RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Sets
2.1.1. Precipitation Data Set
2.1.2. Soil Properties
2.1.3. Temperature Data Set
2.1.4. Calibration and Validation Data Sets
2.2. Antecedent Precipitation Index
2.3. Calibration and Validation Procedure
3. Results
3.1. Calibration and Evaluation
3.2. Two-Fold Cross-Validation
3.3. Comparison with ESA CCI Soil Moisture Data
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
API | Antecedent Precipitation Index |
ASCAT | Advanced Scatterometer |
CDS | Climate Data Store |
CV | Cross Validation |
DJF | December, January, February (Season) |
DWD | Deutscher Wetterdienst (German weather service) |
ECMWF | European Center for Medium-Range Weather Forecasts |
ECV | Essential Climate Variable |
ERA5 | ECMWF Reanalysis v5 |
ESA CCI SM | European Space Agency’s Climate Change Initiative Soil Moisture Product |
FDR | Frequency Domain Reflectometry |
GCOS | Global Climate Observing System |
GPCC | Global Precipitation Climatology Centre |
GPCP | Global Precipitation Climatology Project |
GPM | Global Precipitation Measurement (mission) |
GPS | Global Positioning System |
IMERG | Integrated Multi-satellitE Retrievals for the GPM Mission |
ISMN | International Soil Moisture Network |
ISRIC | International Soil Reference and Information Center |
JJA | June, July, August (Season) |
lAPI | local optimized Antecedent Precipitation Index |
MAM | March, April, May (Season) |
NASA | National Aeronautics and Space Administration |
OPTRAM | Optical Trapezoid Model |
PERSIANN-CDR | Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network-Climate Data Record |
RADOLAN | RAdar OnLine ANeichung (radar online adjustment) |
RMSD | Root Mean Square Difference |
SMAP | Soil Moisture Active Passive (mission) |
SOC | Soil Organic Carbon |
SON | September, October, November (Season) |
TDR | Time Domain Reflectometry |
TERENO | Terrestrial Environmental Observatories |
TOTRAM | Thermal-Optical Triangle Method |
ubRMSD | unbiased Root Mean Square Difference |
UAV | Unmanned Aerial Vehicle |
WMO | World Meteorological Organization |
Appendix A
Filename | RADOLAN_API_v1.0.0.nc |
Filetype | NetCDF4 |
Version | 1.0.0 |
License | CC-BY-SA |
URL | https://doi.org/10.5281/zenodo.4588904 (accessed on 27 April 2021) |
File Size | 20.9 GB |
Dimensions | 692 × 1188 × 43,824 (latitude, longitude, time) |
Spatial Resolution | 1 km × 1 km |
Spatial Coverage | Territory of Germany |
Temporal Coverage | 01.01.2015–31.12.2019 |
Overall Opt. | Local Opt. | CV Class I Calibration | CV Class II Calibration | |||||
---|---|---|---|---|---|---|---|---|
Station | ||||||||
Beestland | 19,768.0102 | 6.9960 | 25,888.4543 | 6.7393 | - | - | 23,704.3638 | 7.0166 |
Boeken | 19,768.0102 | 6.9960 | 15,459.5184 | 8.6683 | - | - | 23,704.3638 | 7.0166 |
Goermin | 19,768.0102 | 6.9960 | 13,407.3887 | 8.9687 | - | - | 23,704.3638 | 7.0166 |
Grosszastrow | 19,768.0102 | 6.9960 | 13,103.0731 | 8.7054 | 16,265.6752 | 7.0217 | - | - |
Heydenhof | 19,768.0102 | 6.9960 | 13,002.0141 | 10.3239 | - | - | 23,704.3638 | 7.0166 |
Neu Tellin | 19,768.0102 | 6.9960 | 17,048.6849 | 7.9655 | 16,265.6752 | 7.0217 | - | - |
Rustow | 19,768.0102 | 6.9960 | 18,155.6516 | 8.7882 | 16,265.6752 | 7.0217 | - | - |
Sanzkow | 19,768.0102 | 6.9960 | 15,280.2734 | 12.2186 | - | - | 23,704.3638 | 7.0166 |
Sommersdorf | 19,768.0102 | 6.9960 | 15,931.4899 | 7.4929 | 16,265.6752 | 7.0217 | - | - |
Toitz | 19,768.0102 | 6.9960 | 26,363.4512 | 8.3422 | - | - | 23,704.3638 | 7.0166 |
Zarrenthin | 19,768.0102 | 6.9960 | 24,362.5183 | 6.5954 | - | - | 23,704.3638 | 7.0166 |
Gevenich | 19,768.0102 | 6.9960 | 3238.0722 | 11.7320 | 16,265.6752 | 7.0217 | - | - |
Merzenhausen | 19,768.0102 | 6.9960 | 3399.5669 | 14.6008 | 16,265.6752 | 7.0217 | - | - |
Schoeneseiffen | 19,768.0102 | 6.9960 | 4502.4258 | 36.9911 | 16,265.6752 | 7.0217 | - | - |
Selhausen | 19,768.0102 | 6.9960 | 4390.2302 | 15.1374 | 16,265.6752 | 7.0217 | - | - |
Wildenrath | 19,768.0102 | 6.9960 | 4129.9100 | 13.6303 | - | - | 23,704.3638 | 7.0166 |
Wallerfing_A2 | 19,768.0102 | 6.9960 | 2991.0367 | 7.0635 | 16,265.6752 | 7.0217 | - | - |
Wallerfing_A4 | 19,768.0102 | 6.9960 | 4604.2422 | 6.2033 | 16,265.6752 | 7.0217 | - | - |
Wallerfing_A6 | 19,768.0102 | 6.9960 | 3552.1796 | 4.0507 | - | - | 23,704.3638 | 7.0166 |
Wallerfing_P2 | 19,768.0102 | 6.9960 | 3009.0580 | 5.6143 | 16,265.6752 | 7.0217 | - | - |
Wallerfing_P6 | 19,768.0102 | 6.9960 | 3115.7178 | 3.3863 | - | - | 23,704.3638 | 7.0166 |
Wallerfing_P4 | 19,768.0102 | 6.9960 | 3612.4949 | 5.8123 | - | - | 23,704.3638 | 7.0166 |
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Station | Network | Cal/Val | Coordinates | Sand | Clay | Available |
---|---|---|---|---|---|---|
Set | [%] | [%] | Time Period | |||
Beestland | TERENO-NE | I | 53.9255N, 12.9180E | 60 | 10 | 20111107–20191010 |
Boeken | TERENO-NE | II | 53.9971N, 13.3124E | 58 | 15 | 20111107–20190523 |
Goermin | TERENO-NE | I | 53.9828N, 13.2579E | 54 | 15 | 20111107–20191010 |
Grosszastrow | TERENO-NE | II | 54.0170N, 13.2733E | 59 | 14 | 20111107–20191106 |
Heydenhof | TERENO-NE | II | 53.8682N, 13.2686E | 52 | 17 | 20130206–20191106 |
Neu Tellin | TERENO-NE | I | 53.8598N, 13.2121E | 61 | 13 | 20111107–20191010 |
Rustow | TERENO-NE | II | 53.9581N, 13.0786E | 60 | 13 | 20111107–20191106 |
Sanzkow | TERENO-NE | II | 53.8810N, 13.1243E | 65 | 10 | 20111107–20191106 |
Sommersdorf | TERENO-NE | II | 53.7899N, 12.9021E | 58 | 12 | 20151020–20191010 |
Toitz | TERENO-NE | II | 53.9725N, 12.9906E | 59 | 14 | 20111107–20190910 |
Voelschow | TERENO-NE | I | 53.8712N, 13.3459E | 59 | 14 | 20130128–20190619 |
Zarrenthin | TERENO-NE | I | 53.9425N, 13.2857E | 59 | 13 | 20111107–20191107 |
Gevenich | TERENO-Rur | II | 50.9892N, 6.32355E | 22 | 16 | 20110804–20190403 |
Merzenhausen | TERENO-Rur | II | 50.9303N, 6.29747E | 21 | 16 | 20111103–20190103 |
Schoeneseiffen | TERENO-Rur | I | 50.5149N, 6.37559E | 28 | 22 | 20100222–20190425 |
Selhausen | TERENO-Rur | II | 50.8691N, 6.44954E | 19 | 19 | 20130424–20161029 |
Wildenrath | TERENO-Rur | II | 51.1327N, 6.16918E | 75 | 8 | 20120416–20181004 |
Wallerfing_A2 | Wallerfing | I | 48.6953N, 12.8673E | 22 | 25 | 20160422–20161026 |
Wallerfing_A4 | Wallerfing | I | 48.6969N, 12.8673E | 22 | 25 | 20160422–20161026 |
Wallerfing_A6 | Wallerfing | I | 48.6891N, 12.8722E | 26 | 23 | 20160422–20161026 |
Wallerfing_P2 | Wallerfing | I | 48.6907N, 12.8746E | 26 | 23 | 20160422–20161026 |
Wallerfing_P4 | Wallerfing | II | 48.7028N, 12.8966E | 29 | 21 | 20160422–20161026 |
Wallerfing_P6 | Wallerfing | I | 48.7037N, 12.8989E | 29 | 21 | 20160422–20161026 |
RMSD [Vol%] | ubRMSD [Vol%] | R | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
In-Situ | CCI | In-Situ | CCI | In-Situ | CCI | |||||||
Station | API | lAPI | CCI | API | API | lAPI | CCI | API | API | lAPI | CCI | API |
Beestland | 2.29 * | 2.02 * | 5.19 | 5.77 | 2.16 * | 2.02 * | 3.26 | 3.27 | 0.69 * | 0.69 * | 0.56 | 0.55 |
Boeken | 2.19 * | 1.76 * | 4.34 | 4.58 | 1.88 * | 1.76 * | 4.32 | 4.36 | 0.60 * | 0.71 * | 0.42 | 0.40 |
Goermin | 2.83 * | 2.29 * | 4.34 | 4.41 | 2.78 * | 2.29 * | 4.30 | 4.30 | 0.64 * | 0.77 * | 0.50 | 0.44 |
Grosszastrow | 3.09 * | 2.67 * | 5.19 | 4.76 | 3.09 * | 2.67 * | 4.87 | 4.51 | 0.60 * | 0.71 * | 0.36 | 0.28 |
Heydenhof | 2.93 * | 2.03 * | 4.49 | 4.28 | 2.15 * | 2.02 * | 4.01 | 4.28 | 0.67 * | 0.71 * | 0.53 | 0.44 |
Neu Tellin | 1.84 * | 1.72 * | 4.26 | 4.62 | 1.84 * | 1.71 * | 3.37 | 3.80 | 0.77 * | 0.80 * | 0.59 | 0.41 |
Rustow | 2.67 * | 2.29 * | 3.79 | 3.99 | 2.30 * | 2.28 * | 3.78 | 3.69 | 0.59 * | 0.63 * | 0.48 | 0.49 |
Sanzkow | 4.04 | 2.28 * | 3.87 | 4.12 | 2.72 * | 2.28 * | 3.77 | 3.51 | 0.70 * | 0.79 * | 0.55 | 0.59 |
Sommersdorf | 2.01 * | 1.81 * | 4.21 | 4.32 | 2.00 * | 1.81 * | 2.82 | 3.25 | 0.76 * | 0.80 * | 0.71 | 0.60 |
Toitz | 2.59 * | 1.55 * | 3.07 | 3.91 | 1.55 * | 1.55 * | 3.06 | 3.25 | 0.72 * | 0.71 * | 0.63 | 0.57 |
Voelschow | 3.21* | 1.74 * | 4.27 | 4.48 | 2.03* | 1.73* | 4.07 | 4.34 | 0.61 * | 0.76 * | 0.52 | 0.43 |
Zarrenthin | 2.96 * | 2.87 * | 4.72 | 4.24 | 2.91* | 2.83* | 4.56 | 4.21 | 0.32 | 0.32 | 0.33 | 0.41 |
Gevenich | 7.94 * | 4.51 * | 8.84 | 3.74 | 7.35 | 4.51 * | 6.67 | 2.61 | 0.62 | 0.84 * | 0.69 | 0.59 |
Merzenhausen | 8.09 | 6.51 * | 7.12 | 4.30 | 7.84 | 6.50 | 5.76 | 3.84 | 0.05 | 0.57 | 0.68 | 0.21 |
Schoeneseiffen | 8.90 | 3.87 * | 6.99 | 4.30 | 7.20 | 3.87 * | 6.80 | 2.52 | 0.54 | 0.88 * | 0.59 | 0.47 |
Selhausen | 5.91 | 4.15 * | 4.21 | 3.56 | 5.62 | 4.15 * | 4.21 | 3.04 | 0.51 | 0.77 | 0.81 | 0.42 |
Wildenrath | 8.87 * | 5.01 * | 11.54 | 4.80 | 6.96 | 5.00 * | 6.42 | 2.60 | 0.44 | 0.77 * | 0.57 | 0.54 |
Wallerfing_A2 | 4.29 * | 3.14 * | 6.33 | 3.46 | 3.31 | 3.12 | 2.92 | 1.98 | 0.51 | 0.65 | 0.70 | 0.47 |
Wallerfing_A4 | 4.89 * | 4.01 * | 6.64 | 3.46 | 4.00 | 3.99 | 3.38 | 1.98 | 0.40 | 0.45 | 0.68 | 0.47 |
Wallerfing_A6 | 7.52 * | 2.75 * | 9.24 | 2.46 | 2.73 * | 2.70 * | 2.76 | 1.68 | 0.76 * | 0.73 | 0.75 | 0.65 |
Wallerfing_P2 | 5.19 * | 2.75 * | 6.85 | 2.50 | 2.76 * | 2.68 * | 2.77 | 1.67 | 0.76 * | 0.74 | 0.75 | 0.65 |
Wallerfing_P4 | 4.30 * | 1.80 * | 7.12 | 3.32 | 2.15 * | 1.80 * | 2.54 | 1.56 | 0.81 * | 0.86 * | 0.72 | 0.65 |
Wallerfing_P6 | 8.72 * | 2.03 * | 11.26 | 2.92 | 2.10 * | 2.03 * | 2.63 | 1.57 | 0.81 * | 0.81 * | 0.63 | 0.65 |
Mean | 4.66 * | 2.85 * | 5.99 | 4.01 | 3.45 * | 2.84 * | 4.05 | 3.12 | 0.60 | 0.72 * | 0.60 | 0.49 |
Standard dev. | 2.47 | 1.27 * | 2.36 | 0.77 | 2.01 | 1.27 * | 1.30 | 1.02 | 0.18 | 0.13 | 0.13 | 0.12 |
Run | RMSD [Vol%] | ubRMSD [Vol%] | R |
---|---|---|---|
Overall Calibration | mean: 4.65 stdev: 2.37 | mean: 3.37 stdev: 1.93 | mean: 0.61 stdev: 0.15 |
Avg. of Cross-Validation | mean: 4.72 stdev: 2.29 | mean: 3.38 stdev: 1.93 | mean: 0.61 stdev: 0.16 |
Run I: Validation Set | mean: 4.48 stdev: 2.13 | mean: 2.59 stdev: 1.28 | mean: 0.66 stdev: 0.12 |
Run II: Validation Set | mean: 4.99 stdev: 2.43 | mean: 4.25 stdev: 2.13 | mean: 0.55 stdev: 0.17 |
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Ramsauer, T.; Weiß, T.; Löw, A.; Marzahn, P. RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data. Remote Sens. 2021, 13, 1712. https://doi.org/10.3390/rs13091712
Ramsauer T, Weiß T, Löw A, Marzahn P. RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data. Remote Sensing. 2021; 13(9):1712. https://doi.org/10.3390/rs13091712
Chicago/Turabian StyleRamsauer, Thomas, Thomas Weiß, Alexander Löw, and Philip Marzahn. 2021. "RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data" Remote Sensing 13, no. 9: 1712. https://doi.org/10.3390/rs13091712