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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). 

Accurate estimates of biomass burning (BB) emissions are of great importance worldwide due to the impacts of these emissions on human health, ecosystems, air quality, and climate. Atmospheric modeling efforts to represent these impacts require BB emissions as a key input. This paper is presented by the Biomass Burning Uncertainty: Reactions, Emissions and Dynamics (BBURNED) activity of the International Global Atmospheric Chemistry project and largely based on a workshop held in November 2023. The paper reviews 9 of the BB emissions datasets widely used by the atmospheric chemistry community, all of which rely heavily on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations of fires scheduled to be discontinued at the end of 2025. In this time of transition away from MODIS to new fire observations, such as those from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments, we summarize the contemporary status of BB emissions estimation and provide recommendations on future developments. Development of global BB emissions datasets depends on vegetation datasets, emission factors, and assumptions of fire persistence and phase, all of which are highly uncertain with high degrees of variability and complexity and are continually evolving areas of research. As a result, BB emissions datasets can have differences on the order of factor 2–3, and no single dataset stands out as the best for all regions, species, and times. We summarize the methodologies and differences between BB emissions datasets. The workshop identified 5 key recommendations for future research directions for estimating BB emissions and quantifying the associated uncertainties: development and uptake of satellite burned area products from VIIRS and other instruments; mapping of fine scale heterogeneity in fuel type and condition; identification of spurious signal detections and information gaps in satellite fire radiative power products; regional modeling studies and comparison against existing datasets; and representation of the diurnal cycle and plume rise in BB emissions. 

Abstract Cultivated strawberry ( Fragaria × ananassa ) is an important fruit crop species whose fruits are enjoyed by many worldwide. An octoploid of hybrid origin, the complex genome of this species was recently sequenced, serving as a key reference genome for cultivated strawberry and related species of the Rosaceae family. The current annotation of the F. ananassa genome mainly relies on ab initio predictions and, to a lesser extent, transcriptome data. Here, we present the structure and functional reannotation of the F. ananassa genome based on one PacBio full-length RNA library and ninety-two Illumina RNA-Seq libraries. This improved annotation of the F. ananassa genome, v1.0.a2, comprises a total of 108,447 gene models, with 97.85% complete BUSCOs. The models of 19,174 genes were modified, 360 new genes were identified, and 11,044 genes were found to have alternatively spliced isoforms. Additionally, we constructed a strawberry genome database (SGD) for strawberry gene homolog searching and annotation downloading. Finally, the transcriptome of the receptacles and achenes of F. ananassa at four developmental stages were reanalyzed and qualified, and the expression profiles of all the genes in this annotation are also provided. Together, this study provides an updated annotation of the F. ananassa genome, which will facilitate genomic analyses across the Rosaceae family and gene functional studies in cultivated strawberry.