by Judith Curry
I am preparing a new Special Report on Hurricanes and Climate Change.
This Report is easier than my Special Report on Sea Level and Climate Change. Sea level and glaciers are very fast moving topics, whereas for hurricanes, the big picture conclusions haven’t really changed in a decade.
The Table of Contents for the Report: [ HR outline ]
The topic of tropical cyclones and climate change is regularly assessed by the IPCC and US National Assessment Reports, as well as by other expert reports under the auspices of the WMO, CLIVAR and other organizations. With regards to the question: ‘Why another assessment report on Hurricanes and Climate Change?’ here is my response:
CFAN’s Special Report on Hurricanes and Climate Change is distinguished from recent assessments by the following:
- a focus on hurricane aspects that contribute to landfall impacts
- an emphasis on geologic evidence and interpretation of natural variability
- an approach to ‘detection and attribution’ that does not rely on global climate models
- a perspective on future projections that accounts for uncertainties in climate models and also includes natural climate variability
- a longer format that allows for more in depth explanation suitable for a non-expert audience.
Basically, this Report is motivated by the needs of my clients in the energy and insurance sectors. After grappling with this issue for the past 15 years, both from the perspective of a research scientist and the owner of a weather/climate services company (Climate Forecast Applications Network), I have a perspective that is somewhat different from other academic or government scientists addressing the problem of hurricanes and climate change.
I plan to make the full report available in May, I look forward to your feedback and suggestions.
In this post, I’ll start with Chapter 3 on the observational datasets of hurricane variability and trends. An additional 4 posts on this topic will provided in the coming weeks.
Historical variability and trends
Documenting the variability and trends of hurricane activity requires long and accurate data records. Historical information on hurricane activity is obtained from the following sources:
- satellite observations (since ~1966)
- aircraft instrumental observations (since 1944)
- surface-based instrumental observations – landfalls, ships (since the 1800’s)
- historical reports
Over the years, the way that hurricanes have been observed has changed radically. As a result, many hurricanes are now recorded that would have been missed in the past. Furthermore, satellites are now able to continually assess wind speeds, thus recording peak wind speeds that may have been missed in pre-satellite days. Unfortunately, temporally inconsistent and potentially unreliable global historical data hinder detection of trends in tropical cyclone activity.
This Chapter assesses the variability of global and regional hurricanes over the entire available database. An assessment is provided as to whether we can detect any global or regional trends in hurricane activity from the available data.
3.1 Global
Reliable global hurricane data from satellite has been available since 1970, although inference of hurricane intensity is not judged to be reliable prior to 1980 (and in some regions, prior to 1988). Hurricane intensity is estimated from visible and infrared satellite observations through cloud patterns and infrared cloud top temperatures.
Figure 3.1 shows the time series since 1981 of total global hurricanes and major hurricanes. On average, each year there are about 47 hurricanes with about 20 reaching major hurricane status. Substantial year-to-year variability is seen, with a slight decreasing trend in the number of hurricanes and a slight increasing trend in the number of major hurricanes.
Figure 3.2 shows the time series since 1971 of the global Accumulated Cyclone Energy (ACE) (see Chapter 2 for a definition of ACE). As an integral of global hurricane frequency, duration and intensity, ACE shows greater decadal variation than does the number of hurricanes in Figure 3.1. No trend in ACE is seen, and the recent period of 2009 to 20015 was characterized by particularly low values of ACE.
Figure 3.1: Global Hurricane Frequency (all & major) since 1981 – 12-month running means. The top time series is the number of global tropical cyclones that reached at least hurricane-force (maximum lifetime wind speed exceeds 64-knots). The bottom time series is the number of global tropical cyclones that reached major hurricane strength. Source: Maue (2018).
Figure 3.2: Global and Northern Hemisphere Accumulated Cyclone Energy: 24 month running means. Note that the year indicated represents the value of ACE through the previous 24-months for the Northern Hemisphere (bottom line/gray boxes) and the entire global (top line/blue boxes). The area in between represents the Southern Hemisphere total ACE.
Source: Maue (2018)
3.1.1 Intensity
Figure 3.1 indicates that the number of major hurricanes is increasing globally, whereas the total number of hurricanes is decreasing. An increase in hurricane intensity has long been hypothesized to occur as global sea surface temperatures increase.
Emanuel (2005) identified a trend since 1950 of increasing maximum hurricane Power Dissipation Index (PDI), focusing on hurricanes in the North Atlantic and North Pacific. Shortly thereafter, Webster et al. (2005) showed that while the total number of hurricanes has not increased globally since 1970, the proportion (%) of Category 4 and 5 hurricanes had doubled, implying that the distribution of hurricane intensity has shifted towards more intense hurricanes.
Klotzbach and Landsea (2015) updated the Webster et al. (2005) analysis (Figure 3.3), with an additional 10 years of data and the availability of the International Best Tracks (IBTrACS) dataset, which reflects a cleaning up and homogenization of the data relative to what was used by Webster et al. Interpretation of any increase in the % of Cat 4/5 hurricanes depends on interpretation of the data quality, which Klotzbach and Landsea argue is an issue prior to 1988. Klotzbach and Landsea make a convincing argument that data prior to 1980 should not be used in trend analyses. The debate on the increase in % CAT4/5 hurricanes hinges on whether the data from 1985-1989 is of useful accuracy, since the large jump occurs between 1985-1989 and 1990-1995. The primary problem with the data between 1985 and 1987 is missed tropical cyclones in the North Indian Ocean, and a classification change in Northeast Pacific (both regions contribute a relatively small number to the total global tropical cyclone count).
To address concerns about the validity of intensity data from the earlier periods, Kossin et al. (2013) developed a new homogeneous satellite-derived dataset of hurricane intensity for the period 1982-2009. The lifetime maximum intensity (LMI) achieved by each reported storm is calculated and the frequency distribution of LMI is tested for changes over this period. Kossin et al. found that globally, the stronger tropical cyclones have become more intense at a rate of about +1 m/s per decade during the period (Figure 3.4), but the statistical significance of this trend is marginal. Significant increases in the strongest hurricanes have occurred in the North Atlantic and decreases in the Western North Pacific.
Figure 3.3. (a) Pentad total of the number of hurricanes that achieved a maximum intensity of each category grouping as delineated by the Saffir–Simpson scale. (b) As in (a), but for the percentage of total hurricanes achieving each category grouping. Klotzbach and Landsea (2015)
Figure 3.4. Plots of quantiles (mean to 0.9) of the lifetime maximum intensity (LMI) of storms in the various tropical cyclone formation basins, from a homogenized satellite-based analysis of tropical cyclone intensity (1982–2009). Kossin et al. (2013).
3.1.2 Intensification
Apart from the issue of maximum lifetime intensity achieved by a hurricane, the rate of intensification of hurricanes is receiving increasing scrutiny.
A recent study showed the 95th percentile of 24-h intensity changes significantly increased in the central and eastern tropical Atlantic basin during the period 1986–2015 (Balaguru et al, 2018). The intensification rate increased significantly between 1977 and 2013 in the West Pacific (Mei et al, 2016). In both the Atlantic and West Pacific, the areas with the largest increase in sea surface temperatures (SSTs) were collocated with the largest positive changes in intensification rates.
Bhatia et al. (2019) conducted a comprehensive analysis of global rates (excluding the Indian Ocean) of hurricane intensification for the period 1982-2009 (Figure 3.5). Evaluation of the global data is hampered by intensity analysis uncertainties, although the intensity uncertainty is very low for the North Atlantic. In the two most reliable long-term observational records available for hurricane intensity changes, the proportion of the highest 24-hour hurricane intensification significantly increased in the Atlantic between 1982 and 2009. Globally, a significant increase in hurricane intensification rates is seen in IBTrACS data but not in ADT-HURSAT (satellite-derived).
Figure 3.5 Quantile regression of 24-h intensity changes. Slope of the quantiles for 24-h intensity changes during the period 1982–2009. Slopes are shown for IBTrACS (a, c) and ADT-HURSAT (b, d) globally (a, b) and in the Atlantic basin (c, d). Source: Bhatia et al. (2019)
3.1.3 Tracks
Recent research has highlighted variation in the speed and location of hurricane tracks. These variations are significant in changing landfall locations and hurricane-induced rainfall.
Kossin (2018) showed that that tropical-cyclone translation speed (rate of forward motion) has decreased globally by 10 per cent over the period 1949-2016 (Figure 3.6). The global distribution of translation speed exhibits a clear shift towards slower speeds in the second half of the period.
This slowdown is found in both the Northern and Southern Hemispheres but is stronger and more significant in the Northern Hemisphere, where the annual number of tropical cyclones is generally greater. The times series for the Southern Hemisphere exhibits a change-point around 1980 (Figure 3.6), but the reason for this is not clear. An overall slowdown while over water was found in every basin except the northern Indian Ocean. The largest slowdown was found in the western North Pacific Ocean and the region around Australia.
Figure 3.6 Global (a) and hemispheric (b) time series of annual-mean tropical-cyclone translation speed and their linear trends. Grey shading indicates 95 percent confidence bounds. Source: Kossin (2018).
In addition to the global slowing of hurricane translation speed, there is evidence that hurricanes have migrated poleward in several regions. Migration in the western North Pacific was found to be large, which has had a substantial effect on regional hurricane-related hazard exposure.
Kossin et al. (2014) identified a pronounced poleward migration in the average latitude where tropical cyclones have achieved their lifetime-maximum intensity (LMI) over the period 1982-2012. The poleward trends are evident in both the Northern and Southern Hemispheres, with an average migration of tropical cyclone activity away from the tropics at a rate of about 1° latitude per decade. In the Northern Hemisphere, the western North Pacific shows the largest migration, with the North Atlantic showing essentially no trend.
Moon et al. (2015) suggested that the poleward migration is greatly influenced by regional changes in hurricane frequency associated with multi-decadal variability, particularly for the Northern Hemisphere (NH). Moon et al. found 92% of the poleward trend is a result of the frequency changes associated with multi-decadal variability.
Daloz et al. (2018) examined whether the poleward migration of hurricane lifetime-maximum intensity is associated with a poleward migration of hurricane genesis (formation). They found a shift toward greater average potential number of genesis at higher latitudes over most regions of the Pacific Ocean, which is consistent with a migration of tropical cyclone genesis towards higher latitudes. They also found significant poleward shifts in mean genesis position over the Pacific Ocean basins.
3.1.4 Rainfall
Walsh et al. (2015) concluded that for the globe, a detectable change in tropical cyclone-related rainfall has not been established by existing studies. However, satellite data is being increasingly used to assess tropical cyclone rainfall.
Kim and Ho (2018) examined the variation of hurricane rainfall area over the subtropical oceans using satellite radar precipitation data collected from 1998 to 2014. In the subtropics, higher translation speed and larger vertical wind shear significantly contribute to an increase in hurricane rainfall area by making horizontal rainfall distribution more asymmetric, while sea surface temperature rarely affects the fluctuation of hurricane rainfall area. They suggested that in the subtropics, unlike the tropics, atmospheric circulation conditions are likely more crucial to varying hurricane rainfall area than factors such as sea surface temperature.
3.3 North Atlantic
The North Atlantic has the best data quality of any of the regions. There is credible data on frequency and intensity since 1850, with the intensity data being most reliable since 1944, when aircraft reconnaissance flights began. Prior to the onset of satellite coverage in 1966, NOAA has adjusted total basin-wide counts upward based on historical records of ship track density. During years when fewer ships were making observations in a given region, hurricanes in that region were more likely to have been missed, or their intensity underestimated to be below hurricane strength, leading to a larger corresponding adjustment to the count for those years. These adjustment methods are cited in Knutson et al. (2010).
The impact of undercounting is illustrated in Figure 3.7, which compares the raw hurricane counts (green) with adjusted counts (orange) for the period 1878-2015. The sign of the long-term trend depends critically on the adjustment.
Figure 3.7. Time series for the period 1878-2015 of the total number North Atlantic hurricanes – unadjusted (green); adjusted (orange). The number of U.S. landfalling hurricanes is in red. Curves have been smoothed using a five-year average, plotted at the middle year. Source: https://www.epa.gov/climate-indicators/climate-change-indicators-tropical-cyclone-activity
Figure 3.8 shows the yearly values for the adjusted time series since 1850, for total North Atlantic hurricane counts and major hurricane counts. While the number of major hurricanes prior to 1944 is probably undercounted, it is noteworthy that the number of major hurricanes during the 1950’s and 1960’s was at least as large as the last two decades.
Figure 3.8 Adjusted numbers of total Atlantic hurricanes (top) and major hurricanes (bottom). Source: http://www.aoml.noaa.gov/hrd/hurdat/comparison_table.html
Accumulated Cyclone Energy (ACE) (Figure 3.9) and Power Dissipation Index (PDI) (Figure 3.10) provide integral measures of overall hurricane activity, with PDI providing greater weight to intensity. Values of ACE during the 1950’s and 1960’s are comparable to recent decades. Regarding PDI, the years 1926, 1934 and 1962 have PDI values as large as seen in 2004, 2005, 2017, although prior to 1944 intensity data is less reliable.
Figure 3.9 Accumulated Cyclone Energy Index for the Atlantic Ocean. Source: http://www.aoml.noaa.gov/hrd/hurdat/comparison_table.html. Ourworldindata.org
Figure 3.10 Power Dissipation Index (PDI) for the North Atlantic From 1920-2018. Source: Ryan Maue.
All measures of Atlantic hurricane activity show a significant increase since 1970. However, high values of hurricane activity (comparable to the past two decades) were also observed during the 1950’s and 1960’s, and by some measures also in the late 1920’s and 1930’s.
3.4 Paleotempestology
Hurricane data records for the past 40 years, or even the past 150 years, can present a misleading picture of range of variability of hurricane characteristics. Paleotempestology is the study of storm occurrence prior to the historical record. This provides a way of establishing a longer climate baseline than the relatively short observational record.
Many types of geological proxies have been tested for reconstructing past hurricane activity, including hurricane-induced deposits of sediments in coastal lakes and marshes, stalagmites in caves, tree rings and corals. Since these studies typically focus on a specific geographic location, a caveat is that they cannot distinguish between regional trends and systematic changes in hurricane tracks.
In the Australian region, Haig et al. (2014) used oxygen isotopic analysis of stalagmite records to show that the present low levels of storm activity on the mid west and northeast coasts of Australia are unprecedented over the past 1,500 years. Their results reveal a multicentennial cycle of tropical cyclone activity, the most recent of which commenced around AD 1700. The present cycle includes a sharp decrease in activity after 1960 in Western Australia.
Nyberg et al. (2007) constructed a record of the frequency of major Atlantic hurricanes over the past 270 years using proxy records in the Caribbean from corals and a marine sediment core. The record indicates that the average frequency of major hurricanes decreased gradually from the 1760s until the early 1990s, reaching anomalously low values during the 1970s and 1980s.
Wallace et al. (2015) review paleo-trends in hurricane activity from sedimentary archives in the Gulf of Mexico, Caribbean and western North Atlantic margins. A site from Mattapoisett Marsh, Massachusetts shows that the total hurricane deposits have remained relatively constant between 2200 and 1000 years B.P. (before present). However, the last 800 years B.P. appear to have been a time of relatively frequent total storm deposition. A site from Laguna Playa Grande, Puerto Rico has reconstructed intense hurricanes occurring over the past 5000 years B.P., with prominent increases in activity observed during 4400 – 3600, 2500 – 1000, and 250 – 0 years B.P. In the Gulf of Mexico, while the overall frequency of events remained relatively constant over the 4500 year record, the frequency of high threshold events has varied considerably – periods of frequent intense hurricane strikes occurred during 3950 – 3650, 3600 – 3500, 3350 – 3250, 2800 – 2300, 1250 – 1150, 925 -875, and 750 – 650 years B.P.
Brandon et al. (2013) found a period of increased intense hurricane frequency between ~1700 and ~600 years B.P. and decreased intense storm frequency from ~2500 to ~1700 and ~600 years B.P. to the present.
There has not been a timeline or synthesis of these results for the past five thousand years, either regionally or for the entire coastal region. However, it is clear from these analyses that significant variability of landfall probabilities occurs on century to millennial time scales. There appears to have been a broad ‘hyperactive period’ from 3400 to 1000 years B.P. High activity persisted in the Gulf of Mexico until 1400 AD, with a shift to more frequent severe hurricane strikes from the Bahamas to New England occurring between 1400 and 1675 AD. Since 1760, there was a gradual decline in activity until the 1990’s.
3.4 Conclusions
Analyses of both global and regional variability and trends of hurricane activity provide the basis for detecting changes and understanding their causes.
The relatively short historical record of hurricane activity, and the even shorter record from the satellite era, is not sufficient to assess whether recent hurricane activity is unusual for during the current interglacial period. Results from paleotempestology analyses in the North Atlantic at a limited number of locations indicate that the current heightened activity is not unusual, with a ‘hyperactive period’ apparently occurring from 3400 to 1000 years before present.
Global hurricane activity since 1970 shows no significant trends in overall frequency, although there is some evidence of increasing numbers of major hurricanes and of an increase in the percentage of Category 4 and 5 hurricanes.
In the North Atlantic, all measures of hurricane activity have increased since 1970, although comparably high levels of activities also occurred during the 1950’s and 1960’s.
Reblogged this on Quaerere Propter Vērum.
Excellent analysis, thanks!
Nice!
Is there any good evidence of big energy storm events in modern geology?
Has the rate of this storm debris in the Little Ice Age been found and compared to modern rates? Or perhaps as there is littel storm damage this “lack of evidence” has been overlooked?
A quick search gave this paper:
Atlantic hurricane activity during the last millennium
Michael J. Burna,1 and Suzanne E. Palmer2
Sci Rep. 2015; 5: 12838.
which links SST to cyclone formation in the caribean to SST. A rise during the medieval warm period and a drop during the little ice age periods.
This does not give an idea of intensity, however. Somewhere along the coasts of the Gulf and Florida (and in the Philipines) there should be deposits of coarse sand, organic material from vegetation and marine shells that are only deposited (a few km inland) during high energy events. Perhaps of more interest to Judiths concept of storm damage.
Great post. Much food and data for thought.Thanks
Thanks, Judith.
A prominent NCAR scientist told me that ACE is the worst metric for measuring hurricane activity. It doesn’t measure an energy, it doesn’t consider storm sizes or the speed of the eye. In Hurricane Harvey the eye stalled over Houston and dumped record setting amounts of rain, which caused the real damage (not wind speed).
stay tuned, landfall impacts are in different chapters.
Good. I look forward to reading it.
David –
Do you know of any analyses of trends using the alternative metrics you mention in the article Steven linked below?
I found this in the context of Houston getting wetter. The first point to note is that where a storm dumps it load is at the whim of the Dragon-Kings. The Harvey dump on Houston would need
https://www.washingtonpost.com/resizer/rN4bu2moPok7NSPro3oPt2kRxbg=/1484×0/arc-anglerfish-washpost-prod-washpost.s3.amazonaws.com/public/MGC7P5N6C5G6NGBQ3U6R2LBPB4.png
… to be compared with point rainfall across the region to meaningfully claim a record.
The second point is that for systems that evolve over decades to millennia – the record is far too short to derive justifiable conclusions. Even then linearity seems especially problematic.
https://www.pnas.org/content/pnas/101/12/4136/F5.medium.gif
“Drought frequency (in percent of years) for positive and negative regimes of the PDO and AMO. (A) Positive PDO, negative AMO. (B) Negative PDO, negative AMO. (C) Positive PDO, positive AMO. (D) Negative PDO, positive AMO.”
https://www.pnas.org/content/101/12/4136
So without the unscientific inferences – we are left with the notion that flooding causes damage?
The wind speed in the eye is very low ( eye of the storm ), the speed of progression of the eye is typically pretty pedestrian compared to the wind speeds of the storm. This does not account for much energy.
It’s unclear what issue your anon. NCAR chap has with that.
Kinetic energy is proportional to the square of the speed. So in that sense ACE is an energy term. If the gripe is that using sustained wind speed is not representative of total energy of the storm, that needs to be stated explicitly , with reasons.
All you have so far is an anonymous “NCAR” guy with some unstated objections.
Here is David with a bit more detail
https://slate.com/technology/2017/09/a-better-metric-for-measuring-hurricanes.html
And when the Arctic Sea Ice extent recovers, I expect there will be calls for new metrics more favorable to AGW. When losing the game, change the rules.
If ACE were a temperature metric skeptics would be all over it.
But watch greggrog defend it
Reblogged this on Climate Collections.
How many of the children who are taking a holiday from school, to protest about climate change, know what Russia’s average temperature is?
I am guessing, not many.
If you told them that Russia’s average temperature was +0.2 degrees Celsius, how many would have enough science and mathematics knowledge, to say whether that was hot or cold (especially American children, who are not familiar with Celsius).
I am guessing, not many.
How many of the children who are taking a holiday from school, to protest about climate change, know that Russians live at an average temperature, which is near the freezing point of water?
I am guessing, not many.
How many of the children who are taking a holiday from school, to protest about climate change, know that the average coldest month in Russia (the coldest winter month), is -21.1 degrees Celsius (yes, that is MINUS 21.1).
I am guessing, not many.
How many of the children who are taking a holiday from school, to protest about climate change, know that Russian children are also taking a holiday off school. To demand that the world increases global warming, so that they can survive in the future.
I am guessing, not many.
To increase your knowledge of other countries temperatures (average hottest month, average month, and average coldest month), read the article at this link:
https://agree-to-disagree.com/how-hot-is-that-country
So you think schoolchildren don’t know if it’s hot or cold outside, right?
How many of the children who are taking a holiday from school, to protest about climate change, know even the first thing about climate.
Not many, I am guessing.
Dr. Curry,
Excellent endeavor, a much needed perspective to the nowadays memes that automatically attribute hurricanes to CC. I would call this tendency “The scandal of Attribution” per Nassim Taleb’s expression of “The scandal of Prediction”. As an example of attribution gone amok, addressed in your blog a few weeks ago, but worth repeating: in the aftermath of the recent Camp Fire, there was an avalanche of attributing this catastrophic fire to CC. It happened from the Gov. of California on down, in the face of clear evidence that it was initiated by PG&E’s alleged negligence (see lawsuit possibly leading to bankruptcy) and moreover after Cliff Mass’ excellent forensics like analysis that showed that CC was NOT a significant factor if at all. I recall an article cited in one of your postings where four weather/climate events (hurricanes?) were “analyzed” as to having been predominantly CC caused: 2 were found non CC related, one half/half and one mainly CC caused. I wonder if a body of scientists incl. climate scientists exists or could be formed, possibly sanctioned by IPCC or US Gov. to systematically do after the fact forensics against scientific markers and decide on attribution of major events such as hurricanes or wild fires. I realize that attribution has been addressed before in many ways by various forums. But the current irresponsible attribution of just about any weather/wild fire/etc. event to CC surely diminishes the credibility of the already challenged Climate sciences especially if spread by politicians turned “scientists” or even worse by scientists turned political activists. This is almost reminiscent of the Medieval times in Europe when the plague was blamed on the lack of religiosity of the masses or on specific ethic/religious groups. Sorry for the lengthy comment and below average prose.
Great overview. The 15-year running average for the total number of North Atlantic hurricanes looks vaguely familiar to the 60 year temperature oscillation cycle. Increase in hurricanes during the 1940-1950 warm period, increase in hurricanes in 1880 during the super El Niño, and an increase from 1985 to 2005.
https://imgur.com/a/8Fb5Nc0
Interestingly, the 15-year running average for the total number of North Atlantic hurricanes seems to roughly in phase with the 31/62 year Perigean New/Full moon tidal cycle that naturally breaks up into 31-year epochs starting in 1870, 1901, 1932, 1963, and 1994.
This is of interest since I believe that, westerly moving equatorial Rossby waves are generated by the passage of Kelvin-waves across the Equatorial Atlantic ocean, every time the Moon crosses the Earth’s equator or reaches a lunar standstill. These westerly moving Rossby waves are associated with pairs of tropical low-pressure cells that straddle the equator. These could act as the seeds for the development of hurricanes.
It is possible that the number and/or strength of these low-pressure cells could be influenced by the proximity of the Moon to the Earth when it crosses the Earth’s equator or reaches a lunar standstill. Hence the connection to the 31/62-year Perigean New/Full moon cycle.
Sorry, here is another link to the figure that should have appeared in the above post:
https://1.bp.blogspot.com/-ltGhdRt7CMM/XGp5oywDvMI/AAAAAAAABhg/2g_UQUs5g7AweJZAQhPeKzvCQnOY6ZXNACLcBGAs/s640/IPT1MbJl.jpg
Here is the plot of the Accumulated Cyclone Energy Index for the Atlantic Ocean that allows an extension of the comparison between the Perigean New/Full moon tidal cycle and hurricane strength back to 1850.
https://1.bp.blogspot.com/-XAe-FK287oo/XGqCqp6OZMI/AAAAAAAABh4/XTVIqg6yZ0YnrBMflftnQeMwTwtWRO_pQCLcBGAs/s640/slide09.jpg
The 60-year cycle in the Accumulated Cyclone Energy Index (and number) of North Atlantic hurricanes could also be linked to the 60-year cycle seen in the trade-winds of the tropical Atlantic ocean (going back almost 350 years) and the 60-year cycle in the All India Summer Monsoon rainfall (going back to 1820).
https://3.bp.blogspot.com/-pPhOIijfUrE/WdzjbQQJm4I/AAAAAAAABJo/4-ASQfxgkoYVyyVgERdS3Teg3roPw5mNACLcBGAs/s400/60years_a.JPG
Note: the 31/62-year Perigean New/Full moon tidal cycle is compatible with the data.
Sorry for so many posts, this is the last of this sequence.
If you investigate the precise alignment between the 31/62-year Perigean New/Full Moon tidal cycle with the seasons over inter-decadal to centennial timescales, you find that precise alignments occur at intervals of (28.75 + 31.00) tropical years = 59.75 tropical years. ~ 60 years.
Don’t know how relevant this is, but last year, out of curiousity, I googled ‘Worst U.S. Atlantic Coast Storms’, and was surprised to learn that of the 10 worst storms in recorded history, 5 0f the 10, were between 1928 and 1936.
The issue is not is climate change happening or is climate change not happening or is it causing worse disasters or not. The issue is how much is natural and how much is caused by man made CO2 and what proof is there of this.
None of this helps understand natural causes of climate change. Climate change has happened forever in history and will happen forever in the future.
What is being done to understand natural causes of climate change?
Nothing much, it really is not even discussed.
Its becomes difficult to tease out the natural variabilty when all the research money is being poured into finding the increase in c02 as being at fault. Along with the myopic view that climate change is only caused by increases in co2.
As this blog has noted, there are numerous natural factors with much higher correlations to the frequency and intensity of storms, than the increases in co2, yet the activists are so focused on the single cause, that the overlook the obvious.
Seems like it is going to be as hard to build based on tempest projections as on an analysis paliotempestology results.
The IPCC’s latest report, SR15, actually says that hurricanes are decreasing. This is in my pinned tweet. Chapter 3, page 203
“Numerous studies towards and beyond AR5 have reported a decreasing trend in the global number of tropical cyclones and/or the globally accumulated cyclonic energy (Emanuel, 2005; Elsner et al., 2008; Knutson et al., 2010; Holland and Bruyère, 2014; Klotzbach and Landsea, 2015; Walsh et al., 2016).”
According to E. Garnier, J. Desarthe, and D. Moncoulon, based on detailed historical records, the period 1750–1850 corresponds to the longest and most intense cyclonic episode in French Antilles [11/1519/2015/cpd-11-1519-2015].
“The historic reality of the cyclonicvariability in French Antilles, 1635–2007”
Pingback: Hurricanes & climate change: detection | Watts Up With That?
Pingback: Hurricanes & climate change: detection |
There are at least two meta-studies on storminess in the North Atlantic for the past 6000 years.
Sorrel, P. et al. 2012. Persistent non-solar forcing of Holocene storm dynamics in coastal sedimentary archives. Nature geoscience, 5, 12, 892.
Costas, S. et al. 2016. Windiness spells in SW Europe since the last glacial maximum. Earth and Planetary Science Letters, 436, 82-92.
I did a graphical study on Costas et al meta-study and found strong evidence for a 1500-yr periodicity in storminess, with power on the 750-year harmonic. It is surprising such a clear conclusion from so disparate studies, when it is not evident in the individual studies.
https://curryja.files.wordpress.com/2017/09/figure-75.png
Figure 75. The 1500-year storminess cycle. a) Five Holocene widespread storm intervals defined on the basis of nine independently dated records of northern coastal Europe storm activity. Source: P. Sorrel et al. 2012. Nature Geosci. 5, 892-896. b) Score of the seventeen independent storminess studies for the North Atlantic and Western Mediterranean compiled from the literature in S. Costas et al. 2016. Earth Planet. Sci. Lett. 436, 82–92. c) Figure 10 from Costas et al., 2016 displaying the periods of high storm activity as black boxes for the seventeen studies that are the basis for the score analysis in b. For the identification of the individual studies see the source. DO periodicity is indicated with continuous grey lines. Dashed and dotted grey lines represent harmonics of the DO periodicity. Arrows indicate storminess power at the 750-year harmonic.
https://judithcurry.com/2017/09/15/nature-unbound-v-the-elusive-1500-year-holocene-cycle/
What nearly all studies show is that storminess has been decreasing since the LIA.
Thx, v helpful
I know that I may as well be shadow-band at this site, given the response that I get to most of my posts (essentially zilch) but I have to point out that the 1470-year DO periodicity has a lunar tidal explanation, as well.
The line-of apse of the lunar orbit realigns itself with respect to the stars and the seasons once every 177 years. This happens because:
Full Moon Cycle (FMC) = Time for the lunar line-of-apse to realign wrt Sun
___________________= 1.127385 sidereal years
Lunar Anomalistic Cycle (LAC) = Time for the lunar line-of-apse to precess once around the Earth wrt to the stars.
_________________________= 8.8502 sidereal years
157 x FMC = 176.999 Sidereal years
20 x LAC = 177.004 Sidereal years
Note that the 177-year cycle is an alignment of the egg-shape of the lunar orbit with the stars and seasons does not apply to the Moon itself but just to the shape of its orbit.
The question then becomes: When does the 177-year cycle alignment of the egg-shape of the lunar orbit align with the New and Full Moon (i.e. the synodic or phase month)?
Answer: The Moon realign with the 177-year cycle at multiples of 708 years (= 4 x 177 years).
Sidereal Years___Offset by what fraction of a Synodic (phase) Cycle?
177_______________0.2681 =
354_______________0.5362 =
531_______________0.8043 =
708_______________0.0724 = 2.138 days
885_______________0.3405 =
1062______________0.6806 =
1239______________0.8767 =
1416= 2 x 708______0.1448 = 4.277 days
and 2 x 708 years = 1416 years.
People interested in solar eclipses know that an eclipse will occur above the same fixed location of the Earth once every three SAROS (or eclipse) cycles = 54.06 years (= 3 x 18.03 years)
1416 + 54 years = 1470 years = the quasi 1500 year DO cycle.
The problem, Ian, is that the 1470-yr periodicity was an artifact of GISP2. When GISP2 was put on the GICC05 timescale the 1470-yr band vanished. This is not reflected in any publication, because it is a negative result, but it is well known among researchers of Dansgaard-Oechsger events. Stephen Obrochta mentioned it in his review of an article in Climate of the Past.
1470 is no longer an acceptable number.
Javier, you haven’t read my post at:
http://astroclimateconnection.blogspot.com/2014/01/do-events-cause-rapid-warming-events-in.html
It clearly shows that your claim that the 1470-year periodicity is an artifact of GISP2 is a lie. Just because you keep repeating that lie and quote other people who have made the same mistake as you do, does not make it true.
[quote] There is some controversy about the GISP2, GRIP[,] and NGRIP
scaling chronologies for the Greenland ice core. Shown below
are the timing of DO events 0, 2, 8, 11, 12, and 13 using the latest
NGRIP-based Greenland Ice Core Chronology 2005 (GICC05)
time scale to the period between 14.9 – 32.45 ka b2k (before
A.D. 2000) [end quote]
http://3.bp.blogspot.com/-NZxewcD3Swc/UtYKOVqdtxI/AAAAAAAAAlI/LqK1xA_RAA4/s1600/Methane.jpg
http://3.bp.blogspot.com/-al3LIRly47I/UtYSk_ievpI/AAAAAAAAAlk/M7Pupk3fZVE/s1600/Comparison.jpg
Javier,
I sincerely apologize for my abrupt language. I am not calling you a lier but am saying that what you are asserting is false. And I can show evidence as to why it is scientifically false.
If you go to the research article:
Erhardt, T., Capron, E., Rasmussen, S. O., Schüpbach, S., Bigler, M., Adolphi, F., and Fischer, H.: Decadal-scale progression of Dansgaard-Oeschger warming events, Clim. Past Discuss., https://doi.org/10.5194/cp-2018-176, in review, 2018.
at______ https://www.clim-past-discuss.net/cp-2018-176/
and download the supplementary Xcel files for NEEM and NGRIP data in the .zip file, you will find the following Calcium (Ca) transition times for the OD events between about 11,000 and 60,000 B.C.E. The are on the GICC05 timescale. Use the Ca offsets (50 %) from the nominal ages for the transitions, using the NGRIP2 Excel file:
Transition_____Ca_Age_______Measuremnet
_Name________(years)_________Methods
Holocene____11665.2________Na,Ca,It, d18O
GI-1e_______14652.9________Na,Ca,It, d18O
GI-2.1_____________________NONE
GI-2.2_____________________NONE
GI-3________27728.3________Na, Ca,It, d18O
GI-4________28857.7________Ca,It, d18O
GI-5.1______30817.8________Ca
GI-5.2______32440.7________Na, Ca,It, d18O
GI-6_______33666.8________Ca,It, d18O
GI-7c______35424.4________Na, Ca,It, d18O
GI-8c______38170.1________Na, Ca,It, d18O
GI-9_______40120.3________Ca,It, d18O
GI-10______41402.2________Na, Ca,It, d18O
GI-11______43288.5________Na, Ca,It, d18O
GI-12c_____46808.1________Na, Ca,It, d18O
GI-13c_____49224.1________Na, Ca,It, d18O
GI-14e_____54169.1________Na, Ca,It, d18O
GI-15.1_____5494.6________Na, Ca,It, d18O
GI-15.2_____55772.4_______Na, Ca,It, d18O
GI-16.1c____57985.7_______Ca,It, d18O
GI-16.2_____58239.4_______Na, Ca,It, d18O
GI-17.1c____59037.1_______Na, Ca,It, d18O
GI-17.2_____59384.6_______Na, Ca,It, d18O
Now, this where you have to start thinking outside the box. Lunar alignments do no occur in rigid unchanging cycles that span thousands of years in time. They slowly drift in and out of alignment in what is known as drifting resonances. Hence, it is possible that you could get one 1470-year cycle slowly transitioning into another parallel 1470-year cycle that is offset by say half of the 1470 year cycle = 735 years.
First, we start by excluding DO events GI-2.1 and GI-2.2 because they do not have a Ca age.
Second, we take the following subset of the DO events above and use the Holocene DO transition event as our zero-point. The table below shows how far each event is offset from being a perfect multiple of 1470 years.
Transition___Multiple of___Offset from Perfect
_Name_____1470 years__Multiple of 1470 yrs
_________________________(years)____
Holocene_______0____________ 0.0
GI-1e__________2____________47.7
GI-3___________11___________-106.9
GI-5.1_________13____________42.6
GI-5.2_________14____________195.5
GI-6___________15___________48.4
GI-7c__________16___________239.2
GI-8c__________18___________44.9
GI-10__________20___________337.0
GI-12c_________24___________-137.1
GI-14e_________29___________-126.1
GI-15.2________30____________7.2
GI-17.1c_______32____________331.9
__(mean absolute offset)________128.0 years
Third, we take the remaining DO events and use the DO transition event GI-11 (43288.5 years) as our zero-point (since it is the first that is measured using all four methods). The table below shows how far each event is offset from being a perfect multiple of 1470 years.
Transition___Multiple of___Offset from Perfect
_Name_____1470 years__Multiple of 1470 yrs
GI-4__________-10___________-269.2
GI-11___________0___________0
GI-13c__________4___________55.6
GI-15.1_________8___________-103.9
GI-16.1c________10__________-2.8
GI-16.2_________10__________250.9
GI-17.2_________11__________-73.9
_(mean absolute offset)_______108.0 years
Given that the long term lunar alignment cycle could vary by at least 54 years (i.e. in the real world the lunar cycle could vary between 1416 and 1470 years), with only slight changes in the precision of the alignment and given that there is an additional uncertainty of ~ 30 years introduced by the offsets between the four different methods used to derive the DO transition ages, it should not be surprising that the mean absolute offset for the 1470 year
nominal cycle length is of ~ 110 – 120 years.
[Note there is one weak DO transition event GI-9 (40120.3 years) that does not fit the dual 1470-year pattern laid out above]
https://i.imgur.com/kM81Msj.png
Javier,
One-dimensional spectral analysis is absolutely hopeless at revealing drifting resonances like those that are exhibited by the lunar tidal alignments, especially if the drifting resonances are interlaced.
Some important points to make about the spectra analysis:
a) If you have a series of (what in effect are) multiple sharp spikes or sharp steps in a proxy time series, they will generate a broad band of spectral power in the frequency domain, particularly at sub-harmonic frequencies. The realtive power of the sub-harmonics that are generated will depend on the general temporal structure of the DO spikes. It is possible that this additional “noise” will hide and/or distort any underlying spectral peaks.
b) You would probably get a better result if you used some form of wavelet analysis. However, even this technique would not be able to pick up overlapping parallel sequences of DO events (as wavelet analysis makes no assumptions about which particular series a set of DO peaks belongs to).
Needless to say, it is more than likely that any useful spectral analysis would be a very difficult task.
Javier
This study in Nature from Jamaica (mainly) links cyclone activity to SST and was a min during the LIA.
Atlantic hurricane activity during
the last millennium
Michael J. Burn & Suzanne E. Palmer
Not much use for intensity (damage) though.
Alan
Thank you Alan, I have taken a look and that work has one problem. They assume that the average path of cyclones in the Atlantic hasn’t changed since the LIA.
However we know that the Hadley cell has expanded several degrees of latitude and the Polar cell has contracted correspondingly since the LIA. If you are looking at a place that gets in the main path you see an increase. If you are looking at a place that gets out of the main path you see a decrease. That’s why meta-studies that cover a wide area can be trusted better.
Cyclones form over sun warmed surfaces (>28.5 C) when convection is acted on by the Coriolis force. It comes together in the Main Development Region (MDR).
https://media.nature.com/lw926/nature-assets/srep/2015/150805/srep12838/images/srep12838-f1.jpg
The width of the Hadley Cell is irrelevant and the polar annular mode only relevant in as far as it influences northward heat transport. ENSO adds to frequency and intensity of tropical Atlantic cyclones with moisture and wind from divergent or convergent pressure cells in the eastern Pacific.
This study’s finding are entirely consistent with what is known of the origins – and paths – of tropical Atlantic cyclones.
As far as I know, cyclones are heat engines and not dependent on the Hadley cells.
My own interest in this is that evidence for cyclone activity is high during the PETM and also the mid-miocene CO (as found in the geology), but there is no or very little evidence in the geology for cyclones during the mid K “hothouse”. That SST over major oceans were hot during this period is clear, so another variable must have been involved that changed how these heat engines operate.
I suspect that this factor was a higher patm. I may have a post on this later.
Best
Alan
Of the observations, it should be noted, there was a shift of biases.
Ships avoided the phenomenon, for obvious reasons.
Aircraft actively pursued the phenomenon.
That’s partly the ‘adjustment’ in the NOAA/EPA plot:
https://curryja.files.wordpress.com/2019/02/slide07.png
But unobserved phenomena will forever remain unobserved.
Fortunately, satellite eyes now see all.
US landfalls, while only a small portion of the Atlantic total, did not suffer from this bias. And there does not appear to be any long term trend in hurricanes nor in major hurricanes landfalling on US shores.
Nice write up Judith.
I have often looked for information on the relationship with TCHP and Hurricane frequency and intensity, let alone the impact on TCHP from El Nino’s.
Unfortunately, the changes in methodology on calculating TCHP has changed several times and makes it difficult to evaluate localized trends, aside from the length and coverage of such records. I hope your coming paper will expand on the subject.
http://www.aoml.noaa.gov/phod/cyclone/data/method.html
Based solar activity over the latest solar cycle indicate to some that we may be headed for a ‘Maunder Minimum,’ redux.
Judith: May I politely suggest that your graphs and the literature are analyzing the wrong independent variable – TIME. The passage of time is not making hurricanes more powerful or frequent – but rising SST’s may be. SST’s are rising with time, but natural variability in SSTs and hurricane location means that any proper analysis of cause and effect must be based on the hurricane wind speed (not category) and the SST along the track followed by the hurricane. Cause and effect should be assessed directly hurricane by hurricane; not through their mutual correlation to a third variability, time. With about 90 tropical cyclones per year, reporting data in terms of cyclones per year vastly reduces the amount of data available to be analyzed and introduces complications from ENSO, AMO, and changing measurement technology. Then the numbers go down when one focuses on particular basins or categories or those that reach land.
FWIW, Michaels (2006) looked at the tracks and maximum wind speeds of 270 Atlantic hurricanes and found a wind speed increase of 2.8 m/s per degC rise in SST along the hurricane track. If no one else has published a better study, then this appears be the best answer available.
Thanks for the tip on the Michaels paper
( https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2006GL025757 )
Comments below.
As I looked for other papers showing a direct correlation between the wind speed of tropical storms and SST along storm track, I encountered Kerry Emanuel’s (2007) response Michaels (2006).
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2006GL026942
A key section reads: “A close inspection of the data, however, belies this assumption. It is first important to recognize that the actual thermodynamic control of tropical cyclone intensity is exercised through the potential intensity, which depends mostly on SST and the entropy‐weighted mean temperature of the storm’s outflow. Climatological spatial distributions of potential intensity (available at http://wind.mit.edu/∼emanuel/pcmin/climo.html) show very sharp gradients near the position of the 26°C SST isotherm, but these are almost entirely owing to sharp gradients in the outflow temperature, not to SST gradients per se [Emanuel, 1986]. (This results from the fact that in the subtropics, boundary layer air reaches buoyant equilibrium at the level of the Trade inversion, far lower, and therefore warmer, than the tropopause.) Since outflow temperatures are themselves highly correlated with SST, one is easily led to the false conclusion that potential intensity is highly sensitive to SST in the range centered at 26°C. The strong gradient of potential intensity with respect to SST in this range is owing to strong gradients in outflow temperature and would not translate, for example, to an equally strong dependence of potential intensity on temporal variations of SST when the outflow temperature is held constant.
Potential intensity is a theory, and most hurricanes achieve only a small fraction of their potential intensity. Even if wind speed varies with entropy‐weighted mean temperature of the storm’s outflow, we need hurricane by hurricane data showing how wind speed varies with SST and this parameter. Then we need to know how this parameter has varied in the past and how it is expected to change with rising GHGs. Wind shear is another important factor. The difference between SST and outflow may be more important that SST alone. Since some variables may be correlated, a multi-factorial analysis of the development of individual real hurricanes would obviously be superior to looking at a single factor. Then we need to know something about how all factors are expected to change with time.
None of the above changes my opinion that TIME is not the appropriate variable to place on the x-axis when analyzing hurricane intensity.
(For consistency, I’ll add that time is not the appropriate variable on the x-axis when analyzing global warming. Radiative forcing is the appropriate variable. The slope of the line is TCR and deviations are unforced variability.
None of the above changes my opinion that TIME is not the appropriate variable to place on the x-axis when analyzing hurricane intensity.
Check out the graphics below again.
For both NE Pacific and Atlantic basins, with respect to weaker storms,
major hurricanes tend to have:
1.) longer paths ( both intensification and degradation phases ) and
2.) more westward paths ( in accordance with Beta-plane forces ).
3.) lower latitude of formation
More westward and lower latitude tend to increase the SST a storm is exposed to.
More westward and lower latitude paths tend to increase the duration of the intensification phase, because both tend to protect the storm from destructive wind shear, which tends to increase with higher latitude.
It may be that duration of intensification is much more significant than SST wrt to storm intensity.
And this is born out by the intensification of NE Pacific storms even as they traverse progressively cooler waters.
stay tuned for the next part, on attribution
“Judith: May I politely suggest that your graphs and the literature are analyzing the wrong independent variable – TIME. ”
yup.
stay tuned, the SST argument doesn’t hold up very well
Should note this was Atlantic hurricanes.
The distributions and dynamics are not the same everywhere.
In the Atlantic, storm tracks tend to occur roughly parallel to the SST gradient and peak intensities occur at temperatures near the track average:
https://turbulenteddies.files.wordpress.com/2017/09/atlantic_1949_2016_figure_1.png
In the Pacific, storm tracks tend to occur perpendicular to the SST gradient, and storms intensify even as sea surface temperatures fall:
https://turbulenteddies.files.wordpress.com/2017/09/pacific_1949_2016_figure_4.png
The temperature correlation is not necessarily causation.
Duration of storm, from formation to peak, may be of greater importance.
And this can be largely determined by shear.
Hi Dr. Curry
It looks as the forecast from 7 years ago (we discussed in January 2012) is just about alive and kicking, but it needs the update.
http://www.vukcevic.co.uk/ACE4.htm
vukcevic
Could you please explain why in your fig. 3 (in the link) you moved the Arctic atmospheric pressure “ahead” 15 years.
What is the relationship between Arctic atmospheric pressure and North Atlantic ACE that takes 15 years to unfold.
Regards
Yes.
Both the AAP and the ACE as is the AMO appear to be quasi-periodic oscillations with a period of 60 years. In both mechanical and electric oscillations there is a ¼ period (here 60/4 = 15) relationship between co-related variables, i.e. when the variable A is at max the variable B has greatest rate of change and vice versa.
https://upload.wikimedia.org/wikipedia/commons/7/74/Waveforms_-_inductive_reactance.svg
or simply Sin – Cos relationship
https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Sine_cosine_plot.svg/750px-Sine_cosine_plot.svg.png
That’s an interesting kinda-correlation but your logic for the phase lag is very dubious. “because electricity” does not cut it. You can not explain a 1/4 cycle lag transmitting inter-annual changes 15y hence. For those signals it is not a 1/4 cycle. You could try : thermal energy is the integral of power flux and integration gives a lag but that suffers a similar problem since integration would take out the amplitude of the HF signals.
Isn’t it obvious? The derivative of the sine is the cosine.
If the value of a sinusoidal variable depends on the rate of change of another with the same periodicity, their relationship is 1/4 of the period, as Vukcevic has explained.
No Javier, it is not “obvious” since climate is not a pure sine wave and neither is it an idealised capacitor or inductor. Analogies can be informative but being simplistic in their application is not.
If you want to apply the derivative, say so, and do it . You will not find that the sharp inter-annual variations are also lagged by 15years, since that is not pi/2 for their frequency.
Also a quarter cycle lag is the maximum but it is not the only possible result in a system with inertia, feedbacks and other complicating factors.
It is very interesting what vuk’ has found but some better logic is needed to explain how that could work, if it is to be suggested that it is a real physical effect.
More Random Comments:
* The name: IBTrACS is somewhat offensive with bias
“International Best Track Archive for Climate Stewardship”
What time in history have humans ever assumed stewardship of climate?
* The shortfalls of the Atlantic counts are known, but what of the world’s other basins? This link,
https://tropical.colostate.edu/real-time-cyclone-activity/#1468450487074-f84cb69f-264f
indicates reliability of basin data from:
North Atlantic – 1966-present (Geostationary satellite data available)
Northeast Pacific – 1988-present ( NHC took over )
Northwest Pacific – 1985-present ( JTWC deems quality )
North Indian – 1985-present ( JTWC deems quality )
South Indian – 1985-present ( JTWC deems quality )
South Pacific – 1985-present ( JTWC deems quality )
* The story of the of the first flights into hurricanes is inspiring:
“as a barroom dare, two Army Air Corps pilots challenged each other to fly through a tropical storm. On July 27, 1943, Maj. Joe Duckworth flew a propeller-driven, single-engine North American AT-6 “Texan” trainer into the eye of a tropical storm. Duckworth flew into the eye of that storm twice that day, once with a navigator and again with a weather officer. “
Alcohol and bravado definitely have a place in science.
And the weather officer let the nevigator go first. Was he a weather weenie?
North Atlantic ACE has been dropping since 2005.
https://climategrog.files.wordpress.com/2019/02/ace_n_atl_2017.png
Remember that 2006 was the year Josh Willis discovered the drop in global SST until he was told to ‘get with the program’ and decided to delete the offending data ( mostly from the Atlantic where the cooling was showing up ).
here is an update of the SST vs ACE comparison from my “ACE in the hole” article 3 years back:
https://climategrog.files.wordpress.com/2019/02/sst-vs-ace_n_atl_2017.png
https://judithcurry.com/2016/01/11/ace-in-the-hole/
Note the divergence problem post 2005. Those predicting future cyclone/hurricane behaviour on the sole basis of SST need to be wary of simplistic, single variable predictions of climate.
Of course the classic climatology solution to this kind of problem is to crop off the inconvenient part of the data to “hide the decline” ( ME Mann ) or graft another dataset on using the same line style and blend the two together ( Phil Jones. )
https://i.imgur.com/OsGOXup.jpg
The ACE of the Northatlantic hurricans depends on the SST in the MDR (main development region) during the hurrican season with a rate of 21%. Very significantly. (data: our world in data; ERSSTv5)
There are missing 79%, we are looking for the elephant in the room.
Why this report is particularly valuable: Dr Curry runs a business. Its survival depends upon its providing accurate information. Dr Curry will suffer consequences for producing biased reports. This runs contrary to the academic climate industry, which gets paid for producing worst-case scenarios, regardless of its track record for making good predictions. Viva the free market.
Predicting Hurricanes & climate change.
Long term ie next year, Predictably unpredictable.
Medium term Semi predictable.
So much heat in the relevant area [equatorial] of the Atlantic Ocean for instance.
Modify by heat of neighboring parts of the Atlantic Ocean and Mexican Gulf.
Look at the trends. Total moisture and heat available for precipitation and for Hurricanes assessable equals a mild hope of deriving both numbers and strength, but not location.
Short term moderately unpredictable. The damage done to the surrounding wind streams is utterly chaotic and leads to severe meandering of the Hurricane track and marked variability in the strength.
–
Advice to your clients.
Plan for the worst, hope for the best and double reinforce structures in hurricane proof areas plus build hurricane proof bunkers if you cannot achieve the best strategy [drive inland 100 K when storm is 24 hours away].
For ex@mple
“Severe Tropical Cyclone Oma has made a sudden change in direction and is now bearing down on Brisbane and the Gold Coast.”
Another source that maybe helpful is Michael Chenoweth and Dmitry Divine. 2012. Tropical cyclones in the Lesser Antilles: descriptive statistics and
historical variability in cyclone energy, 1638–2009. Climatic Change, vol. 113, issue 3, pp. 583-598,
http://econpapers.repec.org/article/sprclimat/v_3a113_3ay_3a2012_3ai_3a3_3ap_3a583-598.htm. The authors find no trend in Lesser Antilles Cyclone Energy during the past 320 years. Reviewed in CO2Science.Org: http://co2science.org//articles/V15/N48/C3.php
Should note that there has been much subsidence in Houston over the past 100+ years, w/ some areas sinking 14 feet (probably more by now. Record rainfall? Barely in total for the 4 days, but don’t forget TS Claudette in 1979 – still holds the 24 hr total for the US at 43 in.
https://i.imgur.com/3LgfxXZ.png
Despite the non-science aspecst of global warming alarmism (e.g., the hand of man has been blamed on causing hurricanes and also for a reduction in hurricanes) I think the common wisdom is that heat drives hurricanes. At least no one seems to questions our understanding that they transfer millions of tons of hot air where trillions of watts of heat energy is radiated to empty space (said to be the equivalent of 400, 20 mega-ton hydrogen bombs).
When the globe is heating, from whatever cause, it’s logical to assume that there is this natural response that tends to reduce warming. If so, if humanity’s release of CO2 also is causing a reduction in hurricanes, that would exacerbate global warming and accordingly, reducing the release of CO2 would cause more hurricanes.
Conversely, if humanity’s release of CO2 does not increase hurricane activity, a reduction in hurricane activity must be because the planet is no longer warming.
Dr. Curry ==> If you use Maue’s Fig 3.1 it might be wise to remove the blue shading between the two traces, as it has no meaning and changes the visual interpretation of the graph. One sees the data as a wide bar of something. It is really just two traces — Total (All) hurricanes and Major Hurricanes.
The same is NOT true for the Fig 3.2 in which “The area in between [shaded] represents the Southern Hemisphere total ACE. “
A new paper on the subject
“Despite what seems to have been a cavalcade of extreme nor’easters that then became intense ocean storms punishing Western Europe in recent years, new research involving simple but long-term measurements of air pressure show that storminess in the NE Atlantic has actually returned to normal. An extension of the air pressure-storminess relationship to the latest available year (2016) confirms the calming, following two periods of enhanced storminess in the last 140 years. The finding reveals an oscillation in such heightened activity rather than an upward trend suspected to have been a result of global warming.”
“Northeast Atlantic Storm Activity and its Uncertainty from the late 19th to the 21st Century” by Oliver Krueger in Journal of Climate, in press.
https://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-18-0505.1
Abstract:
Geostrophic wind speeds calculated from mean sea level pressure readings are used to derive time series of northeast Atlantic storminess. The technique of geostrophic wind speed triangles provides relatively homogeneous long-term storm activity data and is thus suited for statistical analyses. This study makes use of historical air pressure data available from the International Surface Pressure Databank (ISPD) complemented with data from the Danish and Norwegian Meteorological Institutes.
For the first time the time series of northeast Atlantic storminess is extended until the most recent year available, i. e. 2016. A multi-decadal increasing trend in storm activity starting in the mid-1960s until the 1990s, whose high storminess levels are comparable to those found in the late 19th century, initiated debate whether this would already be a sign of climate change.
This study confirms that long-term storminess levels have returned to average values in recent years and that the multidecadal increase is part of an extended interdecadal oscillation. In addition, new storm activity uncertainty estimates were developed and novel insights into the connection with the North Atlantic Oscillation (NAO) are provided.
“Without thermal controls, the temperature of the orbiting Space Station’s Sun-facing side would soar to 250 degrees F (121 C), while thermometers on the dark side would plunge to minus 250 degrees F (-157 C). There might be a comfortable spot somewhere in the middle of the station,
but searching for it wouldn’t be much fun!”
https://science.nasa.gov/science-news/science-at-nasa/2001/ast21mar_1/
Guess what, space is not cold, it’s HOT!!
Like standing next to a campfire, hot on the fireside, cold on the back side and without the atmosphere’s 0.3 albedo earth gets hotter not colder.
Because the atmosphere and its associated albedo reflect away 30% of the incoming solar energy (like the reflective panel behind a car’s windshield) the earth is cooler with an atmosphere and not warmer per greenhouse theory.
Because of the significant (>60%) non-radiative heat transfer processes of the atmospheric molecules the surface of the earth cannot radiate as a black body and there is no “extra” energy for the greenhouse gasses to “trap”/absorb/radiate/“warm” the earth.
No greenhouse effect, no CO2 warming, no man caused climate change.
No problem.
Thanks Dr Curry, for such insightful information. I always looked forward to Dr William Grey’s (now Dr Klotzbach’s) hurricane predictions for decades. Living in the northeast and as a 13 year old standing in the eye of Hurricane Donna and then the subsequent return of hurricane force winds was an experience I will never forget. This is takes the analysis deeper and broader than I have read in a single document. Your work is stellar and much appreciated.
.
❶①❶①❶①❶①❶①❶①❶①❶①❶①❶①❶
❶①❶①
❶①❶① . . . Real Temperatures . . .
❶①❶①
❶①❶①❶①❶①❶①❶①❶①❶①❶①❶①❶
.
Are you interested in seeing real temperature data (NOT temperature anomalies)?
I am talking about actual absolute temperatures, like 21.2 degrees Celsius. Not an anomaly, like +1.0 degree Celsius.
I have got the average temperature, the hottest month (summer) temperature, and the coldest month (winter) temperature, for 216 countries.
I have combined the temperature data, with population data, to show how real temperatures vary, for all of the people who live on the Earth.
====================
For a graph showing temperature and population by country, see:
https://agree-to-disagree.com/temp-population-by-country
====================
For graphs showing detailed temperature data for 216 countries, see
https://agree-to-disagree.com/how-hot-is-that-country
typo Fig 3.6 a Global no scale x axis
Very nice post.
It made me curious to hurricans as a part of earth`s energy budget. The cooling effects of hurricans. I don`t know how much significance it have, but I see that NASA has some interest in it too.
“As these awesome and awful storms move across the ocean, they churn up the surface and leave swaths of cooler water in their wake. Sea surface temperatures can drop by as much as 5 degrees Celsius (9° Fahrenheit) within a day or two of a storm’s passing. In the process, vast amounts of heat and moisture are transferred from the ocean to the atmosphere. At the same time, some of that heat is also sinking into the sea, which might have implications for seasonal and long-term climate.”
“Scientists have known for some years that hurricanes and typhoons create cold wakes. As hurricane winds swirl over the ocean, they evaporate water (and with it, heat) into the atmosphere. They drive diverging currents that push warm water masses away from the storm center, leading cooler deep water to rise from the depths to replace it (upwelling). Then there is the cooling rain that falls back into the sea, and the lack of sunlight due to the thick cloud cover.”
“This surface cooling effect can span hundreds of kilometers across the ocean surface and typically reaches 150 to 200 meters (500 to 650 feet) down into the ocean, according to Isaac Ginis, an oceanographer at the University of Rhode Island (URI) who studies cold wakes. The more intense the cyclone, the deeper the stirring and mixing effects can be. Storms that move slowly also reach deeper. The most intense storms can mix water down to 400 meters (1300 feet).”
“Because all of that pre-cyclone surface heat has to go somewhere, it warms deeper layers of the ocean. This may have an effect on the thermohaline circulation, the great current system that moves heat and salt around the global ocean.”
https://earthobservatory.nasa.gov/images/144221/cyclone-effects-run-deep
Hi Judith. Your summary is very nice!
There’s a potential climate change in the Gulf of Mexico which might be of interest to your insurance-industry clients. I think it is happening but I have not examined historical data to see if my impression is real or imagined.
Historically, the GOM experiences a noticeable increase in wind shear by the first of October. The GOM also experiences modest intrusions of less-humid surface air thanks to early-season “cool” fronts. These are parts of the GOM seasonal transition from summer to fall.
The onset of GOM wind shear and drier air seems to happen later nowadays, perhaps mid-October. That extends the period of major-hurricane risk along the northern Gulf Coast by several weeks. October storms in the lower latitudes can be fierce but they tend to diminish due to wind shear as they exist the tropics. If they are not diminishing as much then their threat to the northern Gulf Coast threat grows.
A warming world might extend that seasonal transition even later, to say late October and early November. That would be significant to insurers.
I believe that there’ might also be a subtle storm steering impact. GOM storms might tend to have more of a westerly component to their track, due to the extended season, increasing their threat to Texas and western Louisiana. Those are “target-rich” regions for storm damage which are of interest to insurers.
Anyway, it’s all something to ponder over a cup of coffee. I think that there are GOM composite wind shear calculations maintained by the government and they’re available for some historical period. There are also October SST values and maybe even reanalysis data that might be useful to examining the issue.
interesting, thx. let me know if you do any additional analyses of this
Pingback: Weekly Climate and Energy News Roundup #349 | Watts Up With That?
Pingback: Weekly Climate and Energy News Roundup #349 |
Pingback: Unbewohnbare Erde: Ein Abraham a Sancta Clara d. Klimakatastrophe
Pingback: Tempest in a blog post | Climate Discussion Nexus
Pingback: Hurrikane und Klimawandel 1: Erkennung – EIKE – Europäisches Institut für Klima & Energie
Pingback: NYS Climate and Community Protection Act Rationale – Pragmatic Environmentalist of New York