Projected changes in extreme climate events over Africa under 1.5°C, 2.0°C and 3.0°C global warming levels based on CMIP6 projections

Atmospheric Research, Год журнала: 2023, Номер 292, С. 106872 - 106872

Опубликована: Июнь 16, 2023

Язык: Английский

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Quantifying the Added Value in the NEX-GDDP-CMIP6 Models as Compared to Native CMIP6 in Simulating Africa’s Diverse Precipitation Climatology

Earth Systems and Environment, Год журнала: 2024, Номер 8(2), С. 417 - 436

Опубликована: Апрель 13, 2024

Язык: Английский

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Future water storage changes over the Mediterranean, Middle East, and North Africa in response to global warming and stratospheric aerosol intervention

Earth System Dynamics, Год журнала: 2024, Номер 15(1), С. 91 - 108

Опубликована: Янв. 29, 2024

Abstract. Water storage plays a profound role in the lives of people across Middle East and North Africa (MENA) as it is most water-stressed region worldwide. The lands around Caspian Mediterranean seas are simulated to be very sensitive future climate warming. Available water capacity depends on hydroclimate variables such temperature precipitation that will depend socioeconomic pathways changes climate. This work explores both mean extreme terrestrial (TWS) under an unmitigated greenhouse gas (GHG) scenario (SSP5-8.5) stratospheric aerosol intervention (SAI) designed offset GHG-induced warming above 1.5 ∘C compares with historical period simulations. Both TWS projected significantly decrease SSP5-8.5 over domain, except for Arabian Peninsula, particularly wetter seas. Relative global warming, SAI partially ameliorates decreased wet regions, while has no significant effect increased drier lands. In entire domain studied, larger than pure GHG forcing, mainly due cooling and, turn, substantial evapotranspiration relative SSP5-8.5. Changes excursions reduced by SAI. Extreme scenarios throughout Iran, Iraq, but response more continental eastern hyper-arid different from neighboring dry latter case, we note reduction trend scenarios, values also showing decline compared conditions.

Язык: Английский

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Evaluation of CMIP6 historical simulations over IGAD region of Eastern Africa

Discover Environment, Год журнала: 2023, Номер 1(1)

Опубликована: Авг. 31, 2023

Abstract The Accuracy of model simulations is critical for climate change and its socio-economic impact. This study evaluated23 Global models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). main objective was to identify top 10 best performance capturing patterns rainfall 1981–2014 period over Intergovernmental Authority on Development (IGAD) region Eastern Africa. total rainfall, annual cycle, continuous, categorical Volumatic statistical metrics, scatter plots, Cumulative Distribution Function (CDF), colored code portrait were used assess . Results indicate that most CMIP6 generally capture characteristics observed climatology pattern bimodal unimodal regimes. majority Arid Semi-Arid Lands (ASALs) Kenya, Somalia, Ethiopia, Sudan scored lowest skills, highest bias, over-estimated lower skills June–September (JJAS) compared March–May (MAM) October-December (OND). Quantitatively, a high percent bias exceeding 80% ASALs, correlation coefficient ranging between 0.6 0.7 across Ethiopia’s highlands, 5–40 as Root Mean Squared Error region. In addition, 21 out 23 parts ACCESS-ESM1-5 MIROC6 are opposed CNRM-CM6-1HR under-estimated RMSE values. regional sub-national analysis showed it inconclusive select best-performed based individual metrics analysis. Out models, INM-CM5-0, HadGEM3-GC31-MM, CMCC-CM2-HR4, IPSL-CM6A-LR, KACE-1-0-G, EC-Earth3, NorESM2-MM, GFDL-ESM4, TaiESM1, KIOST-ESM IGAD These findings highlight importance selecting mapping present future hotspots extreme events

Язык: Английский

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Observation and Projection of Marine Heatwaves in the Caribbean Sea from CMIP6 Models

Remote Sensing, Год журнала: 2024, Номер 16(13), С. 2357 - 2357

Опубликована: Июнь 27, 2024

In recent decades, climate change has led to ocean warming, causing more frequent extreme events such as marine heatwaves (MHWs), which have been understudied in the Caribbean Sea. This study addresses this gap using 30 years of daily sea surface temperature (SST) data, complemented by projections for 21st century from nineteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models. 1983–2012 period, significant trends were observed spatially averaged MHWs frequency (1.32 annual per decade and node) mean duration (1.47 ± 0.29 days decade) but not intensity. addition, show large monthly variations these metrics, modulated interannual seasonal changes. seasonality is different three used being intense warm rainy months (intensity between 1.01 1.11 °C, 6.79 7.13 days) longer lasting late boreal winter 0.82 1.00 7.50 8.31 days). The behavior two that can occur both small areas Caribbean. Overall, models tend underestimate annually intensity, while they overestimate when compared observations. are under SSP585, sensible radiational scenario. However, an increase intensity (events much 154 2100) expected, driving a decrease (–37.39 SSP585 2100). These imply conditions at beginning will be nearly permanent Caribbean’s future. Nonetheless, caution advised interpreting due differences models’ simulations data. While advancements oceanic within CMIP6 demonstrate progress previous CMIP initiatives, challenges persist accurately simulating heatwaves.

Язык: Английский

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Habitat suitability modeling to improve conservation strategy of two highly-grazed endemic plant species in saint Catherine Protectorate, Egypt

BMC Plant Biology, Год журнала: 2025, Номер 25(1)

Опубликована: Апрель 16, 2025

Abstract Background Biodiversity is seriously threatened by climate change impacts in the long term. Conservationists must possess a comprehensive knowledge about habitat suitability of different species and factors that control their distribution order to effectively minimize biodiversity loss. Results The present study showed response two endemic taxa Saint Catherine protectorate (SKP) ( Micromeria serbaliana Bufonia multiceps ) anticipate over next few decades using models. In our analysis, we included incorporation bioclimatic variables into SDM modeling process four main algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM) an ensemble model. RF outperformed other models when analyzing , whereas BRT demonstrated superiority case . exhibited best performance, achieving mean TSS 0.94 for 0.86 was mainly affected Mean temperature wettest quarter (Bio8), elevation, Aridity index. On hand, most significant influencing were determined be Isothermality (Bio2/Bio7) × 100 (Bio3), elevation. slightly expanded during period form 2041–2060, then declined again from 2061 2080, while it moderate expansion under periods. Conclusion results research support urgent need conservation efforts, including reintroduction planning situ ex appropriate habitats. Clinical trial number Not applicable.

Язык: Английский

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Future Expansion of Sterculia foetida L. (Malvaceae): Predicting Invasiveness in a Changing Climate

Forests, Год журнала: 2025, Номер 16(6), С. 912 - 912

Опубликована: Май 29, 2025

Sterculia foetida L., commonly known as the Java olive, is a tropical tree species native to regions of East Africa, Asia, and northern Australia. This study employs distribution modeling (SDM) predict potential geographic S. under current future climate scenarios. Using 1425 occurrence data 19 environmental variables, we applied an ensemble modelling approach three algorithms: Boosting Regression Trees (BRT), Generalized Linear Model (GLM), Random Forests (RF), generate maps. Our models showed high accuracy (mean AUC = 0.98) indicate that has broad ecological niche, with suitability in subtropical north Australia (New Guinea Papua), Southeast Asia (India, Thailand, Myanmar, Taiwan, Philippines, Malaysia, Sri Lanka), Oman Yemen southwest Central Africa (Guinea, Ghana, Nigeria, Congo, Kenya Tanzania), Greater Lesser Antilles, Mesoamerica, South America (Colombia, Panama, Venezuela, Ecuador Brazil). Indeed, probability positively correlates Maximum temperature warmest month (bio5), Mean wettest quarter (bio8) Precipitation (bio13). The model results area 4,744,653 km2, representing 37.86% total area, classified into Low (14.12%), Moderate (8.71%), High (15.02%). Furthermore, found habitat for similar trends both near scenarios (SSP1-2.6 SSP5-8.5 2041–2060), slight loss (0.24% 0.25%, respectively) moderate gains (1.98% 2.12%). In far (2061–2080), low scenario (SSP1-2.6) indicated 0.29% 2.52% gain, while (SSP5-8.5) more dramatic increase (0.6%) gain areas (3.79%). These findings are crucial conservation planning management, particularly where considered invasive could become problematic. underscores importance incorporating change projections SDM better understand invasiveness dynamics inform biodiversity strategies.

Язык: Английский

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Analyzing Historical and Projected Precipitation Variability and Trends in Eastern Africa: Insights from CRU and CMIP6 Simulations

Earth Systems and Environment, Год журнала: 2025, Номер unknown

Опубликована: Июнь 2, 2025

Язык: Английский

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Development of intensity–duration–frequency relationships in Khon Kaen City, Thailand under changing climate using GCMs and a simple scaling method

Journal of Water and Climate Change, Год журнала: 2024, Номер 15(3), С. 1204 - 1217

Опубликована: Март 1, 2024

Abstract This study analyses the annual maximum (AM) rainfall series (1991–2022) in Khon Kaen City, Thailand. The AM ranging from 3 to 24 h was best fitted Log-Pearson Type-III distribution. Notably, our findings reveal linear relationships between moments of intensities and durations establishing practicality simple scaling method for disaggregating 24-h data. Additionally, results this are influenced by factors such as sample size, chosen probability Comparisons intensity–duration–frequency (IDF) curves obtained through those derived traditional frequency analysis provide valuable insights. Furthermore, applied bias-corrected data 15 global climate models facilitating generation future IDF under SSP1-2.6, SSP2-4.5, SSP3-7.0 SSP5-8.5 scenarios. Our highlight that events scenario projected exhibit higher emphasizing need understand prepare increased extremes context change. research contributes insights into prediction techniques, which crucial effective water resource management adaptation strategies region.

Язык: Английский

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Evaluating climate change scenarios in the white volta basin: A statistical bias-correction approach

Physics and Chemistry of the Earth Parts A/B/C, Год журнала: 2024, Номер 134, С. 103584 - 103584

Опубликована: Март 30, 2024

Язык: Английский

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