“Agro-meteorological indices and climate model uncertainty over the UK”

A E Harding,M J Mineter,M Rivington,S F B Tett

doi:10.1007/s10584-014-1296-8

Abstract

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.

Highlights

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)
Of the agro-meteorological indices developed by Matthews et al (2008) five were described as ‘very’ or ‘quite’ useful by stakeholder focus groups (Matthews et al 2008), are calculable from a wide number of climate models and have little conceptual overlap (Table 1)
Given that interpolation issues in the construction of the E-OBS data set (Haylock et al 2008) are unlikely to affect the order of events throughout the year, it seems likely that late Start of regional climate model (RCM) run Sensitivity of Historical (1961–1990) mean

Summary

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). Land management invested individuals and agencies are 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

Methods

Results

Conclusion