The changing nature of flooding across the central United States

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58–1.0 Wm−2 a−1 over the 2000–2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3–5.0 × 10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000–2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear-sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm−2 a−1 at Goodwin Creek, MS, and +0.93 Wm−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990–2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

This study evaluates impacts of land use changes due to human settlement on regional summer climate over the central and western United States by performing 30‐day simulations during normal, drought, and flood years. Under current land use the simulated evapotranspiration increased noticeably over the central United States where grassland has been replaced by crops. Simulated evapotranspiration decreased slightly in the western United States. These changes produced wetter and cooler surface air over the central United States and slightly drier and warmer air over the western United States. Responses of surface fluxes and thus screen height variables to land use changes were consistent from year to year, whereas rainfall showed strong interannual variations because of the combination of various dynamic processes involved in precipitation. For normal year conditions, average evapotranspiration and rainfall under current land use increased by 18% and 8%, respectively, over the central United States, whereas they slightly decreased in the western United States. In both flood and drought years, current land use exhibited a rainfall increase in the western United States and a decrease over the central United States. The decrease of rainfall with increased evapotranspiration in the central United States was likely associated with weakening of the dynamic forcing needed to produce precipitation.

Extreme rainfall events (EREs) caused by convection are a major prediction challenge and can lead to deadly flash flooding. This study investigates EREs from 2003 to 2023 over the central and eastern United States using high‐resolution (4‐km) Stage IV precipitation analyses. EREs were defined where 12‐hr accumulations exceeded the 10‐year average recurrence interval thresholds. Summertime (June–August) EREs exhibited pronounced interannual variability, but with statistically significant increasing trends in annual frequency, particularly among those caused by mesoscale convective systems. Significant relationships were also found between summertime convective EREs over the central United States and enhanced poleward moisture transport, consistent with a westward expansion of the climatological North Atlantic Subtropical High. This relationship may aid in medium‐ and long‐range forecasting. However, the spatial scale of EREs often included localized or narrow bands of extreme accumulations, revealing significant challenges in the accurate representation of EREs in weather and climate models.

Simple phase schemes to predict seasonal climate based on leading ENSO indicators can be used to estimate the value of forecast information in agriculture and watershed management, but may be limited in predictive skill. Here, a simple two-tier statistical method is used to hindcast seasonal precipitation over the continental United States, and the resulting skill is compared with that of ENSO phase systems based on Niño-3 sea surface temperature anomaly (SSTA) and Southern Oscillation index (SOI) persistence. The two-tier approach first predicts Niño-3 winter season SSTA, and then converts those predictions to categorical precipitation hindcasts via a simple phase translation process. The hindcasting problem used to make these comparisons is relevant to winter wheat production over the central United States. Thus, given the state of seasonal SOI and Niño-3 indicators defined before August, the goal is to predict the tercile category of the following November–March precipitation. Generally, it was found that the methods based on either predicted or persisted winter Niño-3 conditions were skillful over areas where ENSO affects U.S. winter precipitation—that is, the Southeast and the Gulf Coast, Texas, the southern and central plains, the Southwest, Northwest, and the Ohio River valley—and that the two-tier approach based on predicted Niño-3 conditions was more likely to provide the best skill. Skill based on SOI persistence was generally lower over many of those regions and was insignificant over broad parts of the central and southwest United States, but did lead the other methods over the Ohio River valley and the northwest. A more restrictive test of leading hindcast skill showed that the skill advantages of the two-tier approach over the central and western United States were not substantial, and mainly highlighted SOI persistence’s lack of skill over the central United States and leading skill over the Ohio River valley. However, two-tier hindcasts based on neural-network-predicted Niño-3 SSTA were clearly more skillful than both ENSO phase methods over areas of the Southeast. It is suggested that the relative skill advantage of the two-tier approach may be due in part to the use of arbitrary thresholds in ENSO phase systems.

The potato psyllid, Bactericera cockerelli (Sulc) (Hemiptera: Triozidae), is a vector of the bacterium “Candidatus Liberibacter solanacearum,” the putative causal agent of potato zebra chip disease that has seriously affected the potato industry in the Central and Southwestern United States for the past decade. The 2011 potato growing season saw the first report of zebra chip disease in Washington, Oregon, and Idaho; however, B. cockerelli has been recorded in this region every season at least for the past 7 yr. Studies were conducted to determine the relationship between psyllids collected from the Pacific Northwest potatoes in 2011 and those from the Southwestern and Central United States. High resolution melting analysis of the B. cockerelli mitochondrial Cytochrome C Oxidase subunit I-like gene was conducted on over 450 psyllids collected from numerous locations across the Central and Western United States. Results suggest that at least three potato psyllid haplotypes exist in the United States, correlating to the Central, Western, and Northwestern United States geographical regions. The high resolution melting analysis results were subsequently supported by DNA sequencing data.

Comment on “A paradigm shift in understanding and quantifying the effects of forest harvesting on floods in snow environments” by Kim C. Green and Younes Alila

In this study, the Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to dynamically downscale output from the National Center for Atmospheric Research’s (NCAR’s) Community Climate System Model (CCSM) version 3 and the National Centers for Environmental Prediction (NCEP)–NCAR global reanalysis (NNRP). The latter is used for verification of late-twentieth-century climate simulations from the WRF. This analysis finds that the WRF is able to produce precipitation that is more realistic than that from its driving systems (the CCSM and NNRP). It also diagnoses potential issues with and differences between all of the simulations completed. Specifically, the magnitude of heavy 6-h average precipitation events, the frequency distribution, and the diurnal cycle of precipitation over the central United States are greatly improved. Projections from the WRF for late-twenty-first-century precipitation show decreases in average May–August (MJJA) precipitation, but increases in the intensity of both heavy precipitation events and rain in general when it does fall. A decrease in the number of 6-h periods with rainfall accounts for the overall decrease in average precipitation. The WRF also shows an increase in the frequency of very heavy to extreme 6-h average events, but a decrease in the frequency of all events lighter than those over the central United States. Overall, projections from this study suggest an increase in the frequency of both floods and droughts during the warm season in the central United States.

The contribution of atmospheric rivers to precipitation in Europe and the United States

The observed climate trends over the United States during 1950–2000 exhibit distinct seasonality and regionality. The surface air temperature exhibits a warming trend during winter, spring, and early summer and a modest countrywide cooling trend in late summer and fall, with the strongest warming occurring over the northern United States in spring. Precipitation trends are positive in all seasons, with the largest trend occurring over the central and southern United States in fall. This study investigates the causes of the seasonality and regionality of those trends, with a focus on the cooling and wetting trends in the central United States during late summer and fall. In particular, the authors examine the link between the seasonality and regionality of the climate trends over the United States and the leading patterns of sea surface temperature (SST) variability, including a global warming (GW) pattern and a Pacific decadal variability (PDV) pattern. A series of idealized atmospheric general circulation model (AGCM) experiments were performed forced by SST trends associated with these leading SST patterns, as well as the residual trend pattern (obtained by removing the GW and PDV contributions). The results show that the observed seasonal and spatial variations of the climate trends over the United States are to a large extent explained by changes in SST. Among the leading patterns of SST variability, the PDV pattern plays a prominent role in producing both the seasonality and regionality of the climate trends over the United States. In particular, it is the main contributor to the apparent cooling and wetting trends over the central United States. The residual SST trend, a manifestation of phase changes of the Atlantic multidecadal SST variation during 1950–2000, also exerts influences that show strong seasonality with important contributions to the central U.S. temperature and precipitation during the summer and fall seasons. In contrast, the response over the United States to the GW SST pattern is an overall warming with little seasonality or regional variation. These results highlight the important contributions of decadal and multidecadal variability in the Pacific and Atlantic in explaining the observed seasonality and regionality of the climate trends over the United States during the period of 1950–2000.

Changes in climate intensity and frequency, including extreme events, heavy and intense rainfall, have the greatest impact on water resource management and flood risk management. Significant changes in air temperature, precipitation, and humidity are expected in future due to climate change. The influence of climate change on flood hazards is subject to considerable uncertainty that comes from the climate model discrepancies, climate bias correction methods, flood frequency distribution, and hydrological model parameters. These factors play a crucial role in flood risk planning and extreme event management. With the advent of the Coupled Model Inter-comparison Project Phase 6, flood managers and water resource planners are interested to know how changes in catchment flood risk are expected to alter relative to previous assessments. We examine catchment-based projected changes in flood quantiles and extreme high flow events for Awash catchments. Conceptual hydrological models (HBV, SMART, NAM and HYMOD), three downscaling techniques (EQM, DQM, and SQF), and an ensemble of hydrological parameter sets were used to examine changes in peak flood magnitude and frequency under climate change in the mid and end of the century. The result shows that projected annual extreme precipitation and flood quantiles could increase substantially in the next several decades in the selected catchments. The associated uncertainty in future flood hazards was quantified using aggregated variance decomposition and confirms that climate change is the dominant factor in Akaki (C2) and Awash Hombole (C5) catchments, whereas in Awash Bello (C4) and Kela (C3) catchments bias correction types is dominate, and Awash Kuntura (C1) both climate models and bias correction methods are essential factors. For the peak flow quantiles, climate models and hydrologic models are two main sources of uncertainty (31% and 18%, respectively). In contrast, the role of hydrological parameters to the aggregated uncertainty of changes in peak flow hazard variable is relatively small (5%), whereas the flood frequency contribution is much higher than the hydrologic model parameters. These results provide useful knowledge for policy-relevant flood indices, water resources and flood risk control and for studies related to uncertainty associated with peak flood magnitude and frequency.

Understanding the spatial and temporal variability in fine mineral dust (FD, mineral aerosols with diameters less than 2.5 µm) and coarse aerosol mass (CM, mass of aerosols with diameters between 2.5 and 10 µm) is important for accurately characterizing and perhaps mitigating their environmental and climate impacts. The spatial and seasonal variability of ambient FD and CM was characterized at rural and remote sites across the United States for 2011–2014 using concentration and elemental chemistry data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) aerosol monitoring network. FD concentrations were highest (and had ≥50% contributions to PM2.5 mass) in the southwestern United States in spring and across the central and southeastern United States in summer (20–30% of PM2.5 mass). CM was highest across the Southwest and southern Great Plains in spring and central United States in spring, summer, and fall (≥70% contributions to PM10 mass). Similar FD and CM seasonal variability was observed near source regions in the Southwest, but a seasonal decoupling was observed in most other regions, suggesting the contribution of nonlocal sources of FD or perhaps non‐dust‐related CM. The seasonal and spatial variability in FD elemental ratios (calcium, iron, and aluminum) was fairly uniform across the West; however, in the eastern United States a shift in summer elemental composition indicated contributions from nonlocal source regions (e.g., North Africa). Finally, long‐term trend analyses (2000–2014) indicated increased FD concentrations during spring at sites across the Southwest and during summer and fall in the southeastern and central United States.

Landscape roses ( Rosa sp.) are popular flowering shrubs. Consumers are less willing or able to maintain landscape beds than in years past and require plants that are not only attractive, but well-adapted to regional climatic conditions, soil types, and disease and pest pressures. Marketing and distribution of rose cultivars occurs on a national level; therefore, it is difficult for U.S. consumers in the U.S. Department of Agriculture (USDA) Plant Hardiness Zones 3 to 5 to identify well-adapted, cold-hardy cultivars. Identifying suitable cultivars that have strong genetic resistance to pests and disease and that will tolerate temperature extremes without winter protection in the USDA Plant Hardiness Zones 3 to 5 is of tremendous value to consumers and retailers in northern states. Twenty landscape rose cultivars, primarily developed in north-central North America, were evaluated at five locations in the United States (three in the north-central United States, one in the central United States, and one in the south-central United States) using the low-input, multiyear Earth-Kind ® methodology. Six roses had ≥75% plant survival at the end of the study and were in the top 50% of performers for overall mean horticultural rating at each of the three north-central U.S. sites: ‘Lena’, ‘Frontenac’, ‘Ole’, ‘Polar Joy’, ‘Sunrise Sunset’, and ‘Sven’. Five of these six roses met the same criteria at the central United States (exception ‘Lena’) and the south-central United States (exception ‘Polar Joy’) sites. Cultivar, rating time, and their interaction were highly significant, and block effects were not significant for horticultural rating for all single-site analyses of variance. Significant positive correlations were found between sites for flower number, flower diameter, and overall horticultural rating. Significant negative correlations were found between flower number and diameter within each site and also between black spot ( Diplocarpon rosae ) lesion size from a previous study and overall horticultural rating for three of the five sites. Cane survival ratings were not significantly correlated with overall horticultural rating, suggesting some cultivars can experience severe winter cane dieback, yet recover and perform well. Data from this study benefit multiple stakeholders, including nurseries, landscapers, and consumers, with evidence-based regional cultivar recommendations and breeders desiring to identify regionally adapted parents.

On the unseasonal flooding over the Central United States during December 2015 and January 2016

Trends in flow-adjusted concentrations (indicators of anthropogenic changes) and observed concentrations (indicators of natural and anthropogenic changes) of total phosphorus and total nitrogen from 1993 to 2003 were evaluated in the eastern, central, and western United States by adapting the Regional Kendall trend test to account for seasonality and spatial correlation. The only significant regional trend was an increase in flow-adjusted concentrations of total phosphorus in the central United States, which corresponded to increases in phosphorus inputs from fertilizer in the region, particularly west of the Mississippi River. A similar upward regional trend in observed total phosphorus concentrations in the central United States was not found, likely because precipitation and runoff decreased during drought conditions in the region, offsetting the increased source loading on the land surface. A greater number of regional trends would have been significant if spatial correlation had been disregarded, indicating the importance of spatial correlation modifications in regional trend assessments when sites are not spatially independent.

On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States