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Importance of Radiative Transfer Models in Atmospheric Remote SensingRadiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability.
RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications.

Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections.

Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics.

This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these
Document ID
20230018057
Acquisition Source
Goddard Space Flight Center
Document Type
Poster
Authors
Isaac Moradi
(University of Maryland Global Campus Adelphi, Maryland, United States)
Derek Posselt
(Jet Propulsion Laboratory La Cañada Flintridge, United States)
Ian Adams
(Goddard Space Flight Center Greenbelt, United States)
Patricia Castellanos
(Goddard Space Flight Center Greenbelt, United States)
John Yorks
(Goddard Space Flight Center Greenbelt, United States)
Date Acquired
December 11, 2023
Subject Category
Earth Resources and Remote Sensing
Meeting Information
Meeting: 23rd Meeting of the American Geophysical Union (AGU)
Location: San Francisco, CA
Country: US
Start Date: December 11, 2023
End Date: December 15, 2023
Sponsors: American Geophysical Union
Funding Number(s)
CONTRACT_GRANT: 80NSSC23M0011
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Peer Committee
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