The data set is a time-series of snow pit measurements obtained by the SnowEx community during the 2021 field campaign. etween November 2020 and May 2021 data from 247 snow pits were collected at 24 unique sites distributed over 4 states (CO, ID, MT, UT) throughout the Western United States. Five of the unique sites had a single visit to establish baseline conditions, while the remaining 19 sites had 3 or more repeat visits throughout the season, with a median visit count of 11.5. On a weekly interval, a snow pit was dug approximately 1 m away from the previous week’s snow pit. Available measured parameters are: snow depth, snow temperature, snow density, stratigraphy, grain size, manual wetness, liquid water content (LWC), and snow water equivalent (SWE). Also available are photos of the field notes and snow pit sites.

This data set represents an updated version of the MODIS Snow Covered Area and Grain-size (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRF) data sets previously produced by the NASA Jet Propulsion Laboratory (JPL). Data are derived from near real-time MODIS/Terra surface reflectance data (MOD09GA_NRT) and include the following parameters: snow fraction, snow grain size (form the SCAG algorithm), vegetation fraction, rock fraction, ice fraction, shade fraction, deltavis, radiative forcing, and optical snow grain size (from the DRFS algorithm). Data are available from 19 October 2023 to the present and are currently available for five regions in the western United States (MODIS tiles h08v04, h08v05, h09v04, h09v05, h10v04). Additional tiles will be added over time. These data are provided in GeoTiff format.

This model product provides the Fortran 77 source code for the Lund-Potsdam-Jena (LPJ) Wetland Hydrology and Methane Dynamic Global Vegetation Model (LPJ-WHyMe v1.3.1), auxiliary C++ routines, ASCII and NetCDF input data, and NetCDF example output data. LPJ-WHyMe v1.3.1 simulates peatland hydrology, permafrost dynamics, peatland vegetation, and methane emissions.The model processes can be simulated on an area-averaged 0.5 or 1.0 degree grid cell basis at global, regional, or site scales and on a daily, monthly, or annual time step as appropriate. Input driver data are monthly mean air temperature, total precipitation, percentage of full sunshine, annual atmospheric CO2 concentration, and soil texture class. The simulation for each grid cell begins from "bare ground", requiring a "spin up" (under non-transient climate) of ca. 1,000 years to develop equilibrium vegetation, carbon, and soil structure. Model simulations compare favorably, with some exceptions, to field observations collected from peatland sites (e.g., Degero, Sweden; Lakkasuo, Finland; BOREAS Northern Study Area, Canada; and others) and non-peatland sites (e.g., Point Barrow, Alaska, and Spasskaya, Siberia). LPJ-WHyMe is a further development of LPJ-WHy, which dealt with the introduction of permafrost and peatlands into LPJ. Implementing peatlands in LPJ required the addition of two new plant functional types (PFTs) (flood tolerant C3 graminoids and Sphagnum mosses) to the already existing ten PFTs, the introduction of inundation stress for non-peatland PFTs, a slow-down in decomposition under inundation, and the addition of a root exudates pool. LPJ-WHyMe v1.3.1 adds a methane model subroutine. This model product has one compressed data file (*.zip) and seven companion files.

As part of the BOREAS Follow-on, an extended period of data collection was supported in the NSA because of the continued efforts at the NSA-OBS site. This data set contains near-surface meteorological data collected and averaged over 15 minute intervals from two sites in the NSA, the SRC tower at the Thompson airport (YTH) and a temporary walkup wooden tower at the Old Black Spruce (OBS) tower site.

The BOREAS DSP-4 team acquired and analyzed imaging radar data from the ESA's ERS-1 over a complete annual cycle at the BOREAS sites in Canada in 1994 to detect shifts in radar backscatter related to varying environmental conditions. Two independent transitions correlating with snow melt and soil thaw onset, and possible canopy thaw were revealed by the data.

This data set contains the results of 1 GHz ground-penetrating radar surveys conducted at the Arctic Coastal Plain (ACP) site and the Upper Kuparuk/Toolik (UKT) site in northern Alaska during the SnowEx23 field campaign. Data include two-way travel time, derived snow depth, and derived snow water equivalent. Data were collected between 8 - 14 March 2023.

Contains the data collected in 1995 by the AMS suite A instrument set operated by SRC and provided to BORIS.

The BOREAS RSS-17 team acquired and analyzed imaging radar data from the ESA's ERS-1 over a complete annual cycle at the BOREAS sites in Canada in 1994 to detect shifts in radar backscatter related to varying environmental conditions. Two independent transitions corresponding to soil thaw and possible canopy thaw were revealed by the data. The results demonstrated that radar provides an ability to observe thaw transitions at the beginning of the growing season, which in turn helps constrain the length of the growing season.

The BOREAS RSS-08 team utilized Landsat TM images to perform mapping of snow extent over the SSA. This data set consists of two Landsat TM images which were used to determine the snow-covered pixels over the BOREAS SSA on 18-Jan-1993 and on 06-Feb-1994.

This data set contains the results of ground-penetrating radar surveys conducted at Cameron Pass, Colorado during the SnowEx20 campaign. Data include two-way travel time, lidar-measured snow depth, derived snow water equivalent, derived snow density, and derived relative permittivity. Ground-penetrating radar two-way travel times were sourced from two previously published data sets: SnowEx20 Cameron Pass Ground Penetrating Radar, Version 1 and SnowEx21 Cameron Pass Ground Penetrating Radar, Version 1. The new data presented here represents a recalculation of the snow water equivalent (SWE), snow density, and relative permittivity using terrestrial lidar scan (TLS) data.