CPC Forecasts Current and Future Methods and Requirements

CPC Forecasts: Current and Future Methods and Requirements Ed O’Lenic NOAA-NWS-Climate Prediction Center Camp Springs, Maryland ed. olenic@noaa. gov 301 -763 -8000, ext 7528

Summary • CPC long-lead seasonal outlooks are produced using, in order of perceived reliability: - ENSO composites, trend, soil moisture and dynamical models (DMs) and statistical models. • Frequent model changes hamper perceived reliability of DMs. • Lack of convincing information about model biases reduces reliability of DM forecasts. • Weather/climate impacts of AO, MJO, PDO are known. • Prediction of AO, MJO, PDO is not yet possible. • DMs cannot yet predict subtle differences among ENSOs. • Stratospheric annular mode (SAM) is a link to AO prediction. • DMs ability to predict SAM is unknown/doubtful. • Relationship of Indian Ocean to predictable signals is unclear. • Relationship of QBO, Southern Hemisphere mid-latitude circulations to predictable signals is unclear.

WEATHER vs. CLIMATE

e r F o r e c a s t

Forecast Process Schematic Recent observations Historical observations Dynamical Model Forecasts Verifications/Statistical tools Downscaling, Analogs, Composites Web pages, automated databases Forecaster-created or automated products Dissemination to public

TOOLS VS SIGNALS ENSO PDO AO STRONG MODER WEAK-ATE NEUTRAL COMPOSITES o o TREND o COUPLED AGCM STATISTICAL TOOLSCCA, REGRESSION SOIL MOISTURE – SUMMER MJO STRAT ANNLR MODE QBO o ? o o ? ? ? o o o ? ? ? o TOOL RELIABILITY: o o ~ 70 -100% o ~ 30 -70% o ~ < 30%

Forecast tools page

Forecast tools web page

CMP T Forecasts

CMP NDJ 2000 -01 T Verification

CCA 0. 5 Mo lead NDJ T Outlook

OCN 0. 5 Mo lead NDJ T Outlook

CMP 0. 5 Mo lead NDJ T Outlook

OFFICIAL NDJ 2001 -02 T Outlook

CMP P Forecasts

CMP NDJ 2000 -01 P Verification

CCA 0. 5 Mo lead NDJ P Outlook

OCN 0. 5 Mo lead NDJ P Outlook

Official NDJ 2001 -02 P Outlook

Operations Concept for Ocean/Atmosphere Model • NCEP currently uses dynamical coupled ocean-atmosphere models in combination with statistical models to produce seasonal outlooks with ½ to 5 ½ month leads and, to a lesser extent, monthly outlooks with ½ month lead. Enhanced model operations which include increased numbers of ensemble members, more frequent model runs and enhanced capability to include the influence of within-season variations in SST and OLR will be used to: - Produce more highly resolved distributions of predicted variables, - Produce forecasts which increasingly and more appropriately reflect the influence of intra-seasonal variability on middle latitude climate, - Produce improved week 2 and monthly outlooks and develop and implement new outlook products for the week 3 -4 period. - Develop and implement new products to predict seasonal variations in frequency of extreme events, primarily during ENSO.

Detailed operations concept for ocean-atmosphere model Currently, coupled dynamical model forecasts are one of several tools used in preparing long-range outlooks. NCEP’s model is run to produce one set of ensemble forecasts per month during the first week of the month. This is done in a two-tiered system, in which first, an ensemble of 16 ocean forecasts are created using a coupled GCM. The average of these is used as the official SST forecast. This SST forecast is then used as the lower boundary for an AGCM to create a set of 20 atmosphere ensemble members. The forecasts are run out to 9 months. A 20 -year run of the AGCM is created each month. The seasonal means from this run are used as the climatology to create anomaly maps from each of the ensemble members. The means of these anomaly maps are used as the forecast tools which are presented to the forecasters. The forecasters use the NCEP model tools, together with other model tools to subjectively create outlook maps of the probability of monthly and seasonal mean temperature and total precipitation category.

El Nino Global Impacts

Summary • CPC long-lead seasonal outlooks are produced using, in order of perceived reliability: - ENSO composites, trend, soil moisture and dynamical models (DMs) and statistical models. • Frequent model changes hamper perceived reliability of DMs. • Lack of convincing information about model biases reduces perceived reliability of DM forecasts. • Weather/climate impacts of AO, MJO, PDO are known. • Prediction of AO, MJO, PDO is not yet possible. • DMs cannot yet predict subtle differences among ENSOs. • Stratospheric annular mode (SAM) is a link to AO prediction. • DMs ability to predict SAM is unknown/doubtful. • Relationship of Indian Ocean to predictable signals is unclear. • Relationship of QBO, Southern Hemisphere mid-latitude circulations to predictable signals is unclear.