Fine-scale climate change: modelling spatial variation in biologically meaningful rates of warming
Global Change Biology
Reason for embargo
The existence of fine-grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed 'microrefugia'. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here we present a model that is applied to provide fine-grained, multi-decadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely-derived environmental data were used to construct physical variables that capture the effects of terrain, sea-surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom to provide accurate (mean error = 1.21°C; RMS error = 1.63°C) hourly estimates of temperature at a resolution of 100 m for the period 1977 to 2014. We show that rates of warming vary across a landscape primarily due to long-term trends in weather conditions. Total warming varied from 0.87 to 1.16°C, with the slowest rates of warming evident on north-east-facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost-free season varied from +11 to -54 days and the increase annual growing degree-days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west-facing slopes. We emphasise the importance of multi-decadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change. This article is protected by copyright. All rights reserved.
We thank Michael Ashcroft, Richard Gunton and an anonymous referee for helpful comments on the manuscript and Ray Lawman and Rachel Holder for permission to deploy data loggers on land owned by or managed by the National Trust and Natural England. This research was partly funded by the European Social Fund (09099NCO5), NERC ((NE/L00268X/1) and by Natural England.
This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.
Accepted manuscript online: 6 May 2016