Annual and Seasonal Patterns of Burned Area Products in Arctic-Boreal North America and Russia for 2001–2020

Author:

Clelland Andrew A.12ORCID,Marshall Gareth J.1ORCID,Baxter Robert2ORCID,Potter Stefano3ORCID,Talucci Anna C.3ORCID,Rady Joshua M.3ORCID,Genet Hélène4ORCID,Rogers Brendan M.3ORCID,Natali Susan M.3ORCID

Affiliation:

1. British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge CB3 0ET, UK

2. Department of Biosciences, Durham University, South Road, Durham DH1 3LE, UK

3. Woodwell Climate Research Center, Woods Hole Road, Falmouth, MA 02540, USA

4. Institute of Arctic Biology, University of Alaska Fairbanks, Koyukuk Drive, Fairbanks, AK 99775, USA

Abstract

Boreal and Arctic regions have warmed up to four times quicker than the rest of the planet since the 1970s. As a result, boreal and tundra ecosystems are experiencing more frequent and higher intensity extreme weather events and disturbances, such as wildfires. Yet limitations in ground and satellite data across the Arctic and boreal regions have challenged efforts to track these disturbances at regional scales. In order to effectively monitor the progression and extent of wildfires in the Arctic-boreal zone, it is essential to determine whether burned area (BA) products are accurate representations of BA. Here, we use 12 different datasets together with MODIS active fire data to determine the total yearly BA and seasonal patterns of fires in Arctic-boreal North America and Russia for the years 2001–2020. We found relatively little variability between the datasets in North America, both in terms of total BA and seasonality, with an average BA of 2.55 ± 1.24 (standard deviation) Mha/year for our analysis period, the majority (ca. 41%) of which occurs in July. In contrast, in Russia, there are large disparities between the products—GFED5 produces over four times more BA than GFED4s in southern Siberia. These disparities occur due to the different methodologies used; dNBR (differenced Normalized Burn Ratio) of short-term composites from Landsat images used alongside hotspot data was the most consistently successful in representing BA. We stress caution using GABAM in these regions, especially for the years 2001–2013, as Landsat-7 ETM+ scan lines are mistaken as burnt patches, increasing errors of commission. On the other hand, we highlight using regional products where possible, such as ABoVE-FED or ABBA in North America, and the Talucci et al. fire perimeter product in Russia, due to their detection of smaller fires which are often missed by global products.

Funder

UK Natural Environment Research Council

Gordon and Betty Moore Foundation

Audacious Project

US National Science Foundation Arctic System Science

Publisher

MDPI AG

Reference136 articles.

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