197 resultados para equatorial rainfall pattern


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To gain a new perspective on the interaction of the Atlantic Ocean and the atmosphere, the relationship between the atmospheric and oceanic meridional energy transports is studied in a version of HadCM3, the U.K. Hadley Centre's coupled climate model. The correlation structure of the energy transports in the atmosphere and Atlantic Ocean as a function of latitude, and the cross correlation between the two systems are analyzed. The processes that give rise to the correlations are then elucidated using regression analyses. In northern midlatitudes, the interannual variability of the Atlantic Ocean energy transport is dominated by Ekman processes. Anticorrelated zonal winds in the subtropics and midlatitudes, particularly associated with the North Atlantic Oscillation (NAO), drive anticorrelated meridional Ekman transports. Variability in the atmospheric energy transport is associated with changes in the stationary waves, but is only weakly related to the NAO. Nevertheless, atmospheric driving of the oceanic Ekman transports is responsible for a bipolar pattern in the correlation between the atmosphere and Atlantic Ocean energy transports. In the Tropics, the interannual variability of the Atlantic Ocean energy transport is dominated by an adjustment of the tropical ocean to coastal upwelling induced along the Venezuelan coast by a strengthening of the easterly trade winds. Variability in the atmospheric energy transport is associated with a cross-equatorial meridional overturning circulation that is only weakly associated with variability in the trade winds along the Venezuelan coast. In consequence, there is only very limited correlation between the atmosphere and Atlantic Ocean energy transports in the Tropics of HadCM3

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The annual and interannual variability of idealized, linear, equatorial waves in the lower stratosphere is investigated using the temperature and velocity fields from the ECMWF 15-year re-analysis dataset. Peak Kelvin wave activity occurs during solstice seasons at 100 hPa, during December-February at 70 hPa and in the easterly to westerly quasi-biennial oscillation (QBO) phase transition at 50 hPa. Peak Rossby-gravity wave activity occurs during equinox seasons at 100 hPa, during June-August/September-November at 70 hPa and in the westerly to easterly QBO phase transition at 50 hPa. Although neglect of wind shear means that the results for inertio-gravity waves are likely to be less accurate, they are still qualitatively reasonable and an annual cycle is observed in these waves at 100 hPa and 70 hPa. Inertio-gravity waves with n = 1 are correlated with the QBO at 50 hPa, but the eastward inertio-gravity n = 0 wave is not, due to its very fast vertical group velocity in all background winds. The relative importance of different wave types in driving the QBO at 50 hPa is also discussed. The strongest acceleration appears to be provided by the Kelvin wave while the acceleration provided by the Rossby-gravity wave is negligible. Of the higher-frequency waves, the westward inertio-gravity n = 1 wave appears able to contribute more to the acceleration of the 50 hPa mean zonal wind than the eastward inertio-gravity n = 1 wave.

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Wavenumber-frequency spectral analysis and linear wave theory are combined in a novel method to quantitatively estimate equatorial wave activity in the tropical lower stratosphere. The method requires temperature and velocity observations that are regularly spaced in latitude, longitude and time; it is therefore applied to the ECMWF 15-year re-analysis dataset (ERA-15). Signals consistent with idealized Kelvin and Rossby-gravity waves are found at wavenumbers and frequencies in agreement with previous studies. When averaged over 1981-93, the Kelvin wave explains approximately 1 K-2 of temperature variance on the equator at 100 hPa, while the Rossby-gravity wave explains approximately 1 m(2)s(-2) of meridional wind variance. Some inertio-gravity wave and equatorial Rossby wave signals are also found; however the resolution of ERA-15 is not sufficient for the method to provide an accurate climatology of waves with high meridional structure.

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This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility Of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Parana river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3-month lead November-December-January multi-model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management.

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A full troposphere-stratosphere-mesosphere global circulation model is used in a set of idealised experiments to investigate the sensitivity of the Northern Hemisphere winter stratospheric flow to improvements in the equatorial zonal winds. The model shows significant sensitivity to variability in the upper equatorial stratosphere, the imposition of SAO and QBO like variability in this region advances the timing of midwinter sudden warmings by about one month. Perturbations to the lower equatorial stratosphere are mainly found to influence early winter polar variability. These results suggest that it is important to pay attention to the capability of models to simulate realistic variability in the upper equatorial stratosphere.

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[1] In many practical situations where spatial rainfall estimates are needed, rainfall occurs as a spatially intermittent phenomenon. An efficient geostatistical method for rainfall estimation in the case of intermittency has previously been published and comprises the estimation of two independent components: a binary random function for modeling the intermittency and a continuous random function that models the rainfall inside the rainy areas. The final rainfall estimates are obtained as the product of the estimates of these two random functions. However the published approach does not contain a method for estimation of uncertainties. The contribution of this paper is the presentation of the indicator maximum likelihood estimator from which the local conditional distribution of the rainfall value at any location may be derived using an ensemble approach. From the conditional distribution, representations of uncertainty such as the estimation variance and confidence intervals can be obtained. An approximation to the variance can be calculated more simply by assuming rainfall intensity is independent of location within the rainy area. The methodology has been validated using simulated and real rainfall data sets. The results of these case studies show good agreement between predicted uncertainties and measured errors obtained from the validation data.

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Monsoon droughts over the Indian subcontinent emanate from failures in the seasonal (June-September) monsoon rains. While prolonged dry-spells ("monsoon-breaks'') pervade on sub-seasonal/intra-seasonal time-scales, the underlying causes for these long-lasting anomalies remain elusive. Based on analyses of a suite of observed data sets, we report an ocean-atmosphere dynamical coupling on intra-seasonal time-scales, in the tropical Indian Ocean, which is pivotal in forcing extended monsoon-breaks and causing droughts over the subcontinent. This coupling involves a feedback between the monsoonal flow and thermocline depth in the Equatorial Eastern Indian Ocean (EEIO), in which an anomaly of the summer monsoon circulation induces downwelling and maintains a higher-than-normal heat-content. The near-equatorial anomalies induce strong and sustained suppression of monsoon rainfall over the subcontinent. It is concluded that the intra-seasonal evolution of the ocean-monsoon coupled system is a vital key to unlocking the dynamics of monsoon droughts.