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BARRA v1.0: Kilometre-scale downscaling of an Australian regional atmospheric reanalysis over four midlatitude domains


Su, CH and Eizenberg, N and Jakob, D and Fox-Hughes, P and Steinle, P and White, CJ and Franklin, C, BARRA v1.0: Kilometre-scale downscaling of an Australian regional atmospheric reanalysis over four midlatitude domains, Geoscientific Model Development, 14, (7) pp. 4357-4378. ISSN 1991-959X (2021) [Refereed Article]


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Copyright 2021 The Authors Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.5194/gmd-14-4357-2021


Regional reanalyses provide a dynamically consistent recreation of past weather observations at scales useful for local-scale environmental applications. The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of kilometre-scale (1-4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realize the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four midlatitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind, and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of the intensity and timing of precipitation during the thunderstorm seasons in NSW and spatial patterns of sub-daily rain fields during storm events. BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, as well as underestimation of light rain occurrence. As a hindcast-only system, BARRA-C largely inherits the domain-averaged bias pattern from BARRA-R but does produce different climatological extremes for temperature and precipitation. An added-value analysis of temperature and precipitation extremes shows that BARRA-C provides additional skill over BARRA-R when compared to gridded observations. The spatial patterns of BARRA-C warm temperature extremes and wet precipitation extremes are more highly correlated with observations. BARRA-C adds value in the representation of the spatial pattern of cold extremes over coastal regions but remains biased in terms of magnitude.

Item Details

Item Type:Refereed Article
Keywords:office unified model, forecasting convection, data assimilation, weather research, climate, impact, scheme, Jules, cloud, configuration
Research Division:Earth Sciences
Research Group:Climate change science
Research Field:Climatology
Objective Division:Environmental Management
Objective Group:Air quality, atmosphere and weather
Objective Field:Atmospheric processes and dynamics
UTAS Author:Fox-Hughes, P (Dr Paul Fox-Hughes)
UTAS Author:White, CJ (Dr Chris White)
ID Code:152322
Year Published:2021
Web of Science® Times Cited:4
Deposited By:Geography and Spatial Science
Deposited On:2022-08-17
Last Modified:2022-09-07
Downloads:3 View Download Statistics

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