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REN Hongli , LIU Ying, ZHENG Zhihai BCC/CMA, Beijing, China 10081

April 8-10, 2013 Beijing. A method of analogue-based correction of errors in model prediction and its application to 2013 summer climate prediction. REN Hongli , LIU Ying, ZHENG Zhihai BCC/CMA, Beijing, China 10081. Statistical correction of model prediction errors.

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REN Hongli , LIU Ying, ZHENG Zhihai BCC/CMA, Beijing, China 10081

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  1. April 8-10, 2013 Beijing A method of analogue-based correction of errors in model prediction and its application to 2013 summer climate prediction REN Hongli, LIU Ying, ZHENG Zhihai BCC/CMA, Beijing, China 10081

  2. Statistical correction of model prediction errors Developing statistical methods to utilize historical data information in predictions of climate model . • Systematic Error Correction Constant systematic errors • Analogue-based Correction of Errors (ACE) Flow-dependent errors

  3. Analogue-based Correction of model prediction Errors (ACE) Strategy: Improve model prediction through using abundant historical analogue information. (Ren and Chou, 2005, 2007) Numerical model Hypothesis Real model of atmosphere Model satisfied by analogue If is bounded and is small enough, then Basic equation for ACE :

  4. Application of the ACE in seasonal prediction Seasonal mean of the Eq. Using multi-analogues To estimate prediction errors of the current seasonal-mean predictionand realize the error correction. (Renet al,2006, 2007, 2009; Zheng et al, 2009) Based on the ACE method, the Analogue-Dynamical SeasonalPrediction System (ADSPS) has been developed.

  5. Analogue-Dynamical SeasonalPrediction System(ADSPS) Basic structure of the ADSPS Historical analogues Initial conditions Model prediction Model hindcasts Corrected prediction Error characteristics The schemes for the actual application are developed from this basic structure of the ADSPS.

  6. Applications to spring-summer ENSO prediction • DATA and model • OBS: monthly HadISSTduring 1983-2012 • Interpolated into the resolution of BCC model • Model: BCC Coupled GCM 1.0 (BCC_CGCM1) • Hindcasts: monthly SST during 1983-2012 • Initiate month: Feb. • Predict from Mar. to Aug., every year • Method • – BCC model prediction removing the systematic errors • – Corrected prediction with the ACE

  7. Independent validation • Correction of SSTAs in Mar.―Aug. during 1993-2012 ………… 1994 1993 2012 1983―1992 1983―1993 1983―2011 Illustrations of the designed scheme

  8. Time series of Nino 3.4 Index

  9. TCC Temporal correlation coefficients of Nino 3.4 indices between OBS and BCC or Correction of BCC during 1993-2012 RMSE (℃) of Nino 3.4 indices (≥ 0.5 ℃) during 1993-2012

  10. Predictions of Niño3.4 index and SSTA in 2013 A new Warm-Pool El Niño event may be emerging.

  11. Applications to China summer PRCP prediction in recent 4 years 2009 2010 2011 2012 The same level of skill with BCC operation PSscores

  12. 2013 China summer PRCP prediction • Positive PRCP anomalies are located over North China, Northeast China and South China. • Negative PRCP anomalies are located over Northwest China and the Yangtze River basin.

  13. Summary • The method of analogue-based correction of errors (ACE) has been introduced to improve seasonal-mean predictions produced by climate model; • This ACE method can reduce the flow-dependent prediction errors besides the constant systematic errors; • Applications of the method in correcting the predictions of ENSO and China precipitation anomalies this summer show encouraging performance; • The predictions for this summer are worthy of expecting.

  14. Thank you!

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