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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2020

Assimilating GCOM-W1 AMSR2 and TRMM TMI Radiance Data in GEOS Analysis and Reanalysis

The Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) observed the Earth in lower latitudes between 1997 - 2015. Its conical-scan radiometer has nine channels and measured microwave radiances between 10 and 89 GHz. These data provide information on atmospheric temperature, humidity, clouds, precipitation, as well as sea surface temperature. Radiance data from other microwave radiometers such as Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) onboard various Defense Meteorological Satellite Program (DMSP) satellites are assimilated in clear-sky conditions in the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. The GMAO's Hybrid 4D-EnVar-based Atmospheric Data Assimilation System (ADAS) is enhanced with an all-sky microwave radiance data assimilation capability in the real-time GEOS-Forward Processing (FP) system. Currently, the FP system assimilates Global Precipitation Measurement (GPM) microwave imager (GMI) radiance data utilizing this all-sky capability, and is being extended to use more all-sky data from other microwave radiometers. In this presentation, we will focus on impacts of all-sky TMI radiance data on GEOS analyses of atmospheric moisture, precipitation and other fields, and discuss their applications for future GEOS reanalyses.

Jin, Jianjun↗
NASA NTRS2020

Evaluation of Global Fire Weather Database Reanalysis and Short-Term Forecast Products

Daily Fire Weather Index (FWI) System components calculated from the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), are compared to FWI calculations from a global network of weather stations over 2004–2018, and short-term, experimental (8 d) daily FWI forecasts are evaluated for their skill across the Terrestrial Ecoregions of the World for 2018. FWI components from MERRA-2 were, in general, biased low compared to station data, but this reflects a mix of coherent low and high biases of different magnitudes. Biases in different MERRA-2 FWI components were related to different biases in weather input variables for different regions, but temperature and relative humidity biases were the most important overall. FWI forecasts had high skill for 1–2 d lead times for most of the world. For longer lead times, forecast skill decreased most quickly at high latitudes and was most closely related to decreasing skill of relative humidity forecasts. These results provide a baseline for the evaluation and use of fire weather products calculated from global analysis and forecast fields.

Global Fire Weather Database↗
NASA NTRSDate not supplied

PolarMERRA: A collaborative effort for NASA’s polar reanalysis

The polar atmosphere is often poorly represented in global models, adversely impacting analyses in these regions and forecasts on much larger scales. PolarMERRA is an initiative that brings together the modeling expertise from NASA’s global modeling and assimilation office (GMAO) and observational expertise from NASA’s Cryospheric sciences lab to assess and improve the representation of polar processes in the NASA’s modelling system in preparation for upcoming and next generation reanalyses. Model improvements in resolution, physics, and data assimilation have been guided by assessment of model skill in the polar regions. Preliminary results from a novel validation framework indicate a reduction in near surface air temperature, turbulent fluxes, and precipitation biases.

Chelsea Parker↗