Long-Lead Seasonal Forecasts—Where Do We Stand?

Anthony G. Barnston
Search for other papers by Anthony G. Barnston in
Current site
Google Scholar
PubMed
Close
,
Huug M. van den Dool
Search for other papers by Huug M. van den Dool in
Current site
Google Scholar
PubMed
Close
,
Stephen E. Zebiak
Search for other papers by Stephen E. Zebiak in
Current site
Google Scholar
PubMed
Close
,
Tim P. Barnett
Search for other papers by Tim P. Barnett in
Current site
Google Scholar
PubMed
Close
,
Ming Ji
Search for other papers by Ming Ji in
Current site
Google Scholar
PubMed
Close
,
David R. Rodenhuis
Search for other papers by David R. Rodenhuis in
Current site
Google Scholar
PubMed
Close
,
Mark A. Cane
Search for other papers by Mark A. Cane in
Current site
Google Scholar
PubMed
Close
,
Ants Leetmaa
Search for other papers by Ants Leetmaa in
Current site
Google Scholar
PubMed
Close
,
Nicholas E. Graham
Search for other papers by Nicholas E. Graham in
Current site
Google Scholar
PubMed
Close
,
Chester R. Ropelewski
Search for other papers by Chester R. Ropelewski in
Current site
Google Scholar
PubMed
Close
,
Vernon E. Kousky
Search for other papers by Vernon E. Kousky in
Current site
Google Scholar
PubMed
Close
,
Edward A. O'Lenic
Search for other papers by Edward A. O'Lenic in
Current site
Google Scholar
PubMed
Close
, and
Robert E. Livezey
Search for other papers by Robert E. Livezey in
Current site
Google Scholar
PubMed
Close
Full access

The National Weather Service intends to begin routinely issuing long-lead forecasts of 3-month mean U. S. temperature and precipitation by the beginning of 1995. The ability to produce useful forecasts for certain seasons and regions at projection times of up to 1 yr is attributed to advances in data observing and processing, computer capability, and physical understanding—particularly, for tropical ocean-atmosphere phenomena. Because much of the skill of the forecasts comes from anomalies of tropical SST related to ENSO, we highlight here long-lead forecasts of the tropical Pacific SST itself, which have higher skill than the U.S forecasts that are made largely on their basis.

The performance of five ENSO prediction systems is examined: Two are dynamical [the Cane-Zebiak simple coupled model of Lamont-Doherty Earth Observatory and the nonsimple coupled model of the National Centers for Environmental Prediction (NCEP)]; one is a hybrid coupled model (the Scripps Institution for Oceanography-Max Planck Institute for Meteorology system with a full ocean general circulation model and a statistical atmosphere); and two are statistical (canonical correlation analysis and constructed analogs, used at the Climate Prediction Center of NCEP). With increasing physical understanding, dynamically based forecasts have the potential to become more skillful than purely statistical ones. Currently, however, the two approaches deliver roughly equally skillful forecasts, and the simplest model performs about as well as the more comprehensive models. At a lead time of 6 months (defined here as the time between the end of the latest observed period and the beginning of the predict and period), the SST forecasts have an overall correlation skill in the 0.60s for 1982–93, which easily outperforms persistence and is regarded as useful. Skill for extra-tropical surface climate is this high only in limited regions for certain seasons. Both types of forecasts are not much better than local higher-order autoregressive controls. However, continual progress is being made in understanding relations among global oceanic and atmospheric climate-scale anomaly fields.

It is important that more real-time forecasts be made before we rush to judgement. Performance in the real-time setting is the ultimate test of the utility of a long-lead forecast. The National Weather Service's plan to implement new operational long-lead seasonal forecast products demonstrates its effectiveness in identifying and transferring “cutting edge” technologies from theory to applications. This could not have been accomplished without close ties with, and the active cooperation of, the academic and research communities.

*Climate Prediction Center NCEP/NWS/NOAA

+Lamont-Doherty Earth Observatory, Columbia University

#Scripps Institution of Oceanography, University of California

@Coupled Model Project NCEP/NWS/NOAA

Corresponding author address: Anthony Barnston, Climate Prediction Center, W/NP51, World Weather Building, Room 604, 5200 Auth Rd., Camp Springs, MD 20746. E-mail: wd51ab@sgi45.wwb.noaa.gov

The National Weather Service intends to begin routinely issuing long-lead forecasts of 3-month mean U. S. temperature and precipitation by the beginning of 1995. The ability to produce useful forecasts for certain seasons and regions at projection times of up to 1 yr is attributed to advances in data observing and processing, computer capability, and physical understanding—particularly, for tropical ocean-atmosphere phenomena. Because much of the skill of the forecasts comes from anomalies of tropical SST related to ENSO, we highlight here long-lead forecasts of the tropical Pacific SST itself, which have higher skill than the U.S forecasts that are made largely on their basis.

The performance of five ENSO prediction systems is examined: Two are dynamical [the Cane-Zebiak simple coupled model of Lamont-Doherty Earth Observatory and the nonsimple coupled model of the National Centers for Environmental Prediction (NCEP)]; one is a hybrid coupled model (the Scripps Institution for Oceanography-Max Planck Institute for Meteorology system with a full ocean general circulation model and a statistical atmosphere); and two are statistical (canonical correlation analysis and constructed analogs, used at the Climate Prediction Center of NCEP). With increasing physical understanding, dynamically based forecasts have the potential to become more skillful than purely statistical ones. Currently, however, the two approaches deliver roughly equally skillful forecasts, and the simplest model performs about as well as the more comprehensive models. At a lead time of 6 months (defined here as the time between the end of the latest observed period and the beginning of the predict and period), the SST forecasts have an overall correlation skill in the 0.60s for 1982–93, which easily outperforms persistence and is regarded as useful. Skill for extra-tropical surface climate is this high only in limited regions for certain seasons. Both types of forecasts are not much better than local higher-order autoregressive controls. However, continual progress is being made in understanding relations among global oceanic and atmospheric climate-scale anomaly fields.

It is important that more real-time forecasts be made before we rush to judgement. Performance in the real-time setting is the ultimate test of the utility of a long-lead forecast. The National Weather Service's plan to implement new operational long-lead seasonal forecast products demonstrates its effectiveness in identifying and transferring “cutting edge” technologies from theory to applications. This could not have been accomplished without close ties with, and the active cooperation of, the academic and research communities.

*Climate Prediction Center NCEP/NWS/NOAA

+Lamont-Doherty Earth Observatory, Columbia University

#Scripps Institution of Oceanography, University of California

@Coupled Model Project NCEP/NWS/NOAA

Corresponding author address: Anthony Barnston, Climate Prediction Center, W/NP51, World Weather Building, Room 604, 5200 Auth Rd., Camp Springs, MD 20746. E-mail: wd51ab@sgi45.wwb.noaa.gov
Save