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Vegetation phenology models still rely on temperature as the primary limiting factor to growth. They generally do not recognize the importance of photoperiod and water availability, which can cause them to under-perform. Moreover, few models have used machine learning algorithms to find relationships in the data. In this paper, four Vegetation Indexes (VIs), namely the green chromatic coordinate (GCC), the vegetation contrast index (VCI), the normalized difference vegetation index (NDVI) and the two-band enhanced vegetation index (EVI2), are predicted for the North American Great Plains. This is possible by using six PhenoCams, Daily Surface Weather and Climatological Summaries (DAYMET), processing them with the machine learning algorithm XGBoost (XGB) and comparing them with seven phenophase stages throughout a growth cycle. Examining the results, GCC was the best fitting model with an R2 of 0.946, while EVI2 was the poorest with an R2 of 0.895. Also, the results indicate that changing temperature and precipitation patterns are driving a significant change in phenology of the grasslands. We developed a model capable of explaining 90 to 93% of the variability in four VIs across six grassland PhenoCam sites over the growing season using the XGB regression. Our model demonstrates the importance of including photoperiod, temperature, and precipitation information when modeling vegetation phenology. Finally, we were able to construct a 38-year phenology record at each PhenoCam location. [ABSTRACT FROM AUTHOR]

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International H 2 O Project ( I H O P _ 2002 ) is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) is an abundant trace gas in the atmosphere and an important player in atmospheric chemistry, aerosol formation and the atmosphere–surface exchange of nitrogen. The accurate determination of NH 3 emission rates remains a challenge, partly due to the propensity of NH 3 to interact with instrument surfaces, leading to high detection limits and slow response times. In this paper, we present a new method for quantifying ambient NH 3 , using chemical ionization mass spectrometry (CIMS) with deuterated benzene cations as reagents. The setup aimed at limiting sample–surface interactions and achieved a 1 σ precision of 10–20 pptv and an immediate 1/e response rate of < 0.4 s, which compares favorably to the existing state of the art. The sensitivity exhibited an inverse humidity dependence, in particular in relatively dry conditions. Background of up to 10 % of the total signal required consideration as well, as it responded on the order of a few minutes. To showcase the method's capabilities, we quantified NH 3 mixing ratios from measurements obtained during deployment on a Gulfstream I aircraft during the HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems) field campaign in rural Oklahoma during May 2016. Typical mixing ratios were 1–10 parts per billion by volume (ppbv) for the boundary layer and 0.1–1 ppbv in the lower free troposphere. Sharp plumes of up to tens of ppbv of NH 3 were encountered as well. We identified two of their sources as a large fertilizer plant and a cattle farm, and our mixing ratio measurements yielded upper bounds of 350 ± 50 and 0.6 kg NH 3 h -1 for their respective momentary source rates. The fast response of the CIMS also allowed us to derive vertical NH 3 fluxes within the turbulent boundary layer via eddy covariance, for which we chiefly used the continuous wavelet transform technique. As expected for a region dominated by agriculture, we observed predominantly upward fluxes, implying net NH 3 emissions from the surface. The corresponding analysis focused on the most suitable flight, which contained two straight-and-level legs at ∼ 300 m above ground. We derived NH 3 fluxes between 1 and 11 mol km -2 h -1 for these legs, at an effective spatial resolution of 1–2 km. The analysis demonstrated how flux measurements benefit from suitably arranged flight tracks with sufficiently long straight-and-level legs, and it explores the detrimental effect of measurement discontinuities. Following flux footprint estimations, comparison to the NH 3 area emissions inventory provided by the U.S. Environmental Protection Agency indicated overall agreement but also the absence of some sources, for instance the identified cattle farm. Our study concludes that high-precision CIMS measurements are a powerful tool for in situ measurements of ambient NH 3 mixing ratios, and even allow for the airborne mapping of the air–surface exchange of NH 3. [ABSTRACT FROM AUTHOR]

The contiguous grasslands of the Sandhills region in Nebraska, USA, provide habitat for two sympatric, grassland-obligate species of grouse, the greater prairie-chicken (Tympanuchus cupido pinnatus) and the plains sharp-tailed grouse (Tympanuchus phasianellus jamesi). Collectively referred to as prairie grouse, these birds are monitored and managed jointly by wildlife practitioners who face the novel challenge of conserving historically allopatric species in shared range. We reconstructed region-wide and route-specific prairie grouse population trends in the Sandhills, using a 63-year timeseries of breeding ground counts aggregated from old reports and paper archives. Our objective was to repurpose historical data collected for harvest management to address questions pertinent to the conservation of prairie grouse, species whose populations have declined precipitously throughout their respective ranges. Because we cannot change the sampling protocol of historical data to answer new questions, we applied 3 different methods of data analysis—traditional regional mean counts used to adjust harvest regulations, spatially implicit, site-specific counts, and spatially explicit trends. Prairie-chicken populations have increased since the 1950s, whereas sharp-tailed grouse populations have remained stable or slightly declined. However, each species exhibited unique shifts in abundance and distribution over time, and regional indices masked important aspects of population change. Our findings indicate that legacy data have the capacity to tell new stories apart from the questions they were collected to answer. By integrating concepts from landscape ecology—a discipline that emerged decades after the collection of our count data began—we demonstrate the potential of historical data to address questions of modern-day conservation concern, using prairie grouse as a case study. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the United States (US) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2 (E3SMv2) fully coupled Regionally Refined Model (RRM) and documents the overall atmosphere, land, and river results from the Coupled Model Intercomparison Project 6 (CMIP6) DECK (Diagnosis, Evaluation, and Characterization of Klima) and historical simulations - a first-of-kind set of climate production simulations using RRM. The North American 5 (NA) RRM (NARRM) is developed as the high-resolution configuration of E3SMv2 with the primary goal of more explicitly addressing DOE's mission needs regarding impacts to the US energy sector facing Earth system changes. The NARRM features finer horizontal resolution grids centered over NA, consisting of 25→100 km atmosphere and land, 0.125° river routing model, and 14→60 km ocean and sea ice. By design, the computational cost of NARRM is ~3x of the uniform low-resolution (LR) model at 100 km but only ~10-20% of a globally uniform high-resolution model at 25 km. A novel hybrid timestep strategy for the atmosphere is key for NARRM to achieve improved climate simulation fidelity within the high-resolution patch without sacrificing the overall global performance. The global climate, including climatology, time series, sensitivity, and feedback, is confirmed to be largely identical between NARRM and LR as quantified with typical climate metrics. Over the refined NA area, NARRM is generally superior to LR, including for precipitation and clouds over the contiguous US (CONUS), summertime marine stratocumulus clouds off the coast of California, liquid and ice phase clouds near the North 15 polar region, extratropical cyclones, and spatial variability in land hydrological processes. The improvements over land are related to the better resolved topography in NARRM, whereas those over ocean are attributable to the improved air-sea interactions with finer grids for both atmosphere and ocean/sea ice. Some features appear insensitive to the resolution change analyzed here, for instance the diurnal propagation of organized mesoscale convective systems over CONUS, and the warm-season land-atmosphere coupling at the Southern Great Plains. In summary, our study presents a realistically efficient approach to leverage the RRM framework for a standard Earth system model release and high-resolution climate production simulations. [ABSTRACT FROM AUTHOR]

• Offers an extensive review of global research on grassland-human activity interactions since 2000, covering key developments and insights. • Unveils the dynamic evolution of research focus across various stages in the study of human activities in grasslands. • Illustrates the expansion of research from small-scale and botanical to multi-scale and multidisciplinary scopes. • Identifies and emphasizes the prevalent use of analytical tools such as R language, PC-ORD, and Google Earth Engine (GEE) in grassland research. Due to their ecological sensitivity and limited resource availability, grasslands are exceptionally vulnerable to environmental changes and human activities. However, comprehensive and in-depth analyses of the interplay between grasslands and human activities remain scarce. This study employed bibliometrics and critical paper analysis to scrutinize 4738 publications from 2000 to 2023. The findings reveal that: (1) Since 2000, research on grassland-human activity interactions has evolved and intensified, spanning diverse disciplines including environmental ecology, plant science, agricultural science, and biodiversity conservation. A notable trend is the relative clustering of scholars and research institutions within Eastern and Western countries and within national boundaries. China leads in publication volume, whereas the United States exerts greater influence in the international collaborative network. (2) Approximately 80% of the highly co-citation literature concentrates on elucidating scientific knowledge, particularly the impact of human activities on vegetation characteristics, grassland communities, and ecosystems. Research hotspots predominantly encompass European grasslands, North America's Great Plains, and the Tibetan Plateau grasslands in China. The remaining 20% focuses on methodological advancements and tools, with frequent utilization of R language, PC-ORD, and Google Earth Engine (GEE). (3) Initial studies (2000–2005) primarily investigated the effects of specific anthropogenic activities on grassland biomes at a community level through experimental observations. Subsequent research (2006–2013) shifted towards exploring the overarching characteristics and transformations of grassland rangelands at regional scales, heavily relying on remote sensing technologies. More recent studies (2014–2023) have emphasized a comprehensive, quantitative appraisal of the multifaceted impacts of internal and external stressors on grassland ecosystems. This study enhances the understanding of the historical trajectory of grassland-anthropogenic relationship research, highlighting pivotal knowledge and collaborative tools. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) is an abundant trace gas in the atmosphere and an important player in atmospheric chemistry, aerosol formation and the atmosphere-surface exchange of nitrogen. It is recognized as a major source of aerosol pollution, and it may limit the formation of cloud nuclei in remote or cold parts of the atmosphere. For soil and plants, NH3-mediated nitrogen can act as a harmful pollutant or as a desirable nutrient, mostly in natural and agricultural settings, respectively. Agriculture is also the main source of atmospheric NH3 via volatilization from fertilizers and manure processing in livestock farming. The accurate determination of NH3 emission rates remains a challenge, partly due to the propensity of NH3 to interact with instrument surfaces leading to high detection limits and slow response times. In this paper, we present a new method for quantifying ambient NH3, using chemical ionization mass spectrometry (CIMS) with deuterated benzene cations as reagents. The setup aimed at limiting sample-surface interactions and achieved a 1-σ precision of 10-20 pptv and an immediate 1/e response rate < 0.4 s, which compares favorably to the existing state of the art. The sensitivity exhibited an inverse humidity dependence, in particular in relatively dry conditions. Background of up to 10% of the total signal required consideration as well, as it responded on the order of a few minutes. To showcase the method's capabilities, we quantified NH3 mixing ratios from measurements obtained during deployment on a Gulfstream I aircraft during the HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems) field campaign in rural Oklahoma during May 2016. Typical mixing ratios were 1-10 parts per billion by volume (ppbv) for the boundary layer and 0.1-1 ppbv in the lower free troposphere. Sharp plumes of up to 10s of ppbv of NH3 were encountered as well. We identified two of their sources as a large fertilizer plant and a cattle farm, and our mixing ratio measurements yielded upper bounds of 350 ± 50 and 0.6 kg NH3 h--1 for their respective momentary source rates. The fast response of the CIMS also allowed us to derive vertical NH3 fluxes within the turbulent boundary layer via eddy covariance, for which we chiefly used the continuous wavelet transform technique. As expected for a region dominated by agriculture, we observed predominantly upward fluxes, implying net NH3 emissions from surface. The corresponding analysis focused on the most suitable flight, which contained two straight-andlevel legs at -300 m above ground. We derived NH3 fluxes between --4 and 18 mol km--2 h--1 for these legs, at an effective spatial resolution of 1-2 km. The analysis demonstrated how flux measurements benefit from suitably arranged flight tracks with sufficiently long straight-and-level legs, and explores the detrimental effect of measurement discontinuities. Following flux footprint estimations, comparison to the NH3 area emissions inventory provided by the US Environmental Protection Agency indicated overall agreement, but also the absence of some sources, for instance the identified cattle farm. Our study concludes that high-precision CIMS measurements are a powerful tool for in-situ measurements of ambient NH3 mixing ratios, and even allow for the airborne mapping of the air-surface exchange of NH3. [ABSTRACT FROM AUTHOR]

Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of datasets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center (https://adc.arm.gov/discovery/#/ , last access: 11 February 2022) and made publicly available at no cost for all registered users (10.5439/1846798) (Mei and Dexheimer, 2022). These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This paper describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms. [ABSTRACT FROM AUTHOR]

Infrared hyperspectral remote sensing has been widely used in the field of meteorology. Many scientists have carried out research on inversion methods of meteorological elements such as thermodynamic profile, boundary layer height, cloud base height, etc. In this study, a method based on machine learning for cloud detection using ground-based infrared hyperspectral radiation data is proposed. The features of outliers, the cloudy and cloud-free data of Atmospheric Emitted Radiance Interferometer (AERI) radiation are extracted. The "reference values" of cloudy and cloud-free are determined based on the observation data of Vaisala CL31 ceilometer within the time range of 8 min before the corresponding time of AERI. A support vector machine (SVM) algorithm is used for training. The dataset comes from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and North Slope Alaska (NSA) site from 2015 to 2017, and the ARM West Antarctic Radiation Experiment (AWARE) site in 2016 is also analyzed. The instruments used in this paper include AERI, ceilometer, etc. The experimental results reveal that the agreement of cloud detection results between the proposed algorithm and ceilometer is about 93% at each site. However, for high clouds or optically thin clouds, the agreement will decrease. [ABSTRACT FROM AUTHOR]

This paper reports on a third-generation rotating shadow band spectroradiometer (RSS) used to measure global and diffuse horizontal plus direct normal irradiances and transmissions at 1002 wavelengths between 360 and 1070 nm. The prism-dispersed spectral data are from the Atmospheric Radiation Measurement (ARM) Southern Great Plains site in north-central Oklahoma (36.605 ∘ N, 97.486 ∘ W) and cover dates between August 2009 and February 2014. The refurbished RSS isolates the detector in a vacuum chamber with pressures near 10-7 torr. This prevents the deposition of outgassed vapors from the interior of the spectrometer shell on the cooled detector that affected the operation of the first commercial RSS. Methods for (1) ensuring the correct wavelength registration of the data and (2) deriving extraterrestrial responses over the entire spectrum, including throughout strong water vapor and oxygen bands, are described. The resulting data produced are archived as ARM data records and include cloud-screened aerosol optical depths, spectral irradiances and direct normal solar transmission, as well as normalized diffuse and global irradiances. [ABSTRACT FROM AUTHOR]

Since first proposed, the Keystone XL and Dakota Access pipelines have been extensively covered by the media, shaping readers' perceptions of the pipelines, as well as perceptions of the places and peoples impacted by them. Using critical discourse analysis, this paper examines the media coverage, their Plains descriptions, and expressions of place attachment. Through the media's use of "place talk," it presents a hybrid Plains: placeless, yet with a strongly place-attached population who are "tied to the land." As conflicts over environmental and energy projects become increasingly contentious, place and place attachment are important for understanding the conflicts and potentially mobilizing resistance. [ABSTRACT FROM AUTHOR]

Over the past decade, there has been appreciable progress towards modeling the water, energy, and carbon cycles at field scales (10–100 m) over continental to global extents in Earth system models (ESMs). One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via Hydrologic Response Units (HRUs), more commonly known as "tiles" in ESMs. In HydroBlocks, these HRUs are learned via a hierarchical clustering approach from available global high-resolution environmental data. However, until now there has yet to be a river routing approach that is able to leverage HydroBlocks' approach to modeling field-scale heterogeneity; bridging this gap will make it possible to more formally include riparian zone dynamics, irrigation from surface water, and interactive floodplains in the model. This paper introduces a novel dynamic river routing scheme in HydroBlocks that is intertwined with the modeled field-scale land surface heterogeneity. Each macroscale polygon (a generalization of the concept of macroscale grid cell) is assigned its own fine-scale river network that is derived from very high resolution (∼ 30 m) digital elevation models (DEMs); the inlet–outlet reaches of a domain's macroscale polygons are then linked to assemble a full domain's river network. The river dynamics are solved at the reach-level via the kinematic wave assumption of the Saint-Venant equations. Finally, a two-way coupling between each HRU and its corresponding fine-scale river reaches is established. To implement and test the novel approach, a 1.0 ∘ bounding box surrounding the Atmospheric Radiation and Measurement (ARM) Southern Great Plains (SGP) site in northern Oklahoma (United States) is used. The results show (1) the implementation of the two-way coupling between the land surface and the river network leads to appreciable differences in the simulated spatial heterogeneity of the surface energy balance, (2) a limited number of HRUs (∼ 300 per 0.25 ∘ cell) are required to approximate the fully distributed simulation adequately, and (3) the surface energy balance partitioning is sensitive to the river routing model parameters. The resulting routing scheme provides an effective and efficient path forward to enable a two-way coupling between the high-resolution river networks and state-of-the-art tiling schemes in ESMs. [ABSTRACT FROM AUTHOR]

This project involves students in a course-based undergraduate research experience (CURE) as part of the traditional introductory biology laboratory course. Recently, research has shown that student engagement in authentic research has significant positive impacts on students, such as development of science literacy and reasoning skills. Being recently featured in the news, microplastics are a timely, interesting, and relevant topic for students. The authentic research conducted by students was the first attempt at quantification of microplastics in the Great Plains, which garnered further student excitement and engagement. Surface water and substrate samples were collected at 23 locations from small streams, rivers, ponds, and reservoirs in fall 2018. Authentic research, as broadly defined in the pedagogical context, is research conducted primarily by students. In the context of this project, authentic research is specifically defined as research done primarily by students in which the students are asking questions, designing experiments, collecting and analyzing data, and writing a final manuscript that was submitted, and accepted, as a peer-reviewed publication. This project could be incorporated at the high school or university level, for biology major or nonmajor courses. The purpose of this paper is to serve as a how-to, sharing the lesson design with specific detail on student responsibilities. [ABSTRACT FROM AUTHOR]

Over the past decade, there has been appreciable progress towards modeling the water, energy, and carbon cycles at field-scales (10–100 m) over continental to global extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid tiles, or Hydrologic Response Units (HRUs), learned via a hierarchical clustering approach from available global high-resolution environmental data. However, until now, there has yet to be a macroscale river routing approach that is able to leverage HydroBlocks' approach to sub-grid heterogeneity, thus limiting the added value of field-scale land surface modeling in Earth System Models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). This paper introduces a novel dynamic river routing scheme in HydroBlocks that is intertwined with the modeled field-scale land surface heterogeneity. The primary features of the routing scheme include: 1) the fine-scale river network of each macroscale grid cell's is derived from very high resolution (<100 m) DEMs; 2) the inlet/outlet reaches of each macroscale grid cell are linked to assemble the continental river networks; 3) the river dynamics are solved at a reach-level via the Kinematic wave assumption of the Saint-Venant equations; 4) a two-way coupling is established between each sub-grid tile and the river network. To implement and test the novel approach, a 1.0-degree bounding box surrounding the Atmospheric Radiation and Measurement (ARM) Southern Great Plains (SGP) site in Northern Oklahoma (United States) is used. The results show: 1) the implementation of the two-way coupling between the land surface and the river network leads to appreciable differences in the simulated spatial heterogeneity of the surface energy balance; 2) a limited number of tiles (~300 per 0.25-degree cell) are required to approximate the fully distributed simulation adequately; 3) the surface energy balance partitioning is sensitive to the river routing model parameters. The resulting routing scheme provides an effective and efficient path forward to enable a two-way coupling between the high-resolution river networks and existing tiling schemes within Earth system models. [ABSTRACT FROM AUTHOR]

In the U.S. Great Plains (GP), diagnosing precipitation variability is key in developing an understanding of the present and future availability of water in the region. Building on previous work investigating U.S. GP pluvial years, this study uses ERA twentieth century (ERA-20C) reanalysis data to investigate key circulation anomalies driving GP precipitation anomalies during a subset of GP pluvial years (called in this paper Pattern pluvial years). With previous research showing links between tropical Pacific sea surface temperature (SST) anomalies and GP climate variability, this study diagnoses the key circulation anomalies through an analysis of SSTs and their influence on the atmosphere. Results show that during Pattern southern Great Plains (SGP) pluvial years, central tropical Pacific SST anomalies are coincident with key atmospheric anomalies across the Pacific basin and North America. During northern Great Plains (NGP) Pattern pluvial years, no specific pattern of oceanic anomalies emerges that forces the circulation anomaly feature inherent in specific NGP pluvial years. Utilizing the results for SGP pluvial years, a conceptual model is developed detailing the identified pathway for the occurrence of circulation patterns that are favorable for pluvial years over the SGP. Overall, results from this study show the importance of the identified SGP atmospheric anomaly signal and the potential for predictability of such events. [ABSTRACT FROM AUTHOR]

Anthropogenic activities since the European colonization of the North American Great Plains have drastically altered landscape composition and configuration, subsequently affecting native biodiversity. These contemporary human‐modified landscapes may affect mammal species' distributions, diel activity patterns, habitat use, and interspecific interactions, though a better understanding of these effects on mammals occurring in remaining prairie landscapes is needed. To fill this gap, we surveyed 381 randomly selected sites in 2018, 2019, and 2020 using motion‐sensing camera traps across the western part of the US state of Kansas (7,160,077 ha). Sites were separated by ≥2 km (x¯$$ \overline{x} $$ = 8.16 km, SD = 3.61), and cameras were secured to a metal post 40 cm above ground and randomly oriented toward the north or south. We placed an olfactory attractant (mixture of skunk essence and petroleum jelly) on a wooden stake 3 m in front of each camera. Cameras were in place at each site for 28 consecutive days for each year. We manually identified all mammal species detected at each site, collating these data into a database that included taxonomic information for 14 families of mammals (Antilocapridae, Bovidae, Canidae, Cervidae, Cricetidae, Dasypodidae, Didelphidae, Erethizontidae, Felidae, Heteromyidae, Leporidae, Mephitidae, Mustelidae, Procyonidae, Sciuridae, and Muridae) comprising 28 total species. We recorded 31,178 mammal photographs (nonindependent events) over 27,954 camera trap nights during 2018 (n = 10,351), 2019 (n = 9478), and 2020 (n = 8125). Additionally, we included the time and date of each photocapture. Moreover, we gathered survey‐specific data useful for modeling species‐specific detection along with site‐level habitat composition data taken at each site each year. These data will be useful for examining habitat use, species distributions, diel activity patterns, and spatiotemporal interactions between species and across guilds of mammals occurring in a rapidly changing agro‐prairie ecosystem. There are no copyright restrictions, but we ask researchers to cite this paper when using these data for publication. [ABSTRACT FROM AUTHOR]

Modeling alternative irrigation strategies can be a cost-effective and time-saving approach to field-based experiments. However, the efficacy of irrigation scheduling algorithms should be verified using field data from multiple locations. In this study, an auto-irrigation algorithm recently developed for Soil and Water Assessment Tool (SWAT) was further evaluated using irrigation data for corn (Zea mays L.) grown at six research sites across the Southern Great Plains. Simulated monthly irrigation, based on the management allowed depletion (MAD) of plant available soil water, was compared to measured data for irrigation applied in accordance with crop water requirement guidelines outlined by the Food and Agriculture Organization Irrigation and Drainage Paper 56. Overall, results indicated the MAD algorithm simulated monthly field-based irrigation amounts well (Nash-Sutcliffe efficiency; NSE > 0.56). Comparisons revealed the MAD algorithm outperformed the plant water demand and soil water content approaches in SWAT, which tended to underestimate and overestimate irrigations, respectively. • FAO-56 based corn irrigation scheduling data were accessed from six study sites. • Newly developed MAD algorithm simulated irrigation well compared to FAO-56 method. • SWAT existing soil water content algorithm tended to overestimate actual irrigation. • SWAT existing plant water demand algorithm underestimated actual irrigation. • SWAT MAD algorithm should provide benefit for scheduling of field-based irrigation. [ABSTRACT FROM AUTHOR]

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the contiguous United States (CONUS), and implements the GFDL single-moment 6-category cloud microphysics to improve the representation of moist processes. Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena. [ABSTRACT FROM AUTHOR]

Abstract Mechanisms underlying the loss of ecological resilience and a shift to an alternate regime with lower ecosystem service provisioning continues to be a leading debate in ecology, particularly in cases where evidence points to human actions and decision-making as the primary drivers of resilience loss and regime change. In this paper, we introduce the concept of coerced resilience as a way to explore the interplay among social power, ecological resilience, and fire management, and to better understand the unintended and undesired regime changes that often surprise ecosystem managers and governing officials. Philosophically, coercion is the opposite of freedom, and uses influence or force to gain compliance among local actors. The coercive force imposed by societal laws and policies can either enhance or reduce the potential to manage for essential structures and functions of ecological systems and, therefore, can greatly alter resilience. Using a classical fire-dependent regime shift from North America (tallgrass prairie to juniper woodland), and given that coercion is widespread in fire management today, we quantify relative differences in resilience that emerge in a policy-coerced fire system compared to a theoretical, policy-free fire system. Social coercion caused large departures in the fire conditions associated with alternative grassland and juniper woodland states, and the potential for a grassland state to emerge to dominance became increasingly untenable with fire as juniper cover increased. In contrast, both a treeless, grassland regime and a co-dominated grass-tree regime emerged across a wide range of fire conditions in the absence of policy controls. The severe coercive forcing present in fire management in the Great Plains, and corresponding erosion of grassland resilience, points to the need for transformative environmental governance and the rethinking of social power structures in modern fire policies. Highlights • We introduce coerced resilience, which unifies social power theory with resilience. • Philosophically, coercion is the opposite of freedom. • Numerous examples of coercion are evident in today's fire governance system. • Severe coercive forcing has eroded resilience in Great Plains grasslands. • Resilience-based fire management requires rethinking current social power structure. [ABSTRACT FROM AUTHOR]

During the 2015 Plains Elevated Convection at Night (PECAN) field campaign, several nocturnal low-level jets (NLLJs) were observed with integrated boundary layer profiling systems at multiple sites. This paper gives an overview of selected PECAN NLLJ cases and presents a comparison of high-resolution observations with numerical simulations using the Weather Research and Forecasting (WRF) Model. Analyses suggest that simulated NLLJs typically form earlier than the observed NLLJs. They are stronger than the observed counterparts early in the event, but weaker than the observed NLLJs later in the night. However, sudden variations in the boundary layer winds, height of the NLLJ maximum and core region, and potential temperature fields are well captured by the WRF Model. Simulated three-dimensional fields are used for a more focused analysis of PECAN NLLJ cases. While previous studies often related changes in the thermal structure of the nocturnal boundary layer and sudden mixing events to local features, we hypothesize that NLLJ spatial evolution plays an important role in such events. The NLLJ is shown to have heterogeneous depth, wind speed, and wind direction. This study offers detailed documentation of the heterogeneous NLLJ moving down the slope of the Great Plains overnight. As the NLLJ evolves, westerly advection becomes significant. Buoyancy-related mechanisms are proposed to explain NLLJ heterogeneity and down-slope motion. Spatial and temporal heterogeneity of the NLLJ is suggested as a source of the often observed and simulated updrafts during PECAN cases and as a possible mechanism for nocturnal convection initiation. The spatial and temporal characteristics of the NLLJ are interconnected and should not be treated independently. [ABSTRACT FROM AUTHOR]

This paper documents the first U-Pb zircon ages for Ashfall Fossil Beds (Nebraska, USA), a terrestrial Konservat-Lagerstätte mass-death assemblage that is arguably the most diverse of its type and age. The Ashfall tephra was correlated with ignimbrites from the Bruneau-Jarbidge volcanic field (12.7–10.5 Ma) in southwest Idaho based on geochemical analysis. The methods and geochemical data supporting the original age assessment of the ash bed, however, were never published, and there has been a persistent misconception that dateable heavy minerals (e.g., zircon) are absent. Notwithstanding, we recovered abundant zircons from Ashfall Fossil Beds, and from an ash bed ~6 km to the southeast at Grove Lake, Nebraska, and analyzed them through LA-ICP-MS. Our new zircon U-Pb age of 11.86 ± 0.13 Ma substantiates correlation of the Ashfall Fossil Beds deposit to tuffs originating from the Bruneau-Jarbidge caldera (~12.7–10.5 Ma). Our U-Pb zircon age of 6.42 ± 0.06 Ma for the Grove Lake ash bed coincides with supervolcanic activity in the Heise volcanic field (6.6–4.3 Ma) in eastern Idaho. These new dates improve age constraints of strata comprising the Ogallala Group and the important paleontological site. Moreover, we find that detrital and airfall zircons are unevenly distributed in the stratified ash beds we describe herein and presumably in similar deposits worldwide. Therefore, a higher-resolution sampling scheme is necessary in such cases. [ABSTRACT FROM AUTHOR]

This paper documents the first U-Pb zircon ages for Ashfall Fossil Beds (Nebraska, USA), a terrestrial Konservat-Lagersta¨ tte mass-death assemblage that is arguably the most diverse of its type and age. The Ashfall tephra was correlated with ignimbrites from the Bruneau-Jarbidge volcanic field (12.7--10.5 Ma) in southwest Idaho based on geochemical analysis. The methods and geochemical data supporting the original age assessment of the ash bed, however, were never published, and there has been a persistent misconception that dateable heavy minerals (e.g., zircon) are absent. Notwithstanding, we recovered abundant zircons from Ashfall Fossil Beds, and from an ash bed ~6 km to the southeast at Grove Lake, Nebraska, and analyzed them through LA-ICP-MS. Our new zircon U-Pb age of 11.86 ± 0.13 Ma substantiates correlation of the Ashfall Fossil Beds deposit to tuffs originating from the Bruneau-Jarbidge caldera (~12.7-10.5 Ma). Our U-Pb zircon age of 6.42 ± 0.06 Ma for the Grove Lake ash bed coincides with supervolcanic activity in the Heise volcanic field (6.6-4.3 Ma) in eastern Idaho. These new dates improve age constraints of strata comprising the Ogallala Group and the important paleontological site. Moreover, we find that detrital and airfall zircons are unevenly distributed in the stratified ash beds we describe herein and presumably in similar deposits worldwide. Therefore, a higher-resolution sampling scheme is necessary in such cases. [ABSTRACT FROM AUTHOR]

The release of seasonal (and longer) predictions of various climatological quantities is now routine. While undoubtedly devastating to lives and livelihoods, it is unclear whether seasonal extremes in precipitation-for example, extreme dry spells leading to droughts or heavy precipitation events leading to flooding-represent a feasible target for these predictions, that is, whether they are potentially predictable or are instead inherently unpredictable more than a few days to weeks in advance. This paper assesses the potential for predicting seasonal extremes in observed precipitation as a function of region and time of year by decomposing the station-based variance into that attributable to short-memory behavior of typical meteorological events-as generated from station-specific, seasonally varying, daily time-scale stationary stochastic weather models (SSWMs)-and that attributable to longer-time-scale, potentially predictable changes in precipitation-producing processes. Findings suggest the potential for making skillful predictions of seasonal precipitation extremes over the United States is enhanced (reduced) during the cool (warm) season, particularly for heavy precipitation event accumulations. Further, this potential is accentuated along the West Coast, around the Great Lakes, and over the central plains and Ohio River valley but is diminished over the Northeast and northern Great Plains. However, findings also suggest the potential for producing seasonal (and longer) predictions of seasonal precipitation extremes is spatially and seasonally dependent. As such, this paper includes supplemental material for the potentially predictable variance of seasonal extreme dry spell lengths, heavy event accumulations, and total accumulations at 774 stations across all 365 days so readers can evaluate the potential predictability for the location, timing, and metric of most relevance to them. [ABSTRACT FROM AUTHOR]

A recent study found that surface hodographs over the Great Plains of the United States turn in a counterclockwise direction with time. This observed turning is opposite of the clockwise turning observed (and expected, based on theory) at higher altitudes. Using a mesoscale forecast model, the same study shows that it has the same hodograph behavior as found in the observations. The study further shows that the reason for this anomalous counterclockwise turning is the decoupling of the surface layer from the boundary layer after sunset and its recoupling after sunrise. The present paper presents a simple model for this behavior by extending a recent analytical model for the diurnal oscillation to include the surface-layer effect. In addition, selected solution features are analyzed in terms of several of the nondimensional input parameters. [ABSTRACT FROM AUTHOR]

This is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variables across most regions and seasons and higher-resolution models tend to perform better for regional processes. The CMIP5 multimodel ensemble shows a slight improvement relative to CMIP3 models in representing basic climate variables, in terms of the mean and spread, although performance has decreased for some models. Improvements in CMIP5 model performance are noticeable for some regional climate processes analyzed, such as the timing of the North American monsoon. The results of this paper have implications for the robustness of future projections of climate and its associated impacts, which are examined in the third part of the paper. [ABSTRACT FROM AUTHOR]

This paper presents the methodology and results of two ecological-based net ecosystem production (NEP) regression tree models capable of up scaling measurements made at various flux tower sites throughout the U.S. Great Plains. Separate grassland and cropland NEP regression tree models were trained using various remote sensing data and other biogeophysical data, along with 15 flux towers contributing to the grassland model and 15 flux towers for the cropland model. The models yielded weekly mean daily grassland and cropland NEP maps of the U.S. Great Plains at 250 m resolution for 2000-2008. The grassland and cropland NEP maps were spatially summarized and statistically compared. The results of this study indicate that grassland and cropland ecosystems generally performed as weak net carbon (C) sinks, absorbing more C from the atmosphere than they released from 2000 to 2008. Grasslands demonstrated higher carbon sink potential (139 g C.m-2.year-1) than non-irrigated croplands. A closer look into the weekly time series reveals the C fluctuation through time and space for each land cover type. [ABSTRACT FROM AUTHOR]

This paper analyzes factors that affect net migration rates in counties in the U.S. Great Plains between 1930 and 1990, emphasizing the roles of weather (especially drought), environmental amenities, employment, and population, making use of a rich county-level data set. Using a pooled time series model the paper shows that environment is important in population processes, with weather and agricultural change more important in the 1930s and 1940s, and environmental amenities more important in later time periods. The paper provides important insights into how environmental impacts on migration might change over time, and how those changes might be measured. [ABSTRACT FROM AUTHOR]

Since the beginning of the economic crisis, nearby feeder markets have become increasingly important for Hungary's tourism sector with cross-border cooperation schemes playing an ever increasing role. This also holds true for Hungary's Southern Great Plain Region when viewed in its relationship with neighbouring Serbia. This paper examines tourism flow changes in the Southern Hungarian Great Plain Region during the period of the economic crisis especially as far as tourism flows from Serbia are concerned. The analysis is based on official statistical data available in respect of commercial accommodation facilities, analyses on tourism trends carried out at the European level, and regional development documents drawn up for the Hungarian-Serbian cross border region. The economic crisis caused a significant downturn in tourism flows in the Southern Great Plain Region. However, the number of tourists arriving from Serbia to the Southern Great Plain and the number of nights they spent there increased even during the crisis partly because of the favourable geographical location of the region, partly because of the intensive cooperation schemes implemented in the tourism sector, and partly because of organised marketing campaigns. [ABSTRACT FROM AUTHOR]

This study extends the heated condensation framework (HCF) presented in Tawfik and Dirmeyer to include variables for describing the convective background state of the atmosphere used to quantify the contribution of the atmosphere to convective initiation within the context of land-atmosphere coupling. In particular, the ability for the full suite of HCF variables to 1) quantify the amount of latent and sensible heat energy necessary for convective initiation, 2) identify the transition from moistening advantage to boundary layer growth advantage, 3) identify locally originating convection, and 4) compare models and observations, directly highlighting biases in the convective state, is demonstrated. These capabilities are illustrated for a clear-sky and convectively active day over the Atmospheric Radiation Measurement Program Southern Great Plains central station using observations, the Rapid Update Cycle (RUC) operational model, and the North American Regional Reanalysis (NARR). The clear-sky day had a higher and unattainable convective threshold, making convective initiation unlikely. The convectively active day had a lower threshold that was attained by midafternoon, reflecting local convective triggering. Compared to observations, RUC tended to have the most difficulty representing the convective state and captured the threshold for the clear-sky case only because of compensating biases in the moisture and temperature profiles. Despite capturing the observed moisture profile very well, a stronger surface inversion in NARR returned overestimates in the convective threshold. The companion paper applies the HCF variables introduced here across the continental United States to examine the climatological behavior of convective initiation and local land-atmosphere coupling. [ABSTRACT FROM AUTHOR]

The coupling of the land with the planetary boundary layer (PBL) on diurnal time scales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve understanding of land-atmosphere (L-A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, the authors apply a suite of local land-atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-yr period over the U.S. southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation is applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface-PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land-PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. Each RA has a unique land-PBL coupling that has implications for downstream impacts on the diurnal cycle of PBL evolution, clouds, convection, and precipitation as well as representation of extremes and drought. As a result, caution should be used when treating RAs as truth in terms of their water and energy cycle processes. [ABSTRACT FROM AUTHOR]

The authors illustrate a statistical model for predicting tornado activity in the central Great Plains by 1 March. The model predicts the number of tornado reports during April-June using February sea surface temperature (SST) data from the Gulf of Alaska (GAK) and the western Caribbean Sea (WCA). The model uses a Bayesian formulation where the likelihood on the counts is a negative binomial distribution and where the nonstationarity in tornado reporting is included as a trend term plus first-order autocorrelation. Posterior densities for the model parameters are generated using the method of integrated nested Laplacian approximation (INLA). The model yields a 51% increase in the number of tornado reports per degree Celsius increase in SST over the WCA and a 15% decrease in the number of reports per degree Celsius increase in SST over the GAK. These significant relationships are broadly consistent with a physical understanding of large-scale atmospheric patterns conducive to severe convective storms across the Great Plains. The SST covariates explain 11% of the out-of-sample variability in observed F1-F5 tornado reports. The paper demonstrates the utility of INLA for fitting Bayesian models to tornado climate data. [ABSTRACT FROM AUTHOR]

Wheat breeding continues to be an important component of agricultural innovations in the Great Plains region of the US. This paper reviews Oklahoma's wheat breeding program over the past several decades with an emphasis on the economic aspects and planning of future breeding strategies. Over the past century, Oklahoma's wheat yields have increased but the productivity gains have been offset in part due to increased yield variability. The shift to improved wheat varieties has resulted in increased susceptibility to plant disease and pest pressure. While a few varieties introduced over the past few decades have dominated the wheat seed market, recent trends indicate producers are adopting a more diverse range of wheat varieties. Producers' concerns have expanded beyond demands for high yielding varieties to include more market oriented needs to increase protein content and test weight. This paper identifies several key policy instruments that Oklahoma stakeholders and policy makers should consider when planning future breeding strategies. A critical need is to assist Oklahoma producers in adapting to climate change by developing drought and heat resistant wheat varieties. Marketing new varieties would be improved and revenue increased if more innovative pricing structures were adopted to better align producers' willingness to pay with seed development costs, which could then be re-invested in breeding. Research budgets, which have remained stagnant in real terms, will need to be increased to adequately address producers' needs into the 21st century. [ABSTRACT FROM AUTHOR]

Reliable estimation of the atmospheric boundary layer height (ABLH) is critical for a range of meteorological applications, including air quality assessment and weather forecasting. Several algorithms have been proposed to detect ABLH from aerosol LiDAR backscatter data. However, most of these focus on cloud-free conditions or use other ancillary instruments due to strong interference from clouds or residual layer aerosols. In this paper, a machine learning method named the Mahalanobis transform K-near-means (MKnm) algorithm is first proposed to derive ABLH under complex atmospheric conditions using only LiDAR-based instruments. It was applied to the micro pulse LiDAR data obtained at the Southern Great Plains site of the Atmospheric Radiation Measurement (ARM) program. The diurnal cycles of ABLH from cloudy weather were detected by using the gradient method (GM), wavelet covariance transform method (WM), K-means, and MKnm. Meanwhile, the ABLH obtained by these four methods under cloud or residual layer conditions based on micropulse LiDAR data were compared with the reference height retrieved from radiosonde data. The results show that MKnm was good at tracking the diurnal variation of ABLH, and the ABLHs obtained by it have remarkable correlation coefficients and smaller mean absolute error and mean deviation with the radiosonde-derived ABLHs than those measured by other three methods. We conclude that MKnm is a promising algorithm to estimate ABLH under cloud or residual layer conditions. [ABSTRACT FROM AUTHOR]

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation is applied to the dry/wet regimes exhibited in this region, and in the process, a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling test bed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger toward the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g., reanalysis products) in the context of their integrated impacts on the process chain connecting the land surface to the PBL and in support of hydrological anomalies. [ABSTRACT FROM AUTHOR]

This paper examines how pesticides and their technologies were sold to farmers and pilots throughout the midtwentieth century. It principally considers how marketing rhetoric and advertisement strategies used by chemical companies and aerial spraying firms influenced the practices and perspectives of farm producers in the Great Plains. In order to convince landowners and agricultural leaders to buy their pesticides, chemical companies generated advertisements that championed local crop health, mixture accuracy, livestock safety and a chemical-farming ‘way of life’ that kept fields healthy and productive. Combining notions of safety, accuracy and professionalism with pest eradication messages reinforced the standards that landowners, pilots and agriculturalists would hold regarding toxicity and risk when spraying their fields. As the politics of health changed in the aftermath of Rachel Carson''s Silent Spring, these companies and aerial spraying outfits responded by keeping to a vision of agricultural health that required poisons for protection through technological accuracy. [Copyright &y& Elsevier]

The rapid expansion of irrigation in the Great Plains since World War II has resulted in significant water table declines, threatening the long-term sustainability of the Ogallala Aquifer. As discussed in Part I of this paper, the Weather Research and Forecasting Model (WRF) was modified to simulate the effects of irrigation at subgrid scales. Simulations of nine April-October periods (three drought, three normal, and three pluvial) over the Great Plains were completed to assess the full impact of irrigation on the water budget. Averaged over all simulated years, irrigation over the Great Plains contributes to May-September evapotranspiration increases of approximately 4% and precipitation increases of 1%, with localized increases of up to 20%. Results from these WRF simulations are used along with a backward trajectory analysis to identify where evapotranspiration from irrigated fields falls as precipitation (i.e., irrigation-induced precipitation) and how irrigation impacts precipitation recycling. On average, only 15.8% of evapotranspiration from irrigated fields falls as precipitation over the Great Plains, resulting in 5.11 mm of May-September irrigation-induced precipitation and contributing to 6.71 mm of recycled precipitation. Reductions in nonrecycled precipitation suggest that irrigation reduces precipitation of moisture advected into the region. The heaviest irrigation-induced precipitation is coincident with simulated and observed precipitation increases, suggesting that observed precipitation increases in north-central Nebraska are strongly related to evapotranspiration of irrigated water. Water losses due to evapotranspiration are much larger than irrigation-induced precipitation and recycled precipitation increases, confirming that irrigation results in net water loss over the Great Plains. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide an alternative operationalization of amenities that does not privilege certain kinds of natural resources and climatic conditions and that can be used for assessing the quality of life in small towns. The amenity inventory presented here extends previous literature by including a broad range of amenities (natural resource, indoor and outdoor built recreational facilities, public and private services, and downtown amenities). The community level of analysis and small town focus are also unique. The inventory uses both secondary data from public sources and primary data that can be gathered by researchers or community residents. Therefore, in addition to the scholarly contribution of the inventory, the process of defining and assessing community amenities may be a valuable tool for building interpersonal relationships within communities, generating community spirit, and developing strategies for enhancing the local quality of life. [ABSTRACT FROM AUTHOR]

Conservation tillage had initial roots in the Great Plains, but the current adoption of conservation tillage, especially no-till, lags behind in the rest of the United States. This paper documents the results of a recent survey of Oklahoma producers, which was conducted to assess the current status of conservation tillage in the state. Based on responses from 1,703 producers, econometric analysis was conducted to identify factors explaining the observed use of conservation tillage practices in Oklahoma. The survey found that conventional tillage remains the most common tillage practice among Oklahoma producers. According to the survey, conventional tillage is used on 43.2% of the state's total acreage, conservation tillage on 26.7% of the total acreage, and reduced tillage on the remaining 30.1% of the crop acreage. A Tobit model was developed to explain patterns of tillage use based on producer characteristics and their perceptions on how conservation tillage performs relative to conventional tillage according to various economic and agronomic factors. The Tobit model identified operator age, farm size, crop rotation, knowledge, and erosion control as highly significant factors explaining the observed use of conservation tillage. The model results also identified potential constraints to conservation tillage adoption and use in the Southern Plains, suggesting that the unique needs of mixed crop-livestock farming systems, and the dominant winter wheat (Triticum aestivum L.) monoculture, hinder further diffusion of conservation tillage. Future policy should consider addressing the needs of Oklahoma producers, particularly crop producers heavily engaged in livestock activities, as well as finding viable rotation crops to provide alternatives for the winter wheat monoculture. [ABSTRACT FROM AUTHOR]

Reconstructions of the Paleoindian period are archaeology 's origin stories about the native people of North America. These reconstructions have strongly emphasized great differences between recent and ancient Native Americans, echoing a perspective with its roots in the nineteenth century. One central component of the differences archaeologists have seen lies in the way that Paleoindian groups moved across the landscape. Particularly on the Great Plains, these movements have been seen as unpredictable and nonrepetitive, with this view founded largely in interpretations of evidence from large bison kills. This paper compares the overall patterns of post-Clovis Paleoindian and post-Paleoindian communal bison hunting on the Plains, arguing that there is no evidence of rapid or substantial change in such hunting at the end of the Paleoindian period. Although hunting practices did not remain exactly the same over time, most of the basic characteristics of Paleoindian hunting were common on the Plains for millennia. Only the northern Plains stands out from this, and it does so only within the last 2,000 to 3,000 years, probably in reaction to the development of continent-wide exchange networks. Paleoindians certainly lived different lives than did later occupants of the Great Plains, but the literature significantly exaggerates the magnitude of this difference. [ABSTRACT FROM AUTHOR]

Monitoring land surface drought using remote sensing data is a challenge, although a few methods are available. Evapotranspiration (ET) is a valuable indicator linked to land drought status and plays an important role in surface drought detection at continental and global scales. In this study, the evaporative drought index (EDI), based on the estimated actual ET and potential ET (PET), is described to characterize the surface drought conditions. Daily actual ET at 4-km resolution for April–September 2003–05 across the continental United States is estimated using a simple improved ET model with input solar radiation acquired by Moderate-Resolution Imaging Spectroradiometer (MODIS) at a spatial resolution of 4 km and input meteorological parameters from NCEP Reanalysis-2 data at a spatial resolution of 32 km. The PET is also calculated using some of these data. The estimated actual ET has been rigorously validated with ground-measured ET at six Enhanced Facility sites in the Southern Great Plains (SGP) of the Atmosphere Radiation Measurement Program (ARM) and four AmeriFlux sites. The validation results show that the bias varies from −11.35 to 27.62 W m−2 and the correlation coefficient varies from 0.65 to 0.86. The monthly composites of EDI at 4-km resolution during April–September 2003–05 are found to be in good agreement with the Palmer Z index anomalies, but the advantage of EDI is its finer spatial resolution. The EDI described in this paper incorporates information about energy fluxes in response to soil moisture stress without requiring too many meteorological input parameters, and performs well in assessing drought at continental scales. [ABSTRACT FROM AUTHOR]

Paleoindian groups occupied North America throughout the Younger Dryas Chronozone. It is often assumed that cooling temperatures during this interval, and the impact these would have had on biotic communities, posed significant adaptive challenges to those groups. That assessment of the nature, severity and abruptness of Younger Dryas changes is largely based on ice core records from the Greenland ice sheet where changes were indeed dramatic. This paper reviews climatic and environmental records from this time period in continental North America. We conclude that, on the Great Plains and in the Rocky Mountains, conditions were in reality less extreme. It therefore follows that conditions during the Younger Dryas interval may not have measurably added to the challenge routinely faced by Paleoindian groups who, during this interval, successfully (and perhaps rapidly) dispersed across the diverse habitats of Late Glacial North America. [ABSTRACT FROM AUTHOR]

The end Pleistocene to early Holocene drying of the North American midcontinent is an important case study for understanding regional drought, its drivers, and its impacts. This paper synthesizes pollen, δ13C, eolian, and paleohydrological proxies to document the spatial and temporal patterns in the onset and rate of drying. The timing of onset ranged from 14 to 6 ka with most sites drying between 10 and 8 ka (calendar years ago). The dominant spatial pattern is time transgressive, with interior Great Plains sites beginning to dry before peripheral sites. This time-transgressive trend can be explained as a region-wide drying that caused ecotones to shift eastward, or could indicate a progressive shift in atmospheric drying from west to east. One-third of sites responded rapidly to drying; a cluster of rapid responses occurred ca. 8 ka. The combination of onsets between 14 and 6 ka and rapid responses at 8 ka strongly suggests that (1) the combination of high summer insolation, Laurentide Ice Sheet retreat, and Lake Agassiz drainage drove midcontinental drying, and (2) drying accelerated with Laurentide Ice Sheet collapse at 8.4 ka. Local factors strongly mediate the timing and rate of site responses to regional drying. Local responses to future drying in the Great Plains also should be highly variable, which challenges impact assessments of future climate changes. [ABSTRACT FROM AUTHOR]

The career of W Raymond Wood is reviewed in terms of his contributions to interdisciplinary studies in archaeology. This paper contends that his academic training at the University of Nebraska and the University of Oregon influenced this holistic approach to archaeological research. Examples of his interdisciplinary approach to research are described for projects ranging from Quaternary studies in the western Ozark Highland of Missouri to ecological approaches for understanding village life among the Indians living along the Missouri River of the eastern Great Plains. [ABSTRACT FROM AUTHOR]

Abstract: In July 2005, a field campaign was conducted in the Central Great Plains to obtain 60-field/s video imagery of lightning in correlation with reports from the U.S. National Lightning Detection Network (NLDN) and broadband electric field waveforms from the Los Alamos Sferic Array (LASA). A total of 342 GPS time-stamped cloud-to-ground (CG) flashes were recorded in 17 different sessions, and 311 (91%) of these were correlated with reports from the NLDN. Only 6 of the 17 recording sessions were dominated by flashes that lowered negative charge to ground, and 11 were dominated by positive CG flashes. A total of 103 flashes recorded on video were correlated with at least one NLDN report of negative CG strokes, 204 video flashes were correlated with one or two positive stroke reports, and 4 had bipolar reports. In this paper, we will give distributions of the estimated peak current, I p, as reported by the NLDN, of negative and positive first strokes that were recorded on video, the multiplicity of strokes that were recorded on video, and the number of ground contacts per flash that were resolved on video. 41 (40%) of the negative flashes produced just a single-stroke on video, and 62 (60%) showed two or more strokes. The observed multiplicity of negative flashes averaged 2.83, which becomes about 3.14 after correcting for the finite time-resolution of the video camera. 195 (96%) of the positive flashes produced just a single-stroke on video, and 9 (4%) showed two strokes; therefore, the observed multiplicity of positive flashes averaged 1.04. Five out of 9 (56%) of the positive subsequent strokes re-illuminated a previous channel, and 4 out of 9 (44%) created a new ground contact. Simultaneous video, LASA, and NLDN measurements also allowed us to examine the classification of NLDN reports during 3 single-cell storms (one negative and two positive). Based on the LASA waveforms, a total of 204 out of 376 (54%) NLDN reports of CG strokes were determined to be for cloud pulses. The misclassified negative reports had |I p| values ranging from 3.8 kA to 29.7 kA, but only 58 (24%) of these had |I p|>10 kA, and only one misclassified positive report had I p >20 kA. Radar analyses showed that most of the negative and positive CG strokes that were recorded on video were produced within or near the convective cores of storms. The radar imagery also showed that single-cell storms tended to produce one polarity of CG flashes at a time, and that such storms could switch rapidly from negative to positive CG flashes when the reflectivity was near maximum. Multiple-cell storms produced both negative and positive flashes over a broad region, but each polarity tended to cluster near regions of high-reflectivity. [Copyright &y& Elsevier]

The social history of the Kirikir'i·s peoples is dependent on traditional history, archaeology, ethnohistory, cultural anthropology, and linguistics. By using these different lines of evidence, this paper explores one of the primary models (Vehik's "conflict and prestige" model) used to explain protohistoric Kirikir'i·s political development. Because of Vehik's emphasis on warfare and prestige, certain components of Kirikir'i·s social history are either excluded or disregarded. As a result, a political economy perspective is advocated which sees the Protohistoric period as a dynamic era beginning prior to the arrival of Europeans but which is able to account for changes after the appearance of these aliens. Only by unraveling the geopolitical impact of alien interaction as part of the social historical dynamic upon the indigenous societal systems of the Plains, Southwest, and Southeast will scholars of the Protohistoric period be able to understand both the processual and post-processual components of cultural interaction, exchange, and political development. [ABSTRACT FROM AUTHOR]

The 12–13 June 2002 convective initiation case from the International H2O Project (IHOP_2002) field experiment over the central Great Plains of the United States is simulated numerically with the Advanced Regional Prediction System (ARPS) at 3-km horizontal resolution. The case involves a developing mesoscale cyclone, a dryline extending from a low center southwestward with a cold front closely behind, which intercepts the midsection of the dryline, and an outflow boundary stretching eastward from the low center resulting from earlier mesoscale convection. Convective initiation occurred in the afternoon at several locations along and near the dryline or near the outflow boundary, but was not captured by the most intensive deployment of observation instruments during the field experiment, which focused instead on the dryline–outflow boundary intersection point. Standard and special surface and upper-air observations collected during the field experiment are assimilated into the ARPS at hourly intervals in a 6-h preforecast period in the control experiment. This experiment captured the initiation of four groups of convective cells rather well, with timing errors ranging between 10 and 100 min and location errors ranging between 5 and 60 km. The general processes of convective initiation are discussed. Interestingly, a secondary initiation of cells due to the collision between the main outflow boundary and the gust fronts developing out of model-predicted convection earlier is also captured accurately about 7 h into the prediction. The organization of cells into a squall line after 7 h is reproduced less well. A set of sensitivity experiments is performed in which the impact of assimilating nonstandard data gathered by IHOP_2002, and the length and interval of the data assimilation are examined. Overall, the control experiment that assimilated the most data produced the best forecast although some of the other experiments did better in some aspects, including the timing and location of the initiation of some of the cell groups. Possible reasons for the latter results are suggested. The lateral boundary locations are also found to have significant impacts on the initiation and subsequent evolution of convection, by affecting the interior flow response and/or feeding in more accurate observation information through the boundary, as available gridded analyses from a mesoscale operational model were used as the boundary condition. Another experiment examines the impact of the vertical correlation scale in the analysis scheme on the cold pool analysis and the subsequent forecast. A companion paper will analyze in more detail the process and mechanism of convective initiation, based on the results of a nested 1-km forecast. [ABSTRACT FROM AUTHOR]

This paper estimates return levels of extreme snow water equivalents (SWE) in the northern Great Plains region, containing North and South Dakota, Iowa, Minnesota, and Nebraska. The return levels are estimated from extreme-value methods using a new hybrid SWE dataset that improves the spatial resolution of existing data in the area. A novel aspect of the methods is the use of standard error margins to spatially smooth the estimated SWE return levels computed on individual grid cells. The end product is a reliable return-level estimate that controls for uncertainties in the raw observations. The methods should prove useful in analyses of other geographical regions. [ABSTRACT FROM AUTHOR]

An automated, rapidly relocatable nowcasting and prediction system, whose cornerstone is the full-physics, nested-grid, nonhydrostatic fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), has been under development at the Pennsylvania State University since the late 1990s. In the applications presented in this paper, the Rapidly Relocatable Nowcast-Prediction System (RRNPS) provides a continuous stream of highly detailed nowcasts, defined here as gridded meteorological fields produced by a high-resolution mesoscale model assimilating available observations and staying just ahead of the clock to provide immediately available current meteorological conditions. The RRNPS, configured to use 36-, 12-, and 4-km nested domains, is applied over the Great Plains for 18 case days in August 2001, over the East Coast region for 8 case days in April 2002, and for 12 case days during the winter and summer of 2003. The performance of the RRNPS is evaluated using subjective and statistical methods for runs with and without the use of continuous four-dimensional data assimilation (FDDA). A statistical evaluation of the dependence of RRNPS skill on the length of model integration yields further insight into the value added by FDDA in RRNPS nowcasts. It must be emphasized that unlike typical operational analysis systems, none of the current data are used in the nowcasts since the nowcasts are made available just ahead of the clock for immediate use. Because none of the verification data are assimilated into the RRNPS at the time of verification, this evaluation is a true test of the time-integrated effects of previous FDDA on current model solutions. Furthermore, the statistical evaluations also utilize independent data completely withheld from the system at all times. Evaluation of the RRNPS versus observations on the 4- and 12-km grids shows that there is little difference in statistical skill between the two resolutions for the two application regions. However, subjective case evaluations indicate that mesoscale detail is added to the wind and mass fields on the 4-km domain of the RRNPS as compared to the coarser 12-km domain. Statistics suggest that 4-km resolution provides slightly more accurate meteorology for the domain including complex terrain and coastlines. The statistics also show that the use of continuous FDDA in a high-resolution mesoscale model improves the accuracy of the RRNPS nowcasts, and that this unique nowcast prediction system provides immediately available forecast-analysis products that are comparable or superior to those produced at operational centers, especially for the surface and the boundary layer. Finally, the RRNPS is also designed to run locally and on demand in a highly automated mode on modest computing platforms (e.g., a dual-processor PC) with potentially very limited data resources and nonstandard data communications. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) plays an important role in land surface and atmosphere interactions. It modifies energy balance near the surface and the rate of water cycling between land and atmosphere. The lack of observed SM data prohibits understanding of SM variations at climate scales under varying land uses. However, with simulation models it is possible to develop a long-term SM dataset and study these issues. In this paper a water balance model is used to provide a quantitative assessment of SM climatologies for three land uses, namely, irrigated corn, rain-fed corn, and grass, grown under three hydroclimatic regimes in Nebraska. These regimes are stops along an east–west decreasing precipitation gradient of the Great Plains. The simulated SM climatologies are provided for the root zone as a whole and for the five layers of the soil profile to a depth of 1.2 m. As expected, the soil water content in the root zone of irrigated corn was higher than rain-fed corn or grass. The lowest levels of soil water depletion were found under rain-fed corn cultivation due to its complete reliance on naturally available SM. The annual total evapotranspiration (ET) was 34% and 36% higher for irrigated corn than for rain-fed corn and grass, respectively. The study suggests that due to interannual variability the SM variability is higher for deeper depths, as compared to near-surface depths. Growing season SM depletion and prevailing soil water content at various depths of the soil profile varies with crops, soils, and prevailing hydroclimatic conditions. The results show that land use affects the magnitude of SM variability at all time scales. At a daily temporal scale, SM variability is less under irrigated land use and sharply increases under rain-fed land uses. At the monthly scale, SM variability largely follows the trend of the daily time scale. Year-to-year SM variability is significant. Extremely dry or wet conditions enhance and reduce, respectively, the forcing of land use on SM variability at an annual time scale. Thus, large-scale interannual climate variations and land use jointly affect SM variability at this scale. [ABSTRACT FROM AUTHOR]