US Southern Great Plains Research Articles

Dynamical downscaling the impact of spring Western US land surface temperature on the 2015 flood extremes at the Southern Great Plains: effect of domain choice, dynamic cores and land surface parameterization

Recent studies have shown that spring land surface temperature (LST) and subsurface temperature (SUBT) over the high elevation areas in the western US (WUS) have significant impacts on the downstream summer droughts/floods in North America. In this paper, both the National Centers for Environmental Prediction—Global Forecast System (NCEP-GFS) general circulation model (GCM) and the weather research and forecasting (WRF) regional climate model (RCM) are employed, where RCM scenarios utilized initial and lateral boundary conditions derived from the corresponding NCEP-GFS scenarios. Here we use a late spring flood in the US Southern Great Plains (SGP) case to examine whether simulation of the LST/SUBT downstream effects is sensitive to the domain size choice, change in dynamical cores within the same model, as well as to the representation of surface processes parameterizations. Although all RCM experiments with different settings simulate reasonably geographical patterns of observed LST and precipitation anomalies, we found that the choice of the domain size is crucial for proper downscaling the LST/SUBT downstream effects to accurately produce the observed precipitation/LST anomalies over the SGP/WUS, respectively, along with the associated large-scale features. The southern boundary location has been identified to be crucial in producing the SGP Low Level Jet strength, which in turn brings more moisture from the Gulf of Mexico to the SGP and thereby resulting in a better simulation of the precipitation anomaly in that area. The sensitivity of the simulation of the LST/SUBT downstream effect to dynamical cores is assessed by inter-comparing the Non-hydrostatic Mesoscale Model (NMM) and the Advanced Research WRF dynamic cores. We find NMM was better at generating the large-scale eastward wave train, a crucial process associated with the LST/SUBT downstream effect. Meanwhile, this study also shows that the LST/SUBT downstream effects were not significantly dependent on the surface process parameterizations, although the Simplified Simple Biosphere model version 3 (SSiB3) highlighted a better performance over SSiB2.

Agricultural management effects on soil health across the US Southern Great Plains

Improving soil health is commonly suggested as a way to “buffer” agricultural systems against climate change impacts such as increases in drought, storm severity, and annual temperature. A number of producers in the US Southern Great Plains (SGP) and elsewhere have begun to manage their systems with an emphasis on improving soil health, but adoption of these practices is not yet widespread. There is evidence that soil health management (SHM) has positive effects on soil health that conventional management (CM) does not, but the effects have not been compared to sustainability managed conventional systems, nor have they been quantified using a standard method across regional climatic gradients such as those that characterize the SGP. In this study, we used a network of three pairs of SHM and CM sites at 12 locations in Kansas, Oklahoma, and Texas to test a suite of biological, chemical, and physical soil health indicators. We analyzed differences among these indicators to better understand how SHM and CM fields compared across the region, and to identify potential effects of precipitation and temperature on these differences. We found that responses to management were not uniform across the SGP and that soil health indicators responded primarily to climate, rather than to management practices. These results suggest that soil health responses as a result of SHM may be constrained by other factors, resulting in variations across the landscape that make soil health assessments challenging. Our findings underscore the importance of understanding management and other impacts on soil health when developing realistic land management goals.

Canola Emergence and Early Growth Were Not Affected by Allelopathic Properties of Wheat Residue

Core Ideas Negative impacts of fresh wheat residue on canola were demonstrated in the lab. No negative impacts were observed in pot conditions that mimicked the field. Results were generally consistent across 15 wheat varieties and 2 soils. Negative impacts of wheat residue reported on canola are likely physical impacts. Wheat (Triticum aestivum L.) has been studied for its residual chemical effects on other crop plants, which are often cultivar‐specific, but its effects on canola (Brassica napus L.), a crop increasingly rotated with wheat, are less understood. Because canola production is spreading to new areas, including the US Southern Great Plains, our objective was to evaluate the potential for allelopathic properties of wheat residue from regional cultivars to negatively impact emergence and early growth of canola. A laboratory study was conducted, establishing a baseline for potential allelopathic effects, and an outdoor pot study was conducted, designed to test for these effects in conditions mimicking field conditions and crop management (e.g., residue weathered on the soil surface for the summer to simulate fallow). In the laboratory, with exposure to fresh wheat residue extracts, canola germination was delayed, but persistent, concentration‐dependent negative effects on radicle elongation were observed, similar to other reported results. In the pot studies, wheat residue did not affect canola emergence, with minimal variation among 15 wheat cultivars tested in two soils, and early growth increased by an average of 23% with residue treatment. The canola emergence and early growth results indicated an absence of allelopathy at planting and the presence of growth‐promoting factors following wheat residue application. Together, these studies indicate that allelopathic properties of wheat residue can negatively impact canola in laboratory conditions, but suggests these effects are not likely to be realized under typical field conditions. Negative impacts of wheat residue on canola, which have been reported, are likely physical in nature.

Forage Potential of Summer Annual Grain Legumes in the Southern Great Plains

Core Ideas Forage quality gap during mid through late summer affects stocker cattle production. A broad range of under‐utilized grain legumes may serve as high‐quality forages. Adoption of such crops could enhance sustainability of stocker‐based grazing systems. Winter wheat (Triticum aestivum L.) and perennial warm‐season grasses are the primary forage resources for grazing yearling stocker cattle (Bos taurus) in the US Southern Great Plains (SGP). However, low nutritive value of perennial grasses during mid to late summer limits high rates of growth by stocker cattle. In response, there has been a continued search for plant materials with the potential to provide forage high in crude protein (CP) and digestibility during August through September. A broad range of under‐utilized legume species that are grown as grain crops in Africa, India, and South and Central America may have some capacity to serve as high quality pasture or harvested forage in the SGP. However, any crop selection must account for limitations related to unpredictable summer rainfall amounts and patterns, and the frequent occurrence of prolonged drought. Further, any selection should not create water deficits for following winter wheat, the primary forage and grain crop in the region. This article summarizes a small subset of the broad range of underutilized grain legumes (pulses) which exist worldwide and soybean [Glycine max (L.) Merr.] that may have capacity to serve as high quality forage for late‐summer grazing. Bringing these crops into forage–stocker production systems could improve the overall system effectiveness, in addition to providing other ecosystem services (e.g., ground cover, grain crops).

Agronomic and Economic Effects of Two Enhanced‐Efficiency Urea Fertilizer Technologies on Southern Great Plains Winter Wheat

Core Ideas Stabilized urea improved wheat grain yield and protein in the Southern Plains.Stabilized urea at a higher rate brought higher net profits than untreated urea at all price points.A safe seed‐placed rate for polymer‐coated urea in regional wheat is lower than 30 kg N ha–1.No benefit was observed in splitting nitrogen application in this study. In no‐till wheat (Triticum aestivum L.) cropping systems of the US Southern Great Plains, urea fertilizer is commonly surface broadcast and producers rely on unpredictable precipitation in dryland conditions for incorporation into the soil. Several enhanced‐efficiency fertilizer technologies are designed to reduce N loss in this scenario, though there are not published reports on evaluations of these in regional wheat systems. Here we report on an evaluation of two enhanced‐efficiency fertilizer technologies, polymer‐coated urea (PCU) and urease/nitrification inhibitor‐stabilized urea (SU), which were compared to untreated urea at different application rates (0, 31.5, and 70 kg N ha−1) and timings (at‐planting and split) in two locations differing in soil type (clay loam and loamy fine sand). The fertilizer was broadcast, except for PCU, which was drilled in‐row. The greatest yield was observed with a high at‐planting rate of SU, where yield was 26% greater than with untreated urea and 34% greater than with no fertilizer. Yield improvement with SU was associated with greater grain N uptake efficiency and protein content. The high SU rate brought higher net profits than untreated urea at all price points analyzed and surpassed the no‐fertilizer control as price increased. As might be expected with seed placement, there was substantial crop damage at the high rate of PCU, but even minor damage at the lower rate. The results suggest that a safe seed‐placed rate for PCU in wheat in this environment is somewhat lower than 30 kg N ha−1. No benefit was observed in splitting the N application.

Sensitivity of Numerical Simulations of a Mesoscale Convective System to Ice Hydrometeors in Bulk Microphysical Parameterization

Mesoscale convective systems (MCSs) and their associated cloud properties are the important factors that influence the aviation activities, yet they present a forecasting challenge in numerical weather prediction. In this study, the sensitivity of numerical simulations of an MCS over the US Southern Great Plains to ice hydrometeors in bulk microphysics (MP) schemes has been investigated using the Weather Research and Forecasting (WRF) model. It is found that the simulated structure, life cycle, cloud coverage, and precipitation of the convective system as well as its associated cold pools are sensitive to three selected MP schemes, namely, the WRF single-moment 6-class (WSM6), WRF double-moment 6-class (WDM6, with the double-moment treatment of warm-rain only), and Morrison double-moment (MORR, with the double-moment representation of both warm-rain and ice) schemes. Compared with observations, the WRF simulation with WSM6 only produces a less organized convection structure with a short lifetime, while WDM6 can produce the structure and length of the MCS very well. Both simulations heavily underestimate the precipitation amount, the height of the radar echo top, and stratiform cloud fractions. With MORR, the model performs well in predicting the lifetime, cloud coverage, echo top, and precipitation amount of the convection. Overall results demonstrate the importance of including double-moment representation of ice hydrometeors along with warm-rain. Additional experiments are performed to further examine the role of ice hydrometeors in numerical simulations of the MCS. Results indicate that replacing graupel with hail in the MORR scheme improves the prediction of the convective structure, especially in the convective core region.

Aerosol microphysical and radiative effects on continental cloud ensembles

Aerosol–cloud–radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.

Winter Canola: A Potential Dual‐Purpose Crop for the United States Southern Great Plains

Core Ideas Canola forage production was higher than wheat in fall but not in later harvests. Many of the forage quality parameters were superior in canola compared with wheat. Forage harvest decreased canola yield even before bolting but not in wheat. Canola has dual‐purpose use potential (forage and seed yield) with LF harvest. Winter canola (Brassica napus L. biennus) has the potential to be a dual‐purpose crop in the US Southern Great Plains, a region with cereal fallow mono‐cropping. However, there is little information on dual‐purpose canola in the region. Therefore, field studies were conducted in Clovis, NM, in 2013, 2014, and 2015 to compare harvesting time effect on forage productivity (dry matter), quality, and oil and seed production of canola and wheat. Harvesting time treatments were late‐fall (LF), mid‐winter (MW), early‐spring (ES), late‐spring (LS), and no‐harvest (NH). The two forage crops were canola (cv. DKW44‐10, Griffin, and Safran) and wheat (cv. TAM 111 and TAM 113). In general, crop dry matter increased and forage nutritive values decreased with delay in harvest. Dry matter of LF to ES harvests ranged from 2950 to 7740 (canola) and from 2390 to 7490 kg ha−1 (wheat), suggesting superior forage production of canola with LF to ES harvests. Crops had similar crude protein and acid detergent fiber. Canola's neutral detergent fiber was lower (238 vs. 425 g kg−1), whereas its relative feed value (188–425) was higher than wheat (127–204). Average canola seed yields (excluding 2014) were 4360, 3040, 2940, and 2720, 930 kg ha−1 with the NH, LF, MW, ES, and LS forage harvests, respectively. Forage harvest had inconsistent effects on wheat seed yield. These results show canola's potential to produce high‐quality forage and seed yield and indicate that canola can be used as a rotational break crop in the crop–livestock production systems of the Southern Great Plains.

Representing winter wheat in the Community Land Model (version 4.5)

Abstract. Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land–atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.

Human factors were dominant drivers of record low streamflow to a surface water irrigation district in the US southern Great Plains

Irrigated agriculture in the North Fork of the Red River watershed in western Oklahoma and the Texas Panhandle depends on groundwater upstream of Lake Altus-Lugert and surface water from the lake, but like much of the world, the region is prone to water scarcity. During a severe drought from 2010 to 2015, streamflow into the lake reached record lows, and the lake was depleted until no water remained for the surface water irrigation district. Area residents were left wondering whether drought or human factors were primarily responsible for the reduced streamflow and the four years of crop failures that resulted. We aimed to clarify climate and human influences on streamflow in the North Fork of the Red River watershed by (1) quantifying changes in annual streamflow, climate, groundwater use, and land use upstream from Lake Altus-Lugert from 1970 to 2014, (2) determining the relative contributions of climate and human factors to changes in streamflow, and (3) developing statistical models describing the relationships of climate and human variables with streamflow. We found a counteracting increase (around 1986) and decrease (around 2001) in streamflow, with human factors being responsible for slightly more than half (51–56%) of each change. There were no long-term trends in precipitation and reference evapotranspiration (ET0), but low streamflow from 2002 to 2014 coincided with a period of low precipitation, high ET0, and a 75% increase in groundwater withdrawal for irrigation in the Oklahoma portion of the watershed. A multiple regression model containing only precipitation and groundwater withdrawal for irrigation explained 81% of annual streamflow variability. These statistical relationships suggest that upstream groundwater use was an important driver of streamflow changes. Our results indicate that sustained agricultural productivity near Lake Altus-Lugert may require the adoption of conjunctive water management strategies, and our methods offer a framework for similar assessments in other water-scarce regions.

Stem Rust Resistance in ‘Jagger’ Winter Wheat

‘Jagger’ has been used widely as a parent to develop hard red winter wheat (Triticum aestivum L.) varieties throughout the US southern Great Plains. Jagger has resistance to the stem rust pathogen race TTTTF, which is virulent to many winter wheat cultivars, yet the genetic basis of this resistance was unknown. Marker analysis and resistance to leaf rust and stripe rust demonstrated that Jagger has the 2NS/2AS translocation from T. ventricosum (Tausch) Ces., Pass. & Gilelli. This segment contains resistance genes Sr38, Lr37, and Yr17. Stem rust infection types on Jagger, however, indicated that an additional stem rust resistance gene is present. Jagger is resistant to TTTTF whereas the Sr38 stem rust differential line ‘VPM1’ is susceptible. A BC1F3 population developed from the cross Jagger/2*‘LMPG‐6’ was tested with race TTTTF. Resistant and susceptible DNA bulks were genotyped with a custom 9000 SNP Illumina iSelect Bead Chip using bulked segregant analysis. We identified a locus linked with the resistance gene on chromosome arm 4AL, where Sr7 is located. Crosses between Jagger BC1F3 lines resistant to TTTTF and germplasm with Sr7a identified no recombinants, indicating that resistance to TTTTF in Jagger could be conferred by Sr7a. We confirmed the effectiveness of Sr7a resistance to race TKTTF, which caused the stem rust epidemic in Ethiopia from 2013 to 2014. The molecular markers identified in this study may be used to screen for the resistance gene Sr7a and track its presence in breeding programs.

Evaluation of double-moment representation of ice hydrometeors in bulk microphysical parameterization: comparison between WRF numerical simulations and UND-Citation data during MC3E

The influence of double-moment representation of warm-rain and ice hydrometeors on the numerical simulations of a mesoscale convective system (MCS) over the US Southern Great Plains has been evaluated. The Weather Research and Forecasting (WRF) model is used to simulate the MCS with three different microphysical schemes, including the WRF single-moment 6-class (WSM6), WRF double-moment 6-class (WDM6), and Morrison double-moment (MORR) schemes. It is found that the double-moment schemes outperform the single-moment schemes in terms of the simulated structure, life cycle, cloud coverage, precipitation, and microphysical properties of the MCS. However, compared with UND-Citation observations, collected during the Midlatitude Continental Convective Clouds Experiment (MC3E), the WRF simulated ice hydrometeors with all three schemes do not agree well with the observations. Overall results from this study suggest that uncertainty in microphysical schemes could still be a productive area of future research from perspective of both model improvements and observations.

A prototype physical database for passive microwave retrievals of precipitation over the US Southern Great Plains

AbstractAn accurate understanding of the instantaneous, dynamic land surface emissivity is necessary for a physically based, multi‐channel passive microwave precipitation retrieval scheme over land. In an effort to assess the feasibility of the physical approach for land surfaces, a semi‐empirical emissivity model is applied for calculation of the surface component in a test area of the US Southern Great Plains. A physical emissivity model, using land surface model data as input, is used to calculate emissivity at the 10 GHz frequency, combining contributions from the underlying soil and vegetation layers, including the dielectric and roughness effects of each medium. An empirical technique is then applied, based upon a robust set of observed channel covariances, extending the emissivity calculations to all channels. For calculation of the hydrometeor contribution, reflectivity profiles from the Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are utilized along with coincident brightness temperatures (Tbs) from the TRMM Microwave Imager (TMI), and cloud‐resolving model profiles. Ice profiles are modified to be consistent with the higher frequency microwave Tbs. Resulting modeled top of the atmosphere Tbs show correlations to observations of 0.9, biases of 1K or less, root‐mean‐square errors on the order of 5K, and improved agreement over the use of climatological emissivity values. The synthesis of these models and data sets leads to the creation of a simple prototype Tb database that includes both dynamic surface and atmospheric information physically consistent with the land surface model, emissivity model, and atmospheric information.

Green Manures in Continuous Wheat Systems Affect Grain Yield and Nitrogen Content

Continuous winter wheat (Triticum aestivum L. em Thell.) is the foundation for most US Southern Great Plains (SGP) agriculture. Inorganic N fertilizers are important to wheat production, but increasing N prices have caused producers to reconsider growing legumes during summer fallow for green N. This study was conducted during 2008 to 2012 to determine the potential for using lablab [Lablab purpureus (L.) Sweet cv. Rio Verde] to support wheat under conventional and no‐till management compared with soybean [Glycine max (L.) Merr. cv. Laredo] and three inorganic fertilizer treatments (none, 40, and 80 kg N ha−1). Legume seeds were inoculated and sown after wheat harvest each year, grown from June to August, and terminated in early September. Wheat was then sown with or without preplant tillage and grown to maturity. Grain yield, N concentration, and N accumulated in grain were analyzed to define N treatment, tillage system, and year effects. The amount and distribution of precipitation during 2008 to 2012 varied from 53 to 92% and 63 to 160% of the long‐term averages for wheat (688 mm) and legume (162 mm) phases. Tillage effects were nonsignificant (P < 0.76), but N treatment × year interactions were significant for grain yield, N concentration, and N accumulated in grain (P < 0.01). The legumes resulted in some single‐year increases in grain yield, but the overall yield response was inconsistent. The legume treatments reduced N concentration in wheat grain compared with the unfertilized control. These results show that neither legume was an effective short‐term (≤4‐yr) N source for systems of continuous wheat production in the SGP.

Evapotranspiration partitioning and water use efficiency of switchgrass and biomass sorghum managed for biofuel

Switchgrass (Panicum virgatum L.) and biomass sorghum (Sorghum bicolor L. Moench) are two candidate bioenergy crops for the US Southern Great Plains region. In this water-limited region, there is a need to partition evapotranspiration (ET) and to determine the water use efficiency (WUE) of these potential feedstocks. Both crops were grown in a field plot experiment at Stillwater, OK. Soil water content measurements were made by neutron probe every two weeks to a depth of 2.0m in 0.2-m intervals over the course of three growing seasons. Growing season ET was estimated as the difference between growing season precipitation and change in root zone soil water storage. Evapotranspiration was partitioned by measuring canopy interception using interception trays and estimating soil evaporation using the FAO-56 dual crop coefficient method. Transpiration was calculated as ET minus soil evaporation and canopy interception. Transpiration was the largest component of ET; however, soil evaporation and canopy interception accounted for 28% of growing season ET for switchgrass and 42% for biomass sorghum. Although the non-productive losses were greater from biomass sorghum, WUE values of 9–49kgha−1mm−1 based on ET and 22–83kgha−1mm−1 based on transpiration were observed for biomass sorghum, which were greater than the WUE values of switchgrass, 8–21kgha−1mm−1 based on ET and 12–28kgha−1mm−1 based on transpiration. These results demonstrate that biomass sorghum is a candidate feedstock with potential to achieve greater WUE than switchgrass at this location; however, other factors such as economics and ecosystem services should also be considered.

Biases in regional carbon budgets from covariation of surface fluxes and weather in transport model inversions

Abstract. Recent advances in atmospheric transport model inversions could significantly reduce uncertainties in land carbon uptake through the assimilation of CO2 concentration measurements at weekly and shorter timescales. The potential of these measurements for reducing biases in estimated land carbon sinks depends on the strength of covariation between surface fluxes and atmospheric transport at these timescales and how well transport models represent this covariation. Daily to seasonal covariation of surface fluxes and atmospheric transport was estimated in observations at the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility, and compared to an atmospheric transport model inversion (CarbonTracker). Covariation of transport and surface fluxes was stronger in CarbonTracker than in observations on synoptic (daily to weekly) timescales, with a wet year (2007) having significant covariation compared to a dry year (2006). Differences between observed and CarbonTracker synoptic covariation resulted in a 0.3 ppm CO2 enhancement in boundary layer concentrations during the growing season, and a corresponding enhancement in carbon uptake by 13% of the seasonal cycle amplitude in 2007, as estimated by an offline simplified transport model. This synoptic rectification of surface flux variability was of similar magnitude to the interannual variability in carbon sinks alone, and indicates that interannual variability in the inversions can be affected by biases in simulated synoptic rectifier effects. The most significant covariation of surface fluxes and transport had periodicities of 10 days and greater, suggesting that surface flux inversions would benefit from improved simulations of the effects of soil moisture on boundary layer heights and surface CO2 fluxes. Soil moisture remote sensing could be used along with CO2 concentration measurements to further constrain atmospheric transport model inversions.

Weather Research and Forecasting Model simulations of extended warm-season heavy precipitation episode over the US Southern Great Plains: data assimilation and microphysics sensitivity experiments

This study examines eight microphysics schemes (Lin, WSM5, Eta, WSM6, Goddard, Thompson, WDM5, WDM6) in the Advanced Research Weather Research and Forecasting Model (WRF-ARW) for their reproduction of observed strong convection over the US Southern Great Plains (SGP) for three heavy precipitation events of 27–31 May 2001. It also assesses how observational analysis nudging (OBNUD), three-dimensional (3DVAR) and four-dimensional variational (4DVAR) data assimilation (DA) affect simulated cloud properties relative to simulations with no DA (CNTRL). Primary evaluation data were cloud radar reflectivity measurements by the millimetre cloud radar (MMCR) at the Central Facility (CF) of the SGP site of the ARM Climate Research Facility (ACRF). All WRF-ARW microphysics simulations reproduce the intensity and vertical structure of the first two major MMCR-observed storms, although the first simulated storm initiates a few hours earlier than observed. Of three organised convective events, the model best identifies the timing and vertical structure of the second storm more than 50 hours into the simulation. For this well-simulated cloud structure, simulated reflectivities are close to the observed counterparts in the mid- and upper troposphere, and only overestimate observed cloud radar reflectivity in the lower troposphere by less than 10 dBZ. Based on relative measures of skill, no single microphysics scheme excels in all aspects, although the WDM schemes show much-improved frequency bias scores (FBSs) in the lower troposphere for a range of reflectivity thresholds. The WDM6 scheme has improved FBSs and high simulated-observed reflectivity correlations in the lower troposphere, likely due to its large production of liquid water immediately below the melting level. Of all the DA experiments, 3DVAR has the lowest mean errors (MEs) and root mean-squared errors (RMSEs), although both the 3DVAR and 4DVAR simulations reduced noticeably the MEs for seven of eight microphysics schemes relative to CNTRL. Lower-tropospheric θe and convective available potential energy (CAPE) also are closer to the observations for the 4DVAR than CNTRL simulations.

A multi-year record of airborne CO<sub>2</sub> observations in the US Southern Great Plains

Abstract. We report on 10 yr of airborne measurements of atmospheric CO2 mole fraction from continuous and flask systems, collected between 2002 and 2012 over the Atmospheric Radiation Measurement Program Climate Research Facility in the US Southern Great Plains (SGP). These observations were designed to quantify trends and variability in atmospheric mole fraction of CO2 and other greenhouse gases with the precision and accuracy needed to evaluate ground-based and satellite-based column CO2 estimates, test forward and inverse models, and help with the interpretation of ground-based CO2 mole-fraction measurements. During flights, we measured CO2 and meteorological data continuously and collected flasks for a rich suite of additional gases: CO2, CO, CH4, N2O, 13CO2, carbonyl sulfide (COS), and trace hydrocarbon species. These measurements were collected approximately twice per week by small aircraft (Cessna 172 initially, then Cessna 206) on a series of horizontal legs ranging in altitude from 460 m to 5500 m a.m.s.l. Since the beginning of the program, more than 400 continuous CO2 vertical profiles have been collected (2007–2012), along with about 330 profiles from NOAA/ESRL 12-flask (2006–2012) and 284 from NOAA/ESRL 2-flask (2002–2006) packages for carbon cycle gases and isotopes. Averaged over the entire record, there were no systematic differences between the continuous and flask CO2 observations when they were sampling the same air, i.e., over the one-minute flask-sampling time. Using multiple technologies (a flask sampler and two continuous analyzers), we documented a mean difference of < 0.2 ppm between instruments. However, flask data were not equivalent in all regards; horizontal variability in CO2 mole fraction within the 5–10 min legs sometimes resulted in significant differences between flask and continuous measurement values for those legs, and the information contained in fine-scale variability about atmospheric transport was not captured by flask-based observations. The CO2 mole fraction trend at 3000 m a.m.s.l. was 1.91 ppm yr−1 between 2008 and 2010, very close to the concurrent trend at Mauna Loa of 1.95 ppm yr−1. The seasonal amplitude of CO2 mole fraction in the free troposphere (FT) was half that in the planetary boundary layer (PBL) (~ 15 ppm vs. ~ 30 ppm) and twice that at Mauna Loa (approximately 8 ppm). The CO2 horizontal variability was up to 10 ppm in the PBL and less than 1 ppm at the top of the vertical profiles in the FT.

Modeling Resource Use Responses to Macroeconomic Changes: Water in the US Southern Great Plains

This study addressed the impacts of the 2008 US recession on water extraction rates from the Ogallala Aquifer in the Southern High Plains of Texas by examining the differences in projected macroeconomic variables and how they impact agricultural production and irrigation water use. The approach used pre- and post-recession FAPRI-based projections of commodity markets and an economic optimization model formulated for the Ogallala Aquifer to simulate water use adjustments. Results indicate that, based on the projections used, the 2008 recession decreased, then increased water use slightly in the representative counties, ceteris paribus, with minimal cumulative effect, and water use responsiveness to economic forces within the region was variable. This analysis also demonstrates that relating policy and economic changes to resource use changes is possible.

Carbon, water, and heat flux responses to experimental burning and drought in a tallgrass prairie

Drought and fire are common disturbances to grassland ecosystems. We report two years of eddy covariance ecosystem–atmosphere fluxes and biometric variables measured in nearby burned and unburned pastures in the US Southern Great Plains. Over the course of the experiment, annual precipitation (∼600mmyr−1) was lower than the long term mean (∼860mmyr−1). Soil moisture decreased from productive conditions in March 2005 dry, unproductive conditions during the growing season starting in March 2006. Just prior to the burn in early March 2005, burned and unburned pastures contained 520±60 and 360±40gCm−2 of total above ground biomass (AGB) and litter, respectively. The fire removed approximately 200gCm−2 of litter and biomass. In the 2005 growing season following the burn, maximum green AGB was 450±60 and 270±40gCm−2, with corresponding cumulative annual net ecosystem carbon exchange (NEE) of −330 and −150gCm−2 for the burned and unburned pastures, respectively. In contrast to NEE, cumulative mean sensible heat and water fluxes were approximately equal in both pastures during the growing season, suggesting either an increase in water use efficiency or a decrease in evaporation in the burned relative to the unburned pasture. In the 2006 growing season, dry conditions decreased carbon uptake and latent heat, and increased sensible heat fluxes. Peak AGB was reduced to 210±30gCm−2 and 140±30gCm−2 in the burned and unburned pastures, respectively, while NEE was near zero. These results suggest that the lack of precipitation was responsible for most of the interannual variation in carbon exchange for these un-irrigated prairie pastures.