974 resultados para Rainfall Variability


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To date, a number of studies have focused on the influence of sea surface temperature (SST) on global and regional rainfall variability, with the majority of these focusing on certain ocean basins e.g. the Pacific, North Atlantic and Indian Ocean. In contrast, relatively less work has been done on the influence of the central South Atlantic, particularly in relation to rainfall over southern Africa. Previous work by the authors, using reanalysis data and general circulation model (GCM) experiments, has suggested that cold SST anomalies in the central southern Atlantic Ocean are linked to an increase in rainfall extremes across southern Africa. In this paper we present results from idealised regional climate model (RCM) experiments forced with both positive and negative SST anomalies in the southern Atlantic Ocean. These experiments reveal an unexpected response of rainfall over southern Africa. In particular it was found that SST anomalies of opposite sign can cause similar rainfall responses in the model experiments, with isolated increases in rainfall over central southern Africa as well as a large region of drying over the Mozambique Channel. The purpose of this paper is to highlight this finding and explore explanations for the behaviour of the climate model. It is suggested that the observed changes in rainfall might result from the redistribution of energy (associated with upper level changes to Rossby waves) or, of more concern, model error, and therefore the paper concludes that the results of idealised regional climate models forced with SST anomalies should be viewed cautiously.

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Many numerical models for weather prediction and climate studies are run at resolutions that are too coarse to resolve convection explicitly, but too fine to justify the local equilibrium assumed by conventional convective parameterizations. The Plant-Craig (PC) stochastic convective parameterization scheme, developed in this paper, solves this problem by removing the assumption that a given grid-scale situation must always produce the same sub-grid-scale convective response. Instead, for each timestep and gridpoint, one of the many possible convective responses consistent with the large-scale situation is randomly selected. The scheme requires as input the large-scale state as opposed to the instantaneous grid-scale state, but must nonetheless be able to account for genuine variations in the largescale situation. Here we investigate the behaviour of the PC scheme in three-dimensional simulations of radiative-convective equilibrium, demonstrating in particular that the necessary space-time averaging required to produce a good representation of the input large-scale state is not in conflict with the requirement to capture large-scale variations. The resulting equilibrium profiles agree well with those obtained from established deterministic schemes, and with corresponding cloud-resolving model simulations. Unlike the conventional schemes the statistics for mass flux and rainfall variability from the PC scheme also agree well with relevant theory and vary appropriately with spatial scale. The scheme is further shown to adapt automatically to changes in grid length and in forcing strength.

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Climate change is inevitable and will continue into the next century. Since the agricultural sector in Sri Lanka is one of the most vulnerable to climate change, a thorough understanding of climate transition is critical for formulating effective adaptation strategies. This paper provides an overview of the status of climate change and adaptation in the agricultural sector in Sri Lanka. The review clearly indicates that climate change is taking place in Sri Lanka in terms of rainfall variability and an increase in climate extremes and warming. A number of planned and reactive adaptation responses stemming from policy and farm-level decisions are reported. These adaptation efforts were fragmented and lacked a coherent connection to the national development policies and strategies. Research efforts are needed to develop and identify adaptation approaches and practices that are feasible for smallholder farmers, particularly in the dry zone where paddy and other food crops are predominately cultivated. To achieve the envisaged growth in the agricultural sector, rigorous efforts are necessary to mainstream climate change adaptation into national development policies and ensure that they are implemented at national, regional and local levels.

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The relationship between winter (DJF) rainfall over Portugal and the variable large scale circulation is addressed. It is shown that the poles of the sea level pressure (SLP) field variability associated with rainfall variability are shifted about 15° northward with respect to those used in standard definitions of the North Atlantic Oscillation (NAO). It is suggested that the influence of NAO on rainfall dominantly arises from the associated advection of humidity from the Atlantic Ocean. Rainfall is also related to different aspects of baroclinic wave activity, the variability of the latter quantity in turn being largely dependent on the NAO. A negative NAO index (leading to increased westerly surface geostrophic winds into Portugal) is associated with an increased number of deep (ps<980 hPa) surface lows over the central North Atlantic and of intermediate (980rainfall amounts for months with local cyclone cores over the considered region tend to exceed those without. Copyright © 1999 Royal Meteorological Society

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Quasi-stationary convective bands can cause large localised rainfall accumulations and are often anchored by topographic features. Here, the predictability of and mechanisms causing one such band are determined using ensembles of the Met Office Unified Model at convection-permitting resolution (1.5 km grid length). The band was stationary over the UK for 3 h and produced rainfall accumulations of up to 34 mm. The amount and location of the predicted rainfall was highly variable despite only small differences between the large-scale conditions of the ensemble members. Only three of 21 members of the control ensemble produced a stationary rain band; these three had the weakest upstream winds and hence lowest Froude number. Band formation was due to the superposition of two processes: lee-side convergence resulting from flow around an upstream obstacle and thermally forced convergence resulting from elevated heating over the upstream terrain. Both mechanisms were enhanced when the Froude number was lower. By increasing the terrain height (thus reducing the Froude number), the band became more predictable. An ensemble approach is required to successfully predict the possible occurrence of such quasi-stationary convective events because the rainfall variability is largely modulated by small variations of the large-scale flow. However, high-resolution models are required to accurately resolve the small-scale interactions of the flow with the topography upon which the band formation depends. Thus, although topography provides some predictability, the quasi-stationary convective bands anchored by it are likely to remain a forecasting challenge for many years to come.

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The "Vertical structure and physical processes of the Madden-Julian oscillation (MJO)" project comprises three experiments, designed to evaluate comprehensively the heating, moistening and momentum associated with tropical convection in general circulation models (GCMs). We consider here only those GCMs that performed all experiments. Some models display relatively higher or lower MJO fidelity in both initialized hindcasts and climate simulations, while others show considerable variations in fidelity between experiments. Fidelity in hindcasts and climate simulations are not meaningfully correlated. The analysis of each experiment led to the development of process-oriented diagnostics, some of which distinguished between GCMs with higher or lower fidelity in that experiment. We select the most discriminating diagnostics and apply them to data from all experiments, where possible, to determine if correlations with MJO fidelity hold across scales and GCM states. While normalized gross moist stability had a small but statistically significant correlation with MJO fidelity in climate simulations, we find no link with fidelity in medium-range hindcasts. Similarly, there is no association between timestep-to-timestep rainfall variability, identified from short hindcasts, and fidelity in medium-range hindcasts or climate simulations. Two metrics that relate precipitation to free-tropospheric moisture--the relative humidity for extreme daily precipitation, and variations in the height and amplitude of moistening with rain rate--successfully distinguish between higher- and lower-fidelity GCMs in hindcasts and climate simulations. To improve the MJO, developers should focus on relationships between convection and both total moisture and its rate of change. We conclude by offering recommendations for further experiments.

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Multiple observational data sets and atmosphere-only simulations from the Coupled Model Intercomparison Project Phase 5 are analyzed to characterize recent rainfall variability and trends over Africa focusing on 1983–2010. Data sets exhibiting spurious variability, linked in part to a reduction in rain gauge density, were identified. The remaining observations display coherent increases in annual Sahel rainfall (29 to 43 mm yr−1 per decade), decreases in March–May East African rainfall (−14 to −65 mm yr−1 per decade), and increases in annual Southern Africa rainfall (32 to 41 mm yr−1 per decade). However, Central Africa annual rainfall trends vary in sign (−10 to +39 mm yr−1 per decade). For Southern Africa, observed and sea surface temperature (SST)-forced model simulated rainfall variability are significantly correlated (r~0.5) and linked to SST patterns associated with recent strengthening of the Pacific Walker circulation.

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O estudo da variabilidade da precipitação é importante para o planejamento das atividades econômicas, possibilitando o uso mais eficiente e racional dos recursos hídricos. Dessa forma, o objetivo desta pesquisa é caracterizar o estado do Rio Grande do Norte com relação à variabilidade temporal da precipitação, agrupá-lo em regiões homogêneas e comparar diferentes técnicas de agrupamento. Para o estudo da variabilidade pluvial foram utilizados os índices: Grau de Concentração de Precipitação (PCD), que representa o grau em que a precipitação é distribuída ao longo do ano; e o Período de Concentração de Precipitação (PCP), que reflete o período no qual a precipitação está mais concentrada. Para a realização dos agrupamentos foram escolhidas as variáveis: PCD, PCP, médias da precipitações anuais e médias das precipitações mensais. Posteriormente, foi aplicada a análise de agrupamento para obter grupos com características similares. Os resultados mostraram que as precipitações são melhor distribuídas na região leste do estado, neste caso, os meses mais chuvosos são de maio a agosto. Os municípios localizados nessa área possuem dois picos de chuvas, devido à atuação de dois sistemas: Perturbações Ondulatórias dos Alísios (POA s) e Zona de Convergência Intertropical (ZCIT). Nas regiões localizadas a oeste os meses que possuem maior concentração de chuvas são março e abril, neste caso temos apenas um pico de precipitação, devido a atuação da ZCIT. A identificação de áreas homogêneas favorece o planejamento adequado de acordo com as características de cada grupo formado e o RN pode foi dividido em 4 (quatro) regiões homogêneas. As técnicas de agrupamento utilizadas apresentaram resultados semelhantes, porém, sugere-se o uso de mais de uma técnica para que se possa analisar qual delas reflete melhor a realidade local. O estudo da variabilidade de precipitação, através dos índices estudados e do agrupamento realizado, são ferramentas adequadas ao planejamento ambiental e econômico

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Pós-graduação em Geografia - FCT

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Geociências e Meio Ambiente - IGCE

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O presente trabalho apresenta uma contribuição aos estudos de modelagem climática com ênfase na variabilidade pluviométrica sazonal da Amazônia oriental, durante as estações de verão e outono (DJF e MAM). Baseado nos resultados das simulações regionais do RegCM3 para um período de 26 anos (1982/83 a 2007/08) e usando domínio em alta resolução espacial (30 Km) e dois diferentes esquemas de convecção (Grell e MIT), foi investigado o desempenho do modelo em simular a distribuição regional de precipitação sazonal na Amazônia oriental, com referência a um novo conjunto de dados observacional compilado com informações de uma ampla rede integrada de estações pluviométricas. As análises quantitativas evidenciaram que o RegCM3 apresenta erros sistemáticos, sobretudo aqueles relacionados com viés seco no Amapá e norte/nordeste do Pará usando ambos os esquemas Grell e MIT, os quais apontam que o modelo não reproduz as características da ZCIT sobre o Atlântico equatorial. As simulações usando MIT, também apresentaram viés úmido no sudoeste/sul/sudeste do Pará e norte do Tocantins. Além disso, através da técnica de composições, também foi investigado o desempenho do RegCM3 em reproduzir os padrões espaciais anômalos de precipitação sazonal em associação aos episódios ENOS, e as fases do gradiente térmico sobre o Atlântico intertropical. Os resultados demonstraram que o modelo conseguiu representar realisticamente bem o padrão espacial das anomalias pluviométricas acima (abaixo) do normal em grande parte da Amazônia oriental, durante os conhecidos cenários favoráveis, i.e., condições de La Niña e gradiente de aTSM para o Atlântico sul (desfavoráveis, i.e., El Niño e gradiente de aTSM para o Atlântico norte.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)