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MERRA HIRS2 NOAA10 : Gridded Monthly Time-Mean Observation (obs) Values V001 at GES DISC

Entry ID: GES_DISC_MA_HIRS2_NOAA10_OBS_V001

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Summary

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

Link: GET DATA > ECHO

Description: Refine your granule search with ECHO's next generation Earth Science discovery tool (Reverb) using information from this record.

Geographic Coverage

(Click for Interactive Map)

Spatial coordinates

N: 90.0

S: -90.0

E: 180.0

W: -180.0

Temporal Coverage

Start Date: 2000-02-18

Start Date: 2002-07-04

Location Keywords

OCEAN > ARCTIC OCEAN

OCEAN > ATLANTIC OCEAN

Data Resolution

Latitude Resolution: 4 KM, 9 KM
Longitude Resolution: 4 KM, 9 KM
Horizontal Resolution Range: 1 km - < 10 km or approximately .01 degree - < .09 degree
Temporal Resolution: Monthly Climatology
Temporal Resolution Range: Monthly Climatology

Science Keywords

ATMOSPHERE > AEROSOLS > AEROSOL BACKSCATTER > AEROSOL REFLECTANCE

ATMOSPHERE > AEROSOLS > AEROSOL EXTINCTION

ISO Topic Category

BIOTA

CLIMATOLOGY/METEOROLOGY/ATMOSPHERE

GEOSCIENTIFIC INFORMATION

OCEANS

Platform

TERRA > Earth Observing System, TERRA (AM-1)

AQUA > Earth Observing System, AQUA

Instrument

MODIS > Moderate-Resolution Imaging Spectroradiometer

Project

EOS > Earth Observing System

EOSDIS > Earth Observing System Data Information System

ESIP > Earth Science Information Partners Program

Quality For data quality information on MODIS SST products performed by the Ocean
Biology Processing Group (OBPG) see
http://oceancolor.gsfc.nasa.gov/DOCS/modis_sst/

Access Constraints None

Use Constraints Publications of research results utilizing these data must acknowledge the
Ocean Biology Processing Group (OBPG) at the NASA Goddard Space Flight Center,
Greenbelt, MD, USA.

Data Set Progress

IN WORK

Data Center

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

Data Center URL: http://disc.gsfc.nasa.gov/

Data Center Personnel
Name: GES DISC HELP DESK SUPPORT GROUP Phone: 301-614-5224 Fax: 301-614-5268 Email: gsfc-help-disc at lists.nasa.gov Contact Address: Goddard Earth Sciences Data and Information Services Center Code 610.2 NASA Goddard Space Flight Center City: Greenbelt Province or State: MD Postal Code: 20771 Country: USA

Distribution

Distribution Media: FTP

Distribution Format: HDF

Personnel

MELANIE F. MEAUX

Role: DIF AUTHOR

Email: gsfc-gcmduso at mail.nasa.gov

Creation and Review Dates

DIF Creation Date: 2001-06-11

Last DIF Revision Date: 2012-07-27

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