Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system

被引:0
|
作者
Kamineni, R [1 ]
Rizvi, SRH
Kar, SC
Mohanty, UC
Paliwal, RK
机构
[1] Indian Inst Technol, Ctr Atmospher Sci, New Delhi 110016, India
[2] Natl Ctr Medium Range Weather Forecasting, New Delhi 110003, India
关键词
MSMR data; wind speed; total precipitable water content; GDAS; impact;
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Oceansat-1 was successfully launched by India in 1999, with two payloads, namely Multi-frequency Scanning Microwave Radiometer (MSMR) and Ocean Color Monitor (OCM) to study the biological and physical parameters of the ocean. The MSMR sensor is configured as an eight-channel radiometer using four frequencies with dual polarization. The MSMR data at 75 kin resolution from the Oceansat-I have been assimilated in the National Centre for Medium Range Weather Forecasting (NCMRWF) data assimilation forecast system. The operational analysis and forecast system at NCMRWF is based on a T80L18 global spectral model and Spectral Statistical Interpolation (SSI) scheme for data analysis. The impact of the MSMR data is seen globally, however it, is significant over the oceanic region where conventional data are rare. The dry-nature of the control analyses have been removed by utilizing the MSMR data. Therefore, the total precipitable water data from MSMR has been identified as a very crucial parameter in this study. The impact of surface wind speed from MSMR is to increase easterlies over the tropical Indian Ocean. Shifting of the positions of westerly troughs and ridges in the south Indian Ocean has contributed to reduction of temperature to around 30degreesS.
引用
收藏
页码:351 / 364
页数:14
相关论文
共 50 条
  • [41] Physical initialization in the NMC global data assimilation system
    Treadon, RE
    METEOROLOGY AND ATMOSPHERIC PHYSICS, 1996, 60 (1-3) : 57 - 86
  • [42] Ensemble data assimilation with the NCEP Global Forecast System
    Whitaker, Jeffrey S.
    Hamill, Thomas M.
    Wei, Xue
    Song, Yucheng
    Toth, Zoltan
    MONTHLY WEATHER REVIEW, 2008, 136 (02) : 463 - 482
  • [43] Overlapping Windows in a Global Hourly Data Assimilation System
    Slivinski, Laura C.
    Lippi, Donald E.
    Whitaker, Jeffrey S.
    Ge, Guoqing
    Carley, Jacob R.
    Alexander, Curtis R.
    Compo, Gilbert P.
    MONTHLY WEATHER REVIEW, 2022, 150 (06) : 1317 - 1334
  • [44] The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System
    Hong, Song-You
    Kim, Hyun Mee
    Kim, Jung-Eun
    Hwang, Seung-On
    Park, Hoon
    TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES, 2011, 22 (01): : 41 - 47
  • [45] THE CANADIAN GLOBAL DATA ASSIMILATION SYSTEM - DESCRIPTION AND EVALUATION
    MITCHELL, HL
    CHARETTE, C
    LAMBERT, SJ
    HALLE, J
    CHOUINARD, C
    MONTHLY WEATHER REVIEW, 1993, 121 (05) : 1467 - 1492
  • [46] Impacts of data assimilation on the global ocean carbonate system
    Visinelli, L.
    Masina, S.
    Vichi, M.
    Storto, A.
    Lovato, T.
    JOURNAL OF MARINE SYSTEMS, 2016, 158 : 106 - 119
  • [47] Use and impact of automated aircraft data in a global 4DVAR data assimilation system
    Cardinali, C
    Isaksen, L
    Andersson, E
    MONTHLY WEATHER REVIEW, 2003, 131 (08) : 1865 - 1877
  • [48] Satellite Data Assimilation in Global Forecast System in India
    Basu, Swati
    REMOTE SENSING AND MODELING OF THE ATMOSPHERE, OCEANS, AND INTERACTIONS V, 2014, 9265
  • [49] Introduction of the GSI into the NCEP Global Data Assimilation System
    Kleist, Daryl T.
    Parrish, David F.
    Derber, John C.
    Treadon, Russ
    Wu, Wan-Shu
    Lord, Stephen
    WEATHER AND FORECASTING, 2009, 24 (06) : 1691 - 1705
  • [50] A Hybrid Global Ocean Data Assimilation System at NCEP
    Penny, Stephen G.
    Behringer, David W.
    Carton, James A.
    Kalnay, Eugenia
    MONTHLY WEATHER REVIEW, 2015, 143 (11) : 4660 - 4677