4.1 Article

An exceptionally heavy snowfall in Northeast china: large-scale circulation anomalies and hindcast of the NCAR WRF model

期刊

METEOROLOGY AND ATMOSPHERIC PHYSICS
卷 113, 期 1-2, 页码 11-25

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SPRINGER WIEN
DOI: 10.1007/s00703-011-0147-7

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资金

  1. Major State Basic Research Development Program of China (973 Program) [2009CB421406]
  2. Chinese Academy of Sciences [KZCX2-YW-Q1-02]
  3. Special Fund for Public Welfare Industry (Meteorology) [GYHY200906018]
  4. National Natural Science Foundation of China [40821092]

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In Northeast China (NEC), snowfalls usually occur during winter and early spring, from mid-October to late March, and strong snowfalls rarely occur in middle spring. During 12-13 April 2010, an exceptionally strong snowfall occurred in NEC, with 26.8 mm of accumulated water-equivalent snow over Harbin, the capital of the most eastern province in NEC. In this study, the major features of the snowfall and associated large-scale circulation and the predictability of the snowfall are analyzed using both observations and models. The Siberia High intensified and shifted southeastward from 10 days before the snowfall, resulting in intensifying the low-pressure system over NEC and strengthening the East Asian Trough during 12-13 April. Therefore, large convergence of water vapor and strong rising motion appeared over eastern NEC, resulting in heavy snowfall. Hindcast experiments were carried out using the NCAR Weather Research and Forecasting (WRF) model in a two-way nesting approach, forced by NCEP Global Forecast System data sets. Many observed features including the large-scale and regional circulation anomalies and snowfall amount can be reproduced reasonably well, suggesting the feasibility of the WRF model in forecasting extreme weather events over NEC. A quantitative analysis also shows that the nested NEC domain simulation is even better than mother domain simulation in simulating the snowfall amount and spatial distribution, and that both simulations are more skillful than the NCEP Global Forecast System output. The forecast result from the nested forecast system is very promising for an operational purpose.

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