101 research outputs found

    Potential changes in the connectivity of marine protected areas driven by extreme ocean warming

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    Projected future climate scenarios anticipate a warmer tropical ocean and changes in surface currents that will likely influence the survival of marine organisms and the connectivity of marine protected areas (MPAs) networks. We simulated the regional effects of climate change on the demographic connectivity of parrotfishes in nine MPAs in the South Atlantic through downscaling of the HadGEM2-ES Earth System Model running the RCP 8.5 greenhouse gas trajectory. Results indicate a tropicalization scenario over the tropical southwest Atlantic following an increase of sea surface temperature (SST) between 1.8 and 4.5 °C and changes in mean surface currents between − 0.6 to 0.5 m s−1 relative to present conditions. High mortality rates will reduce demographic connectivity and increase the isolation of oceanic islands. The simulation of organismal response to ocean warming shows that acclimation can significantly improve (p < 0.001) particle survival, promoting connectivity and tropicalization of MPAs, with potential impacts on their functional integrity and long-term resilience.publishedVersio

    Precipitação sobre a América do Sul para uma situação de La Niña conjugada com Dipolo positivo e negativo de TSM no Atlantico em simulacoes com o MCG CPTEC/COLA

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    The role of the Atlantic Ocean in a La Niña episode over Northeast of Brazil is investigated using the CPTEC/COLA GCM. Two set of integration are performed using the same negative Sea Surface Temperature (SST) anomalies in the Tropical Pacific Ocean and changing the SST in the Atlantic Ocean. A positive dipole (higher than normal SST at the Tropical North Atlantic and below normal at the Tropical South Atlantic) and a negative dipole (opposite conditions), are set as boundary conditions of SST in the two experiments. Four initial conditions were integrated in each case in order to obtain two ensembles of results. When La Niña was tested conjugated with a positive dipole, the precipitation over Nordeste was below average and for the other case, using negative dipole over Tropical Atlantic, positive precipitation anomalies occurred over the whole Nordeste. Thus, the conditions over Atlantic Ocean have a greater effect on the precipitation of Nordeste than the Pacific Ocean in La Niña. In a previous study of El Niño situation, the north region of Nordeste is affected by the Atlantic SST, but other tropical areas of South America show a change only in the intensity of anomalies. Central and southeast of South America are affected by the Atlantic conditions only in La Niña situation, whereas in El Niño these regions are influenced only by the Pacific Ocean conditions.Pages: 1715-171

    Influencia de Los Oceanos Pacifico y Atlantico sobre el comportamento y de la precipitacion en Venezuela

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    En el presente trabajo se aplicó el Sistema de Modelaje Estadístico de los Océanos - SIMOC con la finalidad de estudiar la relación de los Océanos Atlántico y Pacífico con las anomalías de precipitación registradas en Venezuela, y poder así determinar el área de mayor incidencia y el mes para la previsión de la precipitación durante la temporada de lluvias. A fin de estudiar los Océanos como factores incidentes en el comportamiento de la precipitación en el período de lluvias en Venezuela se seleccionó como variable macroclimática la Temperatura de la Superficie del Mar (SST). Esta información fue obtenida de las series de datos reconstruidas por el National Center for Environmental Prediction (NCEP), a partir del COADS (Comprehensive Oceanic and Atmospheric Data Set) con una resolución de 2 grados de latitud por longitud, en el período 1950-1992 y los provenientes del Climate Prediction Cente r (CPC) en el período 1993-1997; y como campo dependiente el formado por los datos de precipitación, en el período comprendido entre 1951 y 1995. Para seleccionar el campo predictor con mayor impacto en las anomalías de precipitación en la temporada húmeda, se examinó el ensayo donde se explicara el 80% de varianza con el menor número de modos y el primer componente en el campo predictor, retuviera el mayor porcentaje de varianza, y para determinar el mes más representativo y región de mayor influencia sobre el patrón de precipitación, se examinaron el porcentaje de estaciones pluviométricas que presentaran una correlación significativa mayor o igual al valor absoluto de 0.4 con el campo predictor en el mes seleccionado. La validación del modelo se realizó aplicando regresión múltiple durante el período 1981 - 1995. De esta manera se pudo determinar que la mayor ponderación (varianza en número de modos) estuvo representada por el área del Océano Atlántico, en el mes de marzo, donde existe un 62% de estaciones mayor correlacionadas, con anomalías de precipitación promedio registrada durante los meses abril, mayo, junio y julio(a_ j ), período que define el primer trimestre de la temporada húmeda, para la mayor parte del territorio nacional con un régimen de precipitación unimodal (máximo en Junio) afectada directamente por la actividad de la Convergencia Tropical. Como segundo valor más alto de ponderación se presenta en el Océano Pacífico durante el mes de enero, el cual tiene mayor influencia sobre el campo de la precipitación en el mes de febrero, con una incidencia del 32 %, de estaciones que coinciden con aquellas áreas donde existe un patrón semianual y que durante el curso del año completan dos oscilaciones entre lluvioso y seco

    Climate Prediction of precipitation for the Nordeste rainy season of MAM 1999

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    Monthly to seasonal dynamical atmospheric prediction at CPTEC has been performed since January 1995. The model used for these predictions is the CPTEC version of the COLA AGCM which was derived from the NCEP model ( Kinter et al., 1988) and includes a sophisticated biosphere model (Xue et al., 1991). The horizontal resolution of the AGCM is T62 and there are 28 levels in the vertical (L28; Cavalcanti et al., 1995). The seasonal predictions at CPTEC, during the first three years, were results of an ensemble of four members, using four consecutive days as initial conditions. In 1998 there was an increase in the number of ensemble members, with the prediction based on 25 integrations.Pages: 51-5

    Forecasts of Tropical Atlantic SST Anomalies Using a Statistical Ocean Model at CPTEC/INPE - Brazil

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    The Center for Weather Forecast and Climate Studies (CPTEC) located in Brazil, has recently developed and implemented a modeling system to predict tropical Atlantic sea surface temperature anomalies (SSTA). This system named SIMOC (Statistical Modeling System) produces skillful forecasts (better than persistence) for lead times up to six months in advance (Repelli and Nobre, 1998).Pages: 28-3

    Potential changes in the connectivity of marine protected areas driven by extreme ocean warming

    No full text
    Projected future climate scenarios anticipate a warmer tropical ocean and changes in surface currents that will likely influence the survival of marine organisms and the connectivity of marine protected areas (MPAs) networks. We simulated the regional effects of climate change on the demographic connectivity of parrotfishes in nine MPAs in the South Atlantic through downscaling of the HadGEM2-ES Earth System Model running the RCP 8.5 greenhouse gas trajectory. Results indicate a tropicalization scenario over the tropical southwest Atlantic following an increase of sea surface temperature (SST) between 1.8 and 4.5 °C and changes in mean surface currents between − 0.6 to 0.5 m s−1 relative to present conditions. High mortality rates will reduce demographic connectivity and increase the isolation of oceanic islands. The simulation of organismal response to ocean warming shows that acclimation can significantly improve (p < 0.001) particle survival, promoting connectivity and tropicalization of MPAs, with potential impacts on their functional integrity and long-term resilience
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