Evaluating seasonal orographic precipitation in the Interior Western United States using gauge data, gridded precipitation estimates, and a regional climate simulation

Evaluating seasonal orographic precipitation in the Interior Western United States using gauge... AbstractThere are several high-resolution (1-12 km) gridded precipitation datasets covering the Interior Western United States. This study cross-validates seasonal orographic precipitation estimates from the Snow Telemetry (SNOTEL) network, the National Hourly Multisensor Precipitation Analysis Stage IV dataset (NCEP IV), and four gauge-driven gridded datasets, and a 10-year, 4 km convection-permitting Weather Research and Forecasting Model (WRF) simulation. The NCEP IV dataset, which uses the NEXRAD network and precipitation gauges, is challenged in this region because of blockage and lack of low-level radar coverage in complex terrain. The gauge-driven gridded datasets, which statistically interpolate gauge measurements over complex terrain to better estimate orographic precipitation, are challenged by the highly heterogeneous, weather-dependent nature of precipitation in complex terrain at scales finer than can be resolved by the gauge network, such as the SNOTEL network. Gauge-driven gridded precipitation estimates disagree in areas where SNOTEL gauges are sparse, especially at higher elevations. The WRF simulation captures wintertime orographic precipitation distribution and amount well, and biases over specific mountain ranges are identical to those in an independent WRF simulation, suggesting that these biases are at least partly due to errors in the snowfall measurements, or the gridding of these measurements. The substantial disagreement between WRF and the gridded datasets over some mountains may motivate re-evaluation of some gauge records and installation of new SNOTEL gauges in regions marked by large discrepancies between modeled and gauge-driven precipitation estimates. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrometeorology American Meteorological Society

Evaluating seasonal orographic precipitation in the Interior Western United States using gauge data, gridded precipitation estimates, and a regional climate simulation

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1525-7541
D.O.I.
10.1175/JHM-D-17-0056.1
Publisher site
See Article on Publisher Site

Abstract

AbstractThere are several high-resolution (1-12 km) gridded precipitation datasets covering the Interior Western United States. This study cross-validates seasonal orographic precipitation estimates from the Snow Telemetry (SNOTEL) network, the National Hourly Multisensor Precipitation Analysis Stage IV dataset (NCEP IV), and four gauge-driven gridded datasets, and a 10-year, 4 km convection-permitting Weather Research and Forecasting Model (WRF) simulation. The NCEP IV dataset, which uses the NEXRAD network and precipitation gauges, is challenged in this region because of blockage and lack of low-level radar coverage in complex terrain. The gauge-driven gridded datasets, which statistically interpolate gauge measurements over complex terrain to better estimate orographic precipitation, are challenged by the highly heterogeneous, weather-dependent nature of precipitation in complex terrain at scales finer than can be resolved by the gauge network, such as the SNOTEL network. Gauge-driven gridded precipitation estimates disagree in areas where SNOTEL gauges are sparse, especially at higher elevations. The WRF simulation captures wintertime orographic precipitation distribution and amount well, and biases over specific mountain ranges are identical to those in an independent WRF simulation, suggesting that these biases are at least partly due to errors in the snowfall measurements, or the gridding of these measurements. The substantial disagreement between WRF and the gridded datasets over some mountains may motivate re-evaluation of some gauge records and installation of new SNOTEL gauges in regions marked by large discrepancies between modeled and gauge-driven precipitation estimates.

Journal

Journal of HydrometeorologyAmerican Meteorological Society

Published: Jul 21, 2017

References

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