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Data Assimilation: Comparison and Hybridization between Ensemble and Variational Methods

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Book cover Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Prediction

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Abstract

The accuracy of numerical weather prediction (NWP) depends critically on the qualities of the initial conditions and the forecast model. The initial conditions of an NWP model usually come from data assimilation (DA), a procedure that aims to estimate the state and uncertainty of the atmosphere as accurately as possible by combining all available atmospheric information. In other words, DA is known as the process of creating the best estimate of the initial state for NWP models through combining all sources of information, including the first guess from previous short-term model forecasts and observations, along with the associated uncertainties in each source of information.

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Author information

Authors and Affiliations

  1. Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania, USA

    Fuqing Zhang

  2. NCMRWF, A-50, Institutional Area, Sector-62, Noida, India

    Ashish Routray

Authors
  1. Fuqing Zhang
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  2. Ashish Routray
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Editor information

Editors and Affiliations

  1. School of Earth, Ocean and Climate Sciences, Indian Institute of Technology Bhubaneswar, 110016, Hauz Khas, Delhi, India

    U. C. Mohanty

  2. Hurricane Research Division, Atlantic Oceanographic Meteorological Laboratory, NOAA, Rickenbacker Causeway, 4301, 33149, Miami, FL, USA

    Sundararaman G. Gopalakrishnan

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Zhang, F., Routray, A. (2016). Data Assimilation: Comparison and Hybridization between Ensemble and Variational Methods. In: Mohanty, U.C., Gopalakrishnan, S.G. (eds) Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Prediction. Springer, Dordrecht. https://doi.org/10.5822/978-94-024-0896-6_13

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