NCEP/NCAR CDAS/Reanalysis

The analysis is available here as a dataset, including an interactive viewer and downloadable data files.

Entries are included for much more of the dataset than is currently on-line. We are starting with the MONTHLY data and working our way to finer resolution as needed. Check the outline to see which variables are actually on-line here at present (see below for other sources).

The NCEP/NCAR Reanalysis Project is a joint project between the National Centers for Environmental Prediction (NCEP, formerly "NMC") and the National Center for Atmospheric Research (NCAR). The goal of this joint effort is to produce new atmospheric analyses using historical data (1957 onwards) and as well to produce analyses of the current atmospheric state (Climate Data Assimilation System, CDAS).

Until recently, the meteorological community has had to use analyses that supported the real-time weather forecasting. These analyses are very inhomogeneous in time as there have been big improvements in the data assimilation systems. This played havoc with climate monitoring as these improvements were often produced changes in the apparent "climate". Even fundamental quantities such as the strength of the Hadley cell has changed over the years as a result of the changes in the data assimilation systems.

The quality and utility of the re-analyses should be superior to NCEP's original analyses because

  • a state-of-the-art data assimilation is used
  • more observations are used
  • quality control has been improved
  • the model/data assimilation procedure will remain essentially unchanged during the project
  • many more fields are being saved (ex. potential vorticity on isentropic surfaces, diabatic heating)
  • global (some older analyses were hemispheric)
  • better vertical resolution (stratosphere)
  • For more information ...

    This documentation and the data were taken from the NOAA NCEP/NCAR Reanalysis page, which has additional information, including CD-ROM availability, error reports, and much more data.