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    Long-Lead Seasonal Forecasts—Where Do We Stand?

    Source: Bulletin of the American Meteorological Society:;1994:;volume( 075 ):;issue: 011::page 2097
    Author:
    Barnston, Anthony G.
    ,
    van den Dool, Huug M.
    ,
    Rodenhuis, David R.
    ,
    Ropelewski, Chester R.
    ,
    Kousky, Vernon E.
    ,
    O'Lenic, Edward A.
    ,
    Livezey, Robert E.
    ,
    Zebiak, Stephen E.
    ,
    Cane, Mark A.
    ,
    Barnett, Tim P.
    ,
    Graham, Nicholas E.
    ,
    Ji, Ming
    ,
    Leetmaa, Ants
    DOI: 10.1175/1520-0477(1994)075<2097:LLSFDW>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: 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 upto 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 nonsimpie 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 predictand 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. 1t 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.
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      Long-Lead Seasonal Forecasts—Where Do We Stand?

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    contributor authorBarnston, Anthony G.
    contributor authorvan den Dool, Huug M.
    contributor authorRodenhuis, David R.
    contributor authorRopelewski, Chester R.
    contributor authorKousky, Vernon E.
    contributor authorO'Lenic, Edward A.
    contributor authorLivezey, Robert E.
    contributor authorZebiak, Stephen E.
    contributor authorCane, Mark A.
    contributor authorBarnett, Tim P.
    contributor authorGraham, Nicholas E.
    contributor authorJi, Ming
    contributor authorLeetmaa, Ants
    date accessioned2017-06-09T14:41:26Z
    date available2017-06-09T14:41:26Z
    date copyright1994/11/01
    date issued1994
    identifier issn0003-0007
    identifier otherams-24549.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4161233
    description abstractThe 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 upto 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 nonsimpie 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 predictand 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. 1t 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.
    publisherAmerican Meteorological Society
    titleLong-Lead Seasonal Forecasts—Where Do We Stand?
    typeJournal Paper
    journal volume75
    journal issue11
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/1520-0477(1994)075<2097:LLSFDW>2.0.CO;2
    journal fristpage2097
    journal lastpage2114
    treeBulletin of the American Meteorological Society:;1994:;volume( 075 ):;issue: 011
    contenttypeFulltext
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