Publication Of “Comments on ‘A Unified Modeling Approach to Climate System” By R. A. Pielke Sr And “Reply” By Hurrell Et Al 2010

After a year and a half (- since September 24 2009 – see), the Bullein of the American Meterological Society has finally published my Comment on the article

James Hurrell, Gerald A. Meehl, David Bader, Thomas L. Delworth, Ben Kirtman, Bruce Wielicki
Bulletin of the American Meteorological Society, 2009: A Unified Modeling Approach to Climate System Prediction; Volume 90, Issue 12 (December 2009) pp. 1819-1832

My article is

Comments on “A Unified Modeling Approach to Climate System Prediction” by Roger A. Pielke Sr.
http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS2975.1

and the Hurrell at al reply is

Reply –  James W. Hurrell, Gerald A. Meehl, Dave Bader, Thomas L. Delworth, Ben Kirtman, Bruce Wielick.
http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS3118.1

I am commenting on the Hurrell et al Reply below. I have excerpted text from their Reply and commented below each excerpt

“Modeling evidence to date demonstrates long-term climate change is primarily a boundary value problem associated with changes in radiative forcing.”

This statement conflicts with the extensive evidence that climate is significantly affected by forcings beyond radiative forcings. For example, in

National Research Council, 2005: Radiative forcing of climate change: Expanding the concept and addressing uncertainties. Committee on Radiative Forcing Effects on Climate Change, Climate Research Committee, Board on Atmospheric Sciences and Climate, Division on Earth and Life Studies, The National Academies Press, Washington, D.C., 208 pp

it is reported that

“Several types of forcings—most notably aerosols, land-use and land-cover change, and modifications to biogeochemistry—impact the climate system in nonradiative ways, in particular by modifying the hydrological cycle and vegetation dynamics. Aerosols exert a forcing on the hydrological cycle by modifying cloud condensation nuclei, ice nuclei, precipitation efficiency, and the ratio between solar direct and diffuse radiation received. Other nonradiative forcings modify the biological components of the climate system by changing the fluxes of trace gases and heat between vegetation, soils, and the atmosphere and by modifying the amount and types of vegetation. No metrics for quantifying such nonradiative forcings have been accepted. Nonradiative forcings have eventual radiative impacts, so one option would be to quantify these radiative impacts. However, this approach may not convey appropriately the impacts of nonradiative forcings on societally relevant climate variables such as precipitation or ecosystem function.”

The recently (2010) adopted official American Meteorological Society statement Inadvertent Weather Modification contains the text

“The cumulative changes in surface and atmospheric heat and moisture profiles [from aerosol radiative effects, cloud-mediated effects of aerosols, and changes in land use] modify atmospheric circulation and weather patterns on all scales, including synoptic storm tracks, in ways that are just beginning to be explored. In the aggregate, these changes can affect air quality, ecosystems, and water resources. The cumulative impacts of inadvertent weather modification may thus result in local or regional-scale climatic alterations superimposed on, and interacting with, natural and GHG-induced climate variability and change”

and

” High-priority research and new technological capabilities are required to improve understanding of the impacts of inadvertent weather modification………..research efforts on unintended weather modification should be recognized as addressing parts of the broader question of climate variability and change, which crosses geopolitical boundaries.”

Hurrell et al continue in their Reply

Pielke (2010) confuses the distinction between predicting the evolution of individual weather events beyond two weeks or so and the possibility of predicting changes in the statistics of weather events. Changes in forcing external to the climate system, as well as the amplification or diminution of the resulting changes in climate due to feedback mechanisms, can lead to predictable changes in weather statistics.

Unfortunately, the confusion is not mine.  The only difference between weather forecasts of daily weather and the forecasts of the statistics of weather (i.e., “climatology) is the averaging time. For example, a 24 hour average temperature for tomorrow, January 20 2011 is clearly considered weather (an average over 24 hours). However, so is the 2011-2020 average temperature for those ten January 20ths.

Hurrell et al also write

Consider the proven ability of climate models to simulate the annual cycle of seasonal variations (i.e., the changes in climate from winter to summer) or their ability to capture past excursions of climate resulting from changes in both natural and anthropogenic forcing, including the amount of solar energy reaching Earth, the amount of particulate matter in the atmosphere from volcanic eruptions, and atmospheric concentrations of anthropogenic gases and particles. The impressive fidelity of the twentieth-century climate simulations assessed in the latest report of the Intergovernmental Panel on Climate Change (Solomon et al. 2007) is a good example….

The models have been successful in simulating the annual cycle.   However, there has not been skill in predicting changes in the climate system despite what Hurell et al wrote. As just one (excellent) example, the paper

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.

concludes that

We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe.We also spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections are also poor.

Hurrell et al also write

“….there is ample evidence that climate models can capture nonlinear change thresholds and feedbacks (e.g., Holland et al. 2006; Pitman and Stouffer 2006).”

We report in our paper (with specific examples)

Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox, H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas, 2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s climate system. Climatic Change, 65, 11-38

that the

“Earth’s climate system is highly nonlinear: inputs and outputs are not proportional, change is often episodic and abrupt, rather than slow and gradual, and multiple equilibria are the norm….there is a relatively poor understanding of the different types of nonlinearities, how they manifest under various conditions .and whether they reflect a climate system driven by astronomical forcings, by internal feedbacks, or by a combination of both.”

The claim by Hurrell et al that “climate models can capture nonlinear change thresholds and feedbacks”  grossly overstates their capabilities. They have failed, for example, to skillfully predict (or even simulate) the time evolution of such major climate features as El Niño, La Niña, the Pacific Decadal Ocsillation and the North Atlantic Oscillation. One of the examples that Hurrell et al present to bolster their claim that “that climate models can capture nonlinear change thresholds”   [Holland et al, 2006: Future abrupt reductions in summer arctic sea ice] is a model prediction for the coming decades! 

The excerpt from Hurrell et al is

“We do agree with Pielke (2010) that the effects of initial conditions and the presence of significant nonlinearities become more important when regional climate change over the next few decades is considered…”

This statement appears to almost completely refute what they reported earlier in their Reply where they wrote 

“Modeling evidence to date demonstrates long-term climate change is primarily a boundary value problem associated with changes in radiative forcing.”

Thus while I appreciate the opportunity to have a Comment/Reply interaction with the authors of the Hurrell et al 2009 paper. they remain unresolved issues they have not yet adequately addressed.

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