[en] The release of cold temperature constraints on photosynthesis has led to increased productivity (greening) in significant parts (32–39%) of the Arctic, but much of the Arctic shows stable (57–64%) or reduced productivity (browning, <4%). Summer drought and wildfires are the best-documented drivers causing browning of continental areas, but factors dampening the greening effect of more maritime regions have remained elusive. Here we show how multiple anomalous weather events severely affected the terrestrial productivity during one water year (October 2011–September 2012) in a maritime region north of the Arctic Circle, the Nordic Arctic Region, and contributed to the lowest mean vegetation greenness (normalized difference vegetation index) recorded this century. Procedures for field data sampling were designed during or shortly after the events in order to assess both the variability in effects and the maximum effects of the stressors. Outbreaks of insect and fungal pests also contributed to low greenness. Vegetation greenness in 2012 was 6.8% lower than the 2000–11 average and 58% lower in the worst affected areas that were under multiple stressors. These results indicate the importance of events (some being mostly neglected in climate change effect studies and monitoring) for primary productivity in a high-latitude maritime region, and highlight the importance of monitoring plant damage in the field and including frequencies of stress events in models of carbon economy and ecosystem change in the Arctic. Fourteen weather events and anomalies and 32 hypothesized impacts on plant productivity are summarized as an aid for directing future research. (letter)

[en] The duration and extent of snow cover is expected to change rapidly with climate change. Therefore, there is a need for improved monitoring of snow for the benefit of forecasting, impact assessments and the population at large. Remotely sensed techniques prove useful for remote areas where there are few field-based monitoring stations. This paper reports on a study of snow season using snow cover area fraction data from the two northernmost counties in Norway, Troms and Finnmark. The data are derived from the daily 500 m standard snow product (MOD10A1) from the NASA Terra MODerate Resolution Imaging Spectroradiometer (MODIS) sensor for the 2000–2010 period. This dataset has been processed with multi-temporal interpolation to eliminate clouds. The resulting cloud-free daily time series of snow cover fraction maps, have subsequently been used to derive the first and last snow-free day for the entire study area. In spring, the correlation between the first snow-free day mapped by MODIS data and snow data from 40 meteorological stations was highly significant ( p  < 0.05) for 36 of the stations, and with a of bias of less than 10 days for 34 of the stations. In autumn, 31 of the stations show highly significant ( p  < 0.05) correlation with MODIS data, and the bias was less than 10 days for 27 of the stations. However, in some areas and some years, the start and end of the snow season could not be detected due to long overcast periods. In spring 2002 and 2004 the first snow-free day was early, but arrived late in 2000, 2005 and 2008. In autumn 2009 snowfall arrived more than 7 days earlier in 50% of the study area as compared to the 2000–2010 average. MODIS-based snow season products will be applicable for a wide range of sectors including hydrology, nature-based industries, climate change studies and ecology. Therefore refinement and further testing of this method should be encouraged. (letter)

[en] Extreme winter events that damage vegetation are considered an important climatic cause of arctic browning—a reversal of the greening trend of the region—and possibly reduce the carbon uptake of northern ecosystems. Confirmation of a reduction in CO₂ uptake due to winter damage, however, remains elusive due to a lack of flux measurements from affected ecosystems. In this study, we report eddy covariance fluxes of CO₂ from a peatland in northern Norway and show that vegetation CO₂ uptake was delayed and reduced in the summer of 2014 following an extreme winter event earlier that year. Strong frost in the absence of a protective snow cover—its combined intensity unprecedented in the local climate record—caused severe dieback of the dwarf shrub species Calluna vulgaris and Empetrum nigrum. Similar vegetation damage was reported at the time along ∼1000 km of coastal Norway, showing the widespread impact of this event. Our results indicate that gross primary production (GPP) exhibited a delayed response to temperature following snowmelt. From snowmelt up to the peak of summer, this reduced carbon uptake by 14 (0–24) g C m⁻² (∼12% of GPP in that period)—similar to the effect of interannual variations in summer weather. Concurrently, remotely-sensed NDVI dropped to the lowest level in more than a decade. However, bulk photosynthesis was eventually stimulated by the warm and sunny summer, raising total GPP. Species other than the vulnerable shrubs were probably resilient to the extreme winter event. The warm summer also increased ecosystem respiration, which limited net carbon uptake. This study shows that damage from a single extreme winter event can have an ecosystem-wide impact on CO₂ uptake, and highlights the importance of including winter-induced shrub damage in terrestrial ecosystem models to accurately predict trends in vegetation productivity and carbon sequestration in the Arctic and sub-Arctic. (letter)