Central Oklahoma Research Articles

Leveraging Collaborative Partnerships to Enhance NWS and Emergency Management Communications through Exercising

Abstract Tabletop exercises examining weather-related hazards are not uncommon but are often built around somewhat generic scenarios that only touch on the meteorological communication environment at a very shallow level. A recent exercise in central Oklahoma sought to change that. A local emergency manager, personnel from a National Weather Service (NWS) forecast office, and a severe weather researcher with a background in exercise design and facilitation worked together to create and deliver a realistic severe weather simulation. Exercise participants were exposed to detailed forecast information via NWSChat—a dedicated communication tool used to connect NWS forecasters, emergency managers, and media members for real-time information sharing. NWS forecasters were able to both actively play in the exercise due to the use of NWSChat and observe how local decision-makers interpreted and utilized the impact-based decision support service (IDSS) graphics and short-term forecast updates. The collaborative approach of developing a detailed scenario with numerous real-world IDSS graphics, along with the use of NWSChat for real-time delivery, resulted in overwhelmingly positive feedback from the participants. The local emergency management office identified numerous areas for improvement in communicating real-time forecast information across their jurisdiction, along with gaps in current plans and resources. Meanwhile, the NWS forecast office had the opportunity to experiment with using the new NWSChat platform in a high-impact severe weather environment before a real-world event took place. Forecasters also gained insight into current IDSS graphic interpretation, noting areas for improved messaging to end users, such as adding storm motion to existing severe weather graphics.

Carbon dioxide fluxes over irrigated and rainfed alfalfa in the Southern Great Plains, USA

The annual dynamics of carbon dioxide (CO2) fluxes for irrigated and rainfed alfalfa (Medicago sativa L.) in the Southern Great Plains of the United States of America (USA) under different watering regimes are not yet fully understood. The main objective of this study was to examine the dynamics of eddy covariance (EC) measured CO2 fluxes in relation to various biophysical factors and hay harvests for irrigated and rainfed alfalfa in central Oklahoma, USA. The study also aimed to investigate the relationship between CO2 fluxes and satellite-derived enhanced vegetation index (EVI) at different spatiotemporal scales and to assess the temporal variability in CO2 fluxes and EVI to variable growing conditions and hay harvests. The cumulative hay yields were 7.15 t ha−1 (two harvests in 2019) in the rainfed field and ∼9 t ha−1 (4–5 harvests in 2020 and 2021) in the irrigated field. Having sufficient rainfall during April and May was crucial to achieve economically feasible yields of alfalfa during the first harvest in May. The availability of water strongly regulated the potential for regrowth and carbon uptake of alfalfa following harvesting. The alfalfa fields were near carbon neutral or a small carbon source from January to mid-March and carbon sink after the initiation of vegetative growth in mid-March. The alfalfa fields were strong carbon sinks (cumulative annual net ecosystem CO2 exchange, NEE, up to −578 g C m−2 in irrigated field) on an annual scale. When accounting for the loss of carbon due to the removal of hay from the fields, the carbon balance of the alfalfa fields varied from small carbon sinks to small carbon sources, depending on the amount of hay harvested annually and the growing conditions. In general, the temporal patterns of CO2 fluxes and EVI were similar in relation to growing conditions and hay harvests. However, some discrepancies and time lags were observed due to the coarse spatiotemporal resolution of the EVI products. Thus, it is essential to integrate two or more satellite products with different temporal and spatial resolutions to accurately monitor the frequent and varying sizes of hay harvests and vegetation regrowth after harvesting, and to simulate continuous time-series CO2 fluxes.

Evaluation of Lightning Flash Rate Parameterizations in a Cloud‐Resolved WRF‐Chem Simulation of the 29–30 May 2012 Oklahoma Severe Supercell System Observed During DC3

AbstractEighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud‐resolved simulation of the 29–30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly‐developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model‐simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model‐simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor‐based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

Modeling the impact of measured and projected climate and management systems on agricultural fields: Surface runoff, soil moisture, and soil erosion.

As global climate change poses a challenge to crop production, it is imperative to prioritize effective adaptation of agricultural systems based on a scientific understanding of likely impacts. In this study, we applied an integrated watershed modeling framework to examine the impacts of projected climate on runoff, soil moisture, and soil erosion under different management systems in Central Oklahoma. The proposed model uses measured climate data and three downscaled ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) at the water resources and erosion watershed to understand the impact of climate change and various climate conditions under three management systems: (1) continuous winter wheat (Triticum aestivum) under conventional tillage (WW-CT; baseline system), (2) continuous winter wheat under no-till (WW-NT), and (3) cool and warm season forage cover crop mixes under no-till (CC-NT). The study indicates that the occurrence of agricultural drought is projected to increase while erosion rates will remain unchanged under the WW-CT. In contrast, climate simulations imposed on the WW-NT and CC-NT systems significantly reduce runoff and sediment while preserving soil moisture levels. Especially, implementing the CC-NT system can bolster food security and foster sustainable farming practices in Central Oklahoma in the face of a changing climate.

Opioid and other drug use and drug-related mortality as indicators of Hepatitis C and Human Immunodeficiency Virus in Oklahoma

Objectives Outbreaks of injection drug use (IDU)-associated infections have become major public health concerns in the era of the opioid epidemic. This study aimed to (1) identify county-level characteristics associated with acute HCV infection and newly diagnosed IDU-associated HIV in Oklahoma and (2) develop a vulnerability index using these metrics. Methods This study employs a county-level ecological design to examine those diagnosed with acute or chronic HCV or newly diagnosed IDU-associated HIV. Poisson regression was used to estimate the association between indicators and the number of new infections in each county. Primary outcomes were acute HCV and newly diagnosed IDU-associated HIV. A sensitivity analysis included all HCV (acute and chronic) cases. Three models were run using variations of these outcomes. Stepwise backward Poisson regression predicted new infection rates and 95% confidence intervals for each county from the final multivariable model, which served as the metric for vulnerability scores. Results Predictors for HIV-IDU cases and acute HCV cases differed. The percentage of the county population aged 18–24 years with less than a high school education and population density were predictive of new HIV-IDU cases, whereas the percentage of the population that was male, white, Pacific Islander, two or more races, and people aged 18–24 years with less than a high school education were predictors of acute HCV infection. Counties with the highest predicted rates of HIV-IDU tended to be located in central Oklahoma and have higher population density than the counties with the highest predicted rates of acute HCV infection. Conclusions There is high variability in county-level factors predictive of new IDU-associated HIV infection and acute HCV infection, suggesting that different public health interventions need to be tailored to these two case populations.

Calibrating Agro-Hydrological Model under Grazing Activities and Its Challenges and Implications

Recently, the Agricultural Policy Extender (APEX) model was enhanced with a grazing module, and the modified grazing database, APEXgraze, recommends sustainable livestock farming practices. This study developed a combinatorial deterministic approach to calibrate runoff-related parameters, assuming a normal probability distribution for each parameter. Using the calibrated APEXgraze model, the impact of grazing operations on native prairie and cropland planted with winter wheat and oats in central Oklahoma was assessed. The existing performance criteria produced four solutions with very close values for calibrating runoff at the farm outlet, exhibiting equifinality. The calibrated results showed that runoff representations had coefficients of determination and Nash–Sutcliffe efficiencies >0.6 in both watersheds, irrespective of grazing operations. Because of non-unique solutions, the key parameter settings revealed different metrics yielding different response variables. Based on the least objective function value, the behavior of watersheds under different management and grazing intensities was compared. Model simulations indicated significantly reduced water yield, deep percolation, sediment yield, phosphorus and nitrogen loadings, and plant temperature stress after imposing grazing, particularly in native prairies, as compared to croplands. Differences in response variables were attributed to the intensity of tillage and grazing activities. As expected, grazing reduced forage yields in native prairies and increased crop grain yields in cropland. The use of a combinatorial deterministic approach to calibrating parameters offers several new research benefits when developing farm management models and quantifying sensitive parameters and uncertainties that recommend optimal farm management strategies under different climate and management conditions.

Ice Crystal Alignment: A Concept for High-Temporal-Resolution Monitoring Using Polarimetric Phased Array Radar

Abstract This article describes a concept whereby future operational polarimetric phased array radars (PPAR) routinely monitor ice crystal alignment regions caused by thundercloud electric fields with volume scan updates (∼12 min−1) sufficient to resolve the temporal variation due to lightning and subsequent rapid electric field regeneration in nonsevere thunderstorms. Routine observations of crystal alignment regions may enhance thunderstorm nowcasting through comparison of their temporal and spatial structure with other polarimetric signatures, integration with lightning detection data, and assimilation into convection resolving numerical weather prediction models. If crystal alignment observations indicate strong electrification well in advance of the first lightning strike and likewise reliably indicate the decay of strong electric fields at the end of a storm, this capability may improve warning for lightning-sensitive activities such as airport ramp operations and space launch. Experimental observations of crystal alignment volumes in central Oklahoma severe storms and their relation to those storms’ structures are presented and used to motivate discussion of possible PPAR architectures. In one case—a tornadic supercell—these observations illustrate an important limitation. Even the hypothesized 12 min−1 volume scan update rate would not resolve the temporal variation of the crystal alignment regions in such storms, suggesting that special, adaptive scanning methods may be appropriate for such storms. We describe how future operational phased array radars could support a crystal alignment measurement mode via parallel, time-multiplexed processing and discuss potential impacts on the radar’s primary weather observation mission. We conclude by discussing research needed to better understand technical challenges and operational benefits.

Evaluation and Intercomparison of Small Uncrewed Aircraft Systems Used for Atmospheric Research

Abstract Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.

Multiscale fractures, stress and reservoir quality characterization: The Mississippian Meramec and Osage intervals, STACK play, Central Oklahoma

This study characterized in-situ stress-fields and multi-scale fractures in the low porosity and low permeability Mississippian-aged “Meramec and Osage” intervals in the Anadarko Basin of central Oklahoma. As the two reservoirs' productivity is influenced by fractures, understanding fracture nature, frequency and distribution is important for the development of these reservoirs. The study implemented an integrated approach to characterize in-situ stress-fields and related fractures utilizing 3D seismic data, cores, petrophysics, and formation micro-imaging logs. Density of fractures was interpreted from integrated analyses of seismic, petrophysical, core, and FMI log data. Fracture orientations were determined from the seismic and FMI log data. Detected fractures in the “Meramec” interval preferentially occur in pervasively calcite-cemented rock with low porosity. Because of the adverse effect of calcite cementation, fractures did not significantly improve reservoir quality within the “Meramec” interval. In contrast, detected fractures in the “Osage” interval added sufficient porosity and permeability to overcome negative cementation effects and improved the overall reservoir quality. This study revealed a rotation of the horizontal stress orientations from ancient stress regimes to the present-day in-situ stress regimes. The study demonstrated the application of integrated seismic and non-seismic data in fracture and stress-field characterization, improved our understanding of the effects of fractures on reservoir quality to reduce risks associated with exploring low-porosity/low-permeability mixed carbonate and siliciclastic reservoirs.

Profit efficiency in the provision of ecosystem services in the Cross Timbers forests

We focused on modeling the profitability of the Cross Timbers (CT) forests with regards to the provision of ecosystem services, including timber production, carbon sequestration, and water yield. The Cross Timbers region spans from southern Kansas to central Oklahoma into Texas, encompassing marginally productive timberlands. We utilized a translog stochastic profit frontier approach to analyze forest plot data collected from the Forest Inventory Analysis program between 2008 and 2019. Our results indicated that, on average, the CT forests yield around 85% of the maximum profit. Only 12% of the forest plots generated positive revenues, and the average profit across all forest plots was -$484.51 ha−1. This means that even with a 15% reduction in profit losses, the majority of the forest plots in the CT region would still not be economically viable. Forest age, ownership, forest species, and site productivity were statistically significant impacts on profit efficiency. At the margin, we found that profit inefficiency increased under private ownership and with higher levels of site productivity. Furthermore, as forests age, profit efficiency was also reduced. These findings highlight the complexity and variability of forest management systems and underscore the need for further research to fully understand the factors influencing efficiency in different contexts.

A comparison of moderate and high spatial resolution satellite data for modeling gross primary production and transpiration of native prairie, alfalfa, and winter wheat

Although agroecosystems have a significant potential to offset carbon dioxide (CO2), the amount of CO2 captured can vary significantly depending on management practices. Accurate estimation of gross primary production (GPP) and transpiration (T) of agroecosystems at the field scale are essential for the study of food security and water resource management. To date, the carbon and water fluxes data products for commercial agroecosystems are limited, mostly at the moderate spatial resolution (MSR, hundreds of meters), which cannot be used to assess the temporal dynamics of GPP and T at the field scale. This study used the vegetation photosynthesis model (VPM) and vegetation transpiration model (VTM) to estimate field-level daily GPP (GPPVPM) and T (TVTM), respectively, in native prairie, alfalfa (Medicago sativa L.), and winter wheat (Triticum aestivum L.) in central Oklahoma, USA. We evaluated the reliability and advantages of vegetation indices (enhanced vegetation index, EVI and land surface water index, LSWI) in monitoring the land surface phenology using moderate spatial resolution data from Moderate Resolution Imaging Spectroradiometer (MODIS) and high spatial resolution (HSR, tens of meters) data from Landsat and Sentinel-2. The accuracy of GPPVPM and TVTM estimates at different spatial scales was evaluated using GPP (GPPEC) and evapotranspiration (ETEC) from the eddy flux tower sites, respectively. Results demonstrate the capacity of VPM and VTM to estimate the field-level carbon and water flux dynamics and their responses to weather conditions. The use of HSR vegetation indices helped to address certain challenges faced by MSR indices, especially in capturing the crop phenology in smaller areas with conservation measures or disturbances. The findings highlight the importance of using HSR GPP estimates to reduce uncertainty in quantifying CO2 fluxes for croplands and grasslands. The findings also demonstrate the ability of the models to track field-level vegetation phenology, carbon uptake, and water use in agroecosystems under different management practices.

Impacts of soil pH and extractable aluminum on winter canola production in the southern Great Plains

Winter canola (Brassica napus L.) is a potential alternative to winter wheat in Oklahoma rotation systems as a means to overcome the negative impacts of continuous wheat systems. However, its performance may suffer in the acid soils that are common to intensive agriculture systems in the southern Great Plains region. The objective of this study was to quantify the impact of soil pH and Al3+ concentration on winter canola production. Two field trials were conducted in 2016 and 2017 across four different locations in central Oklahoma to evaluate the performance of four canola cultivars in soils with a range of pH from 4.0 to 8.0. Yield, soil pH, and Al3+ concentrations were measured from each plot to study the relationships between these variables. At all but one location, soil pH and Al3+ concentrations were inversely related and when data across these locations were combined, Al3+ concentrations decreased as pH increased to a critical value of 4.8 (r2 = 0.83). In general, it was found that yield decreased linearly as pH decreased below 5.8 (r2 = 0.75) and increased linearly as Al3+ concentrations decreased below 87 mg kg−1 (r2 = 0.73). Above these thresholds, yield was unrelated to pH or Al3+ concentrations. It was also observed that at one location with very low naturally occurring Al3+, high canola yields were achievable even in low soil pH. Therefore, Al3+ concentrations may be a better indicator of the effects of acidic soils on winter canola yields than pH values alone.

Rickettsia tillamookensis (Rickettsiales: Rickettsiaceae) in Ixodes scapularis (Acari: Ixodidae) in Oklahoma.

Some of the most prevalent arthropod-borne pathogens impacting humans in the United States are transmitted by Ixodes ticks. However, little is known regarding the Rickettsia species that inhabit Ixodes scapularis in the United States. The aim of this study was to screen adult I. scapularis collected in central Oklahoma over an 8-yr period for the presence of tick-borne rickettsial pathogens or potential pathogens. During 2014-2021, 112 adult specimens of I. scapularis were collected from central Oklahoma. Amplicons for Rickettsia spp. were amplified from 53 (47.3%) of the samples. Of the positive ticks, 42 (79.2%) amplicon-positive Rickettsia samples were 100% identical to Rickettsia buchneri, 10 (18.9%) were 100% identical to R. tillamookensis strain Tillamook 23, and 1 (1.9%) specimen showed high identity for Rickettsia amblyommatis. This study highlights the importance of considering Rickettsia-specific assays when assessing Ixodes species ticks for potential pathogens.

Seasonality of Amblyomma americanum (Acari: Ixodidae) Activity and Prevalence of Infection with Tick-Borne Disease Agents in North Central Oklahoma.

Background: Amblyomma americanum is the most common tick infesting both animals and humans in the southern United States and transmits a variety of zoonotic agents. The rise in tick-borne diseases (TBD) globally imparts a need for more active surveillance of tick populations to accurately quantify prevalence and risk of tick-borne infectious organisms. To better understand TBD risk in north central Oklahoma, this study aimed to describe the current seasonal activity of A. americanum in this region and investigate the seasonality of tick-borne infectious agents. Materials and Methods: Tick collections were performed twice a month for a duration of 2 years at a field site in Payne County, Oklahoma. Total nucleic acid was extracted from a subset of adult A. americanum and tested for Rickettsia spp., Ehrlichia spp., and Borrelia spp. using established PCR protocols. Results: Peak activity times for each life stage were observed, with adults primarily active 1 month earlier than historical seasonal trends describe, and male A. americanum active earlier in the year than female A. americanum. Rickettsia spp., Ehrlichia chaffeensis, Ehrlichia ewingii, and Borrelia lonestari were found in 26.4%, 6.1%, 2.5%, and 1.1% of adult A. americanum, respectively. No seasonal trend in spotted fever group Rickettsia spp. (SFGR) was observed in peak activity months. Conclusions: This study found an apparently shifting phenology for A. americanum adults in Oklahoma. While these results did not show a trend in SFGR, further investigation is needed to better understand the potential seasonality of infection prevalence within A. americanum across the expanding range of this vector, especially considering the extended activity of males in winter months.

Monitoring Terrestrial Water Storage, Drought and Seasonal Changes in Central Oklahoma With Ambient Seismic Noise

AbstractSignificant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS and drought is critical for water‐resource management and water‐deficit estimation. We use continuous seismic ambient noise to monitor temporal evolution of near‐surface seismic velocity, dv/v, in central Oklahoma from 2013 to 2022. The derived dv/v is found to be negatively correlated with gravitational measurements and groundwater depths, showing the impact of groundwater storage on seismic velocities. The hydrological effects involving droughts and recharge of groundwater occur on a multi‐year time scale and dominate the overall derived velocity changes. The thermoelastic response to atmospheric temperature variations occurs primarily on a yearly timescale and dominates the superposed seasonal velocity changes in this study. The occurrences of droughts appear simultaneously with local peaks of dv/v, demonstrating the sensitivity of near‐surface seismic velocities to droughts.

A multi-sensor array for detecting and analyzing nocturnal avian migration.

Avian migration has fascinated humans for centuries. Insights into the lives of migrant birds are often elusive; however, recent, standalone technological innovations have revolutionized our understanding of this complex biological phenomenon. A future challenge for following these highly mobile animals is the necessity of bringing multiple technologies together to capture a more complete understanding of their movements. Here, we designed a proof-of-concept multi-sensor array consisting of two weather surveillance radars (WSRs), one local and one regional, an autonomous moon-watching sensor capable of detecting birds flying in front of the moon, and an autonomous recording unit (ARU) capable of recording avian nocturnal flight calls. We deployed this array at a field site in central Oklahoma on select nights in March, April, and May of 2021 and integrated data from this array with wind data corresponding to this site to examine the influence of wind on the movements of spring migrants aloft across these spring nights. We found that regional avian migration intensity is statistically significantly negatively correlated with wind velocity, in line with previous research. Furthermore, we found evidence suggesting that when faced with strong, southerly winds, migrants take advantage of these conditions by adjusting their flight direction by drifting. Importantly, we found that most of the migration intensities detected by the sensors were intercorrelated, except when this correlation could not be ascertained because we lacked the sample size to do so. This study demonstrates the potential for multi-sensor arrays to reveal the detailed ways in which avian migrants move in response to changing atmospheric conditions while in flight.

Viability of Veterinary-Relevant Viruses in Decomposing Tissues over a 90-Day Period Using an In-Vitro System.

Depopulation is frequently employed during outbreaks of high-impact animal diseases. Security breaches in sites managing mortality may jeopardize pathogen control efforts as infected carcasses can serve as an infection source. This study evaluated the viability and nucleic acid detection of veterinary-relevant viruses or their surrogates in decomposing tissues. The used viruses were: Senecavirus A1 (SVA), feline calicivirus (FCV), bovine viral diarrhea virus (BVDV), porcine epidemic diarrhea virus (PEDV), bovine alphaherpesvirus 1 (BoHV-1), and swinepox virus (SwPV). Viruses were spiked in three decomposing tissues (swine bone marrow and spleen, and bovine bone marrow) and maintained for 90 days. Samples were kept under two temperature conditions resembling the average soil temperature in central Oklahoma, US, during the winter and summer (5.5 °C and 29.4 °C). At 5.5 °C, SVA and FCV remained viable over the 90 days of the study, followed by BVDV (75 days), BoHV-1 and SwPV (60 days), and PEDV (10 days). At 29.4 °C, SVA remained viable for 45 days, followed by BVDV and BoHV-1 (14 days). SwPV was viable for 10 days, whereas FCV and PEDV were viable for 5 days. Overall, viral nucleic acid detection was not significantly altered during the study. These findings support decision-making and risk management in sites overseeing animal mortality.

Targeted Balloon Observations of Stratosphere‐To‐Troposphere Transport From a Mesoscale Convective System

AbstractStratosphere‐troposphere exchange (STE) is important to the global radiation budget because it is capable of inducing significant changes in trace greenhouse gases such as ozone and water vapor. In the extratropics, stratosphere‐to‐troposphere—or downward—transport (STT) dominates and is routinely driven by upper‐troposphere jet circulations and cyclones. Tropopause‐overshooting convection provides a more rapid STE pathway, but STT in convection is less understood and targeted observations are limited to a handful of fortuitous aircraft encounters. In this study, we seek to improve understanding of STT near thunderstorm anvils using balloon observations of ozone, ground‐based radar observations, visible satellite imagery, and model output. Radar and satellite imagery are used to identify and ultimately target convection driving the “ozone‐wrapping” process. Herein, observations from a single mesoscale convective system in central Oklahoma are reported. A significant ozone enhancement 40%–60% greater than background concentrations in the free troposphere was observed during the balloon ascent underneath and within the anvil of the storm. Backwards particle trajectories were calculated to rule out other sources of this feature such as long‐range transport of stratospheric air and smoke pollution from nearby wildfires. To our knowledge, this work presents the first targeted ozonesonde launch and sampling of this STT process.

Role of parasitoids and landscape structure in aphid population dynamics in winter canola

Three aphid species infest winter canola, Brassica napus L. fields in central Oklahoma and are serious pests: the cabbage aphid, Brevicoryne brassicae L., green peach aphid, Myzus persicae (Sulzer), and turnip aphid, Lipaphis pseudobrassicae (Davis). Mortality caused by parasitoids may be an important component of biological control of aphids in Oklahoma canola fields. Therefore, it is important to determine the effect of parasitoids on aphids in canola and the factors that affect it. We undertook a study during three consecutive growing seasons to: 1) estimate aphid suppression by parasitoids in each of 23 canola fields using cages that excluded natural enemies and cages that permitted access by parasitoids; and 2) evaluate how aphid parasitism in canola is related to the composition and configuration of the landscape surrounding each canola field. Parasitism was estimated using turnip aphid infested sentinel canola plants stationed in each field in autumn and in spring of each growing season. Two parasitoids with broad host ranges, Diaeretiella rapae (M’Intosh) and Aphelinus nigritus (Howard), parasitized turnip aphids in canola. There were fewer aphids and more parasitoids in cages that permitted access to parasitoids than in cages that excluded natural enemies. Partial redundancy analysis demonstrated that parasitism rate by D. rapae was positively related to landcover of wetlands and negatively related to contagion of patches. Parasitism by A. nigritus was positively but weakly associated with landcover of summer crops, but not with any other measured landscape variable. Wetlands in central Oklahoma agricultural landscapes apparently are habitat for aphid parasitoids from which they disperse to canola fields and parasitize aphids. Partial redundancy analysis showed that relative aphid density in fields was negatively related to parasitism by D. rapae. Results indicate that parasitoids suppress aphid infestations in canola fields and demonstrate potential for habitat management to improve biological control of aphids in canola.

Doppler Lidar Measurements of Wind Variability and LLJ Properties in Central Oklahoma during the August 2017 Land–Atmosphere Feedback Experiment

Abstract Low-level jets (LLJs) are an important nocturnal source of wind energy in the U.S. Great Plains. An August 2017 lidar-based field-measurement campaign [the Land–Atmosphere Feedback Experiment (LAFE)] studied LLJs over the central SGP site in Oklahoma and found nearly equal occurrences of the usual southerly jets and postfrontal northeasterly jets—typically rare during this season—for an opportunity to compare the two types of LLJs during this month. Southerly winds were stronger than the northeasterlies by more than 4 m s−1 on average, reflecting a significantly higher frequency of winds stronger than 12 m s−1. The analysis of this dataset has been expanded to other SGP Doppler-lidar sites to quantify the variability of winds and LLJ properties between sites of different land use. Geographic variations of winds over the study area were noted: on southerly wind nights, the winds blew stronger at the highest, westernmost sites by 2 m s−1, whereas on the northeasterly flow nights, the easternmost sites had the strongest wind speeds. Lidar measurements at 5 sites during August 2017, contrasted to the 2016–21 summertime data, revealed unusual wind and LLJ conditions. Temporal hodographs using hourly averaged winds at multiple heights revealed unorganized behavior in the turbulent stable boundary layer (SBL) below the jet nose. Above the nose, some nights showed veering qualitatively similar to inertial oscillation (IO) behavior, but at amplitudes much smaller than expected for an IO, whereas other nights showed little veering. Vertical hodographs had a linear shape in the SBL, indicating little directional shear there, and veering above, resulting in a hook-shaped hodograph with height. Significance Statement Doppler-lidar measurements at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) were used to quantify the variability of winds and low-level jet (LLJ) properties between five sites of different land use and wind regimes across this area. Knowledge of wind and LLJ structure and dynamics is important for many applications, and strong southerly LLJ winds at night are an important resource for wind energy. The analysis of multiyear (2016–21) summertime LLJ parameters provided insight into the LLJ climatology in this part of the Great Plains.