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Sally A. McFarlane, James H. Mather, and Eli J. Mlawer

calculated on the cloud properties within each column, and then the contributions of each column are summed to obtain the domain-averaged fluxes of heating rates. ARM studies showed that GCM-scale domain-averaged errors in surface and TOA fluxes calculated using the ICA were generally less than 20 W m −2 , and those in atmospheric heating rates were typically less than 3% ( Marshak et al. 1995 , 1999a ; Barker et al. 1999 ; Cole et al. 2005a ). The detailed radar and lidar observations from the ARM

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Robert G. Ellingson, Robert D. Cess, and Gerald L. Potter

. 46). The ICRCCM community considered the gamut of the then available laboratory and atmospheric observations that might be used to validate the LBL models (e.g., broadband hemispheric flux data, aircraft or surface-based spectral data, satellite spectrometers or laboratory spectra). Each was found lacking for a variety of reasons, such as poor calibration, the lack of detailed measurements of the radiatively important variables, or incomplete range of variables found in the atmosphere (laboratory

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John E. Walsh, David H. Bromwich, James. E. Overland, Mark C. Serreze, and Kevin R. Wood

hindered early uses of satellite products in the Arctic, lidar and radar profilers on the CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) satellites have been used to obtain Arctic cloud climatologies that differ in some ways from earlier depictions. For example, Liu et al. (2012) showed that cloud frequencies derived from radar and lidar profilers on CloudSat and CALIPSO have seasonal maxima and minima in autumn and winter, respectively

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M. A. Miller, K. Nitschke, T. P. Ackerman, W. R. Ferrell, N. Hickmon, and M. Ivey

and structure of orographic flows and the microphysical morphology of associated convection. The plan included contributions from scientific groups in Germany who deployed instrumentation such as a scanning Doppler lidar and several specialized microwave radiometers alongside the AMF1. The expanded capabilities that were provided by these guest instruments served as a blueprint for the development of AMF1 over the next few years. It was operated in the Black Forest for one year in concert with an

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David A. R. Kristovich, Eugene Takle, George S. Young, and Ashish Sharma

designed to study different urban configurations and spatial scales (ranging from indoor/building or canyon, neighborhood, city, regional) and used a suite of instruments (station observations, towers, lidars, sodars, radars, aircraft, and satellites). The 2000s also saw an increase in the number of long-term experiments aimed to provide information on the UBL in a wider range of environmental conditions. For example, since 2005, a long-term mesoscale weather observational network in southern Finland

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Sue Ellen Haupt, Robert M. Rauber, Bruce Carmichael, Jason C. Knievel, and James L. Cogan

all funding for cloud seeding research by the early 1990s. In retrospect, many of the physical studies of that era could also be scrutinized based on advances in our understanding of aircraft probes (e.g., Jackson and McFarquhar 2014 ), and on more recent measurements from remote sensing technologies such as cloud radars, cloud lidars, and radiometers that were introduced in later decades (e.g., Geerts et al. 2015 ). Nevertheless, federal funding for cloud seeding research remained unavailable

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Greg M. McFarquhar, Darrel Baumgardner, and Andrew J. Heymsfield

known to within about 5% for climate studies, which means that the asymmetry parameter ( g ) needs to be known within about 2% to 5%. Theoretical calculations ( Um and McFarquhar 2007 ) of g are typically larger than those derived from directional radiation or nephelometer measurements, with assumptions of surface roughness used to reduce the discrepancies (e.g., Yang et al. 2008 ). However, there is no closure between radiative observations and theoretical calculations because there are few

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Gerald M. Stokes

Park, played the key role in the early phase of the proposal. As one of the architects and key investigators of ICRCCM, he had already prepared a plan together with Warren Wiscombe of NASA (who would later become the third ARM Chief Scientist) for the Spectral Radiance Experiment (SPECTRE; Ellingson and Wiscombe 1996 ; Ellingson et al. 2016 , chapter 1) to add real observations to the comparison of the radiative modeling algorithms. Their approach called for the characterization of the physical

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V. Ramaswamy, W. Collins, J. Haywood, J. Lean, N. Mahowald, G. Myhre, V. Naik, K. P. Shine, B. Soden, G. Stenchikov, and T. Storelvmo

such as Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) lidar aerosol data collocated with MODIS cloud data (e.g., Costantino and Bréon 2013 ). However, in situ airborne platforms with dedicated instrumentation such as nephelometers and aerosol optical particle counters continued to provide vital information on the aerosol vertical profiles at a level of detail and vertical resolution impossible to achieve with satellite-mounted lidars. In modeling, dual

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Larry K. Berg and Peter J. Lamb

most relevant properties (e.g., surface sensible and latent heat fluxes, soil surface heat flux, soil moisture, near-surface air temperature, and humidity) are made using a suite of instrument systems deployed at extended facilities around the primary central facility of each site [e.g., the Southern Great Plains (SGP); Sisterson et al. (2016 , chapter 6)]. The Surface Meteorological Observations Systems (SMOS), later called Surface Meteorological stations (SMET) systems, provide measurements of

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