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Abstract. Fire is the dominant disturbance agent in Alaskan and Canadianboreal ecosystems and releases large amounts of carbon into the atmosphere.Burned area and carbon emissions have been increasing with climate change,which have the potential to alter the carbon balance and shift the regionfrom a historic sink to a source. It is therefore critically important totrack the spatiotemporal changes in burned area and fire carbon emissionsover time. Here we developed a new burned-area detection algorithm between2001–2019 across Alaska and Canada at 500 m (meters) resolution thatutilizes finer-scale 30 m Landsat imagery to account for land coverunsuitable for burning. This method strictly balances omission andcommission errors at 500 m to derive accurate landscape- and regional-scaleburned-area estimates. Using this new burned-area product, we developedstatistical models to predict burn depth and carbon combustion for the sameperiod within the NASA Arctic–Boreal Vulnerability Experiment (ABoVE) coreand extended domain. Statistical models were constrained using a database offield observations across the domain and were related to a variety ofresponse variables including remotely sensed indicators of fire severity,fire weather indices, local climate, soils, and topographic indicators. Theburn depth and aboveground combustion models performed best, with poorerperformance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001–2019 over the ABoVE domain (2.87 Mhaacross all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1standard deviation) of carbon (C) per year, with a mean combustionrate of 3.13 ± 1.17 kg C m−2. Mean combustion and burn depthdisplayed a general gradient of higher severity in the northwestern portionof the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greatermean combustion. Our estimates are generally consistent with previousefforts to quantify burned area, fire carbon emissions, and their drivers inregions within boreal North America; however, we generally estimate higherburned area and carbon emissions due to our use of Landsat imagery, greateravailability of field observations, and improvements in modeling. The burnedarea and combustion datasets described here (the ABoVE Fire EmissionsDatabase, or ABoVE-FED) can be used for local- to continental-scaleapplications of boreal fire science. 

Abstract. Permafrost-affected ecosystems of the Arctic–boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P-band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the ∼80 SAR flight lines and how they fit into the ABoVE experimental design (Miller et al., 2023; https://doi.org/10.3334/ORNLDAAC/2150). The Supplement provides hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including boreal forest canopy structure from TomoSAR data over Delta Junction, AK, and the Boreal Ecosystem Research and Monitoring Sites (BERMS) area in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band airborne SAR data (https://uavsar.jpl.nasa.gov/cgi-bin/data.pl).