Development of maximum relevant prior feature ensemble (MRPFE) index to characterize future drought using global climate models DOI Creative Commons

Atta Gul,

Sadia Qamar,

Mahrukh Yousaf

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июль 9, 2024

Abstract Drought is one of the foremost outcomes global warming and climate change. It a serious threat to humans other living beings. To reduce adverse impact drought, mitigation strategies as well sound projections extreme events are essential. This research aims strengthen robustness anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop new index, named Maximum Relevant Prior Feature Ensemble index that based on newly proposed weighting scheme, called weighted ensemble (WE). application, study considers 32 randomly scattered grid points within Tibetan Plateau region 18 GCMs Coupled Model Intercomparison Project Phase 6 (CMIP6) precipitation. study, comparative inferences WE scheme made with traditional simple model averaging (SMA). investigate trend long-term probability various classes, employs Markov chain steady states probability, Mann–Kendall test, Sen’s Slope estimator. The twofold. Firstly, inference shows has greater efficiency than SMA conflate GCMs. Secondly, indicates projected experience “moderate (MD)” in century.

Язык: Английский

A novel regional forecastable multiscalar standardized drought index (RFMSDI) for regional drought monitoring and assessment DOI Creative Commons

Aamina Batool,

Veysi Kartal, Zulfiqar Ali

и другие.

Agricultural Water Management, Год журнала: 2025, Номер 308, С. 109289 - 109289

Опубликована: Янв. 16, 2025

Язык: Английский

Процитировано

0
Development of Trivariate Multiscalar–Standardized Drought Index (TMSDI) for assessing drought characteristics DOI

Aamina Batool,

Veysi Kartal, Zulfiqar Ali

и другие.

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(3)

Опубликована: Фев. 11, 2025

Язык: Английский

Процитировано

0
A New Hybrid Weighted Regional Drought Index to Improve Regional Drought Assessment DOI

Alina Mukhtar,

Aamina Batool,

Zulfiqar Ali

и другие.

Water Resources Management, Год журнала: 2024, Номер 38(14), С. 5541 - 5558

Опубликована: Июль 5, 2024

Язык: Английский

Процитировано

1
Development of maximum relevant prior feature ensemble (MRPFE) index to characterize future drought using global climate models DOI Creative Commons

Atta Gul,

Sadia Qamar,

Mahrukh Yousaf

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июль 9, 2024

Abstract Drought is one of the foremost outcomes global warming and climate change. It a serious threat to humans other living beings. To reduce adverse impact drought, mitigation strategies as well sound projections extreme events are essential. This research aims strengthen robustness anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop new index, named Maximum Relevant Prior Feature Ensemble index that based on newly proposed weighting scheme, called weighted ensemble (WE). application, study considers 32 randomly scattered grid points within Tibetan Plateau region 18 GCMs Coupled Model Intercomparison Project Phase 6 (CMIP6) precipitation. study, comparative inferences WE scheme made with traditional simple model averaging (SMA). investigate trend long-term probability various classes, employs Markov chain steady states probability, Mann–Kendall test, Sen’s Slope estimator. The twofold. Firstly, inference shows has greater efficiency than SMA conflate GCMs. Secondly, indicates projected experience “moderate (MD)” in century.

Язык: Английский

Процитировано

1