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MERRA AMSUA NOAA16 : Gridded Monthly Time-Mean Observation minus Analysis (oma) Values V001 at GES DISC Entry ID: GES_DISC_MA_AMSUA_NOAA16_OMA_V001 |
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Summary
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Abstract:
The differences between the observations and the forecast background used for the analysis (the innovations or O-F for short) and those between the observations and the final analysis (O-A) are by-products of any assimilation system and provide information about the quality of the analysis and the impact of the observations. Innovations have been traditionally used to diagnose observation, background and analysis errors at observation locations (Hollingsworth and Lonnberg 1989; Dee and da Silva 1999). At the most simplistic level, innovation variances can be used as an upper bound on background errors, which are, in turn, an upper bound on the analysis errors. With more processing (and the assumption of optimality), the O-F and O-A statistics can be used to estimate observation, background and analysis errors (Desroziers et al. 2005). They can also be used to estimate the systematic and random errors in the analysis fields. Unfortunately, such data are usually not readily available with reanalysis products. With MERRA, however, a gridded version of the observations and innovations used in the assimilation process is being made available. The dataset allows the user to conveniently perform investigations related to the observing system and to calculate error estimates. Da Silva (2011) provides an overview and analysis of these datasets for MERRA. The innovations may be thought of as the correction to the background required by a given instrument, while the analysis increment (A-F) is the consolidated correction once all instruments, observation errors, and background errors have been taken into consideration. The extent to which the O-F statistics for the various instruments are similar to the A-F statistics reflects the degree of homogeneity of the observing system as a whole. Using the joint probability density function (PDF) of innovations and analysis increments, da Silva (2011) introduces the concepts of the effective gain (by analogy with the Kalman gain) and the contextual bias. In brief, the effective gain for an observation is a measure of how much the assimilation system has drawn to that type of observation, while the contextual bias is a measure of the degree of agreement between a given observation type and all other observations assimilated. With MERRAs gridded observation and innovation data sets, a wealth of information is available for examination of the quality of the analyses and how the different observations impact the analyses and interact with each other. Such examinations can be conducted regionally or globally and should provide useful information for the next generation of reanalyses. |
Related URL
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Link:
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Description: Refine your granule search with ECHO's next generation Earth Science discovery tool (Reverb) using information from this record. Link: VIEW PROJECT HOME PAGE Description: The GES DISC Data Modelling and Assimilation web site. Link: VIEW RELATED INFORMATION Description: The GMAO home page |
Geographic Coverage
| N: 90.0 | S: -90.0 | E: 180.0 | W: -180.0 |
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Data Set Citation
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Dataset Originator/Creator:
GMAO
Dataset Title: MERRA AMSUA NOAA16 : Gridded Monthly Time-Mean Observation minus Analysis (oma) Values Dataset Release Date: June 1, 2011 Dataset Release Place: NASA Goddard Space Flight Center Version: 001 Data Presentation Form: Digital Science Data Online Resource: http://disc.sci.gsfc.nasa.gov/MDISC/ |
Temporal Coverage
| Start Date: 2001-01-01 |
Location Keywords
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GEOGRAPHIC REGION
> GLOBAL
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Data Resolution
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Latitude Resolution:
2/3 degrees
Longitude Resolution: 1/2 degrees Vertical Resolution: 15 levels Temporal Resolution: Monthly |
Science Keywords
| ATMOSPHERE >ALTITUDE >BAROMETRIC ALTITUDE [Definition] |
| LAND SURFACE >LAND USE/LAND COVER >LAND COVER [Definition] |
| LAND SURFACE >TOPOGRAPHY >TERRAIN ELEVATION [Definition] |
ISO Topic Category
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CLIMATOLOGY/METEOROLOGY/ATMOSPHERE
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Project
| EOSDIS >Earth Observing System Data Information System [Information] |
| ESIP >Earth Science Information Partners Program [Information] |
| MERRA TIME-MEAN OBSERVATION DATA >MERRA for Research and Applications Gridded Monthly Time-Mean Obs Dataset [Information] |
| CWIC >CEOS WGISS Integrated Catalog [Information] |
Keywords
| TB |
| EOSDIS |
Data Set Progress
| COMPLETE |
Data Center
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Goddard Earth Sciences Data and Information Services Center (formerly Goddard DAAC), Global Change Data Center, Earth Sciences Division, Science and Exploration Directorate, Goddard Space Flight Center, NASA
[Information]
Data Center URL: http://disc.gsfc.nasa.gov/
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Distribution
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Distribution_Media:
Online (FTP)
Distribution_Format: HDF (Grid) Fees: Free |
Personnel
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GLOBAL MODELING AND ASSIMILATION OFFICE Role: TECHNICAL CONTACT Phone: 301-614-6142 Email: data at gmao.gsfc.nasa.gov Contact Address: NASA Goddard Space Flight Center Code 610.1 City: Greenbelt Province or State: MD Postal Code: 20771 Country: USA |
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DANA
OSTRENGA Role: DIF AUTHOR Phone: 301-614-5475 Email: dana.m.ostrenga at nasa.gov Contact Address: NASA Goddard Space Flight Center Code 610.2 City: Greenbelt Province or State: MD Postal Code: 20771 Country: USA |
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ARLINDO
DASILVA Role: INVESTIGATOR Email: Arlindo.Dasilva at nasa.gov Contact Address: NASA/Goddard Space Flight Center Data Assimilation Office City: Greenbelt Province or State: MD Postal Code: 20771 Country: USA |
Publications/References
(),
Creation and Review Dates
DIF Creation Date:
2007-06-14
Last DIF Revision Date:
2011-06-21
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