Additional geographical or spatial references datacite.geolocation	Amazon, Cerrado
Countries to which the data refer datacite.geolocation.iso3166	BRAZIL
Description of the data datacite.resourceType	The repository contains the following datasets: • S4F.CCILC_S4Fba_dynEF: The TUD-S4F default experiment computes dynamic emission factors and uses as input burned area data for the year 2020 from the GFA-S4F approach and for the other years from the ESA CCI fire (v5.1) dataset . • S4F.CCILC_S4Fba_fixEF: This experiment differs from S4F.CCILC_S4Fba_dynEF in the estimated emissions because it is based on fixed emission factors for forests and grasslands. Estimated fuel loads and fuel consumption are identical to S4F.CCILC_S4Fba_dynEF. • S4F.CCILC_FireCCI51: This experiment uses burned area from ESA's CCI fire (v5.1) dataset only and dynamic emission factors. • KNMI.S5p provides CO and NO emissions for all regions for 2020. Leite_Fuel_db: This dataset is an ancillary dataset (not produced within ESA Sense4Fire) and provides estimates of surface fuel loads from the Cerrado (Leite et al., 2022)
Type of the data datacite.resourceTypeGeneral	Dataset
Total size of the dataset datacite.size	1941879868693
Author dc.contributor.author	Forkel, Matthias
Author dc.contributor.author	Kinalczyk, Daniel
Author dc.contributor.author	Wessollek, Christine
Upload date dc.date.accessioned	2024-12-20T12:13:13Z
Publication date dc.date.available	2024-12-20T12:13:13Z
Publication date dc.date.issued	2024-12-20
Abstract of the dataset dc.description.abstract	This repository provides datasets of fuels and fire emissions for the Amazon and Cerrado that were derived and analysed in the publication by Forkel et al. (2024). This publication demonstrates the first application and benchmarking of the TUD.S4F and KNMI.S5p approaches to estimate fire emissions and to investigate the effects of woody debris on fire emissions. TUD.S4F, developed at TUD Dresden University of Technology, is a satellite data-model fusion approach that combines several satellite products to estimate fuel loads, fuel moisture, fuel consumption, and fire emissions. Emission factors are computed dynamically depending on fuel type and fuel composition. TUD.S4F (version 0.2) is described in the Methods and Supplementary material of Forkel et al. (2024) and the related model code is available here: https://doi.org/10.5281/zenodo.14274230. TUD-S4F provides fuel loads, fuel consumption and fire emissions at a spatial resolution of 333 x 333 m and aggregated to 0.1 x 0.1° for the Amazon/Cerrado for the period 2014-01-01 to 2021-10-20 at 10-daily time step. KNMI.S5p provides fire emission for carbon monoxide (CO) and nitrogen oxides (NO) derived from Sentinel-5p observations. The data is provided at 0.1 x 0.1° and at daily time step for the year 2020. Both TUD.S4F and KNMI.S5p are products of the Sense4Fire projected, awarded from the European Space Agency to TU Dresden, the Royal Dutch Meteorological Institute (KNMI) and BeZero Carbon Ltd.
Public reference to this page dc.identifier.uri	https://opara.zih.tu-dresden.de/handle/123456789/1166
Public reference to this page dc.identifier.uri	https://doi.org/10.25532/OPARA-688
Publisher dc.publisher	Technische Universität Dresden
Licence dc.rights	Attribution-NonCommercial 4.0 International	en
URI of the licence text dc.rights.uri	http://creativecommons.org/licenses/by-nc/4.0/
Specification of the discipline(s) dc.subject.classification	3::34::315::315-02
Title of the dataset dc.title	S4F: Fuel Loads, Fuel Moisture, Fuel Consumption and Fire Emissions for the Cerrado Amazon Region
Software opara.descriptionSoftware.ResourceProcessing	R
Software opara.descriptionSoftware.ResourceProduction	R
Project abstract opara.project.description	The Amazon forest is fire-sensitive but where fires were uncommon as a natural disturbance, deforestation and drought are accelerating fire occurrences, which threaten the integrity of the tropical forest, the carbon cycle, and air quality. Fire emissions depend on fuel amount and type, moisture conditions and burning behaviour. Higher resolution satellite data has helped more accurately map global burnt area, however, the effects of fuels on the combustion process and on the composition of fire emissions remain uncertain in current fire emission inventories. By using multiple Earth observation-based approaches, here we show that total fire emissions in the Amazon and Cerrado biomes are dominated by smouldering combustion of woody debris. The representation of woody debris and surface litter presents a critical uncertainty in fire emission inventories and global vegetation models. For the fire season 1st August to 31st October 2020, for which all approaches are available, we quantify Tg dry matter burnt, corresponding to carbon monoxide emissions of Tg CO. Our results emphasise how Earth observation approaches for fuel and fire dynamics and of atmospheric trace gases reduce uncertainties of fire emission estimates. The findings enable diagnosing the representation of fuels, wildfire combustion and its effects on atmospheric composition and the carbon cycle in global vegetation-fire models.
Public project website(s) opara.project.publicReference	https://sense4fire.eu/
Project title opara.project.title	Sense4Fire

S4F: Fuel Loads, Fuel Moisture, Fuel Consumption and Fire Emissions for the Cerrado Amazon Region

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