Adrien Guyot

Clouds generated by intense wildfires can evolve from pyrocumulus (pyroCu) to pyrocumulonimbus (pyroCb), injecting smoke into the upper troposphere and occasionally the stratosphere. Automated satellite-based detection of pyroCb is therefore critical for monitoring extreme fire–atmosphere interactions, yet such approaches inherently rely on cloud-top properties rather than the underlying convective dynamics. Here, we evaluate the pyroCb detection algorithm of Peterson et al. (2017), originally developed for GOES observations over North America, in the Australian context using Himawari-8 multispectral imagery during the 2019–2020 Black Summer bushfires. Satellite-derived classifications are assessed against independent observations from operational weather radar and total lightning networks within a multi-sensor framework implemented in the PyroScope platform. An object-based tracking approach is used to compare the temporal evolution of radar- and satellite-derived pyroconvective features. Satellite observations reliably capture the onset of deep pyroconvective development, showing strong agreement with radar-derived echo-top heights and lightning activity during the early phase. However, a systematic divergence emerges as events evolve, with satellite-derived objects increasingly dominated by horizontally advected anvil structures rather than the actively convecting core. This behaviour is reflected in increasing centroid displacement, decreasing spatial overlap, and an apparent overestimation of plume extent and persistence in satellite retrievals. To investigate this limitation, we introduce an additional spectral test to separate detached or decaying anvils (class 4) from intense pyroCb (class 5), and explicitly evaluate the impact of this classification on object-based metrics. Restricting the analysis to class 5 reduces the spatial extent and persistence of satellite-derived objects, but does not fully eliminate the divergence with radar observations at later stages, highlighting the inherent limitations of an anvil-based detection paradigm. These results demonstrate that satellite-based pyroCb detection should be interpreted as a cloud-top representation of pyroconvection rather than a direct measure of the actively convecting core. Multi-sensor integration is therefore essential to distinguish between initiation, mature, and decay phases of pyroconvection. The object-based tracking framework developed here provides a foundation for future studies of pyroCb lifecycle, including the quantification of growth, decay, and potential precursors to pyroCb formation.

Clouds generated by intense wildfires can evolve from pyrocumulus (pyroCu) to pyrocumulonimbus (pyroCb), injecting smoke into the upper troposphere and occasionally the stratosphere. Automated satellite-based detection of pyroCb is therefore critical for monitoring extreme fire–atmosphere interactions, yet such approaches inherently rely on cloud-top properties rather than the underlying convective dynamics. Here, we evaluate the pyroCb detection algorithm of Peterson et al. (2017), originally developed for GOES observations over North America, in the Australian context using Himawari-8 multispectral imagery during the 2019–2020 Black Summer bushfires. Satellite-derived classifications are assessed against independent observations from operational weather radar and total lightning networks within a multi-sensor framework implemented in the PyroScope platform. An object-based tracking approach is used to compare the temporal evolution of radar- and satellite-derived pyroconvective features. Satellite observations reliably capture the onset of deep pyroconvective development, showing strong agreement with radar-derived echo-top heights and lightning activity during the early phase. However, a systematic divergence emerges as events evolve, with satellite-derived objects increasingly dominated by horizontally advected anvil structures rather than the actively convecting core. This behaviour is reflected in increasing centroid displacement, decreasing spatial overlap, and an apparent overestimation of plume extent and persistence in satellite retrievals. To investigate this limitation, we introduce an additional spectral test to separate detached or decaying anvils (class 4) from intense pyroCb (class 5), and explicitly evaluate the impact of this classification on object-based metrics. Restricting the analysis to class 5 reduces the spatial extent and persistence of satellite-derived objects, but does not fully eliminate the divergence with radar observations at later stages, highlighting the inherent limitations of an anvil-based detection paradigm. These results demonstrate that satellite-based pyroCb detection should be interpreted as a cloud-top representation of pyroconvection rather than a direct measure of the actively convecting core. Multi-sensor integration is therefore essential to distinguish between initiation, mature, and decay phases of pyroconvection. The object-based tracking framework developed here provides a foundation for future studies of pyroCb lifecycle, including the quantification of growth, decay, and potential precursors to pyroCb formation.

Extreme wildfire behaviour is increasingly associated with deep pyro-convection and pyro-cumulonimbus (pyroCb) development, posing challenges for both scientific understanding and operational wildfire management. Existing wildfire intelligence relies on a combination of aerial observations, satellite remote sensing, numerical weather prediction, and in-situ measurements, which can be limited in resolving rapidly evolving plume dynamics and near-fire wind changes. Portable weather radars represent a promising observational approach by providing high-resolution measurements of plume structure, kinematics, and microphysical properties, together with conventional radar products such as precipitation and outflow detection. However, their role within wildfire intelligence frameworks remains relatively unexplored. In this study, we review two decades of portable radar observations of wildfires and prescribed burns and present new analyses from a recent deployment of a mobile dual-polarization X-band radar during an extreme wildfire in Eastern Australia. Building on these observations, we introduce a set of radar-derived diagnostics relevant to wildfire intelligence, including plume depth evolution, signatures of pyro-convective dynamics, detection of low-level wind changes, and indicators associated with transitions from pyro-cumulus to deep convection. These diagnostics complement existing satellite and modelling approaches by providing information on processes that are not directly observable from current operational platforms. Using a Technology Readiness Level (TRL) framework, we assess the maturity of portable radar applications for wildfire monitoring. While fundamental aspects of pyrometeor scattering remain at low readiness (TRL 1–3), repeated field deployments indicate increasing maturity of plume observations (TRL 4–5), with some diagnostic products approaching pre-operational capability. These findings suggest that further progress will depend not only on technical development but also on practical considerations such as deployment logistics, integration with existing systems, and operational evaluation. Overall, portable weather radar may provide an additional component of future multi-sensor wildfire intelligence systems, helping to bridge part of the observational gap between satellite remote sensing and fireground measurements while improving understanding of fire–atmosphere interactions.

Extreme wildfire behaviour is increasingly associated with deep pyro-convection and pyro-cumulonimbus (pyroCb) development, posing challenges for both scientific understanding and operational wildfire management. Existing wildfire intelligence relies on a combination of aerial observations, satellite remote sensing, numerical weather prediction, and in-situ measurements, which can be limited in resolving rapidly evolving plume dynamics and near-fire wind changes. Portable weather radars represent a promising observational approach by providing high-resolution measurements of plume structure, kinematics, and microphysical properties, together with conventional radar products such as precipitation and outflow detection. However, their role within wildfire intelligence frameworks remains relatively unexplored. In this study, we review two decades of portable radar observations of wildfires and prescribed burns and present new analyses from a recent deployment of a mobile dual-polarization X-band radar during an extreme wildfire in Eastern Australia. Building on these observations, we introduce a set of radar-derived diagnostics relevant to wildfire intelligence, including plume depth evolution, signatures of pyro-convective dynamics, detection of low-level wind changes, and indicators associated with transitions from pyro-cumulus to deep convection. These diagnostics complement existing satellite and modelling approaches by providing information on processes that are not directly observable from current operational platforms. Using a Technology Readiness Level (TRL) framework, we assess the maturity of portable radar applications for wildfire monitoring. While fundamental aspects of pyrometeor scattering remain at low readiness (TRL 1–3), repeated field deployments indicate increasing maturity of plume observations (TRL 4–5), with some diagnostic products approaching pre-operational capability. These findings suggest that further progress will depend not only on technical development but also on practical considerations such as deployment logistics, integration with existing systems, and operational evaluation. Overall, portable weather radar may provide an additional component of future multi-sensor wildfire intelligence systems, helping to bridge part of the observational gap between satellite remote sensing and fireground measurements while improving understanding of fire–atmosphere interactions.

Extreme wildfire behaviour is increasingly associated with deep pyro-convection and pyro-cumulonimbus (pyroCb) development, posing challenges for both scientific understanding and operational wildfire management. Existing wildfire intelligence relies on a combination of aerial observations, satellite remote sensing, numerical weather prediction, and in-situ measurements, which can be limited in resolving rapidly evolving plume dynamics and near-fire wind changes. Portable weather radars represent a promising observational approach by providing high-resolution measurements of plume structure, kinematics, and microphysical properties, together with conventional radar products such as precipitation and outflow detection. However, their role within wildfire intelligence frameworks remains relatively unexplored. In this study, we review two decades of portable radar observations of wildfires and prescribed burns and present new analyses from a recent deployment of a mobile dual-polarization X-band radar during an extreme wildfire in Eastern Australia. Building on these observations, we introduce a set of radar-derived diagnostics relevant to wildfire intelligence, including plume depth evolution, signatures of pyro-convective dynamics, detection of low-level wind changes, and indicators associated with transitions from pyro-cumulus to deep convection. These diagnostics complement existing satellite and modelling approaches by providing information on processes that are not directly observable from current operational platforms. Using a Technology Readiness Level (TRL) framework, we assess the maturity of portable radar applications for wildfire monitoring. While fundamental aspects of pyrometeor scattering remain at low readiness (TRL 1–3), repeated field deployments indicate increasing maturity of plume observations (TRL 4–5), with some diagnostic products approaching pre-operational capability. These findings suggest that further progress will depend not only on technical development but also on practical considerations such as deployment logistics, integration with existing systems, and operational evaluation. Overall, portable weather radar may provide an additional component of future multi-sensor wildfire intelligence systems, helping to bridge part of the observational gap between satellite remote sensing and fireground measurements while improving understanding of fire–atmosphere interactions.

Extreme wildfire behaviour is increasingly associated with deep pyro-convection and pyro-cumulonimbus (pyroCb) development, posing challenges for both scientific understanding and operational wildfire management. Existing wildfire intelligence relies on a combination of aerial observations, satellite remote sensing, numerical weather prediction, and in-situ measurements, which can be limited in resolving rapidly evolving plume dynamics and near-fire wind changes. Portable weather radars represent a promising observational approach by providing high-resolution measurements of plume structure, kinematics, and microphysical properties, together with conventional radar products such as precipitation and outflow detection. However, their role within wildfire intelligence frameworks remains relatively unexplored. In this study, we review two decades of portable radar observations of wildfires and prescribed burns and present new analyses from a recent deployment of a mobile dual-polarization X-band radar during an extreme wildfire in Eastern Australia. Building on these observations, we introduce a set of radar-derived diagnostics relevant to wildfire intelligence, including plume depth evolution, signatures of pyro-convective dynamics, detection of low-level wind changes, and indicators associated with transitions from pyro-cumulus to deep convection. These diagnostics complement existing satellite and modelling approaches by providing information on processes that are not directly observable from current operational platforms. Using a Technology Readiness Level (TRL) framework, we assess the maturity of portable radar applications for wildfire monitoring. While fundamental aspects of pyrometeor scattering remain at low readiness (TRL 1–3), repeated field deployments indicate increasing maturity of plume observations (TRL 4–5), with some diagnostic products approaching pre-operational capability. These findings suggest that further progress will depend not only on technical development but also on practical considerations such as deployment logistics, integration with existing systems, and operational evaluation. Overall, portable weather radar may provide an additional component of future multi-sensor wildfire intelligence systems, helping to bridge part of the observational gap between satellite remote sensing and fireground measurements while improving understanding of fire–atmosphere interactions.

Clouds generated by intense wildfires can evolve from pyrocumulus (pyroCu) to pyrocumulonimbus (pyroCb), injecting smoke into the upper troposphere and occasionally the stratosphere. Automated satellite-based detection of pyroCb is therefore critical for monitoring extreme fire–atmosphere interactions, yet such approaches inherently rely on cloud-top properties rather than the underlying convective dynamics. Here, we evaluate the pyroCb detection algorithm of Peterson et al. (2017), originally developed for GOES observations over North America, in the Australian context using Himawari-8 multispectral imagery during the 2019–2020 Black Summer bushfires. Satellite-derived classifications are assessed against independent observations from operational weather radar and total lightning networks within a multi-sensor framework implemented in the PyroScope platform. An object-based tracking approach is used to compare the temporal evolution of radar- and satellite-derived pyroconvective features. Satellite observations reliably capture the onset of deep pyroconvective development, showing strong agreement with radar-derived echo-top heights and lightning activity during the early phase. However, a systematic divergence emerges as events evolve, with satellite-derived objects increasingly dominated by horizontally advected anvil structures rather than the actively convecting core. This behaviour is reflected in increasing centroid displacement, decreasing spatial overlap, and an apparent overestimation of plume extent and persistence in satellite retrievals. To investigate this limitation, we introduce an additional spectral test to separate detached or decaying anvils (class 4) from intense pyroCb (class 5), and explicitly evaluate the impact of this classification on object-based metrics. Restricting the analysis to class 5 reduces the spatial extent and persistence of satellite-derived objects, but does not fully eliminate the divergence with radar observations at later stages, highlighting the inherent limitations of an anvil-based detection paradigm. These results demonstrate that satellite-based pyroCb detection should be interpreted as a cloud-top representation of pyroconvection rather than a direct measure of the actively convecting core. Multi-sensor integration is therefore essential to distinguish between initiation, mature, and decay phases of pyroconvection. The object-based tracking framework developed here provides a foundation for future studies of pyroCb lifecycle, including the quantification of growth, decay, and potential precursors to pyroCb formation.

Clouds generated by intense wildfires can evolve from pyrocumulus (pyroCu) to pyrocumulonimbus (pyroCb), injecting smoke into the upper troposphere and occasionally the stratosphere. Automated satellite-based detection of pyroCb is therefore critical for monitoring extreme fire–atmosphere interactions, yet such approaches inherently rely on cloud-top properties rather than the underlying convective dynamics. Here, we evaluate the pyroCb detection algorithm of Peterson et al. (2017), originally developed for GOES observations over North America, in the Australian context using Himawari-8 multispectral imagery during the 2019–2020 Black Summer bushfires. Satellite-derived classifications are assessed against independent observations from operational weather radar and total lightning networks within a multi-sensor framework implemented in the PyroScope platform. An object-based tracking approach is used to compare the temporal evolution of radar- and satellite-derived pyroconvective features. Satellite observations reliably capture the onset of deep pyroconvective development, showing strong agreement with radar-derived echo-top heights and lightning activity during the early phase. However, a systematic divergence emerges as events evolve, with satellite-derived objects increasingly dominated by horizontally advected anvil structures rather than the actively convecting core. This behaviour is reflected in increasing centroid displacement, decreasing spatial overlap, and an apparent overestimation of plume extent and persistence in satellite retrievals. To investigate this limitation, we introduce an additional spectral test to separate detached or decaying anvils (class 4) from intense pyroCb (class 5), and explicitly evaluate the impact of this classification on object-based metrics. Restricting the analysis to class 5 reduces the spatial extent and persistence of satellite-derived objects, but does not fully eliminate the divergence with radar observations at later stages, highlighting the inherent limitations of an anvil-based detection paradigm. These results demonstrate that satellite-based pyroCb detection should be interpreted as a cloud-top representation of pyroconvection rather than a direct measure of the actively convecting core. Multi-sensor integration is therefore essential to distinguish between initiation, mature, and decay phases of pyroconvection. The object-based tracking framework developed here provides a foundation for future studies of pyroCb lifecycle, including the quantification of growth, decay, and potential precursors to pyroCb formation.

Extreme wildfire behaviour is increasingly associated with deep pyro-convection and pyro-cumulonimbus (pyroCb) development, posing challenges for both scientific understanding and operational wildfire management. Existing wildfire intelligence relies on a combination of aerial observations, satellite remote sensing, numerical weather prediction, and in-situ measurements, which can be limited in resolving rapidly evolving plume dynamics and near-fire wind changes. Portable weather radars represent a promising observational approach by providing high-resolution measurements of plume structure, kinematics, and microphysical properties, together with conventional radar products such as precipitation and outflow detection. However, their role within wildfire intelligence frameworks remains relatively unexplored. In this study, we review two decades of portable radar observations of wildfires and prescribed burns and present new analyses from a recent deployment of a mobile dual-polarization X-band radar during an extreme wildfire in Eastern Australia. Building on these observations, we introduce a set of radar-derived diagnostics relevant to wildfire intelligence, including plume depth evolution, signatures of pyro-convective dynamics, detection of low-level wind changes, and indicators associated with transitions from pyro-cumulus to deep convection. These diagnostics complement existing satellite and modelling approaches by providing information on processes that are not directly observable from current operational platforms. Using a Technology Readiness Level (TRL) framework, we assess the maturity of portable radar applications for wildfire monitoring. While fundamental aspects of pyrometeor scattering remain at low readiness (TRL 1–3), repeated field deployments indicate increasing maturity of plume observations (TRL 4–5), with some diagnostic products approaching pre-operational capability. These findings suggest that further progress will depend not only on technical development but also on practical considerations such as deployment logistics, integration with existing systems, and operational evaluation. Overall, portable weather radar may provide an additional component of future multi-sensor wildfire intelligence systems, helping to bridge part of the observational gap between satellite remote sensing and fireground measurements while improving understanding of fire–atmosphere interactions.