Global Reach-Level 3-Hourly River Flood Reanalysis (1980–2019) DOI Open Access
Yuan Yang, Ming Pan, Peirong Lin

et al.

Bulletin of the American Meteorological Society, Journal Year: 2021, Volume and Issue: 102(11), P. E2086 - E2105

Published: July 8, 2021

Abstract Better understanding and quantification of river floods for very local “flashy” events calls modeling capability at fine spatial temporal scales. However, long-term discharge records with a global coverage suitable extreme analysis are still lacking. Here, grounded on recent breakthroughs in runoff hydrology, modeling, high-resolution hydrography, climate reanalysis, we developed 3-hourly record globally 2.94 million reaches during the 40-yr period 1980–2019. The underlying chain consists VIC land surface model (0.05°, 3-hourly) that is well calibrated bias corrected RAPID routing (2.94 catchment vectors), precipitation input from MSWEP other meteorological fields downscaled ERA5. Flood (above 2-yr return) their characteristics (number, distribution, seasonality) were extracted studied. Validations against flow 6,000+ gauges CONUS daily 14,000+ show good performance across all ranges, skills reconstructing flood (high extremes), benefit (and need for) subdaily modeling. This data record, referred as Global Reach-Level Reanalysis (GRFR), publicly available https://www.reachhydro.org/home/records/grfr .

Language: Английский

A typology of compound weather and climate events DOI
Jakob Zscheischler, Olivia Martius, Seth Westra

et al.

Nature Reviews Earth & Environment, Journal Year: 2020, Volume and Issue: 1(7), P. 333 - 347

Published: June 15, 2020

Language: Английский

Citations

950

Anthropogenic intensification of short-duration rainfall extremes DOI
Hayley J. Fowler, Geert Lenderink, Andreas F. Prein

et al.

Nature Reviews Earth & Environment, Journal Year: 2021, Volume and Issue: 2(2), P. 107 - 122

Published: Jan. 15, 2021

Language: Английский

Citations

564

Understanding and managing connected extreme events DOI Open Access
Colin Raymond, Radley Horton, Jakob Zscheischler

et al.

Nature Climate Change, Journal Year: 2020, Volume and Issue: 10(7), P. 611 - 621

Published: June 15, 2020

Language: Английский

Citations

496

Advances in understanding large‐scale responses of the water cycle to climate change DOI
Richard P. Allan, Mathew Barlow, Michael P. Byrne

et al.

Annals of the New York Academy of Sciences, Journal Year: 2020, Volume and Issue: 1472(1), P. 49 - 75

Published: April 4, 2020

Abstract Globally, thermodynamics explains an increase in atmospheric water vapor with warming of around 7%/°C near to the surface. In contrast, global precipitation and evaporation are constrained by Earth's energy balance at ∼2–3%/°C. However, this rate is suppressed rapid adjustments response greenhouse gases absorbing aerosols that directly alter budget. Rapid forcings, cooling effects from scattering aerosol, observational uncertainty can explain why observed responses currently difficult detect but expected emerge accelerate as increases aerosol forcing diminishes. Precipitation be smaller over land than ocean due limitations on moisture convergence, exacerbated feedbacks affected adjustments. Thermodynamic fluxes amplify wet dry events, driving intensification extremes. The deviate a simple thermodynamic in‐storm larger‐scale feedback processes, while changes large‐scale dynamics catchment characteristics further modulate frequency flooding increases. Changes circulation radiative evolving surface temperature patterns capable dominating cycle some regions. Moreover, direct impact human activities through abstraction, irrigation, use change already significant component regional importance demand grows population.

Language: Английский

Citations

416

Current European flood-rich period exceptional compared with past 500 years DOI
Günter Blöschl, Andrea Kiss, Alberto Viglione

et al.

Nature, Journal Year: 2020, Volume and Issue: 583(7817), P. 560 - 566

Published: July 22, 2020

Language: Английский

Citations

277

More meteorological events that drive compound coastal flooding are projected under climate change DOI Creative Commons
Emanuele Bevacqua, Michalis Vousdoukas, Giuseppe Zappa

et al.

Communications Earth & Environment, Journal Year: 2020, Volume and Issue: 1(1)

Published: Nov. 12, 2020

Abstract Compound flooding arises from storms causing concurrent extreme meteorological tides (that is the superposition of storm surge and waves) precipitation. This can severely affect densely populated low-lying coastal areas. Here, combining output climate ocean models, we analyse concurrence probability conditions driving compound flooding. We show that, under a high emissions scenario, would increase globally by more than 25% 2100 compared to present. In latitudes above 40 o north, could become 2.5 times as frequent, in contrast parts subtropics where it weaken. Changes precipitation account for most (77% 20%, respectively) projected change probability. The evolution dependence between tide dominates uncertainty projections. Our results indicate that not accounting these effects adaptation planning leave communities insufficiently protected against

Language: Английский

Citations

194

Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management DOI Creative Commons
Louise Slater, Bailey Anderson, Marcus Buechel

et al.

Hydrology and earth system sciences, Journal Year: 2021, Volume and Issue: 25(7), P. 3897 - 3935

Published: July 7, 2021

Abstract. Hydroclimatic extremes such as intense rainfall, floods, droughts, heatwaves, and wind or storms have devastating effects each year. One of the key challenges for society is understanding how these are evolving likely to unfold beyond their historical distributions under influence multiple drivers changes in climate, land cover, other human factors. Methods analysing hydroclimatic advanced considerably recent decades. Here we provide a review drivers, metrics, methods detection, attribution, management, projection nonstationary extremes. We discuss issues uncertainty associated with approaches (e.g. arising from insufficient record length, spurious nonstationarities, incomplete representation sources modelling frameworks), examine empirical simulation-based frameworks analysis extremes, identify gaps future research.

Language: Английский

Citations

189

Uncovering Flooding Mechanisms Across the Contiguous United States Through Interpretive Deep Learning on Representative Catchments DOI
Shijie Jiang, Yi Zheng, Chao Wang

et al.

Water Resources Research, Journal Year: 2021, Volume and Issue: 58(1)

Published: Dec. 27, 2021

Abstract Long short‐term memory (LSTM) networks represent one of the most prevalent deep learning (DL) architectures in current hydrological modeling, but they remain black boxes from which process understanding can hardly be obtained. This study aims to demonstrate potential interpretive DL gaining scientific insights using flood prediction across contiguous United States (CONUS) as a case study. Two interpretation methods were adopted decipher machine‐captured patterns and inner workings LSTM networks. The by expected gradients method revealed three distinct input‐output relationships learned LSTM‐based runoff models 160 individual catchments. These correspond flood‐inducing mechanisms—snowmelt, recent rainfall, historical rainfall—that account for 10.1%, 60.9%, 29.0% 20,908 flow peaks identified data set, respectively. Single flooding mechanisms dominate 70.7% investigated catchments (11.9% snowmelt‐dominated, 34.4% rainfall‐dominated, 24.4% rainfall‐dominated mechanisms), remaining 29.3% have mixed mechanisms. spatial variability dominant reflects catchments' geographic climatic conditions. Moreover, additive decomposition unveils how network behaves differently retaining discarding information when emulating different types floods. Information inputs within previous time steps partially stored predict snowmelt‐induced rainfall‐induced floods, while only is retained. Overall, this provides new perspective processes extremes demonstrates prospect artificial intelligence‐assisted discovery future.

Language: Английский

Citations

160

Joint Trends in Flood Magnitudes and Spatial Extents Across Europe DOI Creative Commons
Matthias Kemter, Bruno Merz, Norbert Marwan

et al.

Geophysical Research Letters, Journal Year: 2020, Volume and Issue: 47(7)

Published: April 1, 2020

The magnitudes of river floods in Europe have been observed to change, but their alignment with changes the spatial coverage or extent individual has not clear. We analyze flood and extents for 3,872 hydrometric stations across over past five decades classify each based on antecedent weather conditions. find positive correlations between 95% stations. In central British Isles, association increasing trends is due a magnitude-extent correlation precipitation soil moisture along shift generating processes. highlights importance transnational risk management.

Language: Английский

Citations

149

Changes in Antecedent Soil Moisture Modulate Flood Seasonality in a Changing Climate DOI
Conrad Wasko, Rory Nathan, Murray C. Peel

et al.

Water Resources Research, Journal Year: 2020, Volume and Issue: 56(3)

Published: Feb. 19, 2020

Due to difficulties in identifying a climate change signal flood magnitude, it has been suggested that shifts timing, is, the day of annual streamflow maxima, may be detectable. Here, we use high-quality streamflow, largely free snowmelt, from 221 catchments across Australia investigate influence soil moisture and rainfall timing on maxima timing. In tropical areas find is strongly linked both maxima. However, southern more correlated with than The link between flood, moisture, confounded by event severity: For less extreme events likely correspond whereas becomes increasingly important as severity increases. Using circular regression nonstationarity, shifting earlier year tropics later southwest continent, consistent changes mean due expansion. southeast Australia, there evidence mechanisms controlling seasonality are changing reversal trends post Millennium Drought. Overall, compared found have greater

Language: Английский

Citations

140