Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston.

Category 4 landfalling hurricane Harvey poured more than a metre of rainfall across the heavily populated Houston area, leading to unprecedented flooding and damage. Although studies have focused on the contribution of anthropogenic climate change to this extreme rainfall event1-3, limited attention has been paid to the potential effects of urbanization on the hydrometeorology associated with hurricane Harvey. Here we find that urbanization exacerbated not only the flood response but also the storm total rainfall. Using the Weather Research and Forecast model-a numerical model for simulating weather and climate at regional scales-and statistical models, we quantify the contribution of urbanization to rainfall and flooding. Overall, we find that the probability of such extreme flood events across the studied basins increased on average by about 21 times in the period 25-30 August 2017 because of urbanization. The effect of urbanization on storm-induced extreme precipitation and flooding should be more explicitly included in global climate models, and this study highlights its importance when assessing the future risk of such extreme events in highly urbanized coastal areas.

Impact of coronavirus-driven reduction in aerosols on precipitation in the western United States.

Among the many impacts of COVID-19, the pandemic led to improved air quality conditions in the countries under quarantine due to the shutdown of industries, drastically reduced traffic, and lockdowns. Meanwhile, the western United States, particularly the coastal areas from Washington to California, received much less precipitation than normal during early 2020. Is it possible that this reduction in precipitation was driven by the reduced aerosols due to the coronavirus? Here we show that the reduction in aerosols resulted in higher temperatures (up to ∼0.5 °C) and generally lower snow amounts but cannot explain the observed low precipitation amounts over this region. In addition to an assessment of the effects of the coronavirus-related reduction in aerosols on precipitation across the western United States, our findings also provide basic information on the potential impacts different mitigation efforts aimed at reducing anthropogenic aerosols would have on the regional climate.

Greenhouse gases drove the increasing trends in spring precipitation across the central USA.

The central USA experienced major flooding during spring 2019, with both the Missouri and Mississippi Rivers at major flood stage at several locations, causing levees to breach and widespread flooding. Here, we examine the total precipitation responsible for the spring 2019 flooding across the central USA from the perspective of weather types. We focus on the weather type (referred to as 'Midwest Water Hose' (MWH) (Zhang and Villarini. 2019 Climate Dynamics 53, 4217-4232. (doi:10.1007/s00382-019-04783-4))) that contributes the most to the total precipitation across the central USA. This weather type contributed to more than 70% of the total precipitation received across much of this region during January-May 2019, and it has been occurring increasingly frequently over the past 40 years. Furthermore, we found that climate model experiments with the historical change of greenhouse gas concentration can well reproduce the observed rising trend, while this is not the case for the natural forcing experiments. Therefore, the rising trend and the high frequency of the MWH can be mainly attributed to the rising greenhouse gases caused by human activities, rather than natural forcing. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Incorporating climate change in flood estimation guidance.

Research into potential implications of climate change on flood hazard has made significant progress over the past decade, yet efforts to translate this research into practical guidance for flood estimation remain in their infancy. In this commentary, we address the question: how best can practical flood guidance be modified to incorporate the additional uncertainty due to climate change? We begin by summarizing the physical causes of changes in flooding and then discuss common methods of design flood estimation in the context of uncertainty. We find that although climate science operates across aleatory, epistemic and deep uncertainty, engineering practitioners generally only address aleatory uncertainty associated with natural variability through standards-based approaches. A review of existing literature and flood guidance reveals that although research efforts in hydrology do not always reflect the methods used in flood estimation, significant progress has been made with many jurisdictions around the world now incorporating climate change in their flood guidance. We conclude that the deep uncertainty that climate change brings signals a need to shift towards more flexible design and planning approaches, and future research effort should focus on providing information that supports the range of flood estimation methods used in practice. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Towards advancing scientific knowledge of climate change impacts on short-duration rainfall extremes.

A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows and potential for these to worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project of the GEWEX (Global Energy and Water Exchanges) Hydroclimatology Panel. Here, we summarize the main findings so far and suggest future directions for research, including: the benefits of convection-permitting climate modelling; towards understanding mechanisms of change; the usefulness of temperature-scaling relations; towards detecting and attributing extreme rainfall change; and the need for international coordination and collaboration. Evidence suggests that the intensity of long-duration (1 day+) heavy precipitation increases with climate warming close to the Clausius-Clapeyron (CC) rate (6-7% K-1), although large-scale circulation changes affect this response regionally. However, rare events can scale at higher rates, and localized heavy short-duration (hourly and sub-hourly) intensities can respond more strongly (e.g. 2 × CC instead of CC). Day-to-day scaling of short-duration intensities supports a higher scaling, with mechanisms proposed for this related to local-scale dynamics of convective storms, but its relevance to climate change is not clear. Uncertainty in changes to precipitation extremes remains and is influenced by many factors, including large-scale circulation, convective storm dynamics andstratification. Despite this, recent research has increased confidence in both the detectability and understanding of changes in various aspects of intense short-duration rainfall. To make further progress, the international coordination of datasets, model experiments and evaluations will be required, with consistent and standardized comparison methods and metrics, and recommendations are made for these frameworks. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Uncovering the role of the East Asian jet stream and heterogeneities in atmospheric rivers affecting the western United States.

Atmospheric rivers (ARs) exert major socioeconomic repercussions along the US West Coast by inducing heavy rainfall, flooding, strong winds, and storm surge. Despite the significant societal and economic repercussions of these storms, our understanding of the physical drivers responsible for their interannual variability is limited, with different climate modes identified as possible mechanisms. Here we show that the Pacific-Japan (PJ) teleconnections/patterns and the East Asian subtropical jet (EASJ) exhibit a strong linkage with the total frequency of ARs making landfall over the western United States, much stronger than the other potential climate modes previously considered. While our findings indicate that the PJ pattern and EASJ are the most relevant climate modes driving the overall AR activity, we also uncover heterogeneities in AR tracks. Specifically, we show that not all ARs making landfall along the West Coast come from a single population, but rather that it is possible to stratify these storms into three clusters. While the PJ pattern and EASJ are major drivers of AR activity for two clusters, the cluster that primarily affects the US Southwest is largely driven by other climate modes [El Niño Southern Oscillation (ENSO), the Atlantic meridional mode (AMM), the Pacific-North America (PNA) teleconnection pattern, and the North Pacific Gyre Oscillation (NPGO)]. Therefore, important regional differences exist and this information can substantially enhance our ability to predict and prepare for these storms and their impacts.

Extreme rainfall activity in the Australian tropics reflects changes in the El Niño/Southern Oscillation over the last two millennia.

Assessing temporal variability in extreme rainfall events before the historical era is complicated by the sparsity of long-term "direct" storm proxies. Here we present a 2,200-y-long, accurate, and precisely dated record of cave flooding events from the northwest Australian tropics that we interpret, based on an integrated analysis of meteorological data and sediment layers within stalagmites, as representing a proxy for extreme rainfall events derived primarily from tropical cyclones (TCs) and secondarily from the regional summer monsoon. This time series reveals substantial multicentennial variability in extreme rainfall, with elevated occurrence rates characterizing the twentieth century, 850-1450 CE (Common Era), and 50-400 CE; reduced activity marks 1450-1650 CE and 500-850 CE. These trends are similar to reconstructed numbers of TCs in the North Atlantic and Caribbean basins, and they form temporal and spatial patterns best explained by secular changes in the dominant mode of the El Niño/Southern Oscillation (ENSO), the primary driver of modern TC variability. We thus attribute long-term shifts in cyclogenesis in both the central Australian and North Atlantic sectors over the past two millennia to entrenched El Niño or La Niña states of the tropical Pacific. The influence of ENSO on monsoon precipitation in this region of northwest Australia is muted, but ENSO-driven changes to the monsoon may have complemented changes to TC activity.

Soybean Area and Baseflow Driving Nitrate in Iowa's Raccoon River.

Improved understanding of the drivers of stream nitrate is necessary to improve water quality. This is particularly true for Iowa, a large contributor to Mississippi River Basin nitrate loads. Here, we focus on the Raccoon River at Des Moines, Iowa, and develop statistical models to describe the monthly (from March to August) nitrate concentrations in terms of eight drivers representing monthly climate, monthly hydrology, and yearly cropping practices. We consider six two-parameter distributions, linear and nonlinear dependencies between the predictors, and the distributions' parameters. Model selection was performed by penalizing more complex models. Our results show that the Weibull and Gumbel distributions are the only two selected distributions. Baseflow and the previous year's soybean [ (L.) Merr.] area were the two predictors most often identified as important. Our modeling results imply that increases in soybean area have led to increasing nitrate concentrations. Moreover, nitrate concentrations are related to baseflow in a nonlinear way, with effects strongest when baseflow is near or below the average condition. Additional relevant predictors were precipitation and, to a lesser extent, temperature. We conclude that best management practices and improved conservation targeting soybean in a corn ( L.)-soybean rotation will improve water quality in this artificially drained system.

Assessing the relation of USDA conservation expenditures to suspended sediment reductions in an Iowa watershed.

From 1936 to 2010, U.S. Department of Agriculture (USDA) agencies spent $293.7 billion (value adjusted for inflation at the 2009 level) on conservation programs. Of these expenditures, $75.2 billion (26%) were allocated for technical assistance (TA; it is related to costs associated with USDA field staff providing their expert advice to farmers) and $218.5 billion (74%) for financial assistance (FA; monetary incentives for farmers to adopt conservation programs). A major environmental goal of these programs was to reduce soil erosion and sediment leaving the land. In this study, we correlate expenditures on FA and TA programs to a unique long (1937-2009) record of total suspended solids (TSS) and sediment load (SL) for the Raccoon River at Van Meter, Iowa. Study results suggest that three predictors (rainfall, TA and FA) are important in explaining the temporal changes in annual TSS and SL and provide evidence that USDA expenditures helped reduce TSS and SL in the Raccoon River. TA was more effective than FA in reducing TSS levels in the watershed. Our empirical model represents an initial, broad-scale attempt to correlate conservation expenditures to a specific water quality outcome, although more work is needed to disentangle the impacts associated with other unexplored factors.

Higher emissions scenarios lead to more extreme flooding in the United States.

Understanding projected changes in flooding across the contiguous United States (CONUS) helps increase our capability to adapt to and mitigate against this hazard. Here, we assess future changes in flooding across CONUS using outputs from 28 global climate models and four scenarios of the Coupled Model Intercomparison Project Phase 6. We find that CONUS is projected to experience an overall increase in flooding, especially under higher emission scenarios; there are subregional differences, with the Northeast and Southeast (Great Plains of the North and Southwest) showing higher tendency towards increasing (decreasing) flooding due to changes in flood processes at the seasonal scale. Moreover, even though trends may not be detected in the historical period, these projected future trends highlight the current needs for incorporating climate change in the future infrastructure designs and management of the water resources.

Precipitation inequality exacerbates streamflow inequality, but dams moderate it.

Access to clean water is a fundamental human right, yet millions worldwide face the dire consequences of water scarcity and inadequate sanitation. Water inequality, characterized by disparities in access and availability of water resources, has emerged as a critical global challenge with far-reaching social, economic, and environmental implications. Using a globally representative observational streamflow dataset and Gini coefficients, this study investigates how streamflow inequality, which has a large impact on inequality of water availability, varies spatially and temporally, and its relationship with different underlying catchment characteristics. This study finds that watersheds in arid climates exhibit a higher degree of streamflow inequality than polar and equatorial ones. Africa experiences the highest streamflow inequality, followed by Australia, while South America experiences relatively lower streamflow inequality. Around 19.6 % of the catchments in Australia display an increasing trend in streamflow inequality, pointing to worsening conditions. Conversely, South America experiences a decreasing trend in streamflow inequality in 18.3 % of its catchments during the same period. It is also found that a more evenly distributed precipitation within the catchment and higher dam storage capacity corresponds to more evenly distributed streamflow availability throughout the year. This study enhances our understanding of streamflow inequality worldwide, which will aid policy formulation to foster sustainable development.

Bayesian negative binomial regression model with unobserved covariates for predicting the frequency of north atlantic tropical storms.

Predicting the annual frequency of tropical storms is of interest because it can provide basic information towards improved preparation against these storms. Sea surface temperatures (SSTs) averaged over the hurricane season can predict annual tropical cyclone activity well. But predictions need to be made before the hurricane season when the predictors are not yet observed. Several climate models issue forecasts of the SSTs, which can be used instead. Such models use the forecasts of SSTs as surrogates for the true SSTs. We develop a Bayesian negative binomial regression model, which makes a distinction between the true SSTs and their forecasts, both of which are included in the model. For prediction, the true SSTs may be regarded as unobserved predictors and sampled from their posterior predictive distribution. We also have a small fraction of missing data for the SST forecasts from the climate models. Thus, we propose a model that can simultaneously handle missing predictors and variable selection uncertainty. If the main goal is prediction, an interesting question is should we include predictors in the model that are missing at the time of prediction? We attempt to answer this question and demonstrate that our model can provide gains in prediction.

Climate change projected to impact structural hillslope connectivity at the global scale.

Structural connectivity describes how landscapes facilitate the transfer of matter and plays a critical role in the flux of water, solutes, and sediment across the Earth's surface. The strength of a landscape's connectivity is a function of climatic and tectonic processes, but the importance of these drivers is poorly understood, particularly in the context of climate change. Here, we provide global estimates of structural connectivity at the hillslope level and develop a model to describe connectivity accounting for tectonic and climate processes. We find that connectivity is primarily controlled by tectonics, with climate as a second order control. However, we show climate change is projected to alter global-scale connectivity at the end of the century (2070 to 2100) by up to 4% for increasing greenhouse gas emission scenarios. Notably, the Ganges River, the world's most populated basin, is projected to experience a large increase in connectivity. Conversely, the Amazon River and the Pacific coast of Patagonia are projected to experience the largest decreases in connectivity. Modeling suggests that, as the climate warms, it could lead to increased erosion in source areas, while decreased rainfall may hinder sediment flow downstream, affecting landscape connectivity with implications for human and environmental health.

On the compounding of nitrate loads and discharge.

Compound extremes can arise from combinations of multiple drivers, and even non-extreme univariate events can combine to cause large societal and economic impacts. In this study, we model multivariate compound events focusing on the potential interaction of nitrate loads and discharge. We use daily discharge and nitrate loads at seven US Geological Survey sites in the state of Iowa. We apply a two-sided conditional sampling method, which derives two joint probabilities conditioning on discharge and nitrate loads, respectively. Our results show that there is a dependence between discharge and nitrate loads, which can be described through bivariate modeling and the subsequent estimation of their joint annual exceedance probabilities (AEPs). The magnitude of the joint AEPs to extreme discharge and extreme nitrate loads exhibit different structures across the different sites, highlighting the different roles of these two quantities in controlling their compounding. In examining the ranges in design values for a given AEP, we found that the largest variability in highly likely values was generally associated with high agricultural intensity, high hog density, and fertilizer expenditures.

Sensitivity of northwest Australian tropical cyclone activity to ITCZ migration since 500 CE.

Tropical cyclones (TCs) regularly form in association with the intertropical convergence zone (ITCZ), and thus, its positioning has implications for global TC activity. While the poleward extent of the ITCZ has varied markedly over past centuries, the sensitivity with which TCs responded remains poorly understood from the proxy record, particularly in the Southern Hemisphere. Here, we present a high-resolution, composite stalagmite record of ITCZ migrations over tropical Australia for the past 1500 years. When integrated with a TC reconstruction from the Australian subtropics, this time series, along with downscaled climate model simulations, provides an unprecedented examination of the dependence of subtropical TC activity on meridional shifts in the ITCZ. TCs tracked the ITCZ at multidecadal to centennial scales, with a more southward position enhancing TC-derived rainfall in the subtropics. TCs may play an increasingly important role in Western Australia's moisture budgets as subtropical aridity increases due to anthropogenic warming.

Classification of flood-generating processes in Africa.

River flooding has large societal and economic impacts across Africa. Despite the importance of this topic, little is known about the main flood generating mechanisms in Africa. This study is based on 13,815 flood events that occurred between 1981 and 2018 in 529 catchments. These flood events are classified to identify the different flood drivers: excess rains, long rains and short rains. Out of them, excess rains on saturated soils in Western Africa, and long rains for catchments in Northern and Southern Africa, are the two dominant mechanisms, contributing to more than 75% of all flood events. The aridity index is strongly related to the spatial repartition of the different flood generating processes showing the climatic controls on floods. Few significant changes were detected in the relative importance of these drivers over time, but the rather short time series available prevent a robust assessment of flood driver changes in most catchments. The major implication of these results is to underline the importance of soil moisture dynamics, in addition to rainfall, to analyze the evolution of flood hazards in Africa.

Development of statistical models for estimating daily nitrate load in Iowa.

There is an ongoing need to increase our understanding of the sources and timing of stream nitrate loads across agricultural watersheds in Iowa as water quality improvement strategies are implemented. The goal of this study was to model the relationship between nitrate load and the two components of streamflow (i.e., baseflow and stormflow) to quantify in-stream nitrate patterns and develop a new method for estimating loads on days when monitoring data are not available. We analyzed eight watersheds in Iowa that had long-term water quality data where grab samples have been collected from 1987 to 2019. Four regression models were developed that related daily nitrate load to daily baseflow, stormflow, and streamflow discharge. The first model considered baseflow as a predictor, the second model used stormflow, the third model included both baseflow and stormflow as two different covariates, and the final model used total streamflow (unseparated). For all eight watersheds, the baseflowstormflow models had the highest correlation coefficients, which indicates that both components are necessary and together improve nitrate load estimates. While baseflow models estimated lower nitrate loads better, stormflow models captured the variability associated with larger loads. In addition, streamflow models tended to overestimate large nitrate loads. This simple modeling framework can be used to calculate daily, monthly and annual nitrate loads. Delineating nitrate loads between stormflow and baseflow can help identify differences in nitrate sources for nutrient reduction and remediation.

Changes in Atlantic major hurricane frequency since the late-19th century.

Atlantic hurricanes are a major hazard to life and property, and a topic of intense scientific interest. Historical changes in observing practices limit the utility of century-scale records of Atlantic major hurricane frequency. To evaluate past changes in frequency, we have here developed a homogenization method for Atlantic hurricane and major hurricane frequency over 1851-2019. We find that recorded century-scale increases in Atlantic hurricane and major hurricane frequency, and associated decrease in USA hurricanes strike fraction, are consistent with changes in observing practices and not likely a true climate trend. After homogenization, increases in basin-wide hurricane and major hurricane activity since the 1970s are not part of a century-scale increase, but a recovery from a deep minimum in the 1960s-1980s. We suggest internal (e.g., Atlantic multidecadal) climate variability and aerosol-induced mid-to-late-20th century major hurricane frequency reductions have probably masked century-scale greenhouse-gas warming contributions to North Atlantic major hurricane frequency.

Projected changes in flooding: a continental U.S. perspective.

Our study focuses on the projected changes in annual and seasonal maximum daily runoff (used as a proxy for flooding) across the continental United States based on outputs from eight global climate models (GCMs) from the Sixth Coupled Model Intercomparison Project (CMIP6). Analyses performed at the regional scale indicate that the GCMs are generally able to reproduce the observed changes in runoff extremes, especially at the seasonal scale, with no single model that outperforms the others across the different seasons and regions. Overall, annual maximum daily runoff is projected to increase during the 21st century, especially in large areas of the southeastern United States and Pacific Northwest, and to decrease in the Rocky Mountains and the northern Great Plains. The largest changes in extremes are projected to be in winter and spring, with a more muted signal for summer and fall.