Study on drought events in China based on time-varying nested Archimedean-copula function

Zhao, Ziyang; Wang, Hongrui; Shi, Qiuyang; Wang, Cheng

doi:10.2166/ws.2021.233

Cited by 2 publications

(1 citation statement)

References 64 publications

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“…In addition, high-dimensional copulas can be used in the same analysis by making the ENSO or IOD index as one of the edges of the copula. This means that the joint distribution model used is no longer divided based on ENSO or IOD categories, but the joint distribution model that is formed can assess the behavior of climate indicators based on the movement of the ENSO or IOD index using tri-variate copulas or more, such as nested Archimedean copula (Zhao et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

NURDIATI¹,

NAJIB²,

THALIB³

2022

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El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can affect the increase in rainfall intensity and the number of dry days, also known as dry spells that can cause drought and increase the potential for forest fires. This study examines the effect of ENSO and IOD conditions on the joint distribution of the number of dry days and total precipitation in a fire-prone area in southern Sumatra, Indonesia. The joint distribution is constructed using rotated copulas from several families, including Gaussian, student's t, Clayton, Gumbel, Frank, Joe, Galambos, BB1, BB6, BB7, and BB8. Fire-prone areas are defined using k-mean clustering, while the copula parameters are estimated using the inference of function for margins (IFM) method. Based on the peak of joint probability density functions (PDFs), ENSO and IOD conditions had a significant effect in the dry season but had no significant effect in the rainy season. The peak of joint PDFs is getting to the dry-dry conditions when the ENSO and IOD indexes increase in the dry season. However, based on coincidence probability, ENSO conditions still influence the joint distribution between the number of dry days and total precipitation during the rainy season but not with IOD conditions. The lower the ENSO index, the higher the probability of wet conditions co-occurring in the number of dry days and total precipitation. Meanwhile, ENSO and IOD conditions significantly affect the coincidence probability between the number of dry days and total precipitation. Moderate-Strong El Niño has the most considerable coincidence probability of 68.5%, followed by Positive IOD with 62.6%. The two conditions had similar effects on the joint distribution of the number of dry days and total precipitation. Moreover, the association between the number of dry days and the total precipitation was stronger in the dry season than in the rainy season.

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Section: Discussionmentioning

confidence: 99%

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

NURDIATI¹,

NAJIB²,

THALIB³

2022

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An assessment methodology for drought severity and vulnerability using precipitation-based indices for the arid, semi-arid and humid districts of Tamil Nadu, India

Natarajan¹,

Vasudevan²,

Raja³

et al. 2022

Water Supply

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As the short and long-term impacts of climate change are becoming more visible at smaller regional scales, frequent occurrence (absence) of erratic precipitation as well as water scarcity issues can be identified as reliable indicators for predicting meteorological droughts. A supervised declaration of meteorological drought based on available precipitation data requires an understanding of reliability and consistency of drought indices for appropriate severity classification. An attempt has been made in this study to critically evaluate the performance of six popular drought indices namely, Standardized Precipitation Index (SPI), China Z Index (CZI), Modified China Z Index (MCZI), Deciles Index (DI), Rainfall Anomaly Index (RAI), and Z-Score Index (ZSI) for four districts in Tamil Nadu falling under arid (Karur), semi-arid (Cuddalore), dry sub-humid (Kanyakumari) and moist sub-humid (Coimbatore) conditions based on 120 years of precipitation records. Results showed that the SPI and CZI provided similar quantification of drought events (about 18% of the total months) irrespective of their climatic considerations while ZSI and RAI resulted in overestimation of drought severity (about 30–47%). Based on the classification strategy adopted for the selected indices, a framework for drought vulnerability assessment is proposed in conjunction with the estimated drought severity classifications.

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Study on drought events in China based on time-varying nested Archimedean-copula function

Cited by 2 publications

References 64 publications

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

An assessment methodology for drought severity and vulnerability using precipitation-based indices for the arid, semi-arid and humid districts of Tamil Nadu, India

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