Eric Gagliano

Postdoctoral Scholar · Remote Sensing · Cryosphere · SAR

Terrain Analysis and Cryosphere Observation Lab · University of Washington

I'm a postdoctoral researcher at UW CEE's Terrain Analysis and Cryosphere Observation Lab, with a research focus on understanding when and where mountain snowmelt occurs — a critical question for the more than one billion people who depend on seasonal snowpack for freshwater. I graduated from UW with my PhD in December 2025, and my dissertation work combined satellite radar remote sensing with large-scale cloud computing to produce the first global, high-resolution record of snowmelt runoff onset timing, processing ~3.9 million Sentinel-1 C-band SAR scenes at 80-meter resolution from 2015 to 2024. This dataset enabled a systematic analysis of elevation, aspect, and temperature controls on snowmelt timing patterns across ~150 mountain ranges.


As a postdoc, I'm continuing to work on snowmelt phase delineation and wet snow detection, and I'm developing and evaluating snowmelt methods that leverage data from NASA's newly launched NISAR L-band SAR mission. I'm also building scalable, automatically-updating geospatial data pipelines using emerging tools like Icechunk and GitHub Actions. Alongside research, I develop and maintain open-source Python tools to make snow-related geospatial datasets more accessible to the broader community. I'm passionate about teaching — I've taught UW's graduate Geospatial Data Analysis in Python (CEE 467/CEWA 567) twice and TA'd often — and hope to eventually transition to a public high school teaching role.

Global Snowmelt Runoff Onset — Sentinel-1 SAR Dataset

A 10-year (2015–2024), 80-meter resolution global dataset of annual mountain snowmelt onset timing derived from ~3.9 million Sentinel-1 SAR scenes. Covers ~150 mountain ranges and is validated against 900+ SNOTEL/CCSS weather stations. The dataset reveals global patterns in snowmelt timing and their links to climate variability.

SAR Sentinel-1 Snowmelt Global Dataset Cryosphere

Capturing Mountain Snowmelt with SAR (GRL 2023)

Demonstrated the use of Sentinel-1 C-band backscatter change-point analysis to detect snowmelt runoff onset across Western U.S. mountain ranges. First systematic evaluation of SAR-derived snowmelt timing against in-situ streamflow records.

Publication GRL Western US Change Detection

MODIS Snow Phenology — Interactive Map

A global, 500-meter resolution snow phenology dataset derived from a decade (2015–2024) of MODIS 8-day maximum snow extent observations. Explore snow appearance, disappearance, and duration for any location and year, with cloud-gap filling and polar-region corrections applied. [code]

MODIS Interactive Map Global Dataset Cryosphere

easysnowdata

A Python package that makes it easy to access snow-related geospatial datasets — including SNOTEL/CCSS station records, MODIS snow products, SAR-derived snowmelt timing, and more. Designed for researchers and practitioners working with snowpack data at scale.

Python Open Source Snow Data PyPI

SAR Snowmelt Timing Toolbox

A Zenodo-archived toolbox for detecting snowmelt onset from Sentinel-1 SAR backscatter time series. Includes preprocessing, change-point detection, and visualization utilities.

Python SAR Processing Zenodo

snotel_ccss_stations

A curated dataset of SNOTEL and CCSS station metadata with convenient Python access utilities, useful for snow water equivalent and snowmelt validation studies.

Python SNOTEL Open Data

MODIS Seasonal Snow Mask

Tool for generating seasonal snow cover masks from MODIS satellite imagery, useful for identifying snow-covered regions and masking analysis to seasonally snow-covered areas.

Python MODIS Snow Cover Remote Sensing

Sentinel-1 Local Incidence Angle Maps

Tool for generating per-pixel local incidence angle maps for Sentinel-1 SAR imagery, useful for terrain correction in mountainous areas.

SAR DEM Python

Icechunk + GitHub Actions Demo

A demo of building a global-scale raster dataset with GitHub Actions for parallel compute and Icechunk for versioned, conflict-free Zarr storage. Hundreds of concurrent runners process MODIS land surface temperature data across 376 tiles worldwide (753 GB in ~40 minutes), visualized in an interactive web map. [code]

Icechunk GitHub Actions Zarr Cloud Computing

Geospatial Data Analysis in Python — Course JupyterBook

Open-access course materials for CEE 467/CEWA 567 at UW, which I designed and teach. Covers vector and raster data processing, remote sensing, and cloud-based geospatial workflows in Python. New cohort each winter quarter.

Teaching Python JupyterBook Open Educational Resource

spicy-snow

A collaborative SnowEx project for snow depth estimation from Sentinel-1 cross-polarization SAR. Developed during SnowEx HackWeek 2022 and continuing as an active open-source project.

SnowEx SAR Snow Depth Collaborative

Soft Serve Review Map

An interactive map cataloguing soft serve ice cream spots, color-coded by rating (0–10) and sized by number of visits.

Interactive Map Ice Cream

Gagliano, E., Shean, D., & Henderson, S.

Global patterns and controls on mountain snowmelt runoff onset from a decade of high-resolution observations

Mower, R., Pflug, J. M., Gagliano, E., Gutmann, E., Cristea, N., & Lundquist, J. D.

Identifying wet pixels for SAR-based SWE retrieval using model output and Sentinel-1 backscatter signals

Bennett, M., Gagliano, E.

Breaker of images? Synthetic aperture radar and the rise of satellite iconoclasm

Environment & Planning F

Gagliano, E., Shean, D., & Henderson, S.

A global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR, 2015–2024

Earth System Science Data · preprint

Mirza, B., Gagliano, E., Small, E., Raleigh, M.

Remotely sensed melt fraction enhances streamflow modeling in snow-dominated ungauged Basins with long short-term memory networks

Hydrological Processes

Brencher, G., Shean, D., Henderson, S., & Gagliano, E.

Accurate snow depth predictions across the Western U.S. using a deep learning model trained on 7 years of airborne lidar snow depth measurements

preprint

Kaur, P., Webb, R., Tarricone, J., Rittger, K., McGrath, D., Gagliano, E., et al.

Feasibility mapping of L-band InSAR for SWE retrievals across the Western United States

Geophysical Research Letters, 53, e2025GL120162 · DOI

Rickenbaugh, L., Sproles, E., Gagliano, E., Covino, T., Tuholske, C., & Carroll, R. W. H.

When and Where does Water Originate? Leveraging Stable Water Isotopes and Synthetic Aperture Radar to Assess the Hydrology of a Snow-Dominated Watershed in Southwestern Montana

Remote Sensing Applications: Society and Environment, 101887

Detre, A., McGrath, D., Gagliano, E., Bonnell, R., Webb, R., Marshall, H. P., & Shean, D.

Sentinel-1 SAR Estimates of Snowmelt Onset Coincide With SNOTEL Soil Moisture Pulses Across the Western United States

Hydrological Processes, 39(12), e70341 · DOI

Hoppinen, Z., Palomaki, R. T., Brencher, G., Dunmire, D., Gagliano, E., Marziliano, A., ..., & Marshall, H. P.

Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites

The Cryosphere, 18(11), 5407–5430 · DOI

Gagliano, E., Shean, D., Henderson, S., & Vanderwilt, S.

Capturing the onset of mountain snowmelt runoff using satellite synthetic aperture radar

Geophysical Research Letters, 50(21), e2023GL105303 · DOI

Rogic, N., Charbonnier, S. J., Garin, F., Dayhoff II, G. W., Gagliano, E., Rodgers, M., ..., & Shean, D.

Characterizing and mapping volcanic flow deposits on Mount St. Helens via dual-band SAR imagery

Remote Sensing, 15(11), 2791 · DOI

Applying to STEM PhD Programs from Undergrad

A guide for undergraduates navigating the PhD application process in STEM fields.

My full curriculum vitae, updated automatically from Google Docs.