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, Journal Year: 2023, Volume and Issue: 292, P. 106872 - 106872

Published: June 16, 2023

Language: Английский

---

Obtaining refined Euro-Mediterranean rainfall projections through regional assessment of CMIP6 General Circulation Models

Global and Planetary Change, Journal Year: 2025, Volume and Issue: unknown, P. 104725 - 104725

Published: Jan. 1, 2025

Language: Английский

---

Evaluating CMIP6 Historical Mean Precipitation over Africa and the Arabian Peninsula against Satellite-Based Observation

Atmosphere, Journal Year: 2023, Volume and Issue: 14(3), P. 607 - 607

Published: March 22, 2023

This study evaluated the historical precipitation simulations of 49 global climate models (GCMs) Coupled Model Intercomparison Project Phase 6 (CMIP6) in reproducing annual and seasonal climatology, linear trends, their spatial correlation with SST across Africa Arabian Peninsula during period 1980–2014, using Global Precipitation Climatology Centre (GPCP) data as a reference. Taylor’s diagram was used to quantify strengths weaknesses simulating precipitation. The CMIP6 multi-mean ensemble (MME) majority GCMs replicated dominant features temporal variations reasonably well. MME outperformed individual models. variation closely matched observation. results showed that at scales, GPCP reproduced coherent pattern terms magnitude humid region received >300 mm arid <50 Peninsula. from same modeling centers levels different seasons regions. overestimate (underestimate) (arid semi-arid)-climate zones. pre-monsoon (i.e., DJFMA) were better than monsoon-precipitation model (MJJASON). stronger wetting (drying) trends northern hemisphere. In contrast, strong drying trend weak shown Southern Hemisphere. captures zones relationship between sea-surface temperature (SST) exhibited high (−0.80 0.80) large variability regions (CMIP6 MME) heterogenous (homogeneous) pattern, higher coefficients recorded all cases. Individual homogeneity values. differences by highlight significance each model’s unique dynamics physics; however, selection should be considered for specific applications.

Language: Английский

---

Blue and green water availability under climate change in arid and semi-arid regions

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102743 - 102743

Published: July 30, 2024

Challenges involving water scarcity have raised concerns about sustainability and human well-being in many regions of Iran. Uncertainty related to the effects climate change further complicates use projections for resources planning. Hence, investigating impacts on is essential their efficient management. In present study, availability was assessed under different using eight CMIP6 General Circulation Models (GCMs) create a multi-model ensemble well-performing GCMs over Hamedan-Bahar watershed western Iran three futures, near (2026 2050), mid (2051 2075), far (2076 2100). Impacts blue green by coupling Soil Water Assessment Tool (SWAT) with modelled applying distribution mapping bias correction Shared Socioeconomic Pathways Scenarios (SSPs). The results showed that (MIROC6, CMCC-ESM2, NorESM2-MM) agreed well observed region. mean annual precipitation projected decrease at most 16.3% SSP5–8.5 scenario during mid-future. Maximum minimum temperatures are expected increase 2.3 2.4 °C, respectively, future. highest reductions storage flow were 22%, 28.5% 35%, contrast, 18% Thus, sensitive future climatic changes requiring considerations adaptation strategies mitigate deficits.

Language: Английский

---

Current and projected changes in climate extremes and agro-climatic zones over East Africa

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(3)

Published: Feb. 27, 2025

Language: Английский

---

Temporal trends in extreme temperature indices over Malawi during 1961–2015

Discover Atmosphere, Journal Year: 2025, Volume and Issue: 3(1)

Published: Feb. 27, 2025

Language: Английский

---

Machine Learning Algorithms as State-of-the-Art Tools for Prediction of Climatic Conditions: With Focus on Global Land Temperatures

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 18, 2025

Temperatures in various places are drastically increasing or reducing. Skyrocketing land temperatures expected to change the frequency and intensity of current temperature extremes. Determining evolving trends is thus immeasurable. Most importantly, global can be forecasted using machine learning algorithms. In our study, polynomial regression artificial neural networks were used predict for next 100 years. Scenario analysis was also done business-as-usual, moderate mitigation, aggressive mitigation approaches. All data visualizations historical data, predicted from scenario with aid MATLAB R2024a. Predictions revealed that a rapid increase occur 2012 2032 while followed by gentle rise 2100 based on networks’ prediction. The results dire need adopted implemented as soon possible. Despite predictions made two algorithms, more reliable compared those obtained regression.

Language: Английский

---

Climate Trend Analysis in the Ramis Catchment, Upper Wabi Shebelle Basin, Ethiopia, Using the CMIP6 Dataset

Journal of African Earth Sciences, Journal Year: 2024, Volume and Issue: 217, P. 105347 - 105347

Published: Sept. 1, 2024

Language: Английский

---

A non-parametric method to investigate internal trends in time sequence: A case study of temperature and precipitation

Ecological Indicators, Journal Year: 2023, Volume and Issue: 158, P. 111373 - 111373

Published: Dec. 10, 2023

Trend testing is essential for time sequence analysis. However, the existing trend methods mainly study trends of as a whole, while there lack feasible research tools internal sequence. Therefore, non-parametric method was proposed to overall and using ideas set pair, Cox-Stuart, Innovative Analysis Methodology, Mann-Kendall applied temperature precipitation sequences. The indicated that global were significantly increasing at confidence level α = 0.05. For precipitation, (both internal) Laifeng Leibo decreasing, respectively, some significant (α 0.05); however, Pingbian Sangzhi not exactly same, i.e., high (low) values in (Sangzhi) different from other rest. In general, successfully tested only but also their (divided into low, middle, values) trends. These results agreed with linear slope, Sen's Mann-Kendall, its improved. can be used analysis

Language: Английский

---

Spatio‐temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts

Global Ecology and Biogeography, Journal Year: 2024, Volume and Issue: 33(5)

Published: Feb. 26, 2024

Abstract Aim Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors shifts, with identification general trends being great interest to conservation efforts. However, studies reviewing relationships between shifts questioned existence such generalized trends, due mixed results weak correlations, well analytical shortcomings. The aim this study was test relationship empirically, using approaches account for common sources bias when assessing trends. Location Tanzania, East Africa. Time period 1980–1999 2000–2020. Major taxa studied 57 savannah specialist birds found belonging 26 families 11 orders. Methods We applied recently developed integrated spatio‐temporal distribution models R‐INLA, combining citizen science bird Atlas data estimate ranges species, quantify predictive power traditional trait groups, exposure‐related sensitivity traits. based our on 40 years observations African savannahs, a biome has experienced increasing climatic non‐climatic pressures over recent decades. correlated patterns linear regression models. Results find indications identified by previous research, but low average explanatory from an ecological perspective, confirming lack meaningful associations. analysis finds compelling species‐specific results. Main conclusions highlight importance individual assessments while demonstrating usefulness approach analyses

Language: Английский

---