Explore the vast range of titles available.

This paper undertakes a hydrometeorological analysis of flood events in the central United States. Vertically integrated horizontal water vapor transport over 1979–2011 is calculated in the ECMWF Interim Re-Analysis (ERA-Interim) and used in an algorithm to identify episodes of high moisture transport, or atmospheric rivers (ARs), over the central United States. The AR events are almost evenly divided among the seasons (143 during the winter, 144 during the spring, and 124 during the fall), with a minimum (40) during the summer. The annual maxima (AM) floods from 1105 basins over the period 1980–2011 are used as a measure of the hydrologic impact of the AR events. Of these basins, 470 (or 42.5%) had more than 50% of their AM floods linked to ARs. Furthermore, 660 of the 1105 basins (59.7%) had 5 or more of their top 10 AM floods related to ARs, indicating that ARs control the upper tail of the flood peak distribution over large portions of the study area. The seasonal composite average of mean sea level pressure anomalies associated with the ARs shows a trough located over the central United States and a ridge over the U.S. East Coast, leading to southerly winds and the advection of moisture over the study region. Based on the findings of this study, ARs are a major flood agent over the central United States.

Precipitation is a key component of the global water cycle and plays a crucial role in flooding, droughts, and water supply. One way to manage its socioeconomic effects is based on precipitation forecasts from numerical weather prediction (NWP) models, and an important step to improve precipitation forecasts is by diagnosing NWP biases. In this study, we investigate the biases in precipitation forecasts from the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS). Using the IFS control forecast from 12 June 2019 to 11 June 2020 at 5219 stations globally, we show that in each of the boreal winter and summer half years, the IFS 1) has an average global wet bias and 2) displays similar bias patterns for forecasts starting at 0000 and 1200 UTC and across forecast days 1–5. These biases are dependent on observed (climatological) precipitation; stations with low observed precipitation have an IFS wet bias, while stations with high observed precipitation have an IFS dry bias. Southeast Asia has a wet bias of 1.61 mm day−1 (in boreal summer) and over the study period the precipitation is overestimated by 31.0% on forecast day 3. This is the hydrological signature of several hypothesized processes including issues specifying the IFS snowpack over the Tibetan Plateau, which may affect the mei-yu front. These biases have implications for IFS land–atmosphere feedbacks, river discharge, and for ocean circulation in the Southeast Asia region. Reducing these biases could lead to more accurate forecasts of the global water cycle.

Daily precipitation in California has been projected to become less frequent even as precipitation extremes intensify, leading to uncertainty in the overall response to climate warming. Precipitation extremes are historically associated with Atmospheric Rivers (ARs). Sixteen global climate models are evaluated for realism in modeled historical AR behavior and contribution of the resulting daily precipitation to annual total precipitation over Western North America. The five most realistic models display consistent changes in future AR behavior, constraining the spread of the full ensemble. They, moreover, project increasing year-to-year variability of total annual precipitation, particularly over California, where change in total annual precipitation is not projected with confidence. Focusing on three representative river basins along the West Coast, we show that, while the decrease in precipitation frequency is mostly due to non-AR events, the increase in heavy and extreme precipitation is almost entirely due to ARs. This research demonstrates that examining meteorological causes of precipitation regime change can lead to better and more nuanced understanding of climate projections. It highlights the critical role of future changes in ARs to Western water resources, especially over California.

Atmospheric rivers (ARs) have significant hydrometeorological impacts on the U.S. West Coast. This study presents the connection between the characteristics of large-scale Rossby wave breaking (RWB) over the eastern North Pacific and the regional-scale hydrological impacts associated with landfalling ARs on the U.S. West Coast (36°–49°N). ARs associated with RWB account for two-thirds of the landfalling AR events and >70% of total AR-precipitation in the winter season. The two regimes of RWB—anticyclonic wave breaking (AWB) and cyclonic wave breaking (CWB)—are associated with different directions of the vertically integrated water vapor transport (IVT). AWB-ARs impinge in a more westerly direction on the coast whereas CWB-ARs impinge in a more southwesterly direction. Most of the landfalling ARs along the northwestern coast of the United States (states of Washington and Oregon) are AWB-ARs. Because of their westerly impinging angles when compared to CWB-ARs, AWBARs arrive more orthogonally to the western Cascades and more efficiently transform water vapor into precipitation through orographic lift than CWB-ARs. Consequently, AWB-ARs are associated with the most extreme streamflows in the region. Along the southwest coast of the United States (California), the southwesterly impinging angles of CWB-ARs are more orthogonal to the local topography. Furthermore, the southwest coast CWB-ARs have more intense IVT. Consequently, CWB-ARs are associated with the most intense precipitation. As a result, most of the extreme streamflows in southwest coastal basins are associated with CWB-ARs. In summary, depending on the associated RWB type, ARs impinge on the local topography at a different angle and have a different spatial signature of precipitation and streamflow.

Widespread flooding occurred across northwest Europe during the winter of 2013/14, resulting in large socioeconomic damages. In the historical record, extreme hydrological events have been connected with intense water vapour transport. Here we show that water vapour transport has higher medium-range predictability compared with precipitation in the winter 2013/14 forecasts from the European Centre for Medium-Range Weather Forecasts. Applying the concept of potential predictability, the transport is found to extend the forecast horizon by 3 days in some European regions. Our results suggest that the breakdown in precipitation predictability is due to uncertainty in the horizontal mass convergence location, an essential mechanism for precipitation generation. Furthermore, the predictability increases with larger spatial averages. Given the strong association between precipitation and water vapour transport, especially for extreme events, we conclude that the higher transport predictability could be used as a model diagnostic to increase preparedness for extreme hydrological events. Extreme winter flooding has caused devastation across Europe in recent years, highlighting the need for improved forecasts. Here, the authors show that the use of water vapour transport, rather than precipitation in weather prediction models, can extend the forecast horizon by as much as 3 days.

Damage from flooding in the winter and fall seasons has been widespread in the United Kingdom (UK) and Western Europe over recent decades. Here we show that winter flood events in the UK are connected to Atmospheric Rivers (ARs), narrow ribbons along which a large flux of moisture is transported from the subtropics to the mid‐latitudes. Combining river flow records with rainfall measurements, satellite data and model simulations, we demonstrate that ARs occur simultaneously with the 10 largest winter flood events since 1970 in a range of British river basins, suggesting that ARs are persistently critical in explaining extreme winter flooding in the UK. Understanding the physical processes that determine the persistence of AR events will be of importance in assessing the risk of future flooding over north‐western Europe and other mid‐latitude regions. Key Points Linked a damaging UK flooding event with AR occurrence Linked persistent ARs with the top 10 floods in a range of UK basins Shown the atmospheric circulation that leads to AR occurrence in western Europe

Atmospheric Rivers (ARs), narrow plumes of enhanced moisture transport in the lower troposphere, are a key synoptic feature behind winter flooding in midlatitude regions. This article develops an algorithm which uses the spatial and temporal extent of the vertically integrated horizontal water vapor transport for the detection of persistent ARs (lasting 18 h or longer) in five atmospheric reanalysis products. Applying the algorithm to the different reanalyses in the vicinity of Great Britain during the winter half‐years of 1980–2010 (31 years) demonstrates generally good agreement of AR occurrence between the products. The relationship between persistent AR occurrences and winter floods is demonstrated using winter peaks‐over‐threshold (POT) floods (with on average one flood peak per winter). In the nine study basins, the number of winter POT‐1 floods associated with persistent ARs ranged from approximately 40 to 80%. A Poisson regression model was used to describe the relationship between the number of ARs in the winter half‐years and the large‐scale climate variability. A significant negative dependence was found between AR totals and the Scandinavian Pattern (SCP), with a greater frequency of ARs associated with lower SCP values. Key Points Develop algorithm for atmospheric river detection in atmospheric reanalyses Link identified ARs with largest winter floods in nine British basins Connect atmospheric river frequency with large‐scale climate variability

Precipitation is an essential climate variable and a fundamental part of the global water cycle. Given its importance to society, precipitation is often assessed in climate monitoring activities, such as in those led by the Copernicus Climate Change Service (C3S). To undertake these activities, C3S predominantly uses ERA5 reanalysis precipitation. Research has shown that short‐range forecasts for precipitation made from this reanalysis can provide valuable estimates of the actual (observed) precipitation in extratropical regions but can be less useful in the tropics. While some of these limitations will be reduced with future reanalyses because of the latest advancements, there is potentially a more immediate way to improve the precipitation estimate. This is to use the precipitation modelled in the Four‐Dimensional Variational (4D‐Var) data assimilation window of the reanalysis, and it is the aim of this study to evaluate this approach. Using observed 24‐h precipitation accumulations at 5637 stations from 2001 to 2020, results show that smaller root‐mean‐square errors (RMSEs) and mean absolute errors are generally found by using the ERA5 4D‐Var precipitation. For example, for all available days from 2001 to 2020, 87.5% of stations have smaller RMSEs. These improvements are driven by reduced random errors in the 4D‐Var precipitation because it is better constrained by observations, which are themselves sensitive to or influence precipitation. However, there are regions (e.g., Europe) where larger biases occur, and via the decomposition of the Stable Equitable Error in Probability Space score, this is shown to be because the 4D‐Var precipitation has a wetter bias on ‘dry’ days than the standard ERA5 short‐range forecasts. The findings also highlight that the 4D‐Var precipitation does improve the discrimination of ‘heavy’ observed events. In conclusion, an improved ERA5 precipitation estimate is largely obtainable, and these results could prove useful for C3S activities and for future reanalyses, including ERA6. This study uses 24‐h precipitation observations at 5637 stations from 2001 to 2020 to evaluate if the precipitation estimate from the ERA5 4D‐Var trajectories is more accurate than that from the standard short‐range forecasts. Results show that the 4D‐Var precipitation has (1) smaller root‐mean‐square errors at 87.5% of stations, (2) a wetter bias on ‘dry’ days, and (3) better discrimination of ‘heavy’ observed events. In conclusion, an improved ERA5 precipitation estimate is largely obtainable.

Robust and physically understandable responses of the global atmospheric water cycle to a warming climate are presented. By considering interannual responses to changes in surface temperature ( T ), observations and AMIP5 simulations agree on an increase in column integrated water vapor at the rate 7 %/K (in line with the Clausius–Clapeyron equation) and of precipitation at the rate 2–3 %/K (in line with energetic constraints). Using simple and complex climate models, we demonstrate that radiative forcing by greenhouse gases is currently suppressing global precipitation ( P ) at ∼−0.15 %/decade. Along with natural variability, this can explain why observed trends in global P over the period 1988−2008 are close to zero. Regional responses in the global water cycle are strongly constrained by changes in moisture fluxes. Model simulations show an increased moisture flux into the tropical wet region at 900 hPa and an enhanced outflow (of smaller magnitude) at around 600 hPa with warming. Moisture transport explains an increase in P in the wet tropical regions and small or negative changes in the dry regions of the subtropics in CMIP5 simulations of a warming climate. For AMIP5 simulations and satellite observations, the heaviest 5-day rainfall totals increase in intensity at ∼15 %/K over the ocean with reductions at all percentiles over land. The climate change response in CMIP5 simulations shows consistent increases in P over ocean and land for the highest intensities, close to the Clausius−Clapeyron scaling of 7 %/K, while P declines for the lowest percentiles, indicating that interannual variability over land may not be a good proxy for climate change. The local changes in precipitation and its extremes are highly dependent upon small shifts in the large-scale atmospheric circulation and regional feedbacks.

Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socioeconomic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date and still represents a major challenge. The capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group activity is used to examine TC response to idealized global-scale perturbations: the doubling of CO₂, uniform 2-K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO₂ scenario (on the order of 5% globally) and an increase in TC rainfall rates associated with a uniform increase of 2 K in SST (both alone and in combination with CO₂ doubling; on the order of 10%–20% globally).