Seasonal Climate Forecasts
|IRI’s Seasonal Climate Forecasts (Net Assessments) are updated every month for the next 6 months into the future. They give probabilistic outlooks for temperature and precipitation to be in the above-normal, near-normal, or below-normal tercile categories, which are defined from the previous 30 years.||Flexible Format Seasonal Climate Forecasts are based on the same forecast information as the Net Assessments. They give probabilistic outlooks for temperature and precipation based on categories or thresholds chosen by the user.||The Seasonal Forecast Verifications page provides skill assessment of IRI’s Net Assessment forecasts 1997-present.|
The IRI net assessment is a multi-institutional product made in collaboration with COLA and GFDL. When using IRI forecasts or related data please cite both the published paper describing the dataset and the datasets themselves. Read more about our forecast system, collaborators and recommended references for citation here. A complete list of all IRI’s extensive climate and forecast products both past and present are available in http://iridl.ldeo.columbia.edu/maproom/Global/Forecasts/. Access all climate monitoring and analysis maprooms here.
|The Current IRI ENSO Forecast provides a monthly summary of the status of El Niño, La Niña, and the Southern Oscillation, or ENSO, based on the NINO3.4 index (120-170W, 5S-5N).||The Current Plume of ENSO Model Predictions show forecasts made by dynamical and statistical models for SST in the Nino 3.4 region for nine overlapping 3-month periods.||ENSO rainfall teleconnection maps examine how frequently observed precipitation was in the above-normal, near-normal, or below-normal tercile category during the 10 largest El Nino and La Nina events between 1950 and 2002.|
A comprehensive list of IRI’s ENSO maps and analyses are available in the ENSO Resources Page.
GCM and SST Forecast Model Outputs
The IRI dynamical climate predictions are currently made with four different atmospheric general circulation models (AGCMs). Each month, each of these models is run 10 or more times, forming an ensemble with one or both of two possible scenarios for the global sea surface temperature (SST), one to four 3-month seasons (three to seven months) into the future. In each set of ensemble runs for a given SST scenario, the only difference between the individual runs is the initial atmospheric state (the current weather) at the beginning of the run.
|AGCMS||SST Anomaly Forecasts used to force AGCMs||AGCM model data: ECHAM4.5 and CCM3.6 are implemented in house for both persisted SST (psst) and scenario SST (ssst) predictions, with 24 ensemble members for each of the four integrations.|
Tailored Climate Products
IRI works closely with sectoral experts in health, water resources, agriculture and disaster management to identify areas in which climate information can be used for decision making and planning, and to ensure that the information is communicated in the best way and tailored to the needs of the users.
|The US-Mexico Drought Prediction maps provide quantifiable, probabilistic drought predictions for the United States and Mexico over the next few months.||The IFRC Maproom provides tailored, user friendly weather and climate information developed by IRI in partnership with the IFRC to answer specific questions of interest to disaster risk managers.|
|The Climate and Agriculture Maproom includes seasonal and sub-seasonal climate information and analyses of importance to agriculture, including historical temperature and precipitation, seasonal temperature and precipitation forecasts, and GCM skill maps.||The Select a Point map room for local Temperature and Precipitation Climatology Background map shows topography of the land. This maproom allows one to click on a specific point and see the average seasonal cycle of temperature and precipitation. Like all maproom maps, it is possible to zoom in on a continent or region.|
Climate Change and Decade-Scale Information
|The Time scales Decomposition Map Room allows one to look at the amount of climate variation contained in climate change trends, decadal-scale variability, or year-to-year variability. There is a brief paper linked to on the map room that provides more details on the methodology, as well as caveats. One can display maps of these quantities, or one can click on a point or select a region for averaging and obtain timeseries of each component.||The Skill assessment of Experimental Decadal Predictions evaluation examines two things: (1) the accuracy of decadal prediction experiments, which were started from ocean conditions close those observed at the beginning of the forecast, compared to the accuracy of climate change projections, which use the same models but do not introduce observed conditions; and (2) how best to estimate uncertainty in the decadal prediction experiments.|