Reanalysis and reforecast data from NOAA’s premiere forecast system are now fully available for the public’s use.

Predictions at the seasonal to sub-seasonal scale are important for planning and decision-making in a variety of disciplines, and improving understanding and model skill at this timescale is a key research priority. An as yet underexplored approach to sub-seasonal prediction using data science and graph theory methods that are increasingly common to other fields outside of meteorology and climate science shows potential to improve predictions at this challenging timescale.

A technical report produced by the NOAA CMIP5 Task Force analyzes how CMIP5--the latest generation of climate model simulations--compares to CMIP3 simulations and projections of regional climate processes for North America.

NOAA’s Modeling, Analysis, Predictions, and Projections (MAPP) program competitively selected a new 3-year project involving $2.8 million in grants and $249,728 in other awards (for a total of $3 million) to help advance common software modeling and data infrastructure for NOAA's global models for weather and climate prediction, ultimately resulting in more efficient model development and use of model data.