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According to IPCC high elevation areas are highly vulnerable to climate change. Since these ecosystems have a considerable carbon stock, it is crucial to investigate the influence of extreme climate conditions such as drought on net ecosystem CO2 fluxes (NEE), the difference between the two components gross primary production (GPP) and ecosystem respiration (Reco). Grasslands cover 20–30% of Swiss landscapes and have a significant carbon stock of about 11% (of total carbon stock of Switzerland according to Bolliger et al. (2008)). However, relative changes in GPP and Reco can transform an ecosystem from a net carbon sink to a net carbon source to the atmosphere, especially under changing environmental conditions. In this study, we aim to understand the impact of extreme summer drought on NEE and evapotranspiration of a Swiss alpine grassland by comparing the year 2018 to the preceding 3-year period. In addition, we studied the influence of a change in snow cover on winter fluxes as an important indicator of climate change. To perform this study, we used continuous eddy covariance data measured for about 4 years at Crap Alv (Alp Weissenstein, CH-AWS, Swiss Fluxnet) located at 2000 m a.s.l. in the Grisons, eastern Switzerland. The site is grazed in summer for about three months from mid-June to mid-September and thus is extensively managed. We hypothesize that the extreme 2018 summer drought reduced carbon uptake while increasing ecosystem respiration and therefore reduced the capacity of the grassland for net CO2 uptake. Bolliger, J., Hagedorn, F., Leifeld, J., Böhl, J., Zimmermann, S., Soliva, R., Kienast, F., 2008. Effects of land-use change on carbon stocks in Switzerland. Ecosystems 11: 895–907. [ABSTRACT FROM AUTHOR]

Seasonal snow has received much attention in the community because of its sensitivity to global climate change and obvious effect on regional energy and water balance. Most previous studies focus on the change of seasonal snow variables under global warming, but less work on its inner principle. In this study, we analyzed the variability of snow cover fraction (SCF) and snow depth (SD) over three typical land cover types of open shrubland, evergreen needleleaf and mixed forest, which have widely distribution in Northern Hemisphere (NH). The results demonstrated that there is different annual variation between SCF and SD over all selected regions, which results that the curves of relationship between monthly SCF and SD are not overlapping between the stages of accumulation and ablation. Meanwhile, SCF and SD showed different characters over selected regions, leading to the curves of relationship between SCF and SD taking different shapes in these regions. Such relationship is an effective tool in the simulation of snow processes in model. However, the relationship is not fully considered in the CMIP5, which always has an underestimate in accumulation stage and an overestimate in ablation stage. Therefore, the different relationship between SCF and SD of snow parameterization scheme in the model over regions is a potential improvement topic to the ability of simulation in the future. [ABSTRACT FROM AUTHOR]

The twin German satellites TerraSAR-X and TanDEM-X have been collecting SAR data inbistatic configuration since 2010. This is currently the only available bistatic mission, wherethe interferometric image pair is acquired within the same survey avoiding temporaldecorrelation. In September 2016 the global TanDEM-X DEM was completed achieving anunprecedented homogeneity and accuracy at 12 m horizontal spacing. Its relative heightaccuracy is specified with 90% confidence level below 2 m and under 4 m for flat and steepterrain, respectively. It achieves in more than the half of the tiles globally 1 m and 2 m forflat and steep terrain, respectively. The global absolute accuracy with 90% confidencelevel is below 3.5 m. The unedited 90 m spacing version is freely available sinceOctober 2018. It is purely derived from the acquired interferometric SAR data, whichdelivers reliable values on non-water surfaces, and covers almost the completelandmass 99.89%. The generation of an edited version is planned for the end of2019, where opportune water levelling and gap filling are considered. On the otherhand, it is very important to be aware of the intrinsic radar characteristics whenusing the TanDEM-X global DEM: the height of forested and snow covered areascorresponds to the mean measured phase center that returns from the illuminatedvolume. The wave’s capability to penetrate into a volume depends on its density,structure and the radar frequency. The height of the generated DEM is in thesecases under the surface. For forest the height is over the terrain close to the topof the canopy and for ice under the terrain. This aspect is sometimes seen as anobstacle to use DEM derived by SAR, on the other hand we see an opportunity todetect volume as it leads to a certain amount of decorrelation on the data. As otherdecorrelation can be well assessed is possible to estimate the volume decorrelation fromthe coherence. Since the delivered raw data is remarkably good, further analysishave been conducted and the data has been used for mapping other bio-physicalvariables, based on these principles. Classification algorithms on ice, forest, and waterhave been developed, as well as tested and validated. A global forest map has beenderived and is freely accessible for scientists. Planned is also a global water mapand Antarctica ice facies map. Furthermore the satellites are well in shape andresources are available to acquire the globe at least once more and allow for thegeneration of a change DEM. From the lessons learned the acquisition plan hasbeen adapted in order to achieve the best in the less time, considering an editedversion of the DEM as base. Finally, the land cover maps in addition to the editedDEM and change DEM are very promising products for geomorphology purposes. [ABSTRACT FROM AUTHOR]