This README.txt file was generated on 2025-7-7 by Edward Bair

GENERAL INFORMATION

Title of Dataset: SPIReS-MODIS-ParBal Snow Water Equivalent Reconstruction: Western USA, water years 2001-2024

Author Information

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

CHANGE LOG

This 2025 version is an update to the 2023 version where:

• Water years 2022-2024 have been added
• The individual MODIS tiles (h08v04; h08v05; h09v04; h09v05; h10v04) are mosaiced, reprojected, and cropped into a Western US Albers Equal Area projection rather than a MODIS Sinusoidal projection. This reprojection reduces the image sizes from 4800 rows x 7200 columns to 4500 rows x 4500 columns.
• The SPIRES code (Bair et al., 2021) for the snow cover has several updates
  • MOD09GA v 6.1 was used
  • The grain size and dust retrievals, which determine the snow albedo, have been adjusted to limit peak values from occurring too early, during the accumulation season. See Palomaki et al. (2025) for a review.
    • Palomaki, R. T., Rittger, K., Lenard, S. J. P., Bair, E., Dozier, J., Skiles, S. M., & Painter, T. H. (2025). Assessment of methods for mapping snow albedo from MODIS. Remote Sensing of Environment, 326, 114742. https://doi.org/10.1016/j.rse.2025.114742
  • There are no longer null values (NaN) for grain size or dust when snow is present.

Date of data collection (single date, range, approximate date) :

2000-10-1 through 2024-7-30

Note: water years 2001 through 2023 are complete (1 Oct through 30 Sep), however 2024 only goes through 30 July as the CERES Syn Ed 4.1a Ed radiation forcing were not available for Aug & Sep 2024 at the time of creation.

Geographic location of data collection:

Western USA

Information about funding sources that supported the collection of the data:

Bair, E. H., J. Dozier, K. Rittger, T. Stillinger, W. Kleiber, and R. E. Davis (2023), How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, 17, 2629–2643, doi: 10.5194/tc-17-2629-2023.

Licenses/restrictions placed on the data: with the License.

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Links to publications that cite or use the data:

Bair, E. H., J. Dozier, K. Rittger, T. Stillinger, W. Kleiber, and R. E. Davis (2023), How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, 17, 2629–2643, doi: 10.5194/tc-17-2629-2023.

1. Links to other publicly accessible locations of the data:
2. Links/relationships to ancillary data sets:
3. 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

1. Recommended citation for this dataset:

Bair, E.H., SPIReS-MODIS-ParBal Snow Water Equivalent Reconstruction: Western USA, water years 2001-2024, doi: 10.25349/D9TK7H, [date accessed].

DATA & FILE OVERVIEW

File list:

1. mosaicreconstruction_2001.h5
2. mosaicreconstruction_2002.h5
3. mosaicreconstruction_2003.h5
4. mosaicreconstruction_2004.h5
5. mosaicreconstruction_2005.h5
6. mosaicreconstruction_2006.h5
7. mosaicreconstruction_2007.h5
8. mosaicreconstruction_2008.h5
9. mosaicreconstruction_2009.h5
10. mosaicreconstruction_2010.h5
11. mosaicreconstruction_2011.h5
12. mosaicreconstruction_2012.h5
13. mosaicreconstruction_2013.h5
14. mosaicreconstruction_2014.h5
15. mosaicreconstruction_2015.h5
16. mosaicreconstruction_2016.h5
17. mosaicreconstruction_2017.h5
18. mosaicreconstruction_2018.h5
19. mosaicreconstruction_2019.h5
20. mosaicreconstruction_2020.h5
21. mosaicreconstruction_2021.h5
22. mosaicreconstruction_2022.h5
23. mosaicreconstruction_2023.h5
24. mosaicreconstruction_2024.h5

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data:

Bair, E. H., J. Dozier, K. Rittger, T. Stillinger, W. Kleiber, and R. E. Davis (2023), How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, 17, 2629–2643, doi: 10.5194/tc-17-2629-2023.

1. Methods for processing the data:

https://github.com/edwardbair/ParBal

1. Instrument- or software-specific information needed to interpret the data:
2. Standards and calibration information, if appropriate:
3. Environmental/experimental conditions:
4. Describe any quality-assurance procedures performed on the data:
5. People involved with sample collection, processing, analysis and/or submission:

DATA-SPECIFIC INFORMATION FOR: 2021.h5 (example water year)

1. Number of variables: 4
2. Number of cases/rows: 4500x4500x365
3. Variable List:

The projection is the Western USA Albers with 500 m pixels. The 5 sinusodial tiles are available on demand. The h5 files can be read with several software packages. We use MATLAB. The /Grid/ReferencingMatrix can be used to create the x and y grid as:

[x y] = [row col 1] * R

where * is matrix multiplication

and R(1,1) - rows 1st, columns 2nd - is the upper left corner pixel x coordinate, R(2,1) is the upper left corner pixel y coordinate

The projection information is provided as a CRSstring

The h5 files contain:

MATLAB matrices, geographic information, 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,
begin on 10-1 and end on 9-30. For example, in MATLAB, this shows the structure of the WY 2021 h5 file.

h5disp('mosaicreconstruction_2001.h5')
HDF5 mosaicreconstruction_2001.h5
Group '/'
Attributes:
'MATLABdates': 730760.000000 ... 731124.000000
'ISOdates': '20001001 ... 20010930'
Group '/Grid'
Attributes:
'mapprojection': 'eqaconicstd'
'angleunits': 'degrees'
'aspect': 'normal'
'falsenorthing': 0.000000
'falseeasting': 0.000000
'geoid': 6378137.000000 0.081819
'mapparallels': 29.500000 45.500000
'nparallels': 2.000000
'origin': 37.500000 -113.000000 0.000000
'scalefactor': 1.000000
'trimlat': -90.000000 90.000000
'trimlon': -135.000000 135.000000
'CRSstring': 'PROJCRS["USA_Contiguous_Albers_Equal_Area_Conic",...,ID["ESRI",102003]]'
'ReferencingMatrix': 3x2 H5T_FLOAT
Dataset 'maxswedates'
Size: 4500x4500
MaxSize: 4500x4500
Datatype: H5T_STD_U16LE (uint16)
ChunkSize: 4500x4500
Filters: deflate(9)
FillValue: 0
Dataset 'melt'
Size: 4500x4500x365
MaxSize: 4500x4500x365
Datatype: H5T_STD_U16LE (uint16)
ChunkSize: 4500x4500x1
Filters: deflate(9)
FillValue: 65535
Attributes:
'units': 'mm'
Dataset 'swe'
Size: 4500x4500x365
MaxSize: 4500x4500x365
Datatype: H5T_STD_U16LE (uint16)
ChunkSize: 4500x4500x1
Filters: deflate(9)
FillValue: 65535
Attributes:
'units': 'mm'
Dataset 'sweHybrid'
Size: 4500x4500x365
MaxSize: 4500x4500x365
Datatype: H5T_STD_U16LE (uint16)
ChunkSize: 4500x4500x1
Filters: deflate(9)
FillValue: 65535
Attributes:
'units': 'mm'

To read all the hybrid SWE values for 2021 use:

sweHybrid=h5read('mosaicreconstruction2001.h5','/Grid/sweHybrid');

1. Missing data codes:
   NaN
2. Specialized formats or other abbreviations used:
   https://www.hdfgroup.org/solutions/hdf5/