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.17.15769Palabras clave:
Fluxos de energia; Modelagem; Vegetação; Superfície-Atmosfera.Resumen
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.
Descargas
Citas
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.
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Esta obra está bajo una licencia internacional Creative Commons Atribución-CompartirIgual 4.0.
Os Autores dos trabalhos aceitos para publicação na revista CONTEXTO GEOGRÁFICO devem concordar com os termos a seguir: a) Autores mantém os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho licenciado sob a Creative Commons Atribuição-NãoComercial-SemDerivações 4.0 Internacional; b) Autores têm permissão e são estimulados a publicar e distribuir seu trabalho online;e c) Considerando que o acesso a revista é público, os artigos publicados são de uso gratuito, com atribuições próprias, em aplicações educacionais e não-comerciais.