Dynamical downscaling of climate changes with an eddy-resolving OGCM- What we learned from CSIRO Ocean Downscaling Strategic Project

Date & time

11am–12pm 19 April 2016

Location

Hales Room, Jaeger 7

Speakers

Dr Xuebin Zhang (CSIRO)

Contacts

 Kial Stewart

In this seminar presentation, CSIRO Ocean Downscaling Strategic Project, its design, progress and results are going to be discussed. The purpose of this strategic project is to provide high-resolution climate change and variability information in the global ocean over the past several decades and in the future, for better understanding, adaptation and mitigation purpose, because typical coarse-resolution climate models are only useful to provide some large-scale climate change information. To fulfil above purpose, we use dynamical downscaling by running an eddy-resolving (1/10 deg) near-global OGCM. Eddy-resolving global ocean models are highly desired for climate studies, but it is challenging because they require careful configuration and substantial computational resources. In the project, we have developed several strategies to run a near-global eddy-resolving OGCM (based on OFAM3) for climate studies. The model is spun up for 20 years, with repeating year 1979 forcing from JRA-55 reanalysis and adaptive relaxation (Newtonian nudging) of temperature and salinity in the deep ocean to an observation-based seasonal climatology. The model is then integrated over the historical period (1979-2014) driven by the JRA-55 reanalysis, with a repeating non-adaptive relaxation of temperature and salinity derived from the last five years of the spin-up experiment. The model is further integrated from current to 2100, driven by merged atmospheric forcings which include high-frequency component from current-day JRA-55 reanalysis and long-term climate change signals from the ensemble of 17 CMIP5 models under RCP8.5. The differences between future and historical experiments are regarded as the “downscaled” changes in the ocean. The consistently designed model runs (historical + future) from 1979 to 2100 provide a powerful dataset for many applications, including providing high-resolution climate change projections for all popular ocean state variables.

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