Stephen B. Shaw

The Relationship between Extreme Hourly Precipitation and Surface Temperature in Different Hydroclimatic Regions of the United States

Abstract In a changing climate, there is an interest in predicting how extreme rainfall events may change. Using historical records, several recent papers have evaluated whether high-intensity precipitation scales with temperature in accordance with the Clausius–Clapeyron (C–C) relationship. For varying locations in Europe, these papers have identified both super C–C relationships as well as a breakdown of the C–C relationship under dry conditions. In this paper, a similar analysis is carried out for the United States using data from 14 weather stations clustered in four different hydroclimatic regions: the coastal northeast, interior New York, the central plains, and the western plains. In all regions except interior New York state, 99th percentile 1-h precipitation generally followed the C–C relation. In interior New York, there was evidence that intensity scaled with a super C–C relationship. For the 99.9th percentile precipitation, interior New York displayed some moderate evidence of a super C–C rela...

Biocolloid retention in partially saturated soils

Unsaturated soils are considered excellent filters for preventing the transport of pathogenic biocolloids to groundwater, but little is known about the actual mechanisms of biocolloid retention. To obtain a better understanding of these processes, a number of visualization experiments were performed and analyzed.

Evaluating Urban Pollutant Buildup/Wash-Off Models Using a Madison, Wisconsin Catchment

Buildup/wash-off (BUWO) models are widely used to estimate pollutant export from urban and suburban watersheds. Here, we propose that the mass of washed-off particulate during a storm event is insensitive to the time between storm events (the traditional predictor of particulate accumulation in BUWO models). Our analysis employed USGS data of total suspended solids and discharge data for nonsnow events in a 9.4-km 2 suburban catchment in Madison, Wis. Kinetic energy of rainfall was calculated using National Weather Service NEXRAD radar reflectivity. A regression analysis found that storm event runoff volume and rainfall kinetic energy explained 81% of the variability in event particulate load; volume alone explained 69% of the variability in event loads. Time between storm events was not significant. Additionally, we simulated storm event particulate loads using a BUWO model and a model assuming a constant mass available for wash-off. Both models produced very similar predictions over a range of parameterizations, suggesting that buildup models could perhaps be simplified under many circumstances.

A U.S.‐based analysis of the ability of the Clausius‐Clapeyron relationship to explain changes in extreme rainfall with changing temperature

Numerous papers have shown links between >99th percentile hourly precipitation and daily temperature (Pextreme versus T), often explained using the Clausius-Clapeyron (CC) relationship. The CC relationship predicts an approximately 7% increase in precipitation intensity per degree celsius. However, recent analyses indicate that the Pextreme versus T rate can be larger than the CC prediction. In this work, we analyze the Pextreme versus T rate with an automated method across the contiguous U.S. using station data aggregated on a 161 km grid. To evaluate controls on Pextreme versus T, we isolate convective storms to evaluate whether greater than CC rates are due to the transition between storm types or are a feature of convective storms at high T. We repeat the analysis using dew point to assess whether T control on extreme P is indeed a matter of moisture availability. When evaluated using both T and dew point, the northeastern U.S. is most likely to exhibit a greater than predicted Pextreme versus T rate (57% of the region when using T). At 56% of these points, the > CC rates appeared to occur entirely because of a transition between frontal and convective storms. At 30% of these sites, a greater than CC relationship appeared to occur entirely because of greater than CC scaling in convective intensity. At 11% of sites neither was found to be significant, and at 3% both were found to contribute significantly. This analysis suggests that > CC scaling is not prevalent everywhere in the contiguous U.S., and in regions where it does occur, it can be due to multiple causes.

Separating heat stress from moisture stress: analyzing yield response to high temperature in irrigated maize

Several recent studies have indicated that high air temperatures are limiting maize (Zea mays L.) yields in the US Corn Belt and project significant yield losses with expected increases in growing season temperatures. Further work has suggested that high air temperatures are indicative of high evaporative demand, and that decreases in maize yields which correlate to high temperatures and vapor pressure deficits (VPD) likely reflect underlying soil moisture limitations. It remains unclear whether direct high temperature impacts on yields, independent of moisture stress, can be observed under current temperature regimes. Given that projected high temperature and moisture may not co-vary the same way as they have historically, quantitative analyzes of direct temperature impacts are critical for accurate yield projections and targeted mitigation strategies under shifting temperature regimes. To evaluate yield response to above optimum temperatures independent of soil moisture stress, we analyzed climate impacts on irrigated maize yields obtained from the National Corn Growers Association (NCGA) corn yield contests for Nebraska, Kansas and Missouri. In irrigated maize, we found no evidence of a direct negative impact on yield by daytime air temperature, calculated canopy temperature, or VPD when analyzed seasonally. Solar radiation was the primary yield-limiting climate variable. Our analyses suggested that elevated night temperature impacted yield by increasing rates of phenological development. High temperatures during grain-fill significantly interacted with yields, but this effect was often beneficial and included evidence of acquired thermo-tolerance. Furthermore, genetics and management—information uniquely available in the NCGA contest data—explained more yield variability than climate, and significantly modified crop response to climate. Thermo-acclimation, improved genetics and changes to management practices have the potential to partially or completely offset temperature-related yield losses in irrigated maize.

Improving risk estimates of runoff producing areas: formulating variable source areas as a bivariate process.

Predicting runoff producing areas and their corresponding risks of generating storm runoff is important for developing watershed management strategies to mitigate non-point source pollution. However, few methods for making these predictions have been proposed, especially operational approaches that would be useful in areas where variable source area (VSA) hydrology dominates storm runoff. The objective of this study is to develop a simple approach to estimate spatially-distributed risks of runoff production. By considering the development of overland flow as a bivariate process, we incorporated both rainfall and antecedent soil moisture conditions into a method for predicting VSAs based on the Natural Resource Conservation Service-Curve Number equation. We used base-flow immediately preceding storm events as an index of antecedent soil wetness status. Using nine sub-basins of the Upper Susquehanna River Basin, we demonstrated that our estimated runoff volumes and extent of VSAs agreed with observations. We further demonstrated a method for mapping these areas in a Geographic Information System using a Soil Topographic Index. The proposed methodology provides a new tool for watershed planners for quantifying runoff risks across watersheds, which can be used to target water quality protection strategies.

Using simple data experiments to explore the influence of non-temperature controls on maize yields in the mid-West and Great Plains

Several recent papers have suggested that high temperatures are associated with reduced maize yields. To better understand the conditions under which this association may occur, we conduct two analyses on maize yields from 1981 to 2011 for 100 U.S. counties with large areas planted to maize in the mid-West and Great Plains. First, we compare statistical yield models in non-irrigated and extensively irrigated counties, after carefully evaluating the degree of crop irrigation in a county and selecting only counties with no irrigation or extensive irrigation. We find that yields in extensively irrigated counties have minimal dependency on temperature factors in the regression model. Second, we compare statistical yield models across non-irrigated counties using data sets with and without years with known extreme moisture anomalies. We find that for Minnesota, Central Iowa, and Northern Illinois, the sufficiency of yield models based only on temperature factors are highly leveraged by the few years with extreme moisture anomalies. In western Iowa and much of Illinois, temperature factors consistently explain a moderate amount of yield variability, even when extreme moisture anomalies are removed. In general, these findings suggest that in many regions maize yields are not solely dependent on temperature and that other factors (e.g. humidity, soil moisture, flooding) likely need to be accounted for to improve statistical yield models and to make accurate projections of maize yield in a changing climate.

Identifying spatial clustering in change points of streamflow across the contiguous U.S. between 1945 and 2009

Much of the work investigating sudden changes in streamflow in the U.S. has used only a small subset of all available gage data and has identified only a single change point in each gages period of record. In this paper, we apply a change point detection and clustering algorithm that uses all U.S. Geological Survey flow gages with near-continuous records, detects multiple change points in annual streamflow, and groups change points into geographic clusters which are not predefined by any political or hydrologic boundaries. We identify 17 spatially distinct change point clusters, 13 of which are related to concurrent changes in precipitation. Several geographic regions display multiple clusters, indicating multiple change points in time. The presence of abrupt changes in streamflow suggests that natural variability in the climate signal may be dominating observed streamflow variations in the last 60 years in many locations in the contiguous U.S.

Landscape Features Associated With Blacklegged Tick (Acari: Ixodidae) Density and Tick-Borne Pathogen Prevalence at Multiple Spatial Scales in Central New York State

Abstract Blacklegged ticks (Ixodes scapularis Say, Acari: Ixodidae) are the most commonly encountered and medically relevant tick species in New York State (NY) and have exhibited recent geographic range expansion. Forests and adjacent habitat are important determinants of I. scapularis density and may influence tick-borne pathogen prevalence. We examined how percent forest cover, dominant land cover type, and habitat type influenced I. scapularis nymph and adult density, and associated tick-borne pathogen prevalence, in an inland Lyme-emergent region of NY. I. scapularis nymphs and adults were collected from edge and wooded habitats using tick drags at 16 sites in Onondaga County, NY in 2015 and 2016. A subsample of ticks from each site was tested for the presence of Borrelia burgdorferi, Borrelia miyamotoi, Anaplasma phagocytophilum, and Babesia microti using a novel multiplex real-time polymerase chain reaction (PCR) assay, and deer tick virus using reverse transcription–PCR. Habitat type (wooded versus edge) was an important determinant of tick density; however, percent forest cover had little effect. B. burgdorferi was the most commonly detected pathogen and was present in ticks from all sites. Ba. microti and deer tick virus were not detected. Habitat type and dominant land cover type were not significantly related to B. burgdorferi presence or prevalence; however, ticks infected with A. phagocytophilum and B. miyamotoi were collected more often in urban environments. Similarity between B. burgdorferi prevalence in Onondaga County and hyperendemic areas of southeastern NY indicates a more rapid emergence than expected in a relatively naive region. Possible mechanistic processes underlying these observations are discussed.

Does an upper limit to river water temperature apply in all places

Hydrological Processes. 2017;31:3729–3739. Abstract There remains continued use of non‐linear, logistic regression models for predicting water temperature from air temperature. A dominant feature of these non‐linear models is an upper bound on river water temperature. This upper bound is often attributed to a large increase in evaporative cooling at high air temperatures, but the exact conditions under which such an increase may occur have not been thoroughly explored. To better understand the appropriateness of the non‐linear model for predicting river water temperatures, it is essential to understand the physical basis for the upper bound and when it should and should not be included in the statistical model. This paper applies and validates an energy balance model against 8 river systems spread across different climate regions of the United States. The energy balance model is then used to develop a diagram relating vapour pressure deficit and air temperature to water temperature. With knowledge of present or future vapour pressure deficit (difference between saturation and actual vapour content in the atmosphere) conditions in a given climate, the diagram can be used to predict the likelihood of an upper bound in the air–water temperature relationship. This investigation offers a fundamental physical explanation of the most appropriate form of statistical models that should be used for predicting future water temperature from air temperature in different geographic regions with different climate conditions. In general, climatic regions that have only a slight increase in vapour pressure deficit with increasing air temperature (typically humid regions) would not be expected to have an upper bound. Conversely, climatic regions in which vapour pressure deficit sharply increases with increasing air temperature (typically arid regions) would be expected to have an upper bound.