scholarly journals Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra

2016 ◽  
Author(s):  
Inge Juszak ◽  
Werner Eugster ◽  
Monique M. P. D. Heijmans ◽  
Gabriela Schaepman-Strub
Keyword(s):  
Active Layer ◽  
Arctic Tundra ◽  
Dwarf Shrub ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Active Layer Thickness ◽  
Vegetation Types ◽  
Transmitted Radiation ◽  
Dwarf Shrubs ◽  
North East

Abstract. Vegetation changes, such as shrub encroachment and wetland expansion, have been observed in many Arctic tundra regions. These changes feed back to permafrost and climate. Permafrost can be protected by soil shading through vegetation as it reduces the amount of solar energy available for thawing. Regional climate can be affected by a reduction in surface albedo as more energy is available for atmospheric and soil heating. Here, we compared the shortwave radiation budget of two common Arctic tundra vegetation types dominated by dwarf shrubs (Betula nana) and wet sedges (Eriophorum angustifolium) in North-East Siberia. We measured time series of the shortwave and longwave radiation budget above the canopy and transmitted radiation below the canopy. Additionally, we quantified soil temperature and heat flux as well as active layer thickness. The mean growing season albedo of dwarf shrubs was 0.15 ± 0.01, for sedges it was higher (0.17 ± 0.02). Dwarf shrub transmittance was 0.36 ± 0.07 on average, and sedge transmittance was 0.28 ± 0.08. The standing dead leaves contributed strongly to the soil shading of wet sedges. Despite a lower albedo and less soil shading, the soil below dwarf shrubs conducted less heat resulting in a 17 cm shallower active layer as compared to sedges. This result was supported by additional, spatially distributed measurements of both vegetation types. Clouds were a major influencing factor for albedo and transmittance, particularly in sedge vegetation. Cloud cover reduced the albedo by 0.01 in dwarf shrubs and by 0.03 in sedges, while transmittance was increased by 0.08 and 0.10 in dwarf shrubs and sedges, respectively. Our results suggest that the observed deeper active layer below wet sedges is not primarily a result of the summer canopy radiation budget. Soil properties, such as soil albedo, moisture, and thermal conductivity, may be more influential, at least in our comparison between dwarf shrub vegetation on relatively dry patches and sedge vegetation with higher soil moisture.

scholarly journals Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra

2016 ◽  
Vol 13 (13) ◽  
pp. 4049-4064 ◽  
Author(s):  
Inge Juszak ◽  
Werner Eugster ◽  
Monique M. P. D. Heijmans ◽  
Gabriela Schaepman-Strub
Keyword(s):  
Active Layer ◽  
Arctic Tundra ◽  
Dwarf Shrub ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Active Layer Thickness ◽  
Vegetation Types ◽  
Transmitted Radiation ◽  
Dwarf Shrubs ◽  
North East

Abstract. Vegetation changes, such as shrub encroachment and wetland expansion, have been observed in many Arctic tundra regions. These changes feed back to permafrost and climate. Permafrost can be protected by soil shading through vegetation as it reduces the amount of solar energy available for thawing. Regional climate can be affected by a reduction in surface albedo as more energy is available for atmospheric and soil heating. Here, we compared the shortwave radiation budget of two common Arctic tundra vegetation types dominated by dwarf shrubs (Betula nana) and wet sedges (Eriophorum angustifolium) in North-East Siberia. We measured time series of the shortwave and longwave radiation budget above the canopy and transmitted radiation below the canopy. Additionally, we quantified soil temperature and heat flux as well as active layer thickness. The mean growing season albedo of dwarf shrubs was 0.15 ± 0.01, for sedges it was higher (0.17 ± 0.02). Dwarf shrub transmittance was 0.36 ± 0.07 on average, and sedge transmittance was 0.28 ± 0.08. The standing dead leaves contributed strongly to the soil shading of wet sedges. Despite a lower albedo and less soil shading, the soil below dwarf shrubs conducted less heat resulting in a 17 cm shallower active layer as compared to sedges. This result was supported by additional, spatially distributed measurements of both vegetation types. Clouds were a major influencing factor for albedo and transmittance, particularly in sedge vegetation. Cloud cover reduced the albedo by 0.01 in dwarf shrubs and by 0.03 in sedges, while transmittance was increased by 0.08 and 0.10 in dwarf shrubs and sedges, respectively. Our results suggest that the observed deeper active layer below wet sedges is not primarily a result of the summer canopy radiation budget. Soil properties, such as soil albedo, moisture, and thermal conductivity, may be more influential, at least in our comparison between dwarf shrub vegetation on relatively dry patches and sedge vegetation with higher soil moisture.

scholarly journals Linking tundra vegetation, snow, soil temperature, and permafrost

2020 ◽  
Vol 17 (16) ◽  
pp. 4261-4279
Author(s):  
Inge Grünberg ◽  
Evan J. Wilcox ◽  
Simon Zwieback ◽  
Philip Marsh ◽  
Julia Boike
Keyword(s):  
Soil Temperature ◽  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Vegetation Change ◽  
Vegetation Type ◽  
Spatial Scales ◽  
Active Layer Thickness ◽  
Vegetation Types ◽  
Thermal Dynamics

Abstract. Connections between vegetation and soil thermal dynamics are critical for estimating the vulnerability of permafrost to thaw with continued climate warming and vegetation changes. The interplay of complex biophysical processes results in a highly heterogeneous soil temperature distribution on small spatial scales. Moreover, the link between topsoil temperature and active layer thickness remains poorly constrained. Sixty-eight temperature loggers were installed at 1–3 cm depth to record the distribution of topsoil temperatures at the Trail Valley Creek study site in the northwestern Canadian Arctic. The measurements were distributed across six different vegetation types characteristic for this landscape. Two years of topsoil temperature data were analysed statistically to identify temporal and spatial characteristics and their relationship to vegetation, snow cover, and active layer thickness. The mean annual topsoil temperature varied between −3.7 and 0.1 ∘C within 0.5 km2. The observed variation can, to a large degree, be explained by variation in snow cover. Differences in snow depth are strongly related with vegetation type and show complex associations with late-summer thaw depth. While cold winter soil temperature is associated with deep active layers in the following summer for lichen and dwarf shrub tundra, we observed the opposite beneath tall shrubs and tussocks. In contrast to winter observations, summer topsoil temperature is similar below all vegetation types with an average summer topsoil temperature difference of less than 1 ∘C. Moreover, there is no significant relationship between summer soil temperature or cumulative positive degree days and active layer thickness. Altogether, our results demonstrate the high spatial variability of topsoil temperature and active layer thickness even within specific vegetation types. Given that vegetation type defines the direction of the relationship between topsoil temperature and active layer thickness in winter and summer, estimates of permafrost vulnerability based on remote sensing or model results will need to incorporate complex local feedback mechanisms of vegetation change and permafrost thaw.

scholarly journals Active Layer Thickness Estimation from X-Band SAR Backscatter Intensity

2016 ◽  
Author(s):  
Barbara Widhalm ◽  
Annett Bartsch ◽  
Marina Leibman ◽  
Artem Khomutov
Keyword(s):  
Land Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Satellite Data ◽  
Active Layer Thickness ◽  
Vegetation Types ◽  
Backscatter Intensity ◽  
X Band ◽  
Spatial Coverage ◽  
The Relationship

Abstract. The active layer above the permafrost, which seasonally thaws during summer is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally. A range of methods, which utilize information from satellite data exist. Their applicability has been demonstrated mostly for shallow depths below 70 cm. Some permafrost areas including central Yamal are characterized by higher Active Layer Thickness (ALT). The relationship between ALT and X-Band SAR backscatter of TerraSAR-X has been investigated in order to explore the possibility of delineating ALT on a continuous and larger spatial coverage in this area. This study shows that the mutual dependency of ALT and TerraSAR-X backscatter on land cover types induces a connection of both parameters. A range of 5 dB can be observed for an ALT range of 100 cm (40–140 cm) and an R2 of 0.66 has been determined over the calibration sites. An increase of ALT with increasing backscatter can be especially determined for ALT > 70 cm. The RMSE over a comparably heterogeneous validation site with maximum ALT of > 150 cm is in the range of 20–22 cm. Deviations are larger for measurement locations with mixed vegetation types.

scholarly journals Linking tundra vegetation, snow, soil temperature, and permafrost

2020 ◽  
Author(s):  
Inge Grünberg ◽  
Evan J. Wilcox ◽  
Simon Zwieback ◽  
Philip Marsh ◽  
Julia Boike
Keyword(s):  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Large Degree ◽  
Small Scale ◽  
Active Layer Thickness ◽  
Snow Melt ◽  
Vegetation Types ◽  
Soil Temperatures ◽  
Temporal And Spatial Characteristics

Abstract. Soil temperatures in permafrost regions are highly heterogeneous on small scales, in part due to variable snow and vegetation cover. Moreover, the temperature distribution that results from the interplay of complex biophysical processes remains poorly constrained. Sixty-eight temperature loggers were installed to record the distribution of topsoil temperatures at the Trail Valley Creek study site in the Northwestern Canadian Arctic. The measurements were distributed across six different vegetation types characteristic for this landscape. Two years of topsoil temperature data were analysed statistically to identify temporal and spatial characteristics and their relationship to vegetation, snow cover and active layer thickness. The mean annual topsoil temperature varied between −3.7 °C and 0.1 °C within a 1.2 km distance, with an approximate average across the landscape of −2.3 °C in 2017 and −1.7 °C in 2018. The observed variation can, to a large degree, be explained by variation in snow cover. Differences in height between vegetation types cause spatially variable snow depth during winter, leading to spatially variable snow melt timing in spring, causing pronounced differences in topsoil mean temperature and temperature variability during those time periods. Summer topsoil temperatures were quite similar below most vegetation types, and not consistently related to active layer thickness at the end of August. The small-scale pattern of vegetation and its influence on snow cover height and snow melt governs the annual topsoil temperature in this permafrost-underlain landscape.

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

scholarly journals Permafrost temperature and active-layer thickness of Yakutia with 0.5-degree spatial resolution for model evaluation

2013 ◽  
Vol 5 (2) ◽  
pp. 305-310 ◽  
Author(s):  
C. Beer ◽  
A. N. Fedorov ◽  
Y. Torgovkin
Keyword(s):  
Layer Thickness ◽  
Spatial Resolution ◽  
Active Layer ◽  
Land Surface ◽  
Grid Cell ◽  
Active Layer Thickness ◽  
East Siberia ◽  
Permafrost Temperature ◽  
Surface Models ◽  
The Mean

Abstract. Based on the map of landscapes and permafrost conditions in Yakutia (Merzlotno-landshaftnaya karta Yakutskoi0 ASSR, Gosgeodeziya SSSR, 1991), rasterized maps of permafrost temperature and active-layer thickness of Yakutia, East Siberia were derived. The mean and standard deviation at 0.5-degree grid cell size are estimated by assigning a probability density function at 0.001-degree spatial resolution. The gridded datasets can be accessed at the PANGAEA repository (doi:10.1594/PANGAEA.808240). Spatial pattern of both variables are dominated by a climatic gradient from north to south, and by mountains and the soil type distribution. Uncertainties are highest in mountains and in the sporadic permafrost zone in the south. The maps are best suited as a benchmark for land surface models which include a permafrost module.

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