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三维变分同化机载雷达资料对飓风预报的影响研究--2012年Isaac试验

陆续 马旭林 王旭光

大气科学Issue(6):1111-1122,12.
大气科学Issue(6):1111-1122,12.DOI:10.3878/j.issn.1006-9895.1503.14262

三维变分同化机载雷达资料对飓风预报的影响研究--2012年Isaac试验

A Study of the Impact of Airborne Radar Data Assimilated by 3DVar on the Prediction of Hurricane-Isaac 2012

陆续 1马旭林 1王旭光2

作者信息

  • 1. 南京信息工程大学气象灾害教育部重点实验室,南京201144
  • 2. 俄克拉荷马大学,美国俄克拉荷马州73072
  • 折叠

摘要

Abstract

Given the increasingly important role of inner-core data in tropical cyclone (TC) forecasting, the present paper investigates the impact of assimilating Tail Doppler Radar (TDR) data on the prediction of hurricanes. A series of experiments are conducted using the operational Weather Research and Forecasting model for Hurricane (HWRF) and grid-point statistical interpolation (GSI) 3D variational (3DVar) system for Hurricane Isaac (2012). It is found that the assimilation of TDR data can correct the storm center to a better position compared to without TDR assimilation. Furthermore, the better inner-core structures in the results of the experiments that assimilated the TDR data have a positive impact on the intensity forecasts. In general, the TDR data improve the TC track and intensity forecast compared to the official forecasts from the operational HWRF, and the forecasts without assimilating the TDR data. The study also suggests that further reducing the background error covariances to be consistent with the dynamical and thermodynamical structures of the hurricanes is needed to further improve analyses and predictions of TCs.

关键词

Grid-point statistical interpolation/3D variational data assimilation/Weather Research and Forecasting model for Hurricane/Tail Doppler Radar data/Tropical cyclone

Key words

Grid-point statistical interpolation/3D variational data assimilation/Weather Research and Forecasting model for Hurricane/Tail Doppler Radar data/Tropical cyclone

分类

天文与地球科学

引用本文复制引用

陆续,马旭林,王旭光..三维变分同化机载雷达资料对飓风预报的影响研究--2012年Isaac试验[J].大气科学,2015,(6):1111-1122,12.

基金项目

国家自然科学基金项目41275111,飓风预报改进项目 ()

大气科学

OA北大核心CSCDCSTPCD

1006-9895

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