DOI: 10.5281/zenodo.10521068
title: Simulated severe convective wind events and environments from the Bureau of Meteorology Atmospheric Regional Projections for Australia (BARPA)

description: Contacts for further details:



This data record and associated research: Andrew Brown (andrewb1@student.unimelb.edu.au)

BARPA data: Chun Hsu Su (chunhsu.su@bom.gov.au), Christian Stassen (Christian.Stassen@bom.gov.au), Harvey Ye (harvey.ye@bom.gov.au)


Introduction

This record contains data in support of Brown et al. (2024), including post-processed regional climate model data, automatic weather station observations, and post-processed reanalysis data over southeastern Australia for various time periods over December-Febrary months only (see descriptions below). This data relates to analysis of severe convective wind gusts in historical and future climate, with analysis scripts in this repository. The data are described here according to the directory structure of this record (noting the files and directories have been compressed into barpa_data.tgz), as well as the relevant data sources. 

Data sources



The Bureau of Meteorology Atmospheric Regional Projections for Australia (BARPA). A regional climate model containing a regional (BARPA-R) and convection-permitting (BARPAC-M) configuration, with large-scale forcing from ERA-Interim (1990-2015) and ACCESS1-0 using a historical (1985-2005) and RCP8.5 (2039-2059) forcing. See Brown et al. (2024) and Su et al. (2021) for more details. Note that any reuse of this data should properly acknowledge the Australian Bureau of Meteorology. Note also that the BARPA data used here was produced as part of the Electricity Sector Climate Information project (with licence and disclaimers here), with more current BARPA versions (not used here) available at https://dx.doi.org/10.25914/z1x6-dq28. 

Measured wind gusts from automatic weather stations (AWS). Gust data is provided by the Australian Bureau of Meteorology, from 272 AWS locations over 2005-2015. Note that any reuse of this data should properly acknowledge the Australian Bureau of Meteorology.

The ERA5 reanalysis from the European Center for Medium Range Weather Forecasting (Hersbach 2020).

The ERA-Interim reanalysis from the European Center for Medium Range Weather Forecasting (Dee 2011).


/10min_points

This directory contains .csv files, with wind gust and related environmental data at 10-minute intervals at point locations, corresponding to automatic weather station locations. Data is available over 2005-2015. Files are named in the form barpac_m_aws_<state>.csv and barpac_m_aws_<state>_barpa_r_interp.csv. Here, <state> represents different administrative regions in southeast Australia, including New South Wales (nsw), Victoria (vic), South Australia (sa) and Tasmania (tas). See Figure 1 in Brown et al. (2024) for a map of station locations, that is also included in the /meta directory. The barpa_r_interp suffix indicates that the BARPAC-M wind gusts have been interpolated to the BARPA-R grid for comparison.

This data is used in Brown et al. (2024) for evaluation and analysis of BARPA wind gusts in the historical climate (forced by ERA-Interim). The user is directed to that paper for more information on data processing. For the .csv files here, column descriptions are provided in Table 1, below.

/daily_points

This directory contains .csv files, with data associated with daily maximum wind gusts at point locations. This data is derived from the 10min_points data described above, with the same column descriptions in Table 1, below. The different files in this directory are as follows:





barpac_m_aws_dmax_obs.csvDaily maximum observed wind gust from AWS measurements, with associated wind gust ratio and environmental conditions from ERA5.




barpac_m_aws_dmax_2p2km.csvDaily maximum simulated wind gust from BARPAC-M at closest grid point to AWS location, with associated wind gust ratio, lighting flash count, and environmental conditions from BARPA-R.




barpac_m_aws_dmax_12km.csvDaily maximum simulated wind gust from BARPA-R at closest grid point to AWS location, with associated wind gust ratio, lightning flash count, and environmental conditions.




barpac_m_aws_dmax_erai.csvDaily maximum simulated wind gust from ERA-Interim at closest grid point to AWS location, with associated wind gust ratio and environmental conditions from ERA5.




barpac_m_aws_dmax_2p2km_barpa_r_interp.csvAs in barpac_m_aws_dmax_2p2km.csv, but wind gusts are interpolated to the BARPA-R grid prior to calculating the daily maximum.



/monthly_nc

This directory contains monthly netcdf files at 12 km horizontal grid spacing, with post-processed BARPA data, relating to simulated severe convective wind gusts (from BARPAC-M), and their associated large-scale environments (from BARPA-R). This includes BARPAC-M and BARPA-R data that has been forced by the ACCESS1-0 global climate model, that is intended for analysis of future changes in severe convective wind events and environments. For further information, the user can refer to the internal file metadata, as well as Brown et al. (2024). The files in this directory are as follows (where <experiment> is either hist for historical climate forcing (1985-2005) or rcp for RCP8.5 climate forcing (2039-2059)):





barpac_scws_<experiment>_monthly.ncMonthly counts of simulated severe convective wind events from BARPAC-M, for each type of environment (see cluster in Table 1).




barpar_<experiment>_monthly.ncMonthly counts of favouable severe convective wind environments from BARPA-R (using bdsd, see Table 1), for each type of environment (see cluster in Table 1).




barpac_scws_bdsd_<experiment>.ncMonthly counts of simulated severe convective wind events from BARPAC-M, that occur under favourable environmental conditions from BARPA-R. For each type of environment (see cluster in Table 1).




barpac_max_<experiment>_monthly.ncMonthly maximum simulated severe convective wind gust, from BARPAC-M, for each type of environment (see cluster in Table 1).



/daily_nc

This directory contains monthly netcdf files at 12 km horizontal grid spacing, with daily maximum wind gusts from BARPAC-M, as well as the wind gust ratio (see wgr_4 in Table 1) and the type of convective environment (from BARPA-R, see cluster in Table 1). This includes BARPA data that has been forced by ERA-Interim and by ACCESS1-0. For further information, the user can refer to the file metadata, as well as Brown et al. (2024). The files in this directory are as follows (where <experiment> is either historical for historical climate forcing or rcp85 for RCP8.5 climate forcing, <forcing_model> is either erai for ERA-Interim or ACCESS1-0, <date1> is the file start date and <date2> is the file end date):



barpa_scw_<forcing_model>_<experiment>_0_<date1>_<date2>.nc


/meta

Lists of AWS stations, for each administrative state, with a file containing column descriptions. Note that not all of the stations listed in these files are used for analysis. Fig1.jpeg is from Brown et al. (2024), showing the BARPAC-M domain (also defines the netcdf file spatial extents), and the location of AWS.

Table 1




Column
Name
Notes


stn_id
Automatic weather station (AWS) identifier
 


time
Wind gust time (UTC)
 


gust
Observed wind gust speed from AWS (m/s)
Observed wind gusts are measured at a height of 10 m, and represent a 3-second average. Data is provided as a one-minute maximum, and is resampled to a 10-minute maximum here for comparison with BARPA


wgr_4
Wind gust ratio
The observed wind gust ratio, defined as the ratio between gust, and the 4-hour mean from the 10-minute data here.


time_6hr
6-hourly time (UTC)
The most recent 6-hourly time step prior to time, associated with environmental diagnostics.


mu_cape
Most unstable convective available potential energy (J/kg)
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


s06
Bulk vertical wind shear from the surface to 6 km above ground level (m/s)
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


dcape
Downdraft convective available potential energy (J/kg)
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


bdsd
Brown and Dowdy (2021) Statistical Diagnostic (BDSD) for identifying favourable severe convective wind environments
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


qmean01
Mass-weighted mean mixing ratio from the surface to 1 km (g/kg)
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


Umean06
Mass-weighted mean wind speed from the surface to 6 km above ground level (m/s)
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


lr13
Temperature lapse rate from 1 km above ground level to 3 km above ground level (◦C/km)
Environmental diagnostic derived from BARPA-R. See Brown et al. (2024) for more information.


cluster
Environment type


Based on statistical clustering of severe convective wind environments by Brown et al. 20230: Strong background wind cluster1: Steep lapse rate cluster2: High moisture cluster

Derived from BARPA-R



s06_era5
See s06
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


qmean01_era5
See qmean01
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


Umean06_era5
See Umea06
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


lr13_era5
See lr13
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


bdsd_era5
See bdsd
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


dcape_era5
See dcape
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


mu_cape_era5
See mu_cape
Environmental diagnostic derived from ERA5. See Brown et al. (2024) for more information.


cluster_era5
See cluster


Based on statistical clustering of severe convective wind environments by Brown et al. 20230: Strong background wind cluster1: Steep lapse rate cluster2: High moisture cluster

Derived from ERA5



wg10_12km_point
Simulated wind gust from BARPA-R (m/s)
Intended to represent a 10 meter wind gust. See Ma et al. (2018) for gust parameterisation details.


wgr_12km_point
Wind gust ratio from BARPA-R 
See wgr_4


wg10_2p2km_point
Simulated wind gust from BARPC-M (m/s)
Intended to represent a 10 meter wind gust. See Ma et al. (2018) for gust parameterisation details.


wgr_2p2km_point
Wind gust ratio from BARPAC-M (see wgr_4)
See wgr_4


n_lightning_fl
Number of daily lightning flashes from BARPAC-M
See Brown et al. (2024) for more information.


erai_wg10
Simulated wind gust from ERA-Interim (m/s).
Intended to represent a 10 meter wind gust. Note that ERA-Interim is provided in 3-hourly intervals, rather than 10-minute intervals for BARPA.