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An Analysis of the Difference between the Multiple Linear Regression Approach and the Multimodel Ensemble Mean


doi: 10.1007/s00376-009-8024-8

  • An investigation of the difference in seasonal precipitation forecast skills between the multiple linear regression (MLR) ensemble and the simple multimodel ensemble mean (EM) was based on the forecast quality of individual models. The possible causes of difference in previous studies were analyzed. In order to make the simulation capability of studied regions relatively uniform, three regions with different temporal correlation coefficients were chosen for this study. Results show the causes resulting in the incapability of the MLR approach vary among different regions. In the Nino3.4 region, strong co-linearity within individual models is generally the main reason. However, in the high latitude region, no significant co-linearity can be found in individual models, but the abilities of single models are so poor that it makes the MLR approach inappropriate for superensemble forecasts in this region. In addition, it is important to note that the use of various score measurements could result in some discrepancies when we compare the results derived from different multimodel ensemble approaches.
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Manuscript History

Manuscript received: 10 November 2009
Manuscript revised: 10 November 2009
通讯作者: 陈斌, bchen63@163.com
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An Analysis of the Difference between the Multiple Linear Regression Approach and the Multimodel Ensemble Mean

  • 1. National Climate Center, China Meteorological Administration, Beijing 100081, Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875,National Climate Center, China Meteorological Administration, Beijing 100081,National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081,Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

Abstract: An investigation of the difference in seasonal precipitation forecast skills between the multiple linear regression (MLR) ensemble and the simple multimodel ensemble mean (EM) was based on the forecast quality of individual models. The possible causes of difference in previous studies were analyzed. In order to make the simulation capability of studied regions relatively uniform, three regions with different temporal correlation coefficients were chosen for this study. Results show the causes resulting in the incapability of the MLR approach vary among different regions. In the Nino3.4 region, strong co-linearity within individual models is generally the main reason. However, in the high latitude region, no significant co-linearity can be found in individual models, but the abilities of single models are so poor that it makes the MLR approach inappropriate for superensemble forecasts in this region. In addition, it is important to note that the use of various score measurements could result in some discrepancies when we compare the results derived from different multimodel ensemble approaches.

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