Articles | Volume 23, issue 8
https://doi.org/10.5194/hess-23-3387-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-3387-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Aug 2019
Research article |
| 19 Aug 2019
| 19 Aug 2019
An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia
Suwash Chandra Acharya
CORRESPONDING AUTHOR
Department of Infrastructure Engineering, the University of
Melbourne, Melbourne, Australia
Rory Nathan
Department of Infrastructure Engineering, the University of
Melbourne, Melbourne, Australia
Quan J. Wang
Department of Infrastructure Engineering, the University of
Melbourne, Melbourne, Australia
Chun-Hsu Su
Bureau of Meteorology, Melbourne, Australia
Nathan Eizenberg
Bureau of Meteorology, Melbourne, Australia
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Cited
29 citations as recorded by crossref.
- Mean and extreme precipitation over Aotearoa New Zealand: A comparison across multiple different estimation techniques G. Vishwanathan et al. 10.1002/joc.8017
- Temporal disaggregation of daily rainfall measurements using regional reanalysis for hydrological applications S. Acharya et al. 10.1016/j.jhydrol.2022.127867
- Downscaling long lead time daily rainfall ensemble forecasts through deep learning H. Jin et al. 10.1007/s00477-023-02444-x
- A Global Perspective of Tropical Cyclone Precipitation in Reanalyses E. Jones et al. 10.1175/JCLI-D-20-0892.1
- Assessment of global reanalysis precipitation for hydrological modelling in data-scarce regions: A case study of Kenya M. Wanzala et al. 10.1016/j.ejrh.2022.101105
- Which Rainfall Errors Can Hydrologic Models Handle? Implications for Using Satellite‐Derived Products in Sparsely Gauged Catchments C. Stephens et al. 10.1029/2020WR029331
- The contributions of fronts, lows and thunderstorms to southern Australian rainfall A. Pepler et al. 10.1007/s00382-020-05338-8
- How reliable are the satellite-based precipitation estimations in guiding hydrological modelling in South China? J. Su et al. 10.1016/j.jhydrol.2021.126705
- BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia C. Su et al. 10.5194/gmd-12-2049-2019
- Quantification of global Digital Elevation Model (DEM) – A case study of the newly released NASADEM for a river basin in Central Vietnam T. Tran et al. 10.1016/j.ejrh.2022.101282
- Evaluation of multiple reanalyses in reproducing the spatio‐temporal variability of temperature and precipitation indices over southern South America R. Balmaceda‐Huarte et al. 10.1002/joc.7142
- Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa M. Dembélé et al. 10.5194/hess-24-5379-2020
- CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia K. Fowler et al. 10.5194/essd-13-3847-2021
- Evaluation of Satellite-Based and Reanalysis Precipitation Datasets with Gauge-Observed Data over Haraz-Gharehsoo Basin, Iran M. Goodarzi et al. 10.3390/su142013051
- Evaluation of IMERG V05B 30-Min Rainfall Estimates over the High-Elevation Tropical Andes Mountains N. Bulovic et al. 10.1175/JHM-D-20-0114.1
- A global view of observed changes in fire weather extremes: uncertainties and attribution to climate change Z. Liu et al. 10.1007/s10584-022-03409-9
- Climate Extremes across the North American Arctic in Modern Reanalyses A. Avila-Diaz et al. 10.1175/JCLI-D-20-0093.1
- Ability of an Australian reanalysis dataset to characterise sub-daily precipitation S. Acharya et al. 10.5194/hess-24-2951-2020
- A review of early severe weather applications of high‐resolution regional reanalysis in Australia P. Fox‐Hughes et al. 10.1002/met.2087
- West African Summer Monsoon Precipitation Variability as Represented by Reanalysis Datasets K. Quagraine et al. 10.3390/cli8100111
- Assessment of the capability of modern reanalyses to simulate precipitation in warm months using adjusted radar precipitation V. Bližňák et al. 10.1016/j.ejrh.2022.101121
- Diverging identifications of extreme precipitation events from satellite observations and reanalysis products: A global perspective based on an object-tracking method T. Wang et al. 10.1016/j.rse.2023.113490
- Spatial and Temporal Evaluation of the Latest High-Resolution Precipitation Products over the Upper Blue Nile River Basin, Ethiopia S. Abebe et al. 10.3390/w12113072
- Comparison of different quantile delta mapping schemes in frequency analysis of precipitation extremes over mainland Southeast Asia under climate change X. Qin & C. Dai 10.1016/j.jhydrol.2021.127421
- Reliability of the ERA5 in Replicating Mean and Extreme Temperatures across Europe K. Velikou et al. 10.3390/w14040543
- Evaluation of ERA5 and ERA5-Land reanalysis precipitation datasets over Spain (1951–2020) J. Gomis-Cebolla et al. 10.1016/j.atmosres.2023.106606
- A dynamic and evidence-based approach to mapping burn potential R. van Dongen et al. 10.1071/WF22077
- Estimating daily precipitation climatology by postprocessing high‐resolution reanalysis data Y. Du et al. 10.1002/joc.8079
- BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia C. Su et al. 10.5194/gmd-12-2049-2019
28 citations as recorded by crossref.
- Mean and extreme precipitation over Aotearoa New Zealand: A comparison across multiple different estimation techniques G. Vishwanathan et al. 10.1002/joc.8017
- Temporal disaggregation of daily rainfall measurements using regional reanalysis for hydrological applications S. Acharya et al. 10.1016/j.jhydrol.2022.127867
- Downscaling long lead time daily rainfall ensemble forecasts through deep learning H. Jin et al. 10.1007/s00477-023-02444-x
- A Global Perspective of Tropical Cyclone Precipitation in Reanalyses E. Jones et al. 10.1175/JCLI-D-20-0892.1
- Assessment of global reanalysis precipitation for hydrological modelling in data-scarce regions: A case study of Kenya M. Wanzala et al. 10.1016/j.ejrh.2022.101105
- Which Rainfall Errors Can Hydrologic Models Handle? Implications for Using Satellite‐Derived Products in Sparsely Gauged Catchments C. Stephens et al. 10.1029/2020WR029331
- The contributions of fronts, lows and thunderstorms to southern Australian rainfall A. Pepler et al. 10.1007/s00382-020-05338-8
- How reliable are the satellite-based precipitation estimations in guiding hydrological modelling in South China? J. Su et al. 10.1016/j.jhydrol.2021.126705
- BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia C. Su et al. 10.5194/gmd-12-2049-2019
- Quantification of global Digital Elevation Model (DEM) – A case study of the newly released NASADEM for a river basin in Central Vietnam T. Tran et al. 10.1016/j.ejrh.2022.101282
- Evaluation of multiple reanalyses in reproducing the spatio‐temporal variability of temperature and precipitation indices over southern South America R. Balmaceda‐Huarte et al. 10.1002/joc.7142
- Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa M. Dembélé et al. 10.5194/hess-24-5379-2020
- CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia K. Fowler et al. 10.5194/essd-13-3847-2021
- Evaluation of Satellite-Based and Reanalysis Precipitation Datasets with Gauge-Observed Data over Haraz-Gharehsoo Basin, Iran M. Goodarzi et al. 10.3390/su142013051
- Evaluation of IMERG V05B 30-Min Rainfall Estimates over the High-Elevation Tropical Andes Mountains N. Bulovic et al. 10.1175/JHM-D-20-0114.1
- A global view of observed changes in fire weather extremes: uncertainties and attribution to climate change Z. Liu et al. 10.1007/s10584-022-03409-9
- Climate Extremes across the North American Arctic in Modern Reanalyses A. Avila-Diaz et al. 10.1175/JCLI-D-20-0093.1
- Ability of an Australian reanalysis dataset to characterise sub-daily precipitation S. Acharya et al. 10.5194/hess-24-2951-2020
- A review of early severe weather applications of high‐resolution regional reanalysis in Australia P. Fox‐Hughes et al. 10.1002/met.2087
- West African Summer Monsoon Precipitation Variability as Represented by Reanalysis Datasets K. Quagraine et al. 10.3390/cli8100111
- Assessment of the capability of modern reanalyses to simulate precipitation in warm months using adjusted radar precipitation V. Bližňák et al. 10.1016/j.ejrh.2022.101121
- Diverging identifications of extreme precipitation events from satellite observations and reanalysis products: A global perspective based on an object-tracking method T. Wang et al. 10.1016/j.rse.2023.113490
- Spatial and Temporal Evaluation of the Latest High-Resolution Precipitation Products over the Upper Blue Nile River Basin, Ethiopia S. Abebe et al. 10.3390/w12113072
- Comparison of different quantile delta mapping schemes in frequency analysis of precipitation extremes over mainland Southeast Asia under climate change X. Qin & C. Dai 10.1016/j.jhydrol.2021.127421
- Reliability of the ERA5 in Replicating Mean and Extreme Temperatures across Europe K. Velikou et al. 10.3390/w14040543
- Evaluation of ERA5 and ERA5-Land reanalysis precipitation datasets over Spain (1951–2020) J. Gomis-Cebolla et al. 10.1016/j.atmosres.2023.106606
- A dynamic and evidence-based approach to mapping burn potential R. van Dongen et al. 10.1071/WF22077
- Estimating daily precipitation climatology by postprocessing high‐resolution reanalysis data Y. Du et al. 10.1002/joc.8079
1 citations as recorded by crossref.
Latest update: 23 Apr 2024
Short summary
BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to...
