| Grant number: |
18/14423-4
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| Support type: | Scholarships in Brazil - Post-Doctorate |
| Effective date (Start): |
December 01, 2018
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| Status: | Discontinued |
| Field of knowledge: | Physical Sciences and Mathematics
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Geosciences |
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| Principal researcher: | Luciana Vanni Gatti |
| Grantee: | Henrique Luis Godinho Cassol |
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| Home Institution: |
Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). São José dos Campos , SP, Brazil
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| Associated research grant: | 16/02018-2 - Interannual variation of Amazon Basin greenhouse gas balances and their controls in a warming and increasingly variable climate – Carbam: the Amazon carbon balance long-term study,
AP.PFPMCG.TEM
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| Associated scholarship(s): | 20/02656-4 - Net carbon exchanges in the Amazon conciliating satellite data, ground data, and atmospheric profile in a decade of observation using bottom-up approach,
BE.EP.PD
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Abstract
Fires in tropical forests can be considered as one of the most important environmental problems of the XXI century. In the world's largest rainforest, the Amazon, the frequency of fires increased over the last decade as a result of climate variability (drought in 1998, 2005 and 2010) and anthropogenic activities (Aragão and Shimabukuro, 2010, Science). During the 2010 drought, 0.48±0.18 petagrams of carbon per year (PgCyr1) was released to the atmosphere by fires (e.g. Gatti et al. 2014, Nature). However a question is still unanswered: What are the main sources of fire emissions? Are these emissions a result of fires from fast turnover grassland vegetation, with minor impact on the overall atmospheric CO2 accumulation, or are they related to slow turnover forest vegetation, with potentially high impact on the atmospheric CO2 accumulation? It is well known that Amazonian fires can spread to undisturbed forests, causing forest fires and possibly contributing significantly to land use and land cover change component of carbon emissions. Despite being an important component of the global carbon balance, however, the magnitude of forest fire impacts on the long-term stability of carbon stocks are still poorly quantified.In the proposed fellowship the Post-doctoral researcher will use and refine the first systematic bottom-up model for quantifying annual gross carbon emissions from forests affected by fires at the Amazon biome scale. The model called Fire-Associated Transient Emissions from fires in Amazonia (FATE-Amazon) developed by a multidisciplinary research team coordinated by Dr Aragão at the National Institute for Space Research (INPE), was recently applied by Anderson et al. (2015). The model consist in a spatially explicit bookeeping model approach based on remote sensing data, for extracting information on biomass, burned area and land cover types, and empirically derived forest biomass loss due to fires. This model allows disentangling the sources of carbon released to the atmosphere from fires. These estimates will support a comprehensive interpretation and cross-validation of the atmospheric-based analysis of the Amazon carbon cycle.
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Scientific publications
(6)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
CASSOL, HENRIQUE L. G.;
DOMINGUES, LUCAS G.;
SANCHEZ, ALBER H.;
BASSO, LUANA S.;
MARANI, LUCIANO;
TEJADA, GRACIELA;
ARAI, EGIDIO;
CORREIA, CAIO;
ALDEN, CAROLINE B.;
MILLER, JOHN B.;
GLOOR, MANUEL;
ANDERSON, LIANA O.;
ARAGAO, LUIZ E. O. C.;
GATTI, LUCIANA V.
Determination of Region of Influence Obtained by Aircraft Vertical Profiles Using the Density of Trajectories from the HYSPLIT Model.
ATMOSPHERE,
v. 11,
n. 10
OCT 2020.
Web of Science Citations: 0.
SHIMABUKURO, YOSIO EDEMIR;
ARAI, EGIDIO;
DUARTE, VALDETE;
DUTRA, ANDEISE CERQUEIRA;
GODINHO CASSOL, HENRIQUE LUIS;
SANO, EDSON EYJI;
HOFFMANN, TANIA BEATRIZ.
Discriminating Land Use and Land Cover Classes in Brazil Based on the Annual PROBA-V 100 m Time Series.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,
v. 13,
p. 3409-3420,
2020.
Web of Science Citations: 0.