The ARM Radar Network: At the Leading Edge of Cloud and Precipitation Observations

Autor: I. Lindenmaier, Mariko Oue, Karen Johnson, Katia Lamer, Bradley Isom, Edward P. Luke, Eugene E. Clothiaux, J. H. Mather, Scott Collis, Scott E. Giangrande, Jennifer M. Comstock, Nitin Bharadwaj, Pavlos Kollias, Joseph Hardin, Alyssa Matthews
Rok vydání: 2020
Předmět:
Zdroj: Bulletin of the American Meteorological Society. 101:E588-E607
ISSN: 1520-0477
0003-0007
DOI: 10.1175/bams-d-18-0288.1
Popis: 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 toward providing holistic and multiscale 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. In addition, 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. Although 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 provide a comprehensive characterization of a complete volume of the cloudy atmosphere and to act as a natural laboratory for the study of cloud processes.
Databáze: OpenAIRE
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