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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 11, NOVEMBER 1995

PROFESSIONAL PUBLICATIONS...
CLIMATE FEEDBACK MECHANISMS

The first four papers in this section concern the role of water vapor in the response of the climate system to increase greenhouse gases. Some scientists, particularly Richard Lindzen, suggest that increased convection in a warmer climate would dry the upper troposphere, offsetting the warming, and that numerical climate models are inadequate for representing this feedback.


Item #d95nov33

"A Satellite Analysis of Deep Convection, Upper-Tropospheric Humidity, and the Greenhouse Effect," B.J. Soden (GFDL, POB 308, Princeton NJ 08542), R. Fu, J. Clim., 8(10), 2333-2351, Oct. 1995.

Analysis of several types of satellite data demonstrates that in the tropics, deep convection is associated with upper-tropospheric humidity and an enhanced greenhouse effect. Outside the tropics, upper-tropospheric humidity bears little relationship to deep convection. Comparing results with the GFDL climate model suggests that the model is able to represent upper-tropospheric water vapor feedback, despite its relatively simple treatment of moist convective processes.


Item #d95nov34

"Observed Dependence of the Water Vapor and Clear-Sky Greenhouse Effect on Sea Surface Temperature: Comparison with Climate Warming Experiments," S. Bony (Lab. Météor. Dynamique, CNRS, Ecole Normale Supérieure, 24 rue Lhomond, 75231 Paris cedex 05, France), J.-P. Duvel, H. Le Treut, Clim. Dynamics, 11(5), 307-320, July 1995.

Comparing satellite data and meteorological analyses with climate model simulations indicates that it is not possible to validate the sensitivity of climate models directly on the basis of global "climate parameters" derived from short-term observations; rather, it is essential to go back to the validation of individual processes at the regional scale. This is the strategy of the Atmospheric Model Intercomparison Project, and is probably the more reasonable way to increase our confidence in climate model predictions.


Item #d95nov35

"Water Vapor Feedback over the Arctic Ocean," J.A. Curry (Prog. Atmos. & Ocean Sci., Univ. Colorado, Boulder CO 80309), J.L. Schramm et al., J. Geophys. Res., 100(D7), 14,223-14,229, July 20, 1995.

Because numerical climate models predict amplification of greenhouse warming in the Arctic, this study examined the humidity characteristics, clear-sky greenhouse effect and water vapor feedback in the Arctic using 10 years of Russian radiosonde data and a radiative transfer model. Results show that water vapor feedback over the Arctic Ocean is much more complex than in other regions and is complicated by low temperatures, low amounts of water vapor, and the presence of temperature and humidity inversions. Also discusses implications for global warming.


Item #d95nov36

"Climatic Implications of the Seasonal Variation of Upper Troposphere Water Vapor," A.D. Del Genio (NASA-Goddard, Greenbelt MD 20771), W. Kovari Jr., M.-S. Yao, Geophys. Res. Lett., 21(24), 2701-2704, Dec. 1, 1994.

Uses a general circulation model to diagnose the processes that determine seasonal changes in upper tropospheric water vapor. Results suggest that upper tropospheric water vapor feedback is positive at all latitudes, consistent with model predictions.


Item #d95nov37

"Response of Methane Emission from Arctic Tundra to Climatic Change: Results from a Model Simulation," T.R. Christensen (Dept. Plant Ecol., Univ. Copenhagen, Oster Farimagsgade 2D, 1353 Copenhagen, Denmark), P. Cox, Tellus, 47B(3), 301-309, July 1995.

A model of permafrost thermodynamics and methane emission, developed for inclusion in the U.K. Meteorological Office climate model, is validated with field data. Simulations of a doubled CO2 warming scenario show significantly enhanced methane emission from tundra.


Item #d95nov38

"Elevated Concentrations of CO2 May Double Methane Emissions from Mires," P.R. Hutchin, M.C. Press (Dept. Animal & Plant Sci., Univ. Sheffield, POB 601, Sheffield, UK) et al., Global Change Biology, 1(2), 125-128, Apr. 1995.

Intact cores of peat and vegetation were removed from a mire and buried in open top chambers, where they were exposed to a 60% increase in CO2. A profound increase in methane emissions was observed over the four-month period of study, accompanied by a 100% increase in the rate of photosynthesis.


Item #d95nov39

"Use of a Coupled Ice-Ocean Model to Investigate the Sensitivity of the Arctic Ice Cover to Doubling Atmospheric CO2," D. Ramsden (Clim. Modeling & Analysis Div., Can. Clim. Ctr., POB 1799, Victoria, BC V8W 2Y2, Can.), G. Fleming, J. Geophys. Res., 100(C4), 6817-6828, Apr. 15, 1995.

A coupled ice-ocean model is forced with output from a Canadian Climate Center atmospheric model. Experiments indicate that on the whole, the Arctic ice field acts as a regulator of climate change, rather than an accelerator.


Item #d95nov40

"Cloud Feedback Examined Using a Two-Component, Time-Dependent Climate Model," K. Szilder (Dept. Geog., Univ. Alberta, Edmonton AB T6G 2H4, Can.), E.P. Lozowski, Beitr. Phys. Atmos., 68(1), 43-57, Feb. 1995.

A simplified climate model consisting of atmosphere and ocean components is used to analyze climate feedbacks with and without enhanced greenhouse radiation forcing. Results show that water vapor and snow-ice albedo feedbacks may lead to multiple stable equilibria, raising interesting questions that could be investigated with a full GCM. For instance, could the Earth's climate undergo a relatively sudden transition to a very warm mode as the amount of CO2 increases?


Item #d95nov41

"Analysis of Snow Feedbacks in 14 General Circulation Models," D.A. Randall (Dept. Atmos. Sci., Colorado State Univ., Fort Collins CO 80523), R.D. Cess et al., J. Geophys. Res., 99(D10), 20,757-20,771, Oct. 20, 1994.

Results of 14 GCMs were compared through idealized numerical experiments in which the surface energy budgets of the models were analyzed. The feedbacks were negative or weakly positive in some of the models, but strongly positive in others, and in each case were determined by a complex mix of factors.

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