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About data sources

VERSION 6  Click to view document history
Created on: Jul 22, 2010 11:46 AM by Carlos Cruz - Last Modified:  Jul 22, 2010 12:25 PM by Carlos Cruz

"Data assimilation proceeds by analysis cycles. In each analysis  cycle, observations of the current (and possibly, past) state of a  system are combined with the results from a numerical weather prediction model (the forecast) to produce an analysis, which is considered as 'the best' estimate of the current state of the system. This is called the analysis step.  Essentially, the analysis step tries to balance the uncertainty in the  data and in the forecast. The model is then advanced in time and its  result becomes the forecast in the next analysis cycle." (Source: Wikipedia).

 

An important component of the Data Asiimilation system is the "Data". Data refers to observational data obtained from various sources:

 

  • Satellites
  • Balloons
  • Dropsondes
  • Radiosondes
  • Rawinsonde
  • Airplanes
  • Ships
  • Buoys
  • Surface land obs

 

Reanalysis.

 

Retrospective-analyses, or reanalyses, comprise the combination of state of the art models and assimilation methods with highly quality controlled observations, yielding globally continuous data with supporting output diagnostics produced from the model physical parameterizations. The initial reanalyses have proved to be extremely useful data sets for the study of weather and climate variability.  For example, atmospheric reanalyses have also provided forcing and boundary conditions for other components of the Earth system, such as ocean and land models and data assimilation systems. Also, ocean reanalyses have been applied to research in ocean circulation and climate as well as in biochemistry, eco-systems, and geodesy. Subsequent reanalyses have improved upon the models and assimilation techniques, and the observational data sets likewise have improved through quality control.  Presently, new atmospheric, oceanic and land reanalyses are coming available from NASA, NOAA, and other institutions.


Reanalyses continue to evolve, and in the next generations of reanalyses, coupling between components of the Earth system will be more prominent. Quantifying the uncertainty and improving the quality of reanalyses is increasingly important, both for current and new developing reanalysis efforts.

 

Examples:

 

ReanalysisPeriod covered
ResolutionModels
NCEP R11948-presentT62GFS+SSI
ERA401958-20022.5degIFS+ECMWFDAS
JRA-251979-20031.25degJCDAS
NCEP R21979-presentT384GFS+GSI

 

 

MERRA

 

  • MODERN ERA RETROSPECTIVE-ANALYSIS FOR RESEARCH AND APPLICATIONS
  • “MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The Project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context.”
  • Why new reanalysis? Previous long-term reanalyses of the Earth's climate had high levels of uncertainty in precipitation and inter-annual variability.
  • MERRA is anticipated to improve upon the representation of the water cycle in reanalyses.
  • Uses IAU: allows output at higher frequencies than the 6 hourly analyses.
  • 2D diagnostics available at 1 hour intervals.

 

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