Upland climate change impacts

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Three fifths of Scotland comprises hills and moors, and here many ... documented, therefore local representations of future upland climate from climate.
Upland climate change impacts – towards improved site-scale assessments for land managers? John Coll1,2, Stuart W. Gibb1 and John Harrison3 1

Environmental Research Institute, North Highland College, UHI Millennium Institute, Thurso, UK. 2 Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, UK. 3 Department of Geography, University of Dundee, Dundee, Scotland, UK. Introduction With recent warming trends projected to amplify as the present century progresses, there are significant concerns surrounding the possible impact of future warming on mountain regions. Three fifths of Scotland comprises hills and moors, and here many Arctic-alpine community elements occur near their southern range limit and are thought to be particularly sensitive to global warming. Superimposed on altitudinal zonations, strong east-west and north-south climatic gradients determine the elevational limits of vegetation communities and upland land use. Consequently, the altitudinal limits of various bio-climatic zones and land use practises differ between the oceanic hills of the west and the markedly more continental hills of the east However, in areas of complex topography the general shortcomings of Global Climate Models (GCMs) and even the finer-scaled Regional Climate Models (RCMs) are well documented, therefore local representations of future upland climate from climate model outputs alone are problematic. Such limitations create a very real tension for policy makers and conservation managers in terms of formulating adaptation strategies, since the magnitude of possible future changes to key climatic variables in mountain regions remains unclear. Aims and Approach We aim to establish if variably combining climate model outputs and station data can be used to improve local representations of future changes to temperature and precipitation for mountainous regions such as the Highlands. Therefore, here we variably combine climate model outputs, station data and model altitudinal components of change for temperature (T) and precipitation (Precip) based on locally observed relationships. We then briefly explore the implications of the experiments for conducting local-scale impact assessments for communities of high conservation value and for vulnerable sectors such as the ski industry. Methods 1. Temperature T-lapse rate models were constructed at 50m intervals to an elevation of 1300m (~coincident with the highest hills) for a range of seasonally representative lapse values. These were applied to quality controlled 1961-1990 station data (QSd) for Onich (15m) in the west and Balmoral in the east (283m) to represent Lochaber and Cairngorm/Caenlochan ‘uplands’ respectively. Tests against four upland station

records ranging from 663m to 1245m indicated the models were performing credibly across the range of mean seasonal maxima (Tmax) and minima (Tmin). For the outputs evaluated here, the range of seasonal lapse rates were meaned across the altitudinal range and the isotherm values associated with the present upper limit of each vegetation zone identified for both the Onich and Balmoral QS d datasets. Primed with QSd values, the lapse rate models were perturbed by United Kingdom Climate Impacts Programme 2002 (UKCIP02) outputs from the Hadley Centre Regional Climate Model (HadRM3) 50km x 50km grid cells corresponding to the stations for the above scenarios. 2. Precipitation QSd for fourteen monthly Precip stations ranging in elevation from 209m – 497m were averaged for two groupings of stations (n = 5; n = 9) for selected seasonal total Precip values (PΣ). A variety of corrections for the orographic enhancement of precipitation were applied to these averaged 1961-1990 PΣ baseline values (BLd) and projected to an elevation of 1300m. BLd values were then perturbed by UKCIP02 outputs from the HadRM3 50km x 50km grid cells for the above scenarios and the results projected to 1300m. Results and Discussion 1. Scenario Selection Some scenario selection criteria underpinned the choice of HadRM3 simulated future T and Precip changes relative to 1961-1990 (ΔTοC and Δ%Precip) used to perturb the QSd and BLd values. Two UKCIP02 scenarios were applied, one for the 2050s and another for the 2080s. These are linked to their equivalent Intergovernmental Panel for Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) storylines and the UK Office of Science and Technology (OST) Foresight Scenarios as below:  2050s Medium-Low: ~SRES B2 Scenario and OST Foresight Scenario - ‘Local Stewardship’;  2080s High: ~SRES A1F1 Scenario and OFT Foresight Scenario - ‘World Markets’. These were considered to be scenarios reflecting a range of possible future socioeconomic pathways on different time-scales and incorporating differing levels of uncertainty. This 2050s and 2080s focus also integrates HadRM3 outputs indicating a greater magnitude of future changes to ΔTοC and Δ%Precip relative to 1961-1990, changes considered potentially more significant in terms of their upland impact. 2. Temperature The modelling approach adopted indicates substantial upward shifts in the HadRM3 perturbed QSd projected mean seasonal isotherms associated with the upper limit of each vegetation zone. This is the case for both western and eastern mountains, although the magnitude of vertical migration varies, both by scenario and for Tmax and Tmin. For instance, in the greatest warming scenario (2080s High), spring Tmax isotherms currently associated with the upper limit of the forest, sub-alpine and low-alpine zones exhibit a vertical migration of ~300m for each zone in the western mountains.

While for the same scenario, autumn Tmin isotherm values associated with each zone are migrating vertically by 500-750m in the western uplands. Whereas in the eastern mountains, 2080s High perturbed QSd values exhibit summer Tmax isotherm shifts of 450-500m for the equivalent zones, while winter Tmin shifts are ~500m relative to the 1961-1990 altitude band associated with each zone. 3. Precipitation Experimental design for evaluation of Δ%Precip with altitude was largely determined by two criteria;  a mean station elevation in closest accordance with the corresponding HadRM3 grid cell elevation. This to minimise computational adjustments for orography in applying HadRM3 outputs to BLd values;  the spatial distribution of available QSd corresponding to the above criterion and coincident with HadRM3 grid cells in geographically representative locations. Both HadRM3 grid cells (eastern locations) selected for the modelling of Δ%Precip simulate a drying relative to 1961-1990 for all seasons other than winter, when Precip increases. However, the magnitude of Δ%Precip varies, both between the HadRM3 grid cells used and is greater overall for the 2080s than the 2050s. Whichever set of orographic adjustments are applied to BLd values, these changes are carried on through to 1300m. However, there are assumptions involved in considering that orographic relationships will remain the same as at present in a warmer world, these also apply to T-relationships with altitude. In addition, the uncertainties inherent in the UKCIP02 scenario construction will be propogated through the modelling approach adopted here. Nonetheless, we suggest that with ongoing refinement, the approach adopted here can be used to better inform stewardship decisions for communities of high conservation value by providing an improved range of local projections. The extension to this work will be an application of the method to examine what future changes to key seasonal isotherms and precipitation regimes could mean for selected habitats. For example, snowbed vegetation communities and sub-arctic willow scrub are vulnerable habitats with distributions largely confined to the Highlands. Similarly, the approach can be readily applied to the ski industry as a regionally vulnerable sector.