winter warming
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Author(s):  
Yong Wang ◽  
Guang J. Zhang ◽  
Peng Gong ◽  
Robert E. Dickinson ◽  
Rong Fu ◽  
...  

Author(s):  
William Robert Vaughn ◽  
Anthony R. Taylor ◽  
David A. MacLean ◽  
Loïc D'Orangeville

Dormant seeds that require long periods of cold stratification to become germinable may be most sensitive to increases in winter temperatures caused by anthropogenic climate change. In this study, we used outdoor plots with infrared heaters to simulate the effects of projected winter warming (+6°C) for Canada’s Acadian Forest Region and compared seed germination success of tree species with varying stratification requirements. We evaluated four seedlots each of balsam fir (Abies balsamea (L.) Mill.), red spruce (Picea rubens Sarg.), white pine (Pinus strobus L.), red maple (Acer rubrum L.), sugar maple (Acer saccharum Marshall) and yellow birch (Betula alleghaniensis Britton). Three central findings emerged from this study: (1) none of the tested species were significantly affected by warming; (2) the random effect of seedlot explained more variation in germination success of deciduous species than it did for conifers; and (3) balsam fir seedlots exhibited considerable differences in their response to warming, implying intraspecific variation in depth of dormancy. These results suggest seed germination success of the tested tree species may not be impeded by their individual seed characteristics under the magnitude of winter warming projected over the coming century in our study area.


2021 ◽  
Vol 542-543 ◽  
pp. 151604
Author(s):  
Laura H. Spencer ◽  
Erin Horkan ◽  
Ryan Crim ◽  
Steven B. Roberts

2021 ◽  
Author(s):  
Lily Hahn ◽  
Kyle Armour ◽  
David Battisti ◽  
Ian Eisenman ◽  
Cecilia Bitz

Arctic surface warming under greenhouse gas forcing peaks in early winter and reaches its minimum during summer in both observations and model projections. Many mechanisms have been proposed to explain this seasonal asymmetry, but disentangling these processes remains a challenge in the interpretation of general circulation model (GCM) experiments. To isolate these mechanisms, we use an idealized single-column sea ice model (SCM) which captures the seasonal pattern of Arctic warming. SCM experiments demonstrate that as sea ice melts and exposes open ocean, the accompanying increase in effective surface heat capacity can alone produce the observed pattern of peak early winter warming by slowing the seasonal heating and cooling rate, thus delaying the phase and reducing the amplitude of the seasonal cycle of surface temperature. To investigate warming seasonality in more complex models, we perform GCM experiments that individually isolate sea-ice albedo and thermodynamic effects under CO2 forcing. These also show a key role for the effective heat capacity of sea ice in promoting seasonal asymmetry through suppressing summer warming, in addition to precluding summer climatological inversions and a positive summer lapse-rate feedback. Peak winter warming in GCM experiments is further supported by a positive winter lapse-rate feedback that persists with only the albedo effects of sea-ice loss prescribed, due to cold initial surface temperatures and strong surface-trapped warming. While many factors support peak early winter warming as Arctic sea ice declines, these results highlight changes in effective surface heat capacity as a central mechanism contributing to this seasonality.


2021 ◽  
Vol 13 (10) ◽  
pp. 1972
Author(s):  
Kaiwei Li ◽  
Chunyi Wang ◽  
Qing Sun ◽  
Guangzhi Rong ◽  
Zhijun Tong ◽  
...  

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.


2021 ◽  
Author(s):  
Didac Pascual Descarrega ◽  
Margareta Johansson

<p>Winter warming events (WWE) in the Swedish subarctic are abrupt and short-lasting (hours-to-days) events of positive air temperature that occur during wintertime, sometimes accompanied by rainfall (rain on snow; ROS). These events cause changes in snow properties, which affect the below-ground thermal regime that, in turn, controls a suite of ecosystem processes ranging from microbial activity to permafrost and vegetation dynamics. For instance, winter melting can cause ground warming due to the shortening of the snow cover season, or ground cooling as the reduced snow depth and the formation of refrozen layers of high thermal conductivity at the base of the snowpack facilitate the release of soil heat. Apart from these interacting processes, the overall impacts of WWE on ground temperatures may also depend on the timing of the events and the preceding snowpack characteristics. The frequency and intensity of these events in the Arctic, including the Swedish subarctic, has increased remarkably during the recent decades, and is expected to increase even further during the 21st Century. In addition, snow depth (not necessarily snow duration) is projected to increase in many parts of the Arctic, including the Swedish subarctic. In 2005, a manipulation experiment was set up on a lowland permafrost mire in the Swedish subarctic, to simulate projected future increases in winter precipitation. In this study, we analyse this 15-year record of ground temperature, active layer thickness, and meteorological variables, to evaluate the short- (days to weeks) and long-term (up to 1 year) impacts of WWE on the thermal dynamics of lowland permafrost, and provide new insights into the influence of the timing of WWE and the underlying snowpack conditions on the thermal response of permafrost. On the short-term, the thermal responses to WWE are faster and stronger in areas with a shallow snowpack (5-10 cm), although these responses are more persistent in areas with a thicker snowpack (>25 cm), especially after ROS events. On the long term, permafrost in areas with a thicker snowpack exhibit a more durable warming response to WWE that results in thicker active layers at the end of the season. On the contrary, we do not observe a correlation between WWE and end of season active layer thickness in areas with a shallow snowpack. </p>


2021 ◽  
Author(s):  
Jing Tian ◽  
Ning Zong ◽  
Iain P. Hartley ◽  
Nianpeng He ◽  
Jinjing Zhang ◽  
...  

2021 ◽  
Vol 65 ◽  
pp. 125799
Author(s):  
Shankar Panthi ◽  
Ze-Xin Fan ◽  
Achim Bräuning

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