Plains Site Research Articles

Investigating the Impact of Multiphysics on Modeled Planetary Boundary Layer Height Estimates during the PECAN Field Campaign

Abstract Accurate representation of the planetary boundary layer (PBL) in numerical weather prediction is crucial to air quality, weather forecasting, and climate change research and operations. Here, we evaluate the estimates of PBL height (PBLH) from a set of convective-permitting simulations conducted using the Weather Research and Forecasting (WRF) Model during the Plains Elevated Convection at Night (PECAN) campaign (from June to mid-July 2015). Our analysis aims to quantify the variability in PBLH, along with its associated surface variables and atmospheric profiles, to gauge the influence of model physics on the accuracy of simulated PBL properties. Specifically, we conducted twenty-four 45-day retrospective simulations encompassing different combinations of three PBL and two microphysics schemes, two initial and boundary condition (ICBC) datasets, and two model vertical grid spacings. We compare these simulations with measurements from surface sites and radiosonde launches across four sites in the southern Great Plains during PECAN. Our findings indicate that deriving PBLH from modeled atmospheric profiles yields a narrower spread (200–300 m) compared to PBLH calculated from the model’s PBL scheme (400–500 m) relative to radiosonde-derived PBLH under fair weather conditions. The choice of PBL scheme and ICBCs exerts the most significant impact (by up to 400 m) on the spread of modeled PBLH and associated atmospheric profiles, primarily influencing the representation of surface heating, transport, and mixing processes in the model. The model has difficulty reproducing the correct thermodynamic profile under cloud-intense conditions. These results underscore the benefit of using the physically consistent approach in retrieving, evaluating, and assimilating PBLH estimates, as well as the utility of multiphysics to better address model uncertainties. Significance Statement Studies on weather forecast models typically involve running the model multiple times and adjusting model inputs slightly each time to produce a range of predicted variables. This range is crucial for evaluating forecast probabilities and integrating observations into the model. We found that using different model physics schemes can result in an equal or greater spread for predicted variables (here, we focus on boundary layer height and related variables), compared to input tweaks alone. Additionally, a particular scheme can introduce biases. These findings underscore the importance of employing multiple physics schemes in the model, as they widen the coverage (potentially doubling) of outputs, and thus better address forecast uncertainties.

Aerosol Vertical Turbulent Mass Flux Retrievals Through Novel Remote Sensing Algorithm

AbstractIntegrated measurements of aerosol, radiation, cloud, and turbulent transport in the planetary boundary layer (PBL) are essential for understanding and modeling climate and air quality. Here, we developed a new technique for the identification of convective turbulent regions and deriving the vertical distribution of aerosol turbulent mass fluxes within PBL. The algorithm uses retrievals from coherent Doppler lidars and a high spectral resolution lidar. The technique was applied to study particle mass fluxes over 2 months (November–December 2020) during the campaign conducted at the DOE Atmospheric Radiation Measurement Southern Great Plains (SGP) site in Lamont, Oklahoma. The algorithm developed here is capable of continuously deriving vertically resolved (curtains) aerosol mass fluxes. Our data analysis shows that at the site, the 30‐min averaged fluxes at 135 m above the surface were mainly positive (upward) at ∼1 μg m−2 s−1, suggesting that the surface is the primary source of the particle mass supplied to the boundary layer at the SGP site. Analyses of the individual case studies have revealed that not all the derived fluxes can be linked to surface emissions. Both positive and negative values in a range of ±5 μg m−2 s−1 can be caused by convective thermals interacting between the residual layer and the mixed layer and by rotation of the horizontal wind with the height. Large erroneous negative fluxes can also be caused by drizzling/precipitating clouds. We anticipate that the application of the current technique will lead to a more realistic representation of aerosol mass budgets and bidirectional mixing rates.

Study on the characteristics of urban background ozone pollution based on long-term observations from mountain sites in China during 2015–2022

In recent years, Chinese cities have faced persistent O3 pollution challenges. O3 concentrations at urban mountain sites, serving as proxies for urban background O3 levels, can help address data gaps in O3 research in China. This study, for the first time, analyzed O3 data from ten urban mountain sites during 2015–2022 using statistical methods like the Mann-Kendall test, Theil-Sen slope estimation, and Pearson correlation analysis to reveal characteristics and trends in urban background O3 and proposed a metric for assessing mountain sites as urban background stations. Results indicate that O3 at mountain sites were generally higher than at plain sites, regardless of mean, 10th percentile, or 90th percentile the average maximum daily 8-h average (MDA8) O3. Although mountain sites exhibited similar annual and diurnal variations as plain sites, their amplitudes were significantly lower. Significant upward trends (P < 0.05) in MDA8 O3 were observed mainly at plain sites, whereas trends at mountain sites were insignificant (P > 0.05) during 2015–2022. The increase in urban ground-level O3 was largely due to changes in VOCs and NOx emission structures, which reduce nighttime titration effects while enhancing daytime O3 production. The insignificant trends observed at mountain sites suggest that these mountain sites may be in NOx-limited or transitional regimes rather than VOCs-limited regimes, which is also associated with their lower NOx concentrations compared to plain sites. These findings suggest that if China continues to prioritize the reduction of NOx emissions, urban ground-level O3 could further increase and approach the O3 at mountain sites. Finally, this study proposes that the correlation in nighttime O3 concentrations between mountain and plain stations can serve as a valuable indicator for evaluating the suitability of mountain stations as regional background stations in urban areas. It recommends mountain sites in cities such as Changji, Nanping for urban background O3 monitoring stations.

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

The LTAR Grazing Land Common Experiment at Northern Plains.

The USDA Long-Term Agroecosystem Research (LTAR) network aims to enhance sustainable agricultural management practices through a coordinated, cross-site common experiment involving 18 locations across the United States. The objective of this paper is to provide an overview of the LTAR grazing lands common experiment at the Northern Plains (NP) site, where an experiment was initiated in 2019 to answer producers' and researchers' questions about whether the tactical application of fire or grazing can reduce the dominance of invasive Kentucky bluegrass in northern Great Plains ecosystems. As part of the LTAR common experiment, we contrast a prevailing practice (season-long grazing at moderate stocking rate) with four alternative practices at a half-hectare plot scale: (1) mob grazing by cattle, (2) multi-species grazing (mob grazing by cattle, with goats foraging at key times of the year), (3) prescribed fire, and (4) prescribed fire followed by cattle grazing. A stakeholder group is engaged in the co-production process to determine alternative practices and how to apply them. Every 5 years, the treatment with the best overall outcomes is applied at a field scale (15ha), resulting in a core treatment contrast of prevailing versus alternative grazing management systems. This experiment aims to develop alternative agroecological practices that optimize current and future economic and ecosystem benefits.

Enrichment of Phosphates, Lead, and Mixed Soil‐Organic Particles in INPs at the Southern Great Plains Site

AbstractIce nucleating particles (INPs) are rare particles that initiate primary ice formation, a critical step required for subsequent important cloud microphysical processes that ultimately govern cloud phase and cloud radiative properties. Laboratory studies have found that organic‐rich dusts, such as those found in soils, are more efficient INPs compared to mineral dust. However, the atmospheric relevance of these organic‐rich dusts are not well understood, particularly in regions with significant agricultural activity. The Agricultural Ice nuclei at the Southern Great Plains field campaign (AGINSGP) was conducted in rural Oklahoma to investigate how soil dusts contribute to INP populations in the Great Plains. We present chemical characterization of ambient and ice crystal residual particles from a single day of sampling, using single particle mass spectrometry (SPMS) and scanning microscopy. Ambient particles were primarily carbonaceous or secondary aerosol, while the fraction of dust particles was higher in the residual particles. We also observed an unusual particle type consisting of a carbonaceous core mixed with dust fragments on the surface, which was found in higher proportion in residuals. Dust particles measured during residual sampling contained greater proportions of phosphate (63 and 79) and lead (206Pb+). Strong sulfate signals were not seen in the residual dust particles measured by the SPMS, while nitrate was slightly depleted relative to ambient dust. This study shows that organic‐rich soils may be important contributors to the ambient INP population in agricultural regions.

Evaluation of the hyperspectral radiometer (HSR1) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site

Abstract. The Peak Design Ltd hyperspectral radiometer (HSR1) was tested at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site in Lamont, Oklahoma, for 2 months from May to July 2022. The HSR1 is a prototype instrument that measures total (Ftotal) and diffuse (Fdiffuse) spectral irradiance from 360 to 1100 nm with a spectral resolution of 3 nm. The HSR1 spectral irradiance measurements are compared to nearby collocated spectral radiometers, including two multifilter rotating shadowband radiometers (MFRSRs) and the Shortwave Array Spectroradiometer–Hemispheric (SASHe) radiometer. The Ftotal at 500 nm for the HSR1 compared to the MFRSRs has a mean (relative) difference of 0.01 W m−2 nm−1 (1 %–2 %). The HSR1 mean Fdiffuse at 500 nm is smaller than the MFRSRs' by 0.03–0.04 (10 %) W m−2 nm−1. The HSR1 clear-sky aerosol optical depth (AOD) is also retrieved by considering Langley regressions and compared to collocated instruments such as the Cimel sunphotometer (CSPHOT), MFRSRs, and SASHe. The mean HSR1 AOD at 500 nm is larger than the CSPHOT's by 0.010 (8 %) and larger than the MFRSRs' by 0.007–0.017 (6 %–18 %). In general, good agreement between the HSR1 and other instruments is found in terms of the Ftotal, Fdiffuse, and AODs at 500 nm. The HSR1 quantities are also compared at other wavelengths to the collocated instruments. The comparisons are within ∼ 10 % for the Ftotal and Fdiffuse, except for 940 nm, where there is relatively larger disagreement. The AOD comparisons are within ∼ 10 % at 415 and 440 nm; however, a relatively larger disagreement in the AOD comparison is found for higher wavelengths.

Long‐term soil change in the US Great Plains: An evaluation of the Haas Soil Archive

AbstractDiverse patterns of climate and edaphic factors challenge detection of soil property change in the US Great Plains. Because detectable soil change can take decades, insights into the trajectory of soil properties frequently require long‐term site monitoring and, where available, associated soil archives to enable comparisons with initial or baseline states. Unfortunately, few multi‐decadal soil change investigations have been conducted in this region. Here, we document effects of dryland cropping on a suite of soil properties by comparing matched historic (1947) and contemporary (2018) soil samples from the Haas Soil Archive at three sites in the US Great Plains: Moccasin, MT, Akron, CO, and Big Spring, TX. Current analytical methods were used to provide insight into changes in soil texture, pH, carbon, and micronutrients at 0‐ to 15.2‐cm and 15.2‐ to 30.5‐cm depths. Changes in direction and magnitude of soil properties over 71 years were site specific. Changes in textural class occurred at all sites, with Moccasin and Akron transitioning from loam to clay loam and Big Spring from sandy clay loam to sandy loam. The soil pH reaction class changed from slightly alkaline to moderately acid at Akron and slightly alkaline to moderately alkaline at Big Spring. At 0–15.2 cm, soil organic carbon decreased by 15% and 36% at Moccasin and Big Spring, respectively, but increased by 15% at Akron. Soil micronutrients generally declined at all sites. Weather‐related variables derived from air temperature and precipitation records were not correlated with soil change. Inferred factors contributing to soil change included on‐site management, inherent soil features, weather metrics not evaluated, or a combination thereof.

Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Influence of lower-tropospheric moisture on local soil moisture–precipitation feedback over the US Southern Great Plains

Abstract. ​​​​​​​Land–atmosphere coupling (LAC) has long been studied, focusing on land surface and atmospheric boundary layer processes. However, the influence of humidity in the lower troposphere (LT), especially that above the planetary boundary layer (PBL), on LAC remains largely unexplored. In this study, we use radiosonde observations from the US Southern Great Plains (SGP) site and an entrained parcel buoyancy model to investigate the impact of LT humidity on LAC there during the warm season (May–September). We quantify the effect of LT humidity on convective buoyancy by measuring the difference between the 2–4 km vertically integrated buoyancy with the influence of background LT humidity and that without it. Our results show that, under dry soil conditions, anomalously high LT humidity is necessary to produce the buoyancy profiles required for afternoon precipitation events (APEs). These APEs under dry soil moisture cannot be explained by commonly used local LAC indices such as the convective triggering potential and low-level humidity index (CTP / HILow), which do not account for the influence of the LT humidity. On the other hand, consideration of LT humidity is unnecessary to explain APEs under wet soil moisture conditions, suggesting that the boundary layer moisture alone could be sufficient to generate the required buoyancy profiles. These findings highlight the need to consider the impact of LT humidity, which is often decoupled from the humidity near the surface and is largely controlled by moisture transport, in understanding land–atmospheric feedbacks under dry soil conditions, especially during droughts or dry spells over the SGP.

Investigating figulina pottery technology in the southern Po Plain through an integrated archaeometric approach

Figulina pottery refers to a fine, light-coloured ceramic class commonly occurring in Neolithic assemblages of southern and central Italy and, on the opposite side of the Adriatic Sea, along the Dalmatian coast of Croatia. In northern Italy, figulina pottery occurs in limited quantities during the 5th millennium cal. BCE and seems to diverge from the local ceramic productions in terms of technological choices and firing procedures. In light of these technical considerations, past scholarly research hypothesised the existence of networks involving either the exchange of figulina vessels or dynamics of knowledge transmission between Neolithic communities bearing distinct pottery traditions. In this paper, figulina sherds from five mid-late Neolithic settlements located in the southern Po Plain area of northern Italy have been analysed through a multi-analytical archaeometric approach that comprises macroscopic fabric analysis, thin section petrography, X-Ray Powder Diffraction (XRPD) and portable X-Ray Fluorescence (p-XRF). The investigation was carried out with the scope of exploring the technological choices behind the rare figulina pots exceptionally retrieved at the Po Plain sites. Results shed light on the production technology and presumable provenance of the raw materials selected for figulina productions in the region, disclosing possible scenarios of technological transmissions while calling into question the ceramic production model currently hypothesised for Neolithic northern Italy.

Vicuña antipredator diel movement drives spatial nutrient subsidies in a high Andean ecosystem.

Large animals could be important drivers of spatial nutrient subsidies when they ingest resources in some habitats and release them in others, even moving nutrients against elevational gradients. In high Andean deserts, vicuñas (Vicugna vicugna) move daily between nutrient-rich wet meadows, where there is abundant water and forage but high risk of predation by pumas (Puma concolor), and nutrient-poor open plains with lower risk of predation. In all habitats, vicuñas defecate and urinate in communal latrines. We investigated how these latrines impacted soil and plant nutrient concentrations across three habitats in the Andean ecosystem (meadows, plains, and canyons) and used stable isotope analysis to explore the source of fecal nutrients in latrines. Latrine soils had higher concentrations of nitrogen, carbon, and other nutrients than did nonlatrine soils across all habitats. These inputs corresponded with an increase in plant quality (lower C:N) at latrine sites in plains and canyons, but not in meadows. Stable isotope mixing models suggest that ~7% of nutrients in plains latrines originated from vegetation in meadows, which is disproportionately higher than the relative proportion of meadow habitat (2.6%) in the study area. In contrast, ~68% of nutrients in meadow latrines appear to originate from plains and canyon vegetation, though these habitats made up nearly 98% of the study area. Vicuña diel movements thus appear to concentrate nutrients in latrines within habitats and to drive cross-habitat nutrient subsidies, with disproportionate transport from low-lying, nutrient-rich meadows to more elevated, nutrient-poor plains. When these results are scaled up to the landscape scale, the amount of nitrogen and phosphorus subsidized in soil at plains latrines was of the same order of magnitude as estimates of annual atmospheric nitrogen and phosphorus deposition for this region (albeit far more localized and patchy). Thus, vicuña-mediated nutrient redistribution and deposition appears to be an important process impacting ecosystem functioning in arid Andean environments, on par with other major inputs of nutrients to the system.

Predation and Biophysical Context Control Long-Term Carcass Nutrient Inputs in an Andean Ecosystem

Animal carcass decomposition is an often-overlooked component of nutrient cycles. The importance of carcass decomposition for increasing nutrient availability has been demonstrated in several ecosystems, but impacts in arid lands are poorly understood. In a protected high desert landscape in Argentina, puma predation of vicuñas is a main driver of carcass distribution. Here, we sampled puma kill sites across three habitats (plains, canyons, and meadows) to evaluate the impacts of vicuña carcass and stomach decomposition on soil and plant nutrients up to 5 years after carcass deposition. Soil beneath both carcasses and stomachs had significantly higher soil nutrient content than adjacent reference sites in arid, nutrient-poor plains and canyons, but not in moist, nutrient-rich meadows. Stomachs had greater effects on soil nutrients than carcasses. However, we did not detect higher plant N concentrations at kill sites. The biogeochemical effects of puma kills persisted for several years and increased over time, indicating that kills do not create ephemeral nutrient pulses, but can have lasting effects on the distribution of soil nutrients. Comparison to broader spatial patterns of predation risk reveals that puma predation of vicuñas is more likely in nutrient-rich sites, but carcasses have the greatest effects on soil nutrients in nutrient-poor environments, such that carcasses increase localized heterogeneity by generating nutrient hotspots in less productive environments. Predation and carcass decomposition may thus be important overlooked factors influencing ecosystem functioning in arid environments.

Influences of Cloud Microphysics on the Components of Solar Irradiance in the WRF-Solar Model

An accurate forecast of Global Horizontal solar Irradiance (GHI) and Direct Normal Irradiance (DNI) in cloudy conditions remains a major challenge in the solar energy industry. This study focuses on the impact of cloud microphysics on GHI and its partition into DNI and Diffuse Horizontal Irradiance (DHI) using the Weather Research and Forecasting model specifically designed for solar radiation applications (WRF-Solar) and seven microphysical schemes. Three stratocumulus (Sc) and five shallow cumulus (Cu) cases are simulated and evaluated against measurements at the US Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, Southern Great Plains (SGP) site. Results show that different microphysical schemes lead to spreads in simulated solar irradiance components up to 75% and 350% from their ensemble means in the Cu and Sc cases, respectively. The Cu cases have smaller microphysical sensitivity due to a limited cloud fraction and smaller domain-averaged cloud water mixing ratio compared to Sc cases. Cloud properties also influence the partition of GHI into DNI and DHI, and the model simulates better GHI than DNI and DHI due to a non-physical error compensation between DNI and DHI. The microphysical schemes that produce more accurate liquid water paths and effective radii of cloud droplets have a better overall performance.

The Huangshan Neolithic site in Nanyang, Henan

Abstract The Henan Provincial Institute of Cultural Heritage and Archaeology, in conjunction with the Nanyang Municipal Institute of Cultural Heritage and Archaeology, carried out excavations across an area of 2400m2 at the Huangshan site in Nanyang City from May 2018 to January 2022. The site spans various cultural periods, ranging from the Yangshao and Qujialing to Shijiahe cultures. The excavation uncovered a wide variety of structures and artifacts, including one dock, one section of a canal, 48 houses and stone/jade workshops, 157 tombs, eight sacrificial pits, and more than 140 urn burials. As many as 45,000 jade/stone artifacts was also unearthed. These findings confirm that Huangshan was a core settlement bounded by waterways and specialized in large-scale production of stone/jade objects. The excavation also revealed natural transportation waterways connecting the site to the well-known jade quarry of Dushan Mountain. This significant discovery fills a gap in current understandings of Neolithic jade production sites in the Central Plains and middle Yangtze River region.

Sediment thickness map of United States Atlantic and Gulf Coastal Plain Strata, and their influence on earthquake ground motions

With the recent successful accounting of basin depth ground-motion adjustments in seismic hazard analyses for select areas of the western United States, we move toward implementing similar adjustments in the Atlantic and Gulf Coastal Plains by constructing a sediment thickness model and evaluating multiple relevant site amplification models for central and eastern United States seismic hazard analyses. We digitize and combine existing sediment thickness data sets into a composite surface that delineates the base of Cretaceous sediments under the Atlantic Coastal Plain and the base of Mesozoic sediments under the Gulf Coastal Plain. Amplification models dependent on sediment thickness, site natural period, and source-to-site path length are compared with data sets of observed ground motions to evaluate the ability of the new models to improve ground motion estimates. We find that the amplification models can account for observed trends in sediment-thickness and period-dependent residuals, but some tuning is required. For example, the model of Chapman and Guo requires a reference VS30, the time-averaged shear-wave velocity within 30 m of the Earth’s surface, for non-Coastal Plain sites, which we estimate to be between about 1 and 2 km/s. Along with our sediment thickness model, we estimate a velocity profile for application to the Harmon et al. site-natural-period-based model in order to best match the Chapman and Guo period dependence for a broad range of sediment thicknesses. The Next Generation of Attenuation models for the eastern United States Gulf Coast path-based adjustment models can also account for seismic attenuation in the Coastal Plain sediments and reduce the standard deviation of total residuals. If enacted in the U.S. Geological Survey National Seismic Hazard Model, these amplification models will reduce predicted short-period (&lt;1 s) and increase predicted long-period (&gt;1 s) ground motions in the Coastal Plains appreciably.

A Comparison of Forest Biomass and Conventional Harvesting Effects on Estimated Erosion, Best Management Practice Implementation, Ground Cover, and Residual Woody Debris in Virginia

Expanding markets for renewable energy feedstocks have increased demand for woody biomass. Concerns associated with forest biomass harvesting include increased erosion, the applicability of conventional forestry Best Management Practices (BMPs) for protecting water quality, and reduced woody debris retention for soil nutrients and cover. We regionally compared the data and results from three prior independent studies that estimated erosion, BMP implementation, and residual woody debris following biomass and conventional forest harvests in the Mountains, Piedmont, and Coastal Plain of Virginia. Estimated erosion was higher in the Mountains due to steep slopes and operational challenges. Mountain skid trails were particularly concerning, comprising only 8.47% of the total area but from 37.9 to 81.1% of the total site-wide estimated erosion. BMP implementation varied by region and harvest type, with biomass sites having better implementation than conventional sites, and conventional Mountain sites having lower implementation than other regions. Sufficient woody debris remained for BMPs on both harvest types in all regions, with conventional Mountain sites retaining twice that of Coastal Plain sites. BMPs reduced the estimated erosion on both site types suggesting increased implementation could reduce potential erosion in problematic areas. Therefore, proper BMP implementation should be ensured, particularly in Mountainous terrain, regardless of harvest type.

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Abstract There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site at Lamont, Oklahoma, hosts five ARM Doppler lidars that can measure cloud and aerosol properties. In particular, the ARM Doppler lidars record Doppler spectra that contain information about the fall speeds of cloud and precipitation particles. However, due to bandwidth and storage constraints, the Doppler spectra are not routinely stored. This calls for the automation of cloud and rain detection in ARM Doppler lidar data so that the spectral data in clouds can be selectively saved and further analyzed. During the ARMing the Edge field experiment, a Waggle node capable of performing machine learning applications in situ was deployed at the ARM SGP site for this purpose. In this paper, we develop and test four algorithms for the Waggle node to automatically classify ARM Doppler lidar data. We demonstrate that supervised learning using a ResNet50-based classifier will classify 97.6% of the clear-air images and 94.7% of cloudy images correctly, outperforming traditional peak detection methods. We also show that a convolutional autoencoder paired with k-means clustering identifies 10 clusters in the ARM Doppler lidar data. Three clusters correspond to mostly clear conditions with scattered high clouds, and seven others correspond to cloudy conditions with varying cloud-base heights.

Assessment of Warm and Dry Bias over ARM SGP Site in E3SMv2 and E3SM-MMF

Abstract Many climate models exhibit a dry and warm bias over the central United States during the summer months, including the Energy Exascale Earth System Model (E3SM) and its Multiscale Modeling Framework (MMF) configuration. Understanding the causes of this bias is important to shine a light on this common model error and reduce the uncertainty in future projections. In this study, we use E3SMv2 and E3SM-MMF to assess how parameterized and resolved convection affect temperature and precipitation biases over the Southern Great Plains site of the Atmospheric Radiation Measurement program. Both configurations overestimate near-surface temperature and underestimate precipitation at the ARM SGP site. The bias is associated with a lack of low-level clouds during days without precipitation and too much incoming solar radiation causing the surface to warm. Low-level cloud fraction in E3SM-MMF during the nonprecipitating days is lower in comparison to E3SMv2 and observation, consistent with the larger warm bias. We also find that the underestimated precipitation can be characterized as “too frequent, too weak” in E3SMv2 and “too rare, too intense” in E3SM-MMF. These deficiencies conspire to sustain the warm and dry bias over the central United States.

Understanding the nature of early agriculture in the Central Plains of China (ca. 2600BC–221BC): Non-urban settlement perspective through archaeobotanical and stable isotope analysis

Agriculture constitutes the economic foundation for social complexity and civilization process in ancient China. Agricultural practices of ordinary settlements as the basic unit of society could reflect the overall agricultural production and technology and also a basic guarantee for the sustained development and stable operation of the society. The Central Plains of China witnessed the social transition, the onset and development of state-level societies, urbanization process, and the boom of bronze civilization during the Longshan period to Eastern Zhou (ca. 2600BC–221BC). This study primarily aimed to assess the coping strategies of non-urban settlements and the nature of agriculture in Central Plains during this social transformation and development period. It examined the era’s agricultural strategies by reporting the archeaobotanical remains and stable isotopic data of charred grains and legume seeds from the Huqiugang site, a long-lived settlement lasting from Longshan to Eastern Zhou in this area.Findings show that Huqiugang inhabitants adopted active agricultural strategies to confront the social changes and climate fluctuations during Longshan to Eastern Zhou, including effective adjustment of the crop structure, improved crop management and expansion of the agrarian field to cultivate multiple crops. Combined with archaeobotanical remains and stable isotope values of charred plant remains from ordinary contemporaneous sites in the Central Plains, the characteristics of agriculture in non-urban settlements during Longshan to Eastern Zhou in the Central Plains are revealed, including stability of diversified crop patterns, innovation of agricultural technology, and flexibility of agricultural practices, which all contributed to the sustainability of agriculture in this area. Sustainable agriculture provided the economic guarantee of social resilience in the period of social transformation and development in the Central Plains, and was the important driving force for the emergence and development of state-level society, urbanization, and the prosperity of bronze civilization in the Central Plains during Longshan to Eastern Zhou.