85th AMS Annual Meeting

Wednesday, 12 January 2005
Evaluating the use of the Atmospheric and EXchange Inverse (ALEXI) model in short-term prediction and mesoscale diagnosis
John R. Mecikalski, University of Alabama, Huntsville, AL; and S. M. Mackaro, M. C. Anderson, J. M. Norman, and J. B. Basara
Poster PDF (787.5 kB)
Continental scale maps of daily surface energy fluxes are being generated using the Atmospheric Land-Exchange Inverse (ALEXI) model at the University of Wisconsin. This model relies on remote sensing data to operate, including GOES-derived surface brightness temperature changes, AVHRR-derived land cover properties, as well as synoptic weather data. Sensible, latent and ground heat flux components along with net radiation and soil moisture are estimated on the 5-10 km scale from these inputs. Recent efforts have validated this modeling procedure to within 10-12% of surface- or tower-based instruments. Validation results for ALEXI resolutions of 5-10 km compare to within 30% of ground-based sensors. The validation of ALEXI has occurred through the analysis of data collected during the Soil Moisture Atmospheric Coupling EXperiment (SMACEX) field campaign in 2002 within the state of Iowa.

Ongoing research with the ALEXI model involves development of a 2-3 year climatology of land-surface energy, evapotranspiration (ET) and soil moisture (root zone, 6 cm-1.5 m, and surface layer, 0-6 cm) estimates over the continental U.S. This climatology will extend from June 2002 to late 2004. This presentation will highlight the specific details of the ALEXI system that allow us to retrieve the above quantities, and describe the development of new avenues for using ALEXI input/output fields in short-term weather forecasting on mesoscales (20-200 km). Specifically, our presentation will highlight recent advances in the assimilation of ALEXI soil moistures and ET in a real-time NWP system (the ADAS) at UAH. Subsequent, additional validation of the ALEXI and our ADAS assimilation will be performed using data from the Oklahoma Mesonet, especially as the mesoscale quality of ALEXI is proven.

Other new research at UAH is toward developing means of using ALEXI data sets in the prediction of thunderstorm development related to aspects of the land surface, plant canopy, and boundary layer. Specific work is focussed on defining land-surface heterogeneity using various ALEXI fields, in addition to those made available through the processing of MODIS satellite data.

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