Effects of spectral nudging on the 2010 East Asia summer monsoon using WRF model |
| |
Authors: | SHAN Haixia GUAN Yuping HUANG Jianping |
| |
Institution: | 1. Key Laboratory for Semi-Arid Climate Change of the Ministry of Education College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China;State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences,Guangzhou 510301, China 2. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences,Guangzhou 510301, China 3. Key Laboratory for Semi-Arid Climate Change of the Ministry of Education College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China |
| |
Abstract: | The performance of spectral nudging in an investigation of the 2010 East Asia summer monsoon was assessed using the Weather Research and Forecasting (WRF) model, forced by 1-degree NCEP Global Final Analysis (FNL). Two pairs of experiments were made, spectral nudging (SP) and non-spectral nudging (NOSP), with five members in each group. The members were distinguished by different initial times, and the analysis was based on the ensemble mean of the two simulation pairs. The SP was able to constrain error growth in large-scale circulation in upper-level, during simulation, and generate realistic regional scale patterns. The main focus was the model ability to simulate precipitation. The Tropical Rainfall Measuring Mission (TRMM) 3B42 product was used for precipitation verification. Mean precipitation magnitude was generally overestimated by WRF. Nevertheless, SP simulations suppressed overestimation relative to the NOSP experiments. Compared to TRMM, SP also improved model simulation of precipitation in spatial and temporal distributions, with the ability to reproduce movement of rainbands. However, extreme precipitation events were suppressed in the SP simulations. |
| |
Keywords: | downscaling regional climate model East Asia summer monsoon spectral nudging |
本文献已被 CNKI 万方数据 SpringerLink 等数据库收录! |
|