Estimation of the Monthly Precipitation Predictability Limit in China Using the Nonlinear Local Lyapunov Exponent
By using the nonlinear local Lyapunov exponent and nonlinear error growth dynamics, the predictability limit of monthly precipitation is quantitatively estimated based on daily observations collected from approx- imately 500 stations in China for the period 1960-2012. As daily precipitation data are...
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| Summary: | By using the nonlinear local Lyapunov exponent and nonlinear error growth dynamics, the predictability limit of monthly precipitation is quantitatively estimated based on daily observations collected from approx- imately 500 stations in China for the period 1960-2012. As daily precipitation data are not continuous in space and time, a transformation is first applied and a monthly standardized precipitation index （SPI） with Gaussian distribution is constructed. The monthly SPI predictability limit （MSPL） is quantitatively calcu- lated for SPI dry, wet, and neutral phases. The results show that the annual mean MSPL varies regionally for both wet and dry phases： the MSPL in the wet （dry） phase is relatively higher （lower） in southern China than in other regions. Further, the pattern of the MSPL for the wet phase is almost opposite to that for the dry phase in both autumn and winter. The MSPL in the dry phase is higher in winter and lower in spring and autumn in southern China, while the MSPL values in the wet phase are higher in summer and winter than those in spring and autumn in southern China. The spatial distribution of the MSPL resembles that of the prediction skill of monthly precipitation from a dynamic extended-range forecast system. |
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| Bibliography: | 11-2277/P monthly precipitation, nonlinear local Lyapunov exponent （NLLE）, predictability, spatial distribution LIU Jingpeng, LI Weijing, CHEN Lijuan, ZUO Jinqing, ZHANG Peiquna （ 1 Chinese Academy of Meteorological Sciences, Beijing 100081 2 University of Chinese Academy of Sciences, Beijing 100049 3 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science ＆ Technology, Nanjing 210044 4 Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081） By using the nonlinear local Lyapunov exponent and nonlinear error growth dynamics, the predictability limit of monthly precipitation is quantitatively estimated based on daily observations collected from approx- imately 500 stations in China for the period 1960-2012. As daily precipitation data are not continuous in space and time, a transformation is first applied and a monthly standardized precipitation index （SPI） with Gaussian distribution is constructed. The monthly SPI predictability limit （MSPL） is quantitatively calcu- lated for SPI dry, wet, and neutral phases. The results show that the annual mean MSPL varies regionally for both wet and dry phases： the MSPL in the wet （dry） phase is relatively higher （lower） in southern China than in other regions. Further, the pattern of the MSPL for the wet phase is almost opposite to that for the dry phase in both autumn and winter. The MSPL in the dry phase is higher in winter and lower in spring and autumn in southern China, while the MSPL values in the wet phase are higher in summer and winter than those in spring and autumn in southern China. The spatial distribution of the MSPL resembles that of the prediction skill of monthly precipitation from a dynamic extended-range forecast system. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 2095-6037 0894-0525 2198-0934 2191-4788 |
| DOI: | 10.1007/s13351-015-5049-z |