Data assimilation: Comparison and hybridization between ensemble and variational methods

Fuqing Zhang, Ashish Routray

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationAdvanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Predictions
PublisherSpringer Netherlands
Pages361-383
Number of pages23
ISBN (Electronic)9789402408966
ISBN (Print)9789402408942
DOIs
Publication statusPublished - Jan 1 2016

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)
  • Environmental Science(all)

Cite this

Zhang, F., & Routray, A. (2016). Data assimilation: Comparison and hybridization between ensemble and variational methods. In Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Predictions (pp. 361-383). Springer Netherlands. https://doi.org/10.5822/978-94-024-0896-6_13