Assessment of Observed and Projected Extreme Droughts in Perú—Case Study: Candarave, Tacna DOI Creative Commons
Ana Cruz-Baltuano,

Raúl Huarahuara-Toma,

Arlette Silva-Borda

et al.

Atmosphere, Journal Year: 2024, Volume and Issue: 16(1), P. 18 - 18

Published: Dec. 27, 2024

Droughts have always been one of the most dangerous hazards for civilizations, especially when they impact headwaters a watershed, as their effects can spread downstream. In this context, observed droughts (1981–2015) and projected (2016–2100) were assessed in Candarave, Locumba basin. Regarding droughts, SPI-3 SPEI-3 detected seven extreme (1983, 1992, 1996, 1998, 2010, 2011, 2012), with intense occurring 1992 1998. SPI-6 SPEI-6 identified same drought events, highlighting intense. Additionally, it was concluded that VCI also by SPEI; however, more detailed analysis its use is necessary due to limited availability suitable satellite images area. On other hand, high-resolution dataset climate models from sixth phase Coupled Model Intercomparison Project (CMIP6) under SSP3-7.0 scenario used project future droughts. Of dataset, CanESM5, IPSL–CM6A–LR, UKESM1–0–LL did not perform well study SPI SPEI than ten episodes drought, indicating will become frequent, severe, last 30 years century.

Language: Английский

Quantifying Uncertainty in Projections of Desertification in Central Asia Using Bayesian Networks DOI Creative Commons
Jinping Liu, Yanqun Ren, Panxing He

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(4), P. 665 - 665

Published: Feb. 15, 2025

Desertification presents major environmental challenges in Central Asia, driven by climatic and anthropogenic factors. The present study quantifies desertification risk through an integrated approach using Bayesian networks the ESAS model, offering a holistic perspective on dynamics. Four key variables—vegetation cover, precipitation, land-use intensity, soil quality—were incorporated into model to evaluate their influence desertification. A probabilistic was developed gauge with simulations conducted at 200 geospatial points. Hazard maps for 2030–2050 were produced under climate scenarios SSP245 SSP585, incorporating projected changes. All procedures assessment, mapping, downscaling performed Google Earth Engine platform. findings suggest 4% increase 11% SSP585 2050, greatest threats observed western regions such as Kazakhstan, Uzbekistan, Turkmenistan. Sensitivity analysis indicated that vegetation quality exerts strongest desertification, reflected Vegetation Quality Index (VQI) ranging from 1.582 (low Turkmenistan) 1.692 (very low Kazakhstan). comparison of models revealed robust alignment, evidenced R2 value 0.82, Pearson correlation coefficient 0.76, RMSE 0.18. These results highlight utility effective tool assessment scenario analysis, underscoring urgency targeted land management proactive adaptation. Although reclaimed opportunities afforestation sustainable agriculture, carefully considering potential trade-offs biodiversity ecosystem services remains essential.

Language: Английский

Citations

0
Future projections of the rainfall intensity-duration-frequency curves in Beijing-Tianjin-Hebei urban agglomeration based on NEX-GDDP CMIP6 simulations DOI
Lidong Song, Lei Yan,

Fuxin Chai

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106227 - 106227

Published: Feb. 1, 2025

Language: Английский

Citations

0
Soil moisture deficits triggered by increasing compound drought and heat events during the growing season in Arid Central Asia DOI
Qian Wang, Changchun Xu, Jin Long

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: 660, P. 133397 - 133397

Published: April 29, 2025

Language: Английский

Citations

0
Global Warming Will Increase the Risk of Water Shortage in Northwest China DOI Creative Commons

Lu Chang,

Qiang Zhang, R. Iestyn Woolway

et al.

Earth s Future, Journal Year: 2025, Volume and Issue: 13(5)

Published: May 1, 2025

Abstract Drylands with fragile ecosystems and severe water shortages are particularly vulnerable to climatic change. Northwestern China (NWC), a typical arid region, faces uncertainty regarding future wetting or drying trends. A comprehensive assessment projection of these conditions crucial for resource management. In this study, we employ Lagrangian trajectory model, optimal fingerprint analysis, maximum covariance technique evaluate and/or trends in NWC over the historical (1981–2023) (2024–2099) periods. Our results show that 80% experienced increases air temperature, precipitation, evaporation during period. External internal vapor sources contribute 92% 8%, respectively, precipitation changes. Incoming predominantly originated from North Atlantic (31.9%) South Sea ‐ Bay Bengal region (39.3%), strong positive correlation ( r = 0.71) between sea surface temperatures minus NWC. Water enters southern, northern, western boundaries, while 83.4% escapes through eastern boundary. The trend is strongly influenced by combined effects anthropogenic natural forcings, accounting 36.8% observed increase. Under 1.5°C warming scenario, warming‐wetting regions shift northward, whereas higher levels (2°C, 3°C, 4°C) cause southeastward shrink. findings underscore NWC's high sensitivity climate highlight pressing challenge security world.

Language: Английский

Citations

0
A novel statistical framework of drought projection by improving ensemble future climate model simulations under various climate change scenarios DOI

H. Abbas,

Zulfiqar Ali

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(10)

Published: Sept. 17, 2024

Language: Английский

Citations

3
Evaluation and projection of extreme precipitation using CMIP6 model simulations in the Yellow River Basin DOI Creative Commons
Heng Xiao, Yue Zhuo, Peng Jiang

et al.

Journal of Water and Climate Change, Journal Year: 2024, Volume and Issue: 15(5), P. 2326 - 2347

Published: April 16, 2024

ABSTRACT The capabilities of 23 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 were evaluated for six extreme precipitation indices 1961 to 2010 using interannual variability and Taylor skill scores in Yellow River Basin its eight subregions. temporal variations spatial distributions projected 2021 2050 under shared socioeconomic pathway scenarios (SSP2–4.5 SSP5–8.5). results show that most GCMs perform well simulating values (1-day maximum (RX1day) 5-day (RX5day)), duration (consecutive dry days), intensity index (simple daily (SDII)), poor threshold (precipitation on very wet days (R95p) number heavy (R10mm)). changes indicate SSP2-4.5 scenario, future will increase by 15.7% (RX1day), 15.8% (RX5day), 30.3% (R95p), 1d (R10mm), 6.6% (SDII), respectively, decrease 2.1d (CDD). aforementioned are further enhanced SSP5-8.5 scenario. Extreme widely Hekou Town Longmen, northeastern part region Longmen Sanmenxia, below Huayuankou, interflow basin.

Language: Английский

Citations

2
Near-Future Projection of Sea Surface Winds in Northwest Pacific Ocean Based on a CMIP6 Multi-Model Ensemble DOI Creative Commons
Ahmad Bayhaqi, Jeseon Yoo, Chan Joo Jang

et al.

Atmosphere, Journal Year: 2024, Volume and Issue: 15(3), P. 386 - 386

Published: March 21, 2024

Information about wind variations and future conditions is essential for a monsoon domain such as the Northwest Pacific (NWP) region. This study utilizes 10 Generalized Circulation Models (GCM) from CMIP6 to evaluate near-future changes in NWP under various climate warming scenarios. Evaluation against ERA5 reanalysis dataset historical period 1985–2014 reveals relatively small error with an average of no more than 1 m/s, particularly East Asian Marginal Seas (EAMS). Future projections (2026–2050) indicate intensified winds, 5–8% increase summer season EAMS, Yellow Sea, China while slight decreases are observed winter period. Climate mode influences show that El Niño tends decrease speeds southern domain, intensifying winds northern part, SSP5-8.5. Conversely, induces higher positive anomalous SSP2-4.5. These likely linked Niño-induced SST anomalies. For application surface findings further investigations focusing on oceanic consequences anticipated ocean wave climate, which can be studied through model simulations.

Language: Английский

Citations

2
Changes in photovoltaic power output variability due to climate change in China: A multi-model ensemble mean analysis DOI Open Access

Hui-Min Zuo,

H. F. Lü,

Peng Sun

et al.

Journal of Renewable and Sustainable Energy, Journal Year: 2024, Volume and Issue: 16(2)

Published: March 1, 2024

Solar photovoltaic (PV) power plays a crucial role in mitigating climate change. However, change may amplify weather variability and extreme conditions. The conditions can increase the very low PV output thereby need for grid stabilization services. This study examined how affects near- (2025–2054) far-future (2071–2100). ensemble mean calculated using seven global models participating coupled model intercomparison project phase 6 three different shared socioeconomic pathways (SSPs) (SSP126, SSP245, SSP585) was used assessment. standard deviation of monthly share were to assess output. findings indicate that summer projected decrease by 6%–8% central northern Tibet under high emissions scenario (SSP585). months with western regions China, known its abundant solar resources. this provide valuable insight energy planners make up influence future variability.

Language: Английский

Citations

2
Assessment of rainwater resources in urban areas of reception basins of South-to-North Water Diversion Project under climate change. DOI
Weiwei Shao, Yuxing Li,

Xin Su

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 478, P. 143898 - 143898

Published: Oct. 6, 2024

Language: Английский

Citations

2
Assessment of Historical and Future Mean and Extreme Precipitation Over Sub‐Saharan Africa Using NEX‐GDDP‐CMIP6: Part I—Evaluation of Historical Simulation DOI
Sydney Samuel, Gizaw Mengistu Tsidu, Alessandro Dosio

et al.

International Journal of Climatology, Journal Year: 2024, Volume and Issue: 45(2)

Published: Dec. 5, 2024

ABSTRACT This study assesses the performance of 28 NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX‐GDDP‐CMIP6) models and their multi‐model ensemble (MME) in simulating mean extreme precipitation across sub‐Saharan Africa from 1985 to 2014. The Multi‐Source Weighted‐Ensemble Precipitation (MSWEP) Hazards Group InfraRed with Station Data (CHIRPS) are used as reference datasets. Various statistical metrics such bias (MB), spatial correlation coefficients (SCCs), Taylor skill scores (TSS) comprehensive ranking index (CRI) employed evaluate NEX‐GDDP‐CMIP6 at both annual seasonal scales. Results show that can reproduce observed cycle all subregions, model spread within observational uncertainties. MME also successfully reproduces distribution precipitation, achieving SCCs TSSs greater than 0.8 subregions. biases consistent different However, most trends opposite observations. While generally its varies dataset, particularly for number rainy days (RR1) maximum consecutive dry (CDD). TSS values indices differ significantly by region, data index, lowest over South Central highest West Southern Africa. CRI indicates no single consistently outperforms others even same when compared MSWEP CHIRPS. These results may be helpful using future projections impact assessment studies

Language: Английский

Citations

2