The Influence of Assimilating Dropsonde Data on Typhoon Track and Midlatitude Forecasts

被引:99
作者
Weissmann, Martin [1 ]
Harnisch, Florian [1 ]
Wu, Chun-Chieh [2 ]
Lin, Po-Hsiung [2 ]
Ohta, Yoichiro [3 ]
Yamashita, Koji [3 ]
Kim, Yeon-Hee [4 ]
Jeon, Eun-Hee [4 ]
Nakazawa, Tetsuo [5 ]
Aberson, Sim [6 ]
机构
[1] Deutsch Zentrum Luft & Raumfahrt, Inst Atmospher Phys, Oberpfaffenhofen, Germany
[2] Natl Taiwan Univ, Dept Atmospher Sci, Taipei 10764, Taiwan
[3] Japan Meteorol Agcy, Tokyo, Japan
[4] Korea Meteorol Agcy, Natl Inst Meteorol Res, Seoul, South Korea
[5] Meteorol Res Inst, Tsukuba, Ibaraki 305, Japan
[6] NOAA, Atlantic Oceanog & Meteorol Lab, Hurricane Res Div, Miami, FL 33149 USA
基金
美国国家科学基金会;
关键词
4-DIMENSIONAL VARIATIONAL ASSIMILATION; ECMWF OPERATIONAL IMPLEMENTATION; HURRICANE SYNOPTIC SURVEILLANCE; TARGETED OBSERVATIONS; DROPWINDSONDE DATA; DOTSTAR; SYSTEM; IMPACT; GUIDANCE; PHYSICS;
D O I
10.1175/2010MWR3377.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A unique dataset of targeted dropsonde observations was collected during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) in the autumn of 2008. The campaign was supplemented by an enhancement of the operational Dropsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) program. For the first time, up to four different aircraft were available for typhoon observations and over 1500 additional soundings were collected. This study investigates the influence of assimilating additional observations during the two major typhoon events of T-PARC on the typhoon track forecast by the global models of the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction (NCEP), and the limited-area Weather Research and Forecasting (WRF) model. Additionally, the influence of T-PARC observations on ECMWF midlatitude forecasts is investigated. All models show an improving tendency of typhoon track forecasts, but the degree of improvement varied from about 20% to 40% in NCEP and WRF to a comparably low influence in ECMWF and JMA. This is likely related to lower track forecast errors without dropsondes in the latter two models, presumably caused by a more extensive use of satellite data and four-dimensional variational data assimilation (4D-Var) of ECMWF and JMA compared to three-dimensional variational data assimilation (3D-Var) of NCEP and WRF. The different behavior of the models emphasizes that the benefit gained strongly depends on the quality of the first-guess field and the assimilation system.
引用
收藏
页码:908 / 920
页数:13
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