Regional Assimilation System for Transformed Retrievals from Satellite High-Resolution Infrared Data

Abstract

Satellite retrievals strive to exploit the information contained in thousands of channels provided by hyperspectral sensors and show promise in providing a gain in computational efficiency over current radiance assimilation methods by transferring computationally expensive radiative transfer calculations to retrieval providers. This paper describes the implementation of a new approach based on the transformation proposed in 2008 by Migliorini et al., which reduces the impact of the a priori information in the retrievals and generates transformed retrievals (TRs) whose assimilation does not require knowledge of the hyperspectral instruments characteristics. Significantly, the results confirm both the viability of Migliorini’s approach and the possibility of assimilating data from different hyperspectral satellite sensors regardless of the instrument characteristics. The Weather Research and Forecasting (WRF) Model’s Data Assimilation (WRFDA) 3-h cycling system was tested over the central North Pacific Ocean, and the results show that the assimilation of TRs has a greater impact in the characterization of the water vapor distribution than on the temperature field. These results are consistent with the knowledge that temperature field is well constrained by the initial and boundary conditions of the Global Forecast System (GFS), whereas the water vapor distribution is less well constrained in the GFS. While some preliminary results on the comparison between the assimilation with and without TRs in the forecasting system are presented in this paper, additional work remains to explore the impact of the new assimilation approach on forecasts and will be provided in a follow-up publication.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 01, 2020
Source ID
10.1175/jamc-d-19-0203.1

Entities

People

  • Jean-luc Moncet
  • Paolo Antonelli
  • Paolo Scaccia
  • Siebren De Haan
  • Steven Businger
  • Tiziana Cherubini

Organizations

  • Office of Naval Research
  • Royal Netherlands Meteorological Institute
  • University of Hawaiʻi at Mānoa

Tags

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Computer Vision.

Technology Areas

  • Space