Drought predictions for this century

In The National Science Foundation Funds Multi-Decadal Climate Predictions Without An Ability To Verify Their Skill Roger Pielke Sr. links GCM skill at predicting drought with natural variation:

2. “Future efforts to predict drought will depend on models’ ability to predict tropical SSTs.”

In other words, there is NO way to assess the skill of these models are predicting drought as they have not yet shown any skill in SST predictions on time scales longer than a season, nor natural climate cycles such as El Niño [or the PDO, the NAO, etc.].

This seems an convoluted turn of phrase. There are ways to assess the skill of these models — by comparing them with past drought frequency and severity. Such assessments show the models have NO skill at predicting droughts.

The assumption is that IF they were able to predict cycles like PDO etc. then they would be able to predict droughts. But clearly if we average over these cycles, there is still the little problem of overall trends in extreme phenomena, which accuracy at PDO etal. would not necessarily satisfy.

His argument that drought efficacy swings on PDO prediction is useful, however, as a basis for excluding applications of models for climate phenomena that rely on them.

Roger is perhaps being polite about misleading policymakers when he continues:

Funding of multi-decadal regional climate predictions by the National Science Foundation which cannot be verified in terms of accuracy is not only a poor use of tax payer funds, but is misleading policymakers and others on the actual skill that exists in predicting changes in the frequency of drought in the future.

The review by Dai favours the PDSI drought index:

The PDSI was created by Palmer22 with the intent to measure the cumulative departure in surface water balance. It incorporates antecedent and current moisture supply (precipitation) and demand (PE) into a hydrological accounting system. Although the PDSI is a standardized measure, ranging from about −10 (dry) to +10 (wet)…

I always search for the assessment of accuracy first, and as usual the skill of models gets a very little, non-quantitative coverage. Climate scientists are loath judge the models, preferring to cloak their results in paragraphs of uncertainty, and present “dire predictions” of GCMs in garish figures (his Figure 11).

They need to start acting like scientists and stop these misleading practises until it is shown by rigorous empirical testing, and for fundamental reasons, that the current GCMs are fit for the purpose of drought modelling.

Just to show I am not always negative, this recent report has a lot to recommend in it. The authors of “Climate variability and change in south-eastern Australia” do quite a good job of describing the climatological features impacting the area, and putting technical issues, climate, hydrology and social impact together in an informative report.

While they say:

The current rainfall decline is apparently linked
(at least in part) to climate change, raising the
possibility that the current dry conditions may
persist, and even possibly intensify (as has been the
case in south-west Western Australia).

They also admit they don’t know how to combine the output of multiple models:

Some research (Smith & Chandler, 2009) suggests that
uncertainties in climate projections can be reduced
by careful selection of the global climate models, with
less weight being given to models that do not simulate
current climate adequately. Other work suggests that
explicit model selection may not be necessary (Watterson,
2008; Chiew et al., 2009c). Further research is being
done to determine how to combine the output of global
climate models to develop more accurate region-scale
projections of climate change.

I would fault that there is no suggestion that anything other than GCMs might be used, and no evidence the GCMs perform better than a mean value. If a model does no better than the long term average then there is good reason to suppose it has no skill, and throw it out. This is called ‘benchmarking’, but its an alien concept to reject any GCM from the IPCC, apparently.

  • Roman Szeremeta

    Dr Post, the Program Leader of the SEACI Study, in The Australia, also referred to the situation in SW Australia apparently as some sort of validation. “Look, its already happening in WA!”
    Unfortunately for them, the 2009 Annual Report of the Scientific Committe Report on Antartic Reasearch (SCAR) puts it in context.
    “The work in progress indicates that southwest Western Australia experienced periods of higher mean winter rainfall, with high interdecadal variability during 1300 to 1600 AD, followed by lower mean but less variable winter rainfall from 1600 to 1900 AD, which is similar to the past 50 years (Goodwin, in prep.)…”

    So the change in rainfall pattern in SW Australia is part of a long term cyclical pattern going back 700 years, well beyond any influence of AGW.

  • http://pulse.yahoo.com/_JCW5TSCK2N2AFVXP4KYAGSHTZ4 Brian H

    It’s like the UN. Everyone gets an equal vote, no matter how clueless or conflicted.