scholarly journals Caracterização de eventos extremos e de suas causas climáticas com base no Índice Padronizado de Precipitação Para o Leste do Nordeste

2020 ◽  
Vol 13 (2) ◽  
pp. 449
Author(s):  
Djane Fonseca Da Silva ◽  
Maria José DA SILVA LIMA ◽  
PEDRO FERNANDES DE SOUZA NETO ◽  
Heliofábio Barros Gomes ◽  
Fabrício Daniel Dos Santos Silva ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Sunspot Cycle ◽  
Extreme Rainfall ◽  
Temporal Variations ◽  
Precipitation Index ◽  
Spi Index ◽  
Weather Events ◽  
Index Rainfall ◽  
Rain Events ◽  
The Standardized Precipitation Index

Os eventos climáticos extremos demonstram um papel significativo das sociedades, seja por sua intensidade, pela frequência de ocorrência ou pela vulnerabilidade socioambiental. Objetiva-se classificar e quantificar as precipitações na porção leste da região Nordeste (NE) do Brasil através do índice SPI, como também detectar maiores déficits e/ou excesso de precipitação. O Standardized Precipitation Index (SPI) foi utilizado para quantificar déficits de precipitação e identificar eventos secos e chuvosos em diferentes escalas temporais, auxiliando no monitoramento da sua dinâmica temporal. No cálculo do SPI foi utilizado a distribuição gama, e estimados os limites de precipitação que representam a cada categoria do índice. Foram utilizados dados pluviométricos das capitais dos estados que compõem no leste do Nordeste do Brasil, no período de 1961 a 2014 provenientes da Agência Nacional das Águas (ANA). A análise de Ondeletas foi utilizada com objetivo de identificar ciclos de extremos pluviométricos e de suas causas através das escalas temporais detectadas em séries de precipitação para as capitais do leste do Nordeste do Brasil. Os resultados mostraram que as ocorrências de secas foram as maiores em todas as cidades, todavia na categoria extrema os eventos chuvosos revelaram-se mais frequentes. Os anos normais foram os mais persistentes em todas cidades analisadas. Recife apresentou máximas ocorrências de eventos chuvosos. Os eventos com intensidade extrema, seja chuvoso ou seco, ocorreram em boa parte da série em anos de ENOS. O SPI revelou-se uma excelente ferramenta na detecção e no monitoramento de seca/chuvas na região analisada. A presença de escalas temporais relacionadas com eventos ENOS, Dipolo do Atlântico, ciclo de manchas solares e Oscilação Decadal do Pacífico foram identificadas em todas as capitais do leste do NEB.  Characterization of Drought Events Based on the Standardized of Precipitation Index for the East NortheastA B S T R A C TExtreme weather events demonstrate a significant role for societies, whether by their intensity, frequency of occurrence or socio-environmental vulnerability. Objective-classify and quantify as precipitation in the eastern portion of the Northeast (NE) of Brazil through the SPI index, as well as detect larger deficits and / or excess occurrence. The Standardized Precipitation Index (SPI) was used to quantify use deficits and to identify dry and rainy events in different temporal variations, helping to monitor their temporal utilization. No SPI calculations were used for gamma distribution, and estimated capture limits representing each category of the index. Rainfall data were used from the capitals of the states that make up the eastern Northeast of Brazil, with no period from 1961 to 2014, Registration of the National Water Agency (ANA). A wave analysis was used to identify extreme rainfall cycles and their causes caused by temporary variations detected in monitoring series for the eastern capitals of Brazil. The results shown as drought occurrences were the highest in all cities, however in the extreme category of rain events most frequently revealed. The normal years were the most persistent in all cities analyzed. Recife presents maximum occurrences of rain events. Extreme intensity events, whether rainy or dry, occur in much of the series in ENSO years. The SPI revealed an excellent tool for detection and monitoring of drought / gloves in the analyzed region. The presence of temporary variations related to ENOS, Atlantic Dipole, sunspot cycle and Pacific Oscillation events are identified in all eastern NEB capitals.Keywords: SPI; extreme rainfall; drought; Wavelet analysis.

scholarly journals The Standardized Precipitation Index (SPI) in identifying extreme rainfall and droughts in the Paraguaçu River Basin (BA)

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Francisco de Assis Salviano de Sousa ◽  
Maria José Herculano Macedo ◽  
Roni Valter de Souza Guedes ◽  
Vicente de Paulo Rodrigues da Silva
Keyword(s):  
River Basin ◽  
Standardized Precipitation Index ◽  
Extreme Rainfall ◽  
Precipitation Index ◽  
The Standardized Precipitation Index

scholarly journals COMBINATION OF METEOROLOGICAL INDICES AND SATELLITE DATA FOR DROUGHT MONITORING IN TWO DIFFERENT ENVIRONMENTS IN IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 197-200
Author(s):  
M. Behifar ◽  
A. A. Kakroodi ◽  
M. Kiavarz ◽  
F. Amiraslani
Keyword(s):  
Satellite Data ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Drought Monitoring ◽  
Spatial Characteristic ◽  
Drought Indices ◽  
Precipitation Data ◽  
Spi Index ◽  
The Standardized Precipitation Index

Abstract. The main problem using meteorological drought indices include inappropriate distribution of meteorological stations. Satellite data have reliable spatial and temporal resolution and provide valuable information used in many different applications. The Standardized precipitation index has several advantages. The SPI is based on rainfall data alone and has a variable time scale and is thus conducive to describing drought conditions for different application.This study aims to calculate SPI using satellite precipitation data and compare the results with traditional methods. To do this, satellite-based precipitation data were assessed against station data and then the standardized precipitation index was calculated. The results have indicated that satellite-based SPI could illustrate drought spatial characteristic more accurate than station-based index. Also, the standardized property of the SPI index allows comparisons between different locations, which is one of the remote sensing drought indices limitations.

scholarly journals Temporal and Spatial Interpolation of the Standardized Precipitation Index for Computational Efficiency in the Dynamic Drought Index Tool

2015 ◽  
Vol 54 (4) ◽  
pp. 795-810 ◽  
Author(s):  
Arthur T. DeGaetano ◽  
Brian N. Belcher ◽  
William Noon
Keyword(s):  
Gamma Distribution ◽  
Computational Efficiency ◽  
Spatial Interpolation ◽  
Large Scale ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Spi Index ◽  
Fixed Base ◽  
Distribution Parameters ◽  
The Standardized Precipitation Index

AbstractThe feasibility of interpolating gamma-distribution parameters between different precipitation accumulation intervals (durations) is statistically evaluated. The interpolation of these parameters for a specific accumulation interval, but ending on different dates, is similarly assessed. Such interpolation increases the computational efficiency of drought-monitoring tools that require calculation of the standardized precipitation index (SPI) for any user-specified accumulation period on any given day. Spatial interpolation of the distribution parameters is also assessed. Given a 60-yr period of record, few statistically significant differences were found between gamma-distribution percentiles interpolated between fixed base durations and those computed directly. Shorter interpolation intervals (generally 30 days) were required for the shortest (e.g., 30 days) durations, whereas interpolation over periods of as long as 180 days could be used for the longest (between 360 and 720 days) durations. Interpolating the distribution parameters to different ending dates on the basis of those computed for the end of each month was also appropriate. The spatial interpolation of gamma-distribution parameters, although viable in practice for monitoring large-scale drought conditions, was associated with larger SPI differences than was the spatial interpolation of the SPI index itself or the interpolation of historical precipitation and the subsequent calculation of gamma-distribution parameters on the basis of these values.

scholarly journals Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin

2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno
Keyword(s):  
Time Scales ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Long Time ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Different Time Scales

Abstract. At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the longer (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to longer time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations.

scholarly journals Seasonal forecasts of droughts in African basins using the Standardized Precipitation Index

2013 ◽  
Vol 17 (6) ◽  
pp. 2359-2373 ◽  
Author(s):  
E. Dutra ◽  
F. Di Giuseppe ◽  
F. Wetterhall ◽  
F. Pappenberger
Keyword(s):  
Real Time ◽  
Lead Time ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Seasonal Forecasting ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Blue Nile ◽  
Forecasting System ◽  
The Standardized Precipitation Index

Abstract. Vast parts of Africa rely on the rainy season for livestock and agriculture. Droughts can have a severe impact in these areas, which often have a very low resilience and limited capabilities to mitigate drought impacts. This paper assesses the predictive capabilities of an integrated drought monitoring and seasonal forecasting system (up to 5 months lead time) based on the Standardized Precipitation Index (SPI). The system is constructed by extending near-real-time monthly precipitation fields (ECMWF ERA-Interim reanalysis and the Climate Anomaly Monitoring System–Outgoing Longwave Radiation Precipitation Index, CAMS-OPI) with monthly forecasted fields as provided by the ECMWF seasonal forecasting system. The forecasts were then evaluated over four basins in Africa: the Blue Nile, Limpopo, Upper Niger, and Upper Zambezi. There are significant differences in the quality of the precipitation between the datasets depending on the catchments, and a general statement regarding the best product is difficult to make. The generally low number of rain gauges and their decrease in the recent years limits the verification and monitoring of droughts in the different basins, reinforcing the need for a strong investment on climate monitoring. All the datasets show similar spatial and temporal patterns in southern and north-western Africa, while there is a low correlation in the equatorial area, which makes it difficult to define ground truth and choose an adequate product for monitoring. The seasonal forecasts have a higher reliability and skill in the Blue Nile, Limpopo and Upper Niger in comparison with the Zambezi. This skill and reliability depend strongly on the SPI timescale, and longer timescales have more skill. The ECMWF seasonal forecasts have predictive skill which is higher than using climatology for most regions. In regions where no reliable near-real-time data is available, the seasonal forecast can be used for monitoring (first month of forecast). Furthermore, poor-quality precipitation monitoring products can reduce the potential skill of SPI seasonal forecasts in 2 to 4 months lead time.

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