Issues in Simulating the Annual Precipitation of a Semiarid Region in Central Spain

N. Hasler Department of Civil and Environmental Engineering, Duke University, Durham, North Carolina

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R. Avissar Department of Civil and Environmental Engineering, Duke University, Durham, North Carolina

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G. E. Liston Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

Running regional climate models at a high resolution may improve their ability to simulate regional precipitation patterns, making them suitable for studying the impact of human-induced land-cover changes on hydrometeorology. The performance of the Regional Atmospheric Modeling System (RAMS) run in the high-resolution climate mode (4-km grid mesh) has been tested over a small domain in a semiarid region in central Spain. Three 1-yr simulations representing dry, intermediate, and wet conditions were compared to observations collected in 35 rain gauges. The model captured general spatiotemporal features of precipitation, such as the timing of precipitation events and approximate location of storms. A high correlation (0.82) between monthly domain-averaged observed and modeled precipitation was obtained. However, the model had a systematic dry bias, averaging −0.29 mm day−1, equivalent to 26% of annual rainfall. The small domain size, chosen because of computational limits, induced strong lateral boundary forcing, which, combined with uncertainty in NCEP relative humidity fields, was a likely cause for this dry bias.

Corresponding author address: Roni Avissar, Department of Civil and Environmental Engineering, Edmund T. Pratt Jr. School of Engineering, 123 Hudson Hall, Duke University, Durham, NC 27708-0287. Email: avissar@duke.edu

Abstract

Running regional climate models at a high resolution may improve their ability to simulate regional precipitation patterns, making them suitable for studying the impact of human-induced land-cover changes on hydrometeorology. The performance of the Regional Atmospheric Modeling System (RAMS) run in the high-resolution climate mode (4-km grid mesh) has been tested over a small domain in a semiarid region in central Spain. Three 1-yr simulations representing dry, intermediate, and wet conditions were compared to observations collected in 35 rain gauges. The model captured general spatiotemporal features of precipitation, such as the timing of precipitation events and approximate location of storms. A high correlation (0.82) between monthly domain-averaged observed and modeled precipitation was obtained. However, the model had a systematic dry bias, averaging −0.29 mm day−1, equivalent to 26% of annual rainfall. The small domain size, chosen because of computational limits, induced strong lateral boundary forcing, which, combined with uncertainty in NCEP relative humidity fields, was a likely cause for this dry bias.

Corresponding author address: Roni Avissar, Department of Civil and Environmental Engineering, Edmund T. Pratt Jr. School of Engineering, 123 Hudson Hall, Duke University, Durham, NC 27708-0287. Email: avissar@duke.edu

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