Water, Energy, and Carbon with Artificial Neural Networks (WECANN): A statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence

Biogeosciences

Volumn 14, Issue 18, 2017, Pages 4101-4124

  Hamed Alemohammad, Seyed ^a,b   Fang, Bin ^a,b   Konings, Alexandra G ^c   Aires, Filipe ^a,d   Green, Julia K ^a,b   Kolassa, Jana ^e,f   Miralles, Diego ^g   Prigent, Catherine ^a,f   Gentine, Pierre ^a,b,h  

^a Department of Earth and Environmental Sciences   (United States)

^b Center for International Forestry Research   (United States)

^c STANFORD UNIVERSITY   (United States)

^d OBSERVATOIRE DE PARIS   (France)

^e UNIVERSITIES SPACE RESEARCH ASSOCIATION   (United States)

^f NASA GODDARD SPACE FLIGHT CENTER   (United States)

^g GHENT UNIVERSITY   (Belgium)

^h NONE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTIFICIAL NEURAL NETWORK; CARBON; DATA SET; DROUGHT; EDDY COVARIANCE; ENERGY; FLUORESCENCE; HEAT WAVE; LATENT HEAT FLUX; NET PRIMARY PRODUCTION; SENSIBLE HEAT FLUX; SOLAR RADIATION; SPATIAL RESOLUTION; SURFACE FLUX; TURBULENCE; WATER RESOURCE;

EID: 85029767232     PISSN: 17264170     EISSN: 17264189     Source Type: Journal    
DOI: 10.5194/bg-14-4101-2017     Document Type: Article

References (107)

1. Aires, F.: Combining Datasets of Satellite-Retrieved Products, Part I: Methodology and Water Budget Closure, J. Hydrometeorol., 15, 1677-1691, https://doi.org/10.1175/JHM-D-13-0148.1, 2014.
2. Aires, F., Prigent, C., and Rossow, W. B.: Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale:2. Global statistical relationships, J. Geophys. Res., 110, D11103, https://doi.org/10.1029/2004JD005094, 2005.
3. Aires, F., Aznay, O., Prigent, C., Paul, M., and Bernardo, F.: Synergistic multi-wavelength remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp-A, J. Geophys. Res.-Atmos., 117, D18304, https://doi.org/10.1029/2011JD017188, 2012.
4. Alemohammad, S. H., McColl, K. A., Konings, A. G., Entekhabi, D., and Stoffelen, A.: Characterization of precipitation product errors across the United States using multiplicative triple collocation, Hydrol. Earth Syst. Sci., 19, 3489-3503, https://doi.org/10.5194/hess-19-3489-2015, 2015.
5. Anber, U., Gentine, P., Wang, S., and Sobel, A. H.: Fog and rain in the Amazon, P. Natl. Acad. Sci. USA, 112, 11473-11477, https://doi.org/10.1073/pnas.1505077112, 2015.
6. Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems, IEEE Trans. Geosci. Remote Sens., 41, 253-264, https://doi.org/10.1109/TGRS.2002.808356, 2003.
7. Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel, W., Paw, K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities, Bull. Am. Meteorol. Soc., 82, 2415-2434, https://doi.org/10.1175/1520-0477(2001)0822415:FANTTS2.3.CO;2, 2001.
8. Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623-643, https://doi.org/10.1175/2008JHM1068.1, 2009.
9. Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., Rodenbeck, C., Arain, M. A., Baldocchi, D., Bonan, G. B., Bondeau, A., Cescatti, A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson, K. W., Roupsard, O., Veenendaal, E., Viovy, N.,Williams, C.,Woodward, F. I., and Papale, D.: Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate, Science, 329, 834-838, https://doi.org/10.1126/science.1184984, 2010.
10. Boyer, J. S., Byrne, P., Cassman, K. G., Cooper, M., Delmer, D., Greene, T., Gruis, F., Habben, J., Hausmann, N., Kenny, N., Lafitte, R., Paszkiewicz, S., Porter, D., Schlegel, A., Schussler, J., Setter, T., Shanahan, J., Sharp, R. E., Vyn, T. J., Warner, D., and Gaffney, J.: The U.S. drought of 2012 in perspective: A call to action, Global Food Security, 2, 139-143, https://doi.org/10.1016/j.gfs.2013.08.002, 2013
11. Damour, G., Simonneau, T., Cochard, H., and Urban, L.: An overview of models of stomatal conductance at the leaf level, Plant. Cell Environ., 33, 1419-1438, https://doi.org/10.1111/j.1365-3040.2010.02181.x, 2010.
12. da Rocha, H. R., Manzi, A. O., Cabral, O. M., Miller, S. D., Goulden, M. L., Saleska, S. R., R.-Coupe, N., Wofsy, S. C., Borma, L. S., Artaxo, P., Vourlitis, G., Nogueira, J. S., Cardoso, F. L., Nobre, A. D., Kruijt, B., Freitas, H. C., von Randow, C., Aguiar, R. G., and Maia, J. F.: Patterns of water and heat flux across a biome gradient from tropical forest to savanna in Brazil, J. Geophys. Res., 114, G00B12, https://doi.org/10.1029/2007JG000640, 2009.
13. DeLucia, E. H. and Heckathorn, S. A.: The effect of soil drought on water-use efficiency in a contrasting Great Basin desert and Sierran montane species, Plant, Cell Environ., 12, 935-940, https://doi.org/10.1111/j.1365-3040.1989.tb01973.x, 1989.
14. Dewar, R. C.: The Ball-Berry-Leuning and Tardieu-Davies stomatal models: synthesis and extension within a spatially aggregated picture of guard cell function, Plant Cell Environ., 25, 1383-1398, https://doi.org/10.1046/j.1365-3040.2002.00909.x, 2002.
15. D'Odorico, P., Gonsamo, A., Pinty, B., Gobron, N., Coops, N., Mendez, E., and Schaepman, M. E.: Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe, Remote Sens. Environ., 142, 141-154, https://doi.org/10.1016/j.rse.2013.12.005, 2014.
16. Dole, R., Hoerling, M., Perlwitz, J., Eischeid, J., Pegion, P., Zhang, T., Quan, X.-W., Xu, T., and Murray, D.: Was there a basis for anticipating the 2010 Russian heat wave?, Geophys. Res. Lett., 38, L06702, https://doi.org/10.1029/2010GL046582, 2011.
17. Dorigo, W.: ESA CCI Soil Moisture for improved Earth system understanding: state-of-the art and future directions, Remote Sens. Environ., https://doi.org/10.1016/j.rse.2017.07.001, 2017.
18. Drusch, M., Moreno, J., Del Bello, U., Franco, R., Goulas, Y., Huth, A., Kraft, S., Middleton, E. M., Miglietta, F., Mohammed, G., Nedbal, L., Rascher, U., Schuttemeyer, D., and Verhoef, W.: The FLuorescence EXplorer Mission Concept-ESA's Earth Explorer 8, IEEE Trans. Geosci. Remote Sens. 1-12, https://doi.org/10.1109/TGRS.2016.2621820, 2016.
19. Fisher, J. B., Tu, K. P., and Baldocchi, D. D.: Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901-919, https://doi.org/10.1016/j.rse.2007.06.025, 2008.
20. Flexas, J., Escalona, J. M., Evain, S., Gulias, J., Moya, I., Osmond, C. B., and Medrano, H.: Steady-state chlorophyll fluorescence (Fs) measurements as a tool to follow varia-tions of net CO2 assimilation and stomatal conductance during water-stress in C3 plants, Physiol. Plant., 114, 231-240, https://doi.org/10.1034/j.1399-3054.2002.1140209.x, 2002.
21. Foken, T., Mauder, M., Liebethal, C., Wimmer, F., Beyrich, F., Leps, J.-P., Raasch, S., DeBruin, H. A. R., Meijninger, W. M. L., and Bange, J.: Energy balance closure for the LITFASS-2003 experiment, Theor. Appl. Climatol., 101, 149-160, https://doi.org/10.1007/s00704-009-0216-8, 2010.
22. Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
23. Frankenberg, C., O'Dell, C., Guanter, L., and McDuffie, J.: Remote sensing of near-infrared chlorophyll fluorescence from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO2 retrievals, Atmos. Meas. Tech., 5, 2081-2094, https://doi.org/10.5194/amt-5-2081-2012, 2012.
24. Frankenberg, C., O'Dell, C., Berry, J., Guanter, L., Joiner, J., Köhler, P., Pollock, R., and Taylor, T. E.: Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2, Remote Sens. Environ., 147, 1-12, https://doi.org/10.1016/j.rse.2014.02.007, 2014.
25. Gebremichael, M., Krajewski, W. F., Morrissey, M. L., Huffman, G. J., Adler, R. F., Gebremichael, M., Krajewski, W. F., Morrissey, M. L., Huffman, G. J., and Adler, R. F.: A Detailed Evaluation of GPCP 1 Daily Rainfall Estimates over the Mississippi River Basin, J. Appl. Meteorol., 44, 665-681, https://doi.org/10.1175/JAM2233.1, 2005.
26. Govindjee, Downton, W. J. S., Fork, D. C., and Armond, P. A.: Chlorophyll A fluorescence transient as an indicator of water potential of leaves, Plant Sci. Lett., 20, 191-194, https://doi.org/10.1016/0304-4211(81)90261-3, 1981.
27. Gruber, A., Su, C.-H., Zwieback, S., Crow, W., Dorigo, W., and Wagner, W.: Recent advances in (soil moisture) triple collocation analysis, Int. J. Appl. Earth Obs. Geoinf., 45, 200-211, https://doi.org/10.1016/j.jag.2015.09.002, 2016.
28. Guanter, L., Frankenberg, C., Dudhia, A., Lewis, P. E., Gómez-Dans, J., Kuze, A., Suto, H., and Grainger, R. G.: Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements, Remote Sens. Environ., 121, 236-251, https://doi.org/10.1016/j.rse.2012.02.006, 2012.
29. Guanter, L., Zhang, Y., Jung, M., Joiner, J., Voigt, M., Berry, J. A., Frankenberg, C., Huete, A. R., Zarco-Tejada, P., Lee, J.-E., Moran, M. S., Ponce-Campos, G., Beer, C., Camps-Valls, G., Buchmann, N., Gianelle, D., Klumpp, K., Cescatti, A., Baker, J. M., and Griffis, T. J.: Global and timeresolved monitoring of crop photosynthesis with chlorophyll fluorescence, P. Natl. Acad. Sci. USA, 111, E1327-E1333, https://doi.org/10.1073/pnas.1320008111, 2014.
30. Guillod, B. P., Orlowsky, B., Miralles, D., Teuling, A. J., Blanken, P. D., Buchmann, N., Ciais, P., Ek, M., Findell, K. L., Gentine, P., Lintner, B. R., Scott, R. L., Van den Hurk, B., and I. Seneviratne, S.: Land-surface controls on afternoon precipitation diagnosed from observational data: uncertainties and confounding factors, Atmos. Chem. Phys., 14, 8343-8367, https://doi.org/10.5194/acp-14-8343-2014, 2014.
31. Guillod, B. P., Orlowsky, B., Miralles, D. G., Teuling, A. J., and Seneviratne, S. I.: Reconciling spatial and temporal soil moisture effects on afternoon rainfall, Nat. Commun., 6, 6443, https://doi.org/10.1038/ncomms7443, 2015.
32. Hain, C. R., Crow, W. T., Mecikalski, J. R., Anderson, M. C., and Holmes, T.: An intercomparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling, J. Geophys. Res., 116, D15107, https://doi.org/10.1029/2011JD015633, 2011.
33. Havaux, M. and Lannoye, R.: Chlorophyll fluorescence induction: A sensitive indicator of water stress in maize plants, Irrig. Sci., 4, 147-151, https://doi.org/10.1007/BF00273382, 1983.
34. Huffman, G. J., Adler, R. F., Morrissey, M. M., Bolvin, D. T., Curtis, S., Joyce, R., McGavock, B., Susskind, J., Huffman, G. J., Adler, R. F., Morrissey, M. M., Bolvin, D. T., Curtis, S., Joyce, R., McGavock, B., and Susskind, J.: Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations, J. Hydrometeorol., 2, 36-50, https://doi.org/10.1175/1525-7541(2001)0020036:GPAODD2.0.CO;2, 2001.
35. Jasechko, S., Sharp, Z. D., Gibson, J. J., Birks, S. J., Yi, Y., and Fawcett, P. J.: Terrestrial water fluxes dominated by transpiration, Nature, 496, 347-350, https://doi.org/10.1038/nature11983, 2013.
36. Jeong, S.-J., Schimel, D., Frankenberg, C., Drewry, D. T., Fisher, J. B., Verma, M., Berry, J. A., Lee, J.-E., and Joiner, J.: Application of satellite solar-induced chlorophyll fluorescence to understanding large-scale variations in vegetation phenology and function over northern high latitude forests, Remote Sens. Environ., 190, 178-187, https://doi.org/10.1016/j.rse.2016.11.021, 2017.
37. Jiang, C. and Ryu, Y.: Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS), Remote Sens. Environ., 186, 528-547, https://doi.org/10.1016/j.rse.2016.08.030, 2016.
38. Jiménez, C., Prigent, C., and Aires, F.: Toward an estimation of global land surface heat fluxes from multisatellite observations, J. Geophys. Res., 114, D06305, https://doi.org/10.1029/2008JD011392, 2009.
39. Jiménez, C., Prigent, C., Mueller, B., Seneviratne, S. I., Mc-Cabe, M. F., Wood, E. F., Rossow, W. B., Balsamo, G., Betts, A. K., Dirmeyer, P. A., Fisher, J. B., Jung, M., Kanamitsu, M., Reichle, R. H., Reichstein, M., Rodell, M., Sheffield, J., Tu, K., and Wang, K.: Global intercomparison of 12 land surface heat flux estimates, J. Geophys. Res., 116, D02102, https://doi.org/10.1029/2010JD014545, 2011.
40. Jiménez, C., Clark, D. B., Kolassa, J., Aires, F., and Prigent, C.: A joint analysis of modeled soil moisture fields and satellite observations, J. Geophys. Res.-Atmos., 118, 6771-6782, https://doi.org/10.1002/jgrd.50430, 2013.
41. Joiner, J., Guanter, L., Lindstrot, R., Voigt, M., Vasilkov, A. P., Middleton, E. M., Huemmrich, K. F., Yoshida, Y., and Frankenberg, C.: Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2, Atmos. Meas. Tech., 6, 2803-2823, https://doi.org/10.5194/amt-6-2803-2013, 2013.
42. Joiner, J., Yoshida, Y., Vasilkov, A. P., Schaefer, K., Jung, M., Guanter, L., Zhang, Y., Garrity, S., Middleton, E. M., Huemmrich, K. F., Gu, L., and Belelli Marchesini, L.: The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange, Remote Sens. Environ., 152, 375-391, https://doi.org/10.1016/j.rse.2014.06.022, 2014.
43. Joiner, J., Yoshida, Y., Guanter, L., and Middleton, E. M.: New methods for the retrieval of chlorophyll red fluorescence from hyperspectral satellite instruments: simulations and application to GOME-2 and SCIAMACHY, Atmos. Meas. Tech., 9, 3939-3967, https://doi.org/10.5194/amt-9-3939-2016, 2016.
44. Joshi, M. K., Rai, A., and Pandey, A. C.: Validation of TMPA and GPCP 1DD against the ground truth rain-gauge data for Indian region, Int. J. Climatol., 33, 2633-2648, https://doi.org/10.1002/joc.3612, 2012.
45. Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model, Biogeosciences, 6, 2001-2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
46. Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J., Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., de Jeu, R., Dolman, A. J., Eugster, W., Gerten, D., Gianelle, D., Gobron, N., Heinke, J., Kimball, J., Law, B. E., Montagnani, L., Mu, Q., Mueller, B., Oleson, K., Papale, D., Richardson, A. D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N., Weber, U., Williams, C., Wood, E., Zaehle, S., and Zhang, K.: Recent decline in the global land evapotranspiration trend due to limited moisture supply, Nature, 467, 951-954, https://doi.org/10.1038/nature09396, 2010.
47. Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D., Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D., Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A., Merbold, L., Montagnani, L., Moors, E. J., Papale, D., Sottocornola, M., Vaccari, F., and Williams, C.: Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations, J. Geophys. Res., 116, G00J07, https://doi.org/10.1029/2010JG001566, 2011.
48. Kato, S., Loeb, N. G., Rose, F. G., Doelling, D. R., Rutan, D. A., Caldwell, T. E., Yu, L., and Weller, R. A.: Surface Irradiances Consistent with CERES-Derived Top-of-Atmosphere Shortwave and Longwave Irradiances, J. Clim., 26, 2719-2740, https://doi.org/10.1175/JCLI-D-12-00436.1, 2013.
49. Kolassa, J., Aires, F., Polcher, J., Prigent, C., Jimenez, C., and Pereira, J. M.: Soil moisture retrieval from multiinstrument observations: Information content analysis and retrieval methodology, J. Geophys. Res.-Atmos., 118, 4847-4859, https://doi.org/10.1029/2012JD018150, 2013.
50. Kolassa, J., Gentine, P., Prigent, C., and Aires, F.: Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy, Part 1: Satellite data analysis, Remote Sens. Environ., 173, 1-14, https://doi.org/10.1016/j.rse.2015.11.011, 2016.
51. Krause, G. H. and Weis, E.: Chlorophyll Fluorescence and Photosynthesis: The Basics, Annu. Rev. Plant Physiol. Plant Mol. Biol., 42, 313-349, https://doi.org/10.1146/annurev.pp.42.060191.001525, 1991.
52. Landerer, F. W. and Swenson, S. C.: Accuracy of scaled GRACE terrestrial water storage estimates, Water Resour. Res., 48, W04531, https://doi.org/10.1029/2011WR011453, 2012.
53. Lau, W. K. M. and Kim, K.-M.: The 2010 Pakistan Flood and Russian Heat Wave: Teleconnection of Hydrometeorological Extremes, J. Hydrometeorol., 13, 392-403, https://doi.org/10.1175/JHM-D-11-016.1, 2012.
54. Lee, J.-E., Frankenberg, C., van der Tol, C., Berry, J. A., Guanter, L., Boyce, C. K., Fisher, J. B., Morrow, E., Worden, J. R., Asefi, S., Badgley, G., and Saatchi, S.: Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence, P. R. Soc. B, 280, 20130171-20130171, https://doi.org/10.1098/rspb.2013.0171, 2013.
55. Lee, J.-E., Berry, J. A., van der Tol, C., Yang, X., Guanter, L., Damm, A., Baker, I., and Frankenberg, C.: Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4, Glob. Change Biol., 21, 3469-3477, https://doi.org/10.1111/gcb.12948, 2015.
56. Lei, F., Crow, W., Shen, H., Parinussa, R., and Holmes, T.: The Impact of Local Acquisition Time on the Accuracy of Microwave Surface Soil Moisture Retrievals over the Contiguous United States, Remote Sens., 7, 13448-13465, https://doi.org/10.3390/rs71013448, 2015.
57. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425-436, https://doi.org/10.5194/hess-15-425-2011, 2011.
58. Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., de Jeu, R. A. M., Wagner, W., McCabe, M. F., Evans, J. P., and van Dijk, A. I. J. M.: Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sens. Environ., 123, 280-297, https://doi.org/10.1016/j.rse.2012.03.014, 2012.
59. Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato, S., Manalo-Smith, N., andWong, T.: Toward Optimal Closure of the Earth's Top-of-Atmosphere Radiation Budget, J. Clim., 22, 748-766, https://doi.org/10.1175/2008JCLI2637.1, 2009.
60. Luo, L. and Zhang, Y.: Did we see the 2011 summer heat wave coming?, Geophys. Res. Lett., 39, L09708, https://doi.org/10.1029/2012GL051383, 2012.
61. Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Kangwa, M., Smolander, T., and Derksen, C.: Global snow monitoring for climate research: Algorithm theoretical basis document (ATBD)-SWE Algorithm, Version/Revision 1.0/02, 2013.
62. Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903-1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
63. McColl, K. A., Vogelzang, J., Konings, A. G., Entekhabi, D., Piles, M., and Stoffelen, A.: Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target, Geophys. Res. Lett., 41, GL061322, https://doi.org/10.1002/2014GL061322, 2014.
64. McColl, K. A., Roy, A., Derksen, C., Konings, A. G., Alemohammed, S. H., and Entekhabi, D.: Triple collocation for binary and categorical variables: Application to validating landscape freeze/thaw retrievals, Remote Sens. Environ., 176, 31-42, https://doi.org/10.1016/j.rse.2016.01.010, 2016.
65. McFarlane, J. C., Watson, R. D., Theisen, A. F., Jackson, R. D., Ehrler, W. L., Pinter, P. J., Idso, S. B., and Reginato, R. J.: Plant stress detection by remote measurement of fluorescence, Appl. Opt., 19, 3287, https://doi.org/10.1364/AO.19.003287, 1980.
66. McPhee, J., Margulis, S. A., McPhee, J., and Margulis, S. A.: Validation and Error Characterization of the GPCP-1DD Precipitation Product over the Contiguous United States, J. Hydrometeorol., 6, 441-459, https://doi.org/10.1175/JHM429.1, 2005.
67. Michel, D., Jiménez, C., Miralles, D. G., Jung, M., Hirschi, M., Ershadi, A., Martens, B., McCabe, M. F., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms, Hydrol. Earth Syst. Sci., 20, 803-822, https://doi.org/10.5194/hess-20-803-2016, 2016.
68. Miralles, D. G., Crow, W. T., and Cosh, M. H.: Estimating Spatial Sampling Errors in Coarse-Scale Soil Moisture Estimates Derived from Point-Scale Observations, J. Hydrometeorol., 11, 1423-1429, https://doi.org/10.1175/2010JHM1285.1, 2010.
69. Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453-469, https://doi.org/10.5194/hess-15-453-2011, 2011a.
70. Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman, A. J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrol. Earth Syst. Sci., 15, 967-981, https://doi.org/10.5194/hess-15-967-2011, 2011b.
71. Miralles, D. G., van den Berg, M. J., Gash, J. H., Parinussa, R. M., de Jeu, R. A. M., Beck, H. E., Holmes, T. R. H., Jiménez, C., Verhoest, N. E. C., Dorigo, W. A., Teuling, A. J., and Johannes Dolman, A.: El Niño-La Niña cycle and recent trends in continental evaporation, Nature Climate Change, 4, 122-126, https://doi.org/10.1038/nclimate2068, 2014a.
72. Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., and Vilà-Guerau de Arellano, J.: Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation, Nat. Geosci., 7, 345-349, https://doi.org/10.1038/ngeo2141, 2014b.
73. Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., Mc-Cabe, M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q., Seneviratne, S. I.,Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project-Part 2: Evaluation of global terrestrial evaporation data sets, Hydrol. Earth Syst. Sci., 20, 823-842, https://doi.org/10.5194/hess-20-823-2016, 2016.
74. Monteith, J. L. and Moss, C. J.: Climate and the Efficiency of Crop Production in Britain, Philos. Trans. R. Soc. B Biol. Sci., 281, 277-294, https://doi.org/10.1098/rstb.1977.0140, 1977
75. Morton, D. C., Nagol, J., Carabajal, C. C., Rosette, J., Palace, M., Cook, B. D., Vermote, E. F., Harding, D. J., and North, P. R. J.: Amazon forests maintain consistent canopy structure and greenness during the dry season, Nature, 506, 221-224, https://doi.org/10.1038/nature13006, 2014.
76. Morton, D. C., Rubio, J., Cook, B. D., Gastellu-Etchegorry, J.-P., Longo, M., Choi, H., Hunter, M., and Keller, M.: Amazon forest structure generates diurnal and seasonal variability in light utilization, Biogeosciences, 13, 2195-2206, https://doi.org/10.5194/bg-13-2195-2016, 2016.
77. Mu, Q., Heinsch, F. A., Zhao, M., and Running, S.W.: Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519-536, https://doi.org/10.1016/j.rse.2007.04.015, 2007.
78. Mueller, B., Seneviratne, S. I., Jimenez, C., Corti, T., Hirschi, M., Balsamo, G., Ciais, P., Dirmeyer, P., Fisher, J. B., Guo, Z., Jung, M., Maignan, F., McCabe, M. F., Reichle, R., Reichstein, M., Rodell, M., Sheffield, J., Teuling, A. J., Wang, K., Wood, E. F., and Zhang, Y.: Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations, Geophys. Res. Lett., 38, L06402, https://doi.org/10.1029/2010GL046230, 2011.
79. Munier, S. and Aires, F.: A new global method of satellite dataset merging and quality characterization constrained by the terrestrial water cycle budget, Remote Sens. Environ., in review, 2017.
80. Munier, S., Aires, F., Schlaffer, S., Prigent, C., Papa, F., Maisongrande, P., and Pan, M.: Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model, J. Geophys. Res.-Atmos., 119, 12100-12116, https://doi.org/10.1002/2014JD021953, 2014.
81. NASA LP DAAC: Land Cover Type Yearly L3, MCD12C1, V051, 2016.
82. Pan, X., Liu, Y., and Fan, X.: Comparative Assessment of Satellite-Retrieved Surface Net Radiation: An Examination on CERES and SRB Datasets in China, Remote Sens., 7, 4899-4918, https://doi.org/10.3390/rs70404899, 2015.
83. Parinussa, R. M., Meesters, A. G. C. A., Liu, Y. Y., Dorigo, W., Wagner, W., and de Jeu, R. A. M.: Error Estimates for Near-Real-Time Satellite Soil Moisture as Derived From the Land Parameter Retrieval Model, IEEE Geosci. Remote Sens. Lett., 8, 779-783, https://doi.org/10.1109/LGRS.2011.2114872, 2011.
84. Pastorello, G., Agarwal, D., Papale, D., Samak, T., Trotta, C., Ribeca, A., Poindexter, C., Faybishenko, B., Gunter, D., Hollowgrass, R., and Canfora, E.: Observational Data Patterns for Time Series Data Quality Assessment, in 2014 IEEE 10th International Conference on e-Science, 271-278, 2014.
85. Pulliainen, J.: Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and groundbased observations, Remote Sens. Environ., 101, 257-269, https://doi.org/10.1016/j.rse.2006.01.002, 2006.
86. Restrepo-Coupe, N., da Rocha, H. R., Hutyra, L. R., da Araujo, A. C., Borma, L. S., Christoffersen, B., Cabral, O. M. R., de Camargo, P. B., Cardoso, F. L., da Costa, A. C. L., Fitzjarrald, D. R., Goulden, M. L., Kruijt, B., Maia, J. M. F., Malhi, Y. S., Manzi, A. O., Miller, S. D., Nobre, A. D., von Randow, C., Sá, L. D. A., Sakai, R. K., Tota, J., Wofsy, S. C., Zanchi, F. B., and Saleska, S. R.: What drives the seasonality of photosynthesis across the Amazon basin? A cross-site analysis of eddy flux tower measurements from the Brasil flux network, Agr. Forest Meteorol., 182/183, 128-144, https://doi.org/10.1016/j.agrformet.2013.04.031, 2013.
87. Rodriìguez-Fernández, N. J., Aires, F., Richaume, P., Kerr, Y. H., Prigent, C., Kolassa, J., Cabot, F., Jimenez, C., Mahmoodi, A., and Drusch, M.: Soil Moisture Retrieval Using Neural Networks: Application to SMOS, IEEE Trans. Geosci. Remote Sens., 53, 5991-6007, https://doi.org/10.1109/TGRS.2015.2430845, 2015.
88. Rubel, F., Skomorowski, P., and Rudolf, B.: Verification scores for the operational GPCP-1DD product over the European Alps, Meteorol. Z., 11, 367-370, https://doi.org/10.1127/0941-2948/2002/0011-0367, 2002.
89. Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., and Hashimoto, H.: A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production, Bioscience, 54, 547, https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2, 2004.
90. Saleska, S. R., Wu, J., Guan, K., Araujo, A. C., Huete, A., Nobre, A. D., and Restrepo-Coupe, N.: Dry-season greening of Amazon forests, Nature, 531, E4-E5, https://doi.org/10.1038/nature16457, 2016.
91. Schimel, D., Pavlick, R., Fisher, J. B., Asner, G. P., Saatchi, S., Townsend, P., Miller, C., Frankenberg, C., Hibbard, K., and Cox, P.: Observing terrestrial ecosystems and the carbon cycle from space, Glob. Change Biol., 21, 1762-1776, https://doi.org/10.1111/gcb.12822, 2015.
92. Stoffelen, A.: Toward the true near-surface wind speed: Error modeling and calibration using triple collocation, J. Geophys. Res., 103, 7755, https://doi.org/10.1029/97JC03180, 1998.
93. Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., Miskus, D., Stephens, S., Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., Miskus, D., and Stephens, S.: The Drought Monitor, Bull. Am. Meteorol. Soc., 83, 1181-1190, https://doi.org/10.1175/1520-0477(2002)0831181:TDM2.3.CO;2, 2002.
94. Swenson, S. and Wahr, J.: Post-processing removal of correlated errors in GRACE data, Geophys. Res. Lett., 33, L08402, https://doi.org/10.1029/2005GL025285, 2006
95. Toivonen, P. and Vidaver, W.: Variable Chlorophyll a Fluorescence and CO2 Uptake in Water-Stressed White Spruce Seedlings, Plant Physiol., 86, 744-748, https://doi.org/10.1104/pp.86.3.744, 1988.
96. Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 4291-4313, https://doi.org/10.5194/bg-13-4291-2016, 2016.
97. USDA: Crop Production 2012 Summary, http://usda. mannlib.cornell.edu/usda/nass/CropProdSu/2010s/2013/ CropProdSu-01-11-2013.pdf, 2013.
98. van der Tol, C., Verhoef, W., and Rosema, A.: A model for chlorophyll fluorescence and photosynthesis at leaf scale, Agr. Forest Meteorol., 149, 96-105, https://doi.org/10.1016/j.agrformet.2008.07.007, 2009.
99. van Kooten, O. and Snel, J. F. H.: The use of chlorophyll fluorescence nomenclature in plant stress physiology, Photosynth. Res., 25, 147-150, https://doi.org/10.1007/BF00033156, 1990.
100. Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E., and Ertl, M.: Fusion of Active and Passive Microwave Observations To Create an Essential Climate Variable Data Record on Soil Moisture, ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., I-7 (September) 315-321, https://doi.org/10.5194/isprsannals-I-7-315-2012, 2012.
101. Walther, S., Voigt, M., Thum, T., Gonsamo, A., Zhang, Y., Koehler, P., Jung, M., Varlagin, A., and Guanter, L.: Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests, Glob. Change Biol., 22, 2979-2996, https://doi.org/10.1111/gcb.13200, 2016.
102. Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee, R. B., Louis Smith, G., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment, Bull. Am. Meteorol. Soc., 77, 853-868, https://doi.org/10.1175/1520-0477(1996)0770853:CATERE2.0.CO;2, 1996.
103. Xu, L., Saatchi, S. S., Yang, Y., Myneni, R. B., Frankenberg, C., Chowdhury, D., and Bi, J.: Satellite observation of tropical forest seasonality: spatial patterns of carbon exchange in Amazonia, Environ. Res. Lett., 10, 84005, https://doi.org/10.1088/1748-9326/10/8/084005, 2015.
104. Zhang, Y., Guanter, L., Berry, J. A., van der Tol, C., Yang, X., Tang, J., and Zhang, F.: Model-based analysis of the relationship between sun-induced chlorophyll fluorescence and gross primary production for remote sensing applications, Remote Sens. Environ., 187, 145-155, https://doi.org/10.1016/j.rse.2016.10.016, 2016a.
105. Zhang, Y., Peña-Arancibia, J. L., McVicar, T. R., Chiew, F. H. S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y. Y., Miralles, D. G., and Pan, M.: Multi-decadal trends in global terrestrial evapotranspiration and its components, Sci. Rep., 6, 19124, https://doi.org/10.1038/srep19124, 2016b.
106. Zhao, M. and Running, S. W.: Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009, Science, 329, 940-943, https://doi.org/10.1126/science.1192666, 2010.
107. Zhao, M., Heinsch, F. A., Nemani, R. R., and Running, S. W.: Improvements of the MODIS terrestrial gross and net primary production global data set, Remote Sens. Environ., 95, 164-176, https://doi.org/10.1016/j.rse.2004.12.011, 2005.