{"id":579,"date":"2013-09-16T12:59:35","date_gmt":"2013-09-16T16:59:35","guid":{"rendered":"https:\/\/sites.bu.edu\/cliveg\/?page_id=579"},"modified":"2025-12-27T11:54:59","modified_gmt":"2025-12-27T16:54:59","slug":"model-studies","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/cliveg\/research\/model-studies\/","title":{"rendered":"Model Studies"},"content":{"rendered":"

Model Studies<\/h2>\n
    \n
  1. Pu et al., 2025.<\/a> Large gains in leaf scale photosynthetic rates of sparsely vegetated arid and semi-arid lands, Commun Earth Environ (2025).
    \nhttps:\/\/doi.org\/10.1038\/s43247-025-03121-3<\/li>\n
  2. Pu et al., 2025.<\/a> MCI GPP: ensembling a global model- and climate-independent gross primary productivity for 2001\u20132023, Scientific Data, (2025) 12:1965 | https:\/\/doi.org\/10.1038\/s41597-025-06218-8<\/li>\n
  3. Duanmu et al., 2025.<\/a> Changes in leaf and root carbon allocation of global vegetation simulated by the optimally integrated ecosystem models, Agric. For. Meteorol., 362 (2025) 110366<\/li>\n
  4. Winkler et al., 2024.<\/a> Carbon system state determines warming potential of emissions, PLoS ONE 19(8): e0306128. doi: 10.1371\/journal.pone.0306128<\/li>\n
  5. Zuo et al., 2023.<\/a> Simulating Potential Tree Height for Beech\u2013Maple\u2013Birch Forests in Northeastern United States on Google Earth Engine, J. Remote Sens., 2023;3:Article 0084. https:\/\/doi.org\/10.34133\/remotesensing.0084<\/li>\n
  6. Chi et al., 2020.<\/a> Biophysical impacts of Earth greening largely controlled by aerodynamic resistance. Sci. Adv., 6 : eabb1981 <\/li>\n
  7. Zhao et al., 2020.<\/a> Future greening of the Earth may not be as large as previously predicted. Agric. For. Meteorol., doi: 10.1016\/j.agrformet.2020.108111<\/li>\n
  8. Piao et al., 2019.<\/a> Characteristics, drivers and feedbacks of global greening. Nature Reviews Earth and Environment, doi: 10.1038\/s43017-019-0001-x<\/a> <\/li>\n
  9. Winkler et al., 2019.<\/a> Earth system models underestimate carbon fixation by plants in the high latitudes. Nature Communications, doi:10.1038\/s41467-019-08633-z<\/li>\n
  10. Winkler et al., 2019.<\/a> Investigating the applicability of emergent constraints. Earth System Dynamics, doi:10.5194\/esd-10-501-2019<\/li>\n
  11. Zhang et al., 2019.<\/a> Mapping Maximum Tree Height of the Great Khingan Mountain, Inner Mongolia Using the Allometric Scaling and Resource Limitations Model. Forests, doi:10.3390\/f10050380<\/li>\n
  12. Zeng et al., 2018.<\/a> Impact of Earth Greening on the Terrestrial Water Cycle. J. Climate, doi: 10.1175\/JCLI-D-17-0236.1<\/li>\n
  13. Zhu et al., 2016.<\/a> Greening of the Earth and its Drivers. Nature Climate Change, doi:10.1038\/nclimate3004<\/li>\n
  14. Mao et al., 2016.<\/a> Human-induced Greening of the Northern Extratropical Land Surface. Nature Climate Change, doi: 10.1038\/nclimate3056<\/li>\n
  15. Choi et al., 2016.<\/a> Application of the metabolic scaling theory and water\u2013energy balance equation to model large-scale patterns of maximum forest canopy height. Global Ecol. Biogeography, doi:10.1111\/geb.12503<\/li>\n
  16. Reid et al., 2015.<\/a> Global impacts of the 1980s regime shift. Global Change Biology, 2015 (doi: 10.1111\/gcb.13106)<\/li>\n
  17. Piao et al., 2015.<\/a> Detection and attribution of vegetation greening trend in China over the last 30 years, Global Change Biology, 2015 (doi: 10.1111\/gcb.12795)<\/li>\n
  18. Traore et al., 2014.<\/a> Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements, J. Geophys. Res. Biogeosci., 119, 1554\u20131575, doi:10.1002\/2014JG002638.<\/li>\n
  19. Sitch et al., 2013<\/a> Trends and drivers of regional sources and sinks of carbon dioxide over the past two decades, Biogeosciences Discuss., doi:10.5194\/bgd-10-20113-2013, 10:20113\u201320177, 2013<\/li>\n
  20. Xu et al., 2013.<\/a> Temperature and vegetation seasonality diminishment over northern lands. Nature Climate Change, doi: 10.1038\/NCLIMATE1836
    \n    Supplementary Information<\/a><\/li>\n
  21. Ichii et al., 2013<\/a> Recent changes in terrestrial gross primary productivity in Asia from 1982 to 2011, Remote Sens., doi: 10.3390\/rs5116043<\/li>\n
  22. Xin et al., 2013<\/a> A production efficiency model-based method for satellite estimates of corn and soybean yields in the midwestern US, Remote Sens., doi: 10.3390\/rs5115926<\/li>\n
  23. Barichivich et al., 2013.<\/a> Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011, Global Change Biol., 2013, doi: 10.1111\/gcb.12283<\/li>\n
  24. Wang et al., 2013.<\/a> Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets, Remote Sens. 2013, 5, 2857-2882; doi: 10.3390\/rs5062857<\/li>\n
  25. Piao et al., 2013.<\/a> Evaluation of Terrestrial Carbon Cycle Models for their Response to Climate Variability and to CO2 Trends, Global Change Biology, doi: 10.1111\/gcb.12187<\/li>\n
  26. Anav et al., 2013.<\/a> Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models, J. Climate, doi:10.1175\/JCLI-D-12-00417.1<\/li>\n
  27. Mao et al., 2013.<\/a> Global Latitudinal-Asymmetric Vegetation Growth Trends and Their Driving Mechanisms: 1982-2009, Remote Sens. doi:10.3390\/rs5031484<\/li>\n
  28. Zeng et al., 2012.<\/a> Global evapotranspiration over the past three decades: estimation based on the water balance equation combined with empirical models, Environ. Res. Lett., doi: 10.1088\/1748-9326\/7\/1\/014026<\/li>\n
  29. Samanta et al., 2010.<\/a> Physical climate response to a reduction of anthropogenic climate forcing, Earth Interactions, doi: 10.1175\/2010EI325.1<\/li>\n
  30. Robinson et al., 2008. <\/a>An empirical approach to retrieve monthly evapotranspiration over Amazonia, Int. J. Remote Sens., Vol. 29:7045\u20137063.<\/li>\n
  31. Ichii et al., 2007. <\/a> Constraining rooting depths in tropical rainforests using satellite data and ecosystem modeling for accurate simulation of gross primary production seasonality, Global Change Biology, doi: 10.1111\/j.1365-2486.2006.01277.x<\/li>\n
  32. Tian et al., 2004. <\/a> Land boundary conditions from MODIS data and consequences for the albedo of a climate model. Geophys. Res. Lett., doi: 10.1029\/2003GL019104<\/li>\n
  33. Tian et al., 2004. <\/a> Comparison of seasonal and spatial variations of LAI\/FPAR from MODIS and Common Land Model. J. Geophys. Res., doi: 10.1029\/2003JD003777<\/li>\n
  34. Zhou et al., 2003. <\/a> Comparison of seasonal and spatial variations of albedos from MODIS and the Common Land Model. J. Geophys. Res., doi: 10.1029\/2002JD003326<\/li>\n
  35. Zeng et al., 2002. <\/a>Coupling of the common land model to the NCAR community climate model. J. Clim., 15: 1832-1854.<\/li>\n
  36. Dickinson et al., 2002.<\/a> Nitrogen Controls on Climate Model Evapotranspiration. J. Clim., 15(3): 278-295.<\/li>\n
  37. Buermann et al., 2001.<\/a> Evaluation of the utility of satellite-based vegetation leaf area index data for climate simulations. J. Climate, 14(17): 3536-3550.<\/li>\n
  38. Dong et al., 2001.<\/a> Improving numerical precision of simulated soil water fluxes in land surface models. J. Geophys. Res., 106(D13): 14,357-14,368.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Model Studies Pu et al., 2025. Large gains in leaf scale photosynthetic rates of sparsely vegetated arid and semi-arid lands, Commun Earth Environ (2025). https:\/\/doi.org\/10.1038\/s43247-025-03121-3 Pu et al., 2025. MCI GPP: ensembling a global model- and climate-independent gross primary productivity for 2001\u20132023, Scientific Data, (2025) 12:1965 | https:\/\/doi.org\/10.1038\/s41597-025-06218-8 Duanmu et al., 2025. Changes in leaf […]<\/p>\n","protected":false},"author":7541,"featured_media":0,"parent":17,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"page-templates\/no-sidebars.php","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/pages\/579"}],"collection":[{"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/users\/7541"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/comments?post=579"}],"version-history":[{"count":30,"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/pages\/579\/revisions"}],"predecessor-version":[{"id":6135,"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/pages\/579\/revisions\/6135"}],"up":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/pages\/17"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/cliveg\/wp-json\/wp\/v2\/media?parent=579"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}