skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Radiative heating in global climate models


LWR algorithms from various GCMs vary significantly from one another for the same clear sky input data. This variability becomes pronounced when clouds are included. We demonstrate this effect by intercomparing the various models` output using observed data including clouds from ARM/CART data taken in Oklahoma.

; ;  [1]
  1. Univ. of Maryland, College Park, MD (United States)
Publication Date:
Research Org.:
USDOE Office of Energy Research, Washington, DC (United States). Environmental Sciences Div.
OSTI Identifier:
Report Number(s):
ON: DE96010942; TRN: 96:003652-0004
Resource Type:
Resource Relation:
Conference: 5. atmospheric radiation measurement (ARM) science team meeting, San Diego, CA (United States), 19-23 Mar 1995; Other Information: PBD: Apr 1996; Related Information: Is Part Of Proceedings of the fifth Atmospheric Radiation Measurement (ARM) science team meeting; PB: 421 p.
Country of Publication:
United States

Citation Formats

Baer, F., Arsky, N., and Rocque, K.. Radiative heating in global climate models. United States: N. p., 1996. Web.
Baer, F., Arsky, N., & Rocque, K.. Radiative heating in global climate models. United States.
Baer, F., Arsky, N., and Rocque, K.. Mon . "Radiative heating in global climate models". United States. doi:.
title = {Radiative heating in global climate models},
author = {Baer, F. and Arsky, N. and Rocque, K.},
abstractNote = {LWR algorithms from various GCMs vary significantly from one another for the same clear sky input data. This variability becomes pronounced when clouds are included. We demonstrate this effect by intercomparing the various models` output using observed data including clouds from ARM/CART data taken in Oklahoma.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Apr 01 00:00:00 EST 1996},
month = {Mon Apr 01 00:00:00 EST 1996}

Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • Anthropogenically induced climate change is of great current interest because of increases in atmospheric loading of infrared active (greenhouse) gases over the past 150 years and the inferred resultant increase in infrared radiation flux in the troposphere. However, the climate change ascribed to such increases, not to mention predictions of future climate change in response to prospective changes in the earth`s radiation budget, is based virtually entirely on climate model simulations of how the earth`s climate would respond to changes in radiation rather than on empirically established relationships between changes in the earth`s radiation budget and climate change. There ismore » thus an urgent need to evaluate the performance of climate models to ascertain the accuracy with which they represent the changes in temperature and other indicia of climate that have been observed over the industrial period. Such an evaluation, however, requires an accurate assessment of the totality of changes in the earth`s radiation budget in both the longwave (thermal infrared) and shortwave (solar) spectral regions, not just of changes in the longwave due to increased concentrations of long-lived greenhouse gases.« less
  • We are developing two global terrestrial ecosystem models (TERRA and HABITAT) to be coupled to atmospheric and oceanic models in an Earth System Model. TERRA is a model of ecosystem productivity and biogeochemical cycling covering the Earth's land surface as a grid of independent, local models. HABITAT is being designed as a gridded, dynamic model of vegetation response to climate. The TERRA grid cell models are calibrated to 17 vegetation types. The parameter for maximum gross primary productivity was found to average (2.4 +/- 1.4 s.d.) x 10[sup 4] g m[sup [minus]2] y[sup [minus]1] across the 17 types. Maximum ratemore » of nitrogen uptake by vegetation averaged 13 +/- 3 g m[sup [minus]2] y[sup [minus]1] for all forest types, 9 +/- 3 for all woodland and savanna types, and 5 +/- 2 for all grassland, tundra, and shrubland types. Preliminary analysis for designing HABITAT suggests that total annual precipitation and average monthly temperature do not resolve vegetation types. This result emphasizes the need for constructing a set of climatic variables that simplify the biological response.« less
  • In many global climate and weather prediction studies the evolution equations for horizontal winds, water vapor, temperature and surface pressure in a thin, spherical shell are solved using a spectral global climate model (SGCM). Dependent variables are expanded in spherical harmonics which allow for exponential accuracy and semi-implicit timestepping. A spectral/grid transform method is used to evaluate the nonlinear terms.
  • Climate models are driven by forcing, and these forces are seen primarily by the thermal field in general circulation models (GCMs). The major forces that affect the thermal field are longwave radiative (LWR) heating, shortwave radiative (SWR) heating, and convection (cumulus, etc.). These forcing effects are cycled through the thermal field to the motion field by nonlinear transfer. The dependent variables - in particular , temperature, moisture and clouds - evolve in time in a model and determine the subsequent forcing. If the dependent variables are not accurately calculated in space and time, the forcing functions will be adversely affected.Itmore » is thus imperative to determine how sensitive these forces are to the input variables. The authors tested the sensitivity of various LWR heating algorithms taken from general circulation models . The algorithms were tested on a variety of data profiles to cover different geographic regions and seasons.« less
  • Aerosols influence warm clouds in two ways. First, they determine initial drop size distributions, thereby influencing the albedo of clouds. Second, they determine the lifetime of clouds, thereby possibly changing global cloud cover statistics. At the present time, neither effect of aerosols on clouds is included in general circulation models (GCMs). The goal of this project is to develop a global aerosol model and to couple it with the cloud/GCM model developed by Ghan so that the effects of aerosols on clouds can be treated in a realistic and validated manner. This model development will build on existing codes atmore » Lawrence Livermore National Laboratory (LLNL) that are already able to describe some of the important aerosol types and their climate forcing. These codes will be extended to treat realistic sources of all aerosol types of importance. Having developed a global aerosol model, we will use measurements at Atmospheric Radiation Measurement (ARM) sites to validate the model in two ways. First, we will use our global aerosol model to study events of particular interest in the ARM data. This effort will allow us to check the accuracy of the model and its ability to reproduce events from particular time periods. Second, we will use the coupled model to study the climatology of aerosol and cloud microphysical predictions at ARM sites. This effort will allow us to check the accuracy of the model`s predictions in reproducing a long time series of data. These comparison and tests should provide a stringent test of the model`s completeness and prediction capabilities.« less