ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Archive > Volume 43 Issue 3 > 2017,43(3):294-304. DOI:10.7519/j.issn.1000-0526.2017.03.005 Prev Next
Statistical Correction of ENSO Prediction in BCC_CSM1.1m Based on Stepwise Pattern Projection Method
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Abstract:
Using the sea surface temperature (SST) hindcast datasets produced by the climate system model of Beijing Climate Center (BCC_CSM1.1m) from 1991 to 2014, the Stepwise Pattern Projection Method (SPPM) is employed to statistically correct El Ni〖AKn~D〗oSouth Oscillation (ENSO) prediction. The main idea of the SPPM is to produce a prediction at the predictand grid by projecting the predictor field onto its covariance pattern with the onepoint predictand after selecting the predictor domain. The SPPM significantly improves the performance of the prediction over the equatorial Pacific and Indian Ocean. The temporal correlation score has increased 8%-10% in terms of Ni〖AKn~D〗o3.4 SST anomaly index with a 6month lead in the cross validation. The spatial anomaly correlation coefficients for El Ni〖AKn~D〗o event predictions also increase obviously by the SPPM at most lead months, particularly in autumn. Besides, the prediction for the location of warming center also can be improved, compared with that of the original BCC_CSM1.1m.
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