Bias correction of an ocean-atmosphere coupled model

Publication Type  Journal Article
Year of Publication  2000
Authors  Chen, D.; Cane, C. M.; Zebiak, S. E.; Canizares, R.; Kaplan, A.
Journal Title  Geophysical Research Letters
Volume  27
Issue  16
Pages  2585-2588
Journal Date  Aug 15
ISBN Number  0094-8276
Accession Number  ISI:000088771500059
Key Words  sea-surface temperature; el-nino; data assimilation; predictability; prediction; impact; level

A serious problem in the initialization of a climate forecast model is the model-data incompatibility caused by systematic model biases. Here we use the Lament model to demonstrate that these biases can be effectively reduced with a simple statistical correction, and the bias-corrected model can have a more realistic internal variability as well as an improved forecast performance. The results reported here should be of practical use to other ocean-atmosphere coupled models for climate prediction.


344QZTimes Cited:23Cited References Count:9

URL  <Go to ISI>://000088771500059