Abstract
Abstract. The high spatio-temporal variability of precipitation is often difficult to characterise due to limited measurements. The available low-resolution global reanalysis datasets inadequately represent the spatio-temporal variability of precipitation relevant to catchment hydrology. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) provides a high-resolution atmospheric reanalysis dataset across the Australasian region. For hydrometeorological applications, however, it is essential to properly evaluate the sub-daily precipitation from this reanalysis. In this regard, this paper evaluates the sub-daily precipitation from BARRA for a period of 6 years (2010–2015) over Australia against point observations and blended radar products. We utilise a range of existing and bespoke metrics for evaluation at point and spatial scales. We examine bias in quantile estimates and spatial displacement of sub-daily rainfall at a point scale. At a spatial scale, we use the fractions skill score as a spatial evaluation metric. The results show that the performance of BARRA precipitation depends on spatial location, with poorer performance in tropical relative to temperate regions. A possible spatial displacement during large rainfall is also found at point locations. This displacement, evaluated by comparing the distribution of rainfall within a day, could be quantified by considering the neighbourhood grids. On spatial evaluation, hourly precipitation from BARRA is found to be skilful at a spatial scale of less than 100 km (150 km) for a threshold of 75th percentile (90th percentile) at most of the locations. The performance across all the metrics improves significantly at time resolutions higher than 3 h. Our evaluations illustrate that the BARRA precipitation, despite discernible spatial displacements, serves as a useful dataset for Australia, especially at sub-daily resolutions. Users of BARRA are recommended to properly account for possible spatio-temporal displacement errors, especially for applications where the spatial and temporal characteristics of rainfall are deemed very important.
Highlights
Precipitation is highly variable across both space and time, especially at spatial and temporal scales relevant to catchment hydrology (Michaelides et al, 2009)
The objective of this paper is to present an evaluation of sub-daily BARRA precipitation at temporal and spatial resolutions that are relevant to catchment hydrology applications
This is partly due to reduced inherent bias arising from the adoption of longer temporal accumulations, which reduces the potential for differences in timing between observations and model estimates
Summary
Precipitation is highly variable across both space and time, especially at spatial and temporal scales relevant to catchment hydrology (Michaelides et al, 2009). An understanding of the spatio-temporal pattern of precipitation is vital for many scientific and operational applications, such as hydro-climatic modelling and the forecasting of floods (Golding et al, 2016; Kucera et al, 2013; Paschalis et al, 2014). This understanding relies on access to high-resolution precipitation datasets. The general sources of precipitation data are gauge measurements, ground-based radars, satellites, and atmospheric reanalysis models (Michaelides et al, 2009). Global reanalysis datasets (e.g. NCEP-CFSR, Saha et al, 2010; ERA-Interim, Dee et al, 2011; JRA-55, Kobayashi et al, 2015) and satellite products (e.g. TMPA, Huffman et al, 2007; IMERG, Huffman et al, 2018) provide a continuous and consistent estimate at varying spatial (0.05 to 2.5◦) and temporal resolution (hourly to daily)
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