by Judith Curry
In Part I, the Congressional testimony of John Christy and Francis Zwiers on extreme events was discussed. In this post, I focus in on issues related to floods. This topic was also discussed in a previous post on Attribution of Extreme Events Part II.
Both Francis Zwiers and John Christy discussed the two recent papers appearing in Nature, by Pall et al. and Min et al. The relevant text from their testimony is excerpted below:
Francis Zwiers’ testimony
While the research required to answer this question specifically in the context of recent events is yet to be completed, two new papers in Nature (Min et al., 2011; Pall et al., 2011) have presented evidence that changes in the intensity of extreme precipitation since the middle of the 20th century may be linked to human induced global warming, and that in at least in one instance, that human influence on climate had likely substantially increased the risk of flooding.
Further, a warmer atmosphere can, and does, hold more water vapour, which has been detected in data (Santer et al., 2007; Willett et al., 2007; Arndt et al., 2010), and which implies that more moisture is available to form precipitation in extreme events and to provide additional energy to further intensify such eventsv. Many of these expected changes have been observed, and in some instances, are beginning to be linked to human induced warming of the climate system.
Heavy and extreme precipitation events have also received a considerable amount of study. Heavy precipitation has contributed an increasing fraction of total precipitation over the regions for which good instrumental records are available (Groisman et al., 2005; Alexander et al, 2006), and particularly over the US (Karl and Knight, 1998; Kunkel et al., 2007; Peterson et al., 2008; Gleason et al., 2008), indicating an intensification of precipitation extremes. Direct examination of precipitation extremes, such as the largest annual 1-day accumulation, or the largest annual 5-day accumulation, also shows that extreme precipitation has been intensifying over most parts of the world for which suitable records are available (Alexander et al., 2006; Min et al., 2011, Figures 3, 4), with an increase in the likelihood of a typical 2-year event of about 7 percent over the 49 year period from 1951 to 1999.
Climate scientists have long argued that an intensification of extreme precipitation is an expected consequence of human influence on the climate system (e.g., see Allen and Ingram, 2002; Trenberth et al., 2003). Indeed, models do intensify extreme precipitation in response to increasing greenhouse gas concentrations and Min et al. (2011) recently showed, using an ensemble of models, that the observed large-scale increase in heavy precipitation cannot be explained by climate variability, and is most likely due to human influence on climate. However, as with extreme temperature events, place and event based research is required to determine whether increasing greenhouse gas concentrations have altered the odds of a given type of event. Pall et al. (2011) demonstrate a suitable approach, and show that human influence from increased greenhouse gas contributions had substantially increased the odds of flooding in England and Wales in the autumn of year 2000 as compared to the world that would have been if greenhouse gas concentrations had remained at pre- industrial levels (Figure 5).
John Christy’s testimony
Svensson et al. 2006 discuss the possibility of detecting trends in river floods, noting that much of the findings relate to “changes in atmospheric circulation patterns” such as the North Atlantic Oscillation (i.e. natural, unforced variability) which affects England. For the Thames River, there has been no trend in floods since records began in 1880 (their Fig. 5), though multi-decadal variability indicates a lull in flooding events from 1965 to 1990. The authors caution that analyzing flooding events that start during this lull will create a false positive trend with respect to the full climate record.
Flooding events on the Thames since 1990 are similar to, but generally slightly less than those experienced prior to 1940. One wonders that if there are no long-term increases in flood events in England, how could a single event (Fall 2000) be pinned on human causation as in Pall et al. 2011, while previous, similar events obviously could not? Indeed, on a remarkable point of fact, Pall et al. 2011 did not even examine the actual history of flood data in England to understand where the 2000 event might have fit. As best I can tell, this study compared models with models. Indeed, studies that use climate models to make claims about precipitation events might benefit from the study by Stephens et al. 2010 whose title sums up the issue, “The dreary state of precipitation in global models.”
In mainland Europe as well, there is a similar lack of increased flooding (Barredo 2009). Looking at a large, global sample, Svensson et al. found the following.
A recent study of trends in long time series of annual maximum river flows at 195 gauging stations worldwide suggests that the majority of these flow records (70%) do not exhibit any statistically significant trends. Trends in the remaining records are almost evenly split between having a positive and a negative direction.
The dreary state of precipitation in global models
Christy references a paper by Stephens et al. (2010) (see also Pielke Sr.), which is unfortunately behind paywall.
Stephens, G. L., T. L’Ecuyer, R. Forbes, A. Gettlemen, J.‐C. Golaz, A. Bodas‐Salcedo, K. Suzuki, P. Gabriel, and J. Haynes (2010), Dreary state of precipitation in global models, J. Geophys. Res., 115, D24211, doi:10.1029/2010JD014532.
“New, definitive measures of precipitation frequency provided by CloudSat are used to assess the realism of global model precipitation. The character of liquid precipitation (defined as a combination of accumulation, frequency, and intensity) over the global oceans is significantly different from the character of liquid precipitation produced by global weather and climate models. Five different models are used in this comparison representing state‐of‐the‐art weather prediction models, state‐of‐the‐art climate models, and the emerging high‐resolution global cloud “resolving” models. The differences between observed and modeled precipitation are larger than can be explained by observational retrieval errors or by the inherent sampling differences between observations and models. We show that the time integrated accumulations of precipitation produced by models closely match observations when globally composited. However, these models produce precipitation approximately twice as often as that observed and make rainfall far too lightly. This finding reinforces similar findings from other studies based on surface accumulated rainfall measurements. The implications of this dreary state of model depiction of the real world are discussed.”
So the issue is this. Even if we assume the following:
- Sea surface temperatures are warming
- More evaporation occurs from warmer sea surface temperatures (provided that surface wind speeds don’t decrease)
- warmer atmosphere can accommodate more water vapor
- Given the constraints of the Clausius- Clapeyron equation, more water vapor in the atmosphere implies more global precipitation
Stephens et al. implies that these premises does not necessarily imply an increase in the intensity or frequency of floods, nor does it necessarily “load the dice” in favor of such events. Floods depend critically on the spatiotemporal distribution of rainfall, which the climate models simulate poorly. If the hypothesized increase in global rainfall is associated with a larger number of weak rainfall events, or a more even seasonal distribution of rainfall, then we wouldn’t necessarily expect to see more frequent floods.
So even if you accept the above 5 premises, which scenario is more likely: the scenario with an increase in floods, or a scenario with no increase in floods? Well, as per Stephens et al., climate models simply don’t provide any useful information on the subject of localized heavy precipitation events. Climate models may have more potential utility in providing statistics on drought, which are tied to larger scale circulation regimes, are regional in scope and have longer duration (e.g. seasonal or longer).
Learning from modeling floods on weather time scales
The challenge of modeling floods is illustrated in this paper by Hopson and Webster. Even using what is arguably the best weather forecast model in the world (ECMWF), there are substantial biases in the rainfall distributions (see their Fig 3 and associated discussion), which can be adjusted. The model has skill in predicting floods for rivers where there is a large catchment area (this particular application is for the Ganges and Brahmaputra Rivers.)
In terms of attribution studies or future projections, it seems that there might potentially be some skill in terms of slow rise floods in Asian monsoon region for the rivers with large catchment areas, provided that the climate models can capture the Asian monsoon rainfall and the statistics of the intraseasonal oscillation.
Floods are notoriously difficult to predict, particularly flash floods. Coarse resolution global climate models do a “dreary” job of simulating the local distribution of rainfall events. Apart from the actual physics of precipitation and the complex interactions between the cloud microphysics and small scale turbulent and convective dynamics, getting the regional distribution of rainfall events depends on accurate simulation of the statistics of weather events, ENSO, blocking patterns, etc. Coarse resolution climate models do not do a particularly good job in simulating the dynamics that are relevant for formation of extreme precipitation events.
The argument might be made that if there are biases in the climate model precipitation, you could still discern a change in the extreme events, either with time or in attribution experiments (e.g. with natural forcing only, and natural plus anthropogenic forcing). However, there is no reason at all to think that the bias statistics would remain constant for these different climate states. Hence, I conclude that climate models have nothing to say on the attribution or prediction of floods, with the potential exception of a few regions such as the Asian monsoon where the floods are driven by relatively predictable rains over large catchment basins.
Further, prediction of actual river flooding depends on more than a rainfall simulation; it also requires a river routing model. Flash floods are unpredictable on timescales more than a day or two, and are not simulated at all in coarse resolution climate models. Hence I personally have no confidence in the studies of Pall et al. and Min et al. in terms of being able to draw any conclusions about the attribution of floods.
It is possible that the higher resolution time slice experiments conducted for CMIP5 may produce better regional distributions of precipitation events, but that remains to be demonstrated. On the broader subject of extreme events, droughts in principle should be much more predictable by coarse resolution climate models.
In summary, I agree with Christy’s statement that “extreme events are poor metrics for global change.”
Moderation note: this is a technical thread that will be moderated for relevance.
Part of the difficulty in estimating total and extreme precipitation events is likely to involve the extent and duration of warming. A warmed atmosphere will hold more water vapor according to the Clausius-Clapeyron relationship (and confirmed by observations), but the residence time of water vapor also increases, so that an increase in precipitation at any stage is less than estimated from the rate of evaporation. It is also less than the corresponding increase in drought-afflicted areas. Indeed, at the initial stages of a small warming, precipitation may actually decline before beginning to rise –
Global Mean Precipitation Response To Warming
With a greater and more persistent temperature rise, the increase in precipitation is likely to dominate, and with further increases, the distribution of precipitation intensity might be expected to portend an increase in extreme events and/or an increase in total precipitation amounts in regions where river runoff can no longer accommodate the additional precipitation without flooding. The level of warming at which such a critical juncture will be reached is conjectural. It is reasonable to assume that it has not been reached yet in most regions.
The paper you cited states:
IOW precipitation DOES increase with warmer temperature (as Zwiers has argued in his testimony), but only at around one-third of the rate as would be anticipated following a constant RH according to Clausius-Clapeyron.
I suppose this also means that water vapor (the first intermediate step to “more precipitation”) increases with warmer temperature, but also at a much lower rate than would be anticipated following a constant RH according to Clausius-Clapeyron (as Minschwaner and Dessler also observed).
Would this imply that the IPCC model simulations on water vapor feedback are exaggerated?
No it doesn’t, Max. Rather, it reflects the longer atmospheric residence time of water vapor, which is a complex function of altitude, latitude, and boundary layer conditions. As I mentioned below, the observational data indicate that increases in atmospheric humidity have kept pace, or nearly so, with increases in temperature.
Check Minschwaner + Dessler (2004). Observations over the tropics showed that RH did NOT remain constant with warming, but decreased. IPCC model estimates were shown to be too high based on actual observations.
Then there are the NOAA radiosonde data on tropospheric humidity that go back to 1948; these also do not show a lock-step increase in WV with warming following Clausius-Clapeyron.
The real world doesn’t always react the way it should, Fred.
And you can’t always just “blame the thermometers”.
I responded below to Etudiant.
Also see Dessler and Davis 2010 relevant to the fairly constant tropospheric relative humidity (again, relevant to Etudiant’s comment and my response below).
The discussion is on specific humidity rather then relative humidity. The usual over confident nonsense from Fred.
See http://www.climate4you.com/GreenhouseGasses.htm for (NOAA derived) graphs of RH and SH since 1948, at surface, 3km and 9km alt.
Quote from Climate4You:
“Most climate models assume that as an increasing amount of atmospheric CO2 induces slightly increasing atmospheric temperatures, the overall evaporation will increase from the planet surface, and thereby the specific humidity of the lower part of the atmosphere (the Troposphere) will increase as well. As water vapour is the most important greenhouse gas, additional warming will come about, resulting in a much larger temperature increase than that induced from CO2 alone. Climate models therefore, in general, assume the relative Tropospheric humidity to remain more or less stable, as increasing air temperatures are compensated by increasing specific humidity.
“The above diagrams indicate that none of this has been the case since 1948. Only near the planet surface, the relative humidity has remained roughly constant (although with variations), but in the remaining part of the Troposphere below the Tropopause the relative humidity has been decreasing. Even for the specific humidity, this appears to be the case. “
The specific humidity has increased at all levels, and RH has remained constant at most. Whether RH has been constant or has declined in the upper troposphere (while specific humidity increased) is still uncertain, as discussed below in several exchanges. There is evidence for both. Please see the discussions downthread for details and the relevant references.
Fred, I wish that paper wasn’t behind a pay wall. I would like to see the modeled estimates per latitude. I agree that more moisture does not mean more precipitation. The models should show very little initial change in the tropics gradually increasing with latitude, whatever the direction of the precipitation change may be.
Fred, thanks much for the link to this paper.
In summary, I agree with Christy’s statement that “extreme events are poor metrics for global change.”
Just inconvenient if they’re extreme right by your house.
Francis Zwiers made the statement in his testimony:
This sounds like a double-edged sword to me.
“More moisture yields more rain” implies:
More moisture produces more water droplet clouds, which yield more rain.
More water droplet clouds increase the albedo of Earth, thereby reflecting more incoming SW radiation back to space and cooling our planet (negative cloud feedback).
It seems to me you can’t have more precipitation without having more water droplet clouds. And you can’t have more water droplet clouds without increasing the planet’s albedo. And you can’t increase the planet’s albedo without reflecting more incoming SW radiation, thereby leading to cooling (Willis Eschenbach’s “natural thermostat”).
Has Zwiers bought into this hypothesis?
Am I missing something here?
Any interpretation trying to contrive a low climate sensitivity based on clouds bumps up against the fact that clouds didn’t act that way in the past. How did we warm enough to get out of glacial maximum if clouds dampen warming? Milankovich forcings are an order of magnitude smaller than the forcing from our increases in greenhouse gases. Clouds don’t decide to act one way when nobody’s looking and then the opposite way because carbon-addicts don’t want to deal with the results of their addictions.
Maybe, Jeff, but, there are equilibrium seeking mechanisms. So, depending upon other occurrences perhaps there are things that change characteristics depending upon the circumstances.
BTW, I’d like to congratulate you on using an oft sited example skeptics use. “How did we warm enough to get out of glacial maximum….”? Indeed. How and why?
“How did we warm enough to get out of glacial maximum…?”
I asked Gavin Schimdt that question when he was answering all comers on Collide-a-Scape last August. I asked him about an article at RealClimate that said there was an “unknown cause” of the warming of the Antarctic and surrounding oceans that ended glacier periods. His answer was:
“…we don’t know exactly how the changes in orbital forcing get translated into temperature and climate change and we are also not absolutely sure how those climate changes affect the carbon cycle (land and ocean). So there are ‘unknown’ processes at play.”
So it is supposed to be orbital forcing, although we don’t know how. (What I love most about climate science is that it is so precise.)
The latter article Gavin referred me to said: “What is being talked about here is influence of the seasonal radiative forcing change from the earth’s wobble around the sun (the well established Milankovitch theory of ice ages), combined with the positive feedback of ice sheet albedo (less ice = less reflection of sunlight = warmer temperatures) and greenhouse gas concentrations (higher temperatures lead to more CO2 leads to warmer temperatures).”
Apart from whether we really know yet how glacier periods end, taking Gavin’s statements at face value, he still did not change the original article’s admission that inter-glacial warming preceded the rise in CO2 by 800 years, plus or minus a couple hundred years.
Whatever causes inter-glacial warming, it apparently ain’t CO2 (at least for the first 800 or so years). So if a such process, known or unknown, can warm the planet enough to end a glacial period without help from green house gases, wouldn’t it be fair to infer that such a process could also overcome a negative feedback from clouds?
There’s a reason I like to rely on RealClimate to see what the consensus position is on various issues, particularly their older articles. They may fudge and engage in hyperbole (particularly in the comments), but when they cite a paper in support of their proposition, it usually says what they says it does. Unlike the even more political blogs.
This is a quote from the SkepticalScience blog you cited:
“For example, around 18,000 years ago, there was an increase in the amount of sunlight hitting the Southern Hemisphere during the southern spring. This lead to retreating Antarctic sea ice and melting glaciers in the Southern Hemisphere. (Shemesh 2002).”
Notice how direct and certain the argument of causation.
Here is a quote from the abstract of the paper cited:
“Sea ice is the first variable to change during the last deglaciation, followed by nutrient proxies and sea surface temperature.
Assuming a constant sedimentation rate for this interval, our data suggest that sea ice and nutrient changes at about 19 ka B.P. lead the increase in atmospheric pCO2 by approximately 2000 years.”
I don’t have access to the full article, but according to the abstract, it is about an examination of core records to determine the “sequence of events” in an interglacial (hence the paper’s title), not the causation of those events. The article at best speculates about the cause of this sequencing, with nary a word about Milankovitch cycles or the cause of inter-glacial warming, nor any of the certainty in the blog post you cited:
“If gas exchange played a major role in determining glacial to interglacial CO2 variations, then a delay mechanism of a few thousand years is needed to explain the observed sequence of events. Otherwise, the main cause of atmospheric pCO2 change must be sought elsewhere, rather than in the Southern Ocean.”
SkepticalScience purports to state as fact the mechanism by which glacial periods are ended, but the paper cited is not relevant to that point. I’ll take Schmidt’s admission of ignorance on that particular point, than you very much.
Should be “thanK you very much”
Yes, obviously, we’ve mechanisms at play which we don’t understand, and also obvious, our models are woefully inadequate. The positive forcings of clouds, in my mind don’t stand to reason and, neither do the negative forcings of snow and ice. Any one that’s ever done some cold weather training up in the arctic knows snow can act as an insulator. In other words, it is retaining heat that would otherwise escape were it not for the coverage. The clouds, while I understand visible and near visible are two different things, if the white of snow and ice reflect, so too would clouds. In fact, clouds would reflect sooner, not even allowing the energy down to the earth. Beyond that though, I’d have no idea on how to do a quantitative analysis of gain vs. loss because of the latency and the energy may not always be realized by the surface temps, or the surface temps may capture released energy and it could be assumed as gained energy.
Every answer brings more questions.
“We can only explain what happened if we assume that…” is an “argument from ignorance”, for it implies that we know all there is to know.
This assumption is particularly weak when it comes to interpreting paelo-climate data, which itself are fraught with great uncertainties.
I’d prefer to see arguments based on actual physical observations from today.
Spencer has reported such observations on clouds over the tropics, which have not yet been scientifically refuted or invalidated. These show that net cloud feedback with warming is likely to be strongly negative, rather than strongly positive, as previously stimated by all the IPCC model simulations (admittedly with the concession that “cloud feedbacks remain the largest source of uncertainty”).
For sure, more work needs to be done, but right now it looks like the net feedback from clouds is very likely to be negative rather than positive.
Feedback has been discussed extensively elsewhere, and is not on-topic for this thread, so I don’t want to get diverted into repeating some of the earlier points. Spencer/Braswell can be shown almost certainly to be wrong for reasons I’ve mentioned previously. If cloud feedback becomes a central issue in a future thread, I will revisit the issue.
You need to be more specific rather than simply saying: “Spencer/Braswell can be shown almost certainly to be wrong for reasons I’ve mentioned previously”.
That’s simply a cop-out, Fred. “Almost certainly” means nothing, as you know.
But I agree we should continue this discussion on a thread specifically devoted to water vapor and clouds, rather than here.
I would be more specific now if (a) it were on-topic, and (b) I hadn’t discussed it extensively before. I will refrain from repeating myself in a thread devoted to precipitation and flooding rather than cloud feedback. However, if you Google the subject, you will find discussion of the issue. If you want to email me (see the denizens thread), I can also respond there, but I don’t wish to divert this thread from its intended topic. I’m afraid you’ll have to be satisfied with that answer.
The only way my children could explain presents under the tree on December 25 was Santa Clause. Ergo, Santa Claus exists.
(Next up – the Easter Bunny.)
Just a guess, but wouldn’t the energy required to change the state of vast volumes of ice to water have a negative effect on air temperatures, thus reducing the rate evaporation and so of could formation?
My gut feeling is that post glacial conditions would be cool air temperatures, clear, sunny skies and lots of water.
That was supposed to be Cloud formation. DOH.
That makes sense to me Peter. I’d have to agree with you until somebody can show otherwise.
Jeffrey Davis 3/9/11 4:12 pm on Extreme Testimony. Part II:Floods
You say, Milankovich forcings are an order of magnitude smaller than the forcing than the forcing from our increases in greenhouse gases.
The gaping hole in Milankovic’s theory is that it predicts that ice ages should follow the precessional cycle. In particular, the Northern Hemisphere and Southern Hemisphere should have ice ages in alternation every 10,000 years, with the severity of the ice ages modulated by the eccentricity cycle. This is not at all what is observed. …
The problem is not that the amplitude of radiative forcing associated with Milankovic cycles is small: it amounts to an enormous 100W/m^2, with the amplitude determined by the eccentricity cycle. The problem is that the forcing occurs on the fast precessional time scale, whereas the climate response is predominately on a much slower 100,000 year time scale. Bold added, Pierrehumbert, R.T., “Principles of Planetary Climate”, 11/19/08, ¶7.5.1, p. 353.
The problem according to this authority is not the magnitude of the Milankovitch forcings, but its phase and frequency.
Also, the Milankovitch forcing is not so enormous compared to the total greenhouse effect, which is dominated by water vapor. MODTRAN shows that from minimum to maximum CO2 the forcing is about 80 W/m^2, and published estimates for water vapor are greater by a factor of 3 or 4 in the modern atmosphere. The greenhouse effect appears to run around 300 to 400 W/m^2 from the coldest, bone dry, ice age state to the soggy present. Regardless of the relative magnitude, the problem remains with the phase and frequency.
When you say, our increases in greenhouse gases, are you, too, invoking the human cause assumption? Human contributions cause warming according to the best physics, but the amount is too small to be measured. The trick is to use models adjusted to show enough manmade warming to cause panic, but not so large as to be invalidated before Congress yields. Part of the trick is not bothering to have the models account for the glacial minima, leaving them at the level of a scientific conjecture.
The race is on. The on-going cooling trend is invalidating the conjecture while the political mood is awakening to become more demanding. AGW supporters seem to be raising the ante by de-emphasizing warming in favor of climate extremes.
The yearly change in radiance between 305 w/m-2 per and 340w/m-2 is spread over the tens of thousands of years span of the cycle.
Total energy over that time would be, as pointed out, enormous. My reference was to the year-to-year difference.
I haven’t read the chapter you quote, but it looks like pierrehumbert is pointing to the fact that the usefulness of the increase in insolation appears tied to other facts than to a specific increase in the amount of energy.
“When you say, our increases in greenhouse gases, are you, too, invoking the human cause assumption?”
“Don’t put me on, Mr. Nkrumah.”
Jeffrey Davis 3/9/11 4:12 pm; 3/10/11 12:52 pm on Extreme Testimony. Part II:Floods; 3/9/11
You might have noticed that I misquoted you. Apologies. Gremlins typed an extra than the forcing in my citation.
You missed the point about the Milankovitch cycles. Whether you want to deal in W/m^2 or W/m^2/yr, you framed the issue with, How did we warm enough to get out of glacial maximum if clouds dampen warming? When a Believer thinks warming will counter a maximum, any good denialist worth his Sun screen will know immediately the Believer means a minimum. Right?
1. You combined a couple of different ideas when you wrote, it looks like pierrehumbert is pointing to the fact that the usefulness of the increase in insolation appears tied to other facts than to a specific increase in the amount of energy. You are assuming that Earth came out of the glacial minima because of an increase in insolation, which is a best guess when attributed to the Sun. Pierrehumbert’s point was that the recovery can’t be attributed to Milankovitch cycles. The reason is not that the Milankovitch effect is weak, as you suggested. To the contrary, his point is that it is strong BUT out of sync with Earth’s climate variations.
2. When the climate is at a minimum, the atmosphere is bone dry, the clouds and the greenhouse effect are nil.
3. In the current warm state, IPCC is uncertain of the sign of the cloud effects. If IPCC included dynamic cloud albedo, it would have no doubt left. Clouds mitigate warming from all effects. It is the strongest feedback in all climate, and it is negative with regard to surface temperature (and positive with respect to the Sun).
Believers note: IPCC writes at length about cloud albedo or the cloud albedo effect. What it means is the specific cloud reflectivity in units of reciprocal square meter. It doesn’t know the sign of specific cloud reflectivity minus cloud greenhouse effect. For total albedo, a dimensionless number, e.g., 0.3, it needs to multiply the specific cloud reflectivity by what it calls various cloud cover, cloud amount, cloudiness, and more, in square meters, a temperature sensitive parameter. It’s models apparently use a fixed parameterized cloud cover at each location, so the models lose the dynamic cloud albedo effect.
You say, Any interpretation trying to contrive a low climate sensitivity based on clouds bumps up against the fact that clouds didn’t act that way in the past. IPCC’s warm state climate sensitivity, nominally 3ºC, is way too high by a factor somewhere between 2.5 (ERBE data, Lindzen analysis) and 10 (for undetectable change in Bond albedo) because its GCMs misrepresent total cloud albedo. Bump! Surface warms, humidity increases, cloud cover increases, albedo increases, insolation at the surface decreases, warming is mitigated. Clouds always work that way, thanks in part to Clausius-Clapeyron. It’s just that in the past in Earth’s glacial minima clouds were negligible because they largely didn’t exist.
Albedo locks Earth into its glacial minimum states, too, but then it’s surface albedo.
Kwame, caught in a put-on, said hold the watermelon. Now he says hold the AGW. He’s not going to be fooled into dining off the Believers’ menu.
Max – You are in fact missing something. The increase in water vapor occurs in an atmosphere that is warmer and therefore capable of holding more water vapor without condensation, due to the Clausius-Clapeyron relationship. What would be expected under those conditions is that relative humidity (RH) would remain fairly constant, and that has been observed, even though total water vapor has increased. There is still disagreement as to whether high troposphere humidity has increased sufficiently to maintain the same RH or has not quite kept pace, but there is no evidence to suggest a global increase in RH that would lead to increased cloudiness. Recent HIRS, ISCCP, and other data suggest a slight overall decline in low cloud cover, and, although somewhat uncertain, a slight increase in high cirrus clouds. Both of these change would tend to shift cloud behavior away from a cooling influence dominated by low clouds, and toward a warming influence mediated by the high clouds.
To elaborate a bit on the forgoing, a warmer climate increases evaporation and precipitation, thereby accelerating the hydrologic cycle. This does not require the atmosphere to contain more clouds at any given moment, since the ability of clouds to produce rain is replenished by the increased evaporation even if the clouds have not increased in total extent.
In which case this:
isn’t quite accurate. It isn’t the inventory of water in the air that matters in the long run, it’s the rate of evaporation, no?
Sort of like: what goes up has to come down, or even more basically, what comes down had to go up (regardless of what the models might say).
Thanks for reply, Fred. but this does not change the very basic fact that more water vapor (due to more warming) has to result in more water droplet clouds before it can result in more precipitation. That’s the process.
The two salient points here are:
a) more precipitation requires greater water droplet cloud extent, which will result in more albedo and more reflection of incoming SW radiation, thereby to cooling
b) if observations show that precipitation increases at only 1/3 the rate one would expect from a constant RH following Clausius-Clapeyron, then it is logical to assume that WV (and clouds) will also increase at a rate lower than what would be expected from following C-C in lock-step. [And besides, this is what Minschwaner and Dessler found in their satellite observations over the tropics.]
but this does not change the very basic fact that more water vapor (due to more warming) has to result in more water droplet clouds before it can result in more precipitation.
Not necessarily. It does require that the rates at which clouds form, water droplets within them coalesce to form raindrops, and the clouds dissipate increase. It does not require that at any given time, more clouds exist. In other words, increased precipitation and reduced cloud cover can coexist if the cycle accelerates and cloud lifetime diminishes. This can’t be predicted from back of the envelope calculations but is supported by observations.
It would be fascinating to see that someone has actually argued, in a peer reviewed publication, that while global warming will necessarily increase water vapor, which will increase severe precipitation events, which will increase flooding, this all will be done without an increase in clouds.
Is there such a paper? Or are we just… (insert quote from Blazing Saddles here)?
I’m just sitting back and observing the anthropology here. Interesting.
Gary – I don’t know whether all these phenomena have been combined into a single paper – they may have been – but the models that look at humidity, clouds, and precipitation as a function of temperature increases induced by greenhouse gases produce these results. The test then is how the observational data support the same conclusions. To date, the projected increases in humidity and reductions in cloud cover have been verified, but it is too soon to be sure about changes in precipitation rates despite some suggestive evidence cited by Zwiers.
I was curious about your statement that: “To date, the projected increases in humidity and reductions in cloud cover have been verified….” Not being a climate scientist, I Googled it and came up with this.
It looks like the page was generated in 2006, but it claims that the changes in cloud cover til then to have been from 1-3% ( an increase of 2% followed by a decrease of 4%, net 2% negative). It includes this interesting comment:
“Since there a number of events occurring during this time period, the cause of these cloud variations is not yet understood.
Such variations are referred to as “natural” variability, that is the climate varies naturally for reasons that are not fully understood. The problem for understanding climate changes that might be produced by human activities is that the predicted changes are similar in magnitude to those shown here. The difference between natural and human-induced climate change will only appear clearly in much longer ( >= 50 years) data records.”
I wonder if NASA would like to revise and extend its remarks about needing “>=50 year” of data records to tell the difference between natural variability and human-induced climate change?
Gary – I agree that it’s hazardous to infer causality from the cloud data, because the observed trends are consistent with either anthropogenic or natural influences. However, the observations, which appear to show that total cloud cover has changed little, but that the distribution has shifted away from low (cooling) clouds toward high (warming) clouds does tend to support a positive cloud feedback and to contradict a strong negative cloud feedback. The HIRS data on High Cirrus Clouds are informative.
Good morning Fred,
You are better informed than me but I will nonetheless risk being technically embarrassed by stating that I disagree that the data suggests little or no change in cloud cover. Please see the various charts at the nasa website
If you look at albedo, it shows a gradual decline until around 2000 followed by an increase up to present day. This change in albedo seems to be confirmed by changes to SW radiation. Upwelling (ie reflected) SW radiation at TOA follows a similar pattern to albedo whilst the global SW radiation received at the surface (downwelling) seems constant until 2000 when it started to decline quite markedly.
The reason for the change in albedo could be dabated, but it seems to me most likely that it is due to changes in cloud cover which decreased during the 1976 to 1998 warming period and has increased since. The climate shift discussed by Tsonis et al seems the likely cause although the Chief Hrydrologist would probably have it down to changes in the PDO.
Whatever the reasons, it seems to me that the data does suggest changes in cloud cover with some possible cooling in the pipeline if the Chief is correct.
Rob – There have been minor variations but little in the way of a trend for overall cloud cover. However, if you look at the HIRS data in the link I cited above, I think you will see that the total fails to disclose that there has been an increase in high (warming) cirrus clouds. This has been accompanied by a reduction in low (cooling) cloud cover, consistent with a net warming effect from cloud changes –
Max – Typically, a storm draws moist air into itself from an area much larger than that over which it is raining. So water vapor from a large area cycles through the active (raining) part of the storm without necessarily contributing to cloud extent.
As water vapor condenses within the storm to form drops, it releases latent heat, which further drives the convective motions that are ultimately responsible for drawing in more moist air. This is an amplifying effect which further intensifies the storm. This (oversimplified) picture illustrates the valid expectation that storm intensities increase in a warmer (wetter) atmosphere, without necessarily an increase in storm frequency or active extent.
It should be kept in mind that water supplied to the atmosphere comes from evaporation, mainly over the oceans, and mainly controlled by surface temperature and winds; water removed from the atmosphere (rain and snow) is controlled mainly by condensation and droplet growth wherever warm moist air is cooled down, or meets colder air. So, although evaporation and precipitation must balance in the long term, the processes that control each are not closely related, and large local variations are to be expected (and are, of course, are observed).
Thanks for comment. I think I understand. This is the “heat pump” that Willis Eschenbach refers to, I believe. But I still have a hard time accepting that more WV and more precipitation does not mean more water droplets, i.e. clouds, as part of the process.
And I also have a hard time understanding if precipitation only rises at 1/3 the rate expected by following Clausius-Clapeyron in lock-step, that WV formation (and cloud droplet formation) should not also occur at a rate lower that theoretical based on C-C.
I keep reading that “a warmer climate increases evaporation and precipitation, thereby accelerating the hydrologic cycle.” but I never see it quantified.
How much extra warming and how much extra evaporation?
Warming isn’t uniform across the globe. What happens to total evaporation if a region in a particular lattitude warms by say 1DegC whilst a region in another lattitude cools by 0.5DegC? (giving us a warming of 0.5DegC)
Unless these are quantified somehow, this is just a reasonable sounding conjecture, possibly good in a lab but not necessarily so in the real world.
Also, it is possible that Total Sunshine Hours (TSH) has a greater influence on evaporation than temperature. This then would render cloud cover as a very important factor in the hydrological cycle.
To put it mildly…we don’t know, we’re making educated guesses.
“To put it mildly…we don’t know, we’re making educated guesses.”
It’s all speculation at this point. Lots of discussion about what we think we may know about what we don’t know…
Precipitation is terrible to give any meaning to any trends. Unlike temperature, which varies little over a wide range on any given day, precipitation is completely different. All we are doing is measuring precipitation at the station only.
For example, there is a station at London, Ont. airport maintained by Environment Canada. It’s on the very east side of the city. My place is on the west end outside of the city. Yet this summer, as in many times, black clouds would miss me and dump on London. Many cases, rain dropped in areas around us, but not at the airport. Rain is highly localized. It dumps on one area, yet, a stone throws away, they get nothing.
In the winter, it’s even more bizzar. We often get hit with a stringer of snow, 2 feet in 24 hours, while the city get’s nothing, and visa versa. It all depends on the winds off Lake Huron.
So, how does one get an accurate measure of precipitation? Without a station every kilometer, that’s close to an impossible task. Hence rainfall numbers mean nothing about any trending.
The only problem with this whole discussion is that the data shows a noticeable (about 15%) decrease in total column water vapor since 1983, with the decline in the upper atmosphere from 680mb on down.
See Greenhouse gases section here: http://www.climate4you.com/
taken from here: http://isccp.giss.nasa.gov/index.html
So how does that relate to extreme weather or to global warming?
Those data are known to be wrong. They are derived from the NCEP/NCAR reanalysis, which was subsequently been determined to have been subjected to a spurious trend due to downward jumps in recorded humidity as the sensors were changed to respond more rapidly, and thus eliminate excess water recordings due to lagged responses. All of the other four reanalyses show increases in water vapor with a relative constancy of RH. These incorporated satellite data, which is more accurate, and includes brightness temperature measurements confirming the humidity increase. The NCEP/NCAR depended exclusively on radiosonde data subject to the instrumentation distortions mentioned above.
OK, Fred. So it’s “blame the thermometers”, right?
What about Minschwaner & Dessler. Did they also have faulty thermometers?
The reference I cited drew its conclusions based on the accuracy of the modern, satellite-based “thermometers” (humidity measurements), which it took to be correct rather than blameworthy.
Max, the issue of whether tropospheric humidity at all altitudes has been increasing is settled – it has been – but the question as to whether RH humidity in the upper troposphere has remained constant or has not quite kept pace remains unsettled, mainly due to the difficulty of getting measurements that can resolve that level of uncertainty. It is certainly possible that RH has declined somewhat. If so, it has not declined enough to keep specific humidity constant. This remains an area where more precise measurements are needed.
Along the same lines, I haven’t seen any decisive answer to whether upper tropospheric RH has remained constant with warming or declined slightly because humidity increases have not kept pace with temperature increases, the following article by Soden et al 2005 reports evidence for constancy based on satellite-derived radiance measurements. It’s behind a paywall, but they conclude from the HIRS data that “This confirms that both the observations and GCM simulations are, to first order, consistent with a constant relative humidity”.
If anything since 2005 is more definitive, I haven’t seen it.
Sorry for the mangled syntax and the repetitive nature of the first part – it was due to a cut and paste job from a Microsoft Word paragraph I wrote.
FYI, I got behind the paywall for the Soden et al. paper. It confirms constant RH, but it’s basically model stuff with no new observations.
I think physical observations (such as those made by Minschwaner and Dessler) are probably more relevant. They show a reduction in RH with warming.
The much-maligned long-term NOAA radiosonde record shows pretty much the same. It may not be “perfect”, but then neither are a lot of the measurements used in climate science (viz. the SST record).
But, hey, I think we have beaten this dog to death. I have concluded that the physical evidence (as limited as it may be) tells us that the tropospheric RH decreases with warming rather than remaining constant in lock-step with Clausius-Clapeyron, as assumed by the IPCC model simulations.
And you have not shown me any data to convince me otherwise.
Max – See my above link to Soden et al (2005), which cites evidence for a constant upper troposphere humidity based on HIRS radiance data obtained later than the Dessler data. The Dessler reference calculates a lesser increase, (i.e., a decline in RH), and cites references concluding an actual increase in upper troposphere RH. The issue remains unresolved, although all sources conclude that specific humidity increases.
This actually has little relevance to precipitation, because the latter is almost entirely a phenomenon dependent on the far higher absolute water vapor content at lower altitudes. There, the constancy of RH has been well documented.
Since you did not address Minschwaner + Dessler, let me do so. IPCC AR4 Ch. 3 simply stated:
How much “smaller” was this?
M+D Figure 7 shows us that the actually observed increase in water vapor content with warming was only around one-half the value suggested by the M+D model, which itself was only around one-third of the value assumed by the IPCC models with essentially constant RH.
So the observed rate was around one-sixth of than expected from constant RH.
Not to split hairs, but this looks like a substantial difference to me, Fred.
My response was to your earlier comment. Your statement that the Soden paper contain no new observations does not appear to be correct. It reports radiance data supporting the conclusion of constant upper troposphere RH, but again, the disagreement among sources tells us that we can’t draw definitive conclusions yet.
Max – I checked the Soden et al paper again. It does report HIRS observational data from 1984 through 2004, and so it cites more recent data than Minschwaner/Dessler over a longer interval (20 years) extending closer to the present. That doesn’t necessarily make it more “correct” than the Minschwaner/Dessler report, but I think the various studies, in concert, indicate that there is now a range that should be narrowed. They all support an upper troposphere positive water vapor feedback, albeit to different extents. There appears to be little or no disagreement for the lower altitudes.
Thank you for the added information.
Is there a reference document which lays out the data adjustments?
Also is there a NOAA or NASA series that provides the corrected data?
I am surprised that NASA is maintaining an ongoing data base that is demonstrated to be wrong and misleading.
Etudiant – Here is the Dessler and Davis link that I previously cited far upthread –
Dessler and Davis
This cites the evidence for the conclusion that specific humidity has increased, although it doesn’t directly report on the extent to which RH remained constant or declined (see my various responses to Manacker on the divergence of conclusions on that point). I don’t have at my fingertips the reference to the paper discussing why the NCEP/NCAR analysis gave spurious results, but the basic problem involved several change in sensors over time. The earlier sensors sampled water vapor at a given altitude but because of excessive time lag in ending the sampling, each result was contaminated with water from a different altitude. The sensors were replaced on several different occuasions with improved versions with smaller and smaller lags. After each replacement, the recorded humidity took a jump downward, and so the recorded declining trend actually consisted of these several steps rather than a continuous decline.
I don’t know why the data are retained in the way they are. The NCEP/NCAR data are considered accurate for other climate measurements, and my surmise is that NOAA simply wishes to retain the humidity data for the record, while aware that other, later analyses have yielded different results.
Thank you very much for that link.
The paper does highlight some items such as the NCEP/NCAR non response to El Nino events that appear discrepant, which helps support the different trend found in the other reanalyses. Still, D&D only say the NCEP/NCAR data are likely, but not certainly, wrong.
Is there no more recent sensor suite that could provide more certainty or did they get lost on some of our recent launch disappointments?
It seems like a fairly significant element of the puzzle.
The D and D paper was in 2010, and I’m not aware of anything more recent that changes their conclusions. A paper during the past few weeks in either GRL or JGR (I don’t recall which at the moment) provides additional evidence for the increase in upper troposphere humidity with warming, but I only saw the abstract and so I can’t offer details. All the recent data from satellites supports this general conclusion, and I therefore think it’s almost certainly correct. I don’t think anyone is going to go back to the old radiosonde methods to try to get a different answer.
The D and D paper specifically excludes RH as there are significant energetic constraints.
Box 1980 suggests
Predictive modeling [sic], i.e., the rigorous application (extrapolation) of quantitative models to environmental data (at sites other than those used to construct the model) in order to predict actually occurring patterns, can be particularly useful in plant geography and plant environment relations, since it provides a ready means of testing the validity of the model and the understanding behind it.
If we use a standard 30 year set of data , we can observe that the annular mode show us that RH is indeed not constant.
Tapio Schneider et al 2010 indeed ask some interesting questions eg.
It is also clear that the rate of change of evaporation with global- mean surface temperature cannot differ vastly from the 2–3% K−1 quoted above, as would be necessary for significant relative humidity changes. To illustrate how
strongly changes in evaporation and near-surface relative humidity are constrained by the surface energy balance, consider a hypothetical case that will turn out to be
impossible: assume that an increase in the concentration of greenhouse gases would lead to a 3 K global mean surface temperature increase in a statistically steady state, accompanied by a global mean saturation specific humidity increase at the surface by ~19.5%; assume further that this would lead to a reduction in near-surface relative humidity from 80% to 70%. According to (3), evaporation would then have to increase by ~70% in the global mean. Currently, total evaporation at Earth’s surface amounts to a latent heat flux of about 80 W m−2 [Kiehl and Trenberth, 1997;Trenberth et al., 2009]. A 70% increase would imply that an additional energy flux of 56 W m−2 would have to be
available to the surface to balance the additional evaporation.
The global-mean net irradiance would have to increase and/or the upward sensible heat flux at the surface would have to decrease by this amount. But this is impossible:
Current estimates of the equilibrium climate sensitivity are of order 0.8 K surface warming per 1 W m−2 radiative forcing at the top of the atmosphere, and the radiative
forcing at the surface can be of the same order as that at the top of the atmosphere (though they are generally not equal). So a 3 K global mean surface temperature increase is inconsistent with a 56 W m−2 increase in net irradiance at the surface. Likewise, the upward sensible heat flux cannot decrease sufficiently to provide the additional energy flux at the surface because it amounts to only about 20 W m−2 in the global mean and 10 W m−2 in the mean over oceans, where most evaporation occurs [Kiehl and Trenberth, 1997; Trenberth et al., 2009]. The implication of these order of magnitude arguments is that changes in near surface relative humidity and in evaporation (and thus in a statistically steady state in global mean precipitation) are strongly energetically constrained. Order of magnitude estimates of the climate sensitivity indicate that global mean evaporation can change by O(2% K−1), and relation (3) then implies that the near surface relative humidity can change by O(1% K−1) or less.
These are non trivial problems that need to be addressed by a stronger underlying theory then seems to exist.
In the following I try to go through the major factors influencing the changes in overall precipitation and in humidity. They are probably mentioned in some way already in this thread, but I have not noticed a systematic approach to the most important factors.
Continuing from the arguments presented by Schneider et al 2010, the evaporation is linked directly to the energy balance at the surface. Taking into account the fact that the main components of the energy balance at the ocean surface are incoming solar radiation, incoming LW IR, outgoing LW IR and evaporation, we see that the changes in evaporation must be compensated by equal changes in radiative energy balance.
The radiative components of the energy balance are determined by factors that do not react very strongly on the local conditions. The rate of evaporation must therefore settle to the value determined by the radiative balance and this happens trough changes in the surface temperature and humidity near surface. One should not try to calculate the change in evaporation from the change in surface temperature, but from the radiative energy balance. The total amount of rain is then equal to the evaporation over periods long enough to make changes in the water vapor content small compared to the amount of evaporation over that period.
The resulting humidity and the persistence time of water in the atmosphere are then linked by the amount of evaporation/precipitation.
The US (NCDC/NOAA) record shows a decrease in strong to violent tornadoes from 1975 to 2005 (the late 20th century warming period cited by IPCC) and an increase from 1950 to 1975 (the mid-century cooling period).
Did Zwiers have access to these data?
The USGS tells us that 13 major floods occurred after 1975 and 10 before, so there has been a slight increase since the start of late 20th century warming period.
Do these data mean anything?
Probably not, since there are probably too few samples to be meaningful.
NOAA also tells us that of all hurricanes to hit land in the USA:
40 occurred from 1976 to 2005
54 occurred from 1946 to 1975
61 occurred from 1916 to 1945 and
129 occurred prior to 1916
Of the top ten hurricanes in the USA, two occurred in the late 20th century warming period (1975-2005), four occurred in the mid-century cooling period (1945-1975) and three prior to 1945.
So there is no trend here, either.
I’m still having a hard time with the notion that no matter what the extreme weather event is, let’s say floods or droughts to keep it simple, AGW will be linked to it in some way because it was predicted by the GCM’s. How do we falsify the theory? What should we expect if the GCM predictions are wrong? Less severe rain events or less severe droughts? If we have a gentle summer rain, is that evidence the GCM’s are wrong. If we hit a short seasonal dry patch, is that another. Obviously no, since these observations are routinely made daily/seasonally. But that seems to be all that is left when you take any “severe” event and link it to AGW. None of this seems to be very quantifiable. What types of metrics can be used to quantify “severe” events now as compared to “severe” events pre-industrialization?
You are right.
“Severe events” are neither quantifiable nor is their attribution to AGW falsifiable.
Trenberth would like to bend the rules of the scientific method to make the attribution of severe weather events to AGW the “null hypothesis” (see Judith’s earlier thread on this), but that suggestion isn’t going anywhere.
It’s a dilemma, sort of like the old “Radio Minsk” story:
Radio Minsk has a news flash:
Radio Pinsk counters with:
The record shows that there has been no increase in:
– the number of tornadoes
– the number or intensity of hurricanes
– the number of severe floods
as a result of AGW (since the late 20th century warming period cited by IPCC started around 1976).
I have not checked droughts, as the record is a bit sketchy, but it appears clear to me that the physically observed record does not support the IPCC postulation (or Zwiers’ statement) that AGW has caused an incfrease in severe weather events (at least in the USA, for which data are available).
I know this borders on your area of expertise, so would appreciate it if you would tell me if I’m looking at this wrong.
“4) Given the constraints of the Clausius- Clapeyron equation, more water vapor in the atmosphere implies more global precipitation”
A greater potential for precipitation, due to more precipitable water but does that imply greater precipitation.
The other required parameter is PE precipiation efficiency. PE is measured in units day^-1, hence 1/PE is a time constant, the precipicable water divided by the precipitation rate. Globally it was around 8 days (1960s).
The precipitation rate is bound up with the need to transfer heat from the surface to the atmosphere but also with how quickly water vapour turns to clouds and into precipitation.
According to Sellars in the 1960s we had a global precipitation rate of ~2.8mm/day, which is confirm by ERA-40.
Since then ERA-40 global precipitation increased to about 3.5mm/day in 2002 when the series was halted, an increase of about 25%.
There is a problem though, the ERA-40 series for evaporation was essentially flat, somehow ERA rainfall was exceeding evaporation by about 200mm/year (0.6mm/day) by 2002.
The series was halted and ERA-Int(erim) introduced, and it supported the evaporation trend but produced a precipitation series that returned by the mid 2000s to ~2.8mm/day, e.g. no apparent longterm trend, (in my opinion).
What happened to cuase the too series to be so different I do not know, but if ERA-Int is the more correct, nothing much seems to have happend to global precipitation sinc 1960.
Now that raises the question of precipitation efficency. Neither PE nor humidity seem to have ERA series but if absolute humidity has increased significantly and evaporation/precipitation have not then perhaps PE has been dropping marginally, e.g. it rains less easily. This seems to run contrary to what one would expect from an increase in GHG effect which might encourage greater PE, that is a speeding up of the hydrological cycle driven by the thermal requirements of the atmosphere needed to balance its energy books, but the cycle is also governed by the willingness to produce precipitation. So alternatively, PE could be increasing, driven by that thermal requirement, but if that were the case it would necessitate a drop in absolute humidity, if the ERA-Int seriers for precipitation/evaporation are correct.
The series are here:
Deficit rate (precipitation minus evaporation)
I shudder at the complexity of trying to do long-term studies on floods, comparing different eras. Go to downtown Sacramento, CA (one of the notoriously “at risk” cities in the US) and check out the older buildings. Specifically, go to the basements. . . where you will find that they used to the first floor, and now all of downtown has been “moved up a floor” in flood fighing consideration.
Man has been fighting flood dangers with various controls for about as long as we’ve had civilization. . .and then undoing that work by increasing population in at at-risk areas.
How in the world does a large scale long-term study control for that!?
We don’t. I’m sure somebody will start with a basic study and keep turning the knobs on the various considerations until one comes up with the answer they wished. You can’t compare in terms of damage or life, because, as you’ve stated, we build in at risk areas. But going further back, we had less dams. But dams can add to the harm done. And even coming up with an accepted term for a flood, would be a point of contention.
“And even coming up with an accepted term for a flood, would be a point of contention.”
What do you mean by “accepted term”?
No problem John, to answer your question, answer mine. Can you define the word “flood” to an acceptable definition for all interested parties?
For instance, I had an uncle that live on a spot of land where a local river split and then rejoined. He literally lived on an island, right in the middle of continental U.S.A. (The island is about 10 sq miles, give or take) The river, just about every year would move from its banks for a bit. Which wouldn’t be hard, in some places, its only a couple of feet beneath the top of the bank. So, he’d be forced to move from his home on a fairly regular basis, along with some other full time residents. Now, the river wouldn’t usually “officially” make flood stage, yet, the river would come to his front porch.
Is that a flood? If people build below sea level by the sea and water moves back into the area, is that a flood? Well, it is to the people effected. Honestly, I don’t know the answer to my last question.
What you are saying is how do we define what a flood is? If so, I agree. Take that a step further, how do we define what a severe weather event is? I have a problem with “terms” like this being bandied about, when they are poorly defined in “terms” of quantifiable measurements. I posted this question above. How do we measure these types of things? What is the standard? What are the metrics?
If I got your explanation wrong, let me know. Thanks
You got my meaning exactly. With these poorly defined terms with vague meanings, just about any study could render just about any results.
And then everyone would line up on opposite sides and throw rocks at each other…….again.
Not just dams. . . levees, weirs, pumps, changing setback laws, etc etc
Not that I want to come across as particularly dense in this exchange, but I still am not following the explanation. Can you elaborate a little more? The word “term” has many definitions.
In spite of the threading towards me, I’m going to assume you meant that for suyts. . .
I did reply to you since you offered further explanation, however suyts is welcome to elaborate as well. Not to worry, I am not a troll looking to pounce on anyone with a crafty reply, I am simply curious as to what suyts meant in context to the rest of his reply.
I am with you on that John. Classifying extreme floods or any event really, is difficult as I see it. Cost of physical damages varies a lot from region to region. Cost in lives also varies since some countries are poorly prepared for evacuation and rescues. Extent of flooding is relative as well. Australian floods are huge by most standards. I wonder what a reasonable flood intensity scale would be?
Well one could do it statistically: one standard deviation from the local norm is a full flood, two standard deviations is an extreme event, three and you are living on the reef with Sponge Bob Squarepants.
This should not be difficult: take the data, plot it, do the probability curve.
That may be the best way. If someone builds in a 2 sigma flood plane his loss is not flood related but due to mental defect. So what if the sigmas are based on the mean of 50 or 100 year events? That makes more sense to me. Mean high water in a flood plane is kinda useless, it is a flood plane because it tends to flood.
GaryM | March 9, 2011 at 5:16 pm | Asks
“How did we warm enough to get out of glacial maximum…?”
1 kg of ice at -23C contains 5434 KiloJoules of heat.
1 cubic metre of ice weighs 916.7 Kg
At its’ maximum extent. the volume of the Laurentide Ice Sheet was estimated at : 26,500, 000, 000, 000 cubic metres.
Multiply all that out, and you have an awful lot of heat which was previously “locked up” in the ice sheet being released backed into the atmosphere as the ice melts.
Enough to warm the Earth out of the last Glacial maximum?
I don’t know for sure, but I think it is worthy of serious consideration……
Melting doesn’t produce heat, it absorbs it.
Hence the name – Anything Is Possible (even the impossible)
Oh, and I didn’t ask that question, I just tried to show that even the climate scientists admit they don’t really know.
334 kJ of heat required to melt 1Kg of ice at 0C, which promptly releases about 5400kJ to interact with the atmosphere. Still looks like a positive feedback to me.
I’m too lazy to look the numbers up, but I can say with 100% certainty that it don’t work that way.
Did I just get maneuvered into saying “100% certainty”? 8O
:) with less than 100% certainty it would take about 1.3 zettawatts of energy to melt the ice. About the energy of 1600 days of continuous average hurricane activity or about three years worth of human energy use based on 2008 consumption. Then, if all 7 billion of us have a couple Scotch rocks each day ….
Oops! That should be zettajoules.
One believes you volunteered.
But you could argue rounding, in this case.
Please re-fresh your knowledge of basic thermodynamics, you will then understand why this is not a possibility.
Fred you sat ” The level of warming at which such a critical juncture will be reached is conjectural. It is reasonable to assume that it has not been reached yet in most regions.”
Fred which regions do you think it has been reached and do you claim an attribution in those regions to increased flooding? Also, Fred, is it your claim that there has been statistically significant GW in the last decade.
Bob – I would refer you to the Zwiers data for regions that may have been affected already. I haven’t surveyed the data sufficiently to give an independent assessment.
There was a slight warming during the decade 2001-2010. The term “statistically significant” relates not to whether the warming occurred (it did with 100 percent certainty) but to how much confidence we can put into conclusions about long term trends based on that decade. The answer is that our ability to conclude much is very limited, and so the data lack “significance” in that respect.
I tried to address the significance issue in more detail in the following set of comments regarding the 1995-2009 interval – Comments on Significance
Maybe Judith should devote a thread just to this particular issue as it still keeps popping up with depressing and monotonous regularity. It really needs to be killed off once and for all.
Aw, c’mon, Fred.
HadCRUT shows very slight cooling, as does UAH and RSS. GISS (the odd man out again) shows very slight warming.
All in all, there was very slight cooling, but lets agree with Kevin Trenberth and Phil Jones that it was simply “a lack of warming”. (But let’s not “spin” it as “slight warming during the decade 2001-2010”.)
Actually RSS and UAH both show a slight warming tend (more so in the case of UAH).
No, from 2001-2010 it’s a slight cooling – Fred’s statement is wrong.
As Max says, it doesn’t make sense to claim warming or cooling over the last decade, we should just agree that there has not been any significant warming or cooling.
Only for HADCrut. Did you follow my link? Do you dispute that it shows a warming trend for both RSS and UAH?
Anyway, whether it is cooling or warming over that period you are not going to get a statistically significant trend because it’s too short a period, so to claim “no statistically significant warming” for that period doesn’t actually prove anything.
Both UAH and RSS also show a slight cooling trend over the past full decade.
Only GISS shows slight warming.
PaulM is right.
What we have seen is “a lack of warming”.
Andrew- if there was no warming from 2000 to 2010, does it at least indicate that there are factors other than CO2 that are primarily driving the temperature. Given the amount that CO2 rose during that period (10%), if temperatures were flat……what does it mean to you?
No, Andrew is right. The confusion comes from the fact that how Woodfortrees calculates trends is that 2001-2010 is “up to 2010”, so it’s actually 2001-2009 (incl). On the other hand, UAH’s higher trend might have something to do with the fact that UAH changed its base line in the fall and it’s not clear (to me at least), how Woodfortrees handles that and even whether the data goes till the last (low) values at the end of 2010 and the beginning of 2011
What I mean with “whether the data goes till the last (low) values at the end of 2010 and the beginning of 2011”, is that if you look at Andrew’s Woodfortrees chart then you see that the last value is somewhere around 0.375, but UAH last values from September 2010 to January 2011 are 0.48, 0.31, 0.27, 0.18 and 0.0. As I said they did change base line, but it had not clearly an impact as big as 0.375 C.
The change in the base line would affect the whole data set, not
just the period from when it was changed, and I don’t think it makes a significant difference to the overall trend.
The rather pronounced downturn in the anomalies since September is due to the current la Nina and is also reflected in HadCrut.
I know, Andrew. I know of la nina and base lines and so on, but looking at the woodfrortrees graph, it seems that either the UAH change has not gotten into their database or the graph is not going to the “end of data” or something else. Compared with other data sets, something is not right if you compare it with UAH data:
Even Hadcrut appears to show warming to the end of 2010 –
Hadcrut Global Dataset
My point was focused on the meaning of the word “significant”. I was trying to point out that a 10 year interval is often inadequate to infer very much statistically about long term trends, even when the interval is randomly chosen. When it is cherry-picked, it is not merely inadequate but probably misleading. When any time either at the beginning or end of the interval involves an El Nino or La Nina episode, the distortion is likely to be even worse. It is the long term trend that clearly delineates the warming.
Here’s the correct global dataset –
Hadcrut Global Dataset
HadCRUT shows slight cooling over the decade 2001-2010, regardless of what you claim.
Just plot the data you cited in Excel and draw a linear trend line and you will be able to see this (same is true for UAH and RSS). The only “outlier” here is GISS, which shows very slight warming.
Those are the observed facts, Fred, no matter how you may try to “spin” them.
But we are beating a dead horse, and it is getting boring.
Max – I provided a link to the Hadcrut dataset, which readers can visit to draw their own conclusions. Here is a visual depiction of the same data – Hacrut Global Data.
Notice also that for a full decade, you have to start at the beginning of 2001 rather than the end – you therefore need to start with the anomaly data at the end of December, 2000. Otherwise, you only work with 9 years’ of data.
You are, indeed, waffling (as anyone here can plainly see).
We are discussing the HadCRUT temperature trend over the past decade (January 1, 2001 through December 31, 2010) and you bring out a curve going back to 1850!
I do not disagree that there has been a gradual warming trend of around 0.04C per decade since 1850, with warming and cooling occurring in several multi-decadal cycles, sort of like a sine curve on a tilted axis with a total cycle time of ~60 years and an amplitude of +/- 0.2C.
But the past decade has shown no warming, and that is what we were discussing.
The whole “extreme weather event” postulation of IPCC, which was apparently supported in the testimony of Francis Zwiers, is extremely dicey and contains some statistical nonsense.
A look at Table SPM.2. in IPCC AR4 WG1 SPM report (p.8) confirms this.
IPCC tells us it is “likely” (>66%) that the trend of heavy precipitation events (frequency or proportion of total rainfall from heavy rainfall) has increased in trend over the late 20th century.
Was this caused by AGW?
IPCC also tells us it is “more likely than not” (>50%) that there was a “human contribution” (of unspecified magnitude) to this observed trend, with the footnote:
So it appears uncertain a) that there really was an observed past trend b) with a significant “human contribution”, as there were no attribution studies to suggest this.
Yet the likelihood of future trends in the 21st century (based on model scenarios) is stated to be “very likely” (>90%).
No matter how you slice it, this is mumbo-jumbo.
With no quantitative baseline as to what is or isn’t an “extreme” event, there is no way you can measure any more or less severity/frequency of such events relative to the past, right? Metrics such as #of hurricanes, category of hurricanes, inches of rain, #of tornadoes, category of tornadoes etc… are metrics that measure size and/or frequency of weather events and can be compared to past events, but how do they relate to how extreme such an event is? When do we consider a storm an extreme one? Are all hurricanes extreme or only category 4’s and 5’s?
This is climate science. First you count the number of Cat 5 hurricanes. If there is a significant enough increase, those are the “extreme” hurricanes. If not, count the Cat IVs, and so on. Whenever you reach a number that shows a significant enough increase, that is how you define extreme. Perform the same exercise for tornadoes, floods, etc.
If that doesn’t work, construct a new statistical method to “tease” the increase out of the (adjusted) data. Then make a nifty graph comparing your results to a series of model runs that have been tuned to the last 10 years. Publish the results in Nature and wait to collect your Nobel.
or my pet peeve, John, who decided on what the normal temperature is? How can we say that we are .7* above normal? If we take the average for the last million years are we not really quite a bit higher above normal then just .7?
Attached is the link to the Minschwaner and Dessler study on observed tropospheric water vapor trends with warming.
Thank you very much for that link.
What a wonderful blog.
Science discussions and great bedtime reading.
Nice article. I did some estimates on an average hurricane a while back. 600 terawatts per day latent heat was a big number. The increased radiative outgoing due to convection was orders of magnitude less. The reflected incoming radiation by cloud cover (assuming a 1200 kilometer diameter for an average storm) was 60 times greater than the rain out using a fairly conservative number for the solar TSI. So convective clouds are basically neutral unless the associated cloud cover increases.
It might be interesting to use precip proxies with a more solid estimate of cloud cover change relative to precip change. At least I haven’t seen that done yet.
At least someone gets it:
Summary of key points
•Observations and research outcomes since 2008 have confirmed and strengthened the position that the mainstream science then held with a high level of certainty, that the Earth is warming and that human emissions of greenhouse gases are the primary cause.
◦By mainstream science I mean the overwhelming weight of authoritative opinion in the relevant disciplines, as expressed in peer reviewed publications.
•The statistically significant warming trend has been confirmed by observations over recent years:
◦global temperatures continue to rise around the midpoints of the range of the projections of the Intergovernmental Panel on Climate Change (IPCC) and the presence of a warming trend has been confirmed;
◦the rate of sea level rise has accelerated and is tracking above the range suggested by the IPCC; and
◦rates of change in most observable responses of the physical and biological environment to global warming lie at or above expectations from the mainstream science.
•It is an awful reality that no major developments in the science hold out realistic hope that the judgements of the 2008 Review erred in the direction of overestimating the risks of climate change.
◦The judgement of the Review—that the greater risks of severe consequences under a scenario of 550 ppm concentrations of greenhouse gases make the extra mitigation cost to achieve a 450 ppm outcome worthwhile—has been confirmed.
•There is increasing discussion in the legitimate scientific literature of the possibility that large damage will occur at smaller increases in global average temperature than the IPCC focus and United Nations (Copenhagen and Cancun) agreement on holding temperature increase to 2ºC or less above pre-industrial level.
◦There is a case in managing the risks of climate change for seeking to reduce emissions concentrations below 450 ppm carbon dioxide equivalent, but that would first require a credible programme to get to 450 ppm.
•Despite the increased scientific understanding of climate change, and confidence in the science’s conclusions about climate change, public confidence in the science seems to have weakened somewhat in Australia and some other countries since 2008.
•The scientific community has given greater attention to the ‘emissions budget’ approach that was introduced in the 2008 Review to the global and national task of reducing emissions. This approach warns us that we are rapidly utilising the atmosphere’s remaining capacity to absorb greenhouse gases without generating high risks of dangerous climate change—and now face the challenge of absorbing more carbon dioxide from the atmosphere than we are adding from human activity.
◦The immediate implication is that avoiding high risks will require large changes in trajectories at an early date.
global temperatures continue to rise around the midpoints of the range of the projections of the Intergovernmental Panel on Climate Change (IPCC) and the presence of a warming trend has been confirmed;
Here is the evidence
The tide gauge record (used by IPCC until 1993) shows no such acceleration. In fact, the rate of rise was slightly lower in the second half of the 20th century than in the first half.
IPCC (AR4 WG1 SPM, p.5) changed the method to satellite altimetry in 1993, and claimed an acceleration:
In a small footnote IPCC tells us:
Comparing the rate of rise between two time periods using two different measurement methods and two totally different scopes (the total ocean, except regions near the poles and shorelines, which cannot be measured by satellite compared with selected shorelines) is “bad science” at best, especially as the tide gauge record showed no such acceleration.
Seconded- the seal level rise is constant.
The percieved rate rise is probably down to yet another splicing of two records (satelitte and tide).
As for your other points (i’ll number them in order for ease, numbers refer to BLACK dots))
1- not so- there is no high level certainty at all.
2- irrelevant, second and third parts are rubbish too.
3-except that all the models fail to accuratley reflect recent temperatures.
4- no evidence
5- yes and with good reason.
6- complete nonesesne.
If you wish pick a point and we can debate it- too many to go into all of them.
U. of Colorado hasn’t updated their measurements since last August. Anyone know why?
No. They’ve also ‘burried’ the tidal data to so you cannot directly compare satelitte to tidal. It’s quite frustrating to be honest.
Ping em an email- see what they say, it could just be a data-base thing.
Just emailed them. Let you know what I find out.
The UCB blurb you cited tells us:
But, wait a minute! The people actually doing the satellite altimetry measurements of sea level are not so convinced.
Doesn’t sound like “unprecedented accuracy” to me, but more like “spin”.
It is hard to get past your first four points.
1. Observations since 2008 are less compelling in my view. The research in some disciplines is questionable because uncertainty is often poorly addressed.
2. A good deal of the peer reviewed literature is using the same methods that made them questionable to begin with. 95% confidence in a maybe is still a maybe.
3. The significance of the statistically significant trend is decreasing with time. Why?
4. If hugging the lower end of the uncertainty range is what you call the mid range or are you privy to a more realistic uncertainty range?
ianash : I guess you deserve a triple F as all your nice “key points” are proven to be rebutted
1) Observed versus predicted warming :
a) Observational data do not support models and science outcomes that earth is steadily warming nor that human emissions of GHG are the primary cause.
Global mean T° has been stable for the last 13 years whereas CO2 concentration and human emissions have steadily increased.
b) Over the same period, IPCC had predicted a +0.2 to +0.3°C warming that is rebutted by observed T° stagnation.
c) Dr Phil Jones, head of CRU, recognized that there has been no statistically significant warming over the past 15 years.
2) Sea level rise
a) Sea level rise has not accelerated but decelerated since the rate has been divided by roughly 2 (16mm per decade instead 32) since about 2004 or 2005, probably corresponding to the shift of PDO phase into cool mode (i.e Pacific ocean is globally cooling and sea water density is increasing…)
b) Tide gauge data (http://www.psmsl.org/) provide an average rate of sea level rise of about 18mm per decade, that is also almost twice lower than satellite data (32 mm per decade according to TOPEX/JASON measurements)
c) Sea level has slowly but steadily increased over the last 7 k.years, as stigma of the post glacial sea level rise and of the melt-water pulse that occurred 14 k.years ago.
d) IPCC forecasts w.r.t sea level rise have been steadily decreasing along the different reports starting with 370mm per decade (max) in FAR, falling down to 60mm per decade in AR4. This remains largely overestimated since about 4 times higher than the current rate measured by satellites (16mm per decade since 2004), or by tide gauges over the complete 20th century. James Hansen was still predicting 600 mm per decade in 2007 (at the time of AR4 but 10 times higher…) which is just ridiculous.
3) CO2 impact
a) Effect of CO2 enrichment is not proven as detrimental but rather beneficial, especially by stimulating plants’ growth and therefore improving farm outputs (which is all the most needed considering increasing earth’s population).
CO2 is not a poison but essential to life.
b) Moreover, Earth has already experienced CO2 concentrations much higher than current one, without noticeable warming or mass species extinction.
– More than 2000ppm during Triassic and Jurassic (150 to 250 millions years ago)
– Even more than 7000ppm during Precambrian (500 millions years ago) with T° even colder than today!
4) Legitimate scientific literature
I guess you are talking about peer reviewed papers.
But climategate has clearly revealed that peer reviewing process has been corrupted by IPCC leading authors
5) Confidence in the climate science
a) Despite dense research activities and few breakthroughs, scientific understanding of climate change remains as poor as uncertainties are high.
b) Public confidence in the science has obviously weakened due to :
– Excess of alarmism and doomsday prophesies that were not supported by facts.
– Obvious and increasing divergence between forecasts and observational data
– Climategate providing evidence that AGW theory had been based on junk, corrupted and dishonest science.
Sorry try again.
I don’t know if you are familiar with the work of Will Alexander, a retired South African scientist who did a lot of research on water resources and natural disasters. South Africa is a water scarce country and water resource planning has been an important field of study there. Will developed a flood/drought prediction model based on linkages he found between the hydrometeorological data and the double sunspot cycle. You may find this and some of his other work interesting in reference to flood patterns discussed here.
Here is a google scholar search for his work (W.J.R. Alexander):
Here is a guest post at Pielke Snr where you can find a list of references at the bottom. (I find I need to not let his fiery presentation distract me)
See now link is missing:
I agree with Girma, labmunkey and manacher
As ianash reads an increasing trend in the actual sealevel graph,
we can take the rest of his pronouncements with the same degree of doubt (or should I say skepticism). No doubt there is a parallel universe model that “proves” his statements.
Rather than give us bold unsupported assertions or blog posts like your cohort Holly Stick does, please quote the actual data or paper references to show you are capable of independent reasoning.
As a non scientific, but interested Lurker and sometimes poster on most of the Climate based Forums it has become obvious that Judith Curry’s Climate Etc has become a very important site. This is evidenced not just by the interest shown by bloggers but also by the increased Troll activity espousing the same old arguments, appeals to authority and references to RC outpourings to try to disrupt every Thread on here.
Well done Judith Curry and Climate Etc, a new star in the Forum firmament.
Perhaps someone might enlighten me on the effects of water vapor on climate. From the basic Clapeyron equation, the log-log derivative of partial pressure wrt temperature is about 20 (H/RT). Thus a 1% temperature increase leads to a 20% increase in absolute humidity. I believe the adiabatic lapse rate drops from 10 to 7 K/km due to the added heat capacity of water vapor and this 20% change should reduce the lapse rate by an additional 0.6 K/km and would seem more than adequate to neutralize the original 1% rise.
IMO, the basic paper relating energy flux and temperature was written by Onsager in 1931 wherein he shows that, for a steady-state with fixed boundary temperatures, thermodynamics uses all the variables at its disposal to maximize flux. Conversely, with constant flux boundary conditions, temperature differences are minimized. These conclusions are rigorous for the regime where the ratio of flux to thermal gradient is constant and maintains its near-equilibrium value. The conditions for which similar conclusions hold outside this range have yet to be established, as far as I’m aware, but they provide an asymptotic condition when one enters the turbulent regime at the adiabat and the rate of entropy dissipation is determinant.
How long does it take freshwater(rain) to mix with saltwater(oceans)?
So far every week, the U.S. east coast have had massive storms dumping massive amounts off the coast. Some in warm waters and some in colder waters.
It is conceivable that this could create a chain reaction if the storms become closer and closer together. This could generate precipitation unlike we have ever experienced before in our current history.
Judith writes “So the issue is this. Even if we assume the following:
1.Sea surface temperatures are warming”
“So even if you accept the above 5 premises”
I do not accept the premise that sea temperatures are warming. If we assume that sea temperatures will fall for the next 30 years or so of the current negative phase of the PDO, there would be an entirely different discussion. Interesting though this present discussion is, I suggest it is little more that the classic “How many angels can dance on the head of a pin?”.
ARGO results since 2003 tell us that the upper ocean temperature is not warming, but cooling slightly. Even NASA’s Josh Willis has acknowledged this, calling it a “speed bump”.
Question is: will it be a 30-year “speed bump”?
Nobody really knows.
But, together with the “unexplained”, but observed, “lack of warming” of the atmosphere (surface plus troposphere) over the past decade (despite record increase in CO2), this does raise some interesting questions concerning the premise that human CO2 is the principal driver of our planet’s climate, right?.
“One wonders that if there are no long-term increases in flood events in England, how could a single event (Fall 2000) be pinned on human causation as in Pall et al. 2011, while previous, similar events obviously could not?”
“Indeed, on a remarkable point of fact, Pall et al. 2011 did not even examine the actual history of flood data in England to understand where the 2000 event might have fit.”
For some reason, Christy often prefers to not properly identify the aim of a study, or accurately describe the methodology or conclusions.
This is only the beginning of quantification of impacts on human beings. He knows this is among the first papers developing the modeleling tools for specific rather than theoretical evidence. It was not possible before, due to limitations on long-term data and computer power. In this modelling research, extreme rain and snow events (flood generating mechanisms) were incorporated, along with runoff and intensity of flow. The comparison is between simulated changes and observed changes: model to model to real-world climate observation. They found that with greenhouse gases emitted by human activity in the 20th century, the statistical odds of that flood event was likely doubled.
Etc. Terrible. As noted by citizen scientists who are rational skeptics, it’s hard to see how Christy can even believe himself, anymore, or why anyone continues to put him forward as a capable of providing, overall, credible or expert dissent:
re. Stephens et al 2010. Yes, the identified issue is that solar radiation reflected in low clouds is enhanced in current models. Better representation of cloud-climate feedback mechanisms is needed. While not yet widely discussed, Stephens’ concerns about current GCM low cloud albedo bias is not a new finding. See e.g. Trenberth and Fasullo (2010). You seem to want to lump extreme weather events together, and cannot separate the current strengths of models from their current weaknesses. The improvements expected in modelling for regional predictions in the near future is likely going to render what you presently offer in your commercial venture obsolete. :-(.
Realclimate on the two papers in question might also help you to update the lens through which you can view Stephens:
“The comparison is between simulated changes and observed changes: model to model to real-world climate observation.”
This is incorrect. It’s model vs model, with the difference being attributed to warming. All you have to do is read. Christy was correct in his statement . Misleading while telling facts is also lying, so careful with the realclimate lies.
You’re confusing Min et al and Pall et al. Christy’s right about Pall. Min’s models are off from actual data by a few hundred percent, so I pretty much trash can that one.
To this rational skeptic, Christy makes more sense than Zwiers.
He has done a better job of doing his homework and presenting his story, as many have remarked here and on the other thread.
But let’s face it, even forgetting the subject matter, it was an unfair match to start with, IMO.
It is a relatively bad idea to look at short term trends in rainfall – i.e reduction or increase (depending on where you are) since the 1950’s – given the multidecadal changes evident globally.
To quote realclimate – “two new papers in Nature (Min et al. 2011, Pall et al. 2011) have presented evidence that changes in the intensity of extreme precipitation since the middle of the 20th century may be linked to human induced global warming…”
Globally – much of the decadal change in rainfall arises from changes in the Pacific Ocean. Australians have been in a ‘drought dominated regime’ since the Pacific climate shift in 1976/1977 – we have since returned to a ‘flood dominated regime’ which will result in increased flooding in Australia over another 10 to 30 years. This also has impacts on rainfall in the Americas, China, India and Asia. But there are also changes in the Polar vortices which show decadal change and influence storm tracks.
So what is the Australian record – this is what the Bureau of Meteorology said about flood and drought dominated regimes in their 2010 State of the Environment Report? ‘While total rainfall on the Australian continent has been relatively stable, the geographic distribution of rainfall has changed significantly over the past 50 years. Rainfall decreased in south-west and south-east Australia, including all the major population centres, during the same period.’
Here is the trend in rainfall for 1970 to 2010 – http://www.bom.gov.au/cgi-bin/climate/change/trendmaps.cgi?map=rain&area=aus&season=0112&period=1970. There are obvious and significant declines over much of the country. The horrible consequences of a warming planet? I think not.
Here is the trend in rainfall for 1900 to 2010 – http://www.bom.gov.au/cgi-bin/climate/change/trendmaps.cgi?map=rain&area=aus&season=0112&period=1900 – and this tells a very different story.
Australians have had very little change in rainfall anywhere at all and none that could not be attributed to natural variability.
It is a invariably a matter of seeing change and attributing it to greenhouse gases. The reality is that there is natural variability – in both rainfall and temperature – and saying that something is not unnatural is very difficult indeed.
I noticed a comment on realclimate – ‘A whole bunch of big storms, floods, droughts and fires are things that can invoke the fear necessary to get action on GW. Probable attribution is so much better than where we were before.’
This also is a bad idea.
…that should be saying some event is unnatural is very difficult – as indeed was stated in the realclimate post referrd to by Martha
Its called the ‘River Thames’, not the ‘Thames River’.
It flows about 1/2 a mile away from here.
‘Globally, precipitation can be approximated by surface evaporation, since the variability of the atmospheric moisture storage is negligible. This is the case because the fluxes are an order of magnitude larger than the atmospheric storage (423 x 1012 m3 year-1 versus 13 x 1012 m3 according to Baumgartner and Reichel (1975)), the latter being determined by temperature (Clausius–Clapeyron). Hence the residence time of evaporated water in the atmosphere is not more than a few days, before it condenses and falls back to Earth in the form of precipitation. Any change in the globally averaged surface evaporation therefore implies an equivalent change in precipitation, and thus in the intensity of the global hydrological cycle. The process of evaporation requires energy, which it obtains from the surface radiation balance (also known as surface net radiation), composed of the absorbed solar and net thermal radiative exchanges at the Earth’s surface. Globally averaged, this surface radiation balance is positive, since radiative absorption, scattering and emission in the climate system act to generate an energy surplus at the surface and an energy deficit in the atmosphere (Liepert 2010).
Evaporation, or more precisely its energy equivalent, the latent heat flux, is the main process that compensates for this imbalance between surface and atmosphere, since the latent heat dominates the convective energy flux over sensible heating. The radiative energy surplus at the surface is thus mainly consumed by evaporation and moist convection and subsequently released in the atmosphere through condensation. This implies that any alterations in the available radiative energy will induce changes in the water fluxes. Our focus in this editorial is therefore on the surface radiation balance as the principal driver of the global hydrological cycle.’
Energy is everything in climate and in hydrology – a trick is to to reconcile this with the evaporation paradox. Point evaporation has declined over past few decades but total global mean rainfall has increased?
Hint – ENSO is the largest determinant of global hydrological variability by far.
I might be able to suggest a post on hydrology to Dr. Curry.
Talking about energy – found a nice CERES site – http://ceres-tool.larc.nasa.gov/ord-tool/jsp/EBAFSelection.jsp
Has kept me entertained for hours – you can graph it, plot it, Google Earth it, download. Fantastic.
Warm air holds more water vapour, but the water vapour gets into the air based on the vapour pressure gradient at the surface of the water, so cold air absorbs more water vapour more quickly than warm air, but really, wind dominates vapour transfer by churning the air at the water surface, but our most humid days here in the great lakes basin are windless summer days.
The three elements are wind speed, the water vapour deficit (or relative humidity) at the surface and surface irradiance.
Here is the pan evaporation for Australia – the decline matches the global decline. I think it is to do with fossil fuel burning over land masses – black carbon and sulphate emissions.
Here is the 1 day max precipitation data for Australia –
No huge change. There are decadal changes associated with stable blocking patterns – the rest is simply play station science. ENSO + PDO is a pattern that produces dramatic change in regional rainfall and moderate change in global totals. The latter is associated with reduction in cloud over warm ocean and increase in cloud over cool oceans – radiative changes in the central Pacific.