Observing and Understanding the Variability of Water in Weather and Climate


Using observations to develop, initialize, and validate two land-surface schemes within ARPS

Jerald A. Brotzge, CAPS/Univ. of Oklahoma, Norman, OK; and D. Weber

The Advanced Regional Prediction System (ARPS) is a three-dimensional, nonhydrostatic model developed by the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The ARPS was originally designed with the Interactions Soil Biosphere Atmosphere (ISBA) scheme, a "force-restore" land-surface model (LSM). A second LSM option now available in ARPS, dubbed "OUSoil", is a slightly modified version of the OSU-NOAH LSM used operationally by the ETA model.

The ISBA and OUSoil land-surface schemes have been evaluated using extensive data sets collected from the Oklahoma Atmospheric Surface-layer Instrumentation System (OASIS) and Oklahoma Mesonet programs. OASIS is a newly developed observational system that collects, archives, and quality controls atmospheric, surface, and soil data in real-time from 90 sites across Oklahoma. Data has been collected since 1 January, 2000. For this study, several "golden" days were chosen from the spring, summer, and fall of 2000.

Standard weather, surface radiation and flux data, and soil temperature and moisture data were used to initialize, force, and evaluate the ISBA and OUSoil land-surface schemes. This study evaluates the performance of each scheme, and highlights the value of using observations to develop and improve model performance. One-dimensional, twenty-four hour model runs were tested, using OASIS, Mesonet, and NWS sounding data for initialization. In particular, soil temperature and moisture and surface-layer fluxes were evaluated. In general, more detailed attention to initialization and more physically-based model physics improved LSM results.

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Poster Session 2, Weather and Climate Modeling of Water in all its Phases Poster Sessions
Thursday, 13 February 2003, 9:45 AM-11:00 AM

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