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Global Climate Change Digest
A Guide to Information on Greenhouse Gases and Ozone Depletion
Published July 1988 through June 1999

FROM VOLUME 8, NUMBER 9, SEPTEMBER 1995

PROFESSIONAL PUBLICATIONS...
GLOBAL & REGIONAL MODELING

Item #d95sep23

"Evaluation of Total Cloudiness and Its Variability in the Atmospheric Model Intercomparison Project," B.C. Weare (Atmos. Sci. Dept., Hoagland Hall, Univ. California, Davis CA 95616), I.I. Mokhov et al., J. Clim., 8(9), 2224-2238, Sep. 1995.

Compares the total cloudiness from 29 models with observational estimates from the ISCCP C2, Nimbus-7 and Meteor. After global means are removed, the root-mean-square differences between the annual means of the model calculations and the C2 observations vary from 2-4 times the differences between the C2 and Meteor observations. Deficiencies with respect to the model simulations of the mean seasonal cycle are also pronounced. However, the models that have more sophisticated physical processes tend to better simulate the cloud observations.

Item #d95sep24

"Atmospheric Response to Tropical Denuding of Vegetation," R.C. Raghava (Ctr. Atmos. Sci., Indian Inst. Technol., New Delhi 110 016 India), K. Laval et al., Atmos. Environ., 29(16), 1963-2000, Aug. 1995.

Simulated atmospheric circulations during June, July and August 1988 with LMD Atmospheric GCM using a classified vegetation global cover, with and without the tropical vegetation. Results show how tropical forest has a pronounced positive impact on precipitation, and how it modulates the Indian monsoon.

Item #d95sep25

"Long-Term Changes in the Acid and Salt Concentrations of the Greenland Ice Core Project Ice Core from Electrical Stratigraphy," E.W. Wolff (Brit. Antarctic Survey, High Cross, Madingley Rd., Cambridge CB3 0ET, UK), J.C. Moore et al., J. Geophys. Res., 100(D8), 16,249-16,263, Aug. 20, 1995.

Records of electrical conductivity measurement (ECM) and dielectric profile (DEP) are dominated by the acidity of the ice (strongly acidic in warm periods and strongly alkaline in cold periods). These results bear on the deduced concentration of cloud condensation nuclei over the Northern Hemisphere, and may have implications for climate modeling.

Item #d95sep26

"The Chemical Composition of Ancient Atmospheres: A Model Study Constrained by Ice Core Data," P. Martinerie (Lab. Glaciol. & Geophys. l'Environ., BP 96, F-38402 St.-Martin-d'Heres Cedex, France), G.P. Brasseur, C. Granier, ibid., 100(D7), 14,291-14,304, July 20, 1995.

Adapted a coupled chemistry radiation transport 2-D model of the lower and middle atmosphere, to study the chemical composition of the atmosphere before industrialization and at the last glacial maximum. The model was constrained by trace gas concentrations (CO₂, CH₄ and N₂O) derived from polar ice records. Infers changes in middle atmosphere temperature, ozone layer and oxidation capacity of the atmosphere (e.g., CH₄ lifetime) over the last 18,000 years.

Item #d95sep27

Two items from J. Clim, 8(6), June 1995:

"Simulation of El Niño—Southern Oscillation-Like Variability in a Global AOGCM and Its Response to CO₂ Increase," S. Tett (H107 Hadley Ctr., U.K. Meteor. Off., London Rd., Bracknell, Berkshire RG12 2SY, UK), 1473-1502. Examined a 75-year integration of a coupled atmosphere-ocean model for tropical interannual variability. Found no significant change in the one-to-ten-year interannual variance of SST in the east Pacific, suggesting that the size of the SST anomalies during warm or cold events in a greenhouse world may not be significantly different from those of today.

"Seasonal Surrogate for Climate," R.S. Lindzen (Dept. Meteor., Mass. Inst. Technol., Cambridge MA 02139), B. Kirtman et al., 1681-1684. Illustrates a simple necessary condition for a short-term event serving as a surrogate for climate, in the evaluation of model performance.

Item #d95sep28

"Modeling Climate Change in the Absence of Climate Change Data," J.W. Skiles (Johnson Controls, MS 239-20, NASA Ames, Moffett Field CA 94035), Clim. Change, 30(1), 1-6, May 1995.

An editorial comment that climate change prediction exercises are done with invalid GCMs and in the absence of validation data. Until concrete climate change data becomes available, particularly for runoff and river flow, validation of GCM output will remain a qualitative exercise. Those using GCM output need to state the confidence they place in those predictions and the reasons for their confidence.

Item #d95sep29

Three items from Global & Planetary Change, 10(1-4), Apr. 1995:

"Global Climate Sensitivity to Tropical Deforestation," K. McGuffie (Dept. Appl. Phys., Univ. Technology, Sydney, POB 123, Broadway NSW, 2007 Australia), A. Henderson-Sellers et al., 97-128. Used a modified version of the NCAR CCM. A 14-year control integration is followed by a 6-year deforestation experiment in which tropical moist forest is replaced by scrub grassland in the Amazon Basin, S.E. Asia and tropical Africa. The impacts on regional climate varied for each deforested region, with the largest disturbances taking place in the Amazon Basin, and the least changes seen for Africa.

"A Comparison of the CCM1-Simulated Climates for Pre-Industrial and Present-Day CO₂ Levels," S. Marshall (Dept. Geog. & Earth Sci., Univ. N. Carolina, Charlotte NC 28223), M.E. Mann, 163-180. Used an atmospheric CO₂ level of 265 ppm (pre-industrial) and 330 ppm (ca. 1975), and included statistical estimates of the level of confidence in the implied changes. Found a relatively large model response in surface temperature and a smaller response in precipitation, surface pressure and storm track fields. A t-statistic of model results indicates a significant surface temperature response to a relatively small change in CO₂, above the inherent model variability. Observations of global surface temperature anomalies for 1890-1990 show some similarities to the model, especially a warming in regions of the wintertime Northern Hemisphere of 1-3° C.

"Low-Frequency Variability and CO₂ Transient Climate Change. Part 2: EOF Analysis of CO₂ and Model-Configuration Sensitivity," G.C. Campbell (NCAR, POB 3000, Boulder CO 80307), T.G.F. Kittel et al., 201-216. Examined the monthly variance structure of several GCM simulations. Four simulations were evaluated in which present-day and doubled CO₂ experiments with the same atmospheric GCM were coupled to: (1) a simple nondynamic mixed-layer ocean (mixed-layer model); and (2) an ocean GCM (coupled model). Found that different model configuration has a stronger effect on simulated interannual variability globally than does altered CO₂ forcing.

Item #d95sep30

"Impact of the Ongoing Amazonian Deforestation on Local Precipitation: A GCM Simulation Study," G.K. Walker, Y.C. Sud (Clim. & Radiation Branch, Code 913, NASA-Goddard, Greenbelt MD 20771), R. Atlas, Bull. Amer. Meteor. Soc., 76(3), 346-361, Mar. 1995.

Investigates deforestation effects through ensembles of five-day integrations with the Goddard Laboratory for Atmospheres GCM equipped with a simple biosphere model. Effects include decreased precipitation extending in a complex fashion downwind, and a significant increase in drag force due to reduced surface roughness.

Item #d95sep31

"Ocean Modelling Efforts in the Global Climate System," J.-O. Wolff (Antarctic Cooperative Res. Ctr., Univ. Tasmania, GPO Box 252C, Hobart, Tasmania 7001, Australia), Aust. Meteor. Mag., 43(4), 263-281, Dec. 1994.

Gives an extensive overview of ocean models that have been used to elucidate the role of the oceans in different frequency ranges of the climate variability spectrum. Discusses coupling to atmospheric climate models and the use of models to study the role of the oceans in climate dynamics. (Invited paper, 1994 National Australian Meteorological and Oceanographic Society Conference.)

Item #d95sep32

"A Self Organization Climate Model," Yi Chuixiang (Dept. Environ. Sci., Beijing Normal Univ., Beijing 100875), Wu Rongsheng, Chinese J. Atmos. Sci., 18(3), 251-262, 1994.

Uses a highly simplified nonlinear model, which shows a self-organization mechanism for cloud-radiation interaction, to study important feedback processes in the climate system.

Item #d95sep33

"Cloudiness Parameterization and Verification in a Large-Scale Atmospheric Model," A.P. Dastoor (Recherche en Prévision Numérique, Serv. Environ. Atmos., 2121 Rte. Trans-Canadienne, Dorval, PQ H9P 1J3, Can.), Tellus, 46A(5), 615-634, Oct. 1994.

A convective and stratiform condensation scheme, in which cloud amount estimation is a predictive variable, is implemented in the Canadian global spectral model. The total cloud cover is better estimated as the sum of separate estimates of convective and stratiform cloudiness, within the framework of the condensation processes parameterized.

Item #d95sep34

"Simulation of the Possible Influence of Methane and Carbon Monoxide Release on the Global Atmospheric Composition and the Greenhouse Effect," I.L. Karol (Voyeykov Main Geophys. Observ.), A.A. Kiselev, V.A. Frolkis, Phys. Atmos. & Ocean, 29(5), 597-601, Apr. 1994. English translation from the Russian Edition, Sep.-Oct. 1993.

Used a one-dimensional radiative-photochemical model to consider expected 21st century changes based on IPCC scenarios, taking into account changes of air temperature and humidity due to the effects of greenhouse and other trace gases. Atmospheric changes found to occur under greenhouse processes affect the gas composition and increase CO content in the lower stratosphere due to decomposition of CH₄ by atomic Cl.

Item #d95sep35

"Global Coupled General Circulation Models," G.A. Meehl (NCAR, POB 3000, Boulder CO 80307), Bull. Amer. Meteor. Soc., 76(6), 951-957, June 1995.

Presents major conclusions and recommendations on the status of coupled GCMs from a workshop convened by the World Climate Research Program (Oct. 1994, La Jolla, Calif.). Participants concluded that improved communication among those engaged in this activity will be important to further progress.

Item #d95sep36

"Using Paleoclimates to Predict Future Climate: How Far Can Analogy Go?" C. Covey (Global Clim. Res. Div., Lawrence-Livermore Natl. Lab., POB 808, Livermore CA 94550), Clim. Change, 29(4), 403-407, Apr. 1995.

An extensive comment on the disagreement between GCMs and paleodata, which should be cause for concern among those who subscribe to the conventional wisdom. The disciplines of geology and meteorology must be brought together if we are to fully confront theory with observation.

Item #d95sep37

"Global-Mean Temperature and Sea Level Consequences of Greenhouse Gas Concentration and Stabilization," T.M.L. Wigley (Clim. Res. Unit., Univ. E. Anglia, Norwich NR4 7TJ, UK), Geophys. Res. Lett., 22(1), 45-48, Jan. 1, 1995.

Uses models previously employed by the Intergovernmental Panel on Climate Change to calculate scenarios of future CO₂ levels stabilized at 350-750 ppmv, to the year 2500. Uncertainties are large, but results show that even with concerted efforts at stabilization, substantial increases in temperature and sea level can be expected over the next century. Sea level could continue to increase for many centuries after stabilization due to the extremely long time scales associated with the deep ocean (thermal expansion) and with large ice sheets.

Item #d95sep38

"The Current State and Future Direction of Eulerian Models in Simulating the Tropospheric Chemistry and Transport of Trace Species: A Review," L.K. Peters (Dept. Chem. Eng., Virginia Polytechnic Inst., Blacksburg VA 24061), C.M. Berkowitz et al., Atmos. Environ., 29(2), 189-222, Jan. 1995.

Central improvements that would result in a "third generation" model involve feedback processes between meteorology and chemistry, aerosol formation in cloud development, and impacts of chemical perturbations on radiation, climate and biogeochemical cycles. Also includes a comparison of characteristics of existing models, and extensive references.

Item #d95sep39

"A Comparison of GCM Sensitivity to Changes in CO₂ and Solar Luminosity," S. Marshall (Dept. Geog., Univ. N. Carolina, Charlotte NC 28223), R.J. Oglesby et al., Geophys. Res. Lett., 21(23), 2487-2490, Nov. 15, 1994.

Experiments with the NCAR climate model are compared using a formal sensitivity analysis. Since the nature of the model response does not seem to be sensitive to the nature of the forcing, validation of model performance using warm climates of the recent past may be a good indication of its ability to model future warming from CO₂.