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Use of three-cornered hat error estimates in MERRA-2 to guide an improved reanalysis-Part 1The three-cornered hat (3CH) method estimates the uncertainties of three different co-located model or observational data sets (Anthes and Rieckh, 2018; Sjoberg et al., 2021). Rieckh et al. (2021) used the 3CH method to compare the random error statistics of different global forecast and reanalysis models, as well as radio occultation (RO) and radiosonde observations. That study showed that the MERRA-2 reanalysis, while having smaller errors in the stratosphere than its predecessor MERRA, had larger errors in the troposphere than many of the other data sets analyzed. The MERRA-2 errors were particularly large in the tropics. In a collaborative effort between UCAR’s COSMIC (Constellation Observing System for Meteorology, Ionosphere and Meteorology) program and NASA’s Global Modeling and Assimilation Office (GMAO), we carried out further 3CH error diagnostics to help isolate the causes of these larger errors and help guide the development of an improved reanalysis.

This presentation summarizes random error statistics associated with MERRA-2, ECMWF’s ERA5 reanalysis, and COSMIC-2 (C2) RO observations. We compute 3CH error variance estimates of refractivity, as well as temperature and specific humidity using UCAR’s COSMIC Data Analysis and Archive Center (CDAAC) improved 1D-variational (1D-Var) retrieval (wetPf2) over 15 latitude bands from 45S to 45N. The 1D-Var retrievals of specific humidity and temperature for C2 use NCEP’s Global Forecast System (GFS) as the background. Anthes et al. (2021) showed that it gives accurate estimates of temperature and specific humidity in the tropics and subtropics, even in the challenging environment of intense Hurricane Dorian (2019).

This presentation confirms the previous results that MERRA-2 has significantly larger errors in the tropics and subtropics than either C2 or ERA5. Its errors are larger between 30S and 30N compared to 30-45 N-S latitudes, and are also larger over land compared to oceans. Most of the MERRA-2 refractivity errors come from specific humidity, except over land below 3 km where temperature errors are large. These results suggest that moist convection and atmospheric boundary layer physics in MERRA-2 may be responsible for a significant part of the higher uncertainties. These results are being used to guide GMAO in developing an improved next-generation reanalysis, as shown in a companion presentation submitted to this conference (El Akkraoui et al., 2021), which extends this study and describes improvements to MERRA-2 leading to the next GMAO reanalysis.
Document ID
20210020722
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Jeremiah Sjoberg
(University Corporation for Atmospheric Research Boulder, Colorado, United States)
Amal El Akkraoui
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Therese Rieckh
(University Corporation for Atmospheric Research Boulder, Colorado, United States)
Lawrence Takacs
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Richard Anthes
(University Corporation for Atmospheric Research Boulder, Colorado, United States)
Ronald Gelaro
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Date Acquired
August 19, 2021
Subject Category
Mathematical And Computer Sciences (General)
Earth Resources And Remote Sensing
Meeting Information
Meeting: AMS 102nd annual meeting
Location: Houston, TX
Country: US
Start Date: January 23, 2022
End Date: January 27, 2022
Sponsors: American Meteorological Society
Funding Number(s)
CONTRACT_GRANT: NNG17HP01C
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
NASA Peer Committee
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