Assessment of snow cover of northern Eurasia for climate model validation and related GMES snow monitoring services

Assessment of snow cover of northern Eurasia for climate model validation and related GMES snow monitoring services

Pulliainen, J.* Takala, M.*, Lahtinen, P.*, Kontu, A*, Koskinen, J.*, Järvinen, H.*,
Metsämäki, S.**, Eskelinen, M.**, Sucksdorff, Y.**, Kärnä, J-P*** and Luojus, K.***

Contact: jouni.pulliainen@fmi.fi
* Finnish Meteorological Institute, Erik Palmenin Aukio 1,P.O. Box 503, FI-00101, FINLAND
** Finnish Environment Institute
*** Helsinki University of Technology

Snow cover is one of the most important elements of both the climate and hydrological system in the Northern Hemisphere. Large areas of northern Eurasian territory are covered by seasonal snow that has been confirmed to be a sensitive climate change indicator. The snow extent over northern Eurasia influences the air temperature through positive albedo feedback and through insulation of soil from the atmosphere, as demonstrated by observations and modelling. Snow cover is also the main contributor to freshwater run-off in northern Eurasia and thus influences the thermohaline ocean circulation and ocean-atmospheric energy exchange and, consequently, the generation of cyclones bringing the snow back. Knowledge of the extent and amount of snow serves as important information for climate change studies. This includes the use of observational snow cover information as validation input for climate models. By improving the spatial and temporal assessment of snow cover characteristics in the past we can better predict the global climate change and the uncertainties of predictions. The importance of snow cover monitoring is emphasized by the fact that predictions indicate sharp decline in seasonal snow cover.

The sparseness of ground-based meteorological/climatic and hydrological monitoring network is a major handicap for the mapping of snow cover in boreal and sub-arctic zones of Eurasia and North America. For example in Russia, this problem is enhancing as the number of active monitoring stations is rapidly decreasing since early 1990’s. The utilisation of space-borne data in addition to ground-based observations provides a technique to obtain improved information on snow characteristics, such as snow water equivalent (SWE) and the extent of snow. It is expected that the use of this information yields improved spatial mapping of snow cover, which can significantly improve the reliability of climate trend assessments. A great benefit will be the detection of snow line, particularly the transition zone with fractional wet snow coverage, which is commonly known as a difficult object.

In this investigation we developed a comprehensive method to combine satellite data from different sources (space-borne microwave radiometer and optical data) together with ground observations (e.g. from synoptic weather observations). As the ground observation network in northern latitudes is sparse in general, the combined use of satellite data and ground-based observations provides the only possibility to obtain spatially detailed observational information on snow cover. Here, the accuracy improvement obtained by using satellite in addition to ground-based observations is presented. In addition, observed statistical features of snow cover can be compared with climate model simulations to examine model performance in representing contemporary snow cover characteristics. Based on this comparison, we can assess the reliability of projected future trends of snow cover in northern Eurasia.

The Earth Observation (EO) data aided snow information systems developed here are also part of the ESA’s GMES/GSE PolarView service. The developed and implemented Snow Water Equivalent (SWE) monitoring system is operated by the Finnish Meteorological Institute (FMI) covering the whole northern Eurasia, whereas the regional optical data-based monitoring of fractional snow covered area (SCA) service is operated by the Finnish Environment Institute covering about the drainage basin of the Baltic Sea. The characteristics and data products of these services are also presented here.