scholarly journals Classificação de Eventos Extremos de Precipitação em Múltiplas Escalas de Tempo em Belém-PA: Utilizando o Índice de Precipitação Normalizada (Classification of Extreme Precipitation Events in Multiple Time Scales in Belém, PA: Using the Standardized ...)

2014 ◽  
Vol 7 (4) ◽  
pp. 628
Author(s):  
Sérgio Rodrigo Quadros dos Santos ◽  
Celia Campos Braga ◽  
Ana Paula Paes dos Santos ◽  
Thamiris Luiza De Oliveira Brandão Campos ◽  
José Ivaldo Barbosa de Brito
Keyword(s):  
Time Scales ◽  
Extreme Event ◽  
Standardized Precipitation Index ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Extreme Precipitation Events ◽  
The Standardized Precipitation Index ◽  
The City

O Índice de Precipitação Normalizada (SPI) é utilizado para quantificar o déficit e/ou excesso de precipitação nas múltiplas escalas de tempo. Ele tem se mostrado bastante útil no monitoramento da precipitação, principalmente pela sua flexibilidade, simplicidade de cálculo e interpretação. Desta forma este estudo tem como objetivo quantificar os eventos extremos secos e chuvosos na cidade de Belém-PA nas escalas de tempo de 3, 6 e 12 meses por meio do SPI. Para isto, utilizaram-se dados mensais de precipitação provenientes da estação meteorológicas de superfície do INMET no período de 1980-2011. Os resultados mostraram que a escala de tempo do SPI é inversamente proporcional à frequência dos eventos de chuva e seca. Os SPIs 3,6 e 12 mostraram mais eventos secos do que chuvosos para a cidade e a maioria dos eventos de chuva e seca estavam associados, principalmente, ao fenômeno ENOS. ABSTRACT The Standardized Precipitation Index (SPI) is used to quantify the deficit/ excess rainfall at multiple time scales. It has been very useful in monitoring of precipitation, mainly because of its flexibility, ease of calculation and interpretation. Thus this study aims to quantify the extreme wet and dry events in the city of Belém-PA in time scales of 3, 6 and 12 months by SPI. For this, we used monthly precipitation data from meteorological station at the INMET in the period 1980-2011. The results show that the timescale of the SPI is inversely proportional to the frequency of rain and dry events. The SPIs 3.6 and 12 showed driest events that rainy events to the city and most of the rainfall and drought events were associated, mainly, with the ENSO phenomenon. Key Words: Belem; SPI; Extreme Event.   

scholarly journals Climate change effects on drought severity

2008 ◽  
Vol 17 ◽  
pp. 23-29 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades ◽  
J. Tzabiras
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Geographical Information ◽  
Multiple Time Scales ◽  
Drought Severity ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Climate Change Effects

Abstract. This paper evaluates climate change effects on drought severity in the region of Thessaly, Greece. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for the division of Thessaly region to twelve hydrological homogeneous areas based on their geomorphology. Mean monthly precipitation values from 50 precipitation stations of Thessaly for the hydrological period October 1960–September 1990 were used for the estimation of mean areal precipitation. These precipitation timeseries have been used for the estimation of Standardized Precipitation Index (SPI) for multiple time scales (1-, 3-, 6-, 9-, and 12-months) for each sub-basin or area. The outputs of Global Circulation Model CGCM2 were applied for two socioeconomic scenarios, namely, SRES A2 and SRES B2 for the assessment of climate change impact on droughts. The GCM outputs were downscaled to the region of Thessaly using a statistical methodology to estimate precipitation time series for two future periods 2020–2050 and 2070–2100. A method has been proposed for the estimation of annual cumulative drought severity-time scale-frequency curves. These curves integrate the drought severity and frequency for various types of drought. The SPI timeseries and annual weighted cumulative drought severity were estimated and compared with the respective timeseries and values of the historical period 1960–1990. The results showed that the annual drought severity is increased for all hydrological areas and SPI time scales, with the socioeconomic scenario SRES A2 being the most extreme.

scholarly journals The Evaporative Demand Drought Index. Part II: CONUS-Wide Assessment against Common Drought Indicators

2016 ◽  
Vol 17 (6) ◽  
pp. 1763-1779 ◽  
Author(s):  
Daniel J. McEvoy ◽  
Justin L. Huntington ◽  
Michael T. Hobbins ◽  
Andrew Wood ◽  
Charles Morton ◽  
...  
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Time Scales ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Stress Index ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Evaporative Demand ◽  
Hydrologic Drought

Abstract Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought; however, other climatic factors such as solar radiation, wind speed, and humidity can be important drivers in the depletion of soil moisture and evolution and persistence of drought. This work assesses the Evaporative Demand Drought Index (EDDI) at multiple time scales for several hydroclimates as the second part of a two-part study. EDDI and individual evaporative demand components were examined as they relate to the dynamic evolution of flash drought over the central United States, characterization of hydrologic drought over the western United States, and comparison to commonly used drought metrics of the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI), and the evaporative stress index (ESI). Two main advantages of EDDI over other drought indices are that it is independent of precipitation (similar to ESI) and it can be decomposed to identify the role individual evaporative drivers have on drought onset and persistence. At short time scales, spatial distributions and time series results illustrate that EDDI often indicates drought onset well in advance of the USDM, SPI, and SSI. Results illustrate the benefits of physically based evaporative demand estimates and demonstrate EDDI’s utility and effectiveness in an easy-to-implement agricultural early warning and long-term hydrologic drought–monitoring tool with potential applications in seasonal forecasting and fire-weather monitoring.

scholarly journals European drought trends

2015 ◽  
Vol 369 ◽  
pp. 75-79 ◽  
Author(s):  
L. Gudmundsson ◽  
S. I. Seneviratne
Keyword(s):  
Time Scales ◽  
Multiple Testing ◽  
Standardized Precipitation Index ◽  
Multiple Time Scales ◽  
Climate Projections ◽  
Multiple Time ◽  
Drought Frequency ◽  
The Past ◽  
The North ◽  
Recent Climate

Abstract. Recent climate projections suggest pronounced changes in European drought frequency. In the north, increased precipitation volumes are likely to reduce drought occurrence, whereas more frequent droughts are expected for southern Europe. To assess whether this pattern of changes in drought frequency can already be identified for the past decades, we analyse trends in a recently developed pan-European drought climatology that is based on the Standardized Precipitation Index (SPI). The index is derived on multiple time scales, ranging from 1 to 36 months, which allows the assessment of trends in both short term and multi-year droughts. Trends are quantified using the Theil-Sen trend estimator combined with an extension of the Mann–Kendal test (p < 0.05) that accounts for serial correlation. Field significance is assessed on the basis of techniques that control the false discovery rate in a multiple testing setting. The trend analysis indicates that changes in drought frequency are more pronounced on time scales of one year and longer. The analysis also reveals that there has been a tendency for decreased drought frequency in northern Europe in the past decades, whereas droughts have likely become more frequent in selected southern regions.

scholarly journals Assessment of the influence of bias correction on meteorological drought projections for Poland

2015 ◽  
Vol 12 (10) ◽  
pp. 10331-10377 ◽  
Author(s):  
M. Osuch ◽  
R. J. Romanowicz ◽  
D. Lawrence ◽  
W. K. Wong
Keyword(s):  
Time Scales ◽  
Bias Correction ◽  
Climate Model ◽  
Precipitation Index ◽  
Future Climate Change ◽  
Multiple Time Scales ◽  
Climate Projections ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Standard Precipitation Index

Abstract. Possible future climate change effects on drought severity in Poland are estimated for six ENSEMBLE climate projections using the Standard Precipitation Index (SPI). The time series of precipitation represent six different RCM/GCM run under the A1B SRES scenario for the period 1971–2099. Monthly precipitation values were used to estimate the Standard Precipitation Index (SPI) for multiple time scales (1, 3, 6, 12 and 24 months) for a spatial resolution of 25 km × 25 km for the whole country. Trends in SPI were analysed using a Mann–Kendall test with Sen's slope estimator for each 25 km × 25 km grid cell for each RCM/GCM projection and timescale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded E-OBS precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the time scale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarise the mechanisms underlying the influence of bias correction on trends using a simple example of a linear bias correction procedure. In the case of precipitation the bias correction by QM does not change the direction of changes but can change the slope of trend. We also have noticed that the results for the same GCM, with differing RCMs, are characterized by similar pattern of changes, although this behaviour is not seen at all time scales and seasons.

scholarly journals Probabilistic analysis of drought spatiotemporal characteristics inThessaly region, Greece

2004 ◽  
Vol 4 (5/6) ◽  
pp. 719-731 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades
Keyword(s):  
Standardized Precipitation Index ◽  
Multiple Time Scales ◽  
Drought Severity ◽  
Severe Drought ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Spatial Characteristics ◽  
Sustainable Water Resources Management ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics

Abstract. The temporal and spatial characteristics of meteorological drought are investigated to provide a framework for sustainable water resources management in the region of Thessaly, Greece. Thessaly is the most intensely cultivated and productive agricultural plain region in Greece. Thessaly's total area is about 13700 km2 and it is surrounded by mountains and traversed by Pinios River. Using the Standardized Precipitation Index (SPI) as an indicator of drought severity, the characteristics of droughts are examined. Thessaly was divided into 212 grid-cells of 8 x 8 km and monthly precipitation data for the period 1960–1993 from 50 meteorological stations were used for global interpolation of precipitation using spatial co-ordinates and elevation data. Drought severity was assessed from the estimated gridded SPI values at multiple time scales. Firstly, the temporal and spatial characteristics of droughts were analyzed and then, Drought Severity – Areal extent – Frequency (SAF) annual and monthly curves were developed. The analysis indicated that moderate and severe droughts are common in Thessaly region. Using the SAF curves, the return period of selected severe drought events was assessed.

scholarly journals Modeling a Drought Index Using a Nonparametric Approach

2017 ◽  
Vol 19 (1) ◽  
pp. 58-68 ◽  
Keyword(s):  
Time Scales ◽  
Gamma Distribution ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Kernel Density ◽  
Density Estimator ◽  
Monthly Precipitation ◽  
Nonparametric Approach ◽  
The Standardized Precipitation Index ◽  
Drought Classes

<p>Alternatively, to other studies that used parametric distributions (e.g. Gamma) in the estimation of the Standardized Precipitation Index (SPI), this study aims to apply a nonparametric method based on Kernel Density Estimator (KDE) for calculating the SPI. Results of the proposed method were compared with the ones from the most widely used parametric distribution, using a long dataset of monthly precipitation of four meteorological stations in Iran (including Bushehr, Mashhad, Tehran and Esfahan) over a period of 107 water years (1895-2002). The capability of KDE-based SPI was compared with the Gamma-based SPI at four-time scales of 3, 6, 9 and 12 months. The frequencies of the drought classes of SPI were calculated and compared with corresponding expected frequencies. The results revealed that the KDE is more consistent with the expected values of the SPI drought/wet classes frequencies (especially in the extreme classes) at all stations as well as at the four-time scales, compared to the Gamma distribution. The greatest deviation from the expected frequencies for KDE and Gamma distribution were about 10% and 150%, respectively. This study proposes a new analytical approach in modeling SPI that provides more accurate results pertaining frequency of occurrences of extreme drought events. The output of the study can be used in many fields (e.g. tourism, agriculture, insurance, etc.) that are influenced by severe droughts.</p>

scholarly journals Assessing droughts using meteorological drought indices in Victoria, Australia

2014 ◽  
Vol 46 (3) ◽  
pp. 463-476 ◽  
Author(s):  
Siti Nazahiyah Rahmat ◽  
Niranjali Jayasuriya ◽  
Muhammed Bhuiyan
Keyword(s):  
Urban Communities ◽  
Potential Evapotranspiration ◽  
Climatic Variability ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Rural And Urban ◽  
The Standardized Precipitation Index

Droughts adversely impact rural and urban communities, industry, primary production and, thus, a country's economy. Drought monitoring is directed to detecting the onset, persistence and severity of the drought. In this study, meteorological drought indices such as the Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI) and deciles were assessed to investigate how well these indices reflect drought conditions in Victoria, Australia. The Theory of Runs was also used to identify the drought deficit. The study uses 55 years (1955–2010) of monthly precipitation and reference evapotranspiration data for five selected meteorological stations in Victoria, Australia. Results show that drought characterization using SPI and RDI provides a standardized classification of severity thus exhibiting advantages over deciles. As RDI considers both rainfall and potential evapotranspiration in calculations, it could be sensitive to climatic variability. For characterizing agricultural droughts, the application of the RDI is recommended. The use of the SPI was shown to be satisfactory for assessing and monitoring meteorological droughts. The SPI was also successful in detecting the onset and the end of historical droughts for the selected events.

scholarly journals Análise de Eventos Extremos na Região Amazônica (Analysis of Extreme Events in the Amazon Region)

2013 ◽  
Vol 6 (5) ◽  
pp. 1356 ◽  
Author(s):  
Thalyta Soares dos Santos ◽  
Ana Carla Dos Santos Gomes ◽  
Maytê Duarte Leal Coutinho ◽  
Allan Rodrigues Silva ◽  
Aline Anderson de Castro
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Maximum Likelihood Method ◽  
Global Climate ◽  
Standardized Precipitation Index ◽  
Amazon Region ◽  
Likelihood Method ◽  
Monthly Precipitation ◽  
The Standardized Precipitation Index ◽  
Porto Velho

A frequência de eventos severos e extremos de seca e chuva na Amazônia foi analisada utilizando o Índice de Precipitação Normalizada (SPI) nas escalas de 6 (sazonal estação seca/chuvosa) e 12 meses (interanual). A frequência de eventos secos e chuvosos é importante para a climatologia da região, que é considerada um regulador climático global. Para isso foram selecionadas as séries climatológicas, de 1925 a 2000, de seis localidades da região Amazônica: Belém, Cuiabá, Iauretê, Manaus, Porto Velho, Taguatinga. Os SPIs, 6 e 12, que quantificam excesso ou déficit de chuva, nestas duas escalas de tempo, foram calculados a partir dos ajustes de distribuição gama, pelo método da máxima verossimilhança às médias móveis de 6 e 12 meses das precipitações mensais. Esses foram computados a partir da normalização das probabilidades gama, pelos seus respectivos desvios padrões. As séries temporais dos SPIs 6 e 12, mostram longos períodos de oscilação entre eventos secos e chuvosos. A frequência decenal de ambos SPIs indica variações entre as décadas mais chuvosas e secas nos municípios estudados. As décadas mais chuvosas e secas são periódicas para as duas escalas de tempo analisadas em todas as estações, exceto Iauretê. A B S T R A C T The frequency of severe and extremes events of drought and rainfall in the Amazon was analyzed using the Standardized Precipitation Index (SPI) in the scales of six months (dry/wet seasons) and 12 months (inter-annual). This is important for the climatology of the region, which is considered a global climate regulator. With this objective, the climatological series from 1925 to 2000 were selected for six locations in the Amazon region: Belém, Cuiabá, Iauretê, Manaus, Porto Velho and Taguatinga. With the aim of quantify the excess or deficit of rainfall in the selected time scales, the SPIs 6 and 12 were calculated using the fit of the gamma distribution by the maximum likelihood method for the moving averages 6 and 12 months of monthly precipitation. These were computed from the normalization of gamma probabilities by its standard deviation. The time series of SPIs 6 and 12, show long periods of oscillation between dry and wet events. The frequency of both SPIs indicates variations between wet and dry decades in the cities studied. Wetter and drier decades were shown to be periodic for the two time scales considered in all locations, except for Iauretê. Key-Words: SPI, Amazon, Drought, Rain

scholarly journals Systematical Evaluation of Three Gridded Daily Precipitation Products Against Rain Gauge Observations Over Central Asia

2021 ◽  
Vol 9 ◽  
Author(s):  
Tuoliewubieke Dilinuer ◽  
Junqiang Yao ◽  
Jing Chen ◽  
Yong Zhao ◽  
Weiyi Mao ◽  
...  
Keyword(s):  
Central Asia ◽  
Time Scales ◽  
Daily Precipitation ◽  
Rain Gauge ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Climatic Regions ◽  
Arid Desert ◽  
Continental Climate

Understanding the precipitation variability and extreme precipitation over arid Central Asia (CA) has largely been hampered by the lack of daily precipitation observations. The gridded precipitation datasets over CA are large discrepancies. Here, three gauge-based gridded daily precipitation products from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Global Precipitation Climatology Center (GPCC), and Climate Prediction Center Based Analysis of Global Daily Precipitation (CPC_global) were assessed and compared with 49 rain gauge daily observations precipitation (OBS) from January 1985 to December 2015 using different time-scales over CA and different climate regimes, specifically Northern CA with temperate continental climate (NCA), Southwestern CA with dry arid desert climate (SWCA), and Southeastern CA with Mediterranean continental climate (SECA). Four accuracy indices [correlation coefficient (R), Bias, root mean square error (RMSE), and relative bias (RBias)] were employed to evaluate the performance of the three products in depicting the spatiotemporal features of precipitation variation over CA at multiple time scales (including daily, monthly, seasonal, and yearly). The mean annual and daily precipitation of OBS and three gridded products exhibit the trend of a gradual precipitation decreased from SECA to NCA and SWCA. The best overall performance was obtained for APHRODITE and GPCC for daily and annual time-scale, whereas CPC shows noticeable underestimation precipitation in SECA. The monthly precipitation depicted distinct features with a bimodal pattern with a peak in March and another in December, include the SECA and SWCA regions. In contrast, precipitation was concentrated in summer with the peak in July over the NCA region. At monthly scale terms, APHRODITE was more accurate in the wet seasons (winter and spring months) in SWCA and SECA. Additionally, GPCC has fairly better capability in summer months in NCA. Considering the spatial distribution, the bias variability was largerly in mountainous areas than in the plains. Temporally, the bias largerly in the dry seasons than in the wet seasons. At the interannual variability scale, GPCC was capable of qualitatively increasing the CA (NCA and SECA) precipitation during the last 21 years, while APHRODITE underestimated the trends. The CPC overestimated the precipitation trends over all regions. This study can serve as a reference for selecting daily precipitation products with low densities of stations, complex topographies, and similar climatic regions.

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