The influence of assimilating dropsonde data on Typhoon track and midlatitude forecasts
Journal
Monthly Weather Review
Journal Volume
139
Journal Issue
3
Pages
908-920
Date Issued
2011
Author(s)
Weissmann, M.
Harnisch, F.
CHUN-CHIEH WU
Ohta, Y.
Yamashita, K.
Kim, Y.-H.
Jeon, E.-H.
Nakazawa, T.
Aberson, S.
Abstract
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 NCEPandWRFto a comparably low influence inECMWFand 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. © 2011 American Meteorological Society.
Subjects
Data assimilation; Dropsondes; Field experiments; Numerical weather prediction/forecasting; Tropical cyclones
SDGs
Other Subjects
Data assimilation; Dropsondes; Field experiment; Numerical weather prediction/forecasting; Tropical cyclone; Data processing; Experiments; Hurricanes; Mathematical models; Storms; Three dimensional; Value engineering; Weather forecasting; airborne survey; climate prediction; data assimilation; numerical model; tropical cyclone; typhoon; weather forecasting; Taiwan
Type
journal article