SnowCloudMetrics: Snow Information for Everyone
Abstract
:1. Introduction
2. Datasets and Methods
2.1. Snow Cover Frequency
2.2. Snow Disappearance Date
2.3. Cloud Correction in GEE Algorithm
2.4. An Example Application of SCF and SDD in the Amu Darya Basin
2.5. Assessment using Snow Telemetry Network in the Western U.S.
3. Results
3.1. Global Map** of SCF and SDD
3.2. Results from the SNOTEL Assessment
3.3. Results for the Amu Darya Basin Example
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Code and Data Availability
References
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Standard Deviation (σ) | GEE–SNOTEL by Regional Elevation Band | ||||||
---|---|---|---|---|---|---|---|
State | # Stations Sampled | RMSE SNOTEL vs. GEE(SCF) | SNOTEL (+/−SCF) | GEE (+/− SCF) | Low (SCF) | Mid (SCF) | High (SCF) |
Alaska | 35 | 0.1 | 0.07 | 0.09 | −0.09 | −0.03 | −0.04 |
Arizona | 8 | 0.09 | 0.07 | 0.07 | −0.09 | −0.07 | −0.07 |
California | 29 | 0.13 | 0.10 | 0.07 | −0.09 | −0.01 | −0.07 |
Colorado | 113 | 0.10 | 0.08 | 0.08 | −0.10 | −0.05 | −0.05 |
Idaho | 79 | 0.11 | 0.09 | 0.09 | −0.10 | −0.06 | −0.04 |
Montana | 86 | 0.14 | 0.10 | 0.10 | −0.12 | −0.09 | −0.05 |
New Mexico | 17 | 0.13 | 0.09 | 0.09 | −0.07 | −0.11 | −0.13 |
Nevada | 39 | 0.11 | 0.09 | 0.1 | −0.09 | −0.10 | −0.05 |
Oregon | 68 | 0.15 | 0.13 | 0.09 | −0.10 | −0.11 | −0.10 |
Utah | 129 | 0.10 | 0.08 | 0.09 | −0.10 | −0.06 | −0.02 |
Washington | 67 | 0.16 | 0.08 | 0.11 | −0.16 | −0.15 | −0.07 |
Wyoming | 88 | 0.1 | 0.09 | 0.08 | −0.07 | −0.05 | −0.05 |
Mean SDD | GEE–SNOTEL by Regional Elevation Band | ||||||
---|---|---|---|---|---|---|---|
State | # SNOTEL Stations Sampled | RMSESNOTEL vs. GEE (Days) | SNOTEL (Day) | GEE (Day) | Low (Days) | Mid (Days) | High (Days) |
Alaska | 35 | 11 | 14-May | 9-May | −4 | −4 | −6 |
Arizona | 8 | 13 | 6-Apr | 25-Mar | −11 | −13 | −12 |
California | 28 | 24 | 18-May | 4-May | −19 | 3 | −6 |
Colorado | 113 | 17 | 20-May | 11-May | −15 | −7 | −4 |
Idaho | 78 | 26 | 20-May | 5-May | −24 | −12 | −9 |
Montana | 86 | 27 | 28-May | 13-May | −18 | −14 | −9 |
New Mexico | 17 | 19 | 21-Apr | 8-Apr | −12 | −13 | −17 |
Utah | 129 | 19 | 8-May | 1-May | −14 | −7 | −1 |
Washington | 67 | 30 | 26-May | 4-May | −31 | −27 | −8 |
Wyoming | 87 | 18 | 22-May | 15-May | −7 | −6 | −5 |
True Positive (TP) | True Negative (TN) | False Positive (FP) | False Negative (FN) | Accuracy (A) Kappa (K) | |
---|---|---|---|---|---|
Entire Time Series n = 3,692,026 | 1,451,797 (39%) | 1,543,337 (42%) | 196,740 (5%) | 500,152 (14%) | 0.81 (A) 0.62 (K) |
Early-Season (Oct, Nov, Dec) n = 930,783 | 420,149 (45%) | 263,841 (28%) | 82,702 (9%) | 164,091 (18%) | 0.73 (A) 0.46 (K) |
Mid-Season (Jan, Feb, Mar) n = 913,310 | 759,940 (83%) | 18,492 (2%) | 33,253 (4%) | 101,625 (11%) | 0.85 (A) 0.15 (K) |
Late-Season (Apr, May, Jun) n = 919,404 | 269,728 (29%) | 383,927 (42%) | 65,910 (7%) | 199,839 (22%) | 0.71 (A) 0.43 (K) |
SCF Metric | SDD Metric |
---|---|
Annual date range (WY2001 to WY2019) | Annual date range (WY2000 to WY2019) |
Custom spatial extent Shapefile import | Custom spatial extent Shapefile import |
Global coverage Pixel-level data inspector Time series plotting | Northern Hemisphere coverage Pixel-level data inspector Time series plotting |
Data table output (.csv) | Data table output (.csv) |
GeoTIFF image export | GeoTIFF image export |
SRTM 30 m DEM analysis | SRTM 30 m DEM analysis |
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Share and Cite
Crumley, R.L.; Palomaki, R.T.; Nolin, A.W.; Sproles, E.A.; Mar, E.J. SnowCloudMetrics: Snow Information for Everyone. Remote Sens. 2020, 12, 3341. https://doi.org/10.3390/rs12203341
Crumley RL, Palomaki RT, Nolin AW, Sproles EA, Mar EJ. SnowCloudMetrics: Snow Information for Everyone. Remote Sensing. 2020; 12(20):3341. https://doi.org/10.3390/rs12203341
Chicago/Turabian StyleCrumley, Ryan L., Ross T. Palomaki, Anne W. Nolin, Eric A. Sproles, and Eugene J. Mar. 2020. "SnowCloudMetrics: Snow Information for Everyone" Remote Sensing 12, no. 20: 3341. https://doi.org/10.3390/rs12203341