Accelerating assimilation development for new observing systems using EFSO

Details

• Journal Title:
  Nonlinear Processes in Geophysics
• Personal Author:
  Lien, Guo-Yuan ; Hotta, Daisuke ; Kalnay, Eugenia ; Miyoshi, Takemasa ; Chen, Tse-Chun
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office) ; NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction) ; OST (Office of Science and Technology) ; CICS (Cooperative Institute for Climate and Satellites) ; CREST (Center for Earth System Sciences and Remote Sensing Technologies and Tech Center at City College of CUNY)
• Description:
  To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.
• Keywords:
  Forecasting Precipitation
• Source:
  Nonlinear Processes in Geophysics, 25, 129–143
• DOI:
  https://doi.org/10.5194/npg-25-129-2018
• Document Type:
  Journal Article
• Funding:
  Grant no. NA10OAR4310248 ; Grant no. NA16NWS4680009
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:b5a431368ef023b07e9f7778538ae54008b3e5fac0bbf2ae74eea7e990c9035ac2b213ff97c1b52c733fda1c28d676ccdb200d62349641afbd82cc052c85a8e0
• Download URL:
  https://repository.library.noaa.gov/view/noaa/24487/noaa_24487_DS1.pdf
• File Type:
  [PDF - 4.13 MB ]