%0 Online Multimedia %A Mackie, Shona %A Seppala, Annika %A Smith, Inga %D 2020 %T Climate Data and Computing are Hotting Up! %U https://eresearchnz.figshare.com/articles/presentation/Climate_Data_and_Computing_are_Hotting_Up_/11929563 %R 10.6084/m9.figshare.11929563.v1 %2 https://eresearchnz.figshare.com/ndownloader/files/21897837 %K NeSI %K eResearch %K eResearch NZ 2020 %X Understanding our climate and how it changes in future is a topic of increasingly urgent research, with heightened levels of public and political support worldwide. Climate models, however, are necessarily big. In theory, they represent all physical processes from the top of the atmosphere to the bottom of the ocean, over land, water and sea ice, in 3-dimensional grid cells with a resolution of 1 degree or finer. The interaction and evolution of these processes is modelled with a temporal resolution of more than a single timestep per hour, and typically we need to run for at least 100 years. Furthermore, uncertainties and internal variability in the climate system mean that we run an ensemble rather than a single model run. The structure of climate models means they can usually be parallelized to a point, but they are not generally suitable for the distributed computing solutions that can be implemented in other fields. As well as being expensive to run, climate models produce a lot of data (PB scale). The idea is to capture the state of the whole world in a 3-dimensional mesh with a temporal resolution fine enough to see how it changes, and a spatial resolution fine enough to examine any physical process anywhere on Earth that might impact on climate. For example, one model component (atmosphere, ocean etc) can be made of 1.2 million grid points. Saving just one parameter daily for 100 years = 44 billion data points. 30 parameters from 6 ensemble simulations amounts to 8 trillion data points, just from one model component. These data have to be accessible so that we can do processing and monitoring of climate model runs while they are underway, and need to be securely archived in a way that makes them accessible for long term use, and shareable with collaborators both present and future, here in Aotearoa and abroad. Running a climate model is just the beginning of climate research, analysis of the data requires tools capable of accessing and handling large data volumes that are generally stored on remote servers, sometimes overseas, at a speed that makes interrogation and analysis practical.

Climate modelling is one of the most computationally hungry fields of research and New Zealand has recently joined the list of the relatively few countries with the resources and infrastructure to do it. Growing this field of research in New Zealand will need development of resources and expertise to manage those resources. Events like eResearch 2020 are an important way for information to be shared with network architects and data managers to ensure that the systems and infrastructure are in place to support the next generation of climate researchers.

ABOUT THE AUTHOR(S)
Shona Mackie is a climate modeller at University of Otago, developing the New Zealand Earth System Model to include new physics processes, and carrying out senstivity studies using the current version of the model to better understand uncertainties inherent in our climate projections.

Annika Seppälä is a senior lecturer at Otago University Physics department. Her research uses computational simulations together with large space based Earth observation datasets to investigate solar influence on the atmosphere and climate from global to regional scales.

Inga Smith is a senior lecturer in the Department of Physics, University of Otago. Her research interests are in sea ice physics and climate change, particularly the influence of fresh water on sea ice formation.
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