Comparing Local Analysis and Prediction System (LAPS) Assimilations with Independent Observations

Christopher A. Hiemstra Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Glen E. Liston Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado

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Roger A. Pielke Sr. Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Daniel L. Birkenheuer NOAA/Earth System Research Laboratory, Boulder, Colorado

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Steven C. Albers Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado, and NOAA/Earth System Research Laboratory, Boulder, Colorado

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Abstract

Meteorological forcing data are necessary to drive many of the spatial models used to simulate atmospheric, biological, and hydrological processes. Unfortunately, many domains lack sufficient meteorological data and available point observations are not always suitable or reliable for landscape or regional applications. NOAA’s Local Analysis and Prediction System (LAPS) is a meteorological assimilation tool that employs available observations (meteorological networks, radar, satellite, soundings, and aircraft) to generate a spatially distributed, three-dimensional representation of atmospheric features and processes. As with any diagnostic representation, it is important to ascertain how LAPS outputs deviate from a variety of independent observations. A number of surface observations exist that are not used in the LAPS system, and they were employed to assess LAPS surface state variable and precipitation analysis performance during two consecutive years (1 September 2001–31 August 2003). LAPS assimilations accurately depicted temperature and relative humidity values. The ability of LAPS to represent wind speed was satisfactory overall, but accuracy declined with increasing elevation. Last, precipitation estimates performed by LAPS were irregular and reflected inherent difficulties in measuring and estimating precipitation.

Corresponding author address: Dr. Christopher A. Hiemstra, Cooperative Institute for Research in the Atmosphere, Colorado State University, 1375 Campus Delivery, Fort Collins, CO 80523-1375. Email: hiemstra@cira.colostate.edu

Abstract

Meteorological forcing data are necessary to drive many of the spatial models used to simulate atmospheric, biological, and hydrological processes. Unfortunately, many domains lack sufficient meteorological data and available point observations are not always suitable or reliable for landscape or regional applications. NOAA’s Local Analysis and Prediction System (LAPS) is a meteorological assimilation tool that employs available observations (meteorological networks, radar, satellite, soundings, and aircraft) to generate a spatially distributed, three-dimensional representation of atmospheric features and processes. As with any diagnostic representation, it is important to ascertain how LAPS outputs deviate from a variety of independent observations. A number of surface observations exist that are not used in the LAPS system, and they were employed to assess LAPS surface state variable and precipitation analysis performance during two consecutive years (1 September 2001–31 August 2003). LAPS assimilations accurately depicted temperature and relative humidity values. The ability of LAPS to represent wind speed was satisfactory overall, but accuracy declined with increasing elevation. Last, precipitation estimates performed by LAPS were irregular and reflected inherent difficulties in measuring and estimating precipitation.

Corresponding author address: Dr. Christopher A. Hiemstra, Cooperative Institute for Research in the Atmosphere, Colorado State University, 1375 Campus Delivery, Fort Collins, CO 80523-1375. Email: hiemstra@cira.colostate.edu

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