO2. We measure atmospheric CO2 only since ~1960.
Sorry, edimbukvarevic, but the graph you’ve presented is very different from other graphs I’ve seen representing global sea level. One example can be found here:
https://i1.wp.com/climateadaptation.hawaii.gov/wp-content/uploads/2015/11/Brief-1-Figure-4.png
Note the steady rise, with no inflection from 1940-1979.
Dr. Curry has identified your graph as a representation of PDO (Pacific Decadal Oscillation), a very different matter.
JCH, PDO? Becoming skeptical of the consensus AGW? There is no PDO in the official forcing list.
http://ipcc.ch/report/graphics/images/Assessment%20Reports/AR5%20-%20WG1/Chapter%2008/Fig8-18.jpg
Victor, the rate, not the level itself, correlates with temperatures. As it should – higher temperatures mean more land ice melting and more slr rate.
http://www.realclimate.org/images//IPCC_AR5_13.7ab.png
JCH is not dr. Curry.
Of course the PDO is there: it adds up to around zero.
Victor, I think one graph is the rate of SLR in mm per year, which remains almost entirely positive, and the other is the accumulated mm.
I do suspect that almost nobody here realizes that i have wide differences with some of the consensus. I think that is because this blog is almost entirely political.
JCH, ok then. Good to know that you have wide differences with some of the consensus. My presumption was not political.
I’m not sure what your point is, edimbukvarevic. It seems clear that there was no correlation between global warming and sea level rise over a period of 40 years. As it seems to me, you have cast around for something you can find that appears to contradict such a conclusion. This is a tactic I see all too often in the “climate change” literature. When the raw data doesn’t fit one’s preferred conclusion one manages to come up with some other bit of data that does — or at least looks that way. As I see it, either the long term trend of global warming is correlated with sea level rise or not. Shifting our attention to a graph depicting rate of change strikes me as, well, rather “shifty,” iykwim.
And of course glacial melt doesn’t change anything since that too is supposedly affected by atmospheric warming. Sorry about misidentifying you, JCH. The JC got me confused.
Victor,
My point is that sea level rise (slr) is caused largely by land ice melting (2/3), therefore temperatures should correlate better with slr rate (mm/year) than with slr (mm). That is observed too.
CO2 imo is irrelevant, except its rate of change correlates with temperatures too.
A suggestion, meant to be helpful, for the next essay in this series. Others have observed the absence of a “raw” data set, saying all the sets are adjusted. If one is to contribute to clarification, there has to be a common starting point where some of the earliest (as in least adjusted) sets, the closest ones to raw, are ranked; then the most plausible taken up for further study.
The further study involves the adjustments. There has to be a rationale for each adjustment. In the long run, a paper passes or fails on the justification for its adjustments.
Would there be value in taking a nominated set of the best near raw data, then having a round table blog where the credibility of each past proposed adjustment is evaluated?
There needs to be a way to narrow down the candidates that make claims to acceleration. There are too many right now, thus far too many adjustments to place into context for evaluation. Some must be capable of failure and rejection at this point. Of course, those working full time on sea level rise should have such matters in their memories as tools of trade, but it is hard for a visitor to drop in and contribute because of the current mix of conflicting confusion. Geoff
It seems that the big issue may be not whether the adjustments made are valid but whether only adjustments that create a greater apparent acceleration are developed/reported. So looking for valid adjustments that cut the other way but have not been reported might be productive.
IMO, the biggest problem with satellite altimetry measurement has been systematic error. (The large number of measurements made reduces uncertainty due to noise and natural variability.) Processing of altimetry data seems to have gone through a number of phases when systematic errors (greater than confidence intervals) were fixed.
Some discussion of the size of the corrections made when processing satellite altimetry data seems appropriate. Info copied from: http://www.altimetry.info
Propagation corrections
http://www.altimetry.info/radar-altimetry-tutorial/data-flow/data-processing/geophysical-corrections/
Ionosphere
Correction for the path delay in the radar return signal due to the atmosphere’s electron content. Calculated by combining radar altimeter measurements acquired at two separate frequencies (C-band and Ku-band for Topex and Jason-1, Ku-band and S-band for Envisat).
Order of magnitude: 0 to 50 cm
Wet troposphere
Correction for the path delay in the radar return signal due to liquid water in the atmosphere. Calculated from radiometer measurements and/or meteorological models.
Order of magnitude: 0 to 50 cm
Dry troposphere
Correction for the path delay in the radar return signal due to the atmosphere. Calculated from meteorological models.
Order of magnitude: 2.3 m
Surface corrections
Inverse barometer
Correction for variations in sea surface height due to atmospheric pressure variations (atmospheric loading). Calculated from meteorological models.
Order of magnitude: about 15 cm, depending on atmospheric pressure
Electromagnetic bias
Correction for bias in measurements introduced by varying reflectivity of wave crests and troughs. Correction calculated from models. Bias uncertainty is currently the biggest factor in altimeter error budgets.
Order of magnitude: from 0 to 50 cm, depending on wave heights
Geophysical corrections
Ocean tides
Corrections for solid earth and sea surface height variations due to the attraction of the Sun and Moon. Calculated by models.
Order of magnitude: 1 m in mid-ocean, up to 15-20 m near some shorelines.
Solid earth tides
Corrections for solid earth variations due to the attraction of the Sun and Moon. Calculated by models.
Order of magnitude: 50 cm.
Pole tides
Corrections for variations due to the attraction of the Sun and Moon. Calculated by models.
Order of magnitude: 2 cm.
Tidal loading
Corrections for height variations due to changes in tide-induced forces acting on the Earth’s surface. Calculated by models.
Order of magnitude: 30 cm
http://www.altimetry.info/thematic-use-cases/examples-of-altimetry-data-use/mean-sea-level/
The mean sea level is dominated by several haromonics: :
– annual signal
– semi-annual signal
– 60 days signal.
Actually if we want to really focus on the sea level rise we have to filter out from these signals. Filtering these signals is a more complex procedure not implemented here, but the final result is already available in netCDF format on the AVISO web site (link). For example you can plot and superimpose the two curves to observe the differences between filtered and non filtered MSL estimations. The rate of the mean sea level rise as seen by satellite altimetry appears to be about 3 mm/year.
http://www.altimetry.info/radar-altimetry-tutorial/data-flow/data-processing/orbit-determination-2/
“The ability to precisely determine a satellite’s position on orbit is a key factor in the quality of altimetry data. Besides measurements acquired by the location systems onboard the satellites, which are cross-calibrated, we now rely on increasingly accurate orbit determination models.Different products require different levels of accuracy. Data generated within three hours are based on a preliminary orbit from the Diode onboard navigator (DORIS). On the other hand, data generated 30 days post acquisition require the most accurate orbit possible and therefore demand more orbit data and more time for calculations. Expected accuracy on the radial orbit component is 20 cm rms for three-hour data, 2.5 cm rms for three-day data, and 1.5 cm for 30-day data. The ultimate aim is to achieve centimetre accuracy.”
Note: 1 cm rms error in satellite orbit when measuring SLR of 3 mm/yr isn’t good enough. I presume data must be calibrated against places where current sea level is known (ie against a local tide gauge). I’ve seen discussions on the use of calibration, but no explanation for how it is used in practice, if at all.
IIRC a GIA model is used in correcting satellite data (though I think the latest corrections offered GPS and GIA model corrections)
Regional biases in absolute sea-level estimates from tide gauge data due to residual unmodeled vertical land movement DOI: 10.1029/2012GL052348
[1] The only vertical land movement signal routinely corrected for when estimating absolute sea-level change from tide gauge data is that due to glacial isostatic adjustment (GIA). We compare modeled GIA uplift (ICE-5G + VM2) with vertical land movement at ∼300 GPS stations located near to a global set of tide gauges, and find regionally coherent differences of commonly ±0.5–2 mm/yr. Reference frame differences and signal due to present-day mass trends cannot reconcile these differences. We examine sensitivity to the GIA Earth model by fitting to a subset of the GPS velocities and find substantial regional sensitivity, but no single Earth model is able to reduce the disagreement in all regions. We suggest errors in ice history and neglected lateral Earth structure dominate model-data differences, and urge caution in the use of modeled GIA uplift alone when interpreting regional- and global- scale absolute (geocentric) sea level from tide gauge data.
thx, v helpful
More on systematic errors in satellite altimetry. Due to the record of systematic errors, the 95% ci for SLR from satellite altimetry may be fairly meaningless. The next systematic correction could easily move outside the previous confidence interval. Any long-term gradual bias in the data used to correct altimetry data (humidity, for example) will bias SLR.
Advances in Space Research 51 (2013) 1284–1300
The challenges in long-term altimetry calibration for addressing the problem of global sea level change. Fu and Haines. (Non-climate scientists?) http://iranarticles.com/pdfessays/EarthandPlanetary/The%20challenges%20in%20long-term%20altimetry%20calibration.pdf
Long-term change of the global sea level resulting from climate change has become an issue of great societal interest. The advent of the technology of satellite altimetry has modernized the study of sea level on both global and regional scales. In combination with in situ observations of the ocean density and space observations of Earth’s gravity variations, satellite altimetry has become an essential component of a global observing system for monitoring and understanding sea level change. The challenge of making sea level measurements with sufficient accuracy to discern long-term trends and allow the patterns of natural variability to be distinguished from those linked to anthropogenic forcing rests largely on the long-term efforts of altimeter calibration and validation. The issues of long-term calibration for the various components of the altimeter measurement system are reviewed in the paper. The topics include radar altimetry, the effects of tropospheric water vapor, orbit determination, gravity field, tide gauges, and the terrestrial reference frame. The necessity for maintaining a complete calibration effort and the challenges of sustaining it into the future are discussed.
From one of the recent articles on the recent correction of 1993-2000 SLR Data not covered above: This is from the CU group – which hasn’t updated its reflect these recent corrections by any of the five groups.
On the ‘‘Cal-Mode’’ Correction to TOPEX Satellite Altimetry andIts Effect on the Global Mean Sea Level Time Series. B. D. Beckley et al http://onlinelibrary.wiley.com/wol1/doi/10.1002/2017JC013090/full
Abstract: Comparison of satellite altimetry against a high-quality network of tide gauges suggests that sea-surface heights from the TOPEX altimeter may be biased by 65 mm, in an approximate piecewise linear,or U-shaped, drift. This has been previously reported in at least two other studies. The bias is probably caused by use of an internal calibration-mode range correction, included in the TOPEX ‘‘net instrument’’ correction, which is suspect owing to changes in the altimeter’s point target response. Removal of thiscorrection appears to mitigate most of the drift problem. In addition, a new time series based on retrackingthe TOPEX waveforms, again without the calibration-mode correction, also reduces the drift aside for a clearproblem during the first 2 years. With revision, the TOPEX measurements, combined with successor Jason altimeter measurements, show global mean sea level rising fairly steadily throughout most of 24 year timeperiod, with rates around 3 mm/yr, although higher over the last few years.
Background: Many of the challenges that must be overcome are reviewed by Fu and Haines (2013) and Ablain et al. (2017 Paywall). As those authors emphasize, comparison of altimeter measurements against independent measurements of local sea level at tide gauges plays a critical role in establishing the validity of the altimetric time series. There are two main approaches to tide-gauge validation of satellite altimetry. In one, a small set of heavily instrumented stations are set up under the satellite flight path, and the altimeter and in situ sea level measurements, as well as other ancillary measurements (e.g., wet tropospheric path delay), are compared. Forthe T/P and Jason satellites, project teams from NASA and CNES (Bonnefond et al., 2010; Haines et al., 2010;Menard et al., 1994), as well as international collaborators (Mertikas et al., 2010; Watson et al., 2011) maintaina set of four such stations. In the second approach, many dozens of tide gauges from the global international network are employed (Mitchum, 1998). These stations of opportunity are less well instrumented and are usually not directly in the overflight path, but they are invaluable because of the statistical power of averaging over many independent measurements. In several cases, the tide-gauge validation systems now in place have indeed uncovered spurious drifts inthe altimeter measurements. In each case, the NASA and CNES project teams have been able to locate theunderlying reasons for the discrepancies and correct the problems. Several cases have involved drifts in the onboard water-vapor radiometers used to correct altimeter ranges for wet path delay, and these problems have been resolved by independent calibration of the radiometers (e.g., Brown et al., 2007; Ruf, 2002). A more unusual case occurred early in the T/P mission when a spurious drift was found to be due to an error in software used to correct altimeter ranges for oscillator drift (Nerem, 1997); see the discussion by Fu and Haines (2013).
Thx, v. helpful
Judith: I once tried a quadratic fit to the CU data (before the most recent correction to the data). The lag-1 correlation coefficient was extremely high and the autocorrelation correction left about 1 effective data point per year. A text search of Nerem’s PNAS paper uncovered no mention of autocorrelation. (My guess is that their confidence interval for acceleration has been corrected for autocorrelation.)
It is interesting to decompose projections of 21st century SLR into “linear” and “quadratic” components. 65 cm of SLR would be half due to acceleration and half due to linear. To reach 100 cm, one needs about 3-fold more acceleration. 1 inch/decade currently plus 1 inch/decade/decade gives roughly 1 m by the end of the century and is easy to remember and check.
“My guess is that their confidence interval for acceleration has been corrected for autocorrelation.”
Table 1 sees to suggest the errors reported are consequent upon the adjustment errors alone. In other words the residuals could have anything in them (which accords with observations by some here that they remain correlated with ENSO).
Why don’t they just show their workings?
HAS: After refining the early data, and correcting for Pinatubo and El Nino, Nerem obtained an acceleration of 0.084 ± 0.025 mm/yr2. With none of those corrections, I got an acceleration (end of 2016) of 0.028 ± 0.029 using autocorrelation. Lag-1 correlation was 0.96, resulting in a 7X increase in the confidence interval correcting for autocorrelation (and slightly less than one independent data point per year). Since we have similar confidence intervals, I suspect we both corrected for autocorrelation. (There is no guarantee I did this right, of course). My linear term was 3.27 ± 0.36 mm/yr, slightly higher than Nerem’s 3.0 ± 0.4 mm/yr, which makes since since the early SLR was reduced by correction after I obtained it.
I did a linear fit of t and t^2 to the raw data from NASA and the t^2 coefficient is 0.0465 +/- 0.0036 (s.e.). This roughly matches what Nerem report after adjustments (0.042 +/- 0.0125) although the error term is much smaller.
If I add a -1 lag term the t^2 coefficient drops to 0.0081 +/- 0.0021. Much less scary if still significant, but clearly Nerem didn’t fit this model.
As I said I don’t think they included any errors from fitting or explored the appropriate model to fit.
franktoo,
From simple, basic theory, it helps to separate precision from accuracy (systematic bias). Many of the calculations you listed are more about statistical precision. For accuracy studies, one needs either a watertight calculation procedure (like the one for pi to a million places) or a comparison with a different method whose accuracy is properly known (like attempts to compare satellite SLR with tide gauge SLR).
It is not evident to this reader that the claimed accuracy – it has to be better than eventually +/- 1 mm to be useful – is anywhere near satisfied. One must conclude that claimed performance is wishful thinking adjustment, unless the full accuracy calculations are clearly laid out.
Geoff.
Judith and Geoff: Statistical precision is derived from the scatter in the data about a linear or quadratic fit to the sea level data. See my data immediately above. That is due to natural variability in sea level or noise in the measurement.
Accuracy (systematic bias) can’t be assessed from the data itself. When one looks at the large corrections used for changes in the ionosphere and humidity in the troposphere (50 cm), it doesn’t take much of a growing bias in our observations of the the ionosphere and humidity (from re-analysis) to create a bias in SLR. A bias in the observations that produce either of these correction factors that produces a bias of 0.1% per year changes SLR by 0.5 mm/yr. That is larger than the statistical precision in the 25-year trend (± 0.4 mm/yr). Then we have the issue of error in orbit which has an as-yet-unachieved goal of 1 cm (which I suspect means a drift of 1 cm/yr).
The problem with satellite altimetry is its vulnerability to systematic error. Precision is awesome because continuous measurements are being made.
I think Morner doesn’t recognize that the large changes in SLR in the early years were due to correction of systematic errors.
What I can’t figure out is what part calibration and validation activities play in producing the final data products. Are all measurements calibrated vs a network of ground tide gauges (to eliminate the drift of 1+ cm/yr)? Or are the orbits recalculated when validation from the ground tide gauges shows a problem exists? Do each of the five groups independently calculate orbits? Do they correct orbits from a different set of tide gauges? Do they simply grid the data differently? Are they using the same systematic corrections (and making common mistakes) or actually independently doing all steps and producing independent products (like RSS and UAH)?
If you are going to have a large network of tide gauges with GPS to calibrate satellite altimetry, why not rely upon the tide gauges alone? Answer, satellites provide global data. Yes, but we only care about sea level rise at the coast.
helpful points, thx
Yes, but we only care about sea level rise at the coast.
How convenient, but sorry, but one has to care about the whole enchilada.
We want some simulations Jimbo – not just words.
My guess is that there is that there is a multi-decadally varying steric component to SLR and a nonlinear ice and rainfall component to ocean mass. Who am I to argue against nonlinearity in anything? What any of this is in dark ages data is anyone’s guess. Even in space age data – it doesn’t add up.
Total SLR by altimetry.
https://watertechbyrie.files.wordpress.com/2018/02/tital-slr-e1519165018217.jpg
Ocean mass by GRACE.
https://watertechbyrie.files.wordpress.com/2018/02/ocean-mass.jpg
Steric SLR by Argo.
https://watertechbyrie.files.wordpress.com/2018/02/steric-sea-level-e1519163249588.jpg.
I’d figure they should focus on closing the budget before arguing that it is getting much worse. The obvious problems are both the shortness of space age data – and the wonkiness of temperature, ice sheet and hydrology projections.
The NASA page layout is decidedly ordinary – as is my use of the snipping tool.
https://sealevel.nasa.gov/
The Australian today reports on a scientific paper seeking stronger anti-emissions policies now because sea level might be 70 – 120 cms higher in 2300. My response:
It’s a huge step to believe that minor changes in sea level can be accurately projected 280 years hence; but even if sea level does rise 70-120cms in that time, so what? (“’Act now’: Seas set to rise by 2330,” 21/2). That is 280 years – four lifetimes – to adapt to a rise which might be only the length of your leg. During the 20,000 years since the end of the last glaciation, sea level has risen about 120 metres at current shore lines, at times much more rapidly than in recent decades. While records are poor, sea level appears to have begun rising around the beginning of the 19th C, after several centuries associated with cooling and sea level decline. Recent analyses indicate significantly lower rises in the 20th C than cited by the IPCC.
Many countries, including Australia, have adopted very costly emissions reduction policies in case warming continues and is net harmful – neither of which is certain. These policies will have little impact on any further global warming, but will reduce our capacity to deal with whatever other issues or threats arise, both in the short term and long term. It would be sensible to scale back current policies rather than intensify them because there might be a slight further rise in sea level by 2300.
Note: Judith Curry is running a series of blogs on sea level rise, which will form the basis of a published paper. Some of my letter draws on those blogs – I appended the URLs to my letter.
But who to blame? I’d blame urban doofus, pissant progressives for undermining rational policy development for decades while harboring ambitions of economic and community transformation in some bucolic vision of equal poverty. They are doing it still with bleatings about energy emissions threatening more than 2 degrees of horror if more draconian measures than Paris are not implemented immediately. The first is absurd policy and the second ridiculous science. And we do know what poverty brings.
“The Indian Ocean brown cloud or Asian brown cloud is a layer of air pollution that recurrently covers parts of South Asia, namely the northern Indian Ocean, India, and Pakistan.[1][2] Viewed from satellite photos, the cloud appears as a giant brown stain hanging in the air over much of South Asia and the Indian Ocean…” Wikipedia
Black carbon and sulfate are co-emitted aerosols and the warming potential of black carbon is amplified by up to twice depending on the mixing ratio.
“Many ignore the internally mixed state of BC with other aerosols. Such mixing enhances forcing by a factor of two (ref. 39). Field observations have consistently shown that BC is well mixed with sulphates, organics and others” Ramanathan
and Carmichael (2008) – Global and regional climate changes due to black carbon
It may seem iconoclastic but makes perfect physical sense. It would also make mixed aerosols the largest source of anthropogenic warming in the 20th century and the one most easily addressed with off the shelf technology in the 21st – including with high efficiency/low emission coal generation.
e.g. https://watertechbyrie.com/2014/06/30/black-carbon-a-health-and-environment-issue/
https://watertechbyrie.files.wordpress.com/2017/06/hele.jpg
Globally people are reclaiming deserts and restoring soils, forests. wetlands and grasslands in a massive geoengineering project that makes far more scientific, economic, biodiverstity and development sense than any amount of seeding the skies with sulfate, the oceans with iron or cluttering space with solar umbrellas. There is the potential to sequester 100Gt(C) over the next 40 years. But who cares – I am bored to tears with climate change. The benefits for food security, economic development, flood and drought mitigation and biodiversity are tangible.
https://www.youtube.com/watch?v=8QUSIJ80n50
Increased agricultural productivity, increased downstream processing and access to markets build local economies and global wealth. Economic growth provides resources for solving problems – conserving and restoring ecosystems, better sanitation and safer water, better health and education, updating the diesel fleet and other productive assets to emit less black carbon and reduce the health and environmental impacts, developing better and cheaper ways of producing electricity, replacing cooking with wood and dung with better ways of preparing food thus avoiding respiratory disease and again reducing black carbon emissions. A global program of agricultural soils and ecological restoration is the foundation for balancing the human ecology. Many countries have committed to increasing soil carbon by 0.4% per year.
Including Australia where it is a mainstay of meeting the Paris commitment in a comprehensively designed, monitored and verified program that has known costs and is being shared with our region. Very little more is coming from wind and solar. New subsides end in 2020. There is a scramble to build pumped hydro storage to better utilize what there is.
https://watertechbyrie.files.wordpress.com/2018/02/aust-emissions.jpg
Nearly half of emission reductions is coming from the land use sector, and more from efficiency gains, other greenhouse gases and technology improvement. It not only reduces greenhouse gas emissions but puts the economy on a sounder footing. And as I say the costs are known. Beyond 2030 is cheap and abundant 21st century energy.
https://watertechbyrie.files.wordpress.com/2018/02/erf-fourth-auction-november-combined-results.png
I have focused on Australia – because of the detail available. And because all that I could find elsewhere was energy emissions and dire warnings. The difference is that what I have outlined is a pragmatic approach that will likely work. It puts the anthrpogenic component of future sea level rise into a broad, rational context.
Reblogged this on Climate Collections.
Committed sea-level rise under the Paris Agreement and the legacy of delayed mitigation action
This is an utterly dreary techno-babble fantasy. Just the sort of thing JayZee loves.
“Global energy use is expected to rise nearly 50 percent by 2035 and as much as double or triple by midcentury. 7 Policymakers in the Kyoto era viewed soaring global energy demand as an obstacle to emissions reductions. In this new era, we should see it as an opportunity — to catalyze innovation, to enfranchise hundreds of millions of people who now lack access to modern energy sources, and to discover new decarbonization paths.” https://thebreakthrough.org/blog/Climate_Pragmatism_web.pdf
Judith I eagerly await part V. In the meantime, I am having a bit of an emperor’s new clothes moment when I have a look at the individual tide gauge records from around the world in NOAA’s list of 159 stations with records longer than 60 years. http://www.sealevel.info/MSL_NOAA2013_60yr_thumbs.html
Many of them extend into the 19th century; NONE of them show any acceleration. They are remarkably straight, no matter what their slopes. My takeaway is if there is no acceleration in those records at or after the point (ca 1960) the anthropogenic atmospheric CO2 component became significant, then there is no anthropogenic signal.
https://ourworldindata.org/wp-content/uploads/2017/04/Global-CO2-emissions-by-region-since-1751.png
It’s amazing how Vertical Land Motion and gravitational pull are zero effect on the longterm rate of sea level rise. Maybe you’re doing it wrong.
One of the issues is that the acceleration seems localized in tropical east pac, and the southern hemisphere! Natural or AGW? stay tuned . . .
Yes, it is odd that the Eastern Pacific can bully other regions. It’s such a beast. And then there is the AMOC and the east coast of the US.
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