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@InProceedings{Coelho:2013:MeReLi,
               author = "Coelho, Caio Augusto dos Santos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Uma metodologia de regress{\~a}o linear para as previs{\~o}es 
                         clim{\'a}ticas sazonais probabil{\'{\i}}sticas de 
                         precipita{\c{c}}{\~a}o para o Brasil em categorias 
                         terc{\'{\i}}licas/ A linear regression approach for tercile 
                         probability seasonal precipitation forecasts for Brazil",
            booktitle = "Anais...",
                 year = "2013",
         organization = "Simp{\'o}sio Internacional de Climatologia, 5. (SIC).",
             keywords = "Seasonal forecast, precipitation, probability.",
             abstract = "RESUMO: Previs{\~o}es clim{\'a}ticas sazonais de 
                         precipita{\c{c}}{\~a}o para o Brasil v{\^e}m sendo produzidas 
                         em modo operacional pelo CPTEC/INPE desde meados da d{\'e}cada de 
                         noventa. A partir de 2004 a previs{\~a}o sazonal de 
                         precipita{\c{c}}{\~a}o oficial para o Brasil passou a ser 
                         elaborada em conjunto pelo CPTEC/INPE e Instituto Nacional de 
                         Meteorologia (INMET). At{\'e} junho de 2012 o processo de 
                         produ{\c{c}}{\~a}o dessas previs{\~o}es consistia de a) 
                         diagnosticar as atuais condi{\c{c}}{\~o}es clim{\'a}ticas 
                         regionais e globais; b) examinar as previs{\~o}es produzidas por 
                         ambos modelos f{\'{\i}}sicos (din{\^a}micos) e 
                         estat{\'{\i}}sticos; e c) estimar subjetivamente as 
                         probabilidades para as previs{\~o}es de ocorr{\^e}ncia de 
                         precipita{\c{c}}{\~a}o em tr{\^e}s categorias (abaixo da 
                         normal, normal e acima da normal) ap{\'o}s avalia{\c{c}}{\~a}o 
                         de especialistas de todas as informa{\c{c}}{\~o}es 
                         dispon{\'{\i}}veis. Desde julho de 2012 um novo procedimento vem 
                         sendo utilizado para definir objetivamente as probabilidades para 
                         essas tr{\^e}s categorias no est{\'a}gio final do processo 
                         imediatamente antes da dissemina{\c{c}}{\~a}o da previs{\~a}o. 
                         O novo procedimento {\'e} baseado na regress{\~a}o linear entre 
                         as observa{\c{c}}{\~o}es hist{\'o}ricas de 
                         precipita{\c{c}}{\~a}o sazonal e as correspondentes 
                         previs{\~o}es retrospectivas. Neste procedimento as 
                         previs{\~o}es de probabilidade s{\~a}o estimadas levando-se em 
                         considera{\c{c}}{\~a}o o sinal previsto (ou seja, a anomalia 
                         prevista) por um sistema multi-modelos de previs{\~a}o e a 
                         correspondente destreza retrospectiva das previs{\~o}es desse 
                         sistema para o per{\'{\i}}odo 1989-2008. Este sistema 
                         multi-modelos {\'e} atualmente composto por um conjunto de 
                         previs{\~o}es f{\'{\i}}sicas (din{\^a}micas) produzidas pelo 
                         modelo atmosf{\'e}rico do CPTEC/INPE, por um conjunto de 
                         previs{\~o}es estat{\'{\i}}sticas produzidas pelo INMET, e um 
                         conjunto de previs{\~o}es f{\'{\i}}sicas (din{\^a}micas) 
                         produzidas pela Funda{\c{c}}{\~a}o Cearence de Meteorologia e 
                         Recursos H{\'{\i}}dricos (FUNCEME). Este sistema multi-modelos 
                         comp{\~o}em atualmente o sistema nacional de previs{\~a}o 
                         clim{\'a}tica sazonal do Brasil. A anomalia prevista por este 
                         sistema multi-modelo fornece uma estimativa de quanto a m{\'e}dia 
                         da distribui{\c{c}}{\~a}o climatol{\'o}gica (hist{\'o}rica) 
                         deve ser deslocada para a direita (caso o sistema multi-modelo 
                         indique previs{\~a}o de excesso de precipita{\c{c}}{\~a}o) ou 
                         para a esquerda (caso o sistema multimodelo indique previs{\~a}o 
                         de d{\'e}ficit de precipita{\c{c}}{\~a}o). A destreza 
                         hist{\'o}rica das previs{\~o}es desse sistema {\'e} usada para 
                         definir a dispers{\~a}o da distribui{\c{c}}{\~a}o prevista pelo 
                         sistema multimodelo. Para regi{\~o}es onde a destreza {\'e} 
                         maior (menor) a distribui{\c{c}}{\~a}o prevista pelo sistema 
                         multi-modelo ser{\'a} mais estreita (larga), apresentando 
                         dispers{\~a}o reduzida (aumentada) quando comparada com a 
                         distribui{\c{c}}{\~a}o climatol{\'o}gica. A 
                         verifica{\c{c}}{\~a}o da consist{\^e}ncia f{\'{\i}}sica entre 
                         a anomalia prevista pelo sistema multi-modelo e as predominantes 
                         condi{\c{c}}{\~o}es for{\c{c}}antes de grande escala {\'e} uma 
                         etapa fundamente do processo de previs{\~a}o. Este trabalho 
                         apresentar{\'a} esta nova metodologia atualmente utilizada no 
                         Brasil para definir as probabilidades das categorias 
                         terc{\'{\i}}licas da previs{\~a}o sazonal de 
                         precipita{\c{c}}{\~a}o para o Brasil. ABSTRACT: Seasonal 
                         precipitation forecasts for Brazil have been operationally 
                         produced since the mid-nineties by the Center for Weather Forecast 
                         and Climate Studies (CPTEC), of the National Institute for Space 
                         Research (INPE). In 2004 the official precipitation seasonal 
                         forecast for Brazil started to be jointly elaborated by CPTEC/INPE 
                         and the National Institute of Meteorology (INMET). Until June 2012 
                         the process for producing these forecasts consisted in a) 
                         diagnosing the current regional and global climate conditions; b) 
                         examining the forecasts produced by both physically-based 
                         dynamical models and statistical models; and c) subjectively 
                         estimating forecast probabilities for three precipitation 
                         categories (below normal, normal and above normal) after expert 
                         assessment of all available information. Since July 2012 a new 
                         procedure is being used for objectively defining forecast 
                         probabilities for these three categories in the final stage prior 
                         to issuing the forecast. The new procedure is based on the linear 
                         regression of the historical seasonal precipitation observations 
                         on the corresponding retrospective forecasts. In this procedure 
                         forecast probabilities are estimated taking into account the 
                         forecast signal (i.e. the forecast anomaly) of a multi-model 
                         forecasting system and the corresponding retrospective skill of 
                         this system during the period 1989-2008. This multi-model system 
                         is currently composed by an ensemble of physically-based forecasts 
                         produced by CPTEC/INPE atmospheric climate model, an ensemble of 
                         statistical forecasts produced by INMET, and an ensemble of 
                         physically-based forecasts produced by Cear{\'a} State 
                         Meteorology and Water Resources Foundation (FUNCEME). Such 
                         multi-model system composes the Brazilian national seasonal 
                         prediction system. The multi-model forecast anomaly provides an 
                         estimate of how much the mean of the climatological (historical) 
                         distribution should be shifted to the right (if excess 
                         precipitation is forecast by the multi-model system) or to the 
                         felt (if deficit precipitation is forecast by the multi-model 
                         system). The retrospective prediction skill of this system is used 
                         for defining the spread of the multi-model forecast distribution. 
                         For regions where the skill is greatest (smallest) the multi-model 
                         forecast distribution is thinner (wider) presenting reduced 
                         (increased) spread compared to the climatological distribution. 
                         The check for physical consistency between the forecast anomaly 
                         indicated by the multimodel system and the prevailing large scale 
                         forcing is a fundamental part of the forecasting procedure. This 
                         study will present this new methodology currently used in Brazil 
                         for defining tercile probability seasonal precipitation forecasts 
                         for Brazil, including a preliminary performance assessment of 
                         forecasts produced by the new forecasting approach since its 
                         implementation in 2012.",
  conference-location = "Florian{\'o}polis, SC",
      conference-year = "15-19, set.",
        urlaccessdate = "25 jan. 2021"
}


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