Analysis of hydrological drought characteristics using copula function approach

Vaziri, Hamidreza; Karami, Hojat; Mousavi, Sayed‐Farhad; Hadiani, M O

doi:10.1007/s10333-017-0626-7

Cited by 12 publications

(3 citation statements)

References 22 publications

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“…Drought characteristics may have different marginal distribution functions, the most suitable tool for achieving the joint behavior of the drought characteristics in multivariate copula functions. Moreover, the bene t of using Copula functions is the possibility of using different univariate marginal distributions (Vaziri et al 2018). Copula functions as a multivariate analysis method are widely used to analyze the functional structure of drought characteristics (Chen et al 2013;Hao et al 2017;Mirakbari et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

Yisehak

Mesfin

Girma

et al. 2022

Theor Appl Climatol

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Meteorological drought is a climate-related natural disaster. It indicates a shortage of precipitation over a long period, usually for a season or a year. This study was initiated to analyze meteorological drought using copula theory. Long-year (1982Long-year ( -2020 rainfall and soil moisture data were used to analyze standardized precipitation index (SPI) and standardized soil moisture index (SSI), respectively. The best-t copula family was selected to construct the joint probability distribution (JPD) of SPI and SSI. Multivariate standardized drought index (MSDI) at 3-, 6-, and 12-month timescales were analyzed using the MSDI toolbox. The non-parametric Mann-Kendall (M-K) statistical test was used for trend detection. The result shows the newly developed MSDI captured all extreme drought events with the highest severity (-3.21) that occurred during the observation period compared to SPI and SSI. MSDI shows the famine caused by the drought of 1984 and 1985 remains well known to the world, with the drought duration and severity of 10 months and 18.7 years, respectively and its joint return period was 33.0 years. The result of the M-K and Sen's Slope estimator statistical tests shows a positive trend for all drought timescales in the basin. The extreme drought captured by the MSDI most frequently occurred in the basin. This implicated that meteorological drought analysis using multiple indices is better than a single index. The results of this study will help devise drought adaptation and mitigation strategies in the basin and beyond.

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Section: Introductionmentioning

confidence: 99%

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

Yisehak

Mesfin

Girma

et al. 2022

Theor Appl Climatol

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“…Drought characteristics may have different marginal distribution functions, the most suitable tool for achieving the joint behavior of the drought characteristics in multivariate copula functions. Moreover, the bene t of using Copula functions is the possibility of using different univariate marginal distributions (Vaziri et al 2018). Copula functions as a Loading [MathJax]/jax/output/CommonHTML/jax.js multivariate analysis method are widely used to analyze the functional structure of drought characteristics (Chen et al 2013;Hao et al 2017;Mirakbari et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

Yisehak

Shiferaw

Girma

et al. 2021

Preprint

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Meteorological drought is a climate-related natural disaster. It indicates a shortage of precipitation over a long period, usually for a season or a year. This study was initiated to analyze meteorological drought using copula theory. Long-year (1982–2020) rainfall and soil moisture data were used to analyze standardized precipitation index (SPI) and standardized soil moisture index (SSI), respectively. The best-fit copula family was selected to construct the joint probability distribution (JPD) of SPI and SSI. Multivariate standardized drought index (MSDI) at 3-, 6-, and 12-month timescales were analyzed using the MSDI toolbox. The non-parametric Mann-Kendall (M-K) statistical test was used for trend detection. The result shows the newly developed MSDI captured all extreme drought events with the highest severity (-3.21) that occurred during the observation period compared to SPI and SSI. MSDI shows the famine caused by the drought of 1984 and 1985 remains well known to the world, with the drought duration and severity of 10 months and 18.7 years, respectively and its joint return period was 33.0 years. The result of the M-K and Sen’s Slope estimator statistical tests shows a positive trend for all drought timescales in the basin. The extreme drought captured by the MSDI most frequently occurred in the basin. This implicated that meteorological drought analysis using multiple indices is better than a single index. The results of this study will help devise drought adaptation and mitigation strategies in the basin and beyond.

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“…Copulas were applied in hydrology to describe the observed dependence between drought severity and duration (Vaziri et al ., 2018) or in climatology for the joint distribution of temperature and precipitation (Lazoglou and Anagnostopoulou, 2019). The identified dependence, described by a copula family with specific appropriate parameters, could be used for the bias correction of future climate projections.…”

Section: Introductionmentioning

confidence: 99%

TIN‐Copula bias‐correction method for model‐derived maximum temperature in the MENA region

Lazoglou

Zittis

Hadjinicolaou

et al. 2021

Intl Journal of Climatology

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Global and regional climate models' prediction accuracy is limited, often with systematic biases between the model output and observed conditions. The present research aims to minimize the biases between the maximum temperature simulated by a global (HadGEM3) and a regional (WRF) climate model for the period of 2006–2014, based on the ERA5 reanalysis data, used as a proxy for observations (calibration period 1981–2000). For the bias correction, a new approach with the TIN‐Copula method (combination of Triangular Irregular Networks‐TINs and Copulas), suitable for gridded datasets is used. The methodology applies TINs to define the grids to which the corrections are made, and copulas for analysing the dependence between the reanalysis and simulated data during the calibration period. The dependence structure is then used for the bias adjustment. Our methodology is applied to the Middle East and North Africa MENA‐CORDEX domain, where extreme heat conditions prevail, which are projected to accelerate during the 21st century. Besides to the entire area, a detailed analysis was performed for six subregions. Our results indicate that the maximum temperature output of both models diverges from the ERA5 reanalysis, especially during summer. In several subregions and seasons, discrepancies are highest for the HadGEM3 model, which has a much coarser resolution than WRF. The effectiveness of the TIN‐Copula method was tested spatially, temporally and based on two relevant climate indices [daily maximum temperature (TXx) and warm spell duration index (WSDI]), showing that it minimizes model biases.

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Analysis of hydrological drought characteristics using copula function approach

Cited by 12 publications

References 22 publications

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

TIN‐Copula bias‐correction method for model‐derived maximum temperature in the MENA region

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