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portada Land Surface -- Atmosphere Interactions for Climate Modeling: Observations, Models and Analysis
Type
Physical Book
Publisher
Author
Language
English
Pages
314
Format
Paperback
Dimensions
23.4x15.6x1.8 cm
Weight
0.46 kg.
ISBN13
9789401074704
Categories

Land Surface -- Atmosphere Interactions for Climate Modeling: Observations, Models and Analysis

Wood, E. F. (Author) · Springer · Paperback

Land Surface -- Atmosphere Interactions for Climate Modeling: Observations, Models and Analysis - Wood, E. F.

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Synopsis "Land Surface -- Atmosphere Interactions for Climate Modeling: Observations, Models and Analysis"

It is well known that the interactions between land surfaces and the atmosphere, and the resulting exchanges in water and energy have a tremendous affect on climate. The inadequate representation of land-atmosphere interactions is a major weakness in current climate models, and is providing the motivation for the HAPEX and ISLSCP experiments as well as the proposed Global Energy and Water Experiment (GEWEX) and the Earth Observing System (EOS) mission. The inadequate representation reflects the recognition that the well-known phys- ical relationships, which are well described at small scales, result in different relationships when represented at the scales used in climate models. Understanding this transition in the mathematical relationships with increased space-time scales appears to be very difficult, and has led to different approaches; at one extreme, the famous "bucket" model where the land-surface is a simple one layer storage without vegetation; the other extreme may be Seller's Simple Biosphere Model (Sib) where one big leaf covers the climate model grid. Given the heterogeneous nature of landforms, soils and vegetation within a climate model grid, the development of new land surface parameterizations, and their verification through large scale experiments is perceived to be a challenging area of research for the hydrology and meteorology communities. This book evolved from a workshop held at Princeton University to explore the status of land surface parameterizations within climate models, and how observa- tional data can be used to assess these parameterizations and improve models.

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