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Development of Gridded Innovations and Observations Supplement to MERRA-2Atmospheric reanalysis have become an important source of data for weather and climate research, owing to the continuity of the data, but especially because of the multitude of observational data included (radiosondes, commercial aircraft, retrieved data products and radiances). However, the presence of assimilated observations can vary based on numerous factors, and so it is difficult or impossible for a researcher to say with any degree of certainty how many and what type of observations contributed to the reanalysis data they are using at any give point in time or space, or their contribution to the eventual analyzed fields. For example, quality control, transmission interruptions, and station outages can occasionally affect data availability. While orbital paths are known, drift in certain instruments, cloud clearing, and the large number of available instruments makes it challenging to know which satellite is observing any region at any point in the diurnal cycle. Furthermore, there is information from the statistics generated by the data assimilation that can help understand the model and the quality of the reanalysis. Typically, the assimilated observations and their innovations are saved in observation-space data formats and are not easily made available to reanalysis users.Here, we present an early version of a data set has been developed to make the MERRA-2 assimilated observations available for rapid and general use, by simplifying the data format. The observations are binned to a grid similar as MERRA-2 and saved as netCDF. This data collection includes the mean and number of observations in the bin as well as its variance. The data will also include the innovations from the data assimilation, the forecast departure and the analysis increment, as well as bias correction (for satellite radiances). In this paper, we present the data format (called MERRA-2 Gridded Innovations and Observations or GIO) and its strengths and limitations with some initial testing and validation of the methodology.
Document ID
20190000499
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Bosilovich, Michael G. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Da Silva, Arlindo M. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
February 9, 2019
Publication Date
December 10, 2018
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN64294
Meeting Information
Meeting: American Geophysical Union (AGU) 2018 Fall Meeting
Location: Washington, D.C.
Country: United States
Start Date: December 10, 2018
End Date: December 14, 2018
Sponsors: American Geophysical Union (AGU)
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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