Calibrated Subseasonal Tercile categories precipitation experimental forecasts issued 1-2 months behind real time.
The default map shows the latest forecast issued, for combined weeks #2 and #3 lead time (i.e., the 14-day long period 8 to 21 days after the forecast is issued), as probability of the dominant tercile. Forecasts are started weekly (on Thursdays) but are issued with 1 to 2 months delay. Previous forecast issues can be consulted through the control bar menu. Lead time for combined weeks #3 and #4 (i.e., the 14-day long period 15 to 28 days after the forecast is issued) are also available. The smaller side map shows a verification of the forecast in current view as the observed tercile values according to the 1999-2010 training period of the calibration of the forecast.
Clicking on the map will show, for the clicked grid box, the probabilities for the 3 forecasts categories (Below-, Near- and Above- Normal).
The probabilistic forecasts shown here are obtained from the statistical calibration of three models from the Subseasonal to Seasonal (S2S) Prediction Project database (Vitart et al, 2017) which are combined with equal weight to form multi-model ensemble precipitation tercile probabilities forecasts. Individual model forecasts are calibrated separately for each point, start and lead using Extended Logistic Regressions (ELR; Vigaud et al, 2017) based on the historical performance of each model, and thus provide reliable intra-seasonal climate information in regards to a wide range of climate risk of concerns to the decision making communities and for which subseasonal forecasts are particularly well suited.
As subseasonal-to-seasonal (S2S) forecasting techniques are being developped, and more and more models are made available in (near) real-time, this Maproom shows the type of forecast information that can be currently delivered at these time scales.
While the verification map gives you a sense of the performance of a specific forecast issue, you can navigate from here to the Historical Skill Maproom to explore skill scores of historical performance of the forecasting system, by climatological month of issue.
References:
Forecast: Global 1˚ Multi-Model Ensemble forecasts probabilities by category and dominant terciles probabilities available here.
Historical precipitation: Global 1˚ NOAA UNIFIED precipitation data set, historical and real-time available here.
Contact help@iri.columbia.edu with any technical questions or problems with this Map Room.