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

forth recommendations to resolve them. The primary objectives of the monograph are as follows: To summarize our current understanding of ice evolution in clouds, from first ice formation to removal by precipitation, melting, evaporation, or sublimation. To identify those processes in ice formation and evolution that are not well understood, and highlight the impacts of those knowledge gaps on the ability to forecast weather, predict future climate, understand cloud electrification, and foresee

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

Geerts 2016 ; Welsh et al. 2016 ; Bergmaier et al. 2017 ; Mulholland et al. 2017 ; Steenburgh and Campbell 2017 ), and interactions of lake-modified air with surrounding land characteristics and topography (e.g., Veals and Steenburgh 2015 ; Minder et al. 2015 ; Campbell et al. 2016 ; Campbell and Steenburgh 2017 ; Veals et al. 2018 ; Eipper et al. 2018 ; Kristovich et al. 2018 ). e. Forecasting of lake-effect systems, synoptic influence, small lakes As forecasting techniques improved in

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David A. Randall, Cecilia M. Bitz, Gokhan Danabasoglu, A. Scott Denning, Peter R. Gent, Andrew Gettelman, Stephen M. Griffies, Peter Lynch, Hugh Morrison, Robert Pincus, and John Thuburn

for his book “Weather Prediction by Numerical Processes” ( Richardson 1922 ). Partly to create such an example, he attempted what is now called numerical weather prediction (NWP): a direct (but approximate) solution of the equations of motion. The result was his famous “failed” numerical forecast (actually a hindcast) for 20 May 1910. He carried out the calculations by hand, in the intervals between driving for the Friends Ambulance Unit during the war in France ( Ashford 1985 ; Lynch 2006

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Greg M. McFarquhar, Darrel Baumgardner, Aaron Bansemer, Steven J. Abel, Jonathan Crosier, Jeff French, Phil Rosenberg, Alexei Korolev, Alfons Schwarzoenboeck, Delphine Leroy, Junshik Um, Wei Wu, Andrew J. Heymsfield, Cynthia Twohy, Andrew Detwiler, Paul Field, Andrea Neumann, Richard Cotton, Duncan Axisa, and Jiayin Dong

and the corresponding uncertainties in derived products. For example, most of the previous workshops listed in Table 11-1 have been dedicated to problems associated with the measurement of cloud properties, but until recently only the 1984 Workshop on Processing 2D data ( Heymsfield and Baumgardner 1985 ) concentrated on techniques used to analyze or process measurements. With this in mind, workshops on Data Analysis and Presentation of Cloud Microphysical Measurements at the Massachusetts

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Keith L. Seitter, Jinny Nathans, and Sophie Mankins

. The journal’s mission was “to serve its members who are engaged primarily in operational forecasting or who are in research that is directed toward better understanding of weather events that present significant operational forecast problems” ( AMS 1986 ). The intention was to foster dialogue between operational forecasters and researchers by discussing weather events that presented significant forecast problems, offering a forum for new forecasting techniques, and assessing progress in analysis

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I. Gultepe, A. J. Heymsfield, P. R. Field, and D. Axisa

, and the liquid water content. The bulk microphysics algorithms in cloud or forecast models, with varying degrees of complexity (one- or two-moment schemes), can be used to predict parameters related to cloud ice crystals, precipitating snow particles, graupel, and hail ( Morrison and Milbrandt 2011 ). Microphysical processes for converting between hydrometeor types are not well constrained. Figure 6-1 (from Tomita 2008) shows the major components of a six-class microphysical scheme used in

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J. Bühl, S. Alexander, S. Crewell, A. Heymsfield, H. Kalesse, A. Khain, M. Maahn, K. Van Tricht, and M. Wendisch

far, satellite data have to be relied upon heavily in these regions because of the lack of ground-based observations. Satellite data provide near-global coverage of cloud properties and are a crucial component for the evaluation and improvement of weather forecasting and climate models. The CloudSat ( Stephens et al. 2002 ) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ; Winker et al. 2010 ) satellites allow, for the first time, to study ice cloud properties

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D. D. Turner, E. J. Mlawer, and H. E. Revercomb

his large trailer-based MWR at the site also. These activities demonstrated that small details, such as ensuring that the radiometer was level and accounting for the finite beamwidth of the radiometer, were important to obtaining accurate calibrations from the tip-curve technique ( Han and Westwater 2000 ), which was used to determine the calibration of all of the ARM MWRs in the field. Jim Liljegren incorporated these ideas, together with additional findings on the temperature-dependent aspects

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

retrospect. A similar sequence of extreme katabatic wind events was experienced in 1912 by a satellite party of the Scott Antarctic Expedition at Terra Nova Bay (75°S, 165°E) ( Bromwich and Kurtz 1982 ; Bromwich et al. 1993 ). e. A modern renaissance in historical climatology The advent of sparse-input reanalysis and reanalysis-forced modeling and reconstruction techniques in recent years has brought new interest in data that were collected in the past but never integrated into modern large

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J. Verlinde, B. D. Zak, M. D. Shupe, M. D. Ivey, and K. Stamnes

in the surface radiation budget over the sea ice ( Shupe and Intrieri 2004 ). A variety of remote sensor techniques was used to develop the first characterization of Arctic cloud microphysical properties over an annual cycle ( Westwater et al. 2001 ; Lin et al. 2003 ; Turner 2005 ; Shupe et al. 2001 , 2005 , 2006 ), which could be linked to the annual evolution of surface cloud radiative forcing ( Intrieri et al. 2002a ) and net surface energy budget ( Persson et al. 2002 ). With such unique

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