date: Mon, 15 May 2000 13:15:58 -0600 (MDT) from: Dallas McDonald subject: review to: M.Hulme@uea.ac.uk Attached below are two emails that were sent to Dr. Michael C. MacCracken of the National Assessment Coordination Office at the U.S. Global Change Research Program (1) reviewing the Summary for Policymakers of the IPCC Working Group I's Third Assessment Report, and (2) a review of Chapter 10 entitled "Regional Climate Simulation -- Evaluation and Projections" from the same report. I would appreciate any feedback on issues that I have overlooked or overemphasized. With Best Regards, Roger A. Pielke, Sr. +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ >From dallas@cobra.ATMOS.ColoState.EDU Wed May 10 21:16:15 2000 Date: Mon, 8 May 2000 14:13:02 -0600 (MDT) From: Dallas McDonald To: Mike MacCracken Subject: REVIEW of SPM Dear Mike, I appreciate the opportunity to review the Summary for Policymakers (SPM) of the IPCC Working Group I's Third Assessment Report. As we have discussed in the past, I have very substantial concerns regarding the focus of the Report and its incomplete coverage of climate processes. I provided similar comments to the 1992 IPCC Supplement and the 1995 IPCC Report which were not addressed in the final report. The issues that I raise are important scientific points that, if addressed by the IPCC, would contribute to its authoritative role. My specific concerns with the SPM can be summarized as follows. *Landscape processes directly and indirectly significantly influence the Earth's climate system through biophysical, biogeochemical, and biogeographical effects. *Human-caused landuse change has an effect on local, regional, and global climate that is as significant as projected by the IPCC due to the radiative effect of anthropogenic inputs of greenhouse gases. *Since landscape processes (and other atmosphere-surface interactions) involve complex nonlinear feedbacks, the prediction of future climate involves much more than the radiative effect of human-caused increases of greenhouse gases. *The assessment of temperature trends using land-surface data, except for urbanization, has not considered how local and regional landuse change has altered the local and regional climate. The importance of landscape processes in the global climate system has been recently summarized in Pitman et al. (1999 and references therein). The importance of landscape processes in carbon sequestration and release is recognized in the SPM (e.g., line 50, page 5), which makes the exclusion of the influence of vegetation and soil dynamics on the Earth's energy and water budget all the more surprising. Wang and Eltahir (2000a,b), for example, discuss the critical role of biosphere-atmosphere interactions in the Sahel region of Africa, and the need to include biospheric processes as dynamic components of climate models. As carbon dioxide concentrations continue to increase, this enrichment will provide a more favorable environment for plant growth with, as of yet, unknown consequences on the Earth's climate system. Our initial work in the central grasslands of the United States using a coupled atmospheric-biogeochemical model (Eastman 1999; Eastman et al. 2000) indicates that the effect of doubled carbon dioxide would be improved water use efficiency and greater vegetation growth. The net effect, on time periods as short as a growing season according to the coupled models, would be a cooler daytime environment and a warmer nighttime. The role of human-caused landscape disturbance and change on the regional and global climate other than as a component in the carbon budget, is ignored in the SPM. Human-caused landscape change includes deforestation, overgrazing, agricultural activities, and reforestation. Leemans (1999), for example, shows that most landuse change occurred in the 1900s and that landuse change is accelerating (see Figure 1 of his paper). O'Brien (2000) provides additional information on the accelerating rate of tropical deforestation. Pitman and Zhao (2000) and Chase et al. (1996, 2000a) have presented results that indicate a substantial effect on the Earth's atmospheric circulation thousands of kilometers from where historical landscape changes occurred. These teleconnections in the model, for example, produce major shifts in the polar jet stream, with substantial higher latitude regions of warming and cooling. The importance of these two additional human perturbations to the climate system (landscape change, and the biological effect of increased carbon dioxide concentrations) complicate the prediction of the future climate. Climate change is not as simple as stated in the SPM (line 43, page 2 and following) which indicates that the radiative effect of increased greenhouse gases and aerosols dominate how the climate changes. The effect of pollution aerosols on cloud condensation nuclei and ice nuclei in clouds complicate prediction skill even further (Pielke 1984). In their paper discussing the effect of human activity on radiative forcing of climate change, Shine and Forster (1999) specifically state that "...climate change can occur due to non-radiative processes, such as land use changes ...; such changes are not considered here." Trenberth (1999) states that "Improving predictions of what the climate will be, not just with idealized scenarios but taking all factors (including solar radiation, land use change, aerosol effects, and biogeochemical feedbacks) into account is a high priority." The consequences of these additional human perturbations of the climate system, and the variety of feedbacks across a wide spectrum of time and space scales, will reinforce the conclusion of a "discernible human influence", but also limit our ability to predict the future climate. Pielke (2000) illustrates that the IPCC GCM simulations are more appropriately defined as sensitivity experiments (where only a subset of human perturbations) are performed. They should, therefore, be communicated to policymakers as a subset of possible future climate conditions. Pielke and Guenni (1999) discuss introducing a vulnerability perspective to assess what are the major environmental threats to specific resources. With this information, the climate community (and other members of the environmental science community) can assess whether the stakeholder needs are predictable or not. This approach would require that the SPM start with vulnerability assessments, rather than introducing them at the end in the concept of "impacts". The assessment of land-surface temperatures, which is the basis for Figure 1 (page 8) in the SPM also ignores human-caused landscape changes, except for urbanization. These changes can affect both the local and regional temperature record as the landscape cover is altered. Pielke et al. (1999), for example, explain the observed warming and drying in July and August in south Florida as due to the conversion of the natural landscape to its current human-dominated form. Pielke et al. (2000) documented substantial spatial variation in temperature trends in eastern Colorado, some of which are undoubtedly associated with landscape change this century. Segal et al. (1988, 1989) and Stohlgren et al. (1998), for example, document the major role of irrigation on the climate in this region. Without considering how landscape change has influenced Figure 1, why should it be concluded to be a representative measure of temperature trends due to increased anthropogenic greenhouse gases and aerosols? We investigated global and regional temperature trends (Pielke et al. 1998a,b; Chase et al. 2000b) using the 1000-850 mb thickness values for the period 1979-1996 and, consistent with the MSU data, found no consistent global temperature change in the lower troposphere during this period. In contrast, Figure 1 shows warming. If each data set are accurate, as implied by the recent NRC Panel on the reconciliation of MSU and surface data, the radiative effect of increased carbon dioxide and other greenhouse gases and aerosols must be processed differently by the real climate system, than represented in the GCMs. In conclusion, as stated on page 1 of the SPM, "Climate Change in IPCC Working Group 1 usage refers to any change in climate over time whether due to natural variability or as a result of human activity." Clearly, the IPCC has yet to fully deal with the range of forcings that can lead to climate change. I would be glad to provide additional evidence for the conclusions in this write-up. I am copying these comments to the IPCC Co-Chairs, coordinating lead authors of Working Group 1, and other interested scientists. REFERENCES Chase, T.N., R.A. Pielke, T.G.F. Kittel, R. Nemani, and S.W. Running, 1996: The sensitivity of a general circulation model to global changes in leaf area index. J. Geophys. Res., 101, 7393-7408. Chase, T.N., R.A. Pielke, T.G.F. Kittel, R.R. Nemani, and S.W. Running, 2000a: Simulated impacts of historical land cover changes on global climate in northern winter. Climate Dynamics, 16, 93-105. Chase, T.N., R.A. Pielke, J.A. Knaff, T.G.F. Kittel, and J.L. Eastman, 2000b: A comparison of regional trends in 1979-1997 depth-averaged tropospheric temperatures. Int. J. Climatology, in press. Eastman, J.L., 1999: Analysis of the effects of CO2 and landscape change using a coupled plant and meteorological model. Ph.D. Dissertation, Atmospheric Science Paper No. 686, Colorado State University, R.A. Pielke, P.I., 148 pp. Eastman, J.L., M.B. Coughenour, and R.A. Pielke, 2000: The effects of CO2 and landscape change using a coupled plant and meteorological model. Global Change Biology, submitted. Leemans, R., 1999: Land-use change and the terrestrial carbon cycle. IGBP Global Change Newsletter, 37, 24-26. O'Brien, K.L., 2000: Upscaling tropical deforestation: Implications for climate change. Climatic Change, 44, 311-329. Pielke, R.A., 1984: Earth sciences: Atmospheric sciences - 1983, Encyclopaedia Britannica Yearbook of Science and the Future, 279-282. Pielke, R.A. Sr., 2000: Overlooked issues in the U.S. National Climate and IPCC assessments. Preprints, 11th Symposium on Global Change Studies, 80th AMS Annual Meeting, Long Beach, CA, January 9-14, 2000, 32-35. Pielke, R.A. Sr. and L. Guenni, 1999: Vulnerability assessment of water resources to changing environmental conditions. IGBP Global Change Newsletter, 39, 21-23. Pielke, R.A., J. Eastman, T.N. Chase, and T.G.F. Kittel, 1998a: 1973-1996 trends in depth-averaged tropospheric temperature. J. Geophys. Res., 103, 16927-16933. Pielke, R. A., J. Eastman, T.N. Chase, J. Knaff, and T.G.F. Kittel, 1998b: Correction to ``1973-1996 trends in depth-averaged tropospheric temperature''. J. Geophys. Res., 103, 28909-28911. Pielke, R.A., R.L. Walko, L. Steyaert, P.L. Vidale, G.E. Liston, and W.A. Lyons, 1999: The influence of anthropogenic landscape changes on weather in south Florida. Mon. Wea. Rev., 127, 1663-1673. Pielke, R.A., T. Stohlgren, W. Parton, J. Moeny, N. Doesken, L. Schell, and K. Redmond, 2000: Spatial representativeness of temperature measurements from a single site. Bull. Amer. Meteor. Soc., 81, 826-830. Pitman, A.J., and M. Zhao, 2000: The relative impact of observed change in land cover and carbon dioxide as simulated by a climate model. In preparation. Pitman, A., R. Pielke, R. Avissar, M. Claussen, J. Gash, and H. Dolman, The role of the land surface in weather and climate: Does the land surface matter? IGBP Global Change Newsletter, 39, 4-11. Segal, M., R. Avissar, M.C. McCumber, and R.A. Pielke, 1988: Evaluation of vegetation effects on the generation and modification of mesoscale circulations. J. Atmos. Sci., 45, 2268-2292. Segal, M., W. Schreiber, G. Kallos, R.A. Pielke, J.R. Garratt, J. Weaver, A. Rodi, and J. Wilson, 1989: The impact of crop areas in northeast Colorado on midsummer mesoscale thermal circulations. Mon. Wea. Rev., 117, 809-825. Shine, K.P., and P.M. de F. Forster, 1999: The effect of human activity on radiative forcing of climate change: a review of recent developments. Global Planet. Change, 20, 205-225. Stohlgren, T.J., T.N. Chase, R.A. Pielke, T.G.F. Kittel, and J. Baron, 1998: Evidence that local land use practices influence regional climate and vegetation patterns in adjacent natural areas. Global Change Biology, 4, 495-504. Trenberth, K., 1999: Global climate project shows early promise. EOS, 80, 269-275. Wang, G., and E.A.B. Eltahir, 2000a: Biosphere-atmosphere interactions over west Africa 1. Development and validation of a coupled dynamic model. Q. J. Roy. Meteor. Soc., in press. Wang, G. and E.A.B. Eltahir, 2000b: Biosphere-atmosphere interactions over west Africa 2. Multiple climate equilibria. Q. J. Roy. Meteor. Soc., in press. ============================================================================== Roger A. Pielke, Sr., Professor and State Climatologist Department of Atmospheric Science, Colorado State University Fort Collins, CO 80523, Phone/Fax: 970-491-8293 Email: dallas@cobra.atmos.colostate.edu VISIT OUR WEBSITE AT: http://hercules.atmos.colostate.edu/~project ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ >From dallas@cobra.ATMOS.ColoState.EDU Wed May 10 21:16:35 2000 Date: Mon, 8 May 2000 14:37:01 -0600 (MDT) From: Dallas McDonald To: Mike MacCracken Subject: Chapter 10 review Dear Mike, Thank you for the opportunity to provide comments on Chapter 10: Regional Climate Simulation -- Evaluation and Projections. Unfortunately, I have very substantial concerns regarding the use of regional climate models for predictions of climate change more than a season or so into the future. My concerns can be summarized as follows. *Neither the AOGCMs or the regional climate models include all of the significant human effects on the climate system (e.g., see page 22; lines 41-42 where this "very recent development" is discussed). As I communicated to you in my comments on the SPM, the combined effects of human landuse change, the biogeochemical effect on the atmosphere due to increased CO2, and the microphysical effect of pollution aerosols, for example, have not yet been included in these models. Thus the existing model runs should only be interpreted as sensitivity experiments, not forecasts, projections, or even scenarios (Pielke 2000). *The application of statistical and dynamic downscaling as applied to numerical weather prediction is a very appropriate and valuable tool to improve the spatial and temporal skill of weather projections. However, dynamic downscaling from the radiative effects of CO2 and aerosol AOGCM sensitivity experiments cannot provide improved skill for several reasons. First, with respect to dynamic downscaling, there is not a feedback upscale to the AOGCM from the regional model, even if all of the significant large-scale (GCM scale) human-caused disturbances were included. The regional model runs reported in Chapter 10 themselves are incomplete in their representation of regional human changes (e.g., landuse change) and of biogeochemical effects. The AOGCM also has a spatial resolution that is inadequate to properly define the lateral boundary conditions of the regional model. As shown by Anthes and Warner (1978), the lateral boundary conditions are the dominant forcing of regional atmospheric models as associated with propagating features in the polar westerlies. With numerical weather prediction, the observations used in the analysis to initialize a model retain a component of realism even when degraded to the coarser model resolution of a global model. This realism persists for a period of time (up to a week or so), when used as lateral boundary conditions for a regional numerical weather prediction model. This is not true with the AOGCMs where observed data does not exist to influence the predictions. A regional model cannot reinsert model skill, when it is so dependent on lateral boundary conditions, no matter how good the regional model. If this conclusion is disagreed with, the first step to demonstrate that the regional climate model has predictive skill is to integrate an atmospheric GCM with observed SSTs for several seasons into the future. The GCM output would then be downscaled using the regional climate model. There is expected to be some regional skill and this needs to be quantified. This level of skill, however, will necessarily represent the maximum skill theoretically even possible with AOGCMs as applied for forecasts years and decades into the future since, for these periods, SSTs must also be predicted, and not specified. Such experiments have not been systematically completed. Indeed, does the concept of predictive skill even make sense when we cannot verify the models until decades into the future? The statistical downscaling, besides requiring that the AOGCMs are accurate predictions of the future, also require that the statistical equations that are used for downscaling remain invariant under changed regional atmospheric and land-surface conditions. There is no way to test this hypothesis. In fact, it is unlikely to be valid since the regional climate is not passive to larger-scale climate conditions, but is expected to change over time and feedback to the larger scales. More details of this concern regarding downscaling (and the need to replace this approach with a vulnerability perspective) are reported in Pielke and Guenni (1999). The term "resolution" itself is erroneously used in the text (e.g., Appendix 10). As discussed by Pielke (1991) and Laprise (1992), resolution of atmospheric (and also ocean) features in a model, requires at least 4 grid increments in each spatial direction. The listing of resolution as given in the Chapter's tables is incorrect. The inappropriate use of the term resolution in the tables implies a horizontal scale to the stakeholders that is actually too small for the models to resolve. The more appropriate term to use in the tables is "grid increment". I would be glad to elaborate on my substantial concerns regarding Chapter 10. The illusion of skill is presented in the Figures (e.g., more rainfall over the better resolved terrain), but since the results are so dependent on lateral boundary conditions and AOGCMs which are only sensitivity studies, the interpretation of the model results as "projections" is erroneous and is a misleading communication to the stakeholder community. My recommendation is that the Chapter retain the application of high resolution AOGCMs and the downscaling discussion for the current climate, but add a new section where these tools are applied for seasonal weather prediction using observed SSTs, in order to ascertain how skillful the coupled models can predict seasonal weather. A final section would then summarize regional climate sensitivity experiments where the relative effect of regional human disturbance (e.g., the radiative and biological effect within the climate system of increased CO2; landuse change -- both historical and estimates of future possibilities; the radiative and biogeochemical effects of air pollution, such as ozone, nitrogen deposition, etc.). The knowledge of these sensitivities would be much more useful to policymakers than the existing very limited regional climate results, which are inappropriately communicated as projections. Since many decisions are regional and local in scale, the understanding of the involvement of the regional climate system within the entire spectrum of environmental change and variability (and not just the radiative effect of increased CO2 and aerosols) is a more effective methodology to protect society from environmental threats. REFERENCES Anthes, R.A. and T.T. Warner, 1978: Development of hydrodynamic models suitable for air pollution and other mesometeorological studies. Mon. Wea. Rev., 106, 1045-1078. Laprise, R., 1992: The resolution of global spectral models, 73, 1453-1454. Pielke, R.A., 1991: A recommended specific definition of ``resolution''. Bull. Amer. Meteor. Soc., 72, 1914. Pielke, R.A. Sr., 2000: Overlooked issues in the U.S. National Climate and IPCC assessments. Preprints, 11th Symposium on Global Change Studies, 80th AMS Annual Meeting, Long Beach, CA, January 9-14, 2000, 32-35. Pielke, R.A. Sr. and L. Guenni, 1999: Vulnerability assessment of water resources to changing environmental conditions. IGBP Global Change Newsletter, 39, 21-23. ============================================================================== Roger A. Pielke, Sr., Professor and State Climatologist Department of Atmospheric Science, Colorado State University Fort Collins, CO 80523, Phone/Fax: 970-491-8293 Email: dallas@cobra.atmos.colostate.edu VISIT OUR WEBSITE AT: http://hercules.atmos.colostate.edu/~project