This is a map of temporal variability in accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timin

This is a map of accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timing of seasonal snowpack d

This is a map of accumulated snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from daily maximum air temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timing of seaso

This is a map of temporal variability in accumulated fall snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estim

This is a map of accumulated fall snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timing of se

This is a map of temporal variability in accumulated spring snow-free growing potential (snow-free growing degree days, SFGDD) for the Upper Gunnison domain, derived from daily maximum air temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived e

This is a map of accumulated spring snow-free freezing potential (snow-free freezing degree days, SFFDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timing of

This is a map of temporal variability in accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timin

This is a map of accumulated snow-free freezing potential (freezing degree days, FDD) for the Upper Gunnison domain, derived from daily minimum temperature maps interpolated from weather station and microclimate sensor data combined with Landsat-derived estimates of the timing of seasonal snowpack d

These maps represent annual estimates of the number of days of continuous seasonal snowpack from 1993 - 2022. The maps are derived from estimates of the first and last day of bare ground derived from long-term time-series of Landsat, and OLI imagery starting in 1993. Annual estimates represent the n

This dataset represents an estimate of the day of year (i.e. , "Julian Day") of the onset of the seasonal snowpack. Specifically these are estimates of the last day of bare ground derived from long-term time-series of Landsat TM, ETM, and OLI imagery starting in 1993. To facilitate computation of sn

This dataset represents an estimate of the day of year (i.e. , "Julian Day") of the persistence of the seasonal snowpack. Specifically these are estimates of the first day of bare ground derived from long-term time-series of Landsat TM, ETM, and OLI imagery starting in 1993. These maps combine month

A coupled hydrologic and snowpack stable water isotope model is used to assesses controls on isotopic inputs across the East River, Colorado, a large, mountainous basin. The hydrologic model uses the semi-empirical, spatially distributed and publicly available U.S. Geological Survey numerical code P

This dataset contains meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains during water years 2019-2021. Data collection had an emphasis on paired open-forest sites and included three forested elevations. In total, we present 270 snow pit observations

Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence B

Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence B

Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence B

This is a 3m map of snow depth derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset has been clipped and resampled to the standard 3m SDP grid, and is derived directly from: Painter, T. 2018. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. N

This is a 3m map of snow depth derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset has been clipped and resampled to the standard 3m SDP grid, and is derived directly from: Painter, T. 2018. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. N

This is a styled basemap showing snow depth on April 7th 2019 derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset is derived directly from: Painter, T. 2019. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Ce