An ensemble-based assessment of bias adjustment performance, changes in hydrometeorological predictors and compound extreme events in EAS-CORDEX DOI Creative Commons
Patrick Olschewski, Patrick Laux, Jianhui Wei

et al.

Weather and Climate Extremes, Journal Year: 2022, Volume and Issue: 39, P. 100531 - 100531

Published: Nov. 28, 2022

The effectiveness of adaptive measures tackling the effects climate change is dependent on robust projections. This becomes even more important in face intensifying extreme events. One example these events flooding, which embodies a major threat to highly vulnerable coastal urban areas. includes eastern Asia, where multiple megacities are located, e.g. Shanghai and Shenzhen. While ability general circulation models (GCMs) regional (RCMs) project atmospheric changes associated with has improved, systematic errors (biases) remain. study therefore assess capabilities improving quality projections for Asia. performed by evaluating an ensemble consisting bias adjustment methods, GCM-RCM model runs future emission scenarios based representative concentration pathways (RCP) obtained from EAS-CORDEX. We show that significantly improves output best results applying quantile delta mapping. Based we evaluate potential crucial hydrometeorological predictors, univariate compound events, focusing high wind speeds precipitation. Key findings include increase daily maximum temperature 1.5 nearly 4 °C, depending scenario, as well increased levels precipitation under RCP 8.5. Furthermore, distinct intensification including temperatures heavy detected this exceeds overall mean predictors. annual number shows significant up 50% 8.5 South China Sea adjacent

Language: Английский

Quantile delta-mapped spatial disaggregation analysis for summertime compound extremes over China DOI
Rui Zhao, Xiong Zhou, Yongping Li

et al.

Climate Dynamics, Journal Year: 2024, Volume and Issue: 62(9), P. 8453 - 8473

Published: Aug. 5, 2024

Language: Английский

Citations

1
Relative contribution of dynamic and thermodynamic components on Southeast Asia future precipitation changes from different multi-GCM ensemble members DOI Creative Commons
Sheau Tieh Ngai, Srivatsan V. Raghavan, Jing Xiang Chung

et al.

Advances in Climate Change Research, Journal Year: 2024, Volume and Issue: 15(5), P. 869 - 882

Published: Aug. 29, 2024

To address the gap in understanding precipitation changes Southeast Asia and to enhance reliability of climate projections for region through moisture budget analysis, this study examines differences among six multi-model ensembles CMIP6 simulated term analysis. It investigates relative contributions thermodynamic dynamic components seasonal over under highest emission scenario, SSP5-8.5. The comparison between indicates that Good performance model slightly outperform combination all resolution category reducing biases. There is no strong evidence showing good ensemble groups simulating spatial pattern historical precipitation. From perspective budget, regions receiving high rainfall intensity are mainly influenced by convergence during monsoon seasons: northeast (December‒January‒February) southwest (June–July–August). By late 21st century (2081‒2100), show an increase December‒January‒February northern decreased June‒July‒August southern regions. analysis explained mean change largely evaporation followed flux convergence. contributed both components. Greater inter-model uncertainty was found component compared suggesting existence large discrepancy various approaches used GCMs describing atmospheric dynamics. highlights with middle low able narrow uncertainties terms ensembles.

Language: Английский

Citations

1
Improved simulation of compound drought and heat extremes in Eastern China through CWRF downscaling DOI Creative Commons
Han Zhang, Shulei Zhang, Haoran Xu

et al.

Environmental Research Letters, Journal Year: 2024, Volume and Issue: 19(12), P. 124037 - 124037

Published: Oct. 29, 2024

Abstract Given their profound socio-economic impact and increasing occurrence, compound drought heat extremes (CDHEs) have become a focal point of widespread concern. Studies attempted to reproduce predict these using general circulation models (GCMs); however, the performance in capturing events remains controversial. This study presents an improved simulation CDHE trends over eastern China by regional Climate-Weather Research Forecasting model (CWRF) downscale projections two GCMs that participated Coupled Model Intercomparison Project Phase 6. The results show CWRF downscaling significantly underestimation GCM historical simulations, aligning better with observed trends. Moreover, improvements simulating CDHEs are more pronounced than those for univariate events, i.e. extreme events. enhancement largely from CWRF’s representation land-atmosphere interaction processes, as indicated realistic spatial distributions intensities coupling strength index. Under SSP245 SSP585 scenario, again predicts rapid increase mean frequency compared GCMs, values nearing or exceeding 0.4 mid-21st century, suggesting significant future threat region. highlights important role interactions shaping efficacy climate reduce uncertainty event simulations.

Language: Английский

Citations

1
High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model DOI
Mingyun Hu, Xingcheng Lu, Yiang Chen

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 371, P. 123096 - 123096

Published: Nov. 1, 2024

Language: Английский

Citations

1
An ensemble-based assessment of bias adjustment performance, changes in hydrometeorological predictors and compound extreme events in EAS-CORDEX DOI Creative Commons
Patrick Olschewski, Patrick Laux, Jianhui Wei

et al.

Weather and Climate Extremes, Journal Year: 2022, Volume and Issue: 39, P. 100531 - 100531

Published: Nov. 28, 2022

The effectiveness of adaptive measures tackling the effects climate change is dependent on robust projections. This becomes even more important in face intensifying extreme events. One example these events flooding, which embodies a major threat to highly vulnerable coastal urban areas. includes eastern Asia, where multiple megacities are located, e.g. Shanghai and Shenzhen. While ability general circulation models (GCMs) regional (RCMs) project atmospheric changes associated with has improved, systematic errors (biases) remain. study therefore assess capabilities improving quality projections for Asia. performed by evaluating an ensemble consisting bias adjustment methods, GCM-RCM model runs future emission scenarios based representative concentration pathways (RCP) obtained from EAS-CORDEX. We show that significantly improves output best results applying quantile delta mapping. Based we evaluate potential crucial hydrometeorological predictors, univariate compound events, focusing high wind speeds precipitation. Key findings include increase daily maximum temperature 1.5 nearly 4 °C, depending scenario, as well increased levels precipitation under RCP 8.5. Furthermore, distinct intensification including temperatures heavy detected this exceeds overall mean predictors. annual number shows significant up 50% 8.5 South China Sea adjacent

Language: Английский

Citations

6