Identifying Changes in Trends of Summer Air Temperatures of the USA High Plains

Change in climate variables, especially air temperature, can substantially impact water availability, use, management, allocation, and projections for rural and urban applications. This study presents analyses for detecting summer air temperature change by investigating trends of two separate climate-periods in the USA High Plains. Two trend periods, the reference period (1895–1930) and the warming period (1971–2006), were investigated using parametric and nonparametric methods. During the reference period, minimum air temperature (Tmin) was statistically stationary at a nonsignificant increasing rate of 0.02°C/year. However, from early 1970s, Tmin increased at a significant rate of 0.02°C/year. The maximum air temperature (Tmax) had a weaker warming signal than Tmin during the reference period. During the warming period, Tmax had a cooling trend at a nonsignificant rate of −0.004°C/year. About 22% of the High Plains had significant warming trends before 1930. Compared to the summers before 1930, the summer temperatures of the High Palins since the 1970s increased, on average, by 0.86°C. Overall, parametric methods lead to the conclusion that 50% of the study area experienced a significant warming trend in Tmin. In comparison, nonparametric methods indicated that 94% of the study area experienced a warming trend. Overall, in recent decades, summer average temperatures in the High Plains have been warming as compared to the early twentieth-century decades, and the warming is most likely driven primarily by increasing nighttime Tmin

The Effect of Land Cover/Land Use Changes on the Regional Climate of the USA High Plains

We present the detection of the signatures of land use/land cover (LULC) changes on the regional climate of the US High Plains. We used the normalized difference vegetation index (NDVI) as a proxy of LULC changes and atmospheric CO2 concentrations as a proxy of greenhouse gases. An enhanced signal processing procedure was developed to detect the signatures of LULC changes by integrating autoregression and moving average (ARMA) modeling and optimal fingerprinting technique. The results, which are representative of the average spatial signatures of climate response to LULC change forcing on the regional climate of the High Plains during the 26 years of the study period (1981–2006), show a significant cooling effect on the regional temperatures during the summer season. The cooling effect was attributed to probable evaporative cooling originating from the increasing extensive irrigation in the region. The external forcing of atmospheric CO2 was included in the study to suppress the radiative warming effect of greenhouse gases, thus, enhancing the LULC change signal. The results show that the greenhouse gas radiative warming effect in the region is significant, but weak, compared to the LULC change signal. The study demonstrates the regional climatic impact of anthropogenic induced atmospheric-biosphere interaction attributed to LULC change, which is an additional and important climate forcing in addition to greenhouse gas radiative forcing in High Plains region

On the Equality Assumption of Latent and Sensible Heat Energy Transfer Coefficients of the Bowen Ratio Theory for Evapotranspiration Estimations: Another Look at the Potential Causes of Inequalities

Evapotranspiration (ET) and sensible heat (H) flux play a critical role in climate change; micrometeorology; atmospheric investigations; and related studies. They are two of the driving variables in climate impact(s) and hydrologic balance dynamics. Therefore, their accurate estimate is important for more robust modeling of the aforementioned relationships. The Bowen ratio energy balance method of estimating ET and H diffusions depends on the assumption that the diffusivities of latent heat (KV) and sensible heat (KH) are always equal. This assumption is re-visited and analyzed for a subsurface drip-irrigated field in south central Nebraska. The inequality dynamics for subsurface drip-irrigated conditions have not been studied. Potential causes that lead KV to differ from KH and a rectification procedure for the errors introduced by the inequalities were investigated. Actual ET; H; and other surface energy flux parameters using an eddy covariance system and a Bowen Ratio Energy Balance System (located side by side) on an hourly basis were measured continuously for two consecutive years for a non-stressed and subsurface drip-irrigated maize canopy. Most of the differences between KV and KH appeared towards the higher values of KV and KH. Although it was observed that KV was predominantly higher than KH; there were considerable data points showing the opposite. In general; daily KV ranges from about 0.1 m2·s−1 to 1.6 m2·s−1; and KH ranges from about 0.05 m2·s−1 to 1.1 m2·s−1. The higher values for KV and KH appear around March and April; and around September and October. The lower values appear around mid to late December and around late June to early July. Hourly estimates of KV range between approximately 0 m2·s−1 to 1.8 m2·s−1 and that of KH ranges approximately between 0 m2·s−1 to 1.7 m2·s−1. The inequalities between KV and KH varied diurnally as well as seasonally. The inequalities were greater during the non-growing (dormant) seasons than those during the growing seasons. During the study period, KV was, in general, lesser than KH during morning hours and was greater during afternoon hours. The differences between KV and KH mainly occurred in the afternoon due to the greater values of sensible heat acting as a secondary source of energy to vaporize water. As a result; during the afternoon; the latent heat diffusion rate (KV) becomes greater than the sensible heat diffusion rate (KH). The adjustments (rectification) for the inequalities between eddy diffusivities is quite essential at least for sensible heat estimation, and can have important implications for application of the Bowen ratio method for estimation of diffusion fluxes of other gasses

Application of Remote Sensing for Quantifying and Mapping Surface Energy Fluxes in South Central Nebraska: Analyses with Respect to Field Measurements

Large-scale quantification of crop evapotranspiration (ETc) from various vegetation surfaces can aid in planning, managing, and allocating water resources. Field measurement of surface energy fluxes, including ETc, remains (and should remain) a crucial process for calibration and validation of satellite/remote sensing-based methods, which can provide important supporting information for water balance assessments and for analyzing the spatial distribution of energy fluxes on large scales. The Surface Energy Balance System (SEBS) was evaluated in estimating surface energy fluxes in south central Nebraska using Landsat imagery and meteorological data. SEBS-estimated surface energy fluxes were compared to Bowen Ratio Energy Balance System (BREBS) flux data measured over tall (maize) and short (winter wheat and rainfed grass) vegetation surfaces at Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX) tower sites. A total of 54 cloud-free Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus images that were available for both path 29 row 31 and path 29 row 32 were analyzed for the spatial distribution of ETc over the study area. On an all-vegetation-average basis (pooled data from all surfaces), the correlation between estimated and measured surface energy balance components had R2 values of 0.88, 0.90, 0.63, and 0.32 for ETc, net radiation (Rn), sensible heat flux (H), and soil heat flux (G), respectively. SEBS overestimated Rn considerably by 46 W m-2, and estimates for G were also poor. Results were somewhat improved when comparisons were made on an individual vegetation surface basis. In addition to detailed analyses of ETc and other surface energy fluxes of irrigated maize, winter wheat, and rainfed grassland, the spatial distributions of ETc for ten other surfaces (rainfed maize, sorghum, soybean, winter wheat, alfalfa, open water, developed/open space, deciduous forest, grassland/pasture, and woody wetlands) were mapped and evaluated. Substantial variability in ETc was observed over the study area, which was mainly due to the diverse cropping systems and management practices across the area. The SEBS performance was poor and unsatisfactory during days with precipitation events. Additional research is needed to investigate the performance of SEBS for various vegetation surfaces and to develop algorithms to improve the performance of the model to estimate surface energy fluxes for different periods of the growing season and during days with precipitation events

Fuzz Smarter, Not Harder:Towards Greener Fuzzing with GreenAFL

Fuzzing has become a key search-based technique for software testing, but continuous fuzzing campaigns consume substantial computational resources and generate significant carbon footprints. Existing grey-box fuzzing approaches like AFL++ focus primarily on coverage maximisation, without considering the energy costs of exploring different execution paths. This paper presents GreenAFL, an energy-aware framework that incorporates power consumption into the fuzzing heuristics to reduce the environmental impact of automated testing whilst maintaining coverage. GreenAFL introduces two key modifications to traditional fuzzing workflows: energy-aware corpus minimisation considering power consumption when reducing initial corpora, and energy-guided heuristics that direct mutation towards high-coverage, low-energy inputs. We conduct an ablation study comparing vanilla AFL++, energy-based corpus minimisation, and energy-based heuristics to evaluate the individual contributions of each component. Results show that highest coverage, and lowest energy usage is achieved whenever at least one of our modifications is used

Operational Remote Sensing of ET and Challenges

Satellite imagery now provides a dependable basis for computational models that determine evapotranspiration (ET) by surface energy balance (EB). These models are now routinely applied as part of water and water resources management operations of state and federal agencies. They are also an integral component of research programs in land and climat

Variability Analyses of Alfalfa-Reference to Grass-Reference Evapotranspiration Ratios in Growing and Dormant Seasons

Alfalfa-reference evapotranspiration (ETr) values sometimes need to be converted to grass-reference ET (ETo), or vice versa, to enable crop coefficients developed for one reference surface to be used with the other. However, guidelines to make these conversions are lacking. The objectives of this study were to: (1) develop ETr to ETo ratios (Kr values) for different climatic regions for the growing season and nongrowing (dormant) seasons; and (2) determine the seasonal behavior of Kr values between the locations and in the same location for different seasons. Monthly average Kr values from daily values were developed for Bushland, (Tex.), Clay Center, (Neb.), Davis, (Calif.), Gainesville, (Fla.), Phoenix (Ariz.), and Rockport, (Mo.) for the calendar year and for the growing season (May– September). ETr and ETo values that were used to determine Kr values were calculated by several methods. Methods included the standardized American Society of Civil Engineers Penman–Monteith (ASCE-PM), Food and Agriculture Organization Paper 56 (FAO56) equation (68), 1972 and 1982 Kimberly-Penman, 1963 Jensen-Haise, and the High Plains Regional Climate Center (HPRCC) Penman. The Kr values determined by the same and different methods exhibited substantial variations among locations. For example, the Kr values developed with the ASCE-PM method in July were 1.38, 1.27, 1.32, 1.11, 1.28, and 1.19, for Bushland, Clay Center, Davis, Gainesville, Phoenix, and Rockport, respectively. The variability in the Kr values among locations justifies the need for developing local Kr values because the values did not appear to be transferable among locations. In general, variations in Kr values were less for the growing season than for the calendar year. Average standard deviation between years was maximum 0.13 for the calendar year and maximum 0.10 for the growing season. The ASCE-PM Kr values had less variability among locations than those obtained with other methods. The FAO56 procedure Kr values had higher variability among locations, especially for areas with low relative humidity and high wind speed. The 1972 Kim-Pen method resulted in the closest Kr values compared with the ASCE-PM method at all locations. Some of the methods, including the ASCE-PM, produced potentially unrealistically high Kr values (e.g., 1.78, 1.80) during the nongrowing season, which could be due to instabilities and uncertainties that exist when estimating ETr and ETo in dormant season since the hypothetical reference conditions are usually not met during this period in most locations. Because simultaneous and direct measurements of the ETr and ETo values rarely exist, it appears that the approach of ETr to ETo ratios calculated with the ASCE-PM method is currently the best approach available to derive Kr values for locations where these measurements are not available. The Kr values developed in this study can be useful for making conversions from ETr to ETo, or vice versa, to enable using crop coefficients developed for one reference surface with the other to determine actual crop water use for locations, with similar climatic characteristics of this study, when locally measured Kr values are not available

Surface energy balance model of transpiration from variable canopy cover and evaporation from residue-covered or bare soil systems: Model evaluation

A surface energy balance model (SEB) was extended by Lagos et al. Irrig Sci 28:51–64 (2009) to estimate evapotranspiration (ET) from variable canopy cover and evaporation from residue-covered or bare soil systems. The model estimates latent, sensible, and soil heat fluxes and provides a method to partition evapotranspiration into soil/residue evaporation and plant transpiration. The objective of this work was to perform a sensitivity analysis of model parameters and evaluate the performance of the proposed model to estimate ET during the growing and non-growing season of maize (Zea Mays L.) and soybeans (Glycine max) in eastern Nebraska. Results were compared with measured data from three eddy covariance systems under irrigated and rain-fed conditions. Sensitivity analysis of model parameters showed that simulated ET was most sensitive to changes in surface canopy resistance, soil surface resistance, and residue surface resistance. Comparison between hourly estimated ET and measurements made in soybean and maize fields provided support for the validity of the surface energy balance model. For growing season’s estimates, Nash–Sutcliffe coefficients ranged from 0.81 to 0.92 and the root mean square error (RMSE) varied from 33.0 to 48.3 W m–2. After canopy closure (i.e., after leaf area index (LAI = 4) until harvest), Nash–Sutcliffe coefficients ranged from 0.86 to 0.95 and RMSE varied from 22.6 to 40.5 W m–2. Performance prior to canopy closure was less accurate. Overall, the evaluation of the SEB model during this study was satisfactory