Assessing gridded climate datasets to derive regional climate state variables across the Arctic

The rapid warming of Arctic regions has severe consequences for nature and environment. To understand the impact of climate change on terrestrial ecosystems climate indicators, or climate state variables are used to monitor and explain the connections between weather, climate and components of the ecosystems.

Arctic ecosystems are vulnerable to climatic end environmental changes. The number of species is relatively few, and they depend very much on each other.  Weather and/or climate events causing abrupt change in one component will often have a direct consequence on several other components within the entire system.

Within the COAT (Climate-ecological observatory for Arctic Tundra, www.coat.no/en/) several climate indicators addressing these challenges for different ecosystem components have been identified and defined. These indicators consist of time aggregated statistics that summarize climate or weather-related events for a specific season or time periods of the year that typically describe plausible explanation for variability in ecosystems. These indicators represent input variables to conceptual ecosystem component models, e.g. for different types of vegetation, herbivores or ungulates.

To get a better understanding a pan-Arctic approach is initiated to investigate the trends and variability in a selection of these indicators. We have identified five regions in the European Arctic, three in Greenland (Nuuk, Disko, Zackenberg), one on Spitsbergen and one north-eastern Norway. Each of these regions are defined as squares of 200x200 km.

The climate indicators are estimated from a suite of gridded datasets, both regional reanalyzes, hindcasts and observation grids. The indicators are estimated for each grid cell in the input datasets and then aggregated to regional scale.

In this presentation we present a comparison of the derived indicators, highlighting the differences between the various input datasets. We also analyze the temporal variations in and between the various regions to better understand how climate variability can be used to describe ecosystem responses within the areas of interest.