Guest post by Marcel Crok
A few months ago we made the launch of the international discussion platform . This week we start the third dialogue about the (added) value of regional climate models. We have three excellent participants joining this discussion: Bart van den Hurk of KNMI in The Netherlands who is actively involved in the KNMI scenario’s, Jason Evans from the University of Newcastle, Australia, who is coordinator of Coordinated Regional Climate Downscaling Experiment (CORDEX) and Roger Pielke Sr. who through his research articles and his weblog is well known for his outspoken views on climate modelling. Below you find the introductory article on which the three experts had to base their guest blog. After reading that head over to the dialogue.
Introductory article: Are climate models ready to make regional projections?
Climate models are vital tools for helping us understand long-term changes in the global climate system. These models allow us to make physically plausible projections of how the climate might evolve in the future under given greenhouse gas emission scenarios.
Global climate projections for 2050 and 2100 have, amongst other purposes, been used to inform potential mitigation policies, i.e. to get a sense of the challenge we are facing in terms of CO2 emission reductions. The next logical step is to use models for adaptation as well. Stakeholders have an almost insatiable demand for future regional climate projections. These demands are driven by practical considerations related to freshwater resources, especially ecosystems and water related infrastructure, which are vulnerable to climate change.
Global climate models (GCMs) though have grid scales that are quite coarse (>100 km). This hampers the reconstruction of climate change at smaller scales (regional to local). Regions (the size of e.g. the Netherlands) are usually covered by only a few grid points. A crucial question therefore is whether information from global climate models at this spatial scale is realistic and meaningful, in hind cast and/or for the future.
Hundreds of studies have been published in the literature [1] presenting regional projections of climate change for 2050 and 2100. The output of such model simulations is then used by the climate impacts community to investigate what potential future benefits or threats could be expected. However several recent studies cast doubt whether global model output is realistic on a regional scale, even in hind cast. [2-5]
So a legitimate question is whether global and/or regional climate models are ready to be used for regional projections? Is the information reliable enough to use for all kinds of medium to long term adaptation planning? Or should we adopt a different approach?
To improve the resolution of the models other techniques, such as regional climate models (RCMs), or downscaling methods, have been developed. Nesting a regional climate model (with higher spatial resolution) into an existing GCM is one way to downscale data. This is called dynamical downscaling. A second way of downscaling climate model data is through the use of statistical regression. Statistical downscaling is based on relationships linking large-scale atmospheric variables from either GCMs or RCMs (predictors)and local/regional climate variables (predictands) using observations. [6]
Both methods are widely used inside the regional modelling community. The higher spatial resolution allows a more detailed representation of relevant processes, which will hopefully, but not necessarily, result in a “better” prediction. However RCMs operate under a set of boundary conditions that are dependent on the parent GCM. Hence, if the GCM does not do an adequate job of reproducing the climate signal of a particular region, the RCM will simply mimic those inaccuracies and biases. A valid question therefore is if and how the coupling of a RCM to a GCM can provide more refined insights. [7,8]
Recently Kerr [9] caused quite a stir in the regional modelling community by raising doubts about the reliability of regional model output. A debate about the reliability of model simulations is quickly seen as one between proponents and sceptics of anthropogenic global warming. However as Kundzewicz [10] points out “these are pragmatic concerns, raised by hydrologists and water management practitioners, about how useful the GCMs are for the much more detailed level of analysis (and predictability) required for site-specific water management decisions (infrastructure planning, design and operations).”
See Climate dialogue
http://www.climatedialogue.org/are-regional-models-ready-for-prime-time/
The focus of this Climate Dialogue will be on the reliability of climate simulations for the regional scale. An important question will be if there is added value from regional climate downscaling.
More specific questions:
1) How realistic are simulations by GCM’s on the regional scale?
2) Do some parameters (e.g. temperature) perform better than others (e.g. precipitation)?
3) Do some regions perform better than others?
4) To what extent can regional climate models simulate the past?
5) What is the best way to determine the skill of the hind cast?
6) Is there added value of regional models in comparison with global models?
7) What are the relative merits of dynamical and statistical downscaling?
8) How should one judge projections of these regional models?
9) Should global/regional climate models be used for decisions concerning infrastructure development? If so how? If not, what should form a better scientific base for such decisions?
References:
[1] The CMIP3 and CMIP5 list of publications is a good starting point, see http://www-pcmdi.llnl.gov/ipcc/subproject_publications.php and http://cmip.llnl.gov/cmip5/publications/allpublications
[2] G.J. van Oldenborgh, F.J. Doblas Reyes, S.S. Drijfhout, and E. Hawkins, “Reliability of regional climate model trends”, Environmental Research Letters, vol. 8, pp. 014055, 2013. http://dx.doi.org/10.1088/1748-9326/8/1/014055
[3] Anagnostopoulos, G. G., Koutsoyiannis, D., Christofides, A., Efstratiadis, A. &Mamassis, N. (2010) A comparison of local and aggregated climate model outputs with observed data. Hydrol. Sci. J. 55(7), 1094–1110
[4] 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
[5] J. Bhend, and P. Whetton, “Consistency of simulated and observed regional changes in temperature, sea level pressure and precipitation”, Climatic Change, 2013. http://dx.doi.org/10.1007/s10584-012-0691-2
[6] Wilby, R. L. (2010) Evaluating climate model outputs for hydrologicalapplications – Opinion. Hydrol. Sci. J. 55(7), 1090–1093
[7] Kundzewicz, Zbigniew W. and Stakhiv, Eugene Z.(2010) ‘Are climate models “ready for prime time” inwater resources management applications, or is more research needed?’, Hydrological Sciences Journal, 55: 7, 1085 —1089
[8] Pielke, R. A. S., and R. L. Wilby, 2012: Regional climate downscaling: What’s the point? Eos Trans.AGU, 93, PAGE 52, doi:201210.1029/2012EO050008
[9] R.A. Kerr, “Forecasting Regional Climate Change Flunks Its First Test”, Science, vol. 339, pp. 638-638, 2013. http://dx.doi.org/10.1126/science.339.6120.638
[10] Kundzewicz, Zbigniew W. and Stakhiv, Eugene Z.(2010) ‘Are climate models “ready for prime time” in water resources management applications, or is more research needed?’, Hydrological Sciences Journal, 55: 7, 1085 —1089
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no
omnologos, you write “no”.
If you go to the Climate Dialogue site, you will find that this is precisely what Roger Pielke Sr said.
There are a number of studies of the Sahel region of Africa which would suggest neither dynamic nor atatistical downscaling has done a good job with water forecasting even on short time scales ( years). It therefore stretches credulity to think they could perform on decades time scales needed for infrastructure planning.
I posted this comment:
I looked into the CET variability, as the most scrutinised and longest regional set of data, also having good correlation with N. Hemisphere and some with global variability. Graphic results and extrapolation into future (with very short comments) are shown here:
http://www.vukcevic.talktalk.net/CET-NV.htm
The first thing to say is “What CO2 emission reductions”, why would they possibly be necessary?
Second “What Warming”?
A complete and utter waste of good computers and computing time.
I have a simple test for these regional models. Where I live, there are two suburbs less than 5km apart. The one is essentially a desert – it receives on average less than 250mm rain/a. The other is almost a floodplain – it receives over 2000mm annually. I have yet to find a model that can come near describing these observations.
A C Osborn says:
May 18, 2013 at 11:35 am
“The first thing to say is “What CO2 emission reductions”, why would they possibly be necessary?
Second “What Warming”?
A complete and utter waste of good computers and computing time.”
The “Climate Dialogue site” was launched with much fan fare by both sides… to which it was quickly showed to be another doomsday cult site trying it best to pretend to be a science site.
Many ppl posted a whole mile long list of problems with the way they are doing things and so far they have not listened to a single one as far as i know.
ALL of the “discussions” or propaganda as called by normal ppl assume
1. global warming is real and caused by humans.
2. We’re all going to die
3. At no point to they get into the science at all.
4. At no point do they even attempt to define global warming “theory”.
5. Pretty much no basic science at all… its all “post processed” crap.
6. They heavily censor/section/”adjust” the comment section so that only “experts” get a say.
In the end the site is a joke and not really worth dealing with. They are just looking for excuses to look “balanced” and best not to even bother dealing with them.
I know there is a model that does clouds now. One of the guys who wrote the anti AGW book made one, I don’t remember his name.
I think the guy’s name is Postman. One of the hobby sites I go to has a science section and someone had a block quote from him, about how the model generates clouds.
Thank you Jim
The one reason that convinces me regional models aren’t ready yet, is that they aren’t any good at predicting the season’s weather.
This one jumped right off the page for me…..
From Guest Bart van den Hurk
Climate predictions versus climate scenarios
The notion that a tool – an RCM – may possess shortcomings in its predictive skill, but simultaneously prove to be a valuable tool to support narratives that are relevant to policy making and spatial planning can in fact be extended to highlighting the difference between “climate predictions” and “climate scenarios”.
You have GOT to be shi,?b>tting me.
“To support narratives that are relevant to policy making ……..”
Jesus wept.
What a crock, models, models, models. If you don’t understand or even have the slightest idea how our climate works, it’s ridicules and delusional to think you can predict a chaotic system with a computer program and a herculean task to predict regional climate change.
Just around my area there must be half a dozen different climate variations, have we gone so insane in the membrane to think this is even remotely possible? Holy cow, give your heads a shake, all this for a .5 degree of temperature change in 150 years?
Who would of thought weather prediction would be the down fall of mankind……… welcome the computer age.
Back in the late 1960’s the government built a super computer at the University of Illinois to predict weather. Lots of good jobs, but poor weather forecasting as I was told by a participating computer manufacturer. We’re a lot smarter, but still ignorant about the weather.
How much do you want to be that when the tempature starts dropping over the next few decades due to the sun going quiet all of these models are going to start trending downwards.
TomR,Worc,MA,USA says:
May 18, 2013 at 12:55 pm
“To support narratives that are relevant to policy making ……..”
Jesus wept.
vad Hurk is from Wageningen University. That says it all. Don’t take any notice.
omnologos says:
May 18, 2013 at 10:55 am
no
My thoughts exactly!
Why does anyone think that using the same basic input and assumptions from GCMs for RCMs would produce anything useful. It is so obvious that the assumptions in the GCMs are not adequate to derive even a reasonable projection of global climate. Reducing the spatial scale would only magnify the errors. The pac man computer geeks who now play with serious material should scrap the existing models and begin anew. I believe that CO2 is a minor player, maybe even less that the minimum now allocated. The sun, oceans and hydrologic cycle have to be better defined before any more money is wasted. Our children should not be raised in fear of something that may not even be real. But what do I know- I’m just the 70 year old elephant in the room- with a PhD in biogeography/climatology- and years of teaching meteorology and climatology at a university.
omnologos says:
May 18, 2013 at 12:43 pm
Thank you Jim
The one reason that convinces me regional models aren’t ready yet, is that they aren’t any good at predicting the season’s weather.
###############
Huh, having just participated in a study using regional climate data, I’ll have to say your characterization is flat wrong.
thank you Steven Mosher. I am looking forward to be contradicted by reality. I know for a fact that the first useful regional (seasonal) model will be a major hit in all newspapers.
Models which fail every time at less than 72 hours…
And they want to continue to base policy and now regional people movements and living arrangements on them..
Can anyone else see the UN AGENDA 21 looking back at them fro this mirror.?
>>regional projections of climate change for 2050 and 2100.<<
Utter fantasy.
Perhaps this would be a good point to observe that this year is the fiftieth anniversary of the publication of Edward Lorenz's seminal work “Deterministic nonperiodic flow”, which demonstrated the futility of such endeavours as that described above.
Ironically, he was a weatherman himself.
http://www.physicstoday.org/resource/1/phtoad/v66/i5/p27_s1?bypassSSO=1
and well, let s imaginethat one day some models were able to calculate the climate for a given period of time….It is not enough to say they are able to do the same again!!!!
what if a guy gave you ten times the results of a calculation but can explain exactly why he is correct???
The point is uncertainty …
This is one of those areas of study that is going in the wrong direction entirely (focusing on models instead of field research). Regional climate change (natural or otherwise) can best be detected using proxy measures. Bat populations, earth worms, grasshopper emergence, population, and size at end season, salmon runs, bud emergence, frost kill, wild game populations, snow melt dates in rivers, etc are all good ways to detect a trend and are useful 5 years out from the knee. They are less useful for predicting the next knee. These proxies are easily studied (though the researcher will get muddy) and are reliable. However, CO2 has such a small effect I wonder why people are studying it.
Hi Steve – You write
“Huh, having just participated in a study using regional climate data, I’ll have to say your characterization is flat wrong.”
Please be more specific. The post “Are regional models ready for prime time?” is on multi-decadal regional climate projections (what if predictions). Example(s) of peer reviewed studies that show skill in the prediction of changes in regional climate statistics (when the models are run in huindcast) are needed to not answer a “NO” to the question “Are regional models ready for prime time?” As far as I have seen in the literature, there are no papers that show such skill.
Indeed, as I summarize in the article http://pielkeclimatesci.files.wordpress.com/2013/05/b-18preface.pdf, there is little, if any skill, in multi-decadal global mode predictions (in hindcast) when they are run without observational (real world) constraints, even with respect to current climate on multi-year and multi-decadal time scales!
Roger Sr,
The growing semantics surrounding failed models (that is compared to reality. I feel I have to add this because of the BS about their utility [for what I wonder]) because of a bit player CO2 cast as the star. CAGW becoming climate change, eventhough the proponents always identify this change as being getting hotter because of CO2 (and methane at about 20ppb [i.e. 0.02ppm!]); extreme weather, weird weather….and this poppycock about ‘projection’ instead of prediction with error bars and uncertainties no less!
Please sceptics and proponents alike, let’s at least let the dictionary be the expert on the understanding of these words or a chaotic system described in chaotic language will destroy the remaining few tendrils of intelligent clear thought left (this may actually be the objective of the semantics and other agencies to shore up fantasy models – Obama fell for the 97% baloney when it was only 34% consensus). Projections don’t need or use models and they certainly don’t need error bars or % certainty. Predictions do. Secondly, if you are trying to provide scenarios of what might come to pass, with the state of our knowledge of climate science as measured by the surprises thrown in our faces by nature, we can’t leave out the possibility that we will be shiveringly cold for multiple decades or even a century or more, or worse.
The uncertainty isn’t just about how much hotter it is going to get. For starters, let’s drop the 95% confidence limits jazz. We’ve proven that we can’t even muster that. A few more % and you are 100% wrong! Finally the idea of a soul-searching dialogue that doesn’t put everything on the table is just another AGW propaganda tool. Why must we agree at the outset that CO2 is the main driver. Shouldn’t we be approaching an Epiphany on this issue – if the IPCC had used a 95% confidence level bounded by two horizontal lines from about AR2, we would have been all applauding them – they may have been right down the middle if there hadn’t be so many upward adjustments of temp over the last couple of decadesd.
All the discussion seems to revolve around failed models. Surely we should identify the failed modellers, you know the guys who create, feed and control the failed computer models. This process needs to get personal if we are to get any accountability because you can’t make an equation feel guilty.