The pilot phase of the Global Soil Wetness Project

Citation
Pa. Dirmeyer et al., The pilot phase of the Global Soil Wetness Project, B AM METEOR, 80(5), 1999, pp. 851-878
Citations number
73
Categorie Soggetti
Earth Sciences
Journal title
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
ISSN journal
00030007 → ACNP
Volume
80
Issue
5
Year of publication
1999
Pages
851 - 878
Database
ISI
SICI code
0003-0007(199905)80:5<851:TPPOTG>2.0.ZU;2-9
Abstract
The Global Soil Wetness Project (GSWP) is an ongoing land surface modeling activity of the International Satellite Land-Surface Climatology Project (I SLSCP), a part of the Global Energy and Water Cycle Experiment. The pilot p hase of GSWP deals with the production of a two-year global dataset of soil moisture, temperature, runoff, and surface fluxes by integrating uncoupled land surface schemes (LSSs) using externally specified surface forcings fr om observations and standardized soil and vegetation distributions. Approxi mately one dozen participating LSS groups in five nations have taken the co mmon ISLSCP forcing data to drive their state-of-the-art models over the 19 87-88 period to generate global datasets. Many of the LSS groups have perfo rmed specific sensitivity studies, which are intended to evaluate the impac t of uncertainties in model parameters and forcing fields on simulation of the surface water and energy balances. A validation effort exists to compar e the global products to other forms of estimation and measurement, either directly (by comparison to field studies or soil moisture measuring network s) or indirectly (e.g., use of modeled runoff to drive river routing scheme s for comparison to streamflow data). The soil wetness data produced are al so being tested within general circulation models to evaluate their quality and their impact on seasonal to interannual climate simulations. An Inter- Comparison Center has also been established for evaluating and comparing da ta from the different LSSs. Comparison among the model results is used to a ssess the uncertainty in estimates of surface components of the moisture an d energy balances at large scales and as a quality check on the model produ cts themselves.