Session on coupled land surface/hydrological/atmospheric models

The current model capabilities in the context of land surface interactions with the atmosphere include only one-dimensional characteristics of vegetation and soil surface heat, moisture, momentum, and selected other trace gas fluxes (e.g., CO2). The influence of spatially coherent fluxes that result from landscape heterogeneity were not included. Valuable representations of several aspects of the landscape pattern currently exist. These include digital elevation data and measures of the leaf area index (i.e., Normalized Difference Vegetation Index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) data). A major deficiency, however, is the lack of an ability to sample spatially representative shallow and (especially) deep soil moisture. Numerous mesoscale modeling and observed studies demonstrated the sensitivity of planetary boundary layer structure and deep convection to the magnitude of the surface moisture flux

Acid deposition in Colorado: a potential or current problem; local versus long-distance transport into the state

August 13-15, 1986.Includes bibliographical references.A compendium of papers presented at a workshop sponsored by the Cooperative Institute for Research in the Atmosphere, Colorado State University in Fort Collins, Colorado on August 13-15, 1986

The U.S. National Climate Change Assessment: Do the Climate Models Project a Useful Picture of Regional Climate?

9 pages. Includes illustrations Dr. Roger A. Pielke, Sr., President of the American Association of State Climatologists, Colorado State Climatologist and Professor, Department of Atmospheric Science, Colorado State University From testimony presented to the House Subcommittee on Oversight and Investigations, July 25, 2002, and published in Colorado Water, April 2003, 15-19

The U.S. National Climate Change Assessment: Do the Climate Models Project a Useful Picture of Regional Climate?

9 pages. Includes illustrations Dr. Roger A. Pielke, Sr., President of the American Association of State Climatologists, Colorado State Climatologist and Professor, Department of Atmospheric Science, Colorado State University From testimony presented to the House Subcommittee on Oversight and Investigations, July 25, 2002, and published in Colorado Water, April 2003, 15-19

Best practices in prediction for decision-making : lessons from the atmospheric and earth sciences

Predictions that result from scientific research hold great appeal for decision-makers who are grappling with complex and controversial environmental issues, by promising to enhance their ability to determine a need for and outcomes of alternative decisions. A problem exists in that decision-makers and scientists in the public and private sectors solicit, produce, and use such predictions with little understanding of their accuracy or utility, and often without systematic evaluation or mechanisms of accountability. In order to contribute to a more effective role for ecological science in support of decision-making, this paper discusses three ``best practices'' for quantitative ecosystem modeling and prediction gleaned from research on modeling, prediction, and decision-making in the atmospheric and earth sciences. The lessons are distilled from a series of case studies and placed into the specific context of examples from ecological science

Numerical simulation of the influence of the large-scale monsoon flow on the diurnal weather patterns over Kenya

August 1992.Bibliography: pages 204-211.Sponsored by NSF ATM-8915265

Influence of deep cumulus convection on sea breeze dynamics over south Florida, The

May 16, 1988.Includes bibliographical references.Sponsored by the National Aeronautics and Space Administration NAG 5-359.Part I. Model development -- Part II. Model application

Numerical study of the impact of land use modification on local rainfall over Manila, A

Includes bibliographical references

Impact of soil moisture and vegetation distribution on July 1989 climate using a regional climate model

Spring 1995.Bibliography: pages [113]-124.Sponsored by National Park Service CA 1268-2-9004.Sponsored by National Park Service CEGR-R92-0193.Sponsored by National Park Service COLR-R92-0204.Sponsored by U.S. Geological Survey 1434-94-A-1275.Sponsored by Climate System Modeling Program through UCAR S9361