The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Oscar Alves, Li Shi, Yonghong Yin, Robin.

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The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Oscar Alves, Li Shi, Yonghong Yin, Robin Wedd and Harry Hendon CAWCR (Centre for Australian Weather and Climate Research) Australian Bureau of Meteorology Salinity Initialisation and Seasonal Prediction Acknowledgement

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology 1.Salinity re-analysis intercomparison 2.Salinity and seasonal forecast 3.Mechanism for long-term impact 4.Conclusion Outline

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Inter-comparison Salinity from Operational Re-analyses

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Mean State S300 – EN3

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Mean State S300 – EN3 X X X

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Comparison of PEODAS with other re-analyses

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Mean State S300 – EN3

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Comparison of PEODAS with other re-analyses

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Correlation S300 Anomalies with ENACT

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Comparison of PEODAS with other re-analyses

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Comparison of PEODAS with other re-analyses

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology GODAE-OceanView/GSOP Salinity Comparison Intercomparison

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology 100m Salinity compared to ensemble mean

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology 100m Salinity Along the equator

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology S300 along the equator

Does Salinity IC Matter for SP? Equation of state depends on salinity also (0.5ppt ~ 1 C) Does not directly couple to the atmosphere like temperature ? Is it just passive tracer on inter-annual timescales Does it matter if we properly initialise salinity?

POAMA-2 vs POAMA-1.5 New PEODAS ocean assimilation does a good job of salinity (uses Argo data and pre-argo system is multi-variate ie changes salinity based on temperature) Old system does not assimilate salinity and is univariate Does it matter ?

Impact of POAMA-2 assimilation in Pacific ? POAMA-2 Skill in Pacific (spatial ACC) Salt Content POAMA-2-POAMA1.5 Skill SST POAMA-2-POAMA1.5 Skill Heat Content POAMA-2-POAMA1.5 Skill

PEODAS is the POAMA-2 system POAMA-OI is the old POAMA-1.5 system Mean initial state difference ( )

Mean forecast evolution (POAMA-2 – POAMA1.5: same model, different initial conditions)

Add just the T and S perturbations to a single forecasts Idealised experiments

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Summary Real-time monitoring NCEP doing it for Temperature BoM will do it for Salinity This year would be an interesting case as very large spread in forecasts

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Summary/Conclusions Significant spread in salinity analyses for operational forecasting Salinity errors dominate temperature errors in many areas (~50%) Forecasts are sensitive to salinity errors (through adjustment of T) Errors impact mean state (long lasting) SMOS/Aquarius need start using for evaluation, particularly recent cases (e.g. this year was interesting) Independent dataset to evaluate analyses Introduce into the assimilation (but only short record ?)

Last meeting during 2 nd SMOS Science Conference (May 2015) SMOS-Mission Oceanographic Data Exploitation SMOS-MODE SMOS-MODE supports the network of SMOS ocean-related R&D