February 28, 2007
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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 5, NUMBER 12, DECEMBER 1992
CLIMATE CHANGE IMPACTS: TECHNIQUES
"Global Warming and Environmental Change in Sub-Saharan Africa,"
M.H. Glantz (ESIG, NCAR, POB 3000, Boulder CO 80307), Global Environ. Change,
2(3), 183-204, Sep. 1992. Recently proposed climate change impact
scenarios for this region should be considered speculative, and no single
scenario should be used for determining irreversible policy responses.
"Adapting Stochastic Weather Generation Algorithms for Climate Change
Studies," D.S. Wilks (Dept. Soil, Crop, Atmos. Sci., Cornell Univ., Ithaca
NY 14853), Clim. Change, 22(1), 67-84, Sep. 1992.
Presents a method of adapting stochastic weather generation models to
generate synthetic daily time series consistent with assumed future climates,
for investigating agricultural and other impacts. Simulation of time series
exhibiting changes in variability is possible.
"Towards a General Method for Analyzing Regional Impacts of Global
Change," T. Malone (Dept. Marine Sci., N. Carolina State Univ., Raleigh NC
27695), G. Yohe, Global Environ. Change, 2(2), 101-110, June
The effects of global change are likely to be greatest at subnational
levels, but the integration of social and environmental science on these levels
is a challenge. Describes a pioneering government-sponsored study of climate
change in the central U.S., which has incorporated diverse inputs from a range
of disciplines and is potentially applicable in developing countries.
"Modeling Ecological and Agricultural Impacts of Global Change on a
Global Scale," R. Leemans (Nat. Inst. Pub. Health & Environ.
Protect.--RIVM, Dept. Global Change, POB 1, 3720 BA Bilthoven, Neth.), J.
Sci. Indust. Res., 51(8-9), 709-724, Aug.-Sep. 1992.
Discusses methods for developing consistent climate-change scenarios and
linking them to different impact models. Examples are drawn from different
impact studies on large-scale vegetation patterns, forest dynamics and
"A Comparison of GCM-Simulated and Observed Mean January and July
Precipitation," D.R. Legates (Dept. Geog., Univ. Oklahoma, Norman OK
73019), C.J. Willmott, Global Planet. Change, 5(4), 345-363,
The comparison shows that regional differences are commonly quite large,
which suggests cautious use of current-generation GCM output for local- and
regional-scale climate change studies.
"A 2XCO2 Climate Change Scenario over Europe Generated Using a
Limited Area Model Nested in a General Circulation Model. 2. Climate Change
Scenario," F. Giorgi (NCAR, POB 3000, Boulder CO 80307), M.R. Marinucci, G.
Visconti, J. Geophys. Res., 97(D9), 10,011-10,028, June 20,
1992. Results emphasize the inadequacy of simply interpolating coarse resolution
GCM output to obtain estimates of local changes in surface climatic variables
for impact assessments.
"Assessing Impacts of a Climatologically Unique Year (1990) in the
Midwest," S.A. Changnon (Illinois State Water Survey, Midwest. Clim. Ctr.,
Champaign IL 61820), K.E. Kunkel, Phys. Geog., 13(2), 180-190,
Includes discussion of how assessment of the effects of a changed climate
will require that global climate models describe shifts in average dates of
first and last freezes, the frequency of heavy rain events and intensity of
"An Evaluation of Global Warming and Its Impact," U.R. Rao
(Indian Space Res. Organization, Bangalore 560094, India), S.C. Chakravarty,
Current Sci., 62(6), 469-478, Mar. 25, 1992.
An energy balance model shows that the growth of greenhouse gases could
raise temperatures about 4 K by the year 2050 compared to the preindustrial era.
Finds that the possible climatic impacts of warming on a few biophysical
parameters are alarming. Prompt action to control emission of greenhouse gases
"Developing Scenarios of Temperature Thresholds," P.J. Robinson
(Dept. Geog., Univ. North Carolina, Chapel Hill NC 27599), Phys. Geog.,
13(1), 14-30, Jan.-Mar. 1992.
Presents a method for developing regional scenarios of the number of days
per month above a selected temperature, using regressions on observed daily
maximum temperatures, and extrapolation to the results of GCMs. Demonstrates the
method by developing a set of scenarios for the U.S. for a 90° F
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