NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
pyCRTM: A Python Interface for the Community Radiative Transfer ModelThe Community Radiative Transfer Model (CRTM) is a powerful and versatile scalar radiative transfer model for satellite data assimilation and remote sensing applications. It is implemented as an object-oriented Fortran library, enabling flexible code development and optimal runtime performance on clusters. The downsides of the Fortran interface are a steep learning curve for students and the reduced productivity of users that is typical for static compiled languages, in contrast to dynamic interpreted languages like Python. pyCRTM is a new software framework that directly interfaces the CRTM Fortran data structures and procedures in Python, leveraging both the simplicity and ease of use of Python syntax as well as the flexibility arising from the vast contemporary Python ecosystem. The goal of pyCRTM is to lower the barrier of entry for university students to learn and use the CRTM and to boost the productivity of researchers seeking to create new methods in radiative transfer and data assimilation, or seeking to apply the CRTM to study atmospheric phenomena without having to go through the pre-existing complexity of the CRTM Fortran interface.
Document ID
20220002673
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Bryan M Karpowicz ORCID
(University of Maryland, Baltimore County Baltimore, Maryland, United States)
Patrick G Stegmann ORCID
(NOAA Climate Prediction Center College Park, United States)
Benjamin T Johnson
(NOAA Climate Prediction Center College Park, United States)
Hui W Christophersen ORCID
(United States Naval Research Laboratory Washington D.C., District of Columbia, United States)
Edward J Hyer ORCID
(United States Naval Research Laboratory Washington D.C., District of Columbia, United States)
Andrew Lambert
(General Dynamics (United States) Fairfax, Virginia, United States)
Eric Simon
(Science Applications International Corporation (United States) McLean, Virginia, United States)
Date Acquired
February 16, 2022
Publication Date
May 18, 2022
Publication Information
Publication: Journal of Quantitative Spectroscopy and Radiative Transfer
Publisher: Elsevier
Volume: 288
Issue Publication Date: September 1, 2022
ISSN: 0022-4073
Subject Category
Earth Resources And Remote Sensing
Computer Programming And Software
Funding Number(s)
CONTRACT_GRANT: 80NSSC22M0001
CONTRACT_GRANT: GSFC - 606.2 GRANT
CONTRACT_GRANT: SPEC5732
Distribution Limits
Public
Copyright
Other
Technical Review
NASA Peer Committee
Keywords
Python
Radiative Transfer
CRTM
Remote sensing
Data assimulation
No Preview Available