User Profile: Kevin Gallo
Who Uses NASA Earth Science Data? Kevin Gallo, to improve radar and satellite estimations of hail size and damage.
Kevin Gallo, Physical Scientist, National Environmental Satellite, Data, and Information Service, National Oceanic and Atmospheric Administration
Research interests: Gallo uses satellite and in situ data to validate NOAA operational satellite data and products. He is a member of the NOAA Geostationary Operational Environmental Satellite R-Series (GOES-R) Land Algorithm Working Group and is co-lead on developing the NOAA-U.S. Geological Survey (USGS) Land Product Characterization System (LPCS). The LPCS helps facilitate the characterization and validation of land-related products from GOES-R and the Suomi National Polar-orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS).
Current research focus: Gallo and his colleagues are working on developing hail validation and assessment products for the Advanced Baseline Imager (ABI), which is the primary GOES-R instrument for imaging Earth’s weather, oceans, and environment.
Data products used:
Moderate Resolution Imaging Spectroradiometer (MODIS) data sets available through NASA’s Land Processes Distributed Active Archive Center (LP DAAC):
- Daily surface reflectance and vegetation index products with 500 m and 1000 m spatial resolution (short names: MOD09GA and MYD09GA)
- Daily Land Surface Temperature utilized at 1000 m spatial resolution (short names: MOD11A1 and MYD11A1)
- Combined Land Cover product on an annual time scale (short name: MCD12Q1)
Additional data products Gallo uses include:
- Daily VIIRS gridded products (500 m spatial resolution), available through NASA’s Level 1 and Atmosphere Archive and Distribution System (LAADS) DAAC
- Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 Operational Land Imager (OLI) 30 m data products, available through the USGS EarthExplorer website
Research findings: The ABI includes a near-infrared channel that permits computation of vegetation indices at five-minute intervals over the conterminous U.S. Gallo and his colleagues used MODIS and Landsat data to simulate GOES-R ABI vegetation index data. By comparing these simulated vegetation indices with observer- and radar-based assessments of hail damage and size, they found that GOES-R ABI vegetation index products—if available at a 1000 m spatial resolution—may be useful in validating the spatial extent and severity of hail events.
Read about the research:
Gallo, K., Dwyer, J., Foga, S., Jenkerson, C., Longhenry, R. & Stensaas, G. 2015. “NOAA-USGS Land Product Characterization System.” STAR JPSS 2015 Annual Science Team Meeting. Presentation available online at http://www.orbit.nesdis.noaa.gov/star/documents/meetings/2015JPSSAnnual/dayFour/18_Session7c_Gallo_LPVS.pdf.
Gallo, K., Schumacher, P. & Boustead, J. (Principal Investigators). 2014. “Development of GOES-R ABI Hail Validation and Assessment Products.” NASA GOES-R Proposal Abstract. Available online at http://www.goes-r.gov/users/risk-reduce/abstracts/Gallo_abstract.pdf.
Gallo, K., Smith. T., Jungbluth, K. & Schumacher, P. 2012. “Hail Swaths Observed from Satellite Data and Their Relation to Radar and Surface-Based Observations: A Case Study From Iowa in 2009.” Wea. Forecasting 27(3), 796-802 [10.1175/WAF-D-11-00118.1].
Schumacher, P., Gallo, K. & Jungbluth, K. 2010. “Severe storm assessment using satellite data: Case studies from Iowa in 2009.” American Meteorological Society 25th Conference on Severe Local Storms. Abstract available online at https://ams.confex.com/ams/25SLS/webprogram/Paper176192.html.
Last Updated: Dec 6, 2018 at 2:32 PM EST