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Title: The ARM Radar Network: At the Leading-edge of Cloud and Precipitation Observations

Abstract

The ARM observatories include radars that span a range of frequencies and capabilities to characterize the three-dimensional structure and properties of atmospheric hydrometeors. Improving our ability to predict future weather and climate conditions is strongly linked to achieving significant advancements in our understanding of cloud and precipitation processes. Observations are critical to making these advancements because they both improve our understanding of these processes and provide constraints on numerical models. Historically, instruments for observing cloud properties have limited cloud-aerosol investigations to a small subset of cloud-process interactions. To address these challenges, the last decade has seen the U.S. DOE ARM facility significantly upgrade and expand its surveillance radar capabilities towards providing holistic and multi-scale observations of clouds and precipitation. These upgrades include radars that operate at four frequency bands covering a wide range of scattering regimes, improving upon the information contained in earlier ARM observations. The traditional ARM emphasis on the vertical column is maintained, providing more comprehensive, calibrated, and multiparametric measurements of clouds and precipitation. Furthermore, the ARM radar network now features multiple scanning dual-polarization Doppler radars to exploit polarimetric and multi-Doppler capabilities that provide a wealth of information on storm microphysics and dynamics under a wide range ofmore » conditions. While the diversity in wavelengths and detection capabilities are unprecedented, there is still considerable work ahead before the full potential of these radar advancements is realized. This includes synergy with other observations, improved forward and inverse modeling methods, and well-designed data-model integration methods. The overarching goal is to offer a comprehensive characterization of a complete volume of the cloudy atmosphere and to act as a natural laboratory for the study of cloud processes.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [2];  [2];  [2];  [2];  [6];  [6];  [6];  [7];  [2];  [2]
  1. Stony Brook Univ., NY (United States); Brookhaven National Lab. (BNL), Upton, NY (United States); Univ. of Cologne (Germany)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Pennsylvania State Univ., University Park, PA (United States)
  4. City College of New York, NY (United States)
  5. Stony Brook Univ., NY (United States)
  6. Brookhaven National Lab. (BNL), Upton, NY (United States)
  7. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1581955
Alternate Identifier(s):
OSTI ID: 1642427
Report Number(s):
BNL-213519-2020-JAAM; PNNL-SA-150306
Journal ID: ISSN 0003-0007; TRN: US2100798
Grant/Contract Number:  
SC0012704; AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Volume: 101; Journal Issue: 5; Journal ID: ISSN 0003-0007
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Kollias, Pavlos, Bharadwaj, N., Clothiaux, E. E., Lamer, K., Oue, M., Hardin, J., Isom, B., Lindenmaier, I., Matthews, A., Luke, E. P., Giangrande, S. E., Johnson, K., Collis, S., Comstock, J., and Mather, J. H. The ARM Radar Network: At the Leading-edge of Cloud and Precipitation Observations. United States: N. p., 2019. Web. https://doi.org/10.1175/BAMS-D-18-0288.1.
Kollias, Pavlos, Bharadwaj, N., Clothiaux, E. E., Lamer, K., Oue, M., Hardin, J., Isom, B., Lindenmaier, I., Matthews, A., Luke, E. P., Giangrande, S. E., Johnson, K., Collis, S., Comstock, J., & Mather, J. H. The ARM Radar Network: At the Leading-edge of Cloud and Precipitation Observations. United States. https://doi.org/10.1175/BAMS-D-18-0288.1
Kollias, Pavlos, Bharadwaj, N., Clothiaux, E. E., Lamer, K., Oue, M., Hardin, J., Isom, B., Lindenmaier, I., Matthews, A., Luke, E. P., Giangrande, S. E., Johnson, K., Collis, S., Comstock, J., and Mather, J. H. Sun . "The ARM Radar Network: At the Leading-edge of Cloud and Precipitation Observations". United States. https://doi.org/10.1175/BAMS-D-18-0288.1. https://www.osti.gov/servlets/purl/1581955.
@article{osti_1581955,
title = {The ARM Radar Network: At the Leading-edge of Cloud and Precipitation Observations},
author = {Kollias, Pavlos and Bharadwaj, N. and Clothiaux, E. E. and Lamer, K. and Oue, M. and Hardin, J. and Isom, B. and Lindenmaier, I. and Matthews, A. and Luke, E. P. and Giangrande, S. E. and Johnson, K. and Collis, S. and Comstock, J. and Mather, J. H.},
abstractNote = {The ARM observatories include radars that span a range of frequencies and capabilities to characterize the three-dimensional structure and properties of atmospheric hydrometeors. Improving our ability to predict future weather and climate conditions is strongly linked to achieving significant advancements in our understanding of cloud and precipitation processes. Observations are critical to making these advancements because they both improve our understanding of these processes and provide constraints on numerical models. Historically, instruments for observing cloud properties have limited cloud-aerosol investigations to a small subset of cloud-process interactions. To address these challenges, the last decade has seen the U.S. DOE ARM facility significantly upgrade and expand its surveillance radar capabilities towards providing holistic and multi-scale observations of clouds and precipitation. These upgrades include radars that operate at four frequency bands covering a wide range of scattering regimes, improving upon the information contained in earlier ARM observations. The traditional ARM emphasis on the vertical column is maintained, providing more comprehensive, calibrated, and multiparametric measurements of clouds and precipitation. Furthermore, the ARM radar network now features multiple scanning dual-polarization Doppler radars to exploit polarimetric and multi-Doppler capabilities that provide a wealth of information on storm microphysics and dynamics under a wide range of conditions. While the diversity in wavelengths and detection capabilities are unprecedented, there is still considerable work ahead before the full potential of these radar advancements is realized. This includes synergy with other observations, improved forward and inverse modeling methods, and well-designed data-model integration methods. The overarching goal is to offer a comprehensive characterization of a complete volume of the cloudy atmosphere and to act as a natural laboratory for the study of cloud processes.},
doi = {10.1175/BAMS-D-18-0288.1},
journal = {Bulletin of the American Meteorological Society},
number = 5,
volume = 101,
place = {United States},
year = {2019},
month = {5}
}

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Retrieval of Microphysical Properties of Water, Ice, and Mixed-Phase Clouds Using a Triple-Wavelength Radar and Microwave Radiometer
journal, January 2006

  • Yoshida, Yukio; Asano, Shoji; Iwanami, Koyuru
  • Journal of the Meteorological Society of Japan. Ser. II, Vol. 84, Issue 6
  • DOI: 10.2151/jmsj.84.1005

Mixed-phase cloud phase partitioning using millimeter wavelength cloud radar Doppler velocity spectra: MIXED-PHASE CLOUD PHASE PARTITIONING
journal, June 2014

  • Yu, G.; Verlinde, J.; Clothiaux, E. E.
  • Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 12
  • DOI: 10.1002/2013JD021182

Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data
journal, December 2007

  • Zeng, Xiping; Tao, Wei-Kuo; Zhang, Minghua
  • Journal of the Atmospheric Sciences, Vol. 64, Issue 12
  • DOI: 10.1175/2007JAS2170.1

The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models
journal, January 2018

  • Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.
  • Bulletin of the American Meteorological Society, Vol. 99, Issue 1
  • DOI: 10.1175/BAMS-D-16-0258.1

The Vertical Structure of Liquid Water Content in Shallow Clouds as Retrieved From Dual‐Wavelength Radar Observations
journal, December 2019

  • Zhu, Zeen; Lamer, Katia; Kollias, Pavlos
  • Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 24
  • DOI: 10.1029/2019JD031188