Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data
Abstract
:1. Introduction
2. Data and Methods
2.1. Data
2.1.1. Tower Flux Data
2.1.2. Satellite Albedo and Leaf Area Index
2.2. CHTESSEL Model
2.3. Simulation Setup
2.4. Evaluation
3. Results
3.1. Comparison of LAI and Albedo
3.2. Fluxes Evaluation
3.3. Soil Moisture Stress
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
References
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Station | Country | Latitude | Longitude | Plant Functional Type | Time Period |
---|---|---|---|---|---|
Amplero | Italy | 41.9041 | 13.6052 | Grassland | 2003–2006 |
Blodgett | U.S. | 38.8953 | −120.633 | Evergreen needleleaf | 2000–2006 |
Bugac | Hungary | 46.6917 | 19.6017 | Grassland | 2002–2006 |
Espirra | Portugal | 38.6394 | −8.6018 | Evergreen broadleaf | 2001–2006 |
Fort Peck | U.S. | 48.3077 | −105.102 | Grassland | 2000–2006 |
Harvard | U.S. | 42.5378 | −72.1715 | Deciduous broadleaf | 1994–2001 |
Hesse | France | 48.6742 | 7.0656 | Deciduous broadleaf | 1999–2006 |
Howard | Australia | −12.4943 | 131.152 | Woody savannah | 2002–2005 |
Howlandm | U.S. | 45.2041 | −68.7402 | Evergreen needleleaf | 1996–2004 |
Hyytiala | Finland | 61.8474 | 24.2948 | Evergreen needleleaf | 2001–2004 |
Kruger | South Africa | −25.0197 | 31.4969 | Savannah | 2002–2003 |
Loobos | The Netherlands | 52.1679 | 5.744 | Evergreen needleleaf | 1997–2006 |
Mopane | Botswana | −19.9165 | 23.5603 | Woody savannah | 1999–2001 |
Palang | Indonesia | −2.345 | 114.036 | Evergreen broadleaf | 2002–2003 |
Sylvania | U.S. | 46.242 | −89.3477 | Mixed forest | 2002–2005 |
Tumbarumba | Australia | −35.6557 | 148.152 | Evergreen broadleaf | 2002–2005 |
University of Michigan | U.S. | 45.5598 | −84.7138 | Deciduous broadleaf | 1999–2003 |
Station | Vegetation Type | CTR | Optimal | Optimal |
---|---|---|---|---|
Amplero | L, short grass | 100 | 100 | 2 |
Bugac | L, short grass | 100 | 175 | 0.5 |
Fort Peck | L, short grass | 100 | 25 | 0.5 |
Howard | L, tall grass | 175 | 125 | 2 |
Kruger | L, tall grass | 100 | 300 | 2 |
Mopane | L, tall grass | 175 | 300 | 1 |
Blodgett | H, Evergreen needleleaf | 250 | 150 | 3 |
Espirra | H, evergreen broadleaf | 240 | 75 | 3 |
Harvard | H, deciduous broadleaf | 175 | 250 | 1 |
Hesse | H, deciduous broadleaf | 175 | 175 | 2 |
Howlandm | H, evergreen needleleaf | 250 | 275 | 0.5 |
Hyytiala | H, evergreen needleleaf | 250 | 225 | 0.5 |
Loobos | H, evergreen needleleaf | 250 | 150 | 2 |
Palang | H, evergreen broadleaf | 240 | 275 | 2 |
Sylvania | H, interrupted forest | 175 | 400 | 3 |
Tumbarumba | H, evergreen broadleaf | 240 | 225 | 2 |
University of Michigan | H, deciduous broadleaf | 175 | 400 | 3 |
Simulation | Details |
---|---|
CTR | Control simulation with default CHTESSEL parametersand input LAI and Albedo |
MALB | Same as CTR, but replacing the input albedo climatologywith the new high-resolution MODIS climatology |
MLAI | Same as CTR, but replacing the input LAI climatologywith the new high-resolution MODIS climatology |
MLAI_NOSMS | Same as MLAI, but removing the soil moisture stress function from the canopy resistance (setting ) when the soil moisture is above the wilting point in Equation (3) |
MLAI_RSMIN | Same as MLAI, but selecting the optimal for each station from a set ofsimulations with varying between 25 and 500. |
MLAI_ROOT | Same as MLAI, but using a uniform root distribution (Equation (5)) and selecting the optimal for each station from a set of simulations with of 0.5, 1, 2, and 3 m. |
Station | Mean CTR | Mean MALB | RMSD MALB vs. CTR |
---|---|---|---|
Amplero | 0.16 | 0.15 | 0.03 |
Blodgett | 0.13 | 0.1 | 0.02 |
Bugac | 0.18 | 0.16 | 0.03 |
Espirra | 0.16 | 0.14 | 0.02 |
Fort Peck | 0.25 | 0.18 | 0.07 |
Harvard | 0.11 | 0.13 | 0.03 |
Hesse | 0.13 | 0.15 | 0.03 |
Howard | 0.15 | 0.13 | 0.02 |
Howlandm | 0.11 | 0.12 | 0.01 |
Hyytiala | 0.12 | 0.11 | 0.02 |
Kruger | 0.17 | 0.16 | 0.03 |
Loobos | 0.17 | 0.11 | 0.07 |
Mopane | 0.16 | 0.17 | 0.01 |
Palang | 0.14 | 0.13 | 0.01 |
Sylvania | 0.11 | 0.13 | 0.04 |
Tumbarumba | 0.16 | 0.12 | 0.04 |
University of Michigan | 0.11 | 0.13 | 0.03 |
Median | 0.15 | 0.13 | 0.03 |
Station | Mean CTR | Mean MLAI | Mean CGLS | RMSD MLAI vs. CTR | RMSD MODIS vs. CGLS |
---|---|---|---|---|---|
Amplero | 2.43 | 1.7 | 1.51 | 0.9 | 0.29 |
Blodgett | 3.08 | 2.28 | 2.98 | 0.87 | 0.47 |
Bugac | 1.93 | 0.92 | 1.04 | 1.04 | 0.17 |
Espirra | 2.38 | 1.42 | 1.13 | 0.97 | 0.20 |
Fort Peck | 0.89 | 0.35 | 0.34 | 0.54 | 0.08 |
Harvard | 3.14 | 2.45 | 2.78 | 0.75 | 0.58 |
Hesse | 2.35 | 2.66 | 2.27 | 1.65 | 0.52 |
Howard | 1.76 | 1.55 | 1.58 | 0.28 | 0.47 |
Howlandm | 3.08 | 2.40 | 2.83 | 1.04 | 0.82 |
Hyytiala | 2.12 | 1.69 | 1.73 | 0.50 | 0.51 |
Kruger | 1.76 | 0.98 | 0.93 | 0.80 | 0.16 |
Loobos | 2.21 | 1.87 | 1.87 | 0.53 | 0.43 |
Mopane | 1.59 | 0.87 | 0.65 | 0.73 | 0.25 |
Palang | 5.59 | 4.42 | 4.01 | 1.20 | 0.40 |
Sylvania | 2.63 | 1.73 | 2.24 | 0.91 | 0.62 |
Tumbarumba | 3.60 | 4.31 | 3.09 | 0.83 | 0.72 |
University of Michigan | 2.42 | 2.11 | 1.76 | 0.86 | 0.25 |
Median | 2.38 | 1.73 | 1.76 | 0.86 | 0.43 |
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Stevens, D.; Miranda, P.M.A.; Orth, R.; Boussetta, S.; Balsamo, G.; Dutra, E. Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data. Atmosphere 2020, 11, 1362. https://doi.org/10.3390/atmos11121362
Stevens D, Miranda PMA, Orth R, Boussetta S, Balsamo G, Dutra E. Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data. Atmosphere. 2020; 11(12):1362. https://doi.org/10.3390/atmos11121362
Chicago/Turabian StyleStevens, David, Pedro M. A. Miranda, René Orth, Souhail Boussetta, Gianpaolo Balsamo, and Emanuel Dutra. 2020. "Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data" Atmosphere 11, no. 12: 1362. https://doi.org/10.3390/atmos11121362
APA StyleStevens, D., Miranda, P. M. A., Orth, R., Boussetta, S., Balsamo, G., & Dutra, E. (2020). Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data. Atmosphere, 11(12), 1362. https://doi.org/10.3390/atmos11121362