Publication details for Professor B. HuntleyJ.J. Bennie, A.J. Wiltshire, A.N. Joyce, D. Clark, A.R. Lloyd, J. Adamson, T. Parr, R. Baxter & B. Huntley (2010). Characterising inter-annual variation in spatial pattern of thermal microclimate in a UK upland using a combined empirical–physical model. Agricultural and Forest Meteorology 150: 12-19.
- Publication type: Journal Article
Author(s) from Durham
Temperature exerts a fundamental control on ecosystem function, species’ distributions and ecological processes across a range of spatial scales. At the landscape scale, near-surface air temperature may vary spatially over short distances, particularly inmountainous regions. Both themagnitude and spatial pattern of surface temperature may vary on diurnal, seasonal and inter-annual timescales. Furthermore, temperatures measured at the surface of vegetation, influenced by the energy balance of the surface, can differ considerably from air temperature. In order to explore spatial patterns in temperature across the MoorHouse sector of theMoorHouse—Upper Teesdale National Nature Reserve (NNR), Northern Pennines, UK,wederived anempirical linear regressionmodel to predict airtemperature at1 mheight as a functionof landscape metrics derived from a digital elevation model (DTM), and coupled this to an existing physical land-surfacemodel (JULES) in order to predict andmapthermal climate at the vegetation surface across the study area. Spatial patterns in temperature associated with altitudinal lapse rate, katabatic flowand a local fo¨hn effect were incorporated into the regression model. JULES was driven using spatially distributed air temperatures from the empirical model, along with distributed solar and long-wave radiation flux estimates adjusted for surface slope and aspect, and sky-view in order tomodel the surface energy balance and predict thermal climate at the vegetation surface (skin temperature). Aggregate properties such as annual degree days above 5 8C (GDD5), number of ‘‘frost days’’ when the temperature fell below 0 8C (FD0) and number of ‘‘severe frost days’’ when the minimumtemperature fell below5 8C (FD5) were mapped across the reserve for the years 1994–2006. Spatial mapping of surface temperature revealed differences in the 12-year average spatial pattern betweenGDD5, FD0 and FD5, and differences in the spatial patterns of FD0 and FD5 between different years, depending on the relative strength of lapse rates, temperature inversions and the fo¨hn effect. The location of ‘‘warm’’ and ‘‘cool’’ microclimates within the study area varies depending on the dominant atmospheric conditions in a given year and on the thermal property of interest.While GDD5 tended to decrease and FD0 increasedwith increasing altitude in all years, following the gradients in average temperature, the magnitude of these relationships varied considerably between years. FD5 increased in some years and decreased in others, due to the influence of temperature inversions during extreme cold temperature events. We conclude, that in order to predict the landscapescale response of species and communities to climatic change in upland areas accurately, it will be necessary to take into account changes in the frequency and magnitude of different synoptic atmospheric conditions under future climate scenarios.