Fire has a diverse range of impacts on Earth's physical and social systems. Accurate and up to date information on areas affected by fire is critical to better understand drivers of fire activity, as ...well as its relevance for biogeochemical cycles, climate, air quality, and to aid fire management. Mapping burned areas was traditionally done from field sketches. With the launch of the first Earth observation satellites, remote sensing quickly became a more practical alternative to detect burned areas, as they provide timely regional and global coverage of fire occurrence. This review paper explores the physical basis to detect burned area from satellite observations, describes the historical trends of using satellite sensors to monitor burned areas, summarizes the most recent approaches to map burned areas and evaluates the existing burned area products (both at global and regional scales). Finally, it identifies potential future opportunities to further improve burned area detection from Earth observation satellites.
•A review of burned area trends in past 40 years of RS is performed.•Different sensors used for BA mapping presented, including Radar and Lidar.•Main burned area products are commented
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Several different inventories of global and regional anthropogenic and biomass burning emissions are assessed for the 1980–2010 period. The species considered in this study are carbon monoxide, ...nitrogen oxides, sulfur dioxide and black carbon. The inventories considered include the ACCMIP historical emissions developed in support of the simulations for the IPCC AR5 assessment. Emissions for 2005 and 2010 from the Representative Concentration Pathways (RCPs) are also included. Large discrepancies between the global and regional emissions are identified, which shows that there is still no consensus on the best estimates for surface emissions of atmospheric compounds. At the global scale, anthropogenic emissions of CO, NO
x
and SO
2
show the best agreement for most years, although agreement does not necessarily mean that uncertainty is low. The agreement is low for BC emissions, particularly in the period prior to 2000. The best consensus is for NO
x
emissions for all periods and all regions, except for China, where emissions in 1980 and 1990 need to be better defined. Emissions of CO need better quantification in the USA and India for all periods; in Central Europe, the evolution of emissions during the past two decades needs to be better determined. The agreement between the different SO
2
emissions datasets is rather good for the USA, but better quantification is needed elsewhere, particularly for Central Europe, India and China. The comparisons performed in this study show that the use of RCP8.5 for the extension of the ACCMIP inventory beyond 2000 is reasonable, until more global or regional estimates become available. Concerning biomass burning emissions, most inventories agree within 50–80%, depending on the year and season. The large differences between biomass burning inventories are due to differences in the estimates of burned areas from the different available products, as well as in the amount of biomass burned.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Scientific data should be published in a way so that other scientists can benefit from these data, enabling further research. The FAIR Data Principles are defining the basic prerequisite for a good ...data publication: data should be Findable, Accessible, Interoperable, and Reusable. Increasingly, research communities are developing discipline-specific data publication standards under consideration of the FAIR Data Principles. A very comprehensive yet strict data standard has been developed for the climate model output within the Climate Model Intercomparison Project (CMIP), which largely builds upon the Climate and Forecast Metadata Conventions (CF conventions). There are, however, many areas of atmospheric modelling where data cannot be standardised according to the CMIP data standard because, e.g., the data contain specific variables which are not covered by the CMIP standard. Furthermore, fulfilling the strict CMIP data standard for smaller Model Intercomparison Projects (MIPs) requires much effort (in time and manpower) and hence the outcome of these MIPs often remains non-standardised. For innovative model diagnostics, preexisting standards are also not flexible enough. For that reason, the ATMODAT standard, a quality guideline for atmospheric model data, was created. The ATMODAT standard defines a set of requirements that aim at ensuring the high reusability of atmospheric model data publications. The requirements include the use of the netCDF file format, the application of the CF conventions, rich and standardised file metadata, and the publication of the data with a DataCite DOI. Additionally, a tool for checking the conformity of data and metadata to this standard, the atmodat data checker, was developed and is available on GitHub under an open licence. By using the more flexible ATMODAT standard, the publication of standardised datasets is simplified for smaller MIPs. This standardisation process is presented as an example using the data of an aerosol-climate model from the AeroCOM MIP. Furthermore, the landing pages of ATMODAT-compliant data publications can be highlighted with the EASYDAB logo. EASYDAB (Earth System Data Branding) is a newly developed quality label for carefully curated and highly standardised data publications. The ATMODAT data standardisation can easily be transferred to data from other disciplines and contribute to their improved reusability.
In many regions of the world, fires are an important and highly variable source of air pollutant emissions, and they thus constitute a significant if not dominant factor controlling the interannual ...variability of the atmospheric composition. This paper describes the 41‐year inventory of vegetation fire emissions constructed for the Reanalysis of the Tropospheric chemical composition over the past 40 years project (RETRO), a global modeling study to investigate the trends and variability of tropospheric ozone and other air pollutants over the past decades. It is the first attempt to construct a global emissions data set with monthly time resolution over such a long period. The inventory is based on a literature review, on estimates from different satellite products, and on a numerical model with a semiphysical approach to simulate fire occurrence and fire spread. Burned areas, carbon consumption, and total carbon release are estimated for 13 continental‐scale regions, including explicit treatment of some major burning events such as Indonesia in 1997 and 1998. Global carbon emissions from this inventory range from 1410 to 3140 Tg C/a with the minimum and maximum occurring in 1974 and 1992, respectively (mean of 2078 Tg C/a). Emissions of other species are also reported (mean CO of 330 Tg/a, NOx of 4.6 Tg N/a, CH2O of 3.9 Tg/a, CH4 of 15.4 Tg/a, BC of 2.2 Tg/a, OC of 17.6 Tg/a, SO2 of 2.2 Tg/a). The uncertainties of these estimates remain high even for later years where satellite data products are available. Future versions of this inventory may benefit from ongoing analysis of burned areas from satellite data going back to 1982.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Aim This paper presents a new global burned area (BA) product developed within the framework of the European Space Agency's Climate Change Initiative (CCI) programme, along with a first assessment of ...its potentials for atmospheric and carbon cycle modelling. Innovation Methods are presented for generating a new global BA product, along with a comparison with existing BA products, in terms of BA extension, fire size and shapes and emissions derived from biomass burnings. Main conclusions Three years of the global BA product were produced, accounting for a total BA of between 360 and 380 Mha year⁻¹. General omission and commission errors for BA were 0.76 and 0.64, but they decreased to 0.51 and 0.52, respectively, for sites with more than 10% BA. Intercomparison with other existing BA datasets found similar spatial and temporal trends, mainly with the BA included in the Global Fire Emissions Database (GFED4), although regional differences were found (particularly in the 2006 fires of eastern Europe). The simulated carbon emissions from biomass burning averaged 2.1 Pg C year⁻¹.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
We present and discuss a new dataset of gridded emissions covering the historical period (1850–2000) in decadal increments at a horizontal resolution of 0.5° in latitude and longitude. The primary ...purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models are used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.
Recent climate changes have increased fire-prone weather conditions in many
regions and have likely affected fire occurrence, which might impact ecosystem
functioning, biogeochemical cycles, and ...society. Prediction of how fire
impacts may change in the future is difficult because of the complexity of
the controls on fire occurrence and burned area. Here we aim to assess how
process-based fire-enabled dynamic global vegetation models (DGVMs) represent
relationships between controlling factors and burned area. We developed a
pattern-oriented model evaluation approach using the random forest (RF)
algorithm to identify emergent relationships between climate, vegetation, and
socio-economic predictor variables and burned area. We applied this approach
to monthly burned area time series for the period from 2005 to 2011 from satellite
observations and from DGVMs from the “Fire Modeling Intercomparison
Project” (FireMIP) that were run using a common protocol and forcing data sets. The
satellite-derived relationships indicate strong sensitivity to climate
variables (e.g. maximum temperature, number of wet days), vegetation
properties (e.g. vegetation type, previous-season plant productivity and leaf
area, woody litter), and to socio-economic variables (e.g. human population
density). DGVMs broadly reproduce the relationships with climate variables
and, for some models, with population density. Interestingly, satellite-derived responses
show a strong increase in burned area with an increase in previous-season leaf area index
and plant productivity in most fire-prone ecosystems, which was largely
underestimated by most DGVMs. Hence, our pattern-oriented model evaluation
approach allowed us to diagnose that vegetation effects on fire are a main
deficiency regarding fire-enabled dynamic global vegetation models' ability to accurately
simulate the role of fire under global environmental change.
Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between ...fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric CO.sub.2 concentration, population density, land-use change, lightning and climate.
The apparent decline in the global incidence of fire between 1996 and 2015, as measured by satellite-observations of burned area, has been related to socioeconomic and land use changes. However, ...recent decades have also seen changes in climate and vegetation that influence fire and fire-enabled vegetation models do not reproduce the apparent decline. Given that the satellite-derived burned area datasets are still relatively short (<20 years), this raises questions both about the robustness of the apparent decline and what causes it. We use two global satellite-derived burned area datasets and a data-driven fire model to (1) assess the spatio-temporal robustness of the burned area trends and (2) to relate the trends to underlying changes in temperature, precipitation, human population density and vegetation conditions. Although the satellite datasets and simulation all show a decline in global burned area over ~20 years, the trend is not significant and is strongly affected by the start and end year chosen for trend analysis and the year-to-year variability in burned area. The global and regional trends shown by the two satellite datasets are poorly correlated for the common overlapping period (2001-2015) and the fire model simulates changes in global and regional burned area that lie within the uncertainties of the satellite datasets. The model simulations show that recent increases in temperature would lead to increased burned area but this effect is compensated by increasing wetness or increases in population, both of which lead to declining burned area. Increases in vegetation cover and density associated with recent greening trends lead to increased burned area in fuel-limited regions. Our analyses show that global and regional burned area trends result from the interaction of compensating trends in controls of wildfire at regional scales.
Lagrangian particle dispersion models (LPDMs) in backward mode are widely used to quantify the impact of transboundary pollution on downwind sites. Most LPDM applications count particles with ...a technique that introduces a so-called footprint layer (FL) with constant height, in which passing air tracer particles are assumed to be affected by surface emissions. The mixing layer dynamics are represented by the underlying meteorological model. This particle counting technique implicitly assumes that the atmosphere is well mixed in the FL. We have performed backward trajectory simulations with the FLEXPART model starting at Cyprus to calculate the sensitivity to emissions of upwind pollution sources. The emission sensitivity is used to quantify source contributions at the receptor and support the interpretation of ground measurements carried out during the CYPHEX campaign in July 2014. Here we analyse the effects of different constant and dynamic FL height assumptions. The results show that calculations with FL heights of 100 and 300 m yield similar but still discernible results. Comparison of calculations with FL heights constant at 300 m and dynamically following the planetary boundary layer (PBL) height exhibits systematic differences, with daytime and night-time sensitivity differences compensating for each other. The differences at daytime when a well-mixed PBL can be assumed indicate that residual inaccuracies in the representation of the mixing layer dynamics in the trajectories may introduce errors in the impact assessment on downwind sites. Emissions from vegetation fires are mixed up by pyrogenic convection which is not represented in FLEXPART. Neglecting this convection may lead to severe over- or underestimations of the downwind smoke concentrations. Introducing an extreme fire source from a different year in our study period and using fire-observation-based plume heights as reference, we find an overestimation of more than 60 % by the constant FL height assumptions used for surface emissions. Assuming a FL that follows the PBL may reproduce the peak of the smoke plume passing through but erroneously elevates the background for shallow stable PBL heights. It might thus be a reasonable assumption for open biomass burning emissions wherever observation-based injection heights are not available.
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