Climate Model Predictions and Adaptation
February 18th, 2008Posted by: Roger Pielke, Jr.
At a recent conference on adaptation in London, I co-authored a presented paper (with Suraje Dessai, Mike Hulme, and Rob Lempert) on the the role of climate model forecasts in support of adaptation. Our argument is that climate models don’t forecast very well on time and spatial scales of relevance to decision makers facing adaptation choices, and even if they did, given irreducible uncertainties robust decision making is a better approach than seeking to optimize.
For more evidence of why it is that climate models are of little predictive use in adaptation decision making, consider the recent discussion of cooling in Antarctica and the southern oceans from RealClimate:
The pioneer climate modelers Kirk Bryan and Syukuro Manabe took up the question with a more detailed model that revealed an additional effect. In the Southern Ocean around Antarctica the mixing of water went deeper than in Northern waters, so more volumes of water were brought into play earlier. In their model, around Antarctica “there is no warming at the sea surface, and even a slight cooling over the 50-year duration of the experiment.” In the twenty years since, computer models have improved by orders of magnitude, but they continue to show that Antarctica cannot be expected to warm up very significantly until long after the rest of the world’s climate is radically changed.
Bottom line: A cold Antarctica and Southern Ocean do not contradict our models of global warming. For a long time the models have predicted just that.
Today CSIRO in Australia reports that southern oceans have in fact been warming:
The longest continuous record of temperature changes in the Southern Ocean has found that Antarctic waters are warming and sea levels are rising, an Australian scientist said Monday.
I have no doubt that these observations of warming will also be found, somehow, to be consistent with predictions of climate models. And that is the problem; climate scientists, especially those involved in political advocacy for action on climate change, steadfastly refuse to describe what observations over the short term (i.e., when most adaptation decisions are made) would be inconsistent with model predictions. So all observations are consistent with predictions of climate models.
The reason for this situation of total ambiguity is a perceived need to maintain the public credibility of climate model predictions over the very long term in support of political action on climate change in the face of relentless attacks for politically motivated skeptics. So what do we get? Nonsensical and useless pronouncements such as a cooling southern ocean and a warming southern ocean are both consistent with climate model predictions, thus we can trust the models.
The lesson for decision makers grappling with adaptation to future climate changes? Make sure that your decisions are robust to a wide range of future possibilities, and use caution in seeking to optimize based on this or that prediction of the near-term future.
February 18th, 2008 at 4:29 am
Here is my question. We are already uncertain about everything else about the future-population, economics, in fact we were uncertain about future environmental conditions even before we understood climate change as an issue.
As a person engaged in planning at the local and regional level, I don’t have time to keep up with the adaptation literature. Can I just fall back to the existing uncertainty in decisionmaking literature (scenarios, etc.) or is there something unique about uncertainty around climate change that is worth paying attention to? Do we know if people in the adaptation community are familiar with the existing literature on uncertainty in decisionmaking? Or are they possibly reinventing it?
February 18th, 2008 at 10:30 am
docpine- Great question. My answer is that it depends. On hurricanes, and disaster more generally, I’ve argued that climate change uncertainties are lost in the noise of the far more significant influences of growing population and wealth at risk.
But other contexts climate may prove decisive, e.g., for dryland farming. We’ve argued via our SPARC project that what needs to be done is a sensitivity analysis of impacts of concern to various factors that influence those impacts.
Too often the climate impacts literature holds everything constant and lets climate vary/change to assess the unique impact of climate. This is fine, as far as it goes, but neglects the sensitivity to multiple factors.
So yes we have to pay attention to climate change, but not climate change alone. This makes the job of the local and regional planner that much more difficult I fear.
February 19th, 2008 at 9:40 am
Holding everything else constant and just letting climate change is asking for trouble. We also have peak oil with peak coal to follow in 2025 CE, according to some. We seem to have a much greater demand for metals than the minable supply. The increasing population needs more potable water. And so it goes.
Glad I’m not a regional planner. Roger Pielke, Jr., speaks my mind in the comment just above.
February 19th, 2008 at 1:58 pm
Roger, I couldn’t agree more with your conclusion that “given irreducible uncertainties robust decision making [regarding adaptation measures] is a better approach than seeking to optimize.” Long time ago, in a paper in Climatic Change, I had outlined a few criteria for selecting or developing adaptation strategies and measures. One of these criteria was that the measures/strategies should be “independent of results from site-specific impacts assessments, which are unlikely to be available with sufficient confidence at appropriate temporal and spatial resolutions for several years, for either their justification or implementation” (1). And it’s precisely because of this that my policy mantra over the past couple of decades has been: (a) reduce vulnerability to climate-sensitive problems that might be exacerbated by climate change (e.g., extreme events, hunger, vector-borne diseases), and (b) enhance society’s resilience in general to all manners of adversity including climate change by enhancing adaptive capacity (by broadly enhancing economic development, human capital and technological prowess).
(1) Goklany, IM. 1995. “Strategies to Enhance Adaptability: Technological Change, Economic Growth and Free Trade.” Climatic Change 30: 427-449.
February 19th, 2008 at 2:01 pm
Roger, I couldn’t agree more with your conclusion that “given irreducible uncertainties robust decision making [regarding adaptation measures] is a better approach than seeking to optimize.” Long time ago, in a paper in Climatic Change, I had outlined a few criteria for selecting or developing adaptation strategies and measures. One of these criteria was that the measures/strategies should be “independent of results from site-specific impacts assessments, which are unlikely to be available with sufficient confidence at appropriate temporal and spatial resolutions for several years, for either their justification or implementation” (1). And it’s precisely because of this that my policy mantra over the past couple of decades has been: (a) reduce vulnerability to climate-sensitive problems that might be exacerbated by climate change (e.g., extreme events, hunger, vector-borne diseases), and (b) enhance society’s resilience in general to all manners of adversity including climate change by enhancing adaptive capacity (by broadly enhancing economic development, human capital and technological prowess).
(1) Goklany, IM. 1995. “Strategies to Enhance Adaptability: Technological Change, Economic Growth and Free Trade.” Climatic Change 30: 427-449.
February 19th, 2008 at 3:04 pm
My apologies for the duplicate posting above.
On a separate matter, I am puzzled by the statement: “A cold Antarctica and Southern Ocean do not contradict our models of global warming. For a long time the models have predicted just that.” This statement is an amalgam of a straw man argument and revisionism. Regarding the former (i.e., straw man argument), as far as I know, no one has ever claimed that the Antarctica and the Southern Ocean wouldn’t be cold. The issue is whether these areas would be warmer than they were.
With regard to the revisionism aspect, it may be true that some models may have predicted that the Antarctica may cool, but this point was definitely not evident from any of the IPCC assessments. In fact, all the IPCC reports show the Antarctica warming:
1. IPCC’s 1990 Scientific Assessment notes that “All models show enhanced warming in higher latitudes in late Autumn and Winter” (p. 140). “Winter and annual warmings are largest in high latitudes” (p. 143). See also figures on pp. 140-142.
2. IPCC’s Climate Change1995, The Science of Climate Change. See Fig. 17 (p. 38), which compares the increase in temperature from 1955-1974 to 1975-1994 , and Figs. 22-23 which shows future temperature increases.
3. IPCC’s 2001 Synthesis Report shows model results indicating not only that that Antarctica would warm but that it would, by and large, warm greater than the average (pp. 65, 207, 208).
4. IPCC’s 2007 WG I Summary for Policy Makers also shows that the Antarctica would be warming (p. 15).
February 22nd, 2008 at 11:37 am
Indur
The full fourth IPCC report says
Observations: Surface and Atmospheric Climate Change Page 239
Consistent with
observed changes in surface temperature, there has been an
almost worldwide reduction in glacier and small ice cap (not
including Antarctica and Greenland) mass
Page 247
If the GISS data for 2005 are averaged only south
of 75̊N, then 2005 is cooler than 1998. In addition, there were
relatively cool anomalies in 2005 in HadCRUT3 in parts of
Antarctica and the Southern Ocean, where sea ice coverage (see
Chapter 4) has not declined
Page 248
Temperatures over mainland Antarctica (south of 65̊S) have
not warmed in recent decades (Turner et al., 2005), but it is
virtually certain that there has been strong warming over the
last 50 years in the Antarctic Peninsula region
Page 295
contrasting trends of strong warming in the Antarctic Peninsula
and a cooling over most of interior Antarctica
This observational data seems quite contradictory to your quotes and they are both from the IPCC. How can that be surely observations means the models are wrong. The parts they say are melting are up to 6500km from the pole so I hope they continue to do so.
March 14th, 2008 at 7:11 pm
I absolutely agree with the premise (climate models aren’t helpful on adaptive scales) and the conclusion (robust policies are needed) but I don’t think the evidence presented here supports the argument.
The RC/CSIRO comparison strikes me as a strawman that’s neither internally consistent nor sufficient to prove the larger point about adaptation.
The Manabe & Bryan study was hardly a forecast of a cooling southern ocean. Judging by the description in Manabe & Stouffer (2007), it wasn’t even a 3D model, and I very much doubt the results were from an ensemble. The small degree of cooling mentioned by RC could be natural variability or otherwise spurious.
The other statements in the RC post mention a cold Antarctic, but this could mean a variety of things, including “cooler than before” or “less warming than elsewhere.” It seems from other posts (http://www.realclimate.org/index.php/archives/2007/08/regional-climate-projections ) that they mean the latter, a position which is consistent with the IPCC regional results, e.g. AR4 WG1 Ch.11 fig. 11.21.
In that case, there’s no evidence here that the CSIRO results are warmer or cooler than one would expect given the global trend, polar amplification, and the Southern Ocean thermal lag discussed at RC.
Whether or not “climate scientists … steadfastly refuse to describe what observations over the short term … would be inconsistent with model predictions,” it would be straightforward to check for oneself by visiting the PCMDI CMIP3 archive to retrieve raw model results. Given the availability of vast quantities of output, it should be quite easy to determine whether “all observations are consistent with predictions of climate models” and why.
One need not invoke selfish or political motives to understand why there is predictive ambiguity on the adaptive time scale. That’s to be expected given small short-term signals, large variability, and uncertain measurement of the initial system state. See http://www.sciencemag.org/cgi/content/full/317/5835/207
It’s exacerbated by the fact that regional downscaling is difficult and not uniformly available.