A First Verification of Sim2DSphere Model’s Ability to Predict the Spatiotemporal Variability of Parameters Characterizing Land Surface Interactions at Diverse European Ecosystems
Abstract
:1. Introduction
2. Experimental Set-Up
2.1. Sites Description
2.2. Datasets
2.2.1. FLUXNET Ground Monitoring Network
2.2.2. EO and Geospatial Data
2.2.3. Radiosondes Data
2.3. Sim2DSphere Model
3. Methodology
3.1. Pre-Processing
3.1.1. FLUXNET In-Situ
3.1.2. Radiosondes In-Situ
3.1.3. Geospatial Data
3.2. Sim2DSphere Parameterization
3.3. Statistical Comparisons
4. Results
4.1. Latent Heat Flux
4.2. Sensible Heat Flux
4.3. Net Radiation
5. Discussion
5.1. Diurnal Dynamics of Energy and Radiative Fluxes
Comparisons for Different Biomes
5.2. Potential Sources of Uncertainty and Limitations
5.3. Computational Requirements and Model Transferability
6. Final Remarks
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Dates | Site | Lat/Lon | Height (~ in m) | Slope | Biome | Plant Type | Soil Type | Köppen |
---|---|---|---|---|---|---|---|---|
11 June 2020 29 July 2020 14 August 2020 | ES-LJU | 36.926/2.752 | 2.5 | Gentle (<2%) | OSH | evergreen shrubs (macchia) | Clay loam | Csa |
ES-CND | 37.915/−3.227 | 15 | Medium (>2%, <5%) | WSA | Olive cultivars | Clay loam | Csa | |
27 June 2019 29 July 2019 30 August 2019 | FR-AUR | 43.549/1.106 | 3.5 | Significant (>5%, <10%) | CROP | wheat | Clay loam | Cfb |
FR-LAM | 43.493/1.237 | 3.6 | Flat | CROP | maize | Clay loam | Cfb | |
FR-TOU | 43.572/1.374 | 3 | Flat | GRA | Grass | Clay-loam | Cfb | |
30 June 2018 10 August 2018 18 September 2018 | DE-KLI | 50.892/13.522 | 2 | Flat | CROP | maize | Loam | Cfb |
DE-GRI | 50.950/13.513 | 3 | Flat | GRA | C3 short grass | Loam | Cfb | |
DE-THA | 50.964/13.567 | 42 | Gentle (<2%) | ENF | evergreen coniferous trees (Norway Spruce) | Loam | Cfb | |
27 July 2013 12 August 2013 13 September 2013 | IT-CA2 | 42.377/12.026 | 5 | Gentle (<2%) | CRO | crop rotation grassland | Clay loam | Csa |
IT-CA3 | 42.380/12.022 | 5 | Flat | DBF | temp. BL deciduous trees | Clay loam | Csa |
Name | Description | Mathematical Definition |
---|---|---|
Bias/MBE | Bias (accuracy) or Mean Bias Error | |
Scatter/MSD | Scatter (precision) or Standard Deviation | |
RMSD | Root Mean Square Difference | |
R2 | Linear Correlation Coefficient |
Country | Station | Parameter | Bias | Scatter | RMSD | R2 | n |
---|---|---|---|---|---|---|---|
Spain | ES-Lju | Latent heat flux (Wm−2) | 38.87 | 43.94 | 58.66 | 0.250 | 108 |
ES-Cnd | −8.15 | 30.13 | 31.22 | 0.634 | 108 | ||
France | FR-Aur | 44.14 | 49.29 | 66.16 | 0.778 | 108 | |
FR-Lam | −23.42 | 54.66 | 59.47 | 0.805 | 108 | ||
FR-Tou | 21.10 | 39.25 | 44.56 | 0.826 | 108 | ||
Germany | DE-Kli | 7.53 | 28.31 | 29.30 | 0.890 | 108 | |
DE-Gri | 39.79 | 42.65 | 58.33 | 0.748 | 108 | ||
DE-Tha | 39.16 | 44.53 | 59.30 | 0.465 | 108 | ||
Italy | IT-CA2 | 39.37 | 52.09 | 65.29 | 0.584 | 108 | |
IT-CA3 | −22.39 | 60.68 | 64.68 | 0.645 | 108 | ||
Average | 17.6 | 44.53 | 53.69 | 0.662 | |||
Country | Station | Parameter | Bias | Scatter | RMSD | R2 | n |
Spain | ES-Lju | Sensible heat flux (Wm−2) | 0.38 | 58.96 | 58.96 | 0.792 | 108 |
ES-Cnd | 26.84 | 56.88 | 62.90 | 0.802 | 108 | ||
France | FR-Aur | −4.24 | 38.33 | 38.57 | 0.945 | 108 | |
FR-Lam | 79.43 | 59.14 | 99.03 | 0.812 | 108 | ||
FR-Tou | 9.66 | 39.99 | 41.14 | 0.886 | 108 | ||
Germany | DE-Kli | 8.53 | 36.96 | 37.93 | 0.861 | 108 | |
DE-Gri | 27.22 | 34.39 | 43.86 | 0.891 | 108 | ||
DE-Tha | −30.57 | 58.78 | 66.26 | 0.928 | 108 | ||
Italy | IT-CA2 | −20.44 | 61.07 | 64.40 | 0.744 | 108 | |
IT-CA3 | 29.16 | 54.94 | 62.20 | 0.731 | 108 | ||
Average | 12.59 | 49.94 | 57.52 | 0.839 | |||
Country | Station | Parameter | Bias | Scatter | RMSD | R2 | n |
Spain | ES-Lju | Net Radiation (Wm−2) | −31.54 | 130.17 | 140.23 | 0.788 | 101 |
ES-Cnd | −22.97 | 110.98 | 113.33 | 0.828 | 108 | ||
France | FR-Aur | 3.185 | 48.63 | 48.73 | 0.964 | 108 | |
FR-Lam | −29.92 | 73.17 | 79.05 | 0.929 | 108 | ||
FR-Tou | −15.51 | 74.19 | 75.80 | 0.921 | 108 | ||
Germany | DE-Kli | −0.699 | 65.74 | 65.75 | 0.934 | 108 | |
DE-Gri | 15.04 | 68.01 | 69.65 | 0.934 | 108 | ||
DE-Tha | −37.55 | 83.14 | 91.23 | 0.943 | 108 | ||
Italy | IT-CA2 | −4.00 | 58.80 | 58.94 | 0.937 | 106 | |
IT-CA3 | −9.21 | 64.28 | 64.93 | 0.934 | 107 | ||
Average | −13.31 | 77.71 | 80.76 | 0.911 |
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Lekka, C.; Petropoulos, G.P.; Detsikas, S.E. A First Verification of Sim2DSphere Model’s Ability to Predict the Spatiotemporal Variability of Parameters Characterizing Land Surface Interactions at Diverse European Ecosystems. Sensors 2025, 25, 1501. https://doi.org/10.3390/s25051501
Lekka C, Petropoulos GP, Detsikas SE. A First Verification of Sim2DSphere Model’s Ability to Predict the Spatiotemporal Variability of Parameters Characterizing Land Surface Interactions at Diverse European Ecosystems. Sensors. 2025; 25(5):1501. https://doi.org/10.3390/s25051501
Chicago/Turabian StyleLekka, Christina, George P. Petropoulos, and Spyridon E. Detsikas. 2025. "A First Verification of Sim2DSphere Model’s Ability to Predict the Spatiotemporal Variability of Parameters Characterizing Land Surface Interactions at Diverse European Ecosystems" Sensors 25, no. 5: 1501. https://doi.org/10.3390/s25051501
APA StyleLekka, C., Petropoulos, G. P., & Detsikas, S. E. (2025). A First Verification of Sim2DSphere Model’s Ability to Predict the Spatiotemporal Variability of Parameters Characterizing Land Surface Interactions at Diverse European Ecosystems. Sensors, 25(5), 1501. https://doi.org/10.3390/s25051501