气候变化领域集成服务门户(CCPortal): The ARM radar network: At the leading edge of cloud and precipitation observations

CCPortal

DOI	10.1175/BAMS-D-18-0288.1
	The ARM radar network: At the leading edge of cloud and precipitation observations
	Kollias P.; 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.
发表日期	2020
ISSN	00030007
起始页码	E588
结束页码	E660
卷号	101 期号:5
英文摘要	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. © 2020 American Meteorological Society.
语种	英语
scopus关键词	ARM processors; Doppler radar; Inverse problems; Surveillance radar; Cloudy atmospheres; Detection capability; Dual-polarizations; Forward and inverse modeling; Natural laboratories; Precipitation process; Scattering regime; Wealth of information; Precipitation (meteorology)
来源期刊	Bulletin of the American Meteorological Society
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/177894
作者单位	Stony Brook University, State University of New York, Stony Brook, NY, United States; Brookhaven National Laboratory, Upton, NY, United States; University of Cologne, Cologne, Germany; Pacific Northwest National Laboratory, Richland, WA, United States; Pennsylvania State University, University Park, PA, United States; City College of New York, New York, NY, United States; Argonne National Laboratory, Argonne, IL, United States
推荐引用方式 GB/T 7714	Kollias P.,Bharadwaj N.,Clothiaux E.E.,et al. The ARM radar network: At the leading edge of cloud and precipitation observations[J],2020,101(5).
APA	Kollias P..,Bharadwaj N..,Clothiaux E.E..,Lamer K..,Oue M..,...&Mather J.H..(2020).The ARM radar network: At the leading edge of cloud and precipitation observations.Bulletin of the American Meteorological Society,101(5).
MLA	Kollias P.,et al."The ARM radar network: At the leading edge of cloud and precipitation observations".Bulletin of the American Meteorological Society 101.5(2020).