The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Improvements in POAMA2 for the prediction of major climate drivers and south eastern Australian rainfall

CSIRO and the Bureau of Meteorology advise that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO and the Bureau of Meteorology (including each of its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it. Fig. 1 (a)-(c) Regression patterns (right) of observed SST onto the observed times series of the NINO3, EMI and DMI indices (left) for the period of 1980-2010. (d) Regression pattern of observed MSLP (right) onto the observed SAM index (left) Fig. 2 Climate drivers with highest correlation with rainfall at each grid point (left) and correlation of NINO3 (green), EMI (blue), DMI (red), and SAM index (yellow) with SEA area-averaged rainfall (right) over the period of 1980-2010. Fig. 3 Forecast skill of key climate drivers Nino3, EMI, IOD, and the SAM. Coloured lines are the forecast skill over 1980-2006, and black lines are the forecast skill over 1960-2010. Forecast skill is assessed by correlation between forecasts and Fig. 4 Forecast skill (correlation between forecasts and observation) difference between POAMA1.5 and POAMA2 (POAMA2 minus POAMA1.5) as a function of forecast start time and lead time. Pink (blue) colour shading indicates POAMA2 skill to be higher (lower) than that of POAMA1. Fig. 5 (a) POAMA2 and (b) persistence forecast skill (as measured by correlation) of SAM as a function of forecast start time and lead time. (c) Observed correlation between monthly SAM and NINO3 in 1980-2010. Fig. 6 Forecast skill (as measured by correlation) for major climate drivers at lead time zero month (upper panel) and three months (lower panel). The verification season (3 month mean) is along the x-axis. Fig. 7 SST mean state bias at 0 and 6 month lead times in POAMA1.5, each version of POAMA2 and the finally configured POAMA2 consisting of the three versions of POAMA2. Blue colour indicates predicted climatological SST to be colder than the observed over …