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Zeinab Takbiri, Ardeshir Ebtehaj, Efi Foufoula-Georgiou, Pierre-Emmanuel Kirstetter, and F. Joseph Turk

Johnson 2011 ). These characteristics are difficult to accurately parameterize as of today. Second, the already weak snowfall scattering signal tends to be masked by the increased atmospheric emissivity and liquid water content in precipitating conditions ( Liu and Seo 2013 ; Wang et al. 2013 ; Panegrossi et al. 2017 ). Third, changes in surface emissivity due to snow accumulation on the ground can significantly alter the snowfall microwave signal. Dry snow cover scatters the upwelling surface

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Sybille Y. Schoger, Dmitri Moisseev, Annakaisa von Lerber, Susanne Crewell, and Kerstin Ebell

1. Introduction Solid precipitation and its deposition as snow are of great importance for Earth’s energy budget and its hydrological cycle. Especially in the Arctic and already at latitudes higher than 60°N, snowfall is the predominant precipitation type ( Levizzani et al. 2011 ). We know today that temperatures are rising about 2 times faster in the Arctic than anywhere else on Earth due to global warming ( IPCC 2007 ; Serreze and Barry 2011 ), known as Arctic amplification. This has a great

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Thomas Stanley, Dalia B. Kirschbaum, George J. Huffman, and Robert F. Adler

Precipitation Measurement (GPM) Core Observatory , was launched in February 2014 and extends observations of both falling snow and heavy to light rain past 65°N/S ( Hou et al. 2014 ). To provide nearly global coverage with short revisit times, the TRMM and GPM missions rely on a constellation of partner satellites. The TRMM Multisatellite Precipitation Analysis (TMPA) covers the area from 50°N/S from 2000 to present ( Table 1 ), while the Integrated Multisatellite Retrievals for GPM (IMERG) covers 60°N

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Robert A. Houze Jr., Lynn A. McMurdie, Walter A. Petersen, Mathew R. Schwaller, William Baccus, Jessica D. Lundquist, Clifford F. Mass, Bart Nijssen, Steven A. Rutledge, David R. Hudak, Simone Tanelli, Gerald G. Mace, Michael R. Poellot, Dennis P. Lettenmaier, Joseph P. Zagrodnik, Angela K. Rowe, Jennifer C. DeHart, Luke E. Madaus, Hannah C. Barnes, and V. Chandrasekar

. With its onboard Dual-Frequency Precipitation Radar (DPR) and 13-channel GPM Microwave Imager (GMI), the GPM satellite extends into future decades the global surveillance of precipitation provided until 2014 by the Tropical Rainfall Measuring Mission (TRMM) satellite and broadens coverage to higher latitudes, where many of Earth’s snow-covered mountain ranges are located. GPM also serves as a reference for other satellites carrying a variety of microwave imaging or sounding radiometers [see Hou et

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Gail Skofronick-Jackson, Mark Kulie, Lisa Milani, Stephen J. Munchak, Norman B. Wood, and Vincenzo Levizzani

, the reflectivity–snow rate ( Z–S ) relationships employed in radar-based algorithms, either explicitly or implicitly, depend on the particular assumptions about microphysical properties and their uncertainties that are made within the algorithms. For passive microwave retrievals as from GMI, snowfall estimates can also be affected by variable surface emissivity, especially over snow-covered surfaces. The land surface variable emissivity hinders falling snow detection compared to oceanic

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Minda Le and V. Chandrasekar

. The solid black line is the left boundary of the DPR outer swath. Black dashed lines are the boundaries of the DPR inner swath. In Fig. 4b , hydrometeor type from ground radar shows most of the scan is covered by crystal and dry snow, with a small area of scattered rain identified to the west of the radar. DPR reflectivity at 2-km height is in Fig. 4c and the corresponding snow flag is illustrated in Fig. 4d . The region between KCLE 100-km range (big circle) and the DPR inner swath is pretty

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Sarah D. Bang and Daniel J. Cecil

limitations, hail retrievals trained in one location (often the United States) may not translate to other locations around the globe. Cecil and Blankenship (2012) attempt to mitigate this issue by applying regional scaling factors to different regional boxes throughout the AMSR-E domain. Those scaling factors are based on empirical relationships between T b and radar profiles in each region. Surface snow or ice cover can be a major problem for retrievals at high latitudes, or over mountains. Icy or

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Kenneth D. Leppert II and Daniel J. Cecil

found that channels near 85 and 150 GHz appear useful for the detection of snow, and the response to snow and/or graupel increases with increasing frequency. Hong et al. (2005) found that these high-frequency channels are most sensitive to the presence of graupel, followed by cloud ice and snow. The assumption of spherical particles greatly simplifies radiative transfer simulations but is not realistic for many frozen particles. Olson et al. (2016) were able to match 165-GHz BT measurements

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Gail Skofronick-Jackson, Walter A. Petersen, Wesley Berg, Chris Kidd, Erich F. Stocker, Dalia B. Kirschbaum, Ramesh Kakar, Scott A. Braun, George J. Huffman, Toshio Iguchi, Pierre E. Kirstetter, Christian Kummerow, Robert Meneghini, Riko Oki, William S. Olson, Yukari N. Takayabu, Kinji Furukawa, and Thomas Wilheit

The GPM mission collects essential rain and snow data for scientific studies and societal benefit. Water is essential to our planet. It literally moves mountains through erosion, transports heat in Earth’s oceans and atmosphere, keeps our planet from freezing as a result of radiative impacts of atmospheric water vapor, and causes catastrophes through droughts, floods, landslides, blizzards, and severe storms, but most importantly water is vital for nourishing all life on Earth. Precipitation as

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Daniel J. Cecil and Themis Chronis

(GPROF surface types 3–5, corresponding to “maximum vegetation,” “high vegetation,” and “moderate vegetation”) or ocean (GPROF surface type 1). The “ocean” classification can include large water bodies, for example, the Great Lakes. Sea ice, arid regions, surface snow cover, rivers, coasts, and precipitation scenes are excluded. Each orbit is divided into 5° latitude bins. Statistics are derived separately for each of these bins that has at least 10 land and 10 water pixels without precipitation

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