Dissertations / Theses on the topic 'Standardized Precipitation Evapotranspiration Index'

Published Article
The objective of this study was to characterize meteorological droughts in the Central Region of South Africa, Modder River Basin, C52A quaternary catchment using two popular drought indices: Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) and to compare the two indices. Drought events were characterized based on their frequency, duration, magnitude and intensity. The indices were computed for the time-scales that are important for planning and management of water resources, i.e. 3-, 6- and 12-month time-scales. The basic meteorological input data used in the computation of these indices were 57 years (1950-2007) of monthly precipitation and monthly temperature data which were recorded at The Cliff weather station in the quaternary catchment. It was found that both SPI and SPEI responded to drought events in similar fashion in all time-scales. During the analysis period, a total of 37, 26 and 17 drought events were identified in the area based on 3-, 6-, and 12-month times-scales, respectively. Considering event magnitude as severity parameter, results from both indices identified the periods 1984-1985, 1992-1993 and 2003-2005 as the severest drought periods in the area. However, when the effects of both drought duration and magnitude are considered (drought intensity), the most severest drought events were identified during the years 1982/83, 1966 and 1973 based on 3-, 6- and 12-month timescales, respectively. It was concluded that although the SPEI generally exhibits veracity over SPI by including, apart from precipitation, additional meteorological parameter, mean temperature, SPI should be adopted as an appropriate drought monitoring tool in an area, like Africa, where meteorological data are scarce.

Mestrado em Engenharia Agronómica - Instituto Superior de Agronomia
The Palmer Drought Severity Index (PDSI) was tested along with two indices resulting from modifying its original formulation, one concerning the replacement of the Thornthwaite equation to compute potential evapotranspiration (ETP) by the FAO Penman-Monteith method, and the other consisting in replacing the soil water balance model and the ETP computation that passes to correspond to the ETP of an olive orchard, generating a new index: the MedPDSI. A factor for the normalization of the index, the climate characteristic (K), was reviewed and the index was calibrated for each analyzed location. The Standardized Precipitation Index (SPI) for the 9 and 12 month time-scales was also tested and compared with the three variants of the PDSI. The results revealed that the modification of K improved the standardization of the PDSI and that the calibration produced statistically improved results. It was found that the MedPDSI anticipates the initiation of droughts over the original PDSI, either with ETP Thornthwaite or with ETP FAO Penman-Monteith, and tends to classify droughts more severely than the first. The use of 9 month time-scale in the SPI is the one that best relates to the PDSI, since it clearly anticipates the onset of droughts relative to the 12 month scale.

Understanding the patterns and relationships between land surface productivity and the climatic condition is essential to predict the impact of climate change. This study aims to understand spatial temporal variability and relationships of land surface productivity using Normalized Difference Vegetation Index (NDVI) and drought indices, mainly Standard Precipitation Index (SPI) and Standard Precipitation Evaporation Index (SPEI) across four ecoregions: Mojave, Sonoran, Apache Highlands and Chihuahua of the Southwest United States. Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and land cover data, and Parameter Regression on Independent Slopes Model (PRISM) precipitation and temperature data were used for analysis. Using Mann-Kendall, I calculated the trends in annual and seasonal NDVI, SPI and SPEI datasets. I used the Pearson Correlation Coefficients to examine the response of integrated and monthly NDVI values to SPI and SPEI values. The positive and negative trends were found during the annual and monsoon seasons whereas only negative trends were found during the spring season for NDVI, SPI and SPEI values. The relationship between NDVI and coincident and antecedent SPEI values changed significantly by area and season for each of the ecoregions across the east-west seasonal precipitation gradient.

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A pesquisa desenvolvida tem foco na análise espaço-temporal das secas, baseada em informações de chuvas. Para a obtenção das séries históricas representativas das secas e estudo espacial do fenômeno, foi empregada a análise regional de precipitações com momentos-L, além do índice de seca Standardized Precipitation Index (SPI). Para a análise de séries temporais de secas foi utilizada a transformada de ondaletas, uma alternativa à transformada de Fourier, a qual permite identificar periodicidades nas séries além de localizar variações dessas periodicidades ao longo do tempo. Procurou-se ainda investigar possíveis influências dos fenômenos El Niño Oscilação Sul (ENOS), por meio do Índice Oceânico Niño (ION) e do Índice de Oscilação Sul (IOS), e do fenômeno da Oscilação Decenal do Pacífico (ODP) sobre os índices de secas obtidos. Foi proposto incorporar a análise regional de frequência no cálculo das séries de SPI, com vistas a contribuir com a superação da crítica de que, para esse cálculo, longos registros históricos de chuvas são necessários, além de considerar apenas a possibilidade de uso da distribuição de probabilidades Gama. Reforça-se a necessidade de, no cálculo do SPI, considerar outras possibilidades além dessa distribuição e a análise local de frequências, uma vez que valores extremos de chuvas eventualmente distorcem significativamente as estimativas do índice. Além disso, a análise regional de frequência permitiu definir regiões estatisticamente homogêneas, as quais apresentaram abrangência geográfica inversamente proporcional aos totais precipitados médios anuais. Para a análise de séries temporais o uso da transformada de ondaletas não detectou aumento da frequência de ocorrência de secas na área de estudo nos últimos anos. Além disso, não possibilitou fazer uma conexão clara entre as secas na região de estudo e os índices climáticos IOS, ION e ODP. Ainda assim, de alguma forma, percebeu-se que esses fenômenos de grande escala influenciam a intensidade das secas em escala local, uma vez que foi persistente a observação das secas mais extremas na região em fase fria de ENOS e ODP, corroborando a tese de que extremos climáticos são mais intensos na América do Sul quando o ENOS e ODP estão em fase.

This research is focused on space-time analysis of droughts, based on rainfall data. In order to obtain time series of droughts, the Standardized Precipitation Index (SPI), a rainfall based drought index was used. The spatial analysis of the phenomenon was based on the regional analysis with L-moments. For the time series studies, the continuous wavelet transform was used. This technique shows up as an alternative to Fourier analysis, to identify periodicities in time series and to find variations of these frequencies over time. Also was sought to investigate possible influences of El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on the time series of drought index obtained. It was proposed to incorporate the regional frequency analysis with L-moments for the calculation of the SPI, in order to overcome the necessity of long historical records of rainfall data in order to obtain a good estimative of the SPIs time series. Also a variety of probability distribution functions were tested, besides Gama. In addition, the regional frequency analysis came to define statistically homogeneous, which in general are spread over large areas whose sizes are inversely proportional to the mean values of rainfall. The continuous wavelet transform did not identify an increased frequency of occurrence of droughts in the study area over time. Also, through use of this technique, it was not possible to identify increased intensity of the phenomenon in the study area in recent years. Moreover, the technique did not allow making a clear connection between the droughts in the study area and macro climatic indices used (ENSO and PDO). Yet somehow, it was realized that these macro-scale phenomena may influence the intensity of drought on a local scale, as it was observed persistent cold phase ENSO and PDO in the most extreme drought events in the study area, corroborating the thesis that, when ENSO and PDO are in phase, weather extremes are more intense in South America.
A pesquisa desenvolvida tem foco na análise espaço-temporal das secas, baseada em informações de chuvas. Para a obtenção das séries históricas representativas das secas e estudo espacial do fenômeno, foi empregada a análise regional de precipitações com momentos-L, além do índice de seca Standardized Precipitation Index (SPI). Para a análise de séries temporais de secas foi utilizada a transformada de ondaletas, uma alternativa à transformada de Fourier, a qual permite identificar periodicidades nas séries além de localizar variações dessas periodicidades ao longo do tempo. Procurou-se ainda investigar possíveis influências dos fenômenos El Niño Oscilação Sul (ENOS), por meio do Índice Oceânico Niño (ION) e do Índice de Oscilação Sul (IOS), e do fenômeno da Oscilação Decenal do Pacífico (ODP) sobre os índices de secas obtidos. Foi proposto incorporar a análise regional de frequência no cálculo das séries de SPI, com vistas a contribuir com a superação da crítica de que, para esse cálculo, longos registros históricos de chuvas são necessários, além de considerar apenas a possibilidade de uso da distribuição de probabilidades Gama. Reforça-se a necessidade de, no cálculo do SPI, considerar outras possibilidades além dessa distribuição e a análise local de frequências, uma vez que valores extremos de chuvas eventualmente distorcem significativamente as estimativas do índice. Além disso, a análise regional de frequência permitiu definir regiões estatisticamente homogêneas, as quais apresentaram abrangência geográfica inversamente proporcional aos totais precipitados médios anuais. Para a análise de séries temporais o uso da transformada de ondaletas não detectou aumento da frequência de ocorrência de secas na área de estudo nos últimos anos. Além disso, não possibilitou fazer uma conexão clara entre as secas na região de estudo e os índices climáticos IOS, ION e ODP. Ainda assim, de alguma forma, percebeu-se que esses fenômenos de grande escala influenciam a intensidade das secas em escala local, uma vez que foi persistente a observação das secas mais extremas na região em fase fria de ENOS e ODP, corroborando a tese de que extremos climáticos são mais intensos na América do Sul quando o ENOS e ODP estão em fase.

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The precipitation, due to its importance, is considered one of the main variables of the hydrological cycle. An alternative to collect rainfall data is using rainfall measurements by sensors/satellites. Among these kinds of alternative, the Tropical Rainfall Measuring Mission (TRMM) allows the collection with a spatial resolution 0.25º × 0.25º. Thus, the objective of the study is to understand, in more detail, the behavior and distribution of rainfall throughout the Upper São Francisco basin (Sub-40), in a recent period (1998-2013). The survey was conducted in the following steps: collection of TRMM rainfall data from 1998 to 2013 organizing them monthly and yearly; getting Três Marias reservoir in flow data; getting altimetry SRTM data; analyzing the correlation between the TRMM precipitation and the inflows to Três Marias reservoir; generating surface profiles to compare with the precipitation data, analyzing the number of consecutive dry days and consecutive wet days; computing the Standardized Precipitation Index - SPI for each point (169 points); spatial distribution of annual and monthly accumulated rainfall data, the correlation of rainfall and flow, of consecutive wet and dry days, the SPI index and cluster analysis. According to the results, it can be concluded that the years of highest and lowest value of annual rainfall depth was respectively 2009 and 2012. The driest months are June to August, and July is the driest one. In contrast, the wettest months are from November to January, and most rainy month is December. The annual and monthly precipitation depth showed that the northeast region of the basin rains less and the western and southern basin are wetter. The precipitation response to the inflow to the Três Marias reservoir is four days after the rainfall occurs. The relation between precipitation and altimetry shows that most of the annual rainfall depth is directly proportional to altimetry, but in some cases it shows little variability in the ground. Regarding the SPI, it was possible to calculate the beginning, end, intensity and magnitude of each dry and wet season. From the maps, SPI spatial information was produced in order to identify for each period the regions with highest and lowest values. By means of the map and dendrogram clusters, regions with higher and lower similarity between the monthly accumulated rainfall data were identified. Finally, the TRMM sensor proved useful in the analysis of spatial and temporal variability of precipitation over the studied basin, accounting satisfactorily dry and rainy periods. With easy acquisition and handling, satellite data is a viable alternative to collect precipitation data with spatial and temporal quality, especially in areas of difficult access or in developing countries.
A precipitação, pela sua importância, é considerada uma das principais variáveis do ciclo hidrológico. Uma alternativa para coletar dados de chuva é utilizar precipitações obtidas por sensores/satélites. Dentre estes, a Tropical Rainfall Measuring Mission (TRMM) permite a coleta com resolução espacial de 0,25º × 0,25º. Com isso, o objetivo do estudo é compreender, de forma mais detalhada, o comportamento e a distribuição da precipitação ao longo da bacia do Alto São Francisco (Sub-40), em período recente (1998−2013). A pesquisa foi realizada nas seguintes etapas: coleta de dados do TRMM para o período de 1998 a 2013 organizando-os em acumulados mensais e anuais; coleta dos dados de vazão do reservatório Três Marias; coleta de dados de altimetria SRTM; correlação diária entre os elementos de precipitação TRMM; analisar o comportamento da precipitação anual da Sub-40 frente aos dados altimétricos; identificar a quantidade de dias secos e úmidos consecutivos de cada ponto da grade utilizado; extração do Índice Padronizado de Precipitação - SPI para cada ponto (169 pontos); espacialização dos dados de precipitação acumulada anual e mensal, da correlação de chuva e vazão, dos dias secos e úmidos consecutivos, do Índice SPI e da análise de cluster. De acordo com os resultados obtidos, pode-se concluir que os anos de maior e menor valor de precipitações acumuladas anuais foram respectivamente os anos de 2009 e 2012. Os meses mais secos foram os de junho a agosto, sendo julho o mês mais seco. Em contrapartida, os meses mais úmidos foram de novembro a janeiro, com maior precipitação ocorrendo em dezembro. Os dados de precipitação acumuladas anuais e mensais mostraram que a região nordeste da bacia chove menos e que o oeste e sul da bacia são mais úmidos. O tempo de resposta da precipitação frente à vazão afluente ao reservatório Três Marias é de quatro dias após a ocorrência de chuvas. A relação entre a precipitação e altimetria mostra que a maioria dos dados de precipitações acumuladas anuais é diretamente proporcional à altimetria, mas que em alguns casos ela apresenta pouca variabilidade em relação ao terreno. Com relação ao SPI, a partir dos mapas, produziram-se informações de SPI de maneira espacializada identificando a cada período as regiões de maiores e menores valores. Observando os mapas de clusters e dendrograma identificaram-se as regiões com maior e menor similaridade entre os dados de precipitação acumulada mensal. Por fim, o sensor TRMM se mostrou hábil na análise da variabilidade espaço-temporal da precipitação sobre a bacia, representando de forma satisfatória os períodos secos e chuvosos. Com fácil aquisição e manuseio, os dados do satélite são uma alternativa viável para se coletar informações pluviométricas com qualidade espacial e temporal, principalmente em regiões de difícil acesso ou em países em desenvolvimento.

A seca que assola o norte de Minas Gerais é um desencadeante de severos impactos socioambientais. Mudanças na distribuição das precipitações, ou mesmo a redução no volume de chuvas é fator suficiente para a desorganização da atividade econômica regional. Neste contexto, este trabalho analisou a distribuição espaço-temporal da seca/estiagem no norte de Minas Gerais, entre 2003 a 2014. A metodologia consistiu na elaboração de série temporal de anomalia padronizada de NDWI utilizando imagens de reflectância MOD13Q1/MODIS. Para a realização das análises utilizou-se como base: os decretos de anormalidade por motivo de seca/estiagem, dados de perdas e danos, de precipitação e de variação de água da subsuperfície das soluções GRACE. Foram realizadas correlações entre NDWI e precipitação e entre anomalia padronizada de NDWI e anomalia de precipitação, considerando dados sem e com 30 dias de defasagem. Foi aplicado teste de médias, teste t de Student, para a anomalia padronizada de NDWI e a anomalia de precipitação, em um intervalo de confiança de 95%. Os resultados demonstraram que a anomalia padronizada de NDWI identificou de forma satisfatória três períodos de seca/estiagem na região. Estes corroboram com os dados de decretos de emergência e calamidade pública, sendo observado um maior número de decretos, principalmente, nestes períodos. Dois períodos identificados como de seca/estiagem foram noticiados como de estiagem severa no norte de Minas Gerais. Esse fato corrobora os dados de anomalia padronizada de NDWI com a situação ocorrida na região. O quantitativo de áreas afetadas por seca também evidencia o mesmo período de maiores números de ocorrências de seca/estiagem e deficiência na distribuição da precipitação. No entanto, o emprego de anomalia padronizada de NDWI na identificação seca/estiagem, por si só, pode não ser suficiente para essa identificação, uma vez que, o fenômeno pode ocorrer e causar danos e prejuízos, em meio a uma paisagem verde, como constatado para 2010. As análises estatísticas mostraram que existem correlações com graus de intensidade melhores entre o NDWI e a precipitação com uma defasagem de 30 dias. Fato também observado para os dados de anomalia padronizada de NDWI e anomalia de precipitação, todavia, foram observadas correlações de fraca a moderada. O teste de médias apresentou diferenças entre as médias apenas para o ano de 2014. Apesar de em todos os outros períodos as médias não serem estatisticamente diferentes entre si, foram verificados baixos valores de p-value, com excessão do período entre 2008 e 2011, onde são verificados p-value entre 0,4 a 0,9. Ainda que os testes estatísticos não apresentaram uma ótima significância, a variação temporal dos dados de anomalia padronizada de NDWI e de anomalia de precipitação evidencia uma relação similar entre esses dados. Por fim, a comparação com dados das soluções GRACE, identificou os mesmos períodos verificados com a anomalia padronizada de NDWI, sendo então, observado que estes dados corroboram entre si na identificação de seca/estiagem no norte de Minas Gerais.
The drought that affects the north of Minas Gerais State causes severe socio-environment impacts. Changes on the precipitation distribution or even the reduction of the raining amount is enough reason for regional disorganization. In this context, this work analyzed the drought spatial-temporal distribution in the north of Minas Gerais State, between 2003 and 2014. The methodology consisted on the elaboration of time series of standardized anomaly NDWI using images of reflectance MOD13Q1/MODIS. For the analysis it was used the following basis: the abnormality decrees caused by drought, damage and losses data, precipitation and the water subsurface range on GRACE solution. Correlations were conducted between NDWI and precipitation, as well as between standardized anomaly NDWI and precipitation anomaly, considering data with and without 30 days of gap. It was applied average test, the Student t-test, for the standardized anomaly NDWI and precipitation anomaly, with a confidence range of 95%. Results demonstrated that standardized anomaly NDWI satisfactorily identified three seasons of drought in this region. It corroborates with emergency decrees and public calamity data, in what it was observed a higher number of decrees, especially in these periods. Two seasons identified as drought were reported as severe drought in the north of Minas Gerais State. This fact validates the standardized anomaly NDWI data with the situation occurred in the region. The quantity of affected areas drought, also evidences the same period of larger numbers of occurrences drought and disability in the distribution of precipitation. However, the use of standardized anomaly NDWI by itself on the identification of drought may not be enough evidence for this association, since the phenomenon can occur and cause damages and losses among a green landscape, as seen in 2010. Statistical analysis demonstrated that there are correlations with better intensity degrees between the NDWI and the precipitation with a gap of 30 days. This fact was also observed for the standardized anomaly NDWI and precipitation anomaly data, however, mild to moderate correlations were observed. Student t-test demonstrated differences between the averages only for the year of 2014. Despite for all other periods averages were not statistically different, they were observed p-value low values, with the exception of the period between 2008 and 2011, which are verified p-value between 0.4 and 0.9. Although statistical tests did not demonstrated a great significance, the temporal variation of standardized anomaly NDWI data and precipitation anomaly evidenciate a similar relationship between these data. Lastly, the comparison with data from GRACE solutions, identified the same periods verified with the standardized anomaly NDWI, being then observed that these data corroborates between them in the identification of draught in the north of Minas Gerais State.

Anthropogenic activities including urbanization, rapid industrialization, deforestation and burning of fossil fuels are broadly agreed on as primary causes for ongoing climate change. Scientists agree that climate change over the next century will continue to impact water resources with serious implications including storm surge flooding and a sea level rise projected for North America. To date, the majority of climate change studies conducted across the globe have been for large-sized watersheds; more attention is required to assess the impact of climate change on smaller watersheds, which can help to better frame sustainable water management strategies. In the first of three studies described in this dissertation, trends in annual precipitation and air-temperature across the Commonwealth of Kentucky were evaluated using the non-parametric Mann-Kendall test considering meteorological time series data from 84 weather stations. Results indicated that while annual precipitation and mean annual temperature have been stable for most of Kentucky over the period 1950-2010, there is evidence of increases (averages of 4.1 mm/year increase in annual precipitation and 0.01 °C/year in mean annual temperature) along the borders of the Kentucky. Considered in its totality, available information indicates that climate change will occur – indeed, it is occurring – and while much of the state might not clearly indicate it at present, Kentucky will almost certainly not be exempt from its effects. Spatial analysis of the trend results indicated that eastern part of the state, which is characterized by relatively high elevations, has been experiencing decreasing trends in precipitation. In the second study, trends and variability of seven extreme precipitation indices (total precipitation on wet days, PRCPTOT; maximum length of dry and wet periods, CDD and CWD, respectively; number of days with precipitation depth ≥20 mm, R20mm; maximum five-day precipitation depth, RX5day; simple daily precipitation intensity, SDII; and standardized precipitation index, SPI were analyzed for the Kentucky River Basin for both baseline period of 1986-2015 and the late-century time frame of 2070-2099. For the baseline period, the majority of the indices demonstrated increasing trends; however, statistically significant trends were found for only ~11% of station-index combinations of the 16 weather stations considered. Projected magnitudes for PRCPTOT, CDD, CWD, RX5day and SPI, indices associated with the macroweather regime, demonstrated general consistency with trends previously identified and indicated modest increases in PRCPTOT and CWD, slight decreases in CDD, mixed results for RX5day, and increased non-drought years in the late century relative to the baseline period. The study’s findings indicate that future conditions might be characterized by more rainy days but fewer large rainfall events; this might lead to a scenario of increased average annual rainfall but, at the same time, increased water scarcity during times of maximum demand. In the third and final study, the potential impact of climate change on hydrologic processes and droughts over the Kentucky River basin was studied using the watershed model Soil and Water Assessment Tool (SWAT). The SWAT model was successfully calibrated and validated and then forced with forecasted precipitation and temperature outputs from a suite of CMIP5 global climate model (GCMs) corresponding to two different representative concentration pathways (RCP 4.5 and 8.5) for two time periods: 2036-2065 and 2070-2099, referred to as mid-century and late-century, respectively. Climate projections indicate that there will be modest increases in average annual precipitation and temperature in the future compared to the baseline (1976-2005) period. Monthly variations of water yield and surface runoff demonstrated an increasing trend in spring and autumn, while winter months are projected as having decreasing trends. In general, maximum drought length is expected to increase, while drought intensity might decrease under future climatic conditions. Hydrological droughts (reflective of water availability), however, are predicted to be less intense but more persistent than meteorological droughts (which are more reflective of only meteorological variables). Results of this study could be helpful for preparing any climate change adaptation plan to ensure sustainable water resources in the Kentucky River Basin.

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Capes
O estado de Minas Gerais, localizado na região Sudeste do Brasil, possui um território planáltico, com áreas mais elevadas situadas na porção sul. O clima é predominantemente tropical e tropical de altitude, com temperaturas oscilando, normalmente, entre 17 e 20°C. Tais características o tornam, muitas vezes, susceptível a fortes chuvas, provocando transtornos diversos à população. Desse modo, buscou-se analisar a variabilidade da chuva mineira através de técnicas que fossem capazes de definir padrões espaciais e temporais de eventos secos e chuvosos, assim como modulá-los nas escalas tempo-frequência. Para isso, calculou-se o Índice de Precipitação Normalizada (IPN) mensal e trimestral no período 1977-2012. A fim de encontrar padrões espaço-temporais e regiões homogêneas (RH) do IPN mensal e trimestral, utilizaram-se as técnicas da Análise em Componentes Principais (ACP) e Agrupamentos (AA). A técnica da Transformada de Ondeletas (TO) foi aplicada para algumas localidades das diferentes RH em diversas escalas. A TO possibilitou encontrar oscilações importantes no sinal da precipitação, mostrando as componentes dominantes da variabilidade da chuva na área pesquisada. Nos espectros de fase e global de energia da TO, para a chuva mensal, predominou o ciclo anual em todas as localidades. Além da escala anual, observaram-se interações com escalas inferiores a doze meses, possivelmente decorrentes da sazonalidade da precipitação. A TO da precipitação e da Radiação de Onda Longa (ROL) diárias evidenciou frequências maiores que as da chuva mensal. A análise dos espectros de fase e de energia global, nas regiões centro-sul e oeste, apresentou maior energia no início das séries da precipitação e de ROL. Contribuições mais elevadas ocorreram nas escalas sinóticas e intrassazonais, principalmente nas localidades de Viçosa, Bom Despacho, Ituiutaba e Lavras. Esses padrões temporais estão associados com a Oscilação de Madden-Julian (OMJ), intensificando a atuação de sistemas moduladores do clima de Minas Gerais. Oscilações em escalas menores que dez dias foram detectadas nos anos de 2011 e 2012 e podem estar associadas aos sistemas de curto prazo que contribuíram para a chuva mineira. No caso de 2011, os eventos de chuva observados em meados de janeiro foram modulados pelos episódios da Zona de Convergência do Atlântico Sul (ZCAS) e reforçados pela atuação da OMJ.
The state of Minas Gerais, located in southeastern Brazil, has a plateaux area, with higher areas in the southern part. The climate is predominantly tropical and tropical altitude, with temperatures ranging normally between 17 and 20°C. These characteristics make it often susceptible to heavy rains, causing many disorders the population. Thus, it sought to analyze the variability of the rain of Minas Gerais through techniques that were able to define spatial and temporal patterns of dry and wet events, and modulate them in the time-frequency ranges. For this, we calculated the Standardized Precipitation Index (SPI) monthly and quarterly in the period 1977-2012. In order to find spatiotemporal patterns and homogeneous regions (HR) of the monthly and quarterly SPI, we used the techniques of Principal Components Analysis (PCA) and Cluster Analysis (CA). The technique of Wavelets Transform (WT) has been applied to some locations of the different HR at various scales. The WT possible find important variations in rainfall signal, showing the dominant components of rainfall variability in the studied area. In phase spectra and global energy of WT, for the monthly rainfall, dominated the annual cycle in all locations. In addition to the annual scale, there were interactions with scales less than twelve months, possibly due to the seasonality of precipitation. The WT of precipitation and Outgoing Longwave Radiation (OLR) daily reported higher frequencies than the monthly rainfall. Analysis of phase spectra and global power, in south-central and western regions, showed higher energy at the beginning of the series of precipitation and OLR. Higher contributions occurred in the synoptic and intraseasonal scales, especially in the localities of Viçosa, Bom Despacho, Ituiutaba and Lavras. These temporal patterns are associated with the Madden-Julian Oscillation (MJO), intensifying the activity of modulators systems climate of Minas Gerais. Oscillations at smaller scales than ten days were detected in 2011 and 2012 and may be associated with short-term systems that contributed to the Minas Gerais rainfall. In the case of 2011 rain events observed in mid-January they were modulated by episodes of South Atlantic Convergence Zone (SACZ) and reinforced by the performance of MJO.

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This research aims to show meteorological drought occurrences in Paraná State and to present possible future scenarios concerning this extreme weather. There was some requirement to understand better the rainfall patterns in Paraná State when data were analyzed at first, since there were an extensive series of historical precipitation data, from 1980 to 2010 and simulated data by the global model MIROC5 nestled with the Eta regional model, for the future until 2050. The first paper aims to detect analyze variability and precipitation trend in Paraná. Non-parametric tests were applied to detect precipitation trends as well as compare data from historical series with future data. The results have called the researcher’s attention due to the great variability and significant changes in the average monthly precipitation that can occurred in the studied State. Secondly, the extreme drought theme was approached based on the historical series from 1980 to 2015. The second paper aims to analyze variability and future scenarios of drought in Paraná State, using the standardized drought index. The results show that, although there is an increasing trend of precipitation in the State, there is also a change concerning the drought scenario, which warns of a possible decrease in water availability, especially in the Metropolitan mesoregion. Changes in water resources management policies would be interesting to help future mitigation actions of this phenomenon.
Esse trabalho científico tem como objetivo mostrar ocorrências de seca meteorológica sobre o Estado do Paraná e mostrar possíveis cenários futuros desse extremo climático. Em uma primeira análise dos dados, como tínhamos uma série abrangente de precipitação (período de 1980 a 2010) e também dados simulados pelo modelo global MIROC5 aninhado com o modelo regional Eta (para o futuro até 2050), observamos a necessidade de se entender melhor o regime de precipitação no Estado do Paraná. O artigo 1 tem como objetivos detectar e analisar a variabilidade e a tendência de precipitação sobre o Estado, bem como comparar dados da série histórica com dados da série futura. Os resultados chamam atenção para a grande variabilidade e mudanças significativas na precipitação média mensal que poderão ocorrer no Estado do Paraná. Em um segundo momento, o tema seca extrema foi abordado, com série histórica dos anos de 1980 a 2015. O artigo 2 tem como objetivo analisar a variabilidade e os futuros cenários de seca sobre o estado do Paraná, utilizando o índice padronizado de seca. Os resultados mostram que, apesar de haver uma tendência crescente de precipitação sobre o Estado, também há mudança do cenário de seca, a qual alerta sobre uma possível redução da disponibilidade hídrica, principalmente na mesorregião Metropolitana. Mudanças nas políticas de gestão dos recursos hídricos seriam importantes para auxiliar futuras ações mitigadoras desse fenômeno.

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A Bacia Hidrográfica do Rio Paraíba do Sul, assim como grande parte do Sudeste Brasileiro, foi afetada a partir do ano de 2014, por um dos maiores períodos de seca de sua história recente. Visando contribuir com o entendimento deste evento no trecho Paulista desta Bacia, a presente pesquisa propõe utilizar o índice padronizado de precipitação (IPP). O IPP foi calculado para as escalas de 1, 3, 6 e 12 meses para diversas estações pluviométricas localizadas na área de estudo. Os resultados obtidos demonstram que houve eventos de seca em anos anteriores ao ápice da crise 2014/2015, sugerindo que o IPP poderia ser utilizado com ferramenta de gestão e operação dos sistemas hídricos da bacia do Paraíba do Sul.
In 2014, the Basin of Paraiba do Sul River as well as much of the Brazilian Southeastern were affected by a major drought periods in their recent history. In order to contribute to understand this event, this research focuses on using the standardized precipitation index (IPP) in order to evaluate this event in part of São Paulo State Basin. The IPP was calculated using the scale of 1, 3, 6 and 12 months to the several rainfall stations, which is located in the study area. As a result, in the studied basin, there were drought events in the previous years to the summit crisis in the 2014/2015. It is suggested that IPP could be used as a tool management and operation of Basin of Paraiba do Sul water systems.

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O Estado do Rio Grande do Sul tem acumulado perdas na produção agropecuária e econômica, em função da ocorrência de eventos de seca. Apesar de todo o avanço tecnológico, a agricultura ainda depende das condições climáticas e meteorológicas e, por isso, estudos devem ser realizados com o intuito de auxiliar na investigação do comportamento da seca, nas mais diversas regiões. Um passo importante para o entendimento dos eventos de seca é a utilização de índices, que fazem um levantamento da situação, conforme uma escala de intensidade, que objetiva dar um panorama do comportamento hídrico da região.Assim, o presente trabalho tem como objetivo identificar e caracterizar o comportamento da seca, utilizando índices meteorológicos, em diferentes escalas temporais para 40 estações, compostas por uma série de dados de precipitação de 90 anos (1913-2002), localizadas no Estado do Rio Grande do Sul, obtidas através do banco de dados do Instituto Nacional de Meteorologia e da Agência Nacional de Águas.Para tanto, foram utilizados dois índices de seca: Índice Padronizado de Precipitação, nas escalas temporais de 1, 3, 6, 9, 12 e 24 meses, nas intensidades severa e extrema,e o Índice de Moreno,em escala trimestral e semestral,nas intensidades intensa e severa, bem como a contagem do número total de dias secos e análise da sequência de dias secos.Para o preenchimento de dados das séries de precipitação diária, foi utilizada a modelagem estocástica Cadeia de Markov de dois estados. Os resultados mostraram que para o Índice de Moreno, a escala trimestral, comparativamente à escala semestral, apresentou maior concentração de eventos de seca. Para o Índice Padronizado de Precipitação,as maiores sequências de meses secos foram encontradas na intensidade extrema; a maior ocorrência de eventos de seca severa coincidiu em 85% com os períodos de La Niña e a maior incidência de eventos de seca severa e intensa ocorreu na década de 1943 a 1952. Quantoà espacialização do Índice Padronizado de Precipitação, nas escalas 6, 12 e 24 meses, esta representou adequadamente os resultados obtidos nas sequências de períodos secos.
Due to the occurrence of drought events, the state of Rio Grande do Sul has accumulated losses in the agricultural and economic production. Despite the technological advances, agriculture still depends on climatic and weather conditions and, therefore, studies should be conducted in order to help the investigation of drought behavior in various regions. An important step in the understanding of drought events is the use of indexes, which survey the situation, according to an intensity scale, which aims to give an overview of the water behavior in the region. Thus, this study aims to identify and characterize drought behavior by using meteorological indexes, at different time scales for 40 seasons, consisting of a series of rainfall data from 1913 to 2002, located in the state of Rio Grande do Sul, obtained from the database of the National Institute of Meteorology (INMET) and the National Water Agency (ANA). Therefore, two drought indexes were used: Standardized Precipitation Index, in the time scales of 1, 3, 6, 9, 12 and 24 months, in severe and extreme intensities, and the Moreno Index, a quarterly and half-yearly scale, in intense to severe intensities, as well as the count of the total number and sequence analysis of dry days. For data filling of daily precipitation series, the stochastic model was used applying the Markov chain from two states. The results indicated that for the Moreno Index, the quarterly level, compared to the half-yearly scale, showed a higher concentration of drought events. For the Standardized Precipitation Index, the main sequences of dry months were found in extreme intensity; the higher incidence of severe drought events coincided in 85% with periods of La Niña and the higher incidence of severe and intense drought events occurred from 1943 to 1952. As for the spatial distribution of the Standardized Precipitation Index, in the scales 6, 12 and 24 months, it adequately represented the results obtained in the sequences of dry periods.

Meteorological drought indices are commonly calculated from climatic stations that have long-term historical data and then converted to a regular grid using spatial interpolation methods. The gridded drought indices are mapped to aid decision making by policy makers and the general public. This study analyzes the spatial performance of interpolation methods for meteorological drought indices in the United States based on data from the Co-operative Observer Network (COOP) and United States Historical Climatology Network (USHCN) for different months, climatic regions and years. An error analysis was performed using cross-validation and the results were compared for the 9 climate regions that comprise the United States. Errors are generally higher in regions and months dominated by convective precipitation. Errors are also higher in regions like the western United States that are dominated by mountainous terrain. Higher errors are consistently observed in the southeastern U.S. especially in Florida. Interpolation errors are generally higher in the summer than winter. The accuracy of different drought indices was also compared. The Standardized Precipitation and Evapotranspiration Index (SPEI) tends to have lower errors than Standardized Precipitation Index (SPI) in seasons with significant convective precipitation. This is likely because SPEI uses both precipitation and temperature data in its calculation, whereas SPI is based solely on precipitation. There are also variations in interpolation accuracy based on the network that is used. In general, COOP is more accurate than USHCN because the COOP network has a higher density of stations. USHCN is a subset of the COOP network that is comprised of high quality stations that have a long and complete record. However the difference in accuracy is not as significant as the difference in spatial density between the two networks. For multiscalar SPI, USHCN performs better than COOP because the stations tend to have a longer record. The ordinary kriging method (with optimal function fitting) performed better than Inverse Distance Weighted (IDW) methods (power parameters 2.0 and 2.5) in all cases and therefore it is recommended for interpolating drought indices. However, ordinary kriging only provided a statistically significant improvement in accuracy for the Palmer Drought Severity Index (PDSI) with the COOP network. Therefore it can be concluded that IDW is a reasonable method for interpolating drought indices, but optimal ordinary kriging provides some improvement in accuracy. The most significant factor affecting the spatial accuracy of drought indices is seasonality (precipitation climatology) and this holds true for almost all the regions of U.S. for 1-month SPI and SPEI. The high-quality USHCN network gives better interpolation accuracy with 6-, 9- and 12-month SPI and variation in errors amongst the different SPI time scales is minimal. The difference between networks is also significant for PDSI. Although the absolute magnitude of the differences between interpolation with COOP and USHCN are small, the accuracy of interpolation with COOP is much more spatially variable than with USHCN.