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A Note on Some Methods Suitable for Verifying and Correcting the Prediction of Climatic Anomaly


doi: 10.1007/BF02666540

  • The weighted correlation coefficient of the predicted and observed anomalies and the ratio of the weighted norm of predicted anomaly to the observed one, both together, are suggested to be suitable for the estimating of the correctness of climate prediction. The former shows the similarity of the two patterns, and the later indicates the correctness of the predicted intensity of the anomaly. The weighting function can be different for different emphasis, for example, a constant weight means that the correlation coefficient is the conventional one, but same non-uniform weight leads to the ratio of correct sign of the anomaly, the stepwise weight leads lo the formulation of correctness of prediction represented by grades of the anomaly, and so on.Three methods for making correction to the prediction are given in this paper. After subtracting lie mean error of the prediction, one method is developed for maximizing the similarity between the predicted and observed patterns, based on the transformation of the spatial coordinates. Another method is to minimize the mean difference between the two fields. This method can also be simplified as similar to the “optimum interpolation” in the objective analysis of weather chart. The third method is based on the expansion of the anomaly into series or EOF, where the coefficients are the predicted but the EOFs are taken as the “observed” calculated from historical samples.
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    [2] LI Xiaofan, SHEN Xinyong, LIU Jia, 2014: Effects of Doubled Carbon Dioxide on Rainfall Responses to Large-Scale Forcing: A Two-Dimensional Cloud-Resolving Modeling Study, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 525-531.  doi: 10.1007/s00376-013-3030-2
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    [4] Lingyun LOUSchool, of Earth, Zhejiang University, Xiaofan LISchool, 2016: Radiative Effects on Torrential Rainfall during the Landfall of Typhoon Fitow (2013), ADVANCES IN ATMOSPHERIC SCIENCES, 33, 101-109.  doi: 10.1007/s00376-015-5139-y
    [5] YUE Caijun, GAO Shouting, LIU Lu, LI Xiaofan, 2015: A Diagnostic Study of the Asymmetric Distribution of Rainfall during the Landfall of Typhoon Haitang (2005), ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1419-1430.  doi: 10.1007/s00376-015-4246-0
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    [7] ZHAI Guoqing, LI Xiaofan, ZHU Peijun, SHEN Hangfeng, ZHANG Yuanzhi, 2014: Surface Rainfall and Cloud Budgets Associated with Mei-yu Torrential Rainfall over Eastern China during June 2011, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1435-1444.  doi: 10.1007/s00376-014-3256-7
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    [13] Dapeng ZHANG, Yanyan HUANG, Bo SUN, Fei LI, Huijun WANG, 2019: Verification and Improvement of the Ability of CFSv2 to Predict the Antarctic Oscillation in Boreal Spring, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 292-302.  doi: 10.1007/s00376-018-8106-6
    [14] Xiaying ZHU, Mingzhu YANG, Ge LIU, Yanju LIU, Weijing LI, Sulan NAN, Linhai SUN, 2022: A Precursory Signal of June–July Precipitation over the Yangtze River Basin: December–January Tropospheric Temperature over the Tibetan Plateau, ADVANCES IN ATMOSPHERIC SCIENCES.  doi: 10.1007/s00376-022-2079-1
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Manuscript History

Manuscript received: 10 April 1994
Manuscript revised: 10 April 1994
通讯作者: 陈斌, bchen63@163.com
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A Note on Some Methods Suitable for Verifying and Correcting the Prediction of Climatic Anomaly

  • 1. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080

Abstract: The weighted correlation coefficient of the predicted and observed anomalies and the ratio of the weighted norm of predicted anomaly to the observed one, both together, are suggested to be suitable for the estimating of the correctness of climate prediction. The former shows the similarity of the two patterns, and the later indicates the correctness of the predicted intensity of the anomaly. The weighting function can be different for different emphasis, for example, a constant weight means that the correlation coefficient is the conventional one, but same non-uniform weight leads to the ratio of correct sign of the anomaly, the stepwise weight leads lo the formulation of correctness of prediction represented by grades of the anomaly, and so on.Three methods for making correction to the prediction are given in this paper. After subtracting lie mean error of the prediction, one method is developed for maximizing the similarity between the predicted and observed patterns, based on the transformation of the spatial coordinates. Another method is to minimize the mean difference between the two fields. This method can also be simplified as similar to the “optimum interpolation” in the objective analysis of weather chart. The third method is based on the expansion of the anomaly into series or EOF, where the coefficients are the predicted but the EOFs are taken as the “observed” calculated from historical samples.

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