Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Liu, Tianjia; Randerson, James T.; Chen, Yang; Morton, Douglas C.; Wiggins, Elizabeth B.; Smyth, Padhraic; Foufoula-Georgiou, Efi; Nadler, Roy; Nevo, Omer

doi:10.5194/essd-2023-389

Cited by 3 publications

(4 citation statements)

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“…The latency of satellite data (up to 4 h for VIIRS) although lower than the airborne observations is still significant and will limit the accuracy of the representation of the fire state at the beginning of a forecast or will require starting the forecast hours earlier to sync the time of the end of the spin-up phase with the time of the satellite overpass. The fire tracing methods leveraging geostationary satellites like the one proposed by Liu et al (2023) could address this problem by providing synthetic fire perimeters at hourly intervals. However, the coarse resolution of the underlying GOES data (~2 km) may limit the applicability of such methods to large and fast-propagating fires.…”

Section: Discussionmentioning

confidence: 99%

Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model

Kochanski,

Clough,

Farguell

et al. 2023

Front. For. Glob. Change

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Correctly initializing the fire within coupled fire-atmosphere models is critical for producing accurate forecasts of meteorology near the fire, as well as the fire growth, and plume evolution. Improperly initializing the fire in a coupled fire-atmosphere model can introduce forecast errors that can impact wind circulations surrounding the fire and updrafts along the fire front. A well-constructed fire initialization process must be integrated within coupled fire-atmosphere models to ensure that the atmospheric component of the model does not become numerically unstable due to excessive heat fluxes released during the ignition, and that realistic fire-induced atmospheric circulations are established at the model initialization time. The primary objective of this study is to establish an effective fire initialization method in a coupled fire-atmosphere model, based on the analysis of the impact of the initialization procedure on the model’s ability to resolve fire-atmosphere circulations and fire growth. Here, we test three different fire initialization approaches leveraging the FireFlux II experimental fire, which provides a comprehensive suite of observations of the pyroconvective column, local micrometeorology, and fire characteristics. The two most effective fire initialization methods identified using the FireFlux II case study are then tested on the 380,000-acre Creek Fire, which burned across the central Sierra Nevada mountains during the 2020 Western U.S. wildfire season. For this case study, simulated pyroconvection and fire progression are evaluated using plume top height observations from MISR and airborne fire perimeter data, to assess the effectiveness of different initialization methods in the context of establishing pyroconvection and resolving the fire growth. The analyses of both the experimental fire simulation and the wildfire simulation indicate that the spin-up initialization method based on historical fire progression that masks out inactive fire regions provides the best results in terms of resolving the fire-induced vertical circulation and fire progression.

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Section: Discussionmentioning

confidence: 99%

Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model

Kochanski,

Clough,

Farguell

et al. 2023

Front. For. Glob. Change

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“…The GOFER product for the 28 large CA fires contains hourly fire perimeters, active-fire lines, and fire spread rates for three GOFER versions: GOFER-Combined, GOFER-West, and GOFER-East (Liu et al, 2023). Table 2 describes variables contained in the GOFER product.…”

Section: Gofer Product Structure and Variablesmentioning

confidence: 99%

“…The GOFER product of the 28 fires in California from 2019 to 2021 is available on Zenodo at https://doi.org/10.5281/zenodo.8327264 (Liu et al, 2023). An online data visualization app for the GOFER product is available at https://globalfires.earthengine.app/view/gofer (Liu, 2024).…”

Section: Data Availabilitymentioning

confidence: 99%

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Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Liu,

Randerson,

Chen

et al. 2024

Earth Syst. Sci. Data

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Abstract. In the western United States, prolonged drought, a warming climate, and historical fuel buildup have contributed to larger and more intense wildfires as well as to longer fire seasons. As these costly wildfires become more common, new tools and methods are essential for improving our understanding of the evolution of fires and how extreme weather conditions, including heat waves, windstorms, droughts, and varying levels of active-fire suppression, influence fire spread. Here, we develop the Geostationary Operational Environmental Satellites (GOES)-Observed Fire Event Representation (GOFER) algorithm to derive the hourly fire progression of large wildfires and create a product of hourly fire perimeters, active-fire lines, and fire spread rates. Using GOES-East and GOES-West geostationary satellite detections of active fires, we test the GOFER algorithm on 28 large wildfires in California from 2019 to 2021. The GOFER algorithm includes parameter optimizations for defining the burned-to-unburned boundary and correcting for the parallax effect from elevated terrain. We evaluate GOFER perimeters using 12 h data from the Visible Infrared Imaging Radiometer Suite (VIIRS)-derived Fire Event Data Suite (FEDS) and final fire perimeters from the California's Fire and Resource Assessment Program (FRAP). Although the GOES imagery used to derive GOFER has a coarser resolution (2 km at the Equator), the final fire perimeters from GOFER correspond reasonably well to those obtained from FRAP, with a mean Intersection-over-Union (IoU) of 0.77, in comparison to 0.83 between FEDS and FRAP; the IoU indicates the area of overlap over the area of the union relative to the reference perimeters, in which 0 is no agreement and 1 is perfect agreement. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery, where perimeters are available at intervals of 12 h or longer or at ad hoc intervals from aircraft overflights. This is particularly relevant when a fire spreads rapidly, such as at maximum hourly spread rates of over 5 km h−1. Our GOFER algorithm for deriving the hourly fire progression using GOES can be applied to large wildfires across North and South America and reveals considerable variability in the rates of fire spread on diurnal timescales. The resulting GOFER product has a broad set of potential applications, including the development of predictive models for fire spread and the improvement of atmospheric transport models for surface smoke estimates. The resulting GOFER product has a broad set of potential applications, including the development of predictive models for fire spread and the improvement of atmospheric transport models for surface smoke estimates (https://doi.org/10.5281/zenodo.8327264, Liu et al., 2023).

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The Canadian Fire Spread Dataset

Barber,

Jain,

Whitman

et al. 2024

Sci Data

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Satellite data are effective for mapping wildfires, particularly in remote locations where monitoring is rare. Geolocated fire detections can be used for enhanced fire management and fire modelling through daily fire progression mapping. Here we present the Canadian Fire Spread Dataset (CFSDS), encompassing interpolated progressions for fires >1,000 ha in Canada from 2002–2021, representing the day-of-burning and 50 environmental covariates for every pixel. Day-of-burning was calculated by ordinary kriging of active fire detections from the Moderate Resolution Imaging Spectroradiometer and the Visible Infrared Imaging Radiometer Suite, enabling a substantial improvement in coverage and resolution over existing datasets. Day of burning at each pixel was used to identify environmental conditions of burning such as daily weather, derived weather metrics, topography, and forest fuels characteristics. This dataset can be used in a broad range of research and management applications, such as retrospective analysis of fire spread, as a benchmark dataset for validating statistical or machine-learning models, and for forecasting the effects of climate change on fire activity.

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Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Cited by 3 publications

References 1 publication

Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model

Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model

Systematically tracking the hourly progression of large wildfires using GOES satellite observations

The Canadian Fire Spread Dataset

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