This README.txt file was generated on 2023-06-09 by Edward Bair GENERAL INFORMATION 1. Title of Dataset: Snow cover and snow water equivalent for "How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?" 2. Author Information A. Principal Investigator Contact Information Name: Edward Bair Institution: Earth Research Institute, University of California, Santa Barbara Address: 6832 Ellison Hall University of California Santa Barbara, CA 93106-3060 Email: nbair@eri.ucsb.edu 3. Date of data collection (single date, range, approximate date) : 2018-10-1 through 2020-9-30 (spiresHLS) or 2018-01-01 through 2020-12-31 4. Geographic location of data collection : Tuolumne River Basin above Hetch Hetchy, California USA 5. Information about funding sources that supported the collection of the data: see Bair, E. H., Dozier, J., Rittger, K., Stillinger, T., Kleiber, W., and Davis, R. E.: How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, https://doi.org/10.5194/tc-2022-230, in press. 1. Licenses/restrictions placed on the data: Creative Commons Legal Code CC0 1.0 Universal Official translations of this legal tool are available CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE LEGAL SERVICES. DISTRIBUTION OF THIS DOCUMENT DOES NOT CREATE AN ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES THIS INFORMATION ON AN "AS-IS" BASIS. CREATIVE COMMONS MAKES NO WARRANTIES REGARDING THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS PROVIDED HEREUNDER, AND DISCLAIMS LIABILITY FOR DAMAGES RESULTING FROM THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS PROVIDED HEREUNDER. 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Links to publications that cite or use the data: Bair, E. H., Dozier, J., Rittger, K., Stillinger, T., Kleiber, W., and Davis, R. E.: How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, https://doi.org/10.5194/tc-2022-230, in press. 3. Links to other publicly accessible locations of the data: 4. Links/relationships to ancillary data sets: 5. Was data derived from another source? yes A. If yes, list source(s): Bair, E.H., Stillinger, T., and Dozier, J. (2021) Snow Property Inversion from Remote Sensing (SPIReS), IEEE Transactions on Remote Sensing and Geoscience, doi: 10.1109/TGRS.2020.3040328 Rittger, K., Krock, M., Bair, E.H., Stephenson, T., Rajagopolan, B., Bormann, K., and Painter, T. (2021), Multi-sensor fusion using random forests for daily fractional snow cover at 30 m, Remote Sensing of the Environment, 264, 112608, doi: 10.1016/j.rse.2021.112608 6. Recommended citation for this dataset: Bair, E.H., Snow cover and snow water equivalent for "How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?", doi: [tbd], [date accessed] DATA & FILE OVERVIEW 1. File List: 2. Relationship between files, if important: 3. Additional related data collected that was not included in the current data package: 4. Are there multiple versions of the dataset? no A. If yes, name of file(s) that was updated: i. Why was the file updated? ii. When was the file updated? METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Bair, E. H., Dozier, J., Rittger, K., Stillinger, T., Kleiber, W., and Davis, R. E.: How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, https://doi.org/10.5194/tc-2022-230, in press. 2. Methods for processing the data: https://github.com/edwardbair/ParBal 3. Instrument- or software-specific information needed to interpret the data: 4. Standards and calibration information, if appropriate: 5. Environmental/experimental conditions: 6. Describe any quality-assurance procedures performed on the data: 7. People involved with sample collection, processing, analysis and/or submission: DATA-SPECIFIC INFORMATION FOR: 2021.h5 (example water year) 1. Number of variables: 3 - 4 2. Number of cases/rows:1119x1297x365 (or 273) 3. Variable List: The projection is UTM 11 with 30 m pixels. The h5 files can be read with several software packages. We use MATLAB. The h5 files contain: MATLAB matdates, geographic information, spactime cubes of: SCAG-fusion delta_vis (deltavis, vis-nIR albedo degradation due to lap, unitless) grain_size (snow grain size, um) snow_fraction (snow cover fraction, unitless) SPIReS-HLS dust (dust conc. ppm) grain_size (snow grain in size, um) snow_fraction (snow cover fraction, unitless) SWE reconstructions for both snow cover datasets spacetime cubes of max swe dates (maxawedates - empty array of ones), daily snow melt (melt, mm), daily reconstructed SWE (swe, mm), daily hybrid SWE which uses scaled GLDAS SWE for the acc. season (sweHybrid, mm). The spacetime cubes are each one day, 4. Missing data codes: NaN 5. Specialized formats or other abbreviations used: https://www.hdfgroup.org/solutions/hdf5/