Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa

International Journal of Climatology, Год журнала: 2021, Номер 41(15), С. 6474 - 6496

Опубликована: Май 18, 2021

Abstract This study examines the improvement in Coupled Model Intercomparison Project Phase Six (CMIP6) models against predecessor CMIP5 simulating mean and extreme precipitation over East Africa region. The compares climatology of indices simulated by CMIP with CHIRPS data set using robust statistical techniques for 1981–2005. results display varying performance general circulation (GCMs) simulation annual seasonal domain. CMIP6 multi‐model ensemble (hereafter MME) shows improved local cycle a better representation rainfall within two peaks, especially MAM relative to their predecessor. Moreover, is well captured CMIP5. CMIP6‐MME performed than CMIP5‐MME lesser biases Simple Daily Intensity Index (SDII), consecutive dry days (CDD), very heavy >20 mm (R20mm) Africa. Remarkably, most are unable simulate extremely wet (R95p). Some (e.g., NorESM2‐MM CNRM‐CM6‐1) depict reproducing observed across all analyses. OND season some (i.e., R95p, PRCPTOT), except SDII, CDD, R20mm models. Consistent other studies, both CMIP5/6 as compared individual due cancellation systematic errors Generally, depicts However, new model generation still marred uncertainty, thereby depicting unsatisfactory calls further investigation into sources persistent methodology identifying features that can accurately patterns future usage.

Язык: Английский

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Evaluation and projection of precipitation in Pakistan using the Coupled Model Intercomparison Project Phase 6 model simulations

International Journal of Climatology, Год журнала: 2022, Номер 42(13), С. 6665 - 6684

Опубликована: Март 6, 2022

Abstract This study aimed to evaluate the performance of global climate models (GCMs) from family Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulation precipitation and select best performing GCMs for future projection Pakistan under multiple shared socioeconomic pathways (SSPs). The spatiotemporal was evaluated against Climate Research Unit (CRU) data simulating annual during 1951–2014, using Taylor diagram interannual variability skill (IVS). Moreover, modified Mann–Kendall (mMK) Sen's slope estimator (SSE) tests were employed estimate significant trends period 2015–2100. Based on comprehensive ranking index (CRI), HadGEM3‐GC31‐MM model has highest distributions followed by EC‐Earth3‐Veg‐LR, CNRM‐ESM2‐1, MPI‐ESM1‐2‐HR, CNRM‐CM6‐1, MRI‐ESM2‐0, CNRM‐CM6‐1‐HR, EC‐Earth3‐Veg, MCM‐UA‐1‐0, INM‐CM5‐0, KACE‐1‐0‐G, CAMS‐CSM1‐0, HadGEM3‐GC31‐LL models. Furthermore, projections ensemble mean (BMEM) showed that region will experience a substantial increase SSP3‐7.0 SSP5‐8.5 but an indolent rise SSP1‐2.6 SSP2‐4.5 scenarios. summer precipitations exhibit statistically increasing trend relative winter season most magnitude monotonic seasonal progresses low forcing scenario (SSP1‐2.6) high (SSP5‐8.5). findings could provide benchmark selecting appropriate over scare region, like Pakistan. projected are crucial devising adaption mitigation actions towards sustainable planning water resource management, food security, disaster risk management.

Язык: Английский

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Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa

Atmosphere, Год журнала: 2021, Номер 12(4), С. 475 - 475

Опубликована: Апрель 9, 2021

This study assesses the performance of historical rainfall data from Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing spatial and temporal variability over North Africa. Datasets Climatic Research Unit (CRU) Global Precipitation Climatology Centre (GPCC) are used as proxy to observational datasets examine capability 15 CMIP6 models’ their ensemble simulating during 1951–2014. In addition, robust statistical metrics, empirical cumulative distribution function (ECDF), Taylor diagram (TD), skill score (TSS) utilized assess annual seasonal monthly domain. Results show that models satisfactorily reproduce mean climatology dry/wet months. However, some a slight over/under estimation across The overall top ranking all analyses ranging cycle simulation, trend analysis, inter-annual variability, ECDFs, metrics follows: EC-Earth3-Veg, UKESM1-0-LL, GFDL-CM4, NorESM2-LM, IPSL-CM6A-LR, GFDL-ESM4. model outperformed individual resulting TSS ratio (0.79). For future impact studies domain, it is advisable employ multi-model best performing models.

Язык: Английский

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Inter‐comparison of historical simulation and future projections of rainfall and temperature by CMIP5 and CMIP6 GCMs over Egypt

International Journal of Climatology, Год журнала: 2021, Номер 42(8), С. 4316 - 4332

Опубликована: Ноя. 29, 2021

Abstract The global climate models (GCMs) performances of the recently released Coupled Model Intercomparison Project phase 6 (CMIP6) compared to its predecessor, CMIP5, are evaluated anticipate expected changes in over Egypt. Thirteen GCMs and their multi‐model ensemble (MME) both CMIPs were used for this purpose. future projections two radiative concentration pathways (RCP 4.5 8.5) shared socio‐economic (SSP 2–4.5 5–8.5). results revealed improvement most CMIP6 replicating historical rainfall, maximum temperature (Tmax), minimum (Tmin) climatology MME that could reproduce Egypt's spatial distribution seasonal variability. However, bias CMIP5 was higher than CMIP6. uncertainties simulating variability rainfall temperatures lower CMIP5. projection using a reduction precipitation (10–26 mm) economically crucial northern region estimated (0–17 mm), 133.5 mm base period. also projected 0.74–1.63°C more rise Tmax Tmin by end century. study indicates aggravated scenarios Egypt anticipated earlier, models. Therefore, needs streamline existing adaptation mitigation measures account projections.

Язык: Английский

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Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models

Water, Год журнала: 2021, Номер 13(17), С. 2358 - 2358

Опубликована: Авг. 27, 2021

This paper presents an analysis of projected precipitation extremes over the East African region. The study employs six indices defined by Expert Team on Climate Change Detection Indices to evaluate extreme precipitation. Observed datasets and Coupled Model Intercomparison Project Phase (CMIP6) simulations are employed assess changes during two main rainfall seasons: March May (MAM) October December (OND). results show increase in consecutive dry days (CDD) decrease wet (CWD) towards end 21st century (2081–2100) relative baseline period (1995–2014) both seasons. Moreover, simple daily intensity (SDII), very (R95 p), heavy >20 mm (R20 mm), total wet-day (PRCPTOT) demonstrate significant OND compared MAM season. spatial variation for incidences shows likely intensification Uganda most parts Kenya, while a reduction is observed Tanzania may pose serious threat sustainability societal infrastructure ecosystem wellbeing. from these analyses present opportunity understand emergence events capability model outputs CMIP6 estimating changes. More studies recommended examine underlying physical features modulating occurrence relevant policies.

Язык: Английский

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Evaluation and projection of mean surface temperature using CMIP6 models over East Africa

Journal of African Earth Sciences, Год журнала: 2021, Номер 181, С. 104226 - 104226

Опубликована: Май 12, 2021

Язык: Английский

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Multi-Decadal Variability and Future Changes in Precipitation over Southern Africa

Atmosphere, Год журнала: 2021, Номер 12(6), С. 742 - 742

Опубликована: Июнь 9, 2021

The future planning and management of water resources ought to be based on climate change projections at relevant temporal spatial scales. This work uses the new regional demarcation for Southern Africa (SA) investigate spatio-temporal precipitation variability trends centennial-scale observation modeled data, datasets from sixth phase Coupled Model Intercomparison Project (CMIP6). study employs several statistical methods rank models according their simulation ability. Theil–Sen slope estimator is used assess trends, with a Student’s t-test significance test. comparison model historical data enables identification best-performing global (GCMs), which are then employed in projection analysis under two Shared Socioeconomic Pathways (SSPs): SSP2-4.5 SSP5-8.5. GCMs adequately capture annual variation but general overestimation, especially over high-elevation areas. Most fail Lesotho-Eswatini area. three SA FGOALS-g3, MPI-ESM1-2-HR NorESM2-LM. sub-regions demonstrate that cannot generalized localized studies can provide more accurate findings. Overall, wet dry seasons shows an initial increase during near western eastern SA, followed by reduction mid- far both scenarios. Madagascar expected experience decrease amount throughout twenty-first century.

Язык: Английский

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Evaluation of the CMIP6 Precipitation Simulations Over Global Land

Earth s Future, Год журнала: 2022, Номер 10(8)

Опубликована: Авг. 1, 2022

Abstract Precipitation's temporal and spatial patterns under climate change significantly impact global terrestrial ecology human social activities. Climate models are essential tools for assessing the impacts of formulating policies to address change. The evaluation results historical model simulations can represent reliability their future simulations. This study evaluated simulation capabilities 41 All‐Forcing monthly precipitation three integrated over land in Coupled Model Comparison Project Phase 6 (CMIP6). show that capability (GCMs) CMIP6 is highly variable overland around world. variability manifested two aspects: comprehensive ability each different geographical regions climatic zones world significant difference region. These GCMs generally overestimate land, with exception southeast Asia tropical rainforest (Af), where all underestimate precipitation. Some GCMS perform well regionally but poorly on scale. One example shows EC‐Earth3's best at Cwc zone, surpassing model, failed rank top 10 22 29 zones. Our highlight need select appropriate integration when conducting studies regional scales as a critical factor studying predictions.

Язык: Английский

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Comprehensive assessment of CMIP5 and CMIP6 models in simulating and projecting precipitation over the global land

International Journal of Climatology, Год журнала: 2022, Номер 42(13), С. 6859 - 6875

Опубликована: Март 22, 2022

Abstract The warming climate can considerably alter the Earth's water cycle and change precipitation over land. Climate models are primary tools for projecting changes evaluating impacts in various fields. This study compares from 45 Coupled Model Intercomparison Project Phase 5 (CMIP5) 49 6 (CMIP6) to observations. results reveal that CMIP6 outperform CMIP5 simulating patterns global land historical period. cumulative distribution function matching method is used correct bias outputs of selected models, multi‐model ensemble (MME) corrected then utilized under future scenarios observation‐constrained projections show there a significant increasing trend annual during 2021–2100 all four scenarios, rates 3.0, 4.23, 6.77 8.96 mm/decade RCP4.5, SSP2‐4.5, RCP8.5 SSP5‐8.5 respectively. Moreover, average projected increase by 4.9% (RCP4.5), 8.1% (RCP8.5), 4.6% (SSP2‐4.5) 10.1% (SSP5‐8.5) 2081–2100 relative 1986–2005. Increases may result more flood, causing higher flooding risk future.

Язык: Английский

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Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models

Natural Hazards, Год журнала: 2022, Номер 113(2), С. 1151 - 1176

Опубликована: Апрель 9, 2022

Язык: Английский

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