Downscaling regional climate data to calculate the radiative index of dryness in complex terrain

Abstract

The radiative index of dryness (or aridity index) is a non-dimensional measure of the long-term balance between rainfall and net radiation. Quantifying aridity requires spatially distributed information on net radiation and rainfall. The variability in net radiation in complex terrain can be modelled at high spatial resolution by combining point data with equations that incorporate the effects of elevation, surface geometry and atmospheric attenuation of incoming radiation. At large spatial scales and over long time periods, however, the combination of seasonality, year to year variations and spatial variability in climate result in complex spatial-temporal patterns of incoming radiation, which are more effectively captured in satellite-based measurements. This study uses a high resolution model of shortwave radiation as a tool for downscaling satellite-derived data on incoming radiation. The aim was to incorporate topographic effects on net radiation in complex terrain while retaining information on regional and seasonal trends captured in satellite data. The method relies on satellite-based measures of incoming radiation from the Australian Bureau of Meteorology (BoM) to provide the spatial coverage and long-term data that represent the average incoming radiation across the state of Victoria in southeast Australia. These long-term data were coupled with a topographic downscaling algorithm to produce estimates of net radiation and aridity at the resolution of a 20 m digital elevation model. Results show that annual precipitation (and cloud fraction) gradients drive the variability in aridity at large scales (10-100 km) while topography (e.g. slope aspect and slope angle) are the main drivers at small scales (e.g. 1 km). The aridity index varied between 0.24 and 10.95 across the state of Victoria. The effect of aridity on vegetation was apparent at local scales through systematic variations in tree-height along rainfall gradients and across aspects with different levels of exposure to solar radiation.

Climate Dictates Magnitude of Asymmetry in Soil Depth and Hillslope Gradient

“…The soil depth data suggest that under current conditions, erosion rates vary by a factor of 7.4 between the dry and wet end-members of the domain. Gridded LAI values for hillslopes across 5 × 5km polygons over the three focus sites were binned in regular intervals of aridity index (Nyman et al, 2014). Thus, it appears that the effects of Three climatic-domains are identified across the aridity index gradient (in the sense of Budyko, 1974): energy limitation (EL), water limitation (WL), and the transition (TR).…”

“…In high rainfall zones (MAP > 1,200 mm/year) fire frequency is low (>100-year interval; Cheal, 2010), and forests are dominated by stands of tall (>50 m) Eucalyptus regnans trees, or by E. delegatensis trees when elevation is >1,000 m above sea level. Soil hydraulic properties, vegetation structure, and microclimate are all strongly related to aridity index (AI), which has been calculated at the hillslope scale (20 m resolution) from the ratio of mean annual potential evapotranspiration (mm/year) to annual precipitation (Nyman et al, 2014). In intermediate rainfall zones (MAP 800-1,200 mm/year), vegetation structure is influenced by aspect.…”

“…Vegetation reflects climatic conditions at large (eg., Budyko, 1974), intermediate (eg., Tesemma et al, 2014), and small (eg., Nyman et al, 2014) scales. Because vegetation cover has a strong effect on soil erosion (Istanbulluoglu et al, 2004;Istanbulluoglu & Bras, 2005) and development (eg., Amundson et al, 2015), local variations in microclimatic conditions often result in different soil depths (Goodfellow et al, 2014;Pelletier et al, 2013).…”

Effects of aridity in controlling the magnitude of runoff and erosion after wildfire

“…The Köppen‐Greiger climate classification for this part of Victoria is Cfa, warm temperate with hot summers, and cool wet winters [ Kottek et al ., ]. Aridity index is a measure of long‐term water balance between net radiation and precipitation [ Nyman et al ., ] and ranges from 0.2 to 10.2 across Victoria; however, in forested upland and alpine bioregions AI ranges from 0.2 to 6.5, with and mean of 2.2. The mean aridity for the small study catchments was 2.2 which is within the range that is typical of many open forests and woodlands in south‐east Australia.…”

“…Sheridan et al . [] used a downscaled aridity index (AI) (dryness index) [ Budyko , ; Nyman et al ., ], to classify experimental sites in Victorian upland forests, demonstrating a pronounced (order of magnitude) decrease in postwildfire hydraulic conductivity with increasing dryness. Variability in postwildfire physical and hydraulic soil properties was found to be highly correlated with the magnitude of observed postwildfire erosion [ Sheridan et al ., ].…”