Five stakeholder-relevant indices of agro-meteorological change were analysed for the UK, over past (1961-1990) and future (2061-2090) periods. Accumulated Frosts, Dry Days, Growing Season Length, Plant Heat Stress and Start of Field Operations were calculated from the E-Obs (European Observational) and HadRM3 (Hadley Regional Climate Model) PPE (perturbed physics ensemble) data sets. Indices were compared directly and examined for current and future uncertainty. Biases are quantified in terms of ensemble member climate sensitivity and regional aggregation. Maps of spatial change then provide an appropriate metric for end-users both in terms of their requirements and statistical robustness. A future UK is described with fewer frosts, fewer years with a large number of frosts, an earlier start to field operations (e.g., tillage), fewer occurrences of sporadic rainfall, more instances of high temperatures (in both the mean and upper range), and a much longer growing season. 1 Introduction Decision making for climate change adaptation within the land use sector, and appropriate policy development, requires consideration of relevant environmental pressures (Matthews et al. 2008). The variability of key weather-driven factors, thresholds and tolerances must be identified to form the basis for land manager decision-making (Matthews et al. 2008; McCrum et al. 2009; Rivington et al. 2008a, 2013). In the UK 70 % of land-use is agricultural (DEFRA 2011), only 6.8 % can be classified as "urban" (NEA 2012). When in-urban "greenspaces" and water surfaces are accounted for, the UK's built environment drops to roughly 2.3 % of landuse, with less than 0.5 % for Scotland (NEA 2012). Land management invested individuals and agencies are thus highly exposed to environmental change (Kane et al. 1992). Prior studies have focussed largely on metrics of drought (Keyantash and Dracup 2002; Piao et al. 2010) as the most costly form of discrete climate impact (Keyantash and Dracup
ABSTRACT:Atmosphere-Ocean Global Climate Model (AOGCM) output is used for many climate change impact studies and to produce 'predictor' data sets for statistical downscaling methods. Quantitative and qualitative evaluation and validation are required to make informed choices concerning reliable variables and their optimum combinations for both forms of research. Previous study suggests that although mean sea-level pressure is generally well represented in models, biases associated with over-or underestimated activity for the Pacific Decadal Oscillation and the El Nino Southern Oscillation may exist within certain AOGCMs. This potential bias in indices of large-scale atmospheric variability is explored. Improvements in the replication of circulation indices are discovered between the second and third generations of the Canadian AOGCM (CGCM2 and CGCM3). With respect to reanalysis product, CGCM3 output shows less winter-time bias for the Northern Annular Mode and the North Atlantic Index than evident for the other indices under consideration.
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