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Ensemble Transform Sensitivity Method For Target Observations: An OSSE Case Study

Abstract

Unmanned aerial system (UAS) for improving forecast accuracy of high-impact weather systems has been studied under the Sensing Hazards with Operational Unmanned Technology (SHOUT) project in the NOAA joint OSSE system. Due to the limited number of dropsondes, adaptive observation schemes have to be considered in these experiments in order to fully take advantages of this observing system. Among the existing adaptive observation schemes, we investigated ensemble transform (ET) methods and proposed a new ET based method for better performance in computational efficiency. An ET-based sensitivity (ETS) method, which calculates the gradient of forecast error variance reduction to analysis error variance reduction, is proposed to specify regions for possible adaptive observations. The ETS method will be descripted and results from an OSSE case study will be presented.

Article / Publication Data
Active/Online
YES
Available Metadata
Fiscal Year
Published On
January 11, 2016
URL ↗
Event

This publication was presented at the following:

Title
2016 - 96th AMS Annual Meeting
Sponsor
American Meteorological Society
Type
Conference presentation
Location
New Orleans, LA - United States
When
Jan 09, 2016 - Jan 14, 2016

Authors

Authors who have authored or contributed to this publication.

  • Hongli Wang - lead Gsl
    Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder
    NOAA/Global Systems Laboratory
  • Tanya R. Peevey - second Gsl
    Cooperative Institute for Research in the Atmosphere, Colorado State University
    NOAA/Global Systems Laboratory
  • Jason M. English - third Gsl
    Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder
    NOAA/Global Systems Laboratory
  • Andrew C. Kren - fourth Other noaa
    Other
  • Lidia Cucurull - fifth Gsl
    Federal