AVANÇOS DO SIMPLE BIOSPHERE MODEL (SIB) NA REPRESENTAÇÃO DOS PROCESSOS FÍSICOS E BIOGEOQUÍMICOS: UMA REVISÃO DE LITERATURA
DOI:
https://doi.org/10.28998/contegeo.8i.17.15769Parole chiave:
Fluxos de energia; Modelagem; Vegetação; Superfície-Atmosfera.Abstract
Os modelos de superfície terrestre desempenham um papel fundamental na estimativa dos processos físicos que ocorrem no sistema superfície-atmosfera. Sendo essenciais para a compreensão das transferências de energia, massa e momento e como condição de contorno da baixa atmosfera em modelos de circulação geral da atmosfera e de previsão do tempo, uma vez que a estimativa correta desses parâmetros à superfície é necessária para obter previsões precisas. Um desses modelos de superfície amplamente utilizados é o Simple Biosphere Model (SiB), que tem passado por melhorias e avanços desde sua primeira versão. O SiB4 é o mais recente que integra informações sobre cobertura terrestre, fenologia, alocação de carbono e fluxos de energia e massa, fornecendo estimativas válidas para diferentes ecossistemas e contribuindo para a compreensão das mudanças naturais e antropogênicas na superfície terrestre. O supracitado modelo é uma ferramenta que pode ser utilizada em uma ampla variedade de estudos, não se limita a estudos globais, sendo utilizado em estudos regionais para investigar as interações entre a terra e a atmosfera em uma variedade de tipos de vegetação e em uma ampla gama de climas. O presente estudo tem o objetivo de investigar a evolução do referido modelo ao longo das décadas, analisando as melhorias e avanços realizados na representação dos processos físicos e biogeoquímicos da superfície terrestre.
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Riferimenti bibliografici
ASHWORTH, K.; CHUNG, S. H.; GRIFFIN, R. J.; et al. Forest Canopy Atmosphere Transfer (FORCAsT) 1.0: A 1-D model of biosphere-atmosphere chemical exchange. Geoscientific Model Development, v. 8, n. 11, p. 3765–3784, 2015.
BAKER, I.; DENNING, S.; STÖCKLI, R. North American gross primary productivity: regional characterization and interannual variability. Tellus B: Chemical and Physical Meteorology, v. 62, n. 5, p. 533–549, 2010. Disponível em: <https://www.tandfonline.com/doi/full/10.1111/j.1600-0889.2010.00492.x>.
______. HARPER, A. B.; DA ROCHA, H. R.; et al. Surface ecophysiological behavior across vegetation and moisture gradients in tropical South America. Agricultural and Forest Meteorology, v. 182–183, p. 177–188, 2013. Elsevier B.V. Disponível em: <http://dx.doi.org/10.1016/j.agrformet.2012.11.015>.
______. Biophysical Behavior in Tropical South America. Tese (Doutorado em Ecologia) – Fort Collins: Colorado State University. 2011 Disponível em: <http://denning.atmos.colostate.edu/biocycle/Documents/Dissertations/2011.IanBaker.PhD.Dissertation.pdf>.
______. PRIHODKO, L.; DENNING, A. S.; et al. Seasonal drought stress in the amazon: Reconciling models and observations. Journal of Geophysical Research, v. 113, n. G00B01, p. 1–10, 2008.
BALDOCCHI’, D. D.; HARLEY, P. C. Scaling carbon dioxide and water vapour exchange from leaf to canopy in a deciduous forest. II. Model testing and application. 1995.
______. WILSON, K. B.; GU, L. How the environment, canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broad-leaved deciduous forest--an assessment with the biophysical model CANOAK. Tree Physiology, v. 22, n. 15–16, p. 1065–1077, 2002. Disponível em: <https://academic.oup.com/treephys/article-lookup/doi/10.1093/treephys/22.15-16.1065>.
BALLANTYNE, A. P.; MILLER, J. B.; BAKER, I. T.; TANS, P. P.; WHITE, J. W. C. Novel applications of carbon isotopes in atmospheric CO2: what can atmospheric measurements teach us about processes in the biosphere? Biogeosciences, v. 8, n. 10, p. 3093–3106, 2011. Disponível em: <https://bg.copernicus.org/articles/8/3093/2011/>.
BERRY, J.; WOLF, A.; CAMPBELL, J. E.; et al. A coupled model of the global cycles of carbonyl sulfide and CO2 : A possible new window on the carbon cycle. Journal of Geophysical Research: Biogeosciences, v. 118, n. 2, p. 842–852, 2013. Disponível em: <https://onlinelibrary.wiley.com/doi/10.1002/jgrg.20068>.
BIOCYCLE. Denning Research Group, Carbon, Climate, Water and Ecosystem. Acesso em: 05 jun. 2023. Disponível em: <http://biocycle.atmos.colostate.edu/research/models/sib3/>
BONAN, G. B.; PATTON, E. G.; HARMAN, I. N.; et al. Modeling canopy-induced turbulence in the Earth system: A unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0). Geoscientific Model Development, v. 11, n. 4, p. 1467–1496, 2018.
______. WILLIAMS, M.; FISHER, R. A.; OLESON, K. W. Modeling stomatal conductance in the earth system: Linking leaf water-use efficiency and water transport along the soil-plant-atmosphere continuum. Geoscientific Model Development, v. 7, n. 5, p. 2193–2222, 2014.
BUTLER, M. P.; DAVIS, K. J.; DENNING, A. S.; KAWA, S. R. Using continental observations in global atmospheric inversions of CO2 : North American carbon sources and sinks. Tellus B: Chemical and Physical Meteorology, v. 62, n. 5, p. 550–572, 2010. Disponível em: <https://www.tandfonline.com/doi/full/10.1111/j.1600-0889.2010.00501.x>.
CHANG, K. Y.; PAW U, K. T.; CHEN, S. H. Canopy profile sensitivity on surface layer simulations evaluated by a multiple canopy layer higher order closure land surface model. Agricultural and Forest Meteorology, v. 252, p. 192–207, 2018.
CHEESEMAN, M. J. Productivity and Phenology in a Process-Driven Carbon Cycle Model. Dissertação (Master of Science) - Fort Collins: Colorado State University. 2018. Disponível em: <https://mountainscholar.org/handle/10217/193205>.
CHEN, J.; MA, X.; LU, X.; et al. Long-term phosphorus addition alleviates CO2 and N2O emissions via altering soil microbial functions in secondary rather primary tropical forests. Environmental Pollution, v. 323, 2023.
CHEN, Y.; RYDER, J.; BASTRIKOV, V.; et al. Evaluating the performance of land surface model ORCHIDEE-CAN v1.0 on water and energy flux estimation with a single-and multi-layer energy budget scheme. Geoscientific Model Development, v. 9, n. 9, p. 2951–2972, 2016.
CIONCO, R. M. A Mathematical Model for Air Flow in a Vegetative Canopy. Journal of Applied Meteorology, v. 4, n. 4, p. 517–522, 1965.
COLLATZ, G. J.; BALL, J. T.; GRIVET, C.; BERRY, J. A. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer. Agricultural and Forest Meteorology, v. 54, n. 2–4, p. 107–136, 1991.
______. RIBAS-CARBO, M.; BERRY, J. Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants. Australian Journal of Plant Physiology, v. 19, n. 5, p. 519–538, 1992.
CORBIN, K. D.; DENNING, A. S.; LOKUPITIYA, E. Y.; et al. Assessing the impact of crops on regional CO 2 fluxes and atmospheric concentrations. Tellus B: Chemical and Physical Meteorology, v. 62, n. 5, p. 521–532, 2010b. Disponível em: <https://www.tandfonline.com/doi/full/10.1111/j.1600-0889.2010.00485.x>.
______. DENNING, A. S.; LU, L.; WANG, J.-W.; BAKER, I. T. Possible representation errors in inversions of satellite CO2 retrievals. Journal of Geophysical Research, v. 113, n. D2, p. D02301, 2008. Disponível em: <http://doi.wiley.com/10.1029/2007JD008716>.
______. DENNING, S.; GURNEY, K. The space and time impacts on U.S. regional atmospheric CO 2 concentrations from a high resolution fossil fuel CO2 emissions inventory. Tellus B: Chemical and Physical Meteorology, v. 62, n. 5, p. 506–511, 2010a. Disponível em: <https://www.tandfonline.com/doi/full/10.1111/j.1600-0889.2010.00480.x>.
DAI, Y.; ZENG, X.; DICKINSON, R. E.; et al. The Common Land Model. Bulletin of the American Meteorological Society, v. 84, n. 8, p. 1013–1024, 2003. Disponível em: <https://journals.ametsoc.org/doi/10.1175/BAMS-84-8-1013>.
DEARDORFF, J. W. Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. Journal of Geophysical Research, v. 83, n. C4, p. 1889, 1978.
DENNING, A. S.; RANDALL, D. A.; COLLATZ, G. J.; SELLERS, P. J. Simulations of terrestrial carbon metabolism and atmospheric CO2 in a general circulation model. Part 2: Simulated CO2 concentrations. Tellus, Series B: Chemical and Physical Meteorology, v. 48, n. 4, p. 543–567, 1996a.
______. RANDALL, D. A.; COLLATZ, G. J.; SELLERS, P. J. Simulations of terrestrial carbon metabolism and atmospheric CO2 in a general circulation model. Tellus B: Chemical and Physical Meteorology, v. 48, n. 4, p. 543–567, 1996b. Disponível em: <https://www.tandfonline.com/doi/full/10.3402/tellusb.v48i4.15931>.
______. TAKAHASHI, T.; FRIEDLINGSTEIN, P. Can a strong atmospheric CO2 rectifier effect be reconciled with a “reasonable” carbon budget? Tellus B: Chemical and Physical Meteorology, v. 51, n. 2, p. 249–253, 1999. Disponível em: <http://www.tellusb.net/index.php/tellusb/article/view/16277>.
DICKINSON, R. E.; HENDERSON-SELLERS, A.; KENNEDY, P. J. Biosphere-atmosphere transfer scheme (BATS) version 1e as coupled to the NCAR community climate model. Colorado: National Center for Atmospheric Research Boulder, 1993. Disponível em: <http://dx.doi.org/10.5065/D67W6959>.
______. HENDERSON-SELLERS, A.; KENNEDY, P. J.; WILSON, M. F. Biosphere-atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model. Colorado: National Center for Atmospheric Research Boulder, p. 1–82, 1986.
GLATTHOR, N.; HÖPFNER, M.; BAKER, I. T.; et al. Tropical sources and sinks of carbonyl sulfide observed from space. Geophysical Research Letters, v. 42, n. 22, p. 10,082-10,090, 2015. Disponível em: <http://doi.wiley.com/10.1002/2015GL066293>.
HANAN, N. P.; BERRY, J. A.; VERMA, S. B.; et al. Testing a model of CO2, water and energy exchange in Great Plains tallgrass prairie and wheat ecosystems. Agricultural and Forest Meteorology, v. 131, n. 3–4, p. 162–179, 2005. Disponível em: <https://linkinghub.elsevier.com/retrieve/pii/S0168192305001012>.
HARPER, A.; BAKER, I. T.; DENNING, A. S.; et al. Impact of Evapotranspiration on Dry Season Climate in the Amazon Forest. Journal of Climate, v. 27, n. 2, p. 574–591, 2014. Disponível em: <http://journals.ametsoc.org/doi/10.1175/JCLI-D-13-00074.1>.
HAYNES, K.; BAKER, I.; DENNING, A. S. The Simple Biosphere Model, Version 4.2: SiB4 Technical description. Colorado State University, 2020. Disponível em: <https://mountainscholar.org/handle/10217/200691>. Acesso em: 31/1/2023.
______. BAKER, I. T.; DENNING, A. S.; et al. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: 1. Implementation in the Simple Biosphere Model (SiB4). Journal of Advances in Modeling Earth Systems, v. 11, n. 12, p. 4423–4439, 2019a. https://doi.org/10.1029/2018MS001540.
______. BAKER, I.T., BAKER, I. T.; DENNING, A. S.; et al. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling. Journal of Advances in Modeling Earth Systems, v. 11, n. 12, p. 4440-4465, 2019b. https://doi.org/10.1029/2018MS001541.
INOUE, E. On the Turbulent Structure of Airflow within. Journal of the Meteorological Society of Japan. v. 41, n. 6, p. 317–326, 1963. Disponível em: <https://www.jstage.jst.go.jp/article/jmsj1923/41/6/41_6_317 /_article>.
JACKSON, R. B.; CANADELL, J.; EHLERINGER, J. R.; et al. A global analysis of root distributions for terrestrial biomes. Oecologia, v. 108, n. 3, p. 389–411, 1996. Disponível em: <http://link.springer.com/10.1007/BF00333714>.
KEENAN, T. F.; NIINEMETS, Ü. Global leaf trait estimates biased due to plasticity in the shade. Nature Plants, v. 3, n. 1, 2016. Disponível em: <https://www.nature.com/articles/nplants2016201>.
KUAI, L.; WORDEN, J. R.; CAMPBELL, J. E.; et al. Estimate of carbonyl sulfide tropical oceanic surface fluxes using Aura Tropospheric Emission Spectrometer observations. Journal of Geophysical Research: Atmospheres, v. 120, n. 20, p. 12–23, 2015. Disponível em: <https://onlinelibrary.wiley.com/doi/10.1002/2015JD023493>.
LAUVAUX, T.; SCHUH, A. E.; ULIASZ, M.; et al. Constraining the CO2 budget of the corn belt: exploring uncertainties from the assumptions in a mesoscale inverse system. Atmospheric Chemistry and Physics, v. 12, n. 1, p. 337–354, 2012. Disponível em: <https://acp.copernicus.org/articles/12/337/2012/>.
LAW, R. M.; PETERS, W.; RÖDENBECK, C.; et al. TransCom model simulations of hourly atmospheric CO2 : Experimental overview and diurnal cycle results for 2002. Global Biogeochemical Cycles, v. 22, n. 3, p. GB3009, 2008. Disponível em: <http://doi.wiley.com/10.1029/2007GB003050>.
LOKUPITIYA, E. Y.; DENNING, A. S.; SCHAEFER, K.; et al. Carbon and energy fluxes in cropland ecosystems: a model-data comparison. Biogeochemistry, v. 129, n. 1–2, p. 53–76, 2016. Disponível em: <http://link.springer.com/10.1007/s10533-016-0219-3>.
______. DENNING, S.; PAUSTIAN, K.; et al. Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands. Biogeosciences, v. 6, n. 6, p. 969–986, 2009. Disponível em: <https://bg.copernicus.org/articles/6/969/2009/>.
LOKUPITIYA, R. S.; ZUPANSKI, D.; DENNING, A. S.; et al. Estimation of global CO2 fluxes at regional scale using the maximum likelihood ensemble filter. Journal of Geophysical Research, v. 113, n. D20, p. D20110, 2008. Disponível em: <http://doi.wiley.com/10.1029/2007JD009679>.
LU, L.; DENNING, A. S.; DA SILVA-DIAS, M. A.; et al. Mesoscale circulations and atmospheric CO 2 variations in the Tapajós Region, Pará, Brazil. Journal of Geophysical Research, v. 110, n. D21, p. D21102, 2005. Disponível em: <http://doi.wiley.com/10.1029/2004JD005757>.
MONTEITH, J. L. Evaporation and environment. Symposia of the Society for Experimental Biology, v. 19, p. 205–234, 1965. Disponível em: <https://repository.rothamsted.ac.uk/item/8v5v7>.
NICHOLLS, M. E. A multiple-scale simulation of variations in atmospheric carbon dioxide using a coupled biosphere-atmospheric model. Journal of Geophysical Research, v. 109, n. D18, p. D18117, 2004. Disponível em: <http://doi.wiley.com/10.1029/2003JD004482>. .
NIINEMETS, Ü.; KEENAN, T. F.; HALLIK, L. A worldwide analysis of within‐canopy variations in leaf structural, chemical and physiological traits across plant functional types. New Phytologist, v. 205, n. 3, p. 973–993, 2015. Disponível em: <https://onlinelibrary.wiley.com/doi/10.1111/nph.13096>.
OGLE, S. M.; DAVIS, K.; LAUVAUX, T.; et al. An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO2 concentration data. Environmental Research Letters, v. 10, n. 3, p. 034012, 2015. Disponível em: <http://dx.doi.org/10.1088/1748-9326/10/3/034012>.
OLIVEIRA, W. J.; SOUZA, E. R.; CUNHA, J. C.; SILVA, Ê. F. DE F.; VELOSO, V. DE L. Leaf gas exchange in cowpea and CO2 efflux in soil irrigated with saline water. Revista Brasileira de Engenharia Agricola e Ambiental, v. 21, n. 1, p. 32–37, 2017.
PARAZOO, N. C.; DENNING, A. S.; KAWA, S. R.; et al. Mechanisms for synoptic variations of atmospheric CO2 in North America, South America and Europe. Atmospheric Chemistry and Physics, v. 8, n. 23, p. 7239–7254, 2008. Disponível em: <https://acp.copernicus.org/articles/8/7239/2008/>.
______. DENNING, A. S.; KAWA, S. R.; PAWSON, S.; LOKUPITIYA, R. CO2 flux estimation errors associated with moist atmospheric processes. Atmospheric Chemistry and Physics, v. 12, n. 14, p. 6405–6416, 2012. Disponível em: <https://acp.copernicus.org/articles/12/6405/2012/>.
PATRA, P. K.; LAW, R. M.; PETERS, W.; et al. TransCom model simulations of hourly atmospheric CO2 : Analysis of synoptic-scale variations for the period 2002-2003. Global Biogeochemical Cycles, v. 22, n. 4, 2008. Disponível em: <http://doi.wiley.com/10.1029/2007GB003081>.
PITMAN, A. J. The evolution of, and revolution in, land surface schemes designed for climate models. International Journal of Climatology, v. 23, n. 5, p. 479–510, 2003.
POTTER, C. S.; RANDERSON, J. T.; FIELD, C. B.; et al. Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles, v. 7, n. 4, p. 811–841, 1993. Disponível em: <http://doi.wiley.com/10.1029/93GB02725>.
RANDALL, D. A.; DAZLICH, D. A.; ZHANG, C.; et al. A Revised Land Surface Parameterization (SiB2) for GCMS. Part III: The Greening of the Colorado State University General Circulation Model. Journal of Climate, v. 9, n. 4, p. 738–763, 1996. Disponível em: <http://journals.ametsoc.org/doi/10.1175/1520-0442(1996)009%3C0738:ARLSPF%3E2.0.CO;2>.
RANDERSON, J. T.; THOMPSON, M. V.; MALMSTROM, C. M.; FIELD, C. B.; FUNG, I. Y. Substrate limitations for heterotrophs: Implications for models that estimate the seasonal cycle of atmospheric CO2. Global Biogeochemical Cycles, v. 10, n. 4, p. 585–602, 1996. Disponível em: <http://doi.wiley.com/10.1029/96GB01981>.
RAUPACH, M. R.; FINNIGAN, J. Single-Layer Models of Evaporation From Plant Canopies Are Incorrect but Useful, Whereas Multilayer Models Are Correct but Useless: Discuss. Functional Plant Biology, v. 15, n. 6, p. 705, 1988.
______. Canopy Transport Processes. Flow and Transport in the Natural Environment: Advances and Applications. p. 95–127, 1988. Disponível em: <http://link.springer.com/10.1007/978-3-642-73845-6_7>.
______. ANTONIA, R. A.; RAJAGOPALAN, S. Rough-wall turbulent boundary layers. Applied Mechanics Reviews, v. 44, n. 1, p. 1-25, 1991.
REIS, A. O.; COSTA, G. B.; LIMA, M. B.; et al. Sazonalidade e Correlação entre Emissões de Gases Estufa e Variáveis Ambientais em Áreas Florestais Distintas na Amazônia. Biodiversidade Brasileira - BioBrasil, v. 11, n. 4, p. 72–83, 2021. Disponível em: <https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1779>.
REY, A.; CARRASCAL, L. M.; BÁEZ, C. G. G.; et al. Impact of climate and land degradation on soil carbon fluxes in dry semiarid grasslands in SE Spain. Plant and Soil, v. 461, n. 1–2, p. 323–339, 2021.
RYDER, J.; POLCHER, J.; PEYLIN, P.; et al. A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations. Geoscientific Model Development, v. 9, n. 1, p. 223–245, 2016.
SATO, N.; SELLERS, P. J.; RANDALL, D. A.; et al. Effects of Implementing the Simple Biosphere Model in a General Circulation Model. Journal of the Atmospheric Sciences, v. 46, n. 18, p. 2757–2782, 1989. Disponível em: <http://journals.ametsoc.org/doi/10.1175/1520-0469(1989)046%3C2757:EOITSB%3E2.0.CO;2>.
SAYLOR, R. D. The Atmospheric Chemistry and Canopy Exchange Simulation System (ACCESS): model description and application to a temperate deciduous forest canopy. Atmospheric Chemistry and Physics, v. 13, n. 2, p. 693–715, 2013. Disponível em: <https://acp.copernicus.org/articles/13/693/2013/>.
SCHAEFER, K.; DENNING, A. S.; SUITS, N.; et al. Effect of climate on interannual variability of terrestrial CO2 fluxes. Global Biogeochemical Cycles, v. 16, n. 4, p. 1–12, 2002.
______. JAFAROV, E. A parameterization of respiration in frozen soils based on substrate availability. Biogeosciences, v. 13, n. 7, p. 1991–2001, 2016. Disponível em: <https://bg.copernicus.org/articles/13/1991/2016/>.
______. ZHANG, T.; BRUHWILER, L.; BARRETT, A. P. Amount and timing of permafrost carbon release in response to climate warming. Tellus B: Chemical and Physical Meteorology, v. 63, n. 2, p. 165–180, 2011. Disponível em: <http://www.tellusb.net/index.php/tellusb/article/view/16197>.
SCHUH, A. E.; DENNING, A. S.; CORBIN, K. D.; et al. A regional high-resolution carbon flux inversion of North America for 2004. Biogeosciences, v. 7, n. 5, p. 1625–1644, 2010. Disponível em: <https://bg.copernicus.org/articles/7/1625/2010/>.
______. LAUVAUX, T.; WEST, T. O.; et al. Evaluating atmospheric CO 2 inversions at multiple scales over a highly inventoried agricultural landscape. Global Change Biology, v. 19, n. 5, p. 1424–1439, 2013. Disponível em: <https://onlinelibrary.wiley.com/doi/10.1111/gcb.12141>.
SELLERS, P. J.; BERRY, J. A.; COLLATZ, G. J.; FIELD, C. B.; HALL, F. G. Canopy reflectance, photosynthesis, and transpiration. III. A reanalysis using improved leaf models and a new canopy integration scheme. Remote Sensing of Environment, v. 42, n. 3, p. 187–216, 1992.
______. LOS, S. O.; TUCKER, C. J.; et al. A revised land surface parameterization (SiB2) for Atmospheric GCMs. Part II: The generation of global fields of terrestrial biophysical parameters from satellite data. Journal of Climate, v. 9, n. 4, p. 706- 737, 1996.
______. MINTZ, Y.; SUD, Y. C.; DALCHER, A. A Simple Biosphere Model (SIB) for Use within General Circulation Models. Journal of the Atmospheric Science, v. 43, n. 6, p. 505–531, 1986.
______. RANDALL, D. A.; COLLATZ, G. J.; et al. A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation. Journal of Climate, v. 9, n. 4, p. 676–705, 1996.
SILVA, C. M.; VASCONCELOS, S. S.; MOURÃO JÚNIOR, M.; et al. Temporal variation of soil co2 efflux in oil palm-based agroforestry systems in eastern amazon. Acta Amazonica, v. 46, n. 1, p. 1–12, 2016.
STÖCKLI, R.; RUTISHAUSER, T.; BAKER, I.; LINIGER, M. A.; DENNING, A. S. A global reanalysis of vegetation phenology. Journal of Geophysical Research: Biogeosciences, v. 116, n. 3, p. 1–19, 2011.
______. RUTISHAUSER, T.; DRAGONI, D.; et al. Remote sensing data assimilation for a prognostic phenology model. Journal of Geophysical Research: Biogeosciences, v. 113, n. 4, p. 1–19, 2008.
SUITS, N. S.; DENNING, A. S.; BERRY, J. A.; et al. Simulation of carbon isotope discrimination of the terrestrial biosphere. Global Biogeochemical Cycles, v. 19, n. 1, p. 1–15, 2005. Disponível em: <http://doi.wiley.com/10.1029/2003GB002141>.
SULMAN, B. N.; DESAI, A. R.; SCHROEDER, N. M.; et al. Impact of hydrological variations on modeling of peatland CO 2 fluxes: Results from the North American Carbon Program site synthesis. Journal of Geophysical Research: Biogeosciences, v. 117, n. G1, p. 1–21, 2012. Disponível em: <http://doi.wiley.com/10.1029/2011JG001862>.
VAN DER VELDE, I. R.; MILLER, J. B.; SCHAEFER, K.; et al. Terrestrial cycling of 13CO2 by photosynthesis, respiration, and biomass burning in SiBCASA. Biogeosciences, v. 11, n. 23, p. 6553–6571, 2014. Disponível em: <https://bg.copernicus.org/articles/11/6553/2014/>.
VIDALE, P. L.; STÖCKLI, R. Prognostic canopy air space solutions for land surface exchanges. Theoretical and Applied Climatology, v. 80, n. 2–4, p. 245–257, 2005.
WALLWORK, A.; BANIN, L. F.; DENT, D. H.; SKIBA, U.; SAYER, E. Soil carbon storage is related to tree functional composition in naturally regenerating tropical forests. Functional Ecology, v. 36, n. 12, p. 3175–3187, 2022.
WANG, J.-W.; DENNING, A. S.; LU, L.; et al. Observations and simulations of synoptic, regional, and local variations in atmospheric CO 2. Journal of Geophysical Research, v. 112, n. D4, p. D04108, 2007. Disponível em: <http://doi.wiley.com/10.1029/2006JD007410>.
WANG, Y.; DEUTSCHER, N. M.; PALM, M.; et al. Towards understanding the variability in biospheric CO2 fluxes: using FTIR spectrometry and a chemical transport model to investigate the sources and sinks of carbonyl sulfide and its link to CO2. Atmospheric Chemistry and Physics, v. 16, n. 4, p. 2123–2138, 2016. Disponível em: <https://acp.copernicus.org/articles/16/2123/2016/>.
WILLIAMS, C. A.; HANAN, N. P. ENSO and IOD teleconnections for African ecosystems: evidence of destructive interference between climate oscillations. Biogeosciences, v. 8, n. 1, p. 27–40, 2011. Disponível em: <https://bg.copernicus.org/articles/8/27/2011/>.
______. HANAN, N. P.; BAKER, I.; et al. Interannual variability of photosynthesis across Africa and its attribution. Journal of Geophysical Research: Biogeosciences, v. 113, n. G4, p. 1–15, 2008. Disponível em: <http://doi.wiley.com/10.1029/2008JG000718>.
WILSON, N. R.; SHAW, R. H. A Higher Order Closure Model for Canopy Flow. Journal of Applied Meteorology, v. 16, n. 11, p. 1197–1205, 1977. Disponível em: <http://journals.ametsoc.org/doi/10.1175/1520-0450(1977)016<1197:AHOCMF>2.0.CO;2>.
WOLFE, G. M.; THORNTON, J. A. The Chemistry of Atmosphere-Forest Exchange (CAFE) Model - Part 1: Model description and characterization. Atmospheric Chemistry and Physics, v. 11, n. 1, p. 77–101, 2011.
XU, L.; PYLES, R. D.; PAW U, K. T.; et al. Impact of canopy representations on regional modeling of evapotranspiration using the WRF-ACASA coupled model. Agricultural and Forest Meteorology, v. 247, p. 79–92, 2017. Elsevier B.V.
ZUPANSKI, D.; DENNING, A. S.; ULIASZ, M.; et al. Carbon flux bias estimation employing Maximum Likelihood Ensemble Filter (MLEF). Journal of Geophysical Research Atmospheres, v. 112, n. 17, p. 1–18, 2007.
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