Reanalysis Datasets at PSD
PSD maintains a collection of reanalysis datasets for use in climate diagnostics and attribution. Reanalysis datasets are created by assimilating ("inputting") climate observations using the same climate model throughout the entire reanalysis period in order to reduce the affects of modeling changes on climate statistics. Observations are from many different sources including ships, satellites, ground stations, RAOBS, and radar. Currently, PSD makes available reanalysis datasets to the public in our standard netCDF format For some reanalyses, we don't distribute the data but do allow users to analyze and plot from it.
NCEP/NCAR Reanalysis I (1948-present)This reanalysis was the first of it's kind for NOAA. NCEP used the same climate model that were initialized with a wide variety of weather observations: ships, planes, RAOBS, station data, satellite observations and many more. By using the same model, scientists can examine climate/weather statistics and dynamic processes without the complication that model changes can cause. The dataset is kept current using near real-time observations.
NCEP/DOE Reanalysis II (1979-present)NCEP produced a second version of their first reanalysis starting from the beginning of the major satellite era. More observations were added, assimilation errors were corrected and a better version of the model was used.
NARR (1979-present)The NARR reanalysis was done to produce very high resolution output over the North American region. Observational inputs were similar to NCEP I with the addition of assimilated precipitation. The NARR model region was nested in a global, lower resolution model. Outputs are similar to the NCEP I and II models but with more snow, ice and precipitation related variables.
20th Century Reanalysis (V2 and V2c) (1851-2014)The 20th Century Reanalysis version 2 and 2c datasets contain global weather conditions and their uncertainty in six hour intervals from 1851 to 2014. Surface and sea level pressure observations are combined with a short-term forecast from an ensemble of integrations of an NCEP numerical weather prediction model using the recently developed Ensemble Kalman Filter technique to produce an estimate of the complete state of the atmosphere, and the uncertainty in that estimate. Additional observations and a newer version of the NCEP model that includes time-varying CO2 concentrations, solar variability, and volcanic aerosols are used in version 2. The long time range of this dataset allows scientists to examine better long time scale climate processes such as the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation as well as looking at the dynamics of historical climate and weather events. Verification tests have shown that using only pressure creates reasonable atmospheric fields up to the tropopause. Additional tests suggest some correspondence with observed variations in the lower stratosphere.
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