Natural Hazards

, Volume 82, Issue 2, pp 845–855 | Cite as

Satellite radiance assimilation using a 3DVAR assimilation system for hurricane Sandy forecasts

  • Tanvir IslamEmail author
  • Prashant K. Srivastava
  • Dinesh Kumar
  • George P. Petropoulos
  • Qiang Dai
  • Lu Zhuo
Original Paper


In this article, we present an assimilation impact study for forecasting hurricane Sandy using a three‐dimensional variational data assimilation system (3DVAR). In particular, we employ the 3DVAR component of the Weather Research and Forecasting Model and conduct analysis/forecast cycling experiments for “control” and “radiance” assimilation cases for the hurricane Sandy period. In “control” assimilation experiment, only conventional air and surface observations data are assimilated, while, in “radiance” assimilation experiment, along with the conventional air and surface observations data, the satellite radiance data from the Advanced Microwave Sounding Unit-A (AMSU-A) and the Microwave Humidity Sounder (MHS) sensors are also assimilated. For the radiance assimilation, we employ the community radiative transfer model as the forward operator and perform quality control and bias correction procedure before the radiance data are assimilated. In order to assess the impact of the assimilation experiments, we produce 132-h deterministic forecast starting on 00 UTC October 25, 2012. The results reveal that, in particular, the assimilation of AMSU-A satellite radiances helps to improve the short- to medium-range forecast (up to ~60-h lead time). The forecast skill is degraded in the long-range forecast (beyond 60 h) with the AMSU-A assimilation.


Variational data assimilation Numerical weather prediction (NWP) Cyclone forecast Track propagation WRF 3DVAR Radiative transfer ATOVS AMSU-A AMSU-B MHS 



Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). The data for this study are from NOAA’s National Operational Model Archive and Distribution System (NOMADS) which is maintained at NOAA’s National Climatic Data Center (NCDC). The views expressed here are those of the authors solely and do not constitute a statement of policy, decision, or position on behalf of NOAA, NASA, or the authors’ affiliated institutions.


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Tanvir Islam
    • 1
    • 2
    • 3
    Email author
  • Prashant K. Srivastava
    • 4
    • 5
  • Dinesh Kumar
    • 6
  • George P. Petropoulos
    • 7
  • Qiang Dai
    • 8
  • Lu Zhuo
    • 9
  1. 1.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA
  2. 2.NOAA/NESDIS Center for Satellite Applications and ResearchCollege ParkUSA
  3. 3.Cooperative Institute for Research in the AtmosphereColorado State UniversityFort CollinsUSA
  4. 4.NASA Goddard Space Flight CenterGreenbeltUSA
  5. 5.Earth System Science Interdisciplinary CenterUniversity of MarylandCollege ParkUSA
  6. 6.Central University of JammuJammuIndia
  7. 7.Department of Geography and Earth SciencesAberystwyth UniversityAberystwythUK
  8. 8.School of Geographic ScienceNanjing Normal UniversityNanjingChina
  9. 9.Department of Civil EngineeringUniversity of BristolBristolUK

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