Early snowmelt and polar jet dynamics co-influence recent extreme Siberian fire seasons.

The summers of 2019, 2020, and 2021 experienced unprecedented fire activity in northeastern Siberia, driven by record high spring and summer temperatures. Many of these fires burned in permafrost peatlands within the Arctic Circle. We show that early snowmelt together with an anomalous Arctic front jet over northeastern Siberia promoted unusually warm and dry surface conditions, followed by anomalously high lightning and fire activity. Since 1966, spring snowmelt has started 1.7 days earlier each decade. Moreover, Arctic front jet occurrences in summer have more than tripled in frequency over the last 40 years. These interconnected climatological drivers promote extreme fire activity in eastern Siberia, including a northward shift of fires, which may accelerate the degradation of carbon-rich permafrost peatlands.

Overwintering fires in boreal forests.

Forest fires are usually viewed within the context of a single fire season, in which weather conditions and fuel supply can combine to create conditions favourable for fire ignition-usually by lightning or human activity-and spread1-3. But some fires exhibit 'overwintering' behaviour, in which they smoulder through the non-fire season and flare up in the subsequent spring4,5. In boreal (northern) forests, deep organic soils favourable for smouldering6, along with accelerated climate warming7, may present unusually favourable conditions for overwintering. However, the extent of overwintering in boreal forests and the underlying factors influencing this behaviour remain unclear. Here we show that overwintering fires in boreal forests are associated with hot summers generating large fire years and deep burning into organic soils, conditions that have become more frequent in our study areas in recent decades. Our results are based on an algorithm with which we detect overwintering fires in Alaska, USA, and the Northwest Territories, Canada, using field and remote sensing datasets. Between 2002 and 2018, overwintering fires were responsible for 0.8 per cent of the total burned area; however, in one year this amounted to 38 per cent. The spatiotemporal predictability of overwintering fires could be used by fire management agencies to facilitate early detection, which may result in reduced carbon emissions and firefighting costs.

Preprocessing Ground-Based Visible/Near Infrared Imaging Spectroscopy Data Affected by Smile Effects.

A data set of very high-resolution visible/near infrared hyperspectral images of young Pinus contorta trees was recorded to study the effects of herbicides on this invasive species. The camera was fixed on a frame while the potted trees were moved underneath on a conveyor belt. To account for changing illumination conditions, a white reference bar was included at the edge of each image line. Conventional preprocessing of the images, i.e., dividing measured values by values from the white reference bar in the same image line, failed and resulted in bad quality spectra with oscillation patterns that are most likely due to wavelength shifts across the sensor's field of view (smile effect). An additional hyperspectral data set of a Spectralon white reference panel could be used to characterize and correct the oscillations introduced by the division, resulting in a high quality spectra that document the effects of herbicides on the reflectance characteristics of coniferous trees. While the spectra of untreated trees remained constant over time, there were clear temporal changes in the spectra of trees treated with both herbicides. One herbicide worked within days, the other one within weeks. Ground-based imaging spectroscopy with meaningful preprocessing proved to be an appropriate tool for monitoring the effects of herbicides on potted plants.