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The Community Radiative Transfer Model (CRTM): Community-Focused Collaborative Model Development Accelerating Research to OperationsThe Joint Center for Satellite Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) is a fast, 1-D radiative transfer model used in numerical weather prediction, calibration/validation, etc. across multiple federal agencies and universities. The key benefit of the CRTM is that it is a satellite simulator. It provides a highly accurate representation of satellite radiances by using the specific sensor response functions convolved with a line-by-line radiative transfer model (LBLRTM). CRTM covers the spectral ranges consistent with all present operational and most research satellites, from visible to microwave. The capability to simulate ultraviolet radiances and support space-based radar sensors is being added over the next two years in CRTM Version 3.0.

In addition to simulated radiances, the CRTM also provides Jacobian outputs needed to interpret satellite observations for numerical weather prediction. The Jacobian estimates how changes in geophysical parameters affect simulated measurements from satellite sensors. Using the Jacobian in modeling and weather prediction improves the accuracy and efficiency of data analysis, leading to better weather predictions.

The CRTM model's success and growth depend on community contributions and evaluation. To facilitate this, we have made the CRTM highly accessible through modular programming, clear documentation and tutorials, public domain licensing, unfettered public access via Github, and a clear path to operational implementation for innovative research. We encourage and welcome contributions from the community to help us continue to improve the CRTM.
Document ID
20230008420
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Benjamin T Johnson
(Joint Center for Satellite Data Assimilation)
Cheng Dang
(Joint Center for Satellite Data Assimilation)
Patrick Stegmann
(National Center for Atmospheric Research Boulder, Colorado, United States)
Quanhua Liu
(National Oceanic and Atmospheric Administration Washington D.C., District of Columbia, United States)
Isaac Moradi
(University of Maryland University College Adelphi, Maryland, United States)
Thomas Auligne
(Joint Center for Satellite Data Assimilation)
Date Acquired
May 31, 2023
Publication Date
October 1, 2023
Publication Information
Publication: Bulletin of the American Meteorological Society
Publisher: American Meteorological Society
Volume: 104
Issue: 10
Issue Publication Date: October 1, 2023
ISSN: 0003-0007
e-ISSN: 1520-0477
Subject Category
Meteorology and Climatology
Funding Number(s)
CONTRACT_GRANT: 80NSSC23M0011
CONTRACT_GRANT: GSFC - 606.2 GRANT
CONTRACT_GRANT: NOAA-JPSS
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
NASA Peer Committee
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