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Enhanced Snowfall Rate Monitoring and Evaluation Using NASA/SPoRT Data

This document outlines the Snowfall Rate (SFR) product developed through collaboration among NOAA/NESDIS, SPoRT, and Earth System Science Interdisciplinary Center. The SFR utilizes real-time satellite data from AMSU and MHS sensors on POES and Metop satellites to estimate snowfall rates, which typically take about 1.5 hours to reach the surface. It aids in tracking snowstorm evolution, filling data gaps, and identifying snowfall intensity, enhancing operational capabilities for accurate weather forecasting and nowcasting.

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Enhanced Snowfall Rate Monitoring and Evaluation Using NASA/SPoRT Data

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  1. PG All Hand MeetingCICS-MD Update

  2. AMSU/MHS Snowfall Rate (SFR) Product (Courtesy of NASA/SPoRT) • Satellite retrieved water equivalentsnowfall rate over land • Operational product at NOAA/NESDIS - near real-time production • Uses data from microwave sensors (AMSU and MHS) aboard POES and Metop satellites • Estimates snowfall rate in the atmosphere and will take on average 1.5 hours to reach the surface • Four satellites with up to eight passes per day at mid-latitude locations and more at higher latitudes Huan Meng1, Ralph Ferraro1 , Banghua Yan1, Cezar Kongoli2, Limin Zhao1, Nai-Yu Wang2, Jun Dong2 1NOAA/NESDIS 2Earth System Science Interdisciplinary Center, UMCP, USA

  3. Applications • SFR can be paired with GOES IR/VIS/WV images to track the movement and evolution of snowstorm • Fill in data gaps in regions with limited radar, gauge, and/or GOES observations • Identify snowstorm extent and areas with most intense snowfall • Advantage of the time lag between satellite retrieval and ground observation • Reduced latency • Nowcasting • Collaborating with SPoRT and several WFOs to evaluate the product in the 2013-2014 snow season

  4. ATMS Snowfall Rate Product • Advanced Technology Microwave Sounder (ATMS) • ATMS is the follow-on sensors to AMSU and MHS • ATMS is onboard NPP and future JPSS satellites • ATMS snowfall project funded by JPSS Proving Ground program • Complete prototype algorithms by the end of 2013 • Next step: extension to colder climate

  5. Lightning Product Evaluation at OPC • GOES-R Proving Ground Project • Create flash density grids at GLM resolution using a ground-based network (i.e., GLD360) • Evaluation during Summer 2013 • Develop training materials, shadow forecasters, and compose report • Expand to other NWS Centers Flash Locations Flash Density Grids Collaborators Joe Sienkiewicz Greg McFadden Michael Folmer Scott Rudlosky Dustin Shea

  6. Developed a Training Quick Guide

  7. SRSOR plus DCLMA Observations

  8. Ongoing Effort • Goal: Develop proving ground provider capabilities at CICS • Steps Forward • Obtain a NOAAPORT connection • Implement operational software (AWIPS-II, McIDAS, and WDSS) • Create AWIPS-II displays for existing products • Identify operational partners and establish IT connections • Train CICS-MD Scientists and UMD Students on these systems • Our efforts will speed up the implementation of existing products and contribute to the collaborative development of new operational products.

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