Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
20 Dec 2021
Development and technical paper |
| 20 Dec 2021
| 20 Dec 2021
Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model
Department of Geography, University of California, Los Angeles, CA 90095,
USA
Yongkang Xue
Department of Geography, University of California, Los Angeles, CA 90095,
USA
Department of Atmospheric & Oceanic Sciences, University of California,
Los Angeles, CA 90095, USA
Department of Geography, University of California, Los Angeles, CA 90095,
USA
International Center for Climate and Environmental Sciences, Institute of
Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Gregory S. Okin
Department of Geography, University of California, Los Angeles, CA 90095,
USA
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A process-based plant Carbon (C)-Nitrogen (N) interface coupling framework has been developed, which mainly focuses on the plant resistance and N limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem-biogeochemical model and testing results show a general improvement in simulating plant properties with this framework.
Sandy P. Harrison, Roberto Villegas-Diaz, Esmeralda Cruz-Silva, Daniel Gallagher, David Kesner, Paul Lincoln, Yicheng Shen, Luke Sweeney, Daniele Colombaroli, Adam Ali, Chéïma Barhoumi, Yves Bergeron, Tatiana Blyakharchuk, Přemysl Bobek, Richard Bradshaw, Jennifer L. Clear, Sambor Czerwiński, Anne-Laure Daniau, John Dodson, Kevin J. Edwards, Mary E. Edwards, Angelica Feurdean, David Foster, Konrad Gajewski, Mariusz Gałka, Michelle Garneau, Thomas Giesecke, Graciela Gil Romera, Martin P. Girardin, Dana Hoefer, Kangyou Huang, Jun Inoue, Eva Jamrichová, Nauris Jasiunas, Wenying Jiang, Gonzalo Jiménez-Moreno, Monika Karpińska-Kołaczek, Piotr Kołaczek, Niina Kuosmanen, Mariusz Lamentowicz, Martin Lavoie, Fang Li, Jianyong Li, Olga Lisitsyna, José Antonio López-Sáez, Reyes Luelmo-Lautenschlaeger, Gabriel Magnan, Eniko Katalin Magyari, Alekss Maksims, Katarzyna Marcisz, Elena Marinova, Jenn Marlon, Scott Mensing, Joanna Miroslaw-Grabowska, Wyatt Oswald, Sebastián Pérez-Díaz, Ramón Pérez-Obiol, Sanna Piilo, Anneli Poska, Xiaoguang Qin, Cécile C. Remy, Pierre J. H. Richard, Sakari Salonen, Naoko Sasaki, Hieke Schneider, William Shotyk, Migle Stancikaite, Dace Šteinberga, Normunds Stivrins, Hikaru Takahara, Zhihai Tan, Liva Trasune, Charles E. Umbanhowar, Minna Väliranta, Jüri Vassiljev, Xiayun Xiao, Qinghai Xu, Xin Xu, Edyta Zawisza, Yan Zhao, Zheng Zhou, and Jordan Paillard
Earth Syst. Sci. Data, 14, 1109–1124, https://doi.org/10.5194/essd-14-1109-2022, https://doi.org/10.5194/essd-14-1109-2022, 2022
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We provide a new global data set of charcoal preserved in sediments that can be used to examine how fire regimes have changed during past millennia and to investigate what caused these changes. The individual records have been standardised, and new age models have been constructed to allow better comparison across sites. The data set contains 1681 records from 1477 sites worldwide.
Ye Liu, Yun Qian, and Larry K. Berg
Wind Energ. Sci., 7, 37–51, https://doi.org/10.5194/wes-7-37-2022, https://doi.org/10.5194/wes-7-37-2022, 2022
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Uncertainties in initial conditions (ICs) decrease the accuracy of wind speed forecasts. We find that IC uncertainties can alter wind speed by modulating the weather system. IC uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind speed forecast uncertainties. Wind forecast accuracy in the Columbia River Basin is confined by initial uncertainties in a few specific regions, providing useful information for more intense measurement and modeling studies.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Qian Li, Yongkang Xue, and Ye Liu
Hydrol. Earth Syst. Sci., 25, 2089–2107, https://doi.org/10.5194/hess-25-2089-2021, https://doi.org/10.5194/hess-25-2089-2021, 2021
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Most land surface models have difficulty in capturing the freeze–thaw cycle in the Tibetan Plateau and North China. This paper introduces a physically more realistic and efficient frozen soil module (FSM) into the SSiB3 model (SSiB3-FSM). A new and more stable semi-implicit scheme and a physics-based freezing–thawing scheme were applied, and results show that SSiB3-FSM can be used as an effective model for soil thermal characteristics at seasonal to decadal scales over frozen ground.
Yan Yu, Olga V. Kalashnikova, Michael J. Garay, Huikyo Lee, Myungje Choi, Gregory S. Okin, John E. Yorks, James R. Campbell, and Jared Marquis
Atmos. Chem. Phys., 21, 1427–1447, https://doi.org/10.5194/acp-21-1427-2021, https://doi.org/10.5194/acp-21-1427-2021, 2021
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Given the current uncertainties in the simulated diurnal variability of global dust mobilization and concentration, observational characterization of the variations in dust mobilization and concentration will provide a valuable benchmark for evaluating and constraining such model simulations. The current study investigates the diurnal cycle of dust loading across the global tropics, subtropics, and mid-latitudes by analyzing aerosol observations from the International Space Station.
Huilin Huang, Yongkang Xue, Fang Li, and Ye Liu
Geosci. Model Dev., 13, 6029–6050, https://doi.org/10.5194/gmd-13-6029-2020, https://doi.org/10.5194/gmd-13-6029-2020, 2020
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We developed a fire-coupled dynamic vegetation model that captures the spatial distribution, temporal variability, and especially the seasonal variability of fire regimes. The fire model is applied to assess the long-term fire impact on ecosystems and surface energy. We find that fire is an important determinant of the structure and function of the tropical savanna. By changing the vegetation composition and ecosystem characteristics, fire significantly alters surface energy balance.
Cited articles
Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R.,
Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S.,
Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R.,
Yue, C., and Randerson, J. T.: A human-driven decline in global burned area,
Science, 356, 1356–1361, https://doi.org/10.1126/science.aal4108, 2017.
Araújo, F. D. C., Tng, D. Y. P., Apgaua, D. M. G., Coelho, P. A.,
Pereira, D. G. S., and Santos, R. M.: Post-fire plant regeneration across a
closed forest-savanna vegetation transition, Forest Ecol. Manag., 400, 77–84,
https://doi.org/10.1016/j.foreco.2017.05.058, 2017.
Arora, V. K. and Boer, G. J.: Fire as an interactive component of dynamic
vegetation models, J. Geophys. Res.-Biogeo., 110, G02008, https://doi.org/10.1029/2005jg000042, 2005.
Bartholome, E. and Belward, A. S.: GLC2000: a new approach to global land
cover mapping from Earth observation data, Int. J. Remote Sens., 26, 1959–1977,
2005.
Beringer, J., Hutley, L. B., Tapper, N. J., Coutts, A., Kerley, A., and
O'Grady, A. P.: Fire impacts on surface heat, moisture and carbon fluxes
from a tropical savanna in northern Australia, Int. J. Wildland Fire, 12,
333–340, https://doi.org/10.1071/Wf03023, 2003.
Bistinas, I., Harrison, S. P., Prentice, I. C., and Pereira, J. M. C.: Causal relationships versus emergent patterns in the global controls of fire frequency, Biogeosciences, 11, 5087–5101, https://doi.org/10.5194/bg-11-5087-2014, 2014.
Bond, W. J. and Midgley, G. F.: Carbon dioxide and the uneasy interactions
of trees and savannah grasses, Philos T. R. Soc. B, 367, 601–612,
https://doi.org/10.1098/rstb.2011.0182, 2012.
Bond, W. J., Woodward, F. I., and Midgley, G. F.: The global distribution of
ecosystems in a world without fire, New Phytol., 165, 525–537,
https://doi.org/10.1111/j.1469-8137.2004.01252.x, 2005.
Bond-Lamberty, B., Peckham, S. D., Gower, S. T., and Ewers, B. E.: Effects
of fire on regional evapotranspiration in the central Canadian boreal
forest, Global Change Biol., 15, 1242–1254, https://doi.org/10.1111/j.1365-2486.2008.01776.x,
2009.
Bowman, D. M., Balch, J. K., Artaxo, P., Bond, W. J., Carlson, J. M.,
Cochrane, M. A., D'Antonio, C. M., Defries, R. S., Doyle, J. C., Harrison,
S. P., Johnston, F. H., Keeley, J. E., Krawchuk, M. A., Kull, C. A.,
Marston, J. B., Moritz, M. A., Prentice, I. C., Roos, C. I., Scott, A. C.,
Swetnam, T. W., van der Werf, G. R., and Pyne, S. J.: Fire in the Earth
system, Science, 324, 481–484, https://doi.org/10.1126/science.1163886, 2009.
Burton, C., Betts, R., Cardoso, M., Feldpausch, T. R., Harper, A., Jones, C. D., Kelley, D. I., Robertson, E., and Wiltshire, A.: Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES), Geosci. Model Dev., 12, 179–193, https://doi.org/10.5194/gmd-12-179-2019, 2019.
Chambers, S. D. and Chapin, F. S.: Fire effects on surface-atmosphere energy
exchange in Alaskan black spruce ecosystems: Implications for feedbacks to
regional climate, J. Geophys. Res.-Atmos., 107, 8145, https://doi.org/10.1029/2001jd000530, 2002.
CIESIN (Center for International Earth Science Information Network): Gridded population of the world version 3(GPWv3): Population density grids, Technical report, Socioeconomic Data and Applications Center (SEDAC), Columbia University, Palisades, New York, USA, available at: http://sedac.ciesin.columbia.edu/gpw (last access: July 2019), 2005.
Cochrane, M. A., Alencar, A., Schulze, M. D., Souza, C. M., Nepstad, D. C.,
Lefebvre, P., and Davidson, E. A.: Positive feedbacks in the fire dynamic of
closed canopy tropical forests, Science, 284, 1832–1835, 1999.
Cox, P.: Description of the “TRIFFID” Dynamic Global Vegetation Model, Hadley Centre technical note 24, Hadley Centre, Exeter, UK, 1–16, 2001.
das Chagas, D. and Pelicice, F.: Response of vegetation to fire disturbance:
short-term dynamics in two savanna physiognomies, Community Ecol., 19,
211–222, 2018.
De Sales, F., Xue, Y. K., and Okin, G. S.: Impact of burned areas on the
northern African seasonal climate from the perspective of regional modeling,
Clim. Dynam., 47, 3393–3413, https://doi.org/10.1007/s00382-015-2522-4, 2016.
De Sales, F., Okin, G. S., Xue, Y., and Dintwe, K.: On the effects of
wildfires on precipitation in Southern Africa, Clim. Dynam., 52, 951–967, https://doi.org/10.1007/s00382-018-4174-7, 2018.
Dintwe, K., Okin, G. S., and Xue, Y. K.: Fire-induced albedo change and
surface radiative forcing in sub-Saharan Africa savanna ecosystems:
Implications for the energy balance, J. Geophys. Res.-Atmos., 122, 6186–6201,
https://doi.org/10.1002/2016jd026318, 2017.
Dunin, F. X.: Run-off and drainage from grassland catchments, in: Managed Grasslands, B. Analytical Studies, edited by: Snaydon, R. W., 205–213, https://doi.org/102.100.100/269549?index=1, 1987.
Forkel, M., Andela, N., Harrison, S. P., Lasslop, G., van Marle, M., Chuvieco, E., Dorigo, W., Forrest, M., Hantson, S., Heil, A., Li, F., Melton, J., Sitch, S., Yue, C., and Arneth, A.: Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models, Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, 2019.
Furley, P. A., Rees, R. M., Ryan, C. M., and Saiz, G.: Savanna burning and
the assessment of long-term fire experiments with particular reference to
Zimbabwe, Prog. Phys. Geog., 32, 611–634, 2008.
Gatebe, C. K., Ichoku, C. M., Poudyal, R., Roman, M. O., and Wilcox, E.:
Surface albedo darkening from wildfires in northern sub-Saharan Africa,
Environ. Res. Lett., 9, 065003, https://doi.org/10.1088/1748-9326/9/6/065003, 2014.
Gholz, H. L. and Clark, K. L.: Energy exchange across a chronosequence of
slash pine forests in Florida, Agr. Forest Meteorol., 112, 87–102, 2002.
Giglio, L., Randerson, J. T., and van der Werf, G. R.: Analysis of daily,
monthly, and annual burned area using the fourth-generation global fire
emissions database (GFED4), J. Geophys. Res.-Biogeo., 118, 317–328,
https://doi.org/10.1002/jgrg.20042, 2013.
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., and Justice, C. O.:
The Collection 6 MODIS burned area mapping algorithm and product, Remote
Sens. Environ., 217, 72–85, https://doi.org/10.1016/j.rse.2018.08.005, 2018.
Goldewijk, K. K., Beusen, A., and Janssen, P.: Long-term dynamic modeling of global population and built-up area in a spatially explicit way: HYDE 3.1, Holocene, 20, 565–573, 2010.
Govaerts, Y. M., Pereira, J. M., Pinty, B., and Mota, B.: Impact of fires on
surface albedo dynamics over the African continent, J. Geophys.
Res.-Atmos., 107, ACL 8-1–ACL 8-12, https://doi.org/10.1029/2002JD002388, 2002.
Hamilton, D. S., Hantson, S., Scott, C. E., Kaplan, J. O., Pringle, K. J.,
Nieradzik, L. P., Rap, A., Folberth, G. A., Spracklen, D. V., and Carslaw,
K. S.: Reassessment of pre-industrial fire emissions strongly affects
anthropogenic aerosol forcing, Nat. Commun., 9, 3182, https://doi.org/10.1038/s41467-018-05592-9,
2018.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A.,
Tyukavina, A., Thau, D., Stehman, S., Goetz, S. J., and Loveland, T. R.:
High-resolution global maps of 21st-century forest cover change, Science,
342, 850–853, 2013.
Hantson, S., Kelley, D. I., Arneth, A., Harrison, S. P., Archibald, S., Bachelet, D., Forrest, M., Hickler, T., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Nieradzik, L., Rabin, S. S., Prentice, I. C., Sheehan, T., Sitch, S., Teckentrup, L., Voulgarakis, A., and Yue, C.: Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project, Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, 2020.
Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C. D., Sitch, S., Mercado, L. M., Groenendijk, M., Robertson, E., Kattge, J., Bönisch, G., Atkin, O. K., Bahn, M., Cornelissen, J., Niinemets, Ü., Onipchenko, V., Peñuelas, J., Poorter, L., Reich, P. B., Soudzilovskaia, N. A., and Bodegom, P. V.: Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information, Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, 2016.
hhllbao93: hhllbao93/SSiB4-TRIFFID-Fire: Release of SSiB4/TRIFFID-Fire v1.1 (v1.1), Zenodo [code], https://doi.org/10.5281/zenodo.4670922, 2021.
Higgins, S. I., Bond, W. J., and Trollope, W. S. W.: Fire, resprouting and
variability: a recipe for grass-tree coexistence in savanna, J. Ecol., 88,
213–229, https://doi.org/10.1046/j.1365-2745.2000.00435.x, 2000.
Higgins, S. I., Bond, W. J., February, E. C., Bronn, A., Euston-Brown, D. I.
W., Enslin, B., Govender, N., Rademan, L., O'Regan, S., Potgieter, A. L. F.,
Scheiter, S., Sowry, R., Trollope, L., and Trollope, W. S. W.: Effects of
four decades of fire manipulation on woody vegetation structure in savanna,
Ecology, 88, 1119–1125, 2007.
Huang, H., Xue, Y., Li, F., and Liu, Y.: Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0, Geosci. Model Dev., 13, 6029–6050, https://doi.org/10.5194/gmd-13-6029-2020, 2020a.
Huang, H., Xue, Y., Chilukoti, N., Liu, Y., Chen, G., and Diallo, I.:
Assessing Global and Regional Effects of Reconstructed Land-Use and
Land-Cover Change on Climate since 1950 Using a Coupled
Land–Atmosphere–Ocean Model, J. Climate, 33, 8997–9013, 2020b.
Huang, H.: Data for “Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa”, Zenodo [data set], https://doi.org/10.5281/zenodo.5778443, 2021.
Hurtt, G. C., Frolking, S., Fearon, M. G., Moore, B., Shevliakova, E.,
Malyshev, S., Pacala, S. W., and Houghton, R. A.: The underpinnings of
land-use history: three centuries of global gridded land-use transitions,
wood-harvest activity, and resulting secondary lands, Global Change Biol.,
12, 1208–1229, https://doi.org/10.1111/j.1365-2486.2006.01150.x, 2006.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J.,
Fischer, G., Fisk, J. P., Hibbard, K., Houghton, R. A., Janetos, A., Jones,
C. D., Kindermann, G., Kinoshita, T., Goldewijk, K. K., Riahi, K.,
Shevliakova, E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., van
Vuuren, D. P., and Wang, Y. P.: Harmonization of land-use scenarios for the
period 1500-2100: 600 years of global gridded annual land-use transitions,
wood harvest, and resulting secondary lands, Climatic Change, 109, 117–161,
https://doi.org/10.1007/s10584-011-0153-2, 2011.
Jiang, Y., Lu, Z., Liu, X., Qian, Y., Zhang, K., Wang, Y., and Yang, X.-Q.: Impacts of global open-fire aerosols on direct radiative, cloud and surface-albedo effects simulated with CAM5, Atmos. Chem. Phys., 16, 14805–14824, https://doi.org/10.5194/acp-16-14805-2016, 2016.
Jin, Y. and Roy, D. P.: Fire-induced albedo change and its radiative
forcing at the surface in northern Australia, Geophys. Res. Lett., 32, L13401, https://doi.org/10.1029/2005GL022822, 2005.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D., Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J. Q., 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.-Biogeo., 116, G00J07, https://doi.org/10.1029/2010JG001566, 2011.
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G.,
Papale, D., Schwalm, C., Tramontana, G., and Reichstein, M.: The FLUXCOM
ensemble of global land-atmosphere energy fluxes, Scientific Data, 6, 74,
https://doi.org/10.1038/s41597-019-0076-8, 2019.
Lasslop, G. and Kloster, S.: Human impact on wildfires varies between
regions and with vegetation productivity, Environ. Res. Lett., 12, 115011, https://doi.org/10.1088/1748-9326/aa8c82,
2017.
Lasslop, G., Thonicke, K., and Kloster, S.: SPITFIRE within the MPI Earth
system model: Model development and evaluation, J. Adv. Model Earth Sy., 6,
740–755, https://doi.org/10.1002/2013ms000284, 2014.
Lasslop, G., Hantson, S., Harrison, S. P., Bachelet, D., Burton, C., Forkel,
M., Forrest, M., Li, F., Melton, J. R., Yue, C., Archibald, S., Scheiter,
S., Arneth, A., Hickler, T., and Sitch, S.: Global ecosystems and fire:
Multi-model assessment of fire-induced tree-cover and carbon storage
reduction, Glob. Change Biol., 26, 5027–5041, https://doi.org/10.1111/gcb.15160, 2020.
Lenihan, J. M., Daly, C., Bachelet, D., and Neilson, R. P.: Simulating
broad-scale fire severity in a dynamic global vegetation model, Northwest
Sci., 72, 91–101, 1998.
Li, F. and Lawrence, D. M.: Role of Fire in the Global Land Water Budget
during the Twentieth Century due to Changing Ecosystems, J. Climate, 30,
1893–1908, https://doi.org/10.1175/Jcli-D-16-0460.1, 2017.
Li, F., Bond-Lamberty, B., and Levis, S.: Quantifying the role of fire in the Earth system – Part 2: Impact on the net carbon balance of global terrestrial ecosystems for the 20th century, Biogeosciences, 11, 1345–1360, https://doi.org/10.5194/bg-11-1345-2014, 2014.
Li, F., Zeng, X. D., and Levis, S.: A process-based fire parameterization of intermediate complexity in a Dynamic Global Vegetation Model, Biogeosciences, 9, 2761–2780, https://doi.org/10.5194/bg-9-2761-2012, 2012.
Li, F., Lawrence, D. M., and Bond-Lamberty, B.: Impact of fire on global land surface air temperature and energy budget for the 20th century due to changes within ecosystems, Environ. Res. Lett., 12, 044014, https://doi.org/10.1088/1748-9326/aa6685, 2017.
Li, F., Val Martin, M., Andreae, M. O., Arneth, A., Hantson, S., Kaiser, J. W., Lasslop, G., Yue, C., Bachelet, D., Forrest, M., Kluzek, E., Liu, X., Mangeon, S., Melton, J. R., Ward, D. S., Darmenov, A., Hickler, T., Ichoku, C., Magi, B. I., Sitch, S., van der Werf, G. R., Wiedinmyer, C., and Rabin, S. S.: Historical (1700–2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP), Atmos. Chem. Phys., 19, 12545–12567, https://doi.org/10.5194/acp-19-12545-2019, 2019.
Li, W., Du, J., Li, S., Zhou, X., Duan, Z., Li, R., Wu, S., Wang, S., and
Li, M.: The variation of vegetation productivity and its relationship to
temperature and precipitation based on the GLASS-LAI of different African
ecosystems from 1982 to 2013, Int. J. Biometeorol., 63,
847–860, 2019.
Liu, Y., Guo, W. D., and Song, Y. M.: Estimation of key surface parameters
in semi-arid region and their impacts on improvement of surface fluxes
simulation, Sci. China Earth Sci., 59, 307–319, https://doi.org/10.1007/s11430-015-5140-4,
2016.
Liu, Y., Xue, Y., MacDonald, G., Cox, P., and Zhang, Z.: Global vegetation variability and its response to elevated CO2, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data, Earth Syst. Dynam., 10, 9–29, https://doi.org/10.5194/esd-10-9-2019, 2019.
Liu, Z. H., Ballantyne, A. P., and Cooper, L. A.: Biophysical feedback of
global forest fires on surface temperature, Nat. Commun., 10, 214, https://doi.org/10.1038/s41467-018-08237-z, 2019.
López-Saldaña, G., Bistinas, I., and Pereira, J. M. C.: Global analysis of radiative forcing from fire-induced shortwave albedo change, Biogeosciences, 12, 557–565, https://doi.org/10.5194/bg-12-557-2015, 2015.
Lyons, E. A., Jin, Y. F., and Randerson, J. T.: Changes in surface albedo
after fire in boreal forest ecosystems of interior Alaska assessed using
MODIS satellite observations, J. Geophys. Res.-Biogeo., 113, G02012,
https://doi.org/10.1029/2007jg000606, 2008.
Myhre, G., Govaerts, Y., Haywood, J. M., Berntsen, T. K., and Lattanzio, A.:
Radiative effect of surface albedo change from biomass burning, Geophys. Res.
Lett., 32, L20812, https://doi.org/10.1029/2005gl022897, 2005.
Pfeiffer, M., Spessa, A., and Kaplan, J. O.: A model for global biomass burning in preindustrial time: LPJ-LMfire (v1.0), Geosci. Model Dev., 6, 643–685, https://doi.org/10.5194/gmd-6-643-2013, 2013.
Rabin, S. S., Ward, D. S., Malyshev, S. L., Magi, B. I., Shevliakova, E., and Pacala, S. W.: A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1, Geosci. Model Dev., 11, 815–842, https://doi.org/10.5194/gmd-11-815-2018, 2018.
Randerson, J. T., Chen, Y., van der Werf, G. R., Rogers, B. M., and Morton, D. C.: Global burned area and biomass burning emissions from small fires, J. Geophys. Res.-Biogeo., 117, G04012, https://doi.org/10.1029/2012jg002128, 2012.
Saha, M. V., Scanlon, T. M., and D'Odorico, P.: Suppression of rainfall by
fires in African drylands, Geophys. Res. Lett., 43, 8527–8533,
https://doi.org/10.1002/2016gl069855, 2016.
Saha, M. V., D'Odorico, P., and Scanlon, T. M.: Albedo changes after fire as
an explanation of fire-induced rainfall suppression, Geophys. Res. Lett., 44,
3916–3923, https://doi.org/10.1002/2017gl073623, 2017.
Saha, M. V., D'Odorico, P., and Scanlon, T. M.: Kalahari Wildfires Drive
Continental Post-Fire Brightening in Sub-Saharan Africa, Remote Sens.-Basel,
11, 1090, https://doi.org/10.3390/rs11091090, 2019.
Samain, O., Kergoat, L., Hiernaux, P., Guichard, F., Mougin, E., Timouk, F.,
and Lavenu, F.: Analysis of the in situ and MODIS albedo variability at
multiple timescales in the Sahel, J. Geophys. Res.-Atmos., 113, D14119, https://doi.org/10.1029/2007JD009174, 2008.
Sankaran, M., Ratnam, J., and Hanan, N.: Woody cover in African savannas:
the role of resources, fire and herbivory, Global Ecol. Biogeogr.,
17, 236–245, 2008.
Scholes, R. J., Ward, D. E., and Justice, C. O.: Emissions of trace gases
and aerosol particles due to vegetation burning in southern hemisphere
Africa, J. Geophys. Res.-Atmos., 101, 23677–23682, https://doi.org/10.1029/95jd02049, 1996.
Schulze, E. D., Kelliher, F. M., Korner, C., Lloyd, J., and Leuning, R.:
Relationships among Maximum Stomatal Conductance, Ecosystem Surface
Conductance, Carbon Assimilation Rate, and Plant Nitrogen Nutrition – a
Global Ecology Scaling Exercise, Annu. Rev. Ecol. Syst., 25, 629–662, https://doi.org/10.1146/annurev.es.25.110194.003213, 1994.
Seo, H. and Kim, Y.: Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5, Geosci. Model Dev., 12, 457–472, https://doi.org/10.5194/gmd-12-457-2019, 2019.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-year
high-resolution global dataset of meteorological forcings for land surface
modeling, J. Climate, 19, 3088–3111, https://doi.org/10.1175/Jcli3790.1, 2006.
Staal, A., van Nes, E. H., Hantson, S., Holmgren, M., Dekker, S. C., Pueyo,
S., Xu, C., and Scheffer, M.: Resilience of tropical tree cover: The roles
of climate, fire, and herbivory, Global Change Biol., 24, 5096–5109, 2018.
Staver, A. C., Archibald, S., and Levin, S. A.: The Global Extent and
Determinants of Savanna and Forest as Alternative Biome States, Science,
334, 230–232, https://doi.org/10.1126/science.1210465, 2011.
Thonicke, K., Venevsky, S., Sitch, S., and Cramer, W.: The role of fire
disturbance for global vegetation dynamics: coupling fire into a Dynamic
Global Vegetation Model, Global Ecol. Biogeogr., 10, 661–677, https://doi.org/10.1046/j.1466-822x.2001.00175.x, 2001.
Thonicke, K., Spessa, A., Prentice, I. C., Harrison, S. P., Dong, L., and Carmona-Moreno, C.: The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model, Biogeosciences, 7, 1991–2011, https://doi.org/10.5194/bg-7-1991-2010, 2010.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Kasibhatla, P. S., and Arellano Jr., A. F.: Interannual variability in global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6, 3423–3441, https://doi.org/10.5194/acp-6-3423-2006, 2006.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M., Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., and van Leeuwen, T. T.: Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10, 11707–11735, https://doi.org/10.5194/acp-10-11707-2010, 2010.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
van Vuuren, D. P., Lucas, P. L., and Hilderink, H.: Downscaling
drivers of global environmental change: Enabling use of global
SRES scenarios at the national and grid levels, Global Environ.
Chang., 17, 114–130, 2007.
Venevsky, S., Thonicke, K., Sitch, S., and Cramer, W.: Simulating fire
regimes in human-dominated ecosystems: Iberian Peninsula case study, Glob.
Change Biol., 8, 984–998, https://doi.org/10.1046/j.1365-2486.2002.00528.x, 2002.
Venevsky, S., Le Page, Y., Pereira, J. M. C., and Wu, C.: Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations, Geosci. Model Dev., 12, 89–110, https://doi.org/10.5194/gmd-12-89-2019, 2019.
Veraverbeke, S., Verstraeten, W. W., Lhermitte, S., Van de Kerchove, R., and
Goossens, R.: Assessment of post-fire changes in land surface temperature
and surface albedo, and their relation with fire-burn severity using
multitemporal MODIS imagery, Int. J. Wildland Fire, 21, 243–256, 2012.
Ward, D. S., Kloster, S., Mahowald, N. M., Rogers, B. M., Randerson, J. T., and Hess, P. G.: The changing radiative forcing of fires: global model estimates for past, present and future, Atmos. Chem. Phys., 12, 10857–10886, https://doi.org/10.5194/acp-12-10857-2012, 2012.
Wendt, C. K., Beringer, J., Tapper, N. J., and Hutley, L. B.: Local
boundary-layer development over burnt and unburnt tropical savanna: an
observational study, Bound.-Lay. Meteorol., 124, 291–304, 2007.
Xue, Y., Sellers, P. J., Kinter, J. L., and Shukla, J.: A Simplified
Biosphere Model for Global Climate Studies, J. Climate, 4, 345–364,
https://doi.org/10.1175/1520-0442(1991)004<0345:asbmfg>2.0.co;2, 1991.
Yue, C., Ciais, P., Cadule, P., Thonicke, K., and van Leeuwen, T. T.: Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 2: Carbon emissions and the role of fires in the global carbon balance, Geosci. Model Dev., 8, 1321–1338, https://doi.org/10.5194/gmd-8-1321-2015, 2015.
Zhan, X. W., Xue, Y. K., and Collatz, G. J.: An analytical approach for
estimating CO2 and heat fluxes over the Amazonian region, Ecol. Model., 162,
97–117, 2003.
Zhang, Z., Xue, Y., MacDonald, G., Cox, P. M., and Collatz, G. J.:
Investigation of North American vegetation variability under recent climate:
A study using the SSiB4/TRIFFID biophysical/dynamic vegetation model,
J. Geophys. Res.-Atmos., 120, 1300–1321, 2015.
Zou, Y., Wang, Y., Qian, Y., Tian, H., Yang, J., and Alvarado, E.: Using CESM-RESFire to understand climate–fire–ecosystem interactions and the implications for decadal climate variability, Atmos. Chem. Phys., 20, 995–1020, https://doi.org/10.5194/acp-20-995-2020, 2020.
Short summary
This study applies a fire-coupled dynamic vegetation model to quantify fire impact at monthly to annual scales. We find fire reduces grass cover by 4–8 % annually for widespread areas in south African savanna and reduces tree cover by 1 % at the periphery of tropical Congolese rainforest. The grass cover reduction peaks at the beginning of the rainy season, which quickly diminishes before the next fire season. In contrast, the reduction of tree cover is irreversible within one growing season.
This study applies a fire-coupled dynamic vegetation model to quantify fire impact at monthly to...
