Extended Abstract (168K)JP2.7
On the Added Value of High-Resolution Remotely Sensed Soil Moisture Data in a Mesoscale Model
Brian P. Reen, Penn State Univ., University Park, PA; and D. R. Stauffer, K. J. Davis, A. R. Desai, and R. J. Dobosy
The non-hydrostatic Pennsylvania State University / National Center for Atmospheric Research (PSU/NCAR) mesoscale model, MM5, is used to model the conditions over the southern Great Plains (SGP) region during SGP-97, a joint NASA-USDA hydrology project. One goal of this modeling effort is to investigate the added value of high-resolution (800 m) remotely sensed soil moisture data on mesoscale simulations of the boundary layer structure in the period 11-15 July 1997. Initial condition uncertainty regarding soil moisture is important to address due to its influence on the surface moisture and energy budgets. This study will be helpful in determining the potential benefits of current (e.g., ~60 km NASA Aqua Advanced Microwave Scanning Radiometer (AMSR) data) and future higher resolution satellite soil moisture data for improving land-atmosphere interactions on the mesoscale. It is important to note, however, that the potential value of remotely sensed soil moisture for mesoscale modeling is also influenced by the amount and type of vegetation cover and how it is handled by the model.
Many sources of atmospheric and soil moisture data were available during SGP-97. Data sources include the Oklahoma Mesonet, a network of 114 stations (38 of which report soil moisture data) scattered throughout the state of Oklahoma, and the SGP Atmospheric Radiation Measurement's Cloud and Radiation Testbed (ARM-CART) site. Special SGP-97 data include cross sections of water vapor and mixed layer height based on airborne LIDAR (Light Detection and Ranging) and aircraft turbulence/flux data.
The MM5 is configured with four nested domains that have resolutions of 36, 12, 4, and 1.33 km. The 36-km grid covers most of the continental United States with the smaller domains concentrating on the southern Great Plains and particularly Oklahoma. The MM5 normally uses a "climatological" moisture availability based on land use and season. Two additional sources of soil moisture were used in these simulations, remotely sensed soil moisture and an offline land surface model (LSM) driven by observations. A P-3B aircraft used a microwave radiometer known as ESTAR (Electronically Scanned Thinned Array Microwave Radiometer) to remotely sense the soil moisture. These data, with an effective resolution of 800 m, have even higher resolution than the innermost 1.33 km MM5 domain, but are available only over a fairly limited area (~10000 km2). The Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) LSM is being run offline over the 36-km domain to supplement the ESTAR data. In one set of experiments these soil moisture data are being used to set a temporally constant soil moisture availability for use by the MM5. In another set of experiments, these soil moisture values are used to define the initial conditions for the PLACE LSM integrated directly within the MM5. This allows a two-way feedback between the LSM and the MM5, and the mesoscale-model soil moisture field varies in both space and time. This study investigates the effect of soil moisture heterogeneity at different scales on the mean boundary layer structure. Model results are compared with both remote and in-situ measurements, to test the reasonability of the model simulations and to help explain phenomena only partially captured in the measurements.
Joint Poster Session 2, Poster Session - Mesoscale Data Assimilation—with Coffee Break
Tuesday, 31 July 2001, 2:30 PM-4:00 PM
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