Impacts of Climate Change on Temperature and Rainfall on Dawa Sub-watershed, Genale Dawa River Basin, Southern Ethiopia DOI Open Access

Ayana Bulti,

Fentaw Abegaz

International Journal of Atmospheric and Oceanic Sciences, Journal Year: 2024, Volume and Issue: 8(1), P. 1 - 23

Published: Sept. 20, 2024

Understanding how climate change affects the frequency and length of temperature rainfall is global issue. Climate statistical variations over an extended period in features system, such as temperatures precipitation, caused by human natural sources. In this work coordinated regional downscaling experiment for Africa, which integrates forecasts from Coupled Model Intercomparison Project5 based on ensemble GCM RCM model was used to statistically downscale scenarios. This study aimed estimate impacts rainfall. The impact has been evaluated reporting under RCP4.5 8.5 For extraction bias correction daily maximum minimum temperature, well 30-year overlap periods, CMhyd employed. annual are predicted increase 2.94, 3.45, 3.21, 3.59°C increased 2.61, 2.83, 2.71 3.36°C RCP8.5 respectively. reveals average decreases 8.45 9.3% 10.5 10.95% at 8.5, Considering parameters, trends but rainfall, large fluctuations were predicted. Moreover, years parameters all simulated models, scenario estimated a higher amount than scenario. Implement various trees, apply water harvesting structure, Surface runoff more multiple GCM-RCM driving models with outputs improve prediction accuracy future studies.

Language: Английский

Assessment of bias correction methods for high resolution daily precipitation projections with CMIP6 models: A Canadian case study DOI Creative Commons
Xinyi Li, Zhong Li

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102223 - 102223

Published: Feb. 10, 2025

Language: Английский

Citations

1
Changes in the annual cycle of surface air temperature over China in the 21st century simulated by CMIP6 models DOI Creative Commons

Chenwei Zhang,

Guocan Wu, Runze Zhao

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 21, 2025

Language: Английский

Citations

1
Future Climate Projections for Tacna, Peru: Assessing Changes in Temperature and Precipitation DOI Creative Commons
Gustavo De la Cruz, Adrian Huerta,

Pablo Franco-León

et al.

Atmosphere, Journal Year: 2025, Volume and Issue: 16(2), P. 144 - 144

Published: Jan. 29, 2025

The Tacna region, situated in southwestern Peru, is distinguished by its desert and Andean zones, resulting significant climatic variability. However, changes future precipitation temperature patterns could significantly impact sectors such as agriculture, energy, water resources. In this context, research analyzes climate scenarios of precipitation, maximum (Tmax), minimum (Tmin) Tacna. For purpose, was divided into four homogeneous regions (Coast, Low Highlands, High Andes, Plateau) to assess using CMIP6 models for the SSP1-2.6, SSP2-4.5, SSP5-8.5 scenarios. A bias correction these applied Quantile Delta Mapping method improve accuracy. validation results showed better performance compared precipitation. Regarding scenario results, end century, under scenario, Tmax increase up +7 °C while Tmin rise +5 °C, particularly Plateau. Precipitation projected decrease 20% annually higher elevations, albeit with considerable uncertainty; however, no are expected seasonal patterns. This study underscores importance robust projections formulating adaptation strategies resource management infrastructure planning. findings provide essential insights decision-makers address challenges posed change vulnerable southern Peru.

Language: Английский

Citations

0
A Future Scenario Prediction for the Arid Inland River Basins in China Under Climate Change: A Case Study of the Manas River Basin DOI Open Access

Fuchu Zhang,

Xinlin He, Guang Yang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3658 - 3658

Published: April 18, 2025

Global warming poses significant threats to agriculture, ecosystems, and human survival. This study focuses on the arid inland Manas River Basin in northwestern China, utilizing nine CMIP6 climate models five multi-model ensemble methods (including machine learning algorithms such as random forest support vector machines) evaluate historical temperature precipitation simulations (1979–2014) after bias correction via Quantile Mapping (QM). Future trends (2015–2100) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5) are projected analyzed for spatiotemporal evolution. The results indicate that weighted set method (WSM) significantly improves simulation accuracy excluding poorly performing models. Under SSP1-2.6, long-term average increases maximum temperature, minimum 1.654 °C, 1.657 34.137 mm, respectively, with minimal variability. In contrast, SSP5-8.5 exhibits most pronounced warming, reaching 4.485 4.728 60.035 respectively. Notably, rise gradually surpasses indicating a shift toward warmer more humid conditions basin. Spatially, high rates concentrated low-altitude desert areas, while correlate elevation. These findings provide critical insights adaptation strategies, sustainable water resource management, ecological conservation China’s river basins future change.

Language: Английский

Citations

0
The future of urban cycling: A predictive framework for climate change DOI Creative Commons
Xudong Wang, Eduardo Adame Valenzuela,

Chengzeng You

et al.

Transportation Research Part D Transport and Environment, Journal Year: 2025, Volume and Issue: 143, P. 104722 - 104722

Published: April 19, 2025

Language: Английский

Citations

0
Building and urban simulation under future climate: A novel statistical downscaling method for future hourly weather data generation DOI
Pengyuan Shen

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Language: Английский

Citations

0
Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction—Part 1: Spatiotemporal Characteristics DOI Open Access
Amarech Alebie Addisuu, Gizaw Mengistu Tsidu, Lenyeletse Vincent Basupi

et al.

Climate, Journal Year: 2025, Volume and Issue: 13(5), P. 95 - 95

Published: May 4, 2025

Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these emphasize the distribution precipitation within a month or season rather than overall amount. To meet this requirement, study applied three bias correction techniques—scaled mapping (SDM), quantile (QDM), QDM with separate treatment for below above 95th percentile threshold (QDM95)—to daily from eleven Coupled Model Intercomparison Project Phase 6 (CMIP6) models, using Climate Hazards Group Infrared Precipitation Station version 2 (CHIRPS) as reference. This evaluated performance all bias-corrected CMIP6 over Southern Africa 1982 2014 replicating spatial temporal patterns across region against observational datasets, CHIRPS, Climatic Research Unit (CRU), Global Climatology Centre (GPCC), standard statistical metrics. The results indicate that generally performs better native model December–February (DJF) mean seasonal cycle. probability density function (PDF) regional indicates enhances performance, particularly range 3–35 mm/day. However, both corrected uncorrected underestimate higher extremes. pattern correlations GPCC, CRU, compared have improved 0.76–0.89 0.97–0.99, 0.73–0.87 0.94–0.97, 0.74–0.89 respectively. Additionally, Taylor skill scores CRU 0.57–0.80 0.79–0.95, 0.55–0.76 0.80–0.91, 0.54–0.75 0.81–0.91, Overall, among techniques, consistently demonstrated QDM95 SDM various implementation distribution-based resulted significant reduction consistency between observations region.

Language: Английский

Citations

0
High-resolution monthly gridded temperature dataset development and trend analysis across Afghanistan: a spatio-temporal approach DOI

Maghfoorullah Tasal,

Shakil Ahmad, Muhammad Azmat

et al.

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(5)

Published: May 1, 2025

Language: Английский

Citations

0
Quantifying the Impact of Future Climate Change on Flood Susceptibility: An Integration of CMIP6 Models, Machine Learning, and Remote Sensing DOI
Farinaz Gholami, Yue Li,

Junlong Zhang

et al.

Journal of Water Resources Planning and Management, Journal Year: 2024, Volume and Issue: 150(9)

Published: June 19, 2024

Language: Английский

Citations

2
Projecting Irrigation Water and Crop Water Requirements for Paddies Using WEAP-MABIA under Climate Change DOI Creative Commons

Hamizah Rhymee,

Shahriar Shams, Uditha Ratnayake

et al.

Water, Journal Year: 2024, Volume and Issue: 16(17), P. 2498 - 2498

Published: Sept. 3, 2024

Monitoring future irrigation water demand as a part of agricultural interventions is crucial to ensure food security. In this study, the impact climate change on paddy cultivation in Brunei investigated, focusing Wasan rice scheme. This research aims project requirement (IWR) and crop (CWR) or main off season using WEAP-MABIA model. Historical data analysis over past 30 years projections up 2100 are employed assess potential impacts. An ensemble statistically downscaled models, based seven CMIP6 GCMs under shared socioeconomic pathways (SSPs) (SSP245, SSP370, SSP585), was utilised IWR CWR. Using data, three periods were bias-corrected quantile delta mapping (QDM) for 2020–2046 (near future), 2047–2073 (mid 2074–2100 (far future). The model utilises dual coefficient approach evaluate evapotranspiration (ETc), critical factor computing IWR. Results indicate that changes temperatures will lead higher average ETc. Consequently, results elevated demands during season, it especially prominent high-emission scenarios (SSP370 SSP585). While experiences relatively stable slightly increasing trend, consistently shows decreasing trend Moreover, benefits from substantial rainfall increases, effectively reducing despite rise both maximum minimum temperatures. study also highlights some recommendations implementing possible improvements management address effects region. Future investigation should focus enhancing yield predictions by integrating dynamic growth adjusts changing (Kc) values.

Language: Английский

Citations

2