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DOI	10.5194/hess-23-1409-2019
	Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives
	Philip S.; Sparrow S.; Kew S.F.; Van Der Wiel K.; Wanders N.; Singh R.; Hassan A.; Mohammed K.; Javid H.; Haustein K.; Otto F.E.L.; Hirpa F.; Rimi R.H.; Saiful Islam A.K.M.; Wallom D.C.H.; Jan Van Oldenborgh G.
发表日期	2019
ISSN	1027-5606
起始页码	1409
结束页码	1429
卷号	23 期号:3
英文摘要	In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents, for the first time, an attribution of this precipitation-induced flooding to anthropogenic climate change from a combined meteorological and hydrological perspective. Experiments were conducted with three observational datasets and two climate models to estimate changes in the extreme 10-day precipitation event frequency over the Brahmaputra basin up to the present and, additionally, an outlook to 2 C warming since pre-industrial times. The precipitation fields were then used as meteorological input for four different hydrological models to estimate the corresponding changes in river discharge, allowing for comparison between approaches and for the robustness of the attribution results to be assessed. In all three observational precipitation datasets the climate change trends for extreme precipitation similar to that observed in August 2017 are not significant, however in two out of three series, the sign of this insignificant trend is positive. One climate model ensemble shows a significant positive influence of anthropogenic climate change, whereas the other large ensemble model simulates a cancellation between the increase due to greenhouse gases (GHGs) and a decrease due to sulfate aerosols. Considering discharge rather than precipitation, the hydrological models show that attribution of the change in discharge towards higher values is somewhat less uncertain than in precipitation, but the 95% confidence intervals still encompass no change in risk. Extending the analysis to the future, all models project an increase in probability of extreme events at 2 °C global heating since pre-industrial times, becoming more than 1.7 times more likely for high 10-day precipitation and being more likely by a factor of about 1.5 for discharge. Our best estimate on the trend in flooding events similar to the Brahmaputra event of August 2017 is derived by synthesizing the observational and model results: We find the change in risk to be greater than 1 and of a similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach. This study shows that, for precipitation-induced flooding events, investigating changes in precipitation is useful, either as an alternative when hydrological models are not available or as an additional measure to confirm qualitative conclusions. Besides this, it highlights the importance of using multiple models in attribution studies, particularly where the climate change signal is not strong relative to natural variability or is confounded by other factors such as aerosols. © 2019 Author(s).
语种	英语
scopus关键词	Aerosols; Climate models; Floods; Greenhouse gases; Precipitation (meteorology); Risk perception; Sulfur compounds; Anthropogenic climate changes; Confidence interval; Ensemble modeling; Extreme precipitation; Hydrological models; Meteorological input; Natural variability; Precipitation events; Climate change; climate change; climate modeling; extreme event; flood; flooding; greenhouse gas; hydrological modeling; hydrology; meteorology; precipitation (climatology); river discharge; Bangladesh; Brahmaputra Basin
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159731
作者单位	Philip, S., Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands; Sparrow, S., Oxford E-Research Centre, Department of Engineering Science, University of Oxford, Oxford, United Kingdom; Kew, S.F., Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands; Van Der Wiel, K., Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands; Wanders, N., Department of Physical Geography, Utrecht University, Utrecht, Netherlands, Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, United States; Singh, R., Red Cross Red Crescent Climate Centre, The Hague, Netherlands; Hassan, A., Red Cross Red Crescent Climate Centre, The Hague, Netherlands; Mohammed, K., Oxford E-Research Centre, Department of Engineering Science, University of Oxford, Oxford, United Kingdom; Javid, H., Oxford E-Research Centre, Department of Engineering Science, University of Oxford, Oxford, United Kingdom, Environmental Change Institute, Oxford University Centre for...
推荐引用方式 GB/T 7714	Philip S.,Sparrow S.,Kew S.F.,et al. Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives[J],2019,23(3).
APA	Philip S..,Sparrow S..,Kew S.F..,Van Der Wiel K..,Wanders N..,...&Jan Van Oldenborgh G..(2019).Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives.Hydrology and Earth System Sciences,23(3).
MLA	Philip S.,et al."Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives".Hydrology and Earth System Sciences 23.3(2019).