1 / 11

Overview of Multi Model Ensembles CTB SAB Report

This report provides an update on the evaluation of multi-model ensembles, including results from studies conducted by ECMWF, BMRC Australia, BCC Beijing, GFDL, NASA, and NCAR. The report examines the effectiveness of different models and the need for systematic error correction.

tempie
Download Presentation

Overview of Multi Model Ensembles CTB SAB Report

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. Overview of Multi Model EnsemblesCTB SAB Report Suranjana Saha NCEP/EMC August 2007

  2. EUROPEAN IMME • UPDATE • RESULTS OF OUR STUDIES WERE SENT TO THE ECMWF. • THE DIRECTOR, ECMWF SHOWED INTEREST, BUT WANTED HIS OWN SCIENTISTS TO CARRY OUT THE EVALUATION. • DR. DOBLAS-REYES (ECMWF) DOWNLOADED THE CFS RETROSPECTIVE DATA FROM THE CFS SERVER AND IS IN THE PROCESS OF EVALUATING THE IMME, BUT USING THEIR LATEST EUROSIP DATA (INSTEAD OF THE DEMETER DATA). • LATEST INFORMATION IS THAT THE EUROPEANS HAVE CONCLUDED THAT THE CFS IS IMPROVING THEIR MME FORECASTS BUT NEED MORE TIME FOR DECISION MAKING.

  3. EUROPEAN IMME • RISKS • THE EUROPEANS MAY WELL WANT TO KEEP THEIR MME EUROPEAN. • THEIR OPERATIONAL SEASONAL FORECAST PRODUCTS ARE NOT RELEASED IN REAL TIME (ONLY TO MEMBER STATES). • BILATERAL AGREEMENTS WILL HAVE TO BE MADE TO OBTAIN THESE IN REAL TIME FOR ANY OPERATIONAL USE IN AN IMME WITH THE CFS.

  4. OTHER COUNTRIES IN IMME • UPDATE • BMRC, AUSTRALIA • THE AUSTRALIANS ARE IN THE PROCESS OF COMPLETING THE RETROSPECTIVE FORECASTS WITH THEIR COUPLED MODEL. • WHEN THESE FORECASTS ARE COMPLETED, A SIMILAR STUDY WILL BE CONDUCTED TO EVALUATE WHETHER THE AUSTRALIAN MODEL FORECASTS WILL BRING ADDITIONAL SKILL TO THE CFS FORECASTS. • BCC, BEIJING, CHINA • A SIMILAR SITUATION PERTAINS TO THE CHINESE METEOROLOGICAL AGENCY. WHEN THEY HAVE COMPLETED THE RETROSPECTIVE FORECASTS WITH THEIR COUPLED MODEL, WE WILL EVALUATE WHETHER THE CHINESE MODEL FORECASTS WILL BRING ADDITIONAL SKILL TO THE CFS FORECASTS.

  5. NATIONAL MME • UPDATE • GFDL • HINDCAST DATA HAS BEEN OBTAINED FOR 4 INITIAL MONTHS (APR, MAY, OCT, NOV) FROM GFDL. RESULTS OF OUR STUDIES HAVE BEEN SENT TO GFDL. WE ARE AWAITING THEIR DECISION. • NASA • MICHELE REINEKER WILL ADDRESS THIS IN HER PRESENTATION • NCAR • NOT READY TO START THEIR HINDCASTS. • BEN KIRTMAN (COLA) HAS MADE SOME HINDCASTS WITH THE NCAR MODEL WHICH SHOW PROMISE. A FULL HINDCAST NEEDS TO BEDONE FOR EVALUATION IN A MME WITH THE CFS.

  6. How extensive (long) should hindcasts be? Huug van den Dool Climate Prediction Center, NCEP/NWS/NOAA Suranjana Saha Environmental Modeling Center, NCEP/NWS/NOAA

  7. Explained Variance (%) Feb 1981-2001; lead 3 (Nov starts); monthly T2m (US, CD data) Explained Variance=Square of Anom Correlation SEC : Systematic Error Correction; EW: Equal Weights CFS=CFS, USA; EC=ECMWF; PLA=Max Planck Inst, Germany; METF=MeteoFrance, France; UKM=UKMetOffice; INGV=INGV, Italy, LOD=LODYC, France; CERF=CERFACS, France

  8. Anomaly Correlation (%) Feb 1981-2001; lead 3 (Nov starts); monthly T2m (US, CD data) WITH SEC21 WITH SEC8 SEC8-SEC21 Need more years to determine the SEC where/when the inter annual standard deviation is large SEC : Systematic Error Correction

  9. CONCLUSIONS • Without SEC (systematic error correction) there is no skill by any method (for presumably the best month: Feb) • With SEC (1st moment only), there is skill by only a few models (5 out of 8 are still useless) • MME not good when quality of models varies too much • MME3 works well, when using just three good models

  10. CONCLUSIONS (contd) • CFS improves the most from extensive hindcasts (21 years noticeably better than 8) and has the most skill. Other models have far less skill with all years included. • Cross validation (CV) is problematic (leave 3 years out when doing 8 year based SEC?) • Need more years to determine the SEC where/when the inter annual standard deviation is large

  11. 15-member CFS reforecasts 15-member CFS reforecasts

More Related