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Development and Evaluation of a WRF-Based Mesoscale Numerical Weather Prediction System in Northwestern China

1
Institute of Arid Meteorology, China Meteorological Administration; Lanzhou 730020, China
2
Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, Key Laboratory of Arid Climatic Change and Disaster Reduction, China Meteorological Administration, Lanzhou 730020, China
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(6), 344; https://doi.org/10.3390/atmos10060344
Received: 28 May 2019 / Revised: 8 June 2019 / Accepted: 20 June 2019 / Published: 25 June 2019
(This article belongs to the Section Climatology and Meteorology)
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Abstract

Based on the U.S. Weather Research and Forecasting (WRF) numerical model, this study has developed the Northwest Mesoscale Numerical Prediction Service and Experimental System (NW-MNPS). Surface and sounding data assimilation has been introduced for this system. Effects of model vertical layers and land-use data replacement have been assessed. A year-long forecast validation and analysis have been performed. The following results have been obtained: (1) Data assimilation can improve the performance of regional numerical forecasting. (2) Compared to simulations with 40 vertical layers, simulations with 55 vertical layers are more accurate. The average absolute error and root-mean-square error of the 48 h surface element forecast decrease. The analysis of threat score (TS) and equitable threat score (ETS) shows that there are higher TS and ETS values for various precipitation intense levels, in particular for heavy rainfall when comparing a 55-vertical-layer test with a 40-vertical-layer test. (3) Updating the database to include vegetation coverage can more accurately reflect actual surface conditions. The updated land-use data reduce prediction errors in all domains of the NW-MNPS. View Full-Text
Keywords: numerical prediction; land-use update; vertical layers; data assimilation numerical prediction; land-use update; vertical layers; data assimilation
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Zhang, T.; Li, Y.; Duan, H.; Liu, Y.; Zeng, D.; Zhao, C.; Gong, C.; Zhou, G.; Song, L.; Yan, P. Development and Evaluation of a WRF-Based Mesoscale Numerical Weather Prediction System in Northwestern China. Atmosphere 2019, 10, 344.

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