974 resultados para Rainfall Variability


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The destructive environmental and socio-economic impacts of the El Niño/Southern Oscillation1, 2 (ENSO) demand an improved understanding of how ENSO will change under future greenhouse warming. Robust projected changes in certain aspects of ENSO have been recently established3, 4, 5. However, there is as yet no consensus on the change in the magnitude of the associated sea surface temperature (SST) variability6, 7, 8, commonly used to represent ENSO amplitude1, 6, despite its strong effects on marine ecosystems and rainfall worldwide1, 2, 3, 4, 9. Here we show that the response of ENSO SST amplitude is time-varying, with an increasing trend in ENSO amplitude before 2040, followed by a decreasing trend thereafter. We attribute the previous lack of consensus to an expectation that the trend in ENSO amplitude over the entire twenty-first century is unidirectional, and to unrealistic model dynamics of tropical Pacific SST variability. We examine these complex processes across 22 models in the Coupled Model Intercomparison Project phase 5 (CMIP5) database10, forced under historical and greenhouse warming conditions. The nine most realistic models identified show a strong consensus on the time-varying response and reveal that the non-unidirectional behaviour is linked to a longitudinal difference in the surface warming rate across the Indo-Pacific basin. Our results carry important implications for climate projections and climate adaptation pathways.

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Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

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The mechanisms resulting in large daily rainfall events in Northeast Brazil are analyzed using data filtering to exclude periods longer than 30 days. Composites of circulation fields that include all independent events do not reveal any obvious forcing mechanisms as multiple patterns contribute to Northeast Brazil precipitation variability. To isolate coherent patterns, subsets of events are selected based on anomalies that precede the Northeast Brazil precipitation events at different locations. The results indicate that at 10 degrees S, 40 degrees W, the area of lowest annual rainfall in Brazil, precipitation occurs mainly in association with trailing midlatitude synoptic wave trains originating in either hemisphere. Closer to the equator at 5 degrees S, 37.5 degrees W, an additional convection precursor is found to the west, with a spatial structure consistent with that of a Kelvin wave. Although these two sites are located within only several hundred kilometers of each other and the midlatitude patterns that induce precipitation appear to be quite similar, the dates on which large precipitation anomalies occur at each location are almost entirely independent, pointing to separate forcing mechanisms.

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In this study, observations and numerical simulations are used to investigate how different El Nino events affect the development of SST anomalies in the Atlantic and how this relates to the Brazilian northeast (NE) precipitation. The results show that different types of El Nino have different impacts on the SST anomalies of the equatorial and tropical South Atlantic but a similar SST response in the tropical North Atlantic. Strong and long (weak and short) El Ninos with the main heating source located in the eastern (central) Pacific generate cold (warm) anomalies in the cold tongue and Benguela upwelling regions during boreal winter and spring. When the SST anomalies in the eastern equatorial and tropical South Atlantic are cold (warm), the meridional SST gradient across the equator is positive (negative) and the ITCZ is not allowed (allowed) to move southward during the boreal spring; as a consequence, the precipitation is below (above) the average over the NE. Thus, strong and long (weak and short) El Ninos are followed by dry (wet) conditions in the NE. During strong and long El Ninos, changes in the Walker circulation over the Atlantic and in the Pacific-South Atlantic (PSA) wave train cause easterly wind anomalies in the western equatorial Atlantic, which in turn activate the Bjerknes mechanism, establishing the cold tongue in boreal spring and summer. These easterly anomalies are also responsible for the Benguela upwelling. During short and weak El Ninos, westerly wind anomalies are present in the western equatorial Atlantic accompanied by warm anomalies in the eastern equatorial and tropical South Atlantic; a positive phase of the South Atlantic dipole develops during boreal winter. The simulations highlight the importance of ocean dynamics in establishing the correct slope of the equatorial thermocline and SST anomalies, which in turn determine the correct rainfall response over the NE.

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This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of Sao Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of Sao Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

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The State of Sao Paulo is the richest in Brazil, responsible for over 30% of the Brazilian gross rate. It has a population of around 30 million and its economy is based on agriculture and industrial products. Any change in climate can have a profound influence on the socio-economics of the State. In order to determine changes in total and extreme rainfall over Sao Paulo State, climate change indices derived from daily precipitation data were calculated using specially designed software. Maps of trends for a subset of 59 rain gauge stations were analysed for the period 1950-1999 and also for a subset of this period, 1990-1999, representing more recent climate. A non-parametric Mann-Kendall test was applied to the time series. Maps of trends for six annual precipitation indices (annual total precipitation (PRCPTOT), very heavy precipitation days (R20mm), events greater than the 95th percentile (R95p), maximum five days precipitation total (RX5day), the length of the largest wet spell (CWD) and the length of the largest dry spell (CDD)) were analysed for the entire period. These exhibited statistically significant trends associated with a wetter climate. A significant increase in PRCPTOT, associated with very heavy precipitation days, were observed at more than 45% of the rain gauge stations. The Mann-Kendall test identified that the positive trend in PRCPTOT is possibly related to the increase in the R95p and R20mm indices. Therefore, the results suggest that there has been a change in precipitation intensity. In contrast, the indices for the more recent shorter time series are significantly different to the longer term indices. The results indicate that intense precipitation is becoming concentrated in a few days and spread over the period when the CDD and R20mm indices show positive trends, while negative ones are seen in the RX5day index. The trends found could be related to many anthropogenic aspects such as biomass burning aerosols and land use.

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This paper examines moisture transport on intraseasonal timescales over the continent and over the South Atlantic convergence zone (SACZ) during the South America (SA) summer monsoon. Combined Empirical Orthogonal Function analysis (EOFc) of Global Precipitation Climatology Project pentad precipitation, specific humidity, air temperature, zonal and meridional winds at 850 hPa (NCEP/NCAR reanalysis) are performed to identify the large-scale variability of the South America monsoon system and the SACZ. The first EOFc was used as a large-scale index for the South American monsoon (LISAM), whereas the second EOFc characterized the SACZ. LISAM (SACZ) index showed spectral variance on 30-90 (15-20) days and were both band filtered (10-100 days). Intraseasonal wet anomalies were defined when LISAM and SACZ anomalies were above the 75th percentile of their respective distribution. LISAM and SACZ wet events were examined independently of each other and when they occur simultaneously. LISAM wet events were observed with the amplification of wave activity in the Northern Hemisphere and the enhancement of northwesterly cross-equatorial moisture transport over tropical continental SA. Enhanced SACZ was observed with moisture transport from the extratropics of the Southern Hemisphere. Simultaneous LISAM and SACZ wet events are associated with cross-equatorial moisture transport along with moisture transport from Subtropical Southwestern Atlantic.

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This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.

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A variabilidade anual da produção fotossintética (PP) pelo fitoplâncton na zona da barragem da Represa de Jurumirim (São Paulo, Brasil) foi medida após um estudo no período de três anos sucessivos, com o objetivo de identificar padrões recorrentes e suas causas. Medidas da variabilidade da PP em escala diária foram obtidas em dois períodos do ano (estações seca e chuvosa). Nenhum padrão recorrente foi verificado nos dados de PP, visto não haver relação de sua variabilidade com nenhum fator hidrológico (precipitação, nível e vazão de água e washout) nem, aparentemente, com as condições nutritivas da água. A análise de componentes principais revelou que a PP e a taxa de assimilação foram mais elevadas na época do ano em que o conteúdo de PO4(3-) e N-NH4+ foi mais baixo e quando as razões Z EU/Z MIX foram mais elevadas. A produtividade primária/área pode ser estimada pela razão entre a produtividade volumétrica máxima e o coeficiente de extinção vertical da luz. Entretanto, a biomassa integrada na Z EU foi um pobre preditor da produtividade primária/área. Nenhuma correlação foi encontrada entre a temperatura da água com a produtividade primária (por área e volumétrica máxima). em conseqüência, o estudo da PP em três anos sucessivos mostrou que o padrão de variabilidade é tipicamente caótico. em relação às medidas de curta duração, maior PP foi encontrada na estação seca do que na chuvosa. em ambos os períodos, a variabilidade da PP (por área) foi de aproximadamente 35-40%. O padrão foi atribuído não somente à variação na concentração dos nutrientes mas também à magnitude de penetração de luz na água associado ao regime de circulação. Um comentário sobre a relação entre produção primária pelo fitoplâncton com produção pesqueira é também apresentada.

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Purpose - This paper seeks to address the issue of persistent and widespread drought conditions during 2000 and 2001, which were the apparent cause of the decline of water levels in the reservoirs of Brazilian hydroelectric power plants. Design/methodology/approach - This issue is addressed here through a case study of the hydroclimatology of the Paraíba river basin, in Southeast Brazil, home to four large multi-purpose operational reservoirs. Findings - The data analysis shows that neither changes in the frequency nor magnitude of extreme hydrological events (droughts and floods) nor in annual rainfall amounts can be detected from the existing climate record. The explanation is consistent with the fact that the terrestrial water and energy cycles are tightly, and non-linearly, coupled through evapotranspiration. Research limitations/implications - Therefore small change in the seasonality of rainfall can have a significant impact on the basin's overall hydrologic regime, and thus on the availability of water resources. Originality/value - Often, adaptation and resilience to climate variability are discussed in the context of catastrophic events such as floods and droughts. This study suggests that a different type of impacts, those associated with subtle, yet persistent changes of seasonality in the terrestrial water cycle, cannot be ignored in studies of long-term sustainability of water resources. © Emerald Group Publishing Limited.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The emphasis in this research is to evaluate the spatial distribution of the precipitation using a geostatistics approach. Seasonal time scales records considering DJF, MAM, JJA e SON periods performed the analysis. Procedures to evaluate the variogram selection and to produce kriging maps were performed in a GIS environment (ArcGIS®). The results showed that kriging method was very suitable to detect both large changes in the whole area as those local small and subtle changes. Kriging demonstrated be a powerful statistical interpolation method that might be very useful in regions with great complexity in climatology and geomorphology.

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In this study we examine the impact of Indian Ocean sea surface temperature (SST) variability on South American circulation using observations and a suite of numerical experiments forced by a combination of Indian and Pacific SST anomalies. Previous studies have shown that the Indian Ocean Dipole (IOD) mode can affect climate over remote regions across the globe, including over South America. Here we show that such a link exists not only with the IOD, but also with the Indian Ocean basin-wide warming (IOBW). The IOBW, a response to El Nino events, tends to reinforce the South American anomalous circulation in March-to-May associated with the warm events in the Pacific. This leads to increased rainfall in the La Plata basin and decreased rainfall over the northern regions of the continent. In addition, the IOBW is suggested to be an important factor for modulating the persistence of dry conditions over northeastern South America during austral autumn. The link between the IOBW and South American climate occurs via alterations of the Walker circulation pattern and through a mid-latitude wave-train teleconnection.

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We present the first high resolution, approximately similar to 4 years sample spacing, precipitation record from northeastern Brazil (hereafter referred to as 'Nordeste') covering the last similar to 3000 yrs from Th-230-dated stalagmites oxygen isotope records. Our record shows abrupt fluctuations in rainfall tied to variations in the intensity of the South American summer monsoon (SASM), including the periods corresponding to the Little Ice Age (LIA), the Medieval Climate Anomaly (MCA) and an event around 2800 yr B.P. Unlike other monsoon records in southern tropical South America, dry conditions prevailed during the LIA in the Nordeste. Our record suggests that the region is currently undergoing drought conditions that are unprecedented over the past 3 millennia, rivaled only by the LIA period. Using spectral, wavelet and cross-wavelet analyses we show that changes in SASM activity in the region are mainly associated with variations of the Atlantic Multidecadal Oscillation (AMO) and to a lesser degree caused by fluctuations in tropical Pacific SST. Our record also shows a distinct periodicity around 210 years, which has been linked to solar variability. Citation: Novello, V. F., et al. (2012), Multidecadal climate variability in Brazil's Nordeste during the last 3000 years based on speleothem isotope records, Geophys. Res. Lett., 39, L23706, doi: 10.1029/2012GL053936.

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This study analyzes important aspects of the tropical Atlantic Ocean from simulations of the fourth version of the Community Climate System Model (CCSM4): the mean sea surface temperature (SST) and wind stress, the Atlantic warm pools, the principal modes of SST variability, and the heat budget in the Benguela region. The main goal was to assess the similarities and differences between the CCSM4 simulations and observations. The results indicate that the tropical Atlantic overall is realistic in CCSM4. However, there are still significant biases in the CCSM4 Atlantic SSTs, with a colder tropical North Atlantic and a hotter tropical South Atlantic, that are related to biases in the wind stress. These are also reflected in the Atlantic warm pools in April and September, with its volume greater than in observations in April and smaller than in observations in September. The variability of SSTs in the tropical Atlantic is well represented in CCSM4. However, in the equatorial and tropical South Atlantic regions, CCSM4 has two distinct modes of variability, in contrast to observed behavior. A model heat budget analysis of the Benguela region indicates that the variability of the upper-ocean temperature is dominated by vertical advection, followed by meridional advection.