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Title: Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

Abstract

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with those from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s -1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s -1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. Lastly, themore » results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.« less

Authors:
ORCiD logo [1];  [2];  [3]; ORCiD logo [4];  [5]; ORCiD logo [6]
  1. McGill Univ., Montreal, QC (Canada). Dept of Atmospheric and Oceanic Sciences
  2. Stony Brook Univ., NY (United States). School of Marine and Atmospheric Sciences
  3. Stony Brook Univ., NY (United States). School of Marine and Atmospheric Sciences; Brookhaven National Lab. (BNL), Upton, NY (United States). Dept. of Environmental and Climate Sciences
  4. Brookhaven National Lab. (BNL), Upton, NY (United States). Dept. of Environmental and Climate Sciences
  5. Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division
  6. Univ. of Oklahoma, Norman, OK (United States). Cooperative Inst. for Mesoscale Meteorological Studies, and School of Meteorology, NOAA/OAR/National Severe Storms Lab.
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1376172
Report Number(s):
BNL-114147-2017-JA
Journal ID: ISSN 1867-8548; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
Grant/Contract Number:
SC0012704; AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmospheric Measurement Techniques (Online)
Additional Journal Information:
Journal Name: Atmospheric Measurement Techniques (Online); Journal Volume: 10; Journal Issue: 8; Journal ID: ISSN 1867-8548
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

North, Kirk W., Oue, Mariko, Kollias, Pavlos, Giangrande, Scott E., Collis, Scott M., and Potvin, Corey K. Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E. United States: N. p., 2017. Web. doi:10.5194/amt-10-2785-2017.
North, Kirk W., Oue, Mariko, Kollias, Pavlos, Giangrande, Scott E., Collis, Scott M., & Potvin, Corey K. Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E. United States. doi:10.5194/amt-10-2785-2017.
North, Kirk W., Oue, Mariko, Kollias, Pavlos, Giangrande, Scott E., Collis, Scott M., and Potvin, Corey K. 2017. "Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E". United States. doi:10.5194/amt-10-2785-2017. https://www.osti.gov/servlets/purl/1376172.
@article{osti_1376172,
title = {Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E},
author = {North, Kirk W. and Oue, Mariko and Kollias, Pavlos and Giangrande, Scott E. and Collis, Scott M. and Potvin, Corey K.},
abstractNote = {The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with those from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s-1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s-1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. Lastly, the results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.},
doi = {10.5194/amt-10-2785-2017},
journal = {Atmospheric Measurement Techniques (Online)},
number = 8,
volume = 10,
place = {United States},
year = 2017,
month = 8
}

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  • The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with thosemore » from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s -1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s -1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. The results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.« less
  • This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results frommore » six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and BAMEX, the DCS IWC values over midlatitude are significantly different, while their Dm values are close to each other. On the other hand, these DCS IWC and Dm values are 1-2 orders of magnitude larger than those of single-layered cirrus clouds over midlatitudes.« less
  • The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentationmore » used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.« less
    Cited by 10
  • The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentationmore » used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.« less