Community Talk: Emma Howard (Bureau of Meteorology)
BARPA-C - Convective-Scale Regional Climate Modelling in Australia
Abstract
Natural hazards are changing across Australia and globally in response to anthropogenic climate change. Accurate projections of Australian climate hazards, such as intense rainfall, extreme winds, bushfires, and cyclones, depend to varying degrees on the representation of atmospheric convection in climate models and its upscale effects on synoptic weather systems. Furthermore, the locations of exposed populations such as urban centres and coastlines are often poorly resolved in low resolution climate models. The Bureau of Meteorology is developing a suite of modelling systems, BARPA, based on the Met Office Unified Model (MetUM) coupled to the JULES land surface model, for generating an ensemble of projections for Australian Climate Service (ACS).
As a convection-permitting regional climate model, BARPA-C uses the latest regional atmosphere and land- configuration of the models RAL3.2. BARPA-C builds on BARPA-R, the Bureau’s core set of downscaled 17-km projections, which relies on parametrisation to provide atmospheric convection. Following regional climate modelling protocols, BARPA-C has been evaluated by downscaling reanalysis data and comparing modelled to observed climatologies. 10 years of ERA5 have been downscaled to 4-km grid-spacing using BARPA-C, from 2013 to 2022, via the regional-scale BARPA-R nest. The application of spectral nudging techniques to improve the representation of large-scale climate features has been investigated. This presentation will evaluate BARPA-C against high-resolution observational datasets, including radar data, Himawari8 and BARRA-C2. This assessment will also evaluate the ability of BARPA-C to improve the representation of climate hazards, such as intense rainfall and extreme winds, compared to BARPA-R and global driving models.
Please use this thread for further discussion on this talk.
Emma, I have a question about the resolution across the different component of the climate system, in particular the ocean.
- What is the resolution of the ocean in the parent model (sorry I missed the version of ACCESS-ESM you were using)?
- Are you using the SST from the parent model for BARPA-R and BARPA-C ? do you think this could have an impact?
thanks, Clothilde
Hi Clothilde,
Thanks for your question! Our models are atmosphere only with prescribed updating sst. This is true for both resolutions. The results I showed were from ERA5, so we use the same SST as ERA5, bilinearly interpolated from 0.25 degrees and updating daily. For our period, this is essentially coarsened Ostia I think.
We could have substituted in higher resolution Ostia sst if we wanted, however we don’t have a fine resolution equivalent for the GCM experiments, which are our ultimate target.
Our GCM runs will also bilinearly interpolate from the host cmip6 models - EC-Earth3 and ACCESS ESM 1.5 at their native resolution. (80km and about 15km)
there are certainly monsoon processes that we’re not capturing due to not having a coupled ocean.
Emma
Thanks Emma, I had completely missed the fact that you presented a 2013-2022 comparison using ERA5 and ERA5 skin SST . For some reason I thought you were already presenting ACCESS-ESM1.5 downscaling result. Sorry about that…
So now, another question: what are the main differences between BARRA-C2 and BARPA-C?
cheers
Clothilde
Sorry I should have been more clear!
BARPA-R
large Australasia domain (90E-160W)
17km grid spacing
model config paramerises atmosphere convection and is generally similar to the UMs global configuration, similar to access-cm2 (with differences) - called GA7
BARPA-C
Australia only with some coastal buffer (106E - 160E)
4 km grid spacing
model config does not include a parametrisation for convection, so vertical motion develops naturally. similar configuration as used in the bureaus high resolution 1.5 day city scale forecasts (access-c) and identical to the new 1.5 day all-of-australia forecasts under development (ACCESS-A)
hope that helps!
Emma