Data from: Direct insertion of NASA Airborne Snow Observatory-derived snow depth time-series into the iSnobal energy balance snow model

<p>This dataset accompanies a manuscript submission to <em>Water Resources Research</em>. The data herein consists of all of the hourly meteorological forcing variables needed to execute the iSnobal physically based snow model over the Tuolumne River Basin in the Sierra Nevada of California for water years 2013 to 2016. The variables are presented as vectors and include (1) air temperature, (2) relative humidity, (3) computed dew point temperature, (4) computed vapor pressure, (5) precipitation mass, (6) wind speed, (7) wind direction, (8) incoming solar radiation, and (9) a computed cloud factor product. Each variable has been through rigorous quality assurance and quality control to ensure that the data is model-ready. That is, there are no temporal data gaps over the total model domain, yet measurements from singular meteorological sites can go offline from time to time. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Dataset: Direct insertion of NASA Airborne Snow Observatory-derived snow depth time-series into the iSnobal energy balance snow model (Zenodo).</p> <p>File Name: Web Page, url: <a href="https://zenodo.org/record/1228400#.W8YDzGhKiUk">https://zenodo.org/record/1228400#.W8YDzGhKiUk</a> </p><p>The file structure is organized as follows:</p> <p>ASO_50m_depth_surfaces - This folder contains the Airborne Snow Observatory lidar-derived snow depth products aggregated to 50m gridded spatial resolution. Each file is titled with a date such as ‘TBYYYYMMDD_SUPERsnow_depth.asc’. The coordinates are in UTM zone 11N and use the WGS84 coordinate system.</p> <p><strong>static_grids</strong></p> <ul> <li>Static grids are used in each of the subsequent folders and are not changed between years.</li> <li>init0000.ipw <ul> <li>Initialization file to begin the model run. Contains the digital elevation model in band 1, surface roughness raster in band 2, and zeroed images of snow properties in bands 3-7.</li> </ul></li> <li>maxus.nc <ul> <li>netCDF file of 72 separate images of maximum upwind slope for all upwind directions from 0 (north) to 355 degrees in 5-degree increments. Derived using Adam Winstral’s Sx algorithm.</li> </ul></li> <li>tuolx_dem_50m.ipw <ul> <li>Digital elevation model from ASO snow-free acquisition aggregated to 50m gridded spatial resolution. Same information as band 1 in the init0000.ipw file.</li> </ul></li> <li>tuolx_hetchy_mask_50m.ipw <ul> <li>Basin mask of the Tuolumne River Basin above Hetch Hetchy Reservoir. Out-of-basin cells denoted as 0, and in-basin cells denoted as 1.</li> </ul></li> <li>tuolx_vegheight_50m.ipw <ul> <li>Vegetation height raster in meters. Derived from NLCD dataset of vegetation type..</li> </ul></li> <li>tuolx_vegk_50m.ipw <ul> <li>Emissivity of the vegetation canopy. Derived from NLCD dataset of vegetation type.</li> </ul></li> <li>tuolx_vegnlcd_50m.ipw <ul> <li>Vegetation type from the National Land Cover Database.</li> </ul></li> <li>tuolx_vegtau_50m.ipw <ul> <li>Fractional transmissivity of the vegetation canopy. Derived from NLCD dataset of vegetation type.</li> </ul></li> </ul> <p>The directories for each water year contain the configuration file for that year along with the vector meteorological data from measurement sites and site metadata in .csv format.</p> <ul> <li><strong>wy2013</strong></li> <li><strong>wy2014</strong></li> <li><strong>wy2015</strong></li> <li><strong>wy2016</strong> <ul> <li>backup_config.ini</li> <li>air_temp.csv</li> <li>cloud_factor.csv</li> <li>metadata.csv</li> <li>precip.csv</li> <li>vapor_pressure.csv</li> <li>wind_direction.csv</li> <li>wind_speed.csv</li></ul><p></p></li> </ul></li> </ul>

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