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Snowfall rate retrieval from spaceborne passive microwave (PMW) radiometers has gained momentum in recent years. PMW can be so utilized because of its ability to sense in‐cloud precipitation. A physically based, overland snowfall rate (SFR) algorithm has been developed using measurements from the Advanced Microwave Sounding Unit‐A/Microwave Humidity Sounder sensor pair and the Advanced Technology Microwave Sounder. Currently, these instruments are aboard five polar‐orbiting satellites, namely, NOAA‐18, NOAA‐19, Metop‐A, Metop‐B, and Suomi‐NPP. The SFR algorithm relies on a separate snowfall detection algorithm that is composed of a satellite‐based statistical model and a set of numerical weather prediction model‐based filters. There are four components in the SFR algorithm itself: cloud properties retrieval, computation of ice particle terminal velocity, ice water content adjustment, and the determination of snowfall rate. The retrieval of cloud properties is the foundation of the algorithm and is accomplished using a one‐dimensional variational (1DVAR) model. An existing model is adopted to derive ice particle terminal velocity. Since no measurement of cloud ice distribution is available when SFR is retrieved in near real time, such distribution is implicitly assumed by deriving an empirical function that adjusts retrieved SFR toward radar snowfall estimates. Finally, SFR is determined numerically from a complex integral. The algorithm has been validated against both radar and ground observations of snowfall events from the contiguous United States with satisfactory results. Currently, the SFR product is operationally generated at the National Oceanic and Atmospheric Administration and can be obtained from that organization.

Introduction of upper-level potential vorticity (PV) to developing surface low pressure systems is a key component to cyclogenesis. These anomalous PV features generally occur in regions where stratospheric air has penetrated into the troposphere. Operational forecasters need tools to quickly identify PV anomalies via both cloud patterns and atmospheric characteristics because time is limited to make decisions and issue forecasts. A multispectral red, green, and blue (RGB) imagery product from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented that combines the utility of single-channel cloud information from infrared and water vapor imagery with information about ozone content into a single satellite image that assigns specific colors to specific atmospheric characteristics. Referred to as the Air Mass product, it provides detection of cloud and PV features associated with cyclogenesis as demonstrated for a Nor'easter in October 2011 by comparing the imagery to PV in Global Forecast System model analyses and total ozone from the Atmospheric Infrared Sounder. Development of the Air Mass RGB product from MODIS serves as a precursor and training tool for capabilities from the forthcoming operational Geostationary Operational Environmental Satellite R series Advanced Baseline Imager.

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At high latitudes in winter, the atmosphere at flight levels used by passenger and cargo aircraft can reach temperatures cold enough to restrict the flow of jet fuel from the fuel tanks to the engine, due either to water freezing in the fuel or the fuel itself freezing. Currently, aviation forecasters rely on a combination of aircraft reports, pilot reports, a sparse network of radiosondes, and global model fieldsfor identifying and characterizing Cold Air Aloft (CAA) events. More atmospheric data are needed to improve forecasts of CAA placement and timing, and satellite observations can help fill the gap. In particular, products derived from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS) can be utilized by National Weather Service (NWS) forecasters to assist in the production of aviation hazard products. NUCAPS combines measurements from infrared and microwave sounding instruments on polar-orbiting satellites to retrieve atmospheric profiles of temperature and moisture in the high latitudes. NWS forecasters have real-time access to NUCAPS soundings via the Advanced Weather Interactive Processing System-II (AWIPS-II). The Joint Polar Satellite System Sounding Applications Initiative created Gridded NUCAPS in order to view soundings as isobaric surfaces or vertical cross sections in AWIPS-II. The Cooperative Institute for Research in the Atmosphere (CIRA) developed a web-based product for displaying satellite-derived CAA information. This paper describes how the AWIPS-II and CIRA displays of satellite sounding observations augment aviation forecasting activities in Alaska using two specific CAA cases from the 2016–2017 and 2017–2018 winter seasons.