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

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

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Development of Ridge Ensemble Standardized Drought Index (RESDI) for improving drought characterization and future assessment

Environmental Monitoring and Assessment, Год журнала: 2024, Номер 196(7)

Опубликована: Июнь 13, 2024

Язык: Английский

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Improving drought monitoring using climate models with bias‐corrected under Gaussian mixture probability models

International Journal of Climatology, Год журнала: 2024, Номер unknown

Опубликована: Сен. 28, 2024

Abstract Global climate models (GCMs) are extensively used to calculate standardized drought indices. However, inaccuracies in GCM simulations and uncertainties inherent the standardization methodology limit precision of evaluations. The objective this research is remove bias GCMs for improving monitoring assessment. Consequently, article proposes a new framework index under ensemble GCMs—Multi‐Model Quantile Mapped Standardized Precipitation Index (MMQMSPI). In accordance (SPI), second stage derives by assessing feasibility parametric nonparametric during standardization. application, we 18 from Coupled Model Intercomparison Project Phase 6 (CMIP6) data precipitation across 32 grid points within Tibetan Plateau region. comparative findings reveal that integration KCGMD most suitable choice compared other best‐fitted univariate distributions both features proposed framework. research, assess implications evaluating future patterns years 2015–2100 using seven different time periods three scenarios. Temporal behavior clearly shows monthly variations pattern MMQMSPI, these differ on each scale, but drastic change can be seen over long term, i.e., extreme dry wet conditions, with higher probability all

Язык: Английский

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Spatial predictive analysis of drought duration in relation to climate change using interpolation techniques

Stochastic Environmental Research and Risk Assessment, Год журнала: 2024, Номер unknown

Опубликована: Дек. 31, 2024

Язык: Английский

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