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The Coupled Model Project was established at the National Meteorological Center (NMC) in January 1991 to develop a multiseason forecast system based on coupled ocean-atmosphere general circulation models. This provided a focus to combine expertise in near real-time ocean modeling and analyses situated in the Climate Analysis Center (CAC) with expertise in atmospheric modeling and data assimilation in the Development Division. Since the inception of the project, considerable progress has been made toward establishing a coupled forecast system. A T40 version of NMC's operational global medium-range forecast model (MRF) has been modified so as to have improved response to boundary forcing from the Tropics. In extended simulations, which are forced with observed historical global sea surface temperature (SST) fields, the model reproduces much of the observed tropical Pacific and North American rainfall and temperature variability. An ocean reanalysis has been performed for the Pacific basin starting from July 1982 to present and uses a dynamical model-based assimilation system. This also provides the ocean initial conditions for coupled forecast experiments. The current coupled forecast model consists of an active Pacific Ocean model coupled to the T40 version of the NMC's MRF. In the future, a global ocean model will be used to include climate information from the other ocean basins. The initial experiments focused on forecasting Northern Hemisphere winter SST anomalies in the tropical Pacific with a lead time of two seasons. The coupled model showed considerable skill during these experiments. Work is currently under way to quantify the skill in predicting climatic variability over North America.
The Coupled Model Project was established at the National Meteorological Center (NMC) in January 1991 to develop a multiseason forecast system based on coupled ocean-atmosphere general circulation models. This provided a focus to combine expertise in near real-time ocean modeling and analyses situated in the Climate Analysis Center (CAC) with expertise in atmospheric modeling and data assimilation in the Development Division. Since the inception of the project, considerable progress has been made toward establishing a coupled forecast system. A T40 version of NMC's operational global medium-range forecast model (MRF) has been modified so as to have improved response to boundary forcing from the Tropics. In extended simulations, which are forced with observed historical global sea surface temperature (SST) fields, the model reproduces much of the observed tropical Pacific and North American rainfall and temperature variability. An ocean reanalysis has been performed for the Pacific basin starting from July 1982 to present and uses a dynamical model-based assimilation system. This also provides the ocean initial conditions for coupled forecast experiments. The current coupled forecast model consists of an active Pacific Ocean model coupled to the T40 version of the NMC's MRF. In the future, a global ocean model will be used to include climate information from the other ocean basins. The initial experiments focused on forecasting Northern Hemisphere winter SST anomalies in the tropical Pacific with a lead time of two seasons. The coupled model showed considerable skill during these experiments. Work is currently under way to quantify the skill in predicting climatic variability over North America.
The strong El Niño of 1997–98 provided a unique opportunity for National Weather Service, National Centers for Environmental Prediction, Climate Prediction Center (CPC) forecasters to apply several years of accumulated new knowledge of the U.S. impacts of El Niño to their long-lead seasonal forecasts with more clarity and confidence than ever previously. This paper examines the performance of CPC's official forecasts, and its individual component forecast tools, during this event. Heavy winter precipitation across California and the southern plains–Gulf coast region was accurately forecast with at least six months of lead time. Dryness was also correctly forecast in Montana and in the southwestern Ohio Valley. The warmth across the northern half of the country was correctly forecast, but extended farther south and east than predicted. As the winter approached, forecaster confidence in the forecast pattern increased, and the probability anomalies that were assigned reached unprecedented levels in the months immediately preceding the winter. Verification scores for winter 1997/98 forecasts set a new record at CPC for precipitation.
Forecasts for the autumn preceding the El Niño winter were less skillful than those of winter, but skill for temperature was still higher than the average expected for autumn. The precipitation forecasts for autumn showed little skill. Forecasts for the spring following the El Niño were poor, as an unexpected circulation pattern emerged, giving the southern and southeastern United States a significant drought. This pattern, which differed from the historical El Niño pattern for spring, may have been related to a large pool of anomalously warm water that remained in the far eastern tropical Pacific through summer 1998 while the waters in the central Pacific cooled as the El Niño was replaced by a La Niña by the first week of June.
It is suggested that in addition to the obvious effects of the 1997–98 El Niño on 3-month mean climate in the United States, the El Niño (indeed, any strong El Niño or La Niña) may have provided a positive influence on the skill of medium-range forecasts of 5-day mean climate anomalies. This would reflect first the connection between the mean seasonal conditions and the individual contributing synoptic events, but also the possibly unexpected effect of the tropical boundary forcing unique to a given synoptic event. Circumstantial evidence suggests that the skill of medium-range forecasts is increased during lead times (and averaging periods) long enough that the boundary conditions have a noticeable effect, but not so long that the skill associated with the initial conditions disappears. Firmer evidence of a beneficial influence of ENSO on subclimate-scale forecast skill is needed, as the higher skill may be associated just with the higher amplitude of the forecasts, regardless of the reason for that amplitude.
The strong El Niño of 1997–98 provided a unique opportunity for National Weather Service, National Centers for Environmental Prediction, Climate Prediction Center (CPC) forecasters to apply several years of accumulated new knowledge of the U.S. impacts of El Niño to their long-lead seasonal forecasts with more clarity and confidence than ever previously. This paper examines the performance of CPC's official forecasts, and its individual component forecast tools, during this event. Heavy winter precipitation across California and the southern plains–Gulf coast region was accurately forecast with at least six months of lead time. Dryness was also correctly forecast in Montana and in the southwestern Ohio Valley. The warmth across the northern half of the country was correctly forecast, but extended farther south and east than predicted. As the winter approached, forecaster confidence in the forecast pattern increased, and the probability anomalies that were assigned reached unprecedented levels in the months immediately preceding the winter. Verification scores for winter 1997/98 forecasts set a new record at CPC for precipitation.
Forecasts for the autumn preceding the El Niño winter were less skillful than those of winter, but skill for temperature was still higher than the average expected for autumn. The precipitation forecasts for autumn showed little skill. Forecasts for the spring following the El Niño were poor, as an unexpected circulation pattern emerged, giving the southern and southeastern United States a significant drought. This pattern, which differed from the historical El Niño pattern for spring, may have been related to a large pool of anomalously warm water that remained in the far eastern tropical Pacific through summer 1998 while the waters in the central Pacific cooled as the El Niño was replaced by a La Niña by the first week of June.
It is suggested that in addition to the obvious effects of the 1997–98 El Niño on 3-month mean climate in the United States, the El Niño (indeed, any strong El Niño or La Niña) may have provided a positive influence on the skill of medium-range forecasts of 5-day mean climate anomalies. This would reflect first the connection between the mean seasonal conditions and the individual contributing synoptic events, but also the possibly unexpected effect of the tropical boundary forcing unique to a given synoptic event. Circumstantial evidence suggests that the skill of medium-range forecasts is increased during lead times (and averaging periods) long enough that the boundary conditions have a noticeable effect, but not so long that the skill associated with the initial conditions disappears. Firmer evidence of a beneficial influence of ENSO on subclimate-scale forecast skill is needed, as the higher skill may be associated just with the higher amplitude of the forecasts, regardless of the reason for that amplitude.
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.
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.
