DOI: 10.5281/zenodo.10719521
title: Snow Cover in Under Canopy and Open Locations at the HJ Andrews (OR, USA) and the Sagehen (CA, USA) Experimental Forests via Distributed Ground Temperature Sensors (July 2021 to July 2023)

description: These data represent snow cover (expressed as binary snow presence or snow absence), determined using temperature sensors/loggers deployed on the ground in various under canopy and open (forest gap/meadow) locations at two coniferous montane forest sites in the Western USA: the HJ Andrews Experimental Forest (HJA) in Oregon, and the Sagehen Experimental Forest (Sagehen) in California. Measurements reported here were taken between July 2021 and July 2023.

At each sensor location, the following is provided: 

Snow classification for each date, including an assessment of classification uncertainty using a Monte Carlo simulation. A given day (in the PST time zone, i.e. UTC -8:00 hours) is classified as snow covered (a '1' in the data) if the absolute value of the mean temperature for the day is less than or equal to 1.0 deg. C and the standard deviation of the temperature is less than or equal to 0.353 deg. C,  otherwise it is classified as snow-free ('0' in the data). See the included code for details. For the criteria used, also see Kostadinov et al. (2019, doi: https://doi.org/10.1016/j.rse.2018.11.037) and Raleigh et al. (2013; doi: https://doi.org/10.1016/j.rse.2012.09.016).

Importantly, the canopy cover status of each sensor is provided as being either under canopy or in the open. This was determined manually/visually in the field at deployment by ascertaining canopy cover or its absence vertically directly above each sensor. 

Raw temperature files are also included, as output by the Onset(R) HOBOware(R) Pro software. Date/time has been re-formatted in these raw temperature files, and the column headings might be redacted, but otherwise the data is as output by the sensor and HOBOware(R) Pro. 

Calibration in an ice slush was conducted for a subset of the sensors prior to deployment, and these calibration data are included as well (Important Note: the calibration values are not applied to the data set).

The data are given in CSV format. Figures of the temperature, snow classification and calibration data are provided for convenience as well. 

Data analysis and processing, snow classification, as well as figure production was accomplished in MATLAB(R), and the relevant scientific code is included here. Both raw and snow classification files given here were processed and output by MATLAB(R). 

Geographic location for each sensor was determined in the field with a Juniper Systems(TM) Geode (TM) GNS2 receiver, using the ESRI(R) ArcGIS(R) Collector app to collect the locations and average 40 points at each sensor location for improved accuracy, typically sub-meter, enabling high-resolution applications such as tree-scale and lidar studies. For both HJA and Sagehen, a separate CSV file summarizing location, location uncertainty and canopy cover metadata for each sensor is included. Some key parts of these data are also included in each sensor's file headers and in the figures. 
description: Funding and Acknowledgments:

California State University San Marcos is acknowledged for providing funding support for this data collection and research via a Research, Scholarship and Creative Activity (RSCA) grant to T.K. and other internal sources, as well as for providing support for subsequent data processing and analysis. 

Facilities were provided by the H.J. Andrews Experimental Forest and Long Term Ecological Research (LTER) program, administered cooperatively by Oregon State University, the USDA Forest Service Pacific Northwest Research Station, and the Willamette National Forest. This material is based upon work supported by the National Science Foundation under the grant LTER8 DEB-2025755.

Facilities and logistics support were also provided by the Sagehen Creek Field Station located within the Sagehen Experimental Forest.

Dan Sayler and Mark Schultze are acknowledged for providing indispensable site and logistics support. Adrian Harpold and Todd Lookingbill are acknowledged for the multiple fruitful discussions and ideas. 

Software: MathWorks(R) MATLAB(R) was used for sensor data import, processing and analysis and for snow classification and production of the data files and figures included in this data set. 

Onset(R) HOBOware(R) Pro and the Onset(R) mobile apps HOBOmobile(R) and HOBOconnect(R) were used to set up and deploy and sensors and to download and output their data.

ESRI(R) ArcMap(R), ArcGIS(R) Pro and ArcGIS(R) Collector were used for deployment mapping and planning, as well for location data collection. High accuracy location data were collected in the field with a Juniper Systems(R) Geode(TM) GNS2 receiver, and the Geode Connect(R) app was used for setting up and testing the receiver.

WolframAlpha(C) was used to analytically verify the solution for the integral for the standard deviation of a sine curve.