Starting in April 2017, the IRI probabilistic seasonal climate forecast product is based on a re-calibration of model output from the U.S. National Oceanographic and Atmospheric Administration (NOAA)’s North American Multi-Model Ensemble Project (NMME). This includes the ensemble seasonal prediction systems of NOAA’s National Centers for Environmental Prediction, Environment and Climate Change Canada, NOAA/Geophysical Fluid Dynamics Laboratory, NASA, NCAR and COLA/University of Miami. The output from each NMME model is re-calibrated prior to multi-model ensembling to form reliable probability forecasts. The forecasts are now presented on a 1-degree latitude-longitude grid.
Disclaimer: The IRI seasonal forecast is a research product. Please see the NOAA CPC forecast for the official seasonal forecast over the U.S. Please consult your country’s national meteorological service for the official forecast for your country.
Please see the ‘Discussion’ item for an overview of the individual forecasts.
The map on the left shows the probability of the most-likely (tercile) category of precipitation or near-surface temperature. White areas indicate grid points where all 3 categories are equally likely. Grey areas indicate those where the near-normal category is dominant.
The climatological base period currently used is 1991-2020. Details of the forecast system, post-processing, and recommended references for citation can be found here. Forecasts from the individual NMME models are shown on NOAA CPC’s website. Verifications of IRI’s real-time forecasts issued since 1998 can be found on the Seasonal Climate Verifications pages.
To aid in interpretation of the forecast probabilities, maps of the observed precipitation and temperature percentiles are plotted in physical units here: Climatological Percentiles Maproom.
The IRI forecasts are also available as a flexible probabilistic format, providing the probability of exceedance (or non-exceedance) of a user-specified percentile of the climatological distribution: Go to IRI Flexible Forecasts