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The current generation of geostationary Earth-observing satellites provide spectral bandpass, spatial resolution and imaging frequency characteristics well suited to near-continuous active fire detection and monitoring. The earliest of these systems-SEVIRI on-board EUMETSAT’s MSG series-has operated since 2004, and more recently the capability has been expanded globally with the ABI on-board NOAA’s GOES-16 and GOES-17 satellites, and the AHI on-board JMA’s Himawari-8 and Himawari-9. At present, the NOAA and EUMETSAT operational geostationary active fire products are available based on two different algorithms: the Fire Detection and Characterization (FDC) product operating with data from GOES-16 and −17, and FRP-PIXEL active fire products from GOES, Himawari and MSG. We have conducted a comprehensive accuracy assessment of these geostationary fire products across two seasons (1 January–31 March 2020 and 1 July–30 September 2020), based on comparison to Landsat active fire detections made simultaneously (±5 minutes of geostationary overpass time) with the geostationary data. Compared to Landsat we find (i) low false alarm rates, ranging between 4%–7% (FDC) and 2%-6% (FRP-PIXEL)- depending on the season and hemispheric-disk for high confidence pixels, (ii) a reduction in this false alarm rate for FDC due to algorithm changes made since our prior (2018) validation effort (48% false alarms in summer 2018 compared to 4% in summer 2020 for high confidence pixels), and (iii) comparable active fire pixel detection rates for the FDC product (high confidence fire pixel classes only) and the matching FRP-PIXEL product (all fire pixel confidence classes). Overall, the performance of these geostationary products is shown to be strong and complementary in that the FRP-PIXEL product has fewer false alarms but a lower detection rate, whereas the FDC product detects more fire pixels but with a much higher false alarm rate.

Infrared surface spectral emissivity is a fundamental property of terrestrial materials, important in a host of environmental applications ranging from mineral mapping to land cover change determination, and in particular the remote sensing of land surface temperature (LST). Surface spectral emissivity has also been used to inform the chemical and physical composition determination of terrestrial and planetary materials. Multiple laboratories have now developed facilities for determining the surface spectral emissivity of samples from reflected infrared radiation measurements (making use of Kirchhoff’s Law), with the results often made publicly available such as in the ECOSTRESS (Ecosystem Thermal Radiometer Experiment on Space Station) spectral library. However, until now there has been relatively little work conducted in evaluating the uncertainties in these types of measurements and the consistency of measurements made in different laboratories. Here we intercompare surface spectral emissivity measurements in a ‘round-robin’ exercise using identical samples at 7 different international laboratories. During this exercise, 4cm-1 spectral resolution emissivity spectra were determined for three samples: distilled water, which has a uniformly high spectral emissivity, and two artificial samples constructed from gold and aluminium sheets laminated in polyethylene (PE), which show respectively both Lambertian and specular characteristics along with widely varying emissivity features across the 2.5 – 14 μm region. Here we present first results from the round-robin intercomparison exercise and discuss the implications for the uncertainty of surface spectral emissivity values determined in the laboratory and for the satellite LST products and LST field validation studies that rely on them.

Tropical methane sources are an important part of the global methane budget and include natural wetlands, rice agriculture, biomass burning, ruminants, fossil fuels, and waste. δ13CCH4 can provide strong constraints on methane source apportionment. For example, tropical wetlands in this study give δ13CCH4 values between −61.5 ± 2.9‰ and −53.0 ± 0.4‰ and in general are more enriched in 13C than temperate and boreal wetlands. However, thus far, relatively few measurements of δ13CCH4 in methane-enriched air have been made in the tropics. In this study samples have been collected from tropical wetland, rice, ruminant, and biomass burning emissions to the atmosphere. Regional isotopic signatures vary greatly as different processes and source material affect methane signatures. Measurements were made to determine bulk source inputs to the atmosphere, rather than to study individual processes. These measurements provide inputs for regional methane budget models, to constrain emissions with better source apportionment.

To fully understand the carbon (C) cycle impacts of forest fires, both C emissions during the fire and post-disturbance fluxes need to be considered. The latter are dominated by soil surface CO2 flux (Fs), which is still subject to large uncertainties. Fire is generally regarded as the most important factor influencing succession in the boreal forest biome and fire dependant species such as jack pine are widespread. In May 2007, we took concurrent Fs and soil temperature (Ts) measurements in boreal jack pine fire scars aged between 0 and 59 years since fire. To allow comparisons between scars, we adjusted Fs for Ts (FsT) using a Q10 of 2. Mean FsT ranged from 0.56 (± 0.30 sd) to 1.94 (± 0.74 sd) μmol CO2 m−2 s−1. Our results indicate a difference in mean FsT between recently burned (4 to 8 days post fire) and non-burned mature (59 years since fire) forest (P < 0.001), though no difference was detected between recently burned (4 to 8 days post fire) and non-burned young (16 years since fire) forest (P = 0.785). There was a difference in mean FsT between previously young (16 years since fire) and intermediate aged (32 years since fire) scars that were both subject to fire in 2007 (P < 0.001). However, there was no difference in mean FsT between mature (59 years since fire) and intermediate aged (32 years since fire) scars that were both subjected to fire in 2007 (P = 0.226). Furthermore, there was no difference in mean FsT between mature (59 years since fire) and young scars (16 years since fire) that were both subjected to fire in 2007 (P = 0.186). There was an increase in FsT with time since fire for the chronosequence 0, 16 and 59 years post fire (P < 0.001). Our results lead us to hypothesise that the autotrophic:heterotrophic soil respiration ratio increases over post-fire successional time in boreal jack pine systems, though this should be explored in future research. The results of this study contribute to a better quantitative understanding of Fs in boreal jack pine fire scars and will facilitate meta-analyses of Fs in fire scar chronosequences.

Characterising the dynamics of landscape-scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation (EO) sensors mounted onboard geostationary satellites. As a result, a number of operational active fire products have been developed from the data of such sensors. An example of which are the Fire Radiative Power (FRP) products, the FRP-PIXEL and FRP-GRID products, generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from imagery collected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) series of geostationary EO satellites. The processing chain developed to deliver these FRP products detects SEVIRI pixels containing actively burning fires and characterises their FRP output across four geographic regions covering Europe, part of South America and Northern and Southern Africa. The FRP-PIXEL product contains the highest spatial and temporal resolution FRP data set, whilst the FRP-GRID product contains a spatio-temporal summary that includes bias adjustments for cloud cover and the non-detection of low FRP fire pixels. Here we evaluate these two products against active fire data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and compare the results to those for three alternative active fire products derived from SEVIRI imagery. The FRP-PIXEL product is shown to detect a substantially greater number of active fire pixels than do alternative SEVIRI-based products, and comparison to MODIS on a per-fire basis indicates a strong agreement and low bias in terms of FRP values. However, low FRP fire pixels remain undetected by SEVIRI, with errors of active fire pixel detection commission and omission compared to MODIS ranging between 9–13 % and 65–77 % respectively in Africa. Higher errors of omission result in greater underestimation of regional FRP totals relative to those derived from simultaneously collected MODIS data, ranging from 35 % over the Northern Africa region to 89 % over the European region. High errors of active fire omission and FRP underestimation are found over Europe and South America and result from SEVIRI's larger pixel area over these regions. An advantage of using FRP for characterising wildfire emissions is the ability to do so very frequently and in near-real time (NRT). To illustrate the potential of this approach, wildfire fuel consumption rates derived from the SEVIRI FRP-PIXEL product are used to characterise smoke emissions of the 2007 "mega-fire" event focused on Peloponnese (Greece) and used within the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) as a demonstration of what can be achieved when using geostationary active fire data within the Copernicus Atmosphere Monitoring Service (CAMS). Qualitative comparison of the modelled smoke plumes with MODIS optical imagery illustrates that the model captures the temporal and spatial dynamics of the plume very well, and that high temporal resolution emissions estimates such as those available from a geostationary orbit are important for capturing the sub-daily variability in smoke plume parameters such as aerosol optical depth (AOD), which are increasingly less well resolved using daily or coarser temporal resolution emissions data sets. Quantitative comparison of modelled AOD with coincident MODIS and AERONET (Aerosol Robotic Network) AOD indicates that the former is overestimated by ~ 20–30 %, but captures the observed AOD dynamics with a high degree of fidelity. The case study highlights the potential of using geostationary FRP data to drive fire emissions estimates for use within atmospheric transport models such as those implemented in the Monitoring Atmospheric Composition and Climate (MACC) series of projects for the CAMS.

Biomass burning is one of a relatively few natural processes that can inject globally significant quantities of gases and aerosols into the atmosphere at altitudes well above the planetary boundary layer, in some cases at heights in excess of 10 km. The "injection height" of biomass burning emissions is therefore an important parameter to understand when considering the characteristics of the smoke plumes emanating from landscape scale fires, and in particular when attempting to model their atmospheric transport. Here we further extend the formulations used within a popular 1D plume rise model, widely used for the estimation of landscape scale fire smoke plume injection height, and develop and optimise the model both so that it can run with an increased set of remotely sensed observations. The model is well suited for application in atmospheric Chemistry Transport Models (CTMs) aimed at understanding smoke plume downstream impacts, and whilst a number of wildfire emission inventories are available for use in such CTMs, few include information on plume injection height. Since CTM resolutions are typically too spatially coarse to capture the vertical transport induced by the heat released from landscape scale fires, approaches to estimate the emissions injection height are typically based on parametrizations. Our extensions of the existing 1D plume rise model takes into account the impact of atmospheric stability and latent heat on the plume up-draft, driving it with new information on active fire area and fire radiative power (FRP) retrieved from MODIS satellite Earth Observation (EO) data, alongside ECMWF atmospheric profile information. We extend the model by adding an equation for mass conservation and a new entrainment scheme, and optimise the values of the newly added parameters based on comparison to injection heights derived from smoke plume height retrievals made using the MISR EO sensor. Our parameter optimisation procedure is based on a twofold approach using sequentially a Simulating Annealing algorithm and a Markov chain Monte Carlo uncertainty test, and to try to ensure the appropriate convergence on suitable parameter values we use a training dataset consisting of only fires where a number of specific quality criteria are met, including local ambient wind shear limits derived from the ECMWF and MISR data, and "steady state" plumes and fires showing only relatively small changes between consecutive MODIS observations. Using our optimised plume rise model (PRMv2) with information from all MODIS-detected active fires detected in 2003 over North America, with outputs gridded to a 0.1° horizontal and 500 m vertical resolution mesh, we are able to derive wildfire injection height distributions whose maxima extend to the type of higher altitudes seen in actual observation-based wildfire plume datasets than are those derived either via the original plume model or any other parametrization tested herein. We also find our model to be the only one tested that more correctly simulates the very high plume (6 to 8 km a.s.l.), created by a large fire in Alberta (Canada) on the 17 August 2003, though even our approach does not reach the stratosphere as the real plume is expected to have done. Our results lead us to believe that our PRMv2 approach to modelling the injection height of wildfire plumes is a strong candidate for inclusion into CTMs aiming to represent this process, but we note that significant advances in the spatio-temporal resolutions of the data required to feed the model will also very likely bring key improvements in our ability to more accurately represent such phenomena, and that there remain challenges to the detailed validation of such simulations due to the relative sparseness of plume height observations and their currently rather limited temporal coverage which are not necessarily well matched to when fires are most active (MISR being confined to morning observations for example).

A moorland site in Northumberland in the northeast of England was used for a series of experimental burns in heather-dominated vegetation (Calluna vulgaris) and one burn in a stand of gorse (Ulex europaeus) towards the end of March 2010. This article summarises the main aspects of the exercise, its context and objectives, methods used and some of its findings. These experimental burns were part of an ongoing programme of such tests to be carried out in the UK for studying rural vegetation fires or bushfires. Participants from eight academic groups were involved in this first exercise, in partnership with fire services, deploying a range of scientific instrumentation, sampling and burn strategies.Although the UK can experience long dry periods that create ideal conditions for severe rural vegetation fires (as in the spring and summer of 2003, for example), the weather during the experimental period was less ‘ideal’. Conditions were dry enough for burning on only one and a half days over the planned five day period. The burns carried out were closer to marginal than severe conditions for flammability of the heather, although the small-scale gorse plot was found to be highly flammable in spite of rain a few hours earlier. The techniques put to use in the burns, although not at all plots, included: (1) terrestrial LiDAR before and after the burns for mapping topography and structure of vegetation, as well as changes in structure; (2) destructive sampling of biomass, before and after the fires, to examine fuel load, type and proportion burnt; (3) fuel moisture content sampling of fine fuels; (4)characterising smoke emissions using Fourier transform infrared measurements; (5)helicopter-borne infrared imaging of fire spread; (6) aircraft mounted LiDAR and hyperspectral reflectance imaging; (7) field spectroradiometry of pre-fire and post-fire reflectance; (8) thermocouple temperature measurements at points in the vegetation and the soil; (9) soil sampling for analysis of fire-effects;o (10) use of different ignition patterns. The objectives of this and future exercises range from fundamental understanding of rural fire spread and its effects on vegetation, soil and the environment, along with the development and use of remote sensing techniques for analysis of vegetation, fire damage, emissions, etc., to managed burning for vegetation or fuel-load control and the development of a knowledge base for practical fire suppression tactics and techniques in the UK.