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

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Su, CH, Eizenberg, N, Jakob, D, Fox-Hughes, P, Steinle, P, White, CJ ORCID: 0000-0003-1791-4784 and Franklin, C 2021 , 'BARRA v1.0: Kilometre-scale downscaling of an Australian regional atmospheric reanalysis over four midlatitude domains' , Geoscientific Model Development, vol. 14, no. 7 , pp. 4357-4378 , doi: 10.5194/gmd-14-4357-2021.

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Abstract

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 Type: Article
Authors/Creators:Su, CH and Eizenberg, N and Jakob, D and Fox-Hughes, P and Steinle, P and White, CJ and Franklin, C
Keywords: office unified model, forecasting convection, data assimilation, weather research, climate, impact, scheme, Jules, cloud, configuration
Journal or Publication Title: Geoscientific Model Development
Publisher: Copernicus GmbH
ISSN: 1991-959X
DOI / ID Number: 10.5194/gmd-14-4357-2021
Copyright Information:

Copyright 2021 The AuthorsLicensed under Creative Commons Attribution 4.0 International (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/

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