A typology of compound weather and climate events

Nature Reviews Earth & Environment, Год журнала: 2020, Номер 1(7), С. 333 - 347

Опубликована: Июнь 15, 2020

Язык: Английский

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Anthropogenic intensification of short-duration rainfall extremes

Nature Reviews Earth & Environment, Год журнала: 2021, Номер 2(2), С. 107 - 122

Опубликована: Янв. 15, 2021

Язык: Английский

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Understanding and managing connected extreme events

Nature Climate Change, Год журнала: 2020, Номер 10(7), С. 611 - 621

Опубликована: Июнь 15, 2020

Язык: Английский

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Advances in understanding large‐scale responses of the water cycle to climate change

Annals of the New York Academy of Sciences, Год журнала: 2020, Номер 1472(1), С. 49 - 75

Опубликована: Апрель 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.

Язык: Английский

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Current European flood-rich period exceptional compared with past 500 years

Nature, Год журнала: 2020, Номер 583(7817), С. 560 - 566

Опубликована: Июль 22, 2020

Язык: Английский

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More meteorological events that drive compound coastal flooding are projected under climate change

Communications Earth & Environment, Год журнала: 2020, Номер 1(1)

Опубликована: Ноя. 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

Язык: Английский

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Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management

Hydrology and earth system sciences, Год журнала: 2021, Номер 25(7), С. 3897 - 3935

Опубликована: Июль 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.

Язык: Английский

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Uncovering Flooding Mechanisms Across the Contiguous United States Through Interpretive Deep Learning on Representative Catchments

Water Resources Research, Год журнала: 2021, Номер 58(1)

Опубликована: Дек. 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.

Язык: Английский

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Joint Trends in Flood Magnitudes and Spatial Extents Across Europe

Geophysical Research Letters, Год журнала: 2020, Номер 47(7)

Опубликована: Апрель 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.

Язык: Английский

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How Do Climate and Catchment Attributes Influence Flood Generating Processes? A Large‐Sample Study for 671 Catchments Across the Contiguous USA

Water Resources Research, Год журнала: 2021, Номер 57(4)

Опубликована: Фев. 10, 2021

Abstract Hydrometeorological flood generating processes (excess rain, short long snowmelt, and rain‐on‐snow) underpin our understanding of behavior. Knowledge about improves hydrological models, frequency analysis, estimation climate change impact on floods, etc. Yet, not much is known how catchment attributes influence the spatial distribution processes. This study aims to offer a comprehensive structured approach close this knowledge gap. We employ large sample (671 catchments across contiguous United States) evaluate use two complementary approaches: A statistics‐based which compares attribute distributions different processes; random forest model in combination with an interpretable machine learning (accumulated local effects [ALE]). The ALE method has been used often hydrology, it overcomes significant obstacle many statistical methods, confounding effect correlated attributes. As expected, we find (fraction snow, aridity, precipitation seasonality, mean precipitation) be most influential process distribution. However, varies both type. also can predicted for ungauged relatively high accuracy ( R 2 between 0.45 0.9). implication these findings should considered future studies, as changes characteristics

Язык: Английский

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