Sebastian Westermann

Subpixel heterogeneity of ice-wedge polygonal tundra: a multi-scale analysis of land cover and evapotranspiration in the Lena River Delta, Siberia

ABSTRACT Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3 m resolution) with coarse-scale (up to 30 m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes.

Mechanical Effect of van der Waals Interactions Observed in Real Time in an Ultracold Rydberg Gas

We present time-resolved spectroscopic measurements of Rydberg-Rydberg interactions between two Rydberg atoms in an ultracold gas, revealing the pair dynamics induced by long-range van der Waals interactions between the atoms. By detuning the excitation laser, a specific pair distribution is prepared. Penning ionization on a microsecond time scale serves as a probe for the pair dynamics under the influence of the attractive long-range forces. Comparison with a Monte Carlo model not only explains all spectroscopic features but also gives quantitative information about the interaction potentials. The results imply that the interaction-induced ionization rate can be influenced by the excitation laser. Surprisingly, interaction-induced ionization is also observed for Rydberg states with purely repulsive interactions.

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin.

BackgroundGlobal environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data.MethodsWe explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 – 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions.ResultsSignificant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model.ConclusionsOur results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change.

Modeling the impact of wintertime rain events on the thermal regime of permafrost

In this study, we present field measurements and numerical process modeling from western Svalbard showing that the ground surface temperature below the snow is impacted by strong wintertime rain events. During such events, rain water percolates to the bottom of the snow pack, where it freezes and releases latent heat. In the winter season 2005/2006, on the order of 20 to 50 % of the wintertime precipitation fell as rain, thus confining the surface temperature to close to 0 C for several weeks. The measured average ground surface temperature during the snow-covered period is−0.6C, despite of a snow surface temperature of on average−8.5C. For the considered period, the temperature threshold below which permafrost is sustainable on long timescales is exceeded. We present a simplified model of rain water infiltration in the snow coupled to a transient permafrost model. While small amounts of rain have only minor impact on the ground surface temperature, strong rain events have a long-lasting impact. We show that consecutively applying the conditions encountered in the winter season 2005/2006 results in the formation of an unfrozen zone in the soil after three to five years, depending on the prescribed soil properties. If water infiltration in the snow is disabled in the model, more time is required for the permafrost to reach a similar state of degradation.

Small-scale variation of snow in a regional permafrost model

The strong winds prevalent in high altitude and arctic environments heavily redistribute the snow cover, causing a small-scale pattern of highly variable snow depths. This has profound implications for the ground thermal regime, resulting in highly variable near-surface ground temperatures on the metre scale. Due to asymmetric snow distributions combined with the nonlinear insulating effect of snow, the spatial average ground temperature in a 1 km2 area cannot be determined based on the average snow cover for that area. Land surface or permafrost models employing a coarsely classified average snow depth will therefore not yield a realistic representation of ground temperatures. In this study we employ statistically derived snow distributions within 1 km2 grid cells as input to a regional permafrost model in order to represent sub-grid variability of ground temperatures. This improves the representation of both the average and the total range of ground temperatures. The model reproduces observed sub-grid ground temperature variations of up to 6 C, and 98 % of borehole observations match the modelled temperature range. The mean modelled temperature of the grid cell reproduces the observations with an accuracy of 1.5 C or better. The observed sub-grid variations in ground surface temperatures from two field sites are very well reproduced, with estimated fractions of sub-zero mean annual ground surface temperatures within±10 %. We also find that snow distributions within areas of 1 km2 in Norwegian mountain environments are closer to a gamma than to a lognormal theoretical distribution. The modelled permafrost distribution seems to be more sensitive to the choice of distribution function than to the fine-tuning of the coefficient of variation. When incorporating the small-scale variation of snow, the modelled total permafrost area of mainland Norway is nearly twice as large compared to the area obtained with grid-cell average snow depths without a sub-grid approach.

Permafrost – Physical Aspects, Carbon Cycling, Databases and Uncertainties

Permafrost is defined as ground that remains below 0°C for at least 2 consecutive years. About 24% of the northern hemisphere land area is underlain by permafrost. The thawing of permafrost has the potential to influence the climate system through the release of carbon (C) from northern high latitude terrestrial ecosystems, but there is substantial uncertainty about the sensitivity of the C cycle to thawing permafrost. Soil C can be mobilized from permafrost in response to changes in air temperature, directional changes in water balance, fire, thermokarst, and flooding. Observation networks need to be implemented to understand responses of permafrost and C at a range of temporal and spatial scales. The understanding gained from these observation networks needs to be integrated into modeling frameworks capable of representing how the responses of permafrost C will influence the trajectory of climate in the future.

A Comparison between Simulated and Observed Surface Energy Balance at the Svalbard Archipelago

AbstractThe surface energy balance at the Svalbard Archipelago has been simulated at high resolution with the Weather Research and Forecasting Model and compared with measurements of the individual energy fluxes from a tundra site near Ny-Alesund (located north of Norway), as well as other near-surface measurements across the region. For surface air temperature, a good agreement between model and observations was found at all locations. High correlations were also found for daily averaged surface energy fluxes within the different seasons at the main site. The four radiation components showed correlations above 0.5 in all seasons (mostly above 0.9), whereas correlations between 0.3 and 0.8 were found for the sensible and latent heat fluxes. Underestimation of cloud cover and cloud optical thickness led to seasonal biases in incoming shortwave and longwave radiation of up to 30%. During summer, this was mainly a result of distinct days on which the model erroneously simulated cloud-free conditions, whereas...

Rapid degradation of permafrost underneath waterbodies in tundra landscapes—Toward a representation of thermokarst in land surface models

Waterbodies such as lakes and ponds are abundant in vast Arctic landscapes and strongly affect the thermal state of the surrounding permafrost. In order to gain a better understanding of the impact of small- and medium-sized waterbodies on permafrost and the formation of thermokarst, a land surface model was developed that can represent the vertical and lateral thermal interactions between waterbodies and permafrost. The model was validated using temperature measurements from two typical waterbodies located within the Lena River delta in northern Siberia. Impact simulations were performed under current climate conditions as well as under a moderate and a strong climate-warming scenario. The performed simulations demonstrate that small waterbodies can rise the sediment surface temperature by more than 10°C and accelerate permafrost thaw by a factor of between 4 and 5. Up to 70% of this additional heat flux into the ground was found to be dissipated into the surrounding permafrost by lateral ground heat flux in the case of small, shallow, and isolated waterbodies. Under moderate climate warming, the lateral heat flux was found to reduce permafrost degradation underneath waterbodies by a factor of 2. Under stronger climatic warming, however, the lateral heat flux was too small to prevent rapid permafrost degradation. The lateral heat flux was also found to strongly impede the formation of thermokarst. Despite this stabilizing effect, our simulations have demonstrated that underneath shallow waterbodies (<1 m), thermokarst initiation happens 30 to 40 years earlier than in simulations without preexisting waterbody.

Terrestrial Remote Sensing of Snowmelt in a Diverse High-Arctic Tundra Environment Using Time-Lapse Imagery

Snow cover is one of the crucial factors influencing the plant distribution in harsh Arctic regions. In tundra environments, wind redistribution of snow leads to a very heterogeneous spatial distribution which influences growth conditions for plants. Therefore, relationships between snow cover and vegetation should be analyzed spatially. In this study, we correlate spatial data sets on tundra vegetation types with snow cover information obtained from orthorectification and classification of images collected from a time-lapse camera installed on a mountain summit. The spatial analysis was performed over an area of 0.72 km2, representing a coastal tundra environment in southern Svalbard. The three-year monitoring is supplemented by manual measurements of snow depth, which show a statistically significant relationship between snow abundance and the occurrence of some of the analyzed land cover types. The longest snow cover duration was found on “rock debris” type and the shortest on “lichen-herb-heath tundra”, resulting in melt-out time-lag of almost two weeks between this two land cover types. The snow distribution proved to be consistent over the different years with a similar melt-out pattern occurring in every analyzed season, despite changing melt-out dates related to different weather conditions. The data set of 203 high resolution processed images used in this work is available for download in the supplementary materials.

A Tiling Approach to Represent Subgrid Snow Variability in Coupled Land Surface–Atmosphere Models

AbstractA mosaic approach to represent subgrid snow variation in a coupled atmosphere–land surface model (WRF–Noah) is introduced and tested. Solid precipitation is scaled in 10 subgrid tiles based on precalculated snow distributions, giving a consistent, explicit representation of variable snow cover and snow depth on subgrid scales. The method is tested in the Weather Research and Forecasting (WRF) Model for southern Norway at 3-km grid spacing, using the subgrid tiling for areas above the tree line. At a validation site in Finse, the modeled transition time from full snow cover to snow-free ground is increased from a few days with the default snow cover fraction formulation to more than 2 months with the tiling approach, which agrees with in situ observations from both digital camera images and surface temperature loggers. This in turn reduces a cold bias at this site by more than 2°C during the first half of July, with the noontime bias reduced from −5° to −1°C. The improved representation of subgrid ...