Assimilation of GPS Refractivity from FORMOSAT-3/COSMIC Using a Nonlocal Operator with WRF 3DVAR and Its Impact on the Prediction of a Typhoon Event

被引:49
|
作者
Chen, Shu-Ya [1 ]
Huang, Ching-Yuang [1 ]
Kuo, Ying-Hwa [2 ,3 ]
Guo, Yong-Run [3 ]
Sokolovskiy, Sergey [2 ]
机构
[1] Natl Cent Univ, Dept Atmospher Sci, Chungli 32054, Taiwan
[2] Univ Corp Atmospher Res, Boulder, CO USA
[3] Natl Ctr Atmospher Res, Boulder, CO 80307 USA
来源
TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES | 2009年 / 20卷 / 01期
关键词
FORMOSAT-3/COSMIC; Data assimilation; Typhoon; RADIO OCCULTATION DATA; 3-DIMENSIONAL VARIATIONAL ANALYSIS; HORIZONTAL GRADIENTS; SIMULATION; ANGLE; MODEL;
D O I
10.3319/TAO.2007.11.29.01(F3C)
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A nonlocal observation operator has been developed to assimilate GPS radio occultation (RO) refractivity with WRF 3DVAR. For simplicity, in the past GPS RO refractivity was often assimilated using a local observation operator with the assumption that the GPS RO observation was representative of a model local point. Such an operator did not take into account the effects of horizontal inhomogeneity on the derived GPS RO refractivity. In order to more accurately model the observables, Sokolovskiy et al. (2005a) developed a nonlocal observation operator, which would take into account the effects of horizontal inhomogeneity on GPS RO measurements. This nonlocal observation operator calculates the integrated amount of the model refractivity along the ray paths centered at the perigee points. For comparative purposes, the nonlocal observation operator can be simplified by limiting the length of integration near the RO point. This is called the "local operator variant", which is equivalent to the original local operator except that the original one is performed with fixed tangent points at observation levels. For computational efficiency, assimilation using both the nonlocal operator and local operator variant now is performed with smear tangent points at the mean height of each model vertical level. In this study, the statistics of observation errors using both local and nonlocal operators were estimated based on WRF simulations. The observation errors produced by the nonlocal operator are about two times smaller than those generated by the local operator and in agreement with Sokolovskiy et al. (2005b). Each of the three operators is used to assimilate GPS RO refractivity soundings from the FORMOSAT-3/COSMIC mission using the WRF 3DVAR system. The WRF model then is applied to simulate Typhoons Kaemi (July 2006) which struck Taiwan with significant torrential rainfall. The analysis increments produced by the nonlocal operator and local operator variant are quite similar in horizontal and vertical distributions; whereas, the former is slightly stretched along the ray's direction, as a result of the longer integration length. The simulated typhoon tracks prior to landfall are quite similar for the three operators. Both the nonlocal operator and local operator variant improve the detoured track after landfall as predicted by the local operator. The nonlocal operator outperforms the two local operators in rainfall prediction at later times. The performances of the nonlocal operator in general are promising and can replace the local operator at no marked cost of computational efficiency.
引用
收藏
页码:133 / 154
页数:22
相关论文
共 7 条
  • [1] Application of WRF 3DVAR to Operational Typhoon Prediction in Taiwan: Impact of Outer Loop and Partial Cycling Approaches
    Hsiao, Ling-Feng
    Chen, Der-Song
    Kuo, Ying-Hwa
    Guo, Yong-Run
    Yeh, Tien-Chiang
    Hong, Jing-Shan
    Fong, Chin-Tzu
    Lee, Cheng-Shang
    WEATHER AND FORECASTING, 2012, 27 (05) : 1249 - 1263
  • [2] Assimilation of GPS Radio Occultation Refractivity Data with WRF 3D VAR and Its Impact on the Prediction of a Heavy Rainfall Event
    Ha, Ji-Hyun
    Lim, Gyu-Ho
    Choi, Suk-Jin
    JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2014, 53 (06) : 1381 - 1398
  • [3] A comparison of limited-area 3DVAR and ETKF-En3DVAR data assimilation using radar observations at convective scale for the prediction of Typhoon Saomai (2006)
    Shen, Feifei
    Xue, Ming
    Min, Jinzhong
    METEOROLOGICAL APPLICATIONS, 2017, 24 (04) : 628 - 641
  • [4] 3DVAR meteorological data assimilation and aerosol impact on the simulation of heat wave 2022 over Haryana using WRF-Chem
    Deb, Paushali
    Panda, S. K.
    Mondal, Unashish
    Dash, Sushil K.
    Sharma, Devesh
    ATMOSPHERIC POLLUTION RESEARCH, 2025, 16 (04)
  • [5] The Impact of Radar Radial Velocity Data Assimilation Using WRF-3DVAR System with Different Background Error Length Scales on the Forecast of Super Typhoon Lekima (2019)
    Chen, Jiajun
    Xu, Dongmei
    Shu, Aiqing
    Song, Lixin
    REMOTE SENSING, 2023, 15 (10)
  • [6] Assessing the Impact of Surface and Wind Profiler Data on Fog Forecasting Using WRF 3DVAR: An OSSE Study on a Dense Fog Event over North China
    Hu, Huiqin
    Sun, Juanzhen
    Zhang, Qinghong
    JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2017, 56 (04) : 1059 - 1081
  • [7] Assimilation of Water Vapor Retrievals from ZDR Columns Using the 3DVar Method for Improving the Short-Term Prediction of Convective Storms
    Chen, Haiqin
    Gao, Jidong
    Sun, Tao
    Chen, Yaodeng
    Wang, Yunheng
    Carlin, Jacob T.
    MONTHLY WEATHER REVIEW, 2024, 152 (04) : 1077 - 1095