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The Madden-Julian Oscillation and the Maritime Continent

There is a steady beat to the wet season in Bali, as many visitors discover on their afternoon beachside walks. Every day, heat and humidity build up in tall clouds sitting over the mountains, and every evening, all of that stored moisture comes pouring down as the clouds move offshore, over the beaches and out to sea. This weather pattern happens day-in and day-out, a defining feature of the wet season along the coast.

This weather pattern takes place all over the Indonesian archipelago, the group of islands making up a big part of the region known as the Maritime Continent. Every few weeks however, atmospheric changes sweep in from the Indian Ocean, disrupting the regular pattern. One of these changes, called the Madden-Julian Oscillation (MJO), arrives from the Indian Ocean every 30 to 90 days and tracks slowly eastwards, bringing major impacts to the daily weather on the islands.

The MJO brings a large area of storminess and clouds with it, which interacts with the air rising over the steep mountains and suppresses daily variations in surface heating. With a slower pattern of heating and cooling, there is less rainfall over the land and more cloudiness over a wide region. For several days, an unpredictable flurry of rain and storms disrupts the daily rainfall.

 

Researcher Dr Claire Vincent from the University of Melbourne and the Australian Research Council Centre of Excellence in Climate System Science says, “Understanding the interactions between local weather and larger scale variability is critical for learning about the climate of the Maritime Continent. It also has big implications for rainfall and climate in other parts of the world.”

Dr Vincent runs her model on the NCI supercomputer to produce the data she needs. Rainfall and wind observations from gauges on land are helpful, but don’t produce the level of resolution and coverage that is required. Instead, the model – which combines ocean, atmosphere and land components – reproduces the local weather and provides a wealth of information about rainfall, wind and cloudiness to analyse.

She says, “Understanding the details of these phenomena lets us investigate the way they might respond in a warmer world. Developing this deep level of understanding helps many facets of our weather prediction, climate modelling and environmental monitoring activities.”

Further to this, a collaborative effort between Dr Vincent and NCI’s visualisation team takes that data and produces rich, scientifically accurate video examples of the modelling outputs. The video format makes it easy to highlight certain elements of the modelling and show an audience exactly what is happening during the MJO cycle. Whether for use in scientific conferences or online, videos like this showcase the beauty, rigor and detail of atmospheric modelling.

The MJO has been a subject of research for a long time, but it’s only recently that high-resolution modelling has made it possible to see weather patterns in this way. As the wet season rolls on and the rains keep coming every afternoon, we now know a little bit more about what is driving all those patterns.

 

ABOUT THE VIDEO The graphics in this video are based on simulations run with the Weather Research and Forecasting (WRF) model with inputs from the ERA-Interim Reanalysis and the Real-time Global Sea Surface Temperature analysis for the period December 2008 – February 2009. These models and datasources are widely used for weather and climate studies. For more information on the methods used, this journal article provides the details: http://journals.ametsoc.org/doi/full/10.1175/JCLI-D-16-0688.1.

ABOUT THE SCIENTISTS This video was produced by the NCI VizLab, in association with Dr Claire Vincent and A/Prof Todd Lane from the University of Melbourne and the ARC Centre of Excellence for Climate System Science. Compute resources on the NCI supercomputer were used to run the models. The raw data used in the video is available from https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f5210_8718_6512_7201.

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