H. E. Ahrends

Small-scale albedo-temperature relationship contrast with large-scale relations in Alaskan acidic tussock tundra

Arctic tundra vegetation is characterized by an extreme heterogeneity at a small spatial scale. Optimizing the parameterization of tundra ecosystems in climate models requires detailed knowledge and understanding of soil vegetation- atmosphere feedback mechanisms at different spatial scales. We used a mobile multi-sensor platform for observing variable spectral and thermal responses of different representative vegetation communities within two 50 m long transects in August 2010. The observations sites are located on the North Slope of Alaska. The sensor platform was attached to a cable set up at a height of ~1 m above ground. The data were aggregated to distance increments of 45 cm along the transects and standardized (mean-centered) to account for observation date-specific offsets in measurements that were related to specific light and weather conditions but not to the local vegetation surface. A relative increase in the albedo of 0.01 (1%) was related to an increase in radiometric surface temperatures of 0.1 to 1 K, which is the inverse of the generally accepted surface temperature-albedo relationship observed at larger spatial scales. We explain this finding with cooling effects of the albedo-influencing surface wetness which primarily results from moss and soil evaporation. This cooling effect dominates over other more general heating effects that can be expected over surfaces with lower albedo under absence or near-absence of evaporation. Our findings are also supported by NDVI measurements. These locally inverted temperature-albedo feedbacks need to be considered in climate models that resolve Arctic environments with a high abundance of moss covers. Our results show that frequent observations of different tundra ecosystems using mobile multi-sensor platforms can provide data critical for understanding the land-atmosphere-interactions for the Arctic and the global system.

Short-Term Impacts of the Air Temperature on Greening and Senescence in Alaskan Arctic Plant Tundra Habitats

Climate change is warming the temperatures and lengthening the Arctic growing season with potentially important effects on plant phenology. The ability of plant species to acclimate to changing climatic conditions will dictate the level to which their spatial coverage and habitat-type dominance is different in the future. While the effect of changes in temperature on phenology and species composition have been observed at the plot and at the regional scale, a systematic assessment at medium spatial scales using new noninvasive sensor techniques has not been performed yet. At four sites across the North Slope of Alaska, changes in the Normalized Difference Vegetation Index (NDVI) signal were observed by Mobile Instrumented Sensor Platforms (MISP) that are suspended over 50 m transects spanning local moisture gradients. The rates of greening (measured in June) and senescence (measured in August) in response to the air temperature was estimated by changes in NDVI measured as the difference between the NDVI on a specific date and three days later. In June, graminoid- and shrub-dominated habitats showed the greatest rates of NDVI increase in response to the high air temperatures, while forb- and lichen-dominated habitats were less responsive. In August, the NDVI was more responsive to variations in the daily average temperature than spring greening at all sites. For graminoid- and shrub-dominated habitats, we observed a delayed decrease of the NDVI, reflecting a prolonged growing season, in response to high August temperatures. Consequently, the annual C assimilation capacity of these habitats is increased, which in turn may be partially responsible for shrub expansion and further increases in net summer CO2 fixation. Strong interannual differences highlight that long-term and noninvasive measurements of such complex feedback mechanisms in arctic ecosystems are critical to fully articulate the net effects of climate variability and climate change on plant community and ecosystem processes.

Diurnal Dynamics of Wheat Evapotranspiration Derived from Ground-Based Thermal Imagery

The latent heat flux, one of the key components of the surface energy balance, can be inferred from remotely sensed thermal infrared data. However, discrepancies between modeled and observed evapotranspiration are large. Thermal cameras might provide a suitable tool for model evaluation under variable atmospheric conditions. Here, we evaluate the results from the Penman-Monteith, surface energy balance and Bowen ratio approaches, which estimate the diurnal course of latent heat fluxes at a ripe winter wheat stand using measured and modeled temperatures. Under overcast conditions, the models perform similarly, and radiometric image temperatures are linearly correlated with the inverted aerodynamic temperature. During clear sky conditions, the temperature of the wheat ear layer could be used to predict daytime turbulent fluxes (root mean squared error and mean absolute error: 20–35 W∙m−2, r2: 0.76–0.88), whereas spatially-averaged temperatures caused underestimation of pre-noon and overestimation of afternoon fluxes. Errors are dependent on the models’ ability to simulate diurnal hysteresis effects and are largest during intermittent clouds, due to the discrepancy between the timing of image capture and the time needed for the leaf-air-temperature gradient to adapt to changes in solar radiation. During such periods, we suggest using modeled surface temperatures for temporal upscaling and the validation of image data.