Developments in Operational Long-Range Climate Prediction at CPC

Edward A. O’Lenic National Oceanic and Atmospheric Administration/National Weather Service/Climate Prediction Center, Camp Springs, Maryland

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David A. Unger National Oceanic and Atmospheric Administration/National Weather Service/Climate Prediction Center, Camp Springs, Maryland

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Michael S. Halpert National Oceanic and Atmospheric Administration/National Weather Service/Climate Prediction Center, Camp Springs, Maryland

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Kenneth S. Pelman National Oceanic and Atmospheric Administration/National Weather Service/Climate Prediction Center, Camp Springs, Maryland

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Abstract

The science, production methods, and format of long-range forecasts (LRFs) at the Climate Prediction Center (CPC), a part of the National Weather Service’s (NWS’s) National Centers for Environmental Prediction (NCEP), have evolved greatly since the inception of 1-month mean forecasts in 1946 and 3-month mean forecasts in 1982. Early forecasts used a subjective blending of persistence and linear regression-based forecast tools, and a categorical map format. The current forecast system uses an increasingly objective technique to combine a variety of statistical and dynamical models, which incorporate the impacts of El Niño–Southern Oscillation (ENSO) and other sources of interannual variability, and trend. CPC’s operational LRFs are produced each midmonth with a “lead” (i.e., amount of time between the release of a forecast and the start of the valid period) of ½ month for the 1-month outlook, and with leads ranging from ½ month through 12½ months for the 3-month outlook. The 1-month outlook is also updated at the end of each month with a lead of zero. Graphical renderings of the forecasts made available to users range from a simple display of the probability of the most likely tercile to a detailed portrayal of the entire probability distribution.

Efforts are under way at CPC to objectively weight, bias correct, and combine the information from many different LRF prediction tools into a single tool, called the consolidation (CON). CON ½-month lead 3-month temperature (precipitation) hindcasts over 1995–2005 were 18% (195%) better, as measured by the Heidke skill score for nonequal chances forecasts, than real-time official (OFF) forecasts during that period. CON was implemented into LRF operations in 2006, and promises to transfer these improvements to the official LRF.

Improvements in the science and production methods of LRFs are increasingly being driven by users, who are finding an increasing number of applications, and demanding improved access to forecast information. From the forecast-producer side, hope for improvement in this area lies in greater dialogue with users, and development of products emphasizing user access, input, and feedback, including direct access to 5 km × 5 km gridded outlook data through NWS’s new National Digital Forecast Database (NDFD).

Corresponding author address: Edward A. O’Lenic, National Centers for Environmental Prediction, W/NP5, Rm. 604 WWB, 5200 Auth Rd., Camp Springs, MD 20746. Email: ed.olenic@noaa.gov

Abstract

The science, production methods, and format of long-range forecasts (LRFs) at the Climate Prediction Center (CPC), a part of the National Weather Service’s (NWS’s) National Centers for Environmental Prediction (NCEP), have evolved greatly since the inception of 1-month mean forecasts in 1946 and 3-month mean forecasts in 1982. Early forecasts used a subjective blending of persistence and linear regression-based forecast tools, and a categorical map format. The current forecast system uses an increasingly objective technique to combine a variety of statistical and dynamical models, which incorporate the impacts of El Niño–Southern Oscillation (ENSO) and other sources of interannual variability, and trend. CPC’s operational LRFs are produced each midmonth with a “lead” (i.e., amount of time between the release of a forecast and the start of the valid period) of ½ month for the 1-month outlook, and with leads ranging from ½ month through 12½ months for the 3-month outlook. The 1-month outlook is also updated at the end of each month with a lead of zero. Graphical renderings of the forecasts made available to users range from a simple display of the probability of the most likely tercile to a detailed portrayal of the entire probability distribution.

Efforts are under way at CPC to objectively weight, bias correct, and combine the information from many different LRF prediction tools into a single tool, called the consolidation (CON). CON ½-month lead 3-month temperature (precipitation) hindcasts over 1995–2005 were 18% (195%) better, as measured by the Heidke skill score for nonequal chances forecasts, than real-time official (OFF) forecasts during that period. CON was implemented into LRF operations in 2006, and promises to transfer these improvements to the official LRF.

Improvements in the science and production methods of LRFs are increasingly being driven by users, who are finding an increasing number of applications, and demanding improved access to forecast information. From the forecast-producer side, hope for improvement in this area lies in greater dialogue with users, and development of products emphasizing user access, input, and feedback, including direct access to 5 km × 5 km gridded outlook data through NWS’s new National Digital Forecast Database (NDFD).

Corresponding author address: Edward A. O’Lenic, National Centers for Environmental Prediction, W/NP5, Rm. 604 WWB, 5200 Auth Rd., Camp Springs, MD 20746. Email: ed.olenic@noaa.gov

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