Passive microwave remote sensing of the historic February 2010 snowstorms in the Middle Atlantic region of the USA

• Published in: Hydrological Processes
• Main Authors: Foster, James L., Skofronick‐Jackson, Gail, Meng, Huan, Wang, James R., Riggs, George, Kocin, Paul J., Johnson, Benjamin T., Cohen, Judah, Hall, Dorothy K., Nghiem, Son V.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2012
• Subjects: Arctic
• Online Access: http://dx.doi.org/10.1002/hyp.8418; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fhyp.8418; https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.8418

Abstract The snowfall in the Baltimore/Washington metropolitan area during the winter of 2009/2010 was unprecedented and caused serious snow‐related disruptions. In February 2010, snowfall totals approached 2 m, and because maximum temperatures were consistently below normal, snow remained on the ground the entire month. One of the biggest contributing factors to the unusually severe winter weather in 2009/2010, throughout much of the middle latitudes, was the Arctic Oscillation. Unusually high pressure at high latitudes and low pressure at middle latitudes forced a persistent exchange of mass from north to south. In this investigation, a concerted effort was made to link remotely sensed falling snow observations to remotely sensed snow cover and snowpack observations in the Baltimore/Washington area. Specifically, the Advanced Microwave Scanning Radiometer onboard the Aqua satellite was used to assess snow water equivalent, and the Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder were employed to detect falling snow. Advanced Microwave Scanning Radiometer passive microwave signatures in this study are related to both snow on the ground and surface ice layers. In regard to falling snow, signatures indicative of snowfall can be observed in high frequency brightness temperatures of Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder. Indeed, retrievals show an increase in snow water equivalent after the detection of falling snow. Yet, this work also shows that falling snow intensity and/or the presence of liquid water clouds impacts the ability to reliably detect snow water equivalent. Moreover, changes in the condition of the snowpack, especially in the surface features, negatively affect retrieval performance. Copyright © 2011. This article is a U.S. Government work and is in the public domain in the USA.