Alexandre Aguiar
Kevin, pay attention to the fact that the release came from NASA and not from pundits or the mass media. Here is the link.
Kevin, pay attention to the fact that the release came from NASA and not from pundits or the mass media. Here is the link.
Justin Turcotte
EF5
Most would agree polar regions would warm most in a GW setting per albedo feedback and the GCMs show this well. If indeed the case then the polar jet would be weaker since there is less baroclinicity. Lighter winds aloft means less shear for storms and one could therefore argue less tornadoes is just as plausible an outcome with global warming.
cdcollura
EF5
Good day,
Global warming should affect hurricanes the most, as the sea surfaces will also be warmer.
You will still have cycles (NAO, El Nini / La Nina, etc) ofcourse, but all will be affected by higher than normal temperatures.
It's already happening, we saw 2004-2005, and TWO landfalling category-5 storms this year of 2007 (Dean / Felix) only 2 weeks apart in the Caribbean...
Scary
Global warming should affect hurricanes the most, as the sea surfaces will also be warmer.
You will still have cycles (NAO, El Nini / La Nina, etc) ofcourse, but all will be affected by higher than normal temperatures.
It's already happening, we saw 2004-2005, and TWO landfalling category-5 storms this year of 2007 (Dean / Felix) only 2 weeks apart in the Caribbean...
Scary
rdale
EF5
So global warming is the cause for two Cat 5's this year?
Andrew Pritchard
EF5
What about the natural hurricane cycle that I keep hearing about (that we're actually in a peak of, and just had a very quiet year in 2006)? Seems the things we have known for years to occur naturally way back into our history are now forgotten, and used as ways that we are all going to die from global warming.
Mike Smith
As I said in my first post, "Can the GW advocates get any sillier?" The NASA press release explictly forecasts worse severe storms and more tornadoes in its first paragraph. It is not "non-scientists" (unless you consider NASA "non-scientists") that make the claims of worse severe storms. The "pundits" are simply printing what NASA claimed.
Yes, that is not the source paper, but that is not the point nor was it what I was commenting on. NASA clearly has a pro-GW agenda and uses PR techniques to advance its agenda regardless of what the science in question actually says. That is what I object to. The atmospheric processes that create tornadoes are far more complex than simply CAPE + SHEAR (i.e., convective inhibition, etc.).
I will continue to state what I have in several other threads: If the models are so precise that they can figure the frequency of intense CAPE 20 years from now, they are obviously good enough to figure temperature anomalies for multi-state areas (from which CAPE is derived) 20 months from now. Yet, somehow, the models are not used for long range forecasting.
I wonder why.....?
Mike
Kevin Scharfenberg
Yes, I consider PR people without science degrees who write press releases to be non-scientists. If people are basing their discussion on the press releases and not the source documents, there is no hope for them.
Ah yes, the whole conspiracy/agenda thing, the dependable last refuge of people who can't argue about the actual science. Yawn....
Obviously, but it misses the point entirely. Supercells cannot occur in an environment with insufficient CAPE and shear, so if you have reason to believe sufficient values of the two are showing up more frequently at some location, you have reason to conclude the ODDS of supercells also will trend up at that location. Now if there is some evidence that inhibition (or some other negative parameter) are also going up with time, tending to lower the odds, it has not been presented.
Anybody with even basic knowledge of how long-range (1 month to 1 year) forecasting is done knows that there is a much stronger predictive signal from teleconnections (on the shorter side of the scale) to soil moisture conditions to oscillations such as MJO, PDO, NAO, etc. Whereas conclusions reached from analysis of the GCMs are averages over scales of 10-50 years (or even 100 years), where such short-term factors are averaged out over time.
Doug Mitchell
EF2
An asteroid is going to hit earth someday and we'll all be in our respective afterlife destinations laughing about all this.
Dan Robinson
NASA - the National Aeronautics and Space Administration - is issuing climate forecasts.
I hear the Department of the Interior is going to start launching the space shuttle, the Department of Agriculture is going to start setting the interest rates, and the Department of the Treasury will be performing bridge inspections.
I hear the Department of the Interior is going to start launching the space shuttle, the Department of Agriculture is going to start setting the interest rates, and the Department of the Treasury will be performing bridge inspections.
Mike Smith
I retract my previous statement that things couldn't get sillier.
This was printed in a London newspaper today:
VIENNA, Austria: Global warming may be forcing polar bears southward and melting glaciers, but it could also have an impact on your heart.
Doctors warn that the warmer weather expected with climate change might also produce more heart problems.
"If it really is a few degrees warmer in the next 50 years, we could definitely have more cardiovascular disease," said Dr. Karin Schenck-Gustafsson, of the department of cardiology at Sweden's Karolinska Institute.
Some of us get outdoors and exercise more when it is warm. But, perhaps the GCMs are now so good they can predict how much exercise people will get, how nutrition will evolve, and the state of medical science in 50 years.
This was printed in a London newspaper today:
VIENNA, Austria: Global warming may be forcing polar bears southward and melting glaciers, but it could also have an impact on your heart.
Doctors warn that the warmer weather expected with climate change might also produce more heart problems.
"If it really is a few degrees warmer in the next 50 years, we could definitely have more cardiovascular disease," said Dr. Karin Schenck-Gustafsson, of the department of cardiology at Sweden's Karolinska Institute.
Some of us get outdoors and exercise more when it is warm. But, perhaps the GCMs are now so good they can predict how much exercise people will get, how nutrition will evolve, and the state of medical science in 50 years.
Mike Smith
So, let me get this straight: The models that are so good they can reliably forecast mesoscale CAPE (which is what is important for severe weather) can't forecast synoptic scale temperatures and are unable to resolve the PDO, NAO and other synoptic-scale features.
And, they can forecast soil moisture but they can't predict precipitation?
That is just amazing...what useful tools!
I'll say it again: If they are so good they can forecast CAPE on the storm scale, then they should be skillful for averaged (i.e., monthly or seasonal) long range forecasts (i.e., 12 - 24 months) over regions (i.e., over the Plains).
Until the models can make consistently accurate forecasts as outlined above, there is zero reason to believe they can make "averaged" storm scale CAPE and shear predictions 50 years into the future.
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Kevin Scharfenberg
Mike, the GCMs don't forecast anything on the mesoscale. The values of CAPE discussed in the paper were derived using downscaling techniques with synoptic-scale models (such as WRF, MM5, etc.) initialized from the larger-scale GCM background fields. If you'd just read the literature, you would know that.
For the GCM, the test of accuracy is the hindcast, that is, does the model produce a representative variety of large scale environments when averaged over time compared with what was actually observed over the hindcast period. They might not get the exact values of the indices for PDO, NAO or ENSO on a particular day correct, but they do get the range of values over time of these oscillations correct. The GCMs have passed the hindcast test as is well-documented from multiple studies in multiple institutions worldwide, so they have been run into the future to get a variety of future climate scenarios as well documented by the IPCC. Here's the famous example: http://www.grida.no/climate/ipcc_tar/wg1/figspm-4.htm
For a study like NASA's, a representative sample of GCM hindcast output over many tens of years can be used to initialize thousands of runs of a synoptic scale model such as the WRF to see if they can produce reasonable synoptic scale environments in hindcast mode. One metric might be the number of hours of CAPE in excess of 500 J/kg in Wichita Kansas over a 10 year period. If the downscaled models are successful in doing that, we can observe how they change when run into the future. Of course we don't have to use one model, we could use a variety, use ensembles, and use different extreme GCM background fields to get a variety of scenarios. This has been done at multiple institutions and is making it into the literature now.
If a downscaled model succesfully hindcast the number of days of 500+ CAPE in Wichita in the 1950-2000 period and that same model shows a significant increase in the number of days in the 2050-2100 period, I'd say it's reasonable to conclude the probability of supercells in Wichita is higher in the latter period.
Others might say it's a commie liberal conspiracy and post links to irrelevant newspaper articles or make snide remarks. It's left to the reader to decide what constitutes reasonable scientific discussion.
Mike Smith
Sorry, doesn't cut it. Looking backward, the winner of the Super Bowl is a fabulous predictor of stock market behavior.
Forbes Newsletter Watch
Super Bowl Stock Superstition
John Dobosz, 01.28.04, 11:00 AM ET
NEW YORK - A win on Sunday by the New England Patriots in Super Bowl XXXVIII might help ease the pain of Boston fans who watched their Red Sox fall victim yet again to the "Curse of the Bambino" last October in Yankee Stadium. But a Patriot victory over the Carolina Panthers would also suggest that the bull market of 2003 is about to come to a screeching halt in 2004--at least according to one indicator with an 81% success rate.
The predictor: When an original AFL team wins the Super Bowl stocks go down and when an original NFL team wins the Super Bowl stocks go up during that calendar year.
The fact that something works backward does not mean it will work forward, which has been proven over and over in financial modeling. See, for example, www.physorg.com/news11164.html "Physicists Predict the Stock Market." As far as I have been able to determine (and I have looked at a number of these) none of the models derived from "look back" data that have not also been independently verified looking forward have worked in forecast mode. In fact, if you Google "stock market models" you can find a number of these predictions that have crashed and burned...some rather spectacularly.
Predicting a single variable (i.e., the S&P 500) a year ahead of time is, theoretically, a much simpler task than predicing a multivariable parameter like severe thunderstorm intensity. The look back -----> apply technique to get results "x" years into the future has no credibility unless there is a foundation that the model works in "forecast" mode. It is nothing more than an interesting, "what if scenario" to use the words of Judy Curry's recent climateaudit.com post on the topic of IPCC "forecasts."
While scientific discussion and analysis should continue in every field, something is not established as science fact until it is tested and repeatable by any researcher who "does A then B with the result being X" every time.
Contending that the GCM's have skill in predicting severe thunderstorm intensity 50 years from now is not science. It is "faith."
And, if anyone is curious, the Super Bowl predictor was wrong. The Pats (original AFL) beat the Panthers so the market should have had a down year. The Dow was up 0.85% for 2004.
Kevin Scharfenberg
Ahh, and thus we come to the crux of Mr. Smith's confusion.
The football/stock market analogy is talking about a single point forecast, that is, whether 2004 will be positive or negative, based on the hindcast. Likewise you complain about a point forecast, intensity of severe storm forecasts in one future year. Both completely miss the point of what's going on. Essentially, it's a basic lack of understanding about the difference between weather and climate. We're talking about ranges, averages and probabilities over time, not point forecasts in time or space.
In addition, there is no physical connection between the two main variables in the analogy, the stock market and football. Whereas there ARE measurable physical relationships between the variables used in the GCM and the things being forecast, as is hopefully obvious to scientists reading this.
Well obviously forecasting in the single parameter space is less complicated than in the multi-parameter space, but since when is "it's too hard!" been a valid excuse? Judy Curry has it exactly right, but it's something a lot of deniers seem to have trouble understanding or accepting: when taken together the GCMs (and their downscaled children models) provide a range of possible climate scenarios. There's nothing striking, controversial, or surprisng about that. No one is pretending we can forecast the weather on 12 December 2062 over Walla Walla.
I guess one could go see how one of the oldest climate predictions out there published by Hansen et al. in 1988 fared ( http://pubs.giss.nasa.gov/abstracts/1988/Hansen_etal.html ). Turns out the temperature prediction has been remarkably correct (http://www.pnas.org/cgi/content/full/103/39/14288)!
How ridiculous. Are daily weather forecast model ensembles not real science and worthless because they don't come up with exactly the same result each time, but a range of solutions from which probabilities can be derived?
Which is why the "librul conspiracy" (er, climate scientists, LMAO) refers to the results of the GCMs an downscaled models as "scenarios" and not "fact". That said, various versions of GCMs have been run at numerous institutions worldwide and come up with a similar RANGE in results (as discussed by IPCC), which IS a form of consensus from which conclusions can be drawn. That is, an extremely high probability that average global temperatures will be warmer in the future.
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Mike Smith
So, when Kevin Trenberth of NCAR, a member in good standing of the IPCC, writes on June 4, 2007:
I have often seen references to predictions of future climate by the Intergovernmental Panel on Climate Change (IPCC), presumably through the IPCC assessments (the various chapters in the recently completed Working Group I Fourth Assessment can be accessed through this listing). In fact, since the last report it is also often stated that the science is settled or done and now is the time for action.
In fact there are no predictions by IPCC at all. And there never have been. The IPCC instead proffers “what if†projections of future climate that correspond to certain emissions scenarios. There are a number of assumptions that go into these emissions scenarios. They are intended to cover a range of possible self consistent “story lines†that then provide decision makers with information about which paths might be more desirable. But they do not consider many things like the recovery of the ozone layer, for instance, or observed trends in forcing agents. There is no estimate, even probabilistically, as to the likelihood of any emissions scenario and no best guess.
Even if there were, the projections are based on model results that provide differences of the future climate relative to that today. None of the models used by IPCC are initialized to the observed state and none of the climate states in the models correspond even remotely to the current observed climate. In particular, the state of the oceans, sea ice, and soil moisture has no relationship to the observed state at any recent time in any of the IPCC models. There is neither an El Niño sequence nor any Pacific Decadal Oscillation that replicates the recent past; yet these are critical modes of variability that affect Pacific rim countries and beyond. The Atlantic Multidecadal Oscillation, that may depend on the thermohaline circulation and thus ocean currents in the Atlantic, is not set up to match today’s state, but it is a critical component of the Atlantic hurricanes and it undoubtedly affects forecasts for the next decade from Brazil to Europe. Moreover, the starting climate state in several of the models may depart significantly from the real climate owing to model errors. I postulate that regional climate change is impossible to deal with properly unless the models are initialized.
The current projection method works to the extent it does because it utilizes differences from one time to another and the main model bias and systematic errors are thereby subtracted out. This assumes linearity. It works for global forced variations, but it can not work for many aspects of climate, especially those related to the water cycle. For instance, if the current state is one of drought then it is unlikely to get drier, but unrealistic model states and model biases can easily violate such constraints and project drier conditions. Of course one can initialize a climate model, but a biased model will immediately drift back to the model climate and the predicted trends will then be wrong. Therefore the problem of overcoming this shortcoming, and facing up to initializing climate models means not only obtaining sufficient reliable observations of all aspects of the climate system, but also overcoming model biases. So this is a major challenge.
So, these GCM's that do not "remotely" correspond to today's climate will somehow right themselves 20 years in the future and come up the correct answers for the real life non-linear atmosphere. And we are so confident in the accuracy of those answers we should use them as the basis to spend $100,000,000,000 to mitigate GW.
Sorry, from where I sit this is not science. It is "faith."
I have often seen references to predictions of future climate by the Intergovernmental Panel on Climate Change (IPCC), presumably through the IPCC assessments (the various chapters in the recently completed Working Group I Fourth Assessment can be accessed through this listing). In fact, since the last report it is also often stated that the science is settled or done and now is the time for action.
In fact there are no predictions by IPCC at all. And there never have been. The IPCC instead proffers “what if†projections of future climate that correspond to certain emissions scenarios. There are a number of assumptions that go into these emissions scenarios. They are intended to cover a range of possible self consistent “story lines†that then provide decision makers with information about which paths might be more desirable. But they do not consider many things like the recovery of the ozone layer, for instance, or observed trends in forcing agents. There is no estimate, even probabilistically, as to the likelihood of any emissions scenario and no best guess.
Even if there were, the projections are based on model results that provide differences of the future climate relative to that today. None of the models used by IPCC are initialized to the observed state and none of the climate states in the models correspond even remotely to the current observed climate. In particular, the state of the oceans, sea ice, and soil moisture has no relationship to the observed state at any recent time in any of the IPCC models. There is neither an El Niño sequence nor any Pacific Decadal Oscillation that replicates the recent past; yet these are critical modes of variability that affect Pacific rim countries and beyond. The Atlantic Multidecadal Oscillation, that may depend on the thermohaline circulation and thus ocean currents in the Atlantic, is not set up to match today’s state, but it is a critical component of the Atlantic hurricanes and it undoubtedly affects forecasts for the next decade from Brazil to Europe. Moreover, the starting climate state in several of the models may depart significantly from the real climate owing to model errors. I postulate that regional climate change is impossible to deal with properly unless the models are initialized.
The current projection method works to the extent it does because it utilizes differences from one time to another and the main model bias and systematic errors are thereby subtracted out. This assumes linearity. It works for global forced variations, but it can not work for many aspects of climate, especially those related to the water cycle. For instance, if the current state is one of drought then it is unlikely to get drier, but unrealistic model states and model biases can easily violate such constraints and project drier conditions. Of course one can initialize a climate model, but a biased model will immediately drift back to the model climate and the predicted trends will then be wrong. Therefore the problem of overcoming this shortcoming, and facing up to initializing climate models means not only obtaining sufficient reliable observations of all aspects of the climate system, but also overcoming model biases. So this is a major challenge.
So, these GCM's that do not "remotely" correspond to today's climate will somehow right themselves 20 years in the future and come up the correct answers for the real life non-linear atmosphere. And we are so confident in the accuracy of those answers we should use them as the basis to spend $100,000,000,000 to mitigate GW.
Sorry, from where I sit this is not science. It is "faith."
