Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

In permafrost regions, the strong spatial and temporal variability in soil temperature cannot be explained by the weather forcing only. Understanding the local heterogeneity of soil thermal dynamics and their controls is essential to understand how permafrost systems respond to climate change and to develop process-based models or remote sensing products for predicting soil temperature. In this study, we analyzed soil temperature dynamics and their controls in a discontinuous permafrost region on the Seward Peninsula, Alaska. We acquired one-year temperature time series at multiple depths (at 5 or 10 cm intervals up to 85 cm depth) at 45 discrete locations across a 2.3 km2 watershed. We observed a larger spatial variability in winter temperatures than that in summer temperatures at all depths, with the former controlling most of the spatial variability in mean annual temperatures. We also observed a strong correlation between mean annual ground temperature at a depth of 85 cm and mean annual or winter season ground surface temperature across the 45 locations. We demonstrate that soils classified as cold, intermediate, or warm using hierarchical clustering of full-year temperature data closely match their co-located vegetation (graminoid tundra, dwarf shrub tundra, and tall shrub tundra, respectively). We show that the spatial heterogeneity in soil temperature is primarily driven by spatial heterogeneity in snow cover, which induces variable winter insulation and soil thermal diffusivity. These effects further extend to the subsequent summer by causing variable latent heat exchanges. Finally, we discuss the challenges of predicting soil temperatures from snow depth and vegetation height alone by considering the complexity observed in the field data and reproduced in a model sensitivity analysis

Accurate detection of year-to-year variability of plant phenology in an open-canopy black spruce forest in Alaska

第6回極域科学シンポジウム分野横断セッション：[IA] 急変する北極気候システム及びその全球的な影響の総合的解明―GRENE北極気候変動研究事業研究成果報告2015―11月19日（木）　国立極地研究所１階交流アトリウ

Development of phenology model for evaluation of growing season of understory vegetation in an open-canopy black spruce forest in Alaska

第7回極域科学シンポジウム:[OM] 極域気水圏11月29日（火）国立極地研究所 1階 アトリウ

Ground thermal regime in an ice-wedge polygon landscape near Barrow

Ice-wedge polygons are perhaps the most dominant permafrost related features in the Arctic landscape. The microtopography of these features, including rims, troughs, and high and low polygon centers, alter the local hydrology, as water tends to collect in the low areas. During winter, wind redistribution of snow leads to an increased snowpack depth in the low areas, while the slightly higher areas often have thinner snow cover, also leading to differences across the landscape in vegetation communities and soil moisture between higher and lower areas. These differences in local surface conditions lead to spatial variability of the ground thermal regime in the different microtopographic areas and between different types of ice-wedge polygons. We studied four different ice-wedge polygon developmental stages using intensive two-dimensional subsurface temperature measurements. Published here are videos that depict the two-dimensional temperature field cross-section from each polygon, created using the temperature data from five vertical temperature profiles of 16 temperatures for each polygon. The daily average temperature values were interpolated, linearly, onto a grid using the depths converted to elevation and the horizontal distance between temperature profiles. Movies using the daily cross-sections were created to aid in the initial data interpretation and quickly get a sense of the two-dimensional ground thermal dynamics within each polygon. The mean daily ground temperature is shown for the period 15 Sept. 2012 to 30 Oct. 2015 as a cross-section through each polygon (Incipient Polygon starts in 1 Sept. 2013). The magenta bars show the daily snow depth and the location of the snow depth sensors are indicated by the *, black if data is available and red if not. The black line, when present shows the location of the thawing or freezing front. The temperature measurement profiles are shown as black dots for each measurement point