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

events that occasionally propagate that far south in the winter, as well as the occasional near-tropical-like events that come from the south in the summer. However, the typical radiometric uncertainty (i.e., random noise) in the MWR brightness temperature observations is 0.35 K, which translates into a PWV uncertainty of 0.025 cm ( Turner et al. 2007 ); this is a relatively large percentage error for dry cases. At the North Slope of Alaska (NSA) site, the PWV can be as low as 0.1 cm, so the

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Beat Schmid, Robert G. Ellingson, and Greg M. McFarquhar

the differences between model calculations and observations were within the range of uncertainties in the observations and model calculations. e. Mixed-Phase Arctic Cloud Experiment (M-PACE) Prior to the M-PACE project, Greg McFarquhar replaced Bob Ellingson as chief scientist of the ARM-UAV program and served as mission scientist during M-PACE, with Tim Tooman still serving as mission controller. During M-PACE (fall 2004, North Slope, Alaska), mixed-phase clouds were measured in situ by the

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

sources. For example, Hinkelman et al. (1999) found biases of 50 W m −2 , on average, in the downwelling SW radiation at the surface in the Eta model and attributed half of the excess to errors in the treatment of water vapor and aerosol in the model and the other half to errors in the treatment of clouds. Similarly, Kennedy et al. (2011) showed that the North American Regional Reanalysis has significant positive biases in downwelling SW and negative biases in downwelling LW under both clear

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Sue Ellen Haupt, Branko Kosović, Scott W. McIntosh, Fei Chen, Kathleen Miller, Marshall Shepherd, Marcus Williams, and Sheldon Drobot

began exploring nonlinear principal component analysis (NLPCA), demonstrating its applicability on chaotic systems and then on various problems such as simulating sea surface temperature and sea level pressure. This method fits a nonlinear curve rather than a straight line when forming the principal components, thus requiring a method such as an NN to accomplish the fit. It can be used to demonstrate the major modes of climate variability, including the Atlantic Oscillation, Pacific–North America

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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

North American High Ice Water Content projects (HAIC/HIWC); similar figures showing distributions of interarrival times or distances are found in Lawson (2011) , Korolev et al. (2011 , 2013b ), Jackson et al. (2014) and others. The peak at an interarrival time of 6 × 10 −4 s corresponds to naturally occurring particles, whereas the peak at an interarrival time less than 10 −6 s corresponds to shattered artifacts. Generally there may be some overlap between the two modes and different

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Isaac M. Held

( Simmons et al. 1983 ; Geisler et al. 1985 ) that the boreal winter response to tropical heating could not be explained by linearizing about a zonally symmetric flow, since the largest extratropical response was found in the Pacific–North American sector, irrespective of the longitude of the tropical forcing. Simmons et al. (1983) related this behavior to the enhanced response when the tropically forced wave propagates through the strong jet exit region in the Pacific where the zonal flow weakens

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Sonia M. Kreidenweis, Markus Petters, and Ulrike Lohmann

North America for cloud physics and cloud chemistry studies. [Figure from List et al. (1986) .] Fig . 11-23. A representative list of cloud chambers worldwide focused on cloud and aerosol physics research. [Figure from Chang et al. (2016) .] Recognizing the limitations of the classes of chambers described above to adequately address particle–particle interactions, especially for large drops that could not remain suspended for a sufficient time, a variety of wind tunnels were developed to study

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Matthew D. Shupe, Jennifer M. Comstock, David D. Turner, and Gerald G. Mace

, are computed. (d) Example profiles of liquid (red) and ice (blue) water contents derived from the distinct liquid and ice radar reflectivity profiles. [Figure from Shupe et al. (2008a) , courtesy of the Bulletin of the American Meteorological Society .] c. Combined sensor approaches Multisensor cloud retrievals increase the dimensionality of the input information, and thereby provide a stronger constraint on complex, multidimensional cloud properties. Moreover, such retrievals harness the

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

weaknesses of the measurement systems. From Fig. 10-2 , it seems as if there was a global coverage of remote sensing measurement campaigns, dedicated to ice formation. However, continuous long-term measurements are limited to a small band in the Northern Hemisphere with strong accumulations in central Europe and central North America. The distribution of activities in the figure poses the question: Where to go next? There are obviously huge gaps in the global coverage of continuous active remote sensing

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Daniel J. Cziczo, Luis Ladino, Yvonne Boose, Zamin A. Kanji, Piotr Kupiszewski, Sara Lance, Stephan Mertes, and Heike Wex

. Atmos. Chem. Phys. , 15 , 12 547 – 12 566 , doi: 10.5194/acp-15-12547-2015 . 10.5194/acp-15-12547-2015 Mason , R. H. , and Coauthors , 2016 : Size-resolved measurements of ice-nucleating particles at six locations in North America and one in Europe . Atmos. Chem. Phys. , 16 , 1637 – 1651 , doi: 10.5194/acp-16-1637-2016 . 10.5194/acp-16-1637-2016 Mertes , S. , A. Schwarzenböck , P. Laj , W. Wobrock , J.-M. Pichon , G. Orsi , and J. Heintzenberg , 2001 : Changes of cloud

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