Generation and Evaluation of Long-Term Retrospective Forecasts with NCEP Climate Forecast System: Predictability of ENSO and Drought

Lead PI: Prof. Mark A. Cane

Unit Affiliation: Ocean and Climate Physics, Lamont-Doherty Earth Observatory (LDEO)

July 2008 - June 2013
Project Type: Research

DESCRIPTION: The research project's objectives are: 1) develop coupled data assimilation and model initialization procedure for CFS; 2) Use the CFS to generate retrospective forecasts; 3) evaluate the predictability of ENSO using the resulting datasets; 4) and to provide the basis for bias correction. This will be done using a combination of data analyses and model experiments.

OUTCOMES: CFS was set up to handle historical data, used to run a 150 SST control run, and the resulting model output converted to NetCDF. The model run validated that NINO events are properly represented and the model does produce El Nino events, but they are longer than historical evidence suggests. Five journal articles were produced.