Abstract
Abstract. An accurate representation of spatio-temporal characteristics of precipitation fields is fundamental for many hydro-meteorological analyses but is often limited by the paucity of gauges. Reanalysis models provide systematic methods of representing atmospheric processes to produce datasets of spatio-temporal precipitation estimates. The precipitation from the reanalysis datasets should, however, be evaluated thoroughly before use because it is inferred from physical parameterization. In this paper, we evaluated the precipitation dataset from the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) and compared it against (a) gauged point observations, (b) an interpolated gridded dataset based on gauged point observations (AWAP – Australian Water Availability Project), and (c) a global reanalysis dataset (ERA-Interim). We utilized a range of evaluation metrics such as continuous metrics (correlation, bias, variability, and modified Kling–Gupta efficiency), categorical metrics, and other statistics (wet-day frequency, transition probabilities, and quantiles) to ascertain the quality of the dataset. BARRA, in comparison with ERA-Interim, shows a better representation of rainfall of larger magnitude at both the point and grid scale of 5 km. BARRA also more closely reproduces the distribution of wet days and transition probabilities. The performance of BARRA varies spatially, with better performance in the temperate zone than in the arid and tropical zones. A point-to-grid evaluation based on correlation, bias, and modified Kling–Gupta efficiency (KGE′) indicates that ERA-Interim performs on par or better than BARRA. However, on a spatial scale, BARRA outperforms ERA-Interim in terms of the KGE′ score and the components of the KGE′ score. Our evaluation illustrates that BARRA, with richer spatial variations in climatology of daily precipitation, provides an improved representation of precipitation compared with the coarser ERA-Interim. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Highlights
Availability of accurate precipitation datasets is an essential requirement for the modelling of natural processes, hydrometeorological analyses and forecasting, and monitoring climatic variations and changes (Kirschbaum et al, 2017; Kucera et al, 2013; Robertson et al, 2013)
BARRA precipitation captures this variability in the Australian Water Availability Project (AWAP) precipitation
That the AWAP data provide a poor estimate of precipitation over central Australia, where there is a paucity of gauging information
Summary
Availability of accurate precipitation datasets is an essential requirement for the modelling of natural processes, hydrometeorological analyses and forecasting, and monitoring climatic variations and changes (Kirschbaum et al, 2017; Kucera et al, 2013; Robertson et al, 2013). Variations in the density and coverage of the gauging network make it difficult to capture information on the spatial and temporal variability of rainfall. This is the case in areas covered by deserts, mountains, and oceans and in large areas with low population densities (Salio et al, 2015; Thiemig et al, 2012). This presents a challenge for the Australian continent, where the gauges are mostly located along the densely populated coastal regions. The station network is less dense in the central region, which represents the more arid part of the continent (Johnson et al, 2016)
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