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Timothy J. Wagner, David D. Turner, Larry K. Berg, and Steven K. Krueger

Abstract

While fractional entrainment rates for cumulus clouds have typically been derived from airborne observations, this limits the size and scope of available datasets. To increase the number of continental cumulus entrainment rate observations available for study, an algorithm for retrieving them from ground-based remote sensing observations has been developed. This algorithm, called the Entrainment Rate In Cumulus Algorithm (ERICA), uses the suite of instruments at the Southern Great Plains (SGP) site of the U.S. Department of Energy's Atmospheric Radiation Measurement Program (ARM) Climate Research Facility as inputs into a Gauss–Newton optimal estimation scheme, in which an assumed guess of the entrainment rate is iteratively adjusted through intercomparison of modeled cloud attributes to their observed counterparts. The forward model in this algorithm is the explicit mixing parcel model (EMPM), a cloud parcel model that treats entrainment as a series of discrete entrainment events. A quantified value for the uncertainty in the retrieved entrainment rate is also returned as part of the retrieval. Sensitivity testing and information content analysis demonstrate the robust nature of this method for retrieving accurate observations of the entrainment rate without the drawbacks of airborne sampling. Results from a test of ERICA on 3 months of shallow cumulus cloud events show significant variability of the entrainment rate of clouds in a single day and from one day to the next. The mean value of 1.06 km−1 for the entrainment rate in this dataset corresponds well with prior observations and simulations of the entrainment rate in cumulus clouds.

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Benjamin A. Toms, Jessica M. Tomaszewski, David D. Turner, and Steven E. Koch

Abstract

On 10 August 2014, a gravity wave complex generated by convective outflow propagated across much of Oklahoma. The four-dimensional evolution of the wave complex was analyzed using a synthesis of near-surface and vertical observations from the Oklahoma Mesonet and Atmospheric Radiation Measurement (ARM) Southern Great Plains networks. Two Atmospheric Emitted Radiance Interferometers (AERI)—one located at the ARM SGP central facility in Lamont, Oklahoma, and the other in Norman, Oklahoma—were used in concert with a Doppler wind lidar (DWL) in Norman to determine the vertical characteristics of the wave complex. Hydraulic theory was applied to the AERI-derived observations to corroborate the observationally derived wave characteristics.

It was determined that a bore-soliton wave packet initially formed when a density current interacted with a nocturnal surface-based inversion and eventually propagated independently as the density current became diffuse. The soliton propagated within an elevated inversion, which was likely induced by ascending air at the leading edge of the bore head. Bore and density current characteristics derived from the observations agreed with hydraulic theory estimates to within a relative difference of 15%. While the AERI did not accurately resolve the postbore elevated inversion, an error propagation analysis suggested that uncertainties in the AERI and DWL observations had a negligible influence on the findings of this study.

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Thomas P. Ackerman, Ted S. Cress, Wanda R. Ferrell, James H. Mather, and David D. Turner
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Daniel C. Hartung, Jason A. Otkin, Jonathan E. Martin, and David D. Turner

Abstract

The evolution of an undular bore and its associated wind shift, spawned by the passage of a shallow surface cold front over the Southern Great Plains of the United States, is examined using surface and remote sensing observations along with output from a high-resolution numerical model simulation. Observations show that a separation between the wind shift and thermodynamic properties of the front was induced by the formation of a bore over south-central Kansas around 0200 UTC 29 November 2006. By the time the front–bore complex passed through Lamont, Oklahoma, approximately 4 h later, the bore had reached its maximum intensity and its associated wind shift preceded the trailing baroclinic zone by 20 min. Within several hours the bore decayed and a cold frontal passage, characterized by a wind shift coincident with thermodynamic properties was observed at Okmulgee, Oklahoma. Thus, a substantial transformation in both the structural and dynamical characteristics of the bore as well as its relationship to the parent surface front occurred during a short period of time.

The details of this evolution are examined using output from a finescale numerical simulation, performed using the Weather Research and Forecasting (WRF) model. Analysis of the output reveals that as the bore advanced southeastward it moved into a region with a weaker surface stable layer. Consequently, the wave duct that had supported its maintenance steadily weakened resulting in dissipation of the bore. This circumstance led to a merger of the surface temperature and moisture boundaries with the orphaned wind shift, resulting in the cold frontal passage observed at Okmulgee.

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Penny M. Rowe, Larry M. Miloshevich, David D. Turner, and Von P. Walden

Abstract

Middle to upper tropospheric humidity plays a large role in determining terrestrial outgoing longwave radiation. Much work has gone into improving the accuracy of humidity measurements made by radiosondes. Some radiosonde humidity sensors experience a dry bias caused by solar heating. During the austral summers of 2002/03 and 2003/04 at Dome C, Antarctica, Vaisala RS90 radiosondes were launched in clear skies at solar zenith angles (SZAs) near 83° and 62°. As part of this field experiment, the Polar Atmospheric Emitted Radiance Interferometer (PAERI) measured downwelling spectral infrared radiance. The radiosonde humidity profiles are used in the simulation of the downwelling radiances. The radiosonde dry bias is then determined by scaling the humidity profile with a height-independent factor to obtain the best agreement between the measured and simulated radiances in microwindows between strong water vapor lines from 530 to 560 cm−1 and near line centers from 1100 to 1300 cm−1. The dry biases, as relative errors in relative humidity, are 8% ± 5% (microwindows; 1σ) and 9% ± 3% (line centers) for SZAs near 83°; they are 20% ± 6% and 24% ± 5% for SZAs near 62°. Assuming solar heating is minimal at SZAs near 83°, the authors remove errors that are unrelated to solar heating and find the solar-radiation dry bias of 9 RS90 radiosondes at SZAs near 62° to be 12% ± 6% (microwindows) and 15% ± 5% (line centers). Systematic errors in the correction are estimated to be 3% and 2% for microwindows and line centers, respectively. These corrections apply to atmospheric pressures between 650 and 200 mb.

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Tyler J. Thorsen, Qiang Fu, Rob K. Newsom, David D. Turner, and Jennifer M. Comstock

Abstract

A feature detection and extinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement Program’s (ARM) Raman lidar (RL) has been developed. Presented here is Part I of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitrogen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio—to identify features using range-dependent detection thresholds. FEX is designed to be context sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities provides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically thin features containing nonspherical particles, such as cirrus clouds. Improvements over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia, site. While the focus is on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.

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Brian J. Carroll, Belay B. Demoz, David D. Turner, and Ruben Delgado

Abstract

The 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging from 0 to 2 g kg−1 at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded an RMSE of 1.14 g kg−1 in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales on the order of ten to hundreds of kilometers.

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Temple R. Lee, Michael Buban, David D. Turner, Tilden P. Meyers, and C. Bruce Baker

Abstract

The High-Resolution Rapid Refresh (HRRR) model became operational at the National Centers for Environmental Prediction (NCEP) in 2014 but the HRRR’s performance over certain regions of the coterminous United States has not been well studied. In the present study, we evaluated how well version 2 of the HRRR, which became operational at NCEP in August 2016, simulates the near-surface meteorological fields and the surface energy balance at two locations in northern Alabama. We evaluated the 1-, 3-, 6-, 12-, and 18-h HRRR forecasts, as well as the HRRR’s initial conditions (i.e., the 0-h initial fields) using meteorological and flux observations obtained from two 10-m micrometeorological towers installed near Belle Mina and Cullman, Alabama. During the 8-month model evaluation period, from 1 September 2016 to 30 April 2017, we found that the HRRR accurately simulated the observations of near-surface air and dewpoint temperature (R 2 > 0.95). When comparing the HRRR output with the observed sensible, latent, and ground heat flux at both sites, we found that the agreement was weaker (R 2 ≈ 0.7), and the root-mean-square errors were much larger than those found for the near-surface meteorological variables. These findings help motivate the need for additional work to improve the representation of surface fluxes and their coupling to the atmosphere in future versions of the HRRR to be more physically realistic.

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Junjun Hu, Nusrat Yussouf, David D. Turner, Thomas A. Jones, and Xuguang Wang

Abstract

Due to lack of high spatial and temporal resolution boundary layer (BL) observations, the rapid changes in the near-storm environment are not well represented in current convective-scale numerical models. Better representation of the near-storm environment in model initial conditions will likely further improve the forecasts of severe convective weather. This study investigates the impact of assimilating high temporal resolution BL retrievals from two ground-based remote sensing instruments for short-term forecasts of a tornadic supercell event on 13 July 2015 during the Plains Elevated Convection At Night field campaign. The instruments are the Atmospheric Emitted Radiance Interferometer (AERI) that retrieves thermodynamic profiles and the Doppler lidar (DL) that measures horizontal wind profiles. Six sets of convective-scale ensemble data assimilation (DA) experiments are performed: two control experiments that assimilate conventional and WSR-88D radar observations using either relaxation-to-prior-spread (RTPS) or the adaptive inflation (AI) technique and four experiments similar to the control but that assimilate either DL or AERI or both observations in addition to all other observations that are in the control experiments. Results indicate a positive impact of AERI and DL observations in forecasting convective initiation (CI) and early evolution of the supercell storm. The experiment that employs the AI technique to assimilate BL observations in DA enhances the humidity in the near-storm environment and low-level convergence, which in turn helps forecasting CI. The forecast improvement is most pronounced during the first ~3 h. Results also indicate that the AERI observations have a larger impact compared to DL in predicting CI.

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Coltin Grasmick, Bart Geerts, David D. Turner, Zhien Wang, and T. M. Weckwerth

Abstract

The vertical structures of a leading outflow boundary ahead of a continental nocturnal MCS and of the upstream environment are examined in order to answer the question of whether this vertical structure affects new cell formation and thus MCS maintenance. The MCS in question, observed on 15 July 2015 as part of the Plains Elevated Convection at Night (PECAN) experiment, formed near sunset as a surface-based, density current–driven system. As the night progressed and a stable boundary layer developed, convection became elevated, multiple fine lines became apparent (indicative of an undular bore), and convection increasingly lagged the outflow boundary. Bore-like boundaries became most apparent where the outflow boundary was oriented more perpendicular to the low-level jet, and the lower troposphere was more susceptible to wave trapping. This case study uses a rich array of radiosonde data, as well as airborne Raman lidar and ground-based interferometer data, to profile the temperature and humidity in the lower troposphere. In all soundings, the lifting of air in the residual mixed layer over a depth corresponding to the Raman lidar observed vertical displacement reduced CIN to near zero and enabled deep convection, even though most unstable CAPE steadily decreased during the evolution of this MCS. Both types of outflow boundaries (density currents and bores) initiated convection that helped maintain the MCS. In the case of density currents, cold pool depth and wind shear determined new cell formation and thus MCS maintenance. For bore-like boundaries, bore transformation and propagation were additional factors that determined whether convection initiated and whether it contributed to the MCS or remained separated.

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