These data include snow depth and snow water equivalence (SWE) for the 2022 and 2023 water years during 16 separate field campaigns. The field area is comprised of 311 surveyed points in, on the perimeter of, and surrounding six forest openings next to Coal Creek off Coal Bank Pass in the San Juan Mountains in Southwest Colorado, USA. These measurements were taken to look at the relationship between snow accumulation and snow melt patterns between forest gaps of various sizes, and forest edges of various sizes (edge of forest gaps). Canopy metrics, including canopy height, total gap area, mean distance to canopy, canopy closure, leaf area index, non-directional edginess, canopy edginess with a southern aspect, and canopy edginess with a northern aspect were defined using aerial lidar data for the San Juan Mountains and can be found in an affiliated data release titled, ‘High Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar.’ These metrics are also included herein for the 311 surveyed points.

This data release includes snow depth and snow water equivalent (SWE) for the water year 2025 during ten separate field campaigns that took place between late December and late May. The field area is comprised of 703 surveyed points in, on the perimeter of, and surrounding six flat field (‘no_slope’) forest openings, four northern hillslope aspect (‘north_slope’) forest openings and four southern hillslope aspect (‘south_slope’) forest openings next to Coal Creek off Coal Bank Pass in the San Juan Mountains in Southwest Colorado, USA. These measurements were taken to look at the relationship between snow accumulation and snowmelt patterns between forest gaps of various sizes and forest edges of various sizes (edge of forest gaps), and to determine how these relationships may modulate based upon hillslope aspect. Canopy metrics, including canopy height, total gap area, mean distance to canopy, canopy closure, leaf area index, non-directional edginess, canopy edginess with a southern aspect, and canopy edginess with a northern aspect were defined using aerial lidar data for the San Juan Mountains. These canopy metrics can be found in an affiliated data release titled, ‘High Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar.’ They are also included herein for the 703 surveyed points.

These data include snow depth and snow water equivalent (SWE) for a field campaign on April 9, 2024. The field area is comprised of 311 surveyed points in, on the perimeter of, and surrounding six forest openings next to Coal Creek off Coal Bank Pass in the San Juan Mountains in southwestern Colorado, USA. These measurements were taken to look at the relationship between snow accumulation and snow melt patterns between forest gaps of various sizes, and forest edges of various sizes (edge of forest gaps). Canopy metrics, including canopy height, total gap area, mean distance to canopy, canopy closure, leaf area index, non-directional edginess, canopy edginess with a southern aspect, and canopy edginess with a northern aspect were defined using aerial lidar data for the San Juan Mountains and can be found in an affiliated data release titled, ‘High Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar.’ These metrics are also included herein for the 311 surveyed points.

Discrete snow data were collected during multiple winter field campaigns from 2021 to 2022. This data was collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) project focusing on the relation between snow dynamics and the water cycle of a basin. A Snow Water Equivalent (SWE) Coring Tube was used to measure snow depth and mass of snow within the core. These values were used to calculate snow density and snow water equivalent of the core. These data were released in a comma separated value file.

Discrete snowpack data were collected during winter field campaigns from 2020 to 2022. These data were collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) Upper Colorado River Basin project focusing on the relation between snow dynamics and water resources. After a snow pit was dug, the pit face was analyzed for discrete snowpack measurements. Measurements taken were mass, temperature, and total depth. Using the mass values taken with a density cutter, the snow density and snow water equivalent were calculated. These data are released in a comma separated value file.

The data set presents snow pit measurements collected during the NASA SnowEx March 2023 Intensive Observation Period (IOP) in Alaska, USA to use for calibration and validation with coincident airborne SWESARR and lidar measurements as part of the strategy focused on snow water equivalence (SWE) and snow depth (HS). In total, 170 snow pits were excavated between the five sites at locations representing a range of snow depth, vegetation, and topographic conditions. Three study areas represented boreal forest snow near Fairbanks, AK: Farmers Loop Creamers Field (FLCF), Caribou Poker Creek Research Watershed (CPCRW), and Bonanza Creek Experimental Forest (BCEF). Two study areas represented Arctic tundra snow: Arctic Coastal Plain (ACP) and Upper Kuparuk Toolik (UKT).

This data release includes SnowModel output for three headwater study areas in Colorado at seven spatial resolutions and from two forcing datasets over a 40-year period from water year 1980 to 2019. The resolutions include 30 m, 50 m, 100 m, 150 m, 250 m, 500 m, and 1,000 m. The model was run with a 3-hour temporal resolution from September 1, 1980 to August 31, 2019. Two meteorology forcing datasets were used, including National Land Data Assimilation System-2 at 1/8th degree (about 12 km) resolution data and the Weather Research and Forecasting model data at 4 km resolution. Output variables include snow-water equivalent depth (swed), runoff (roff), air temperature (tair), snow-covered area (sca), snow depth (snod), precipitation (prec), and liquid precipitation (rpre). Additionally, topography and vegetation datasets are included for each combination of unique domain and resolution, as well as the model parameterization file for a representative year. The data are organized by water year (WY) for each forcing type. For example, 'XXXX_wyYYYY.zip', where XXXX is either NLDAS2 or WRFCTL, and YYYY is the water year, with each water year including subdirectories for each of the three headwater study areas ('ER', 'FR', and 'SB' for East River, Fraser River, and Senator Beck, respectively). Each headwater study area subdirectory contains a subdirectory for each spatial resolution ('30', '50', '100', '150', '250', '500', '1000'), and each of those subdirectories contains NetCDF files for the seven variables modeled at that resolution. For example,'SA_RES_VAR_wyYYYY.nc', where SA is one of the three headwater study areas, RES is one of the seven spatial resolutions, VAR is one of the seven output variables, and YYYY is the water year.

This data release includes SnowModel output for three headwater study areas in Colorado at seven spatial resolutions and from two forcing datasets over a 40-year period from water year 1980 to 2019. The resolutions include 30 m, 50 m, 100 m, 150 m, 250 m, 500 m, and 1,000 m. The model was run with a 3-hour temporal resolution from September 1, 1980 to August 31, 2019. Two meteorology forcing datasets were used, including National Land Data Assimilation System-2 at 1/8th degree (about 12 km) resolution data and the Weather Research and Forecasting model data at 4 km resolution. Output variables include snow-water equivalent depth (swed), runoff (roff), air temperature (tair), snow-covered area (sca), snow depth (snod), precipitation (prec), and liquid precipitation (rpre). Additionally, topography and vegetation datasets are included for each combination of unique domain and resolution, as well as the model parameterization file for a representative year. The data are organized by water year (WY) for each forcing type. For example, 'XXXX_wyYYYY.zip', where XXXX is either NLDAS2 or WRFCTL, and YYYY is the water year, with each water year including subdirectories for each of the three headwater study areas ('ER', 'FR', and 'SB' for East River, Fraser River, and Senator Beck, respectively). Each headwater study area subdirectory contains a subdirectory for each spatial resolution ('30', '50', '100', '150', '250', '500', '1000'), and each of those subdirectories contains NetCDF files for the seven variables modeled at that resolution. For example,'SA_RES_VAR_wyYYYY.nc', where SA is one of the three headwater study areas, RES is one of the seven spatial resolutions, VAR is one of the seven output variables, and YYYY is the water year.

Discrete snow depth data were collected during multiple winter campaigns during 2020–22. These data were collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) Upper Colorado River Basin project focusing on the relation of snow dynamics and water resources. Snow depth was measured using either an avalanche probe and handheld global positioning system (GPS) unit or a snow depth probe with attached Juniper Systems Geode GPS receiver and a Mesa tablet. These data are released in a comma separated value file.

Ground-based discrete snowpack measurements were collected during winter field campaigns starting in 2020. These data were collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) Upper Colorado River Basin project focusing on the relation between snow dynamics and water resources. This data release consists of three child items. Each child item contains snow depth, snow density, snow temperature, or snow water equivalent values measured discretely in the field. The data are provided in comma separated value (CSV) files.