Southern Great Plains Atmospheric Radiation Research Articles

Reconciling Differences Between Large‐Eddy Simulations and Doppler Lidar Observations of Continental Shallow Cumulus Cloud‐Base Vertical Velocity

AbstractWe investigate a significant model‐observation difference found between cloud‐base vertical velocity for continental shallow cumulus simulated using large‐eddy simulations (LES) and observed by Doppler lidar measurements over the U.S. Southern Great Plains Atmospheric Radiation Measurement Facility. The LES cloud‐base vertical velocity is dominated by updrafts that are consistent with a general picture for convective clouds but is inconsistent with Doppler lidar observations that also show the presence of considerable downdrafts. The underestimation of simulated downdrafts is found to be a robust feature, being insensitive to various numerical, physical, or dynamical choices. We find that simulations can more closely reproduce observations only after improving the model physics to use size‐resolved microphysics and horizontal longwave radiation, both of which modify the cloud buoyancy and velocity structure near cloud side edges. The results suggest that treatments that capture these structures are needed for the proper simulation and subsequent parameterization development of shallow cumulus vertical transport.

Testing and validation of multi‐lidar scanning strategies for wind energy applications

AbstractSeveral factors cause lidars to measure different values of turbulence than an anemometer on a tower, including volume averaging, instrument noise and the use of a scanning circle to estimate the wind field. One way to avoid the use of a scanning circle is to deploy multiple scanning lidars and point them toward the same volume in space to collect velocity measurements and extract high‐resolution turbulence information. This paper explores the use of two multi‐lidar scanning strategies, the tri‐Doppler technique and the virtual tower technique, for measuring 3‐D turbulence. In summer 2013, a vertically profiling Leosphere WindCube lidar and three Halo Photonics Streamline lidars were operated at the Southern Great Plains Atmospheric Radiation Measurement site to test these multi‐lidar scanning strategies. During the first half of the field campaign, all three scanning lidars were pointed at approximately the same point in space and a tri‐Doppler analysis was completed to calculate the three‐dimensional wind vector every second. Next, all three scanning lidars were used to build a ‘virtual tower’ above the WindCube lidar. Results indicate that the tri‐Doppler technique measures higher values of horizontal turbulence than the WindCube lidar under stable atmospheric conditions, reduces variance contamination under unstable conditions and can measure high‐resolution profiles of mean wind speed and direction. The virtual tower technique provides adequate turbulence information under stable conditions but cannot capture the full temporal variability of turbulence experienced under unstable conditions because of the time needed to readjust the scans. Copyright © 2016 John Wiley & Sons, Ltd.

Land–Atmosphere Coupling at the Southern Great Plains Atmospheric Radiation Measurement (ARM) Field Site and Its Role in Anomalous Afternoon Peak Precipitation

Abstract The multimodel Global Land–Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land–atmosphere (LA) coupling and, consequently, land-derived temperature and precipitation predictability. The area including and surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied in the context of LA coupling. Observation-based studies suggest a coupling signal that is much weaker than modeled, if not elusive. Using North American Regional Reanalysis and North American Land Data Assimilation System data, this study provides a 36-yr (1979–2014) climatology of coupling for ARM-SGP that 1) unifies prior interdisciplinary efforts and 2) isolates the origin of the (weak) coupling signal. Specifically, the climatology of a prominent convective triggering potential–low-level humidity index (CTP–HIlow) coupling classification is linked to corresponding synoptic–mesoscale weather and atmospheric moisture budget analyses. The CTP–HIlow classification defines a dry-advantage regime for which convective triggering is preferentially favored over drier-than-average soils as well as a wet-advantage regime for which convective triggering is preferentially favored over wetter-than-average soils. This study shows that wet-advantage days are a result of horizontal moisture flux convergence over the region, and conversely, dry-advantage days are a result of zonal and vertical moisture flux divergence. In this context, the role of the land is nominal relative to that of atmospheric forcing. Surface flux partitioning, however, can play an important role in modulating diurnal precipitation cycle phase and amplitude and it is shown that soil moisture and sensible heat flux are significantly correlated with both occurrence and intensity of afternoon peak precipitation.

Carbonyl sulfide produced by abiotic thermal and photodegradation of soil organic matter from wheat field substrate

AbstractCarbonyl sulfide (COS) is a reduced sulfur gas that is taken up irreversibly in plant leaves proportionally with CO2, allowing its potential use as a tracer for gross primary production. Recently, wheat field soil at the Southern Great Plains Atmospheric Radiation Measurement site in Lamont, Oklahoma, was found to be a measureable source of COS to the atmosphere. To understand the mechanism of COS production, soil and root samples were collected from the site and incubated in the laboratory over a range of temperatures (15–34°C) and light conditions (light and dark). Samples exhibited mostly COS net uptake from the atmosphere in dark and cool (<22–25°C) trials. COS emission was observed during dark incubations at high temperatures (>25°C), consistent with field observations, and at a lower temperature (19°C) when a full spectrum lamp (max wavelength 600 nm) was applied. Sterilized soil and root samples yielded only COS production that increased with temperature, supporting the hypothesis that (a) COS production in these samples is abiotic, (b) production is directly influenced by temperature and light, and (c) some COS consumption in soil and root samples is biotic.

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.

A Probabilistic Bulk Model of Coupled Mixed Layer and Convection. Part II: Shallow Convection Case

Abstract The probabilistic bulk convection model (PBCM) developed in a companion paper is here extended to shallow nonprecipitating convection. The PBCM unifies the clear-sky and shallow convection boundary layer regimes by obtaining mixed-layer growth, cloud fraction, and convective inhibition from a single parameterization based on physical principles. The evolution of the shallow convection PBCM is based on the statistical distribution of the surface thermodynamic state of convective plumes. The entrainment velocity of the mixed layer is related to the mass flux of the updrafts overshooting the dry inversion capping the mixed layer. The updrafts overcoming the convective inhibition generate active cloud-base mass flux, which is the boundary condition for the shallow cumulus scheme. The subcloud-layer entrainment velocity is directly coupled to the cloud-base mass flux through the distribution of vertical velocity and fractional cover of the updrafts. Comparisons of the PBCM against large-eddy simulations from the Barbados Oceanographic and Meteorological Experiment (BOMEX) and from the Southern Great Plains Atmospheric Radiation Measurement Program (ARM) facility demonstrate good agreement in terms of thermodynamic structure, cloud-base mass flux, and cloud top. The equilibrium between the cloud-base mass flux and rate of growth of the mixed layer determines the equilibrium convective inhibition and cloud cover. This process is an important new insight on the coupling between the mixed-layer and cumulus dynamics. Given its relative simplicity and transparency, the PBCM represents a powerful tool for developing process-based understanding and intuition about the physical processes involved in boundary layer–convection interactions, as well as a test bed for diagnosing and validating shallow convection parameterizations.

Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data

Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM) Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS) with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5) in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature observations valuable, which can lead to improved forecasting and more advanced global climate models.

Using boundary layer equilibrium to reduce uncertainties in transport models and CO<sub>2</sub> flux inversions

Abstract. This paper reexamines evidence for systematic errors in atmospheric transport models, in terms of the diagnostics used to infer vertical mixing rates from models and observations. Different diagnostics support different conclusions about transport model errors that could imply either stronger or weaker northern terrestrial carbon sinks. Conventional mixing diagnostics are compared to analyzed vertical mixing rates using data from the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility, the CarbonTracker data assimilation system based on Transport Model version 5 (TM5), and atmospheric reanalyses. The results demonstrate that diagnostics based on boundary layer depth and vertical concentration gradients do not always indicate the vertical mixing strength. Vertical mixing rates are anti-correlated with boundary layer depth at some sites, diminishing in summer when the boundary layer is deepest. Boundary layer equilibrium concepts predict an inverse proportionality between CO2 vertical gradients and vertical mixing strength, such that previously reported discrepancies between observations and models most likely reflect overestimated as opposed to underestimated vertical mixing. However, errors in seasonal concentration gradients can also result from errors in modeled surface fluxes. This study proposes using the timescale for approach to boundary layer equilibrium to diagnose vertical mixing independently of seasonal surface fluxes, with applications to observations and model simulations of CO2 or other conserved boundary layer tracers with surface sources and sinks. Results indicate that frequently cited discrepancies between observations and inverse estimates do not provide sufficient proof of systematic errors in atmospheric transport models. Some previously hypothesized transport model biases, if found and corrected, could cause inverse estimates to further diverge from carbon inventory estimates of terrestrial sinks.

CloudSat Studies of Stratiform Precipitation Systems Observed in the Vicinity of the Southern Great Plains Atmospheric Radiation Measurement Site

Abstract The spaceborne W-band (94 GHz) radar on board the CloudSat polar-orbiting satellite offers new opportunities for retrieving parameters of precipitating cloud systems. CloudSat measurements can resolve the vertical cross sections of such systems. The radar brightband features, which are commonly present when observing stratiform precipitating systems, allow the vertical separation of the ice, mixed, and liquid precipitating hydrometeor layers. In this study, the CloudSat data are used to simultaneously retrieve ice water path (IWP) values for ice layers of precipitating systems using absolute radar reflectivity measurements and mean rainfall rates Rm in the liquid hydrometeor layers using the attenuation-based reflectivity gradient method. The retrievals were performed for precipitating events observed in the vicinity of the Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Climate Research Facility. The retrieval results indicated that IWP values in stratiform precipitating systems vary from a few hundreds up to about 10 thousands of grams per meter squared, and the mean rain rates were in a general range between 0.5 and about 12 mm h−1. On average, mean rainfall increases with an increase in ice mass observed above the melting layer; the corresponding mean correlation coefficient is about 0.35, although events with higher correlation as well as those with no appreciable correlation were observed. Horizontal advection, wind shear, and vertical air motions might be some of the reasons for decorrelation between IWP and Rm retrieved for the same vertical atmospheric column. A mean statistical relation between IWP and Rm derived from CloudSat retrievals is in good agreement with the data obtained from multiwavelength ground-based cloud radar measurements at the SGP site.

Improved retrievals of cloud boundaries from MODIS for use in air quality modeling

A new approach has been developed at the Center for Space Research (CSR) to determine cloud boundaries from satellite data for use in air quality modeling. The approach combines remotely sensed cloud thickness, obtained from the MODIS cloud optical property products, with cloud base height measurements made at surface weather observing facilities to determine cloud top height. When compared to cloud truth estimates, compiled from measurements made at the Southern Great Plains Atmospheric Radiation Measurement Site in Oklahoma, errors in cloud top height from this new method were found to be significantly smaller than those in the MODIS (MOD06) cloud product. It was also found that relatively small errors in MOD06 cloud top temperatures can be magnified in MOD06 cloud top pressures because the interpolation scheme appears to not adequately consider humidity profiles in the NCEP data used to make these conversions.

Comparison between lidar and nephelometer measurements of aerosol hygroscopicity at the Southern Great Plains Atmospheric Radiation Measurement site

Aerosol hygroscopicity has a significant effect on radiative properties of aerosols. Here a lidar method, applicable to cloud‐capped, well‐mixed atmospheric boundary layers, is employed to determine the hygroscopic growth factor f(RH) under unperturbed, ambient atmospheric conditions. The data used for the analysis were collected under a wide range of atmospheric aerosol levels during both routine measurement periods and during the intensive operations period (IOP) in May 2003 at the Southern Great Plains (SGP) Climate Research Facility in Oklahoma, USA, as part of the Atmospheric Radiation Measurement (ARM) program. There is a good correlation (∼0.7) between a lidar‐derived growth factor (measured over the range 85% RH to 96% RH) with a nephelometer‐derived growth factor measured over the RH range 40% to 85%. For these RH ranges, the slope of the lidar‐derived growth curve is much steeper than that of the nephelometer‐derived growth curve, reflecting the rapid increase in particle size with increasing RH. The results are corroborated by aerosol model calculations of lidar backscatter and nephelometer equivalent f(RH) based on in situ aerosol size and composition measurements during the IOP. It is suggested that the lidar method can provide useful measurements of the dependence of aerosol optical properties on relative humidity and under conditions closer to saturation than can currently be achieved with humidified nephelometers.

High-Cloud Horizontal Inhomogeneity and Solar Albedo Bias

High ice cloud horizontal inhomogeneity is examined using optical depth retrievals from four midlatitude datasets. Three datasets include ice cloud microphysical profiles derived from millimeter cloud radar at the Southern Great Plains Atmospheric Radiation Measurement site in Oklahoma. A fourth dataset combines lidar and midinfrared radiometry (LIRAD), and is from the Facility for Atmospheric Remote Sensing at the University of Utah, Salt Lake City, Utah. Plane-parallel homogeneous (PPH) calculations of domain-averaged solar albedo for these four datasets are compared to independent column approximation (ICA) results. A solar albedo bias up to 25% is found over a low reflective surface at a high solar zenith angle. A spherical solar albedo bias as high as 11% is shown. The gamma-weighted radiative transfer (GWRT) scheme is shown to be an effective correction for the solar albedo bias suitable for GCM applications. The GWRT result was, in all cases, within 1‐2 Wm 22 of the ICA outgoing solar flux. The GWRT requires a parameterization of the standard deviation of cloud optical depth. It is suggested that the domain-averaged cloud optical depth and ice water path together can be used in a parameterization to account for 80% of the standard deviation in optical depth.

Estimating Clear-Sky Regional Surface Fluxes in the Southern Great Plains Atmospheric Radiation Measurement Site with Ground Measurements and Satellite Observations

Abstract The authors compared methods for estimating surface fluxes under clear-sky conditions over a large heterogeneous area from a limited number of ground measurements and from satellite observations using data obtained from the southern Great Plains Cloud and Radiation Testbed (CART) site, an area of approximately 350 km × 400 km located in Kansas and Oklahoma. In situ measurements from 10 energy balance Bowen ratio (EBBR) stations showed large spatial variations in latent and sensible heat fluxes across the site because of differences in vegetation and soil conditions. This variation was reproduced by a model for parameterization of subgrid- scale (PASS) surface fluxes that was developed previously and extended in the present study to include a distribution of soil moisture inferred from combined visible and thermal infrared remote sensing data. In the framework of the PASS model, the satellite-derived normalized difference vegetation index and surface temperature were used to derive essential surfa...

A comparison of Sun photometer derivations of total column water vapor and ozone to standard measures of same at the Southern Great Plains Atmospheric Radiation Measurement site

Total column water vapor measurements made over a 1‐year period by collocated instruments at the Southern Great Plains Atmospheric Radiation Measurement program site in northern Oklahoma are compared. Microwave radiometer measurements were validated in an earlier program with extensive comparisons to balloon sonde measurements. Sun photometry, using the multifilter rotating shadowband radiometer (MFRSR), was the second technique used to derive water vapor using the 940‐nm water band when no clouds were between the radiometer and the sun. Bruegge et al.'s implementation of Reagan et al.'s modified Langley technique was applied in this case. This approach is noteworthy in that it does not rely on a comparison to a standard for calibration. The comparison of 101 one‐half‐hour to two‐hour averages produced a root‐mean‐square difference of 0.18 cm compared to a mean value of 1.49 cm, or about 12%, with the MFRSR showing an overall bias of +0.03 cm relative to the microwave radiometer data. This is a somewhat higher rms error than other results using the modified Langley technique, but the comparison was made over the entire range of water vapor columns experienced in a year of observations. As a by‐product of the water vapor derivation procedure for the MFRSR, ozone column abundance was estimated. Seasonally averaged, these data compare favorably with Dobson measurements from Nashville, Tennessee, which is near the same latitude. A more definitive conclusion regarding the Sun photometer ozone derivation technique requires colocated ozone measurements using an accepted standard approach, however, the technique appears to provide a useful ozone estimate for correcting aerosol optical depth derivations.