1 / 18

PEODAS - Enhancing Forecast Accuracy: A Comparative Analysis

Explore the impact of PEODAS assimilation on forecast skill versus the old system, with comparisons to other centers and models. The PEODAS system, developed by CSIRO and the Bureau of Meteorology, leverages a pseudo ensemble Kalman filter for improved accuracy in weather and climate prediction, incorporating optimum interpolation, covariances, and observations. Discover its correlation with re-analyses and observational datasets, highlighting advancements in heat and salt content predictions. Evaluate the system's impact on forecasts, particularly in NINO3 and IOD regions, and analyze the skill improvement in sub-surface variables like salinity. The in-depth analysis showcases the competitive performance of PEODAS in enhancing forecast accuracy and agreement with observational data, presenting a comprehensive overview of its capabilities and limitations.

bquach
Download Presentation

PEODAS - Enhancing Forecast Accuracy: A Comparative Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PEODAS Oscar Alves, Yonghong Yin, Robin Wedd, Maggie Zhao and Harry Hendon CAWCR The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  2. Plan Introduction to PEODAS Impact on Forecast Skill (vs Old System) Comparison with other Centres The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  3. PEODAS (Yin et al 2010) Pseudo Ensemble Kalman Filter – (Based on extension of BLUElink system; Oke et al) 11 member ensemble but used lagged set for covariances (100 member) Compression to central rather than assimilation into each Constant background/obs error ratio (not using ensemble) Background covariance only used from ensemble The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  4. Comparison with POAMA-1 POAMA-1 PEODAS System Optimum Interpolation Pseudo EnKF Covariances 2D Univariate Static 3D Multi-variate Time-evolving Observations Temperature profiles from BoM Temperature and salinity profiles from EU ENACT Forcing NCEP Re-analysis ERA-40 Re-analysis Bias Correction 3D relaxation to Levitus None Re-analysis 1960-present 1980-present The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  5. Example of Ensemble Spread (Estimate of analysis error) Temperature Salinity From Yin et al 2010 The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  6. Correlation between re-analysis and UKMO EN3 dataset Heat Content Salt Content Produced by Maggie Zhao The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  7. Impact on Forecasts (& Comparison with other models) Mostly Based on hind-casts from ~1982-2006 The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  8. NINO 3 and IOD Skill POAMA-2 Produced by Li Shi The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  9. Impact of Assimilation on Heat Content Skill Correlation in Tropics POAMA-2 (3 models) No Assim POAMA-1.5 Produced by Maggie Zhao The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  10. Impact of Assimilation on Salt Content Skill Correlation in Tropics No Assim POAMA-2 (3 models) POAMA-1.5 Produced by Maggie Zhao The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  11. Salinity Correlation Old Forecasts PEODAS Forecasts PEODAS OBS OLD OI OBS EN3 OBS The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  12. Temperature Correlation Old Forecasts PEODAS Forecasts PEODAS OBS OLD OI OBS EN3 OBS The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

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

  14. Comparison with Other Centres Correlation with “Observations” Heat Content Surface Current PEODAS ECMWF Produced by Maggie Zhao The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  15. ENSO Composite Heat Content Produced by Li Shi The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  16. ENSO Composite Heat Content Surface Salinity PEODAS ECMWF NCEP Produced by Li Shi The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  17. IOD Composite Heat Content Surface Salinity PEODAS ECMWF GODAS (NCEP) EN3 Produced by Li Shi The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

  18. Summary • PEODAS assimilation shows good agreement with obs and competitive with other systems • Skill improvement for NINO3 (IOD ?) • Sub-surface skill better compared to NINO3 • But sub-surface skill, especially salinity, depends on observed dataset • (Similar problem looking Great Barrier Reef SST Skill) • What is reality? The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

More Related