This event has passed. See the seminar recording here: Prof. Robert Rauber Director of School of Earth, Society & Environment University of Illinois Urbana-Champaign
The Snowfall Rate (SFR) team at STAR and ESSIC/CISESS, including Huan Meng, Yongzhen Fan, and Jun Dong, has made some notable progress recently that significantly enhances the product and its accessibility to users.
ESSIC/CISESS scientists Soni Yatheendradas and Sujay Kumar are co-authors on a paper in Journal of Hydrometeorology titled, “A novel Machine Learning-based gap-filling of fine-resolution remotely sensed snow cover fraction data by combining downscaling and regression”.
The first nor’easter of 2022 swept through the Mid-Atlantic and the Northeast on January 2-4, 2022, resulting in a heavy snow accumulation of up to 14 inches in Virginia and southern Maryland and stranding hundreds of drivers on Interstate 95 in Virginia. The NOAA NESDIS Snowfall Rate (SFR) product captured the evolution of the snowstorm with retrievals from the Advanced Technology Microwave Sounder (ATMS) sensor aboard the S-NPP and NOAA-20 satellite missions, and the AMSU-A/MHS sensors aboard NOAA-19, Metop-B, and Metop-C.
ESSIC/CISESS Scientist Qingyuan Zhang has a new article to be published in International Journal of Applied Earth Observation and Geoinformation that characterizes the seasonally snow-covered Howland boreal forest ecosystem in Maine, USA with satellite images.
With Halloween behind us, wintery temps are fast approaching College Park! This year, we are resurrecting the historic ESSIC Annual Snow Prediction Pool. This is your opportunity to show off your weather prediction skills to your colleagues and earn bragging rights for the entire 2021-22 snow season.
ESSIC/CISESS scientists Huan Meng and Yongzhen Fan have recently developed a new machine learning snowfall detection (SD) algorithm, based on eXtreme Gradient Boosting (XGB). The algorithm was developed for the Advanced Technology Microwave Sounder (ATMS) onboard NPP and NOAA-20 as well as the MHS/AMSU-A onboard Metop-A, Metop-B, Metop-C and NOAA-19.
Assessment of Precipitation Error Propagation in Discharge Simulations over the Contiguous United States
ESSIC Visiting Assistant Research Scientist Huan Wu has a new paper in Journal of Hydrometeorology titled “Assessment of Precipitation Error Propagation in Discharge Simulations over the Contiguous United States” alongside Naijun Zhou from UMD’s Department of Geographical Sciences.
ESSIC Post-doctoral Associate Eunsang Cho is first author on a paper in Water Resources Research titled “Extreme Value Snow Water Equivalent and Snowmelt for Infrastructure Design Over the Contiguous United States”.