Methods for assessment of models
26 Jan 2016
Methods for assessment of models | 26 Jan 2016
The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data
M. F. McCabe et al.
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Short summary
StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction
Aurélien Gallice, Mathias Bavay, Tristan Brauchli, Francesco Comola, Michael Lehning, and Hendrik Huwald
Geosci. Model Dev., 9, 4491–4519, https://doi.org/10.5194/gmd-9-4491-2016,https://doi.org/10.5194/gmd-9-4491-2016, 2016
Short summary
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak,
J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind,
J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology
project (GPCP) monthly precipitation analysis (1979–present), J.
Hydrometeorol., 4, 1147–1167, 2003.
Allen, R. G.: Using the FAO-56 dual crop coefficient method over an irrigated
region as part of an evapotranspiration intercomparison study, J. Hydrol.,
229, 27–41, 2000.
Armstrong, R. L., Brodzik, M. J., Knowles, K., and Savoie, M.: Global monthly
EASE-Grid snow water equivalent climatology, National Snow and Ice Data
Center, Digital media, Boulder, CO, USA, 2005.
Badgley, G., Fisher, J. B., Jiménez, C., Tu, K. P., and Vinukollu, R.: On
uncertainty in global terrestrial evapotranspiration estimates from choice of
input forcing datasets, J. Hydrometeorol., 16, 1449–1455,
https://doi.org/10.1175/JHM-D-14-0040.1, 2015.
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, B. Am. Meteorol. Soc., 82, 2415–2434, 2001.
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., and Holtslag, A. A. M.: A
remote sensing surface energy balance algorithm for land (SEBAL). 1.
Formulation, J. Hydrol., 212–213, 198–212, 1998.
Bos, M. G., Kselik, R. A. L., Allen, R. G., and Molden, D. J.: Water
Requirements for Irrigation and the Environment, Springer, Dordrecht, the
Netherlands, 2008.
Bouchet, R. J.: Evapotranspiration réelle et potentielle, signification
climatique. General Assembly Berkeley, International Association for
Hydrological Sciences, Gentbrugge, Belgium, 62, 134–142, 1963.
Brutsaert, W.: Evaporation Into the Atmosphere: theory, history, and
applications, Reidel Publishing, Dordrecht, the Netherlands, 1982.
Brutsaert, W.: Hydrology : An Introduction, Cambridge University Press,
Cambridge, UK, 2005.
Carvalhais, N., Reichstein, M., Collatz, G. J., Mahecha, M. D., Migliavacca,
M., Neigh, C. S. R., Tomelleri, E., Benali, A. A., Papale, D., and Seixas,
J.: Deciphering the components of regional net ecosystem fluxes following a
bottom-up approach for the Iberian Peninsula, Biogeosciences, 7, 3707–3729,
https://doi.org/10.5194/bg-7-3707-2010, 2010.
Chahine, M. T.: The hydrological cycle and its influence on climate, Nature,
359, 373–380, 1992.
Chen, X., Su, Z., Ma, Y., Yang, K., Wen, J., and Zhang, Y.: An Improvement of
Roughness Height Parameterization of the Surface Energy Balance System (SEBS)
over the Tibetan Plateau, J. Appl. Meteorol. Clim., 52, 607–622, 2012.
Chiti, T., Papale, D., Smith, P., Dalmonech, D., Matteucci, G., Yeluripati,
J., Rodeghiero, M., and Valentini, R.: Predicting changes in soil organic
carbon in mediterranean and alpine forests during the Kyoto Protocol
commitment periods using the CENTURY model, Soil Use Manage., 26, 475–484,
2010.
Coccia, G., Siemann, A., Pan, M., and Wood, E. F.: Creating consistent
datasets by combining remotely-sensed data and land surface model estimates
through Bayesian uncertainty post-processing: the case of Land Surface
Temperature from HIRS, Remote Sens. Environ., 170, 290–305,
https://doi.org/10.1016/j.rse.2015.09.010, 2015.
Curtis, P. S., Hanson, P. J., Bolstad, P., Barford, C., Randolph, J. C.,
Schmid, H. P., and Wilson, K. B.: Biometric and eddy-covariance based
estimates of annual carbon storage in five eastern North American deciduous
forests, Agr. Forest Meteorol., 113, 3–19, 2002.
Delpierre, N., Soudani, K., Francois, C., Köstner, B., Pontailler, J. Y.,
Nikinmaa, E., Misson, L., Aubinet, M., Bernhofer, C., and Granier, A.:
Exceptional carbon uptake in European forests during the warm spring of 2007:
a data–model analysis, Glob. Change Biol., 15, 1455–1474, 2009.
Don, A., Rebmann, C., Kolle, O., Scherer-Lorenzen, M., and Schulze, E. D.:
Impact of afforestation-associated management changes on the carbon balance
of grassland, Glob. Change Biol., 15, 1990–2002, 2009.
Douville, H., Ribes, A., Decharme, B., Alkama, R., and Sheffield, J.:
Anthropogenic influence on multidecadal changes in reconstructed global
evapotranspiration, Nature Clim. Change, 3, 59–62, 2013.
Dragoni, D., Schmid, H. P., Wayson, C. A., Potter, H., Grimmond, C. S. B.,
and Randolph, J. C.: Evidence of increased net ecosystem productivity
associated with a longer vegetated season in a deciduous forest in
south-central Indiana, USA, Glob. Change Biol., 17, 886–897, 2011.
Ershadi, A., McCabe, M. F., Evans, J. P., Mariethoz, G., and Kavetski, D.: A
Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty
in meteorological forcing to improve model prediction, Water Resour. Res.,
49, 2343–2358, 2013.
Ershadi, A., McCabe, M. F., Evans, J. P., Chaney, N. W., and Wood, E. F.:
Multi-site evaluation of terrestrial evaporation models using FLUXNET data,
Agr. Forest Meteorol., 187, 46–61, 2014.
Ershadi, A., McCabe, M. F., Evans, J. P., and Wood, E. F.: Impact of model
structure and parameterization on Penman–Monteith type evaporation models,
J. Hydrol., 525, 521–535, 2015.
Famiglietti, J. S., Lo, M., Ho, S. L., Bethune, J., Anderson, K. J., Syed, T.
H., Swenson, S. C., de Linage, C. R., and Rodell, M.: Satellites measure
recent rates of groundwater depletion in California's Central Valley,
Geophys. Res. Lett., 38, L03403, https://doi.org/10.1029/2010GL046442, 2011.
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, 2008.
Flanagan, L. B., Cai, T., Black, T. A., Barr, A. G., McCaughey, J. H., and
Margolis, H. A.: Measuring and modeling ecosystem photosynthesis and the
carbon isotope composition of ecosystem-respired CO
2 in three boreal
coniferous forests, Agr. Forest Meteorol., 153, 165–176, 2012.
Fu, D., Chen, B., Zhang, H., Wang, J., Black, T. A., Amiro, B. D., Bohrer,
G., Bolstad, P., Coulter, R., and Rahman, A. F.: Estimating landscape net
ecosystem exchange at high spatial–temporal resolution based on Landsat
data, an improved upscaling model framework, and eddy covariance flux
measurements, Remote Sens. Environ., 141, 90–104, 2014.
Gamon, J. A., Coburn, C., Flanagan, L. B., Huemmrich, K. F., Kiddle, C.,
Sanchez-Azofeifa, G. A., Thayer, D. R., Vescovo, L., Gianelle, D., and Sims,
D. A.: SpecNet revisited: bridging flux and remote sensing communities, Can.
J. Remote Sens., 36, S376–S390, 2010.
Gash, J. H.: An analytical model of rainfall interception by forests
quarterly, Q. J. Roy. Meteor. Soc., 105, 43–45, 1979.
Gilmanov, T., Soussana, J., Aires, L., Allard, V., Ammann, C., Balzarolo, M.,
Barcza, Z., Bernhofer, C., Campbell, C., Cernusca, A., Cescatti, A.,
Clifton-Brown, J., Dirks, B., Dore, S., Eugster, W., Fuhrer, J., Gimeno, C.,
Gruenwald, T., Haszpra, L., Hensen, A., Ibrom, A., Jacobs, A., Jones, M.,
Lanigan, G., Laurila, T., Lohila, A., Manca, G., Marcolla, B., Nagy, Z.,
Pilegaard, K., Pinter, K., Pio, C., Raschi, A., Rogiers, N., Sanz, M.,
Stefani, P., Sutton, M., Tuba, Z., Valentini, R., Williams, M., and
Wohlfahrt, G.: Partitioning European grassland net ecosystem CO
2
exchange into gross primary productivity and ecosystem respiration using
light response function analysis, Agr. Ecosyst. Environ., 121, 93–120, 2007.
Gioli, B., Miglietta, F., De Martino, B., Hutjes, R. W. A., Dolman, H. A. J.,
Lindroth, A., Schumacher, M., Sanz, M. J., Manca, G., and Peressotti, A.:
Comparison between tower and aircraft-based eddy covariance fluxes in five
European regions, Agr. Forest Meteorol., 127, 1–16, 2004.
Göckede, M., Foken, T., Aubinet, M., Aurela, M., Banza, J., Bernhofer,
C., Bonnefond, J. M., Brunet, Y., Carrara, A., Clement, R., Dellwik, E.,
Elbers, J., Eugster, W., Fuhrer, J., Granier, A., Grünwald, T., Heinesch,
B., Janssens, I. A., Knohl, A., Koeble, R., Laurila, T., Longdoz, B., Manca,
G., Marek, M., Markkanen, T., Mateus, J., Matteucci, G., Mauder, M.,
Migliavacca, M., Minerbi, S., Moncrieff, J., Montagnani, L., Moors, E.,
Ourcival, J.-M., Papale, D., Pereira, J., Pilegaard, K., Pita, G., Rambal,
S., Rebmann, C., Rodrigues, A., Rotenberg, E., Sanz, M. J., Sedlak, P.,
Seufert, G., Siebicke, L., Soussana, J. F., Valentini, R., Vesala, T.,
Verbeeck, H., and Yakir, D.: Quality control of CarboEurope flux data –
Part 1: Coupling footprint analyses with flux data quality assessment to
evaluate sites in forest ecosystems, Biogeosciences, 5, 433–450,
https://doi.org/10.5194/bg-5-433-2008, 2008.
Granger, R. J.: Satellite-derived estimates of evapotranspiration in the
Gediz basin, J. Hydrol., 229, 70–76, 2000.
Greve, P., Orlowsky, B., Mueller, B., Sheffield, J., Reichstein, M., and
Seneviratne, S. I.: Global assessment of trends in wetting and drying over
land, Nat. Geosci., 7, 716–721, 2014.
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.
Hansen, M. C., Townshend, J. R. G., DeFries, R. S., and Carroll, M.:
Estimation of tree cover using MODIS data at global, continental and
regional/local scales, Int. J. Remote Sens., 26, 4359–4380, 2005.
Harman, I.: The Role of Roughness Sublayer Dynamics Within Surface Exchange
Schemes, Bound.-Lay. Meteorol., 142, 1–20, 2012.
Hilton, T. W., Davis, K. J., and Keller, K.: Evaluating terrestrial CO
2
flux diagnoses and uncertainties from a simple land surface model and its
residuals, Biogeosciences, 11, 217–235, https://doi.org/10.5194/bg-11-217-2014, 2014.
Hirschi, M., Seneviratne, S. I., Alexandrov, V., Boberg, F., Boroneant, C.,
Christensen, O. B., Formayer, H., Orlowsky, B., and Stepanek, P.:
Observational evidence for soil-moisture impact on hot extremes in
southeastern Europe, Nat. Geosci., 4, 17–21, 2011.
Hoeting, J. A., Madigan, D., Raftery, A. E., and Volinsky, C. T.: Bayesian
Model Averaging: A Tutorial, Stat. Sci., 14, 382–401, 1999.
Hollinger, D. Y., Ollinger, S. V., Richardson, A. D., Meyers, T. P., Dail, D.
B., Martin, M. E., Scott, N. A., Arkebauer, T. J., Baldocchi, D. D., and
Clark, K. L.: Albedo estimates for land surface models and support for a new
paradigm based on foliage nitrogen concentration, Glob. Change Biol., 16,
696–710, 2010.
Horn, J. E. and Schulz, K.: Identification of a general light use efficiency
model for gross primary production, Biogeosciences, 8, 999–1021,
https://doi.org/10.5194/bg-8-999-2011, 2011.
Huffman, G. J., Adler, R. F., Rudolph, B., Schneider, U., and Keehn, P.:
Global precipitation estimates based on a technique for combining
satellite-based estimates, rain gauge analysis, and NWP model precipitation
information, J. Climate, 8, 1284–1295, 1995.
Humphreys, E. R., Black, T. A., Morgenstern, K., Cai, T., Drewitt, G. B.,
Nesic, Z., and Trofymow, J. A.: Carbon dioxide fluxes in coastal Douglas-fir
stands at different stages of development after clearcut harvesting, Agr.
Forest Meteorol., 140, 6–22, 2006.
Jiménez, C., Prigent, C., Mueller, B., Seneviratne, S. I., McCabe, 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.
Jiménez-Muñoz, J., Sobrino, J., Plaza, A., Guanter, L., Moreno, J.,
and Martinez, P.: Comparison Between Fractional Vegetation Cover Retrievals
from Vegetation Indices and Spectral Mixture Analysis: Case Study of
PROBA/CHRIS Data Over an Agricultural Area, Sensors, 9, 768–793, 2009.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J.,
Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., and de Jeu, R.: Recent
decline in the global land evapotranspiration trend due to limited moisture
supply, Nature, 467, 951–954, 2010.
Kross, A., Seaquist, J. W., Roulet, N. T., Fernandes, R., and Sonnentag, O.:
Estimating carbon dioxide exchange rates at contrasting northern peatlands
using MODIS satellite data, Remote Sens. Environ., 137, 234–243, 2013.
Kustas, W. P., Perry, E. M., Doraiswamy, P. C., and Moran, M. S.: Using
satellite remote sensing to extrapolate evapotranspiration in time and space
over a semiarid rangeland, Remote Sens. Environ., 49, 275–286, 1994.
Liu, Y. Y., de Jeu, R. A. M., McCabe, M. F., Evans, J. P., and van Dijk, A.
I. J. M.: Global long-term passive microwave satellite-based retrievals of
vegetation optical depth, Geophys. Res. Lett., 38, L18402, https://doi.org/10.1029/2011GL048684,
2011a.
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, 2011b.
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, 2012.
Liu, Y. Y., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P., and de Jeu,
R. A. M.: Global vegetation biomass change (1988–2008) and attribution to
environmental and human drivers, Global Ecol. Biogeogr., 22, 692–705, 2013.
Lokupitiya, E., Denning, S., Paustian, K., Baker, I., Schaefer, K., Verma,
S., Meyers, T., Bernacchi, C. J., Suyker, A., and Fischer, M.: Incorporation
of crop phenology in Simple Biosphere Model (SiBcrop) to improve
land-atmosphere carbon exchanges from croplands, Biogeosciences, 6, 969–986,
https://doi.org/10.5194/bg-6-969-2009, 2009.
Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Derksen, C., and
Wang, L.: Snow water equivalent (SWE) product guide, Global Snow Monitoring
for Climate Research, European Space Agency Study Contract Report Esrin
Contract 21703/08/I-EC), available at:
http://www.globsnow.info/docs/GlobSnow_2_Final_Report_release.pdf (last
access: 25 January 2016), 2010.
Mach, D. M., Christian, H. J., Blakeslee, R. J., Boccippio, D. J., Goodman,
S. J., and Boeck, W. L.: Performance assessment of the optical transient
detector and lightning imaging sensor, J. Geophys. Res.-Atmos. (1984–2012),
112, D09210, https://doi.org/10.1029/2006JD007787, 2007.
McCabe, M. F. and Wood, E. F.: Scale influences on the remote estimation of
evapotranspiration using multiple satellite sensors, Remote Sens. Environ.,
105, 271–285, 2006.
McCabe, M. F., Wood, E. F., Wójcik, R., Pan, M., Sheffield, J., Gao, H.,
and Su, H.: Hydrological consistency using multi-sensor remote sensing data
for water and energy cycle studies, Remote Sens. Environ., 112, 430–444,
2008.
Merlin, O., Al Bitar, A., Rivalland, V., Béziat, P., Ceschia, E., and
Dedieu, G.: An analytical model of evaporation efficiency for unsaturated
soil surfaces with an arbitrary thickness, J. Appl. Meteorol. Clim., 50,
457–471, 2011.
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. Discuss., 12, 10739–10787,
https://doi.org/10.5194/hessd-12-10739-2015, 2015.
Miralles, D. G., Gash, J. H., Holmes, T. R. H., de Jeu, R. A. M., and Dolman,
A.: Global canopy interception from satellite observations, J. Geophys. Res.,
115, D16122, https://doi.org/10.1029/2009JD013530, 2010.
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, 2011a.
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, 2011b.
Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., and de Arellano, J.
V.-G.: Mega-heatwave temperatures due to combined soil desiccation and
atmospheric heat accumulation, Nat. Geosci., 7, 345–349, 2014a.
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.,
and Dorigo, W. A.: El Niño–La Niña cycle and recent trends in
continental evaporation, Nature Climate Change, 4, 122–126, 2014b.
Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., McCabe,
M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q.,
Seneviratne, S. I., Wood, E. F., and Fernaìndez-Prieto, D.: The
WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation
data sets, Hydrol. Earth Syst. Sci. Discuss., 12, 10651–10700,
https://doi.org/10.5194/hessd-12-10651-2015, 2015.
Monteith, J. L.: Evaporation and environment, Symp. Soc. Exp. Biol., 19,
205–234, 1965.
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, 2007.
Mu, Q., Zhao, M., Kimball, J. S., McDowell, N. G., and Running, S. W.: A
Remotely Sensed Global Terrestrial Drought Severity Index, B. Am. Meteorol.
Soc., 94, 83–98, 2012.
Mu, Q., Zhao, M., and Running, S. W.: MODIS Global Terrestrial
Evapotranspiration (ET) Product (NASA MOD16A2/A3), Algorithm Theoretical
Basis Document, Collection, 5, The University of Montana, Missoula, MT, USA,
available at: http://www.ntsg.umt.edu/node/801 (last access: 25 January
2016), 2013.
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.
Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A.
J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G.,
McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang,
Y., and Seneviratne, S. I.: Benchmark products for land evapotranspiration:
LandFlux-EVAL multi-data set synthesis, Hydrol. Earth Syst. Sci., 17,
3707–3720, https://doi.org/10.5194/hess-17-3707-2013, 2013.
Nesbitt, S. W., Zipser, E. J., and Kummerow, C. D.: An examination of
version-5 rainfall estimates from the TRMM Microwave Imager, precipitation
radar, and rain gauges on global, regional, and storm scales, J. Appl.
Meteorol., 43, 1016–1036, 2004.
Otkin, J. A., Anderson, M. C., Hain, C., and Svoboda, M.: Examining the
Relationship between Drought Development and Rapid Changes in the Evaporative
Stress Index, J. Hydrometeorol., 15, 938–956, 2014.
Penman, H. L.: Natural Evaporation from Open Water, Bare Soil and Grass, P.
Roy. Soc. Lond. A Mat., 193, 120–145, 1948.
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P.
M., Mooney, H. A., and Klooster, S. A.: Terrestrial ecosystem production: a
process model based on global satellite and surface data, Global Biogeochem.
Cy., 7, 811–841, 1993.
Rebmann, C., Göckede, M., Foken, T., Aubinet, M., Aurela, M., Berbigier,
P., Bernhofer, C., Buchmann, N., Carrara, A., and Cescatti, A.: Quality
analysis applied on eddy covariance measurements at complex forest sites
using footprint modelling, Theor. Appl. Climatol., 80, 121–141, 2005.
Reichstein, M., Rey, A., Freibauer, A., Tenhunen, J., Valentini, R., Banza,
J., Casals, P., Cheng, Y., Grünzweig, J. M., and Irvine, J.: Modeling
temporal and large-scale spatial variability of soil respiration from soil
water availability, temperature and vegetation productivity indices, Global
Biogeochem. Cy., 17, 1104, https://doi.org/10.1029/2003GB002035, 2003.
Richardson, A. D., Black, T. A., Ciais, P., Delbart, N., Friedl, M. A.,
Gobron, N., Hollinger, D. Y., Kutsch, W. L., Longdoz, B., and Luyssaert, S.:
Influence of spring and autumn phenological transitions on forest ecosystem
productivity, Philos. T. R. Soc. B, 365, 3227–3246, 2010.
Richey, A. S., Thomas, B. F., Lo, M.-H., Reager, J. T., Famiglietti, J. S.,
Voss, K., Swenson, S., and Rodell, M.: Quantifying renewable groundwater
stress with GRACE, Water Resour. Res., 51, 5217–5238,
https://doi.org/10.1002/2015WR017349, 2015.
Rubel, F. and Kottek, M.: Observed and projected climate shifts 1901–2100
depicted by world maps of the Köppen-Geiger climate classification,
Meteorol. Z., 19, 135–141, 2010.
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P.,
Kistler, R., Woollen, J., and Behringer, D.: The NCEP climate forecast system
reanalysis, B. Am. Meteorol. Soc., 91, 1015–1057, 2010.
Sahoo, A. K., Pan, M., Troy, T. J., Vinukollu, R. K., Sheffield, J., and
Wood, E. F.: Reconciling the global terrestrial water budget using satellite
remote sensing, Remote Sens. Environ., 115, 1850–1865, 2011.
Saigusa, N., Ichii, K., Murakami, H., Hirata, R., Asanuma, J., Den, H., Han,
S.-J., Ide, R., Li, S.-G., Ohta, T., Sasai, T., Wang, S.-Q., and Yu, G.-R.:
Impact of meteorological anomalies in the 2003 summer on Gross Primary
Productivity in East Asia, Biogeosciences, 7, 641–655,
https://doi.org/10.5194/bg-7-641-2010, 2010.
Scott, R. L.: Using watershed water balance to evaluate the accuracy of eddy
covariance evaporation measurements for three semiarid ecosystems, Agr.
Forest Meteorol., 150, 219–225, 2010.
Sheffield, J., Ferguson, C. R., Troy, T. J., Wood, E. F., and McCabe, M. F.:
Closing the terrestrial water budget from satellite remote sensing, Geophys.
Res. Lett., 36, L07403, https://doi.org/10.1029/2009GL037338, 2009.
Simard, M., Pinto, N., Fisher, J. B., and Baccini, A.: Mapping forest canopy
height globally with spaceborne lidar, J. Geophys. Res.-Biogeo., 116, G04021,
https://doi.org/10.1029/2011JG001708, 2011.
Smith, P., Lanigan, G., Kutsch, W. L., Buchmann, N., Eugster, W., Aubinet,
M., Ceschia, E., Béziat, P., Yeluripati, J. B., and Osborne, B.:
Measurements necessary for assessing the net ecosystem carbon budget of
croplands, Agr. Ecosyst. Environ., 139, 302–315, 2010.
Soudani, K., Hmimina, G., Dufrêne, E., Berveiller, D., Delpierre, N.,
Ourcival, J.-M., Rambal, S., and Joffre, R.: Relationships between
photochemical reflectance index and light-use efficiency in deciduous and
evergreen broadleaf forests, Remote Sens. Environ., 144, 73–84, 2014.
Sprintsin, M., Cohen, S., Maseyk, K., Rotenberg, E., Grünzweig, J.,
Karnieli, A., Berliner, P., and Yakir, D.: Long term and seasonal courses of
leaf area index in a semi-arid forest plantation, Agr. Forest Meteorol., 151,
565–574, 2011.
Stackhouse, P. W., Gupta, S. K., Cox, S. J., Zhang, T., Mikovitz, J. C., and
Hinkelman, L. M.: The NASA/GEWEX surface radiation budget release 3.0:
24.5-year dataset, GEWEX News, 21, 10–12, 2011.
Stoy, P. C., Mauder, M., Foken, T., Marcolla, B., Boegh, E., Ibrom, A.,
Arain, M. A., Arneth, A., Aurela, M., and Bernhofer, C.: A data-driven
analysis of energy balance closure across FLUXNET research sites: The role of
landscape scale heterogeneity, Agr. Forest Meteorol., 171, 137–152, 2013.
Su, H., McCabe, M. F., Wood, E. F., Su, Z., and Prueger, J. H.: Modeling
evapotranspiration during SMACEX: Comparing two approaches for local- and
regional-scale prediction, J. Hydrometeorol., 6, 910–922, 2005.
Su, Z.: The Surface Energy Balance System (SEBS) for estimation of turbulent
heat fluxes, Hydrol. Earth Syst. Sci., 6, 85–100,
https://doi.org/10.5194/hess-6-85-2002, 2002.
Sulkava, M., Luyssaert, S., Zhehle, S., and Papale, D.: Assessing and
improving the representativeness of monitoring networks: The European flux
tower network example, J. Geophys. Res., 116, G00J04,
https://doi.org/10.1029/2010JG001562, 2011.
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W.,
Mahoney, R., Vermote, E. F., and El Saleous, N.: An extended AVHRR 8-km NDVI
dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote
Sens., 26, 4485–4498, 2005.
van der Kwast, J., Timmermans, W., Gieske, A., Su, Z., Olioso, A., Jia, L.,
Elbers, J., Karssenberg, D., and de Jong, S.: Evaluation of the Surface
Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements
at the SPARC 2004 site (Barrax, Spain), Hydrol. Earth Syst. Sci., 13,
1337–1347, https://doi.org/10.5194/hess-13-1337-2009, 2009.
Veenendaal, M., Kolle, O., and Lloyd, J.: Seasonal variation in energy fluxes
and carbon dioxide exchange for a broad leaved semi-arid savanna (Mopane
woodland) in Southern Africa, Glob. Change Biol., 10, 318–328, 2004.
Vinukollu, R. K., Sheffield, J., Wood, E. F., Bosilovich, M. G., and Mocko,
D.: Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between
Operational Analyses, a Land Surface Model, and Remote Sensing, J.
Hydrometeorol., 13, 3–26, 2011a.
Vinukollu, R. K., Wood, E. F., Ferguson, C. R., and Fisher, J. B.: Global
estimates of evapotranspiration for climate studies using multi-sensor remote
sensing data: Evaluation of three process-based approaches, Remote Sens.
Environ., 115, 801–823, 2011b.
Weligepolage, K., Gieske, A. S. M., van der Tol, C., Timmermans, J., and Su,
Z.: Effect of sub-layer corrections on the roughness parameterization of a
Douglas fir forest, Agr. Forest Meteorol., 162–163, 115–126, 2012.
Wharton, S., Schroeder, M., Paw U, K. T., Falk, M., and Bible, K.: Turbulence
considerations for comparing ecosystem exchange over old-growth and clear-cut
stands for limited fetch and complex canopy flow conditions, Agr. Forest
Meteorol., 149, 1477–1490, 2009.
Wohl, E., Barros, A., Brunsell, N., Chappell, N. A., Coe, M., Giambelluca,
T., Goldsmith, S., Harmon, R., Hendrickx, J. M. H., Juvik, J., McDonnell, J.,
and Ogden, F.: The hydrology of the humid tropics, Nature Clim. Change, 2,
655–662, 2012.
Yan, Y., Zhao, B., Chen, J., Guo, H., Gu, Y., Wu, Q., and Li, B.: Closing the
carbon budget of estuarine wetlands with tower-based measurements and MODIS
time series, Glob. Change Biol., 14, 1690–1702, 2008.
Yao, Y., Liang, S., Li, X., Hong, Y., Fisher, J. B., Zhang, N., Chen, J.,
Cheng, J., Zhao, S., and Zhang, X.: Bayesian multimodel estimation of global
terrestrial latent heat flux from eddy covariance, meteorological, and
satellite observations, J. Geophys. Res.-Atmos., 119, 4521–4545, 2014.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao,
S., Nemani, R. R., and Myneni, R. B.: Global data sets of vegetation leaf
area index (LAI) 3 g and Fraction of Photosynthetically Active Radiation
(FPAR) 3 g derived from Global Inventory Modeling and Mapping Studies
(GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the period 1981
to 2011, Remote Sensing, 5, 927–948, 2013.