Community Talks 1: Chris Chambers (The University of Melbourne) The role of sea-surface temperatures in a June 2016 east coast heavy rain event: insights from AUS2200 simulations

Community Talk: Chris Chambers (The University of Melbourne)

The role of sea-surface temperatures in a June 2016 east coast heavy rain event: insights from AUS2200 simulations.

Abstract

In early June 2016 an east coast low complex brought extensive heavy rainfall that produced flooding in areas of Queensland, New South Wales, Victoria, and Tasmania. In the lead-up to this event, sea-surface temperatures (SSTs) in the Coral and Tasman Seas were the warmest on record. Our aim is to determine how the high SSTs, and their distribution, influenced the rainfall and the storm-system’s evolution. To do this, three AUS2200 sensitivity to SST simulations, for the period 0000 UTC 3 June to 0000 UTC, 8 June 2016, have been run using ERA5 skin-temperature data over water. The three simulations are run with 1)1980-2019, 3 June average ERA5 skin temperature (Climatology), 2) constant 3 June 2016 ERA5 skin temperature (Fixed), and 3) daily evolving ERA5 skin temperature (Evolving). The Fixed and Evolving simulations, that include the observed warmer SSTs, produce greater rainfall than the Climatology simulation over much of the ocean area and most of the east-coastal mountains. The Fixed and Evolving simulations also produce a deeper east coast cyclone that intensifies over a prominent warm eddy. These cases also keep the low pressure further to the north, off the New South Wales coast, for longer than the Climatology run. Towards the latter stage of the simulation period, a complicated multi-centred low-pressure system around Tasmania, seen in observations, correlates better with the Fixed and Evolving simulations than the Climatology simulation. The potential mechanisms responsible for these differences will be discussed. Additional simulation results will be presented to investigate the relative roles of the warm eddy and the broad-scale warmer SST.

Please use this thread for further discussion on this talk.

Just an observation on what your result might mean for ocean-atmosphere coupling at high resolution. It seems to me that the large scale pattern of SST anomaly is more important than SST gradients for the impact you are seeing … perhaps the atmosphere just can’t “see” those small-scale ocean gradients?

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what is the resolution of the ERA5 skin temperature? or maybe from which product is it sourced from? It seems to me that the details in the SST field were more high resolution than 31km.

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the atmosphere seems to be influenced by large scale ocean temperature patterns, but the dynamics that produce these pattens are quite high resolution : we need a realistic western boundary current, a good shelf-break current interaction and southward propagation along the east coast of Australia and down to Tasmania…etc…

So here is a controversial question: does it mean that we are better off with a HR atmospheric model driven by a skin SST sourced from a high res realistic SST product rather than a coupled ocean-atmosphere (for which we need to compromise resolution )?

In this case the anomalous intensification of the subtropical storm seems to have been driven by the large-scale SST distribution with the smoothing of the ocean eddy having no clear impact. However there are still local scale impacts within the storm on low level temperature and moisture, and an increase in rainfall on the downwind side of the eddy. In particular the rainfall impact does suggest the gradients are important, particularly for coast flooding impacts even in this large rainband system. Previous simulations show the impact of warm eddies and associated gradients on things like convective available potential energy and once you get eddy-triggered thunderstorms the potential for deep tropospheric impacts become greatly amplified.

It does use ERA5 skin temperatures but they are run through a program era5grib to put them in a grib dataset for AUS2200 to use. This process may introduce some smoothing of the ERA5 more blocky data but I haven’t looked at it in detail.