A Climate Prediction Method Based on EMD and Ensemble Prediction Technique |
Bi, Shuoben
(School of Geographic Sciences, Nanjing University of Information Science & Technology)
Bi, Shengjie (Department of Computer Science, Dartmouth College) Chen, Xuan (School of Computer & Software, Nanjing University of Information Science & Technology) Ji, Han (School of Geographic Sciences, Nanjing University of Information Science & Technology) Lu, Ying (School of Geographic Sciences, Nanjing University of Information Science & Technology) |
1 | Xue, Z., Zhang, S.: Advance in research and application about temperature forecastmethod. Journal of Arid Meteorology. 30(3), 451-458 (2012) |
2 | Yang, F., Tian, Y.: Safety prediction on water level of dam based onmean generating function. Journal of Safety Science and Technology. 12(9), 26-29 (2016) |
3 | Yu, W.: Theoretical Study and Application of Time-Frequency Analysis Method Based on Empirical Mode Decomposition. Yanshan University, Qinhuangdao (2006) |
4 | Yu,W.J., Su, R., Shao, M.Y., et al.: Correlation between the regularity of abnormal fluctuation of sea surface temperature and rain and drought disasters in the Lancang River basin. Acta Ecol. Sin. 36(4), 1115-1124 (2016) |
5 | Zhang, T., Tang, H., Li, Y., et al.: Application of ensemble prediction to precipitation forecast statistical model in main urban area of Chongqing. Journal of Meteorology and Environment. 31(5), 112-119 (2015) |
6 | Zhang, H.B., Zhi, X.F., Chen, J., et al.: Achievement of perturbation methods for regional ensemble forecast. Trans. Atmos. Sci. 40(2), 145-157 (2017a) |
7 | Zhang, J., Wang, L., Zuo, R., et al.: A predicting test on climatic time series based on amplitude-frequency separation. Chin. J. Atmos. Sci. 41(3), 501-514 (2017b) |
8 | Zhao, J.P., Huang, D.J.: Mirror extending and circular spline function for empirical mode decomposition method. Journal of Zhejiang University. 2(3), 247-252 (2001) DOI |
9 | Zhong, Y., Jin, T., Qin, S.: New envelope algorithm for Hilbert-Huang transform. Journal of Data Acquisition & Processing. 20(1), 13-17 (2005) |
10 | Zhu, J., Qiu, X.: Dealing with the end issue of EMD based on orthogonal polynomial fitting algorithm. Computer Engineering and Applications. 23, 72-74 (2006) |
11 | Dong, X., Wang, G., Ha, L.: Mean function model for Chifeng Tempreture and precipitation experiment during summer. Meteorology Journal of Inner Mongolia. 01, 24-26 (2008) |
12 | Chen, C., Lin, K.: Relation between Pre-flood Season Precipitation Anomalies in South China and Water Vapor Transportation. Journal of Nanjing Institute ofMeteorology. 27(6), 721-727 (2004) |
13 | Deng, Y., Wang, W., Qian, C., et al.: Frontier process in EMD methods and Hilbert change. Chin. Sci. Bull. 46(3), 257-263 (2001) DOI |
14 | Do, J.: Present situation and Prospect of ensemble numerical prediction. Quarterly Journal of Applied Meteorology. 13(1), 16-28 (2002) |
15 | Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco (2001) |
16 | Du, J.: Present situation and prospects of ensemble numerical prediction. Journal of Applied Meteorological Science. 1(1), 16-28 (2002) |
17 | Duan,M.,Wang, P.: Advances in researches and applications of ensemble prediction. Journal of Nanjing Institute of Meteorology. 27(2), 279-288 (2004) |
18 | Duan,W., Huang, L., Han, Y., Huang, D.: A hybrid EMD-AR model for nonlinear and non-stationary wave forecasting. Journal of Zhejiang University-Science A (Appl Phys & Eng). 17(2), 115-129 (2016) DOI |
19 | Brockwell, Peter J. and Davis, Richard A.: Time series: Theory and methods (Edition). World Publishing Corpration (1988) |
20 | Hu, F., Wang, L., Zuo, R., et al.: Extra-seasonal predicting tests and analyses of several statistical forecasting methods on precipitation over Nanjing in 1998. Climatic and Environmental Research. 22(1), 23-34 (2017) |
21 | Huang, N.E., Zheng, S.: The empirical mode decomposition and the Hilbert Spectrum for nonlinear and nonstationary times series analysis. Proceedings of the Royal Society London. 454, 903-995 (1998) DOI |
22 | Li, Q., Zhao, Y., Liao, H., Li, J.: Effective forecast of Northeast Pacific Sea surface temperature based on a complementary ensemble empirical mode decomposition-support vector machine method. Atmospheric and Oceanic Science Letters. 10(3), 261-267 (2017b) DOI |
23 | Huang, D.J., Zhao, J.P., Su, J.L.: On the end extending in the Hilbert-Huang transform. In: Chio, B.H. (ed.): Progress in coastal engineering and oceanography, vol. 1, pp. 81-92. Coastal Oceanography of Asian Seas. Korean Society of Coastal and Ocean Engineers, Seoul (1999) |
24 | Jia, X., Chen, L., Gao, H., et al.: Advances of the short-rang climate prediction of China. Journal of Applied Meteorological Sciences. 24(6), 641-655 (2013) |
25 | Leith, C. E. Theoretical skill of monte carlo forecasts. Monthly Weather Review. 102(6), 409-418 (1974) DOI |
26 | Li, J., Liao, Y., Zhang, B., Shen, T.: The preliminary application of ensemble prediction. Plateau Meteorology. 26, 860-886 (2007) |
27 | Li, J., Zhao, Y., Liao, H., et al.: SST forecast based on BP neural network and improved EMD algorithm. Climatic and Environmental Research. 22(5), 587-600 (2017a) |
28 | Li, X., Chen, W., Su, X.: Three dimensional reconstruction based on improved empirical mode decomposition. Journal of Sichuan University (Natural Science Edition). 55(1), 111-117 (2018) |
29 | Lin, Z., Wang, S.: End analysis of northern hemisphere temperature variability during last 4 centuries. J. Trop. Meteorol. 24(1), 90-96 (2004) |
30 | Liu, Tinghui.: Research and application of EMD method. Anhui University, Hefei (2004) |
31 | Liu, D.,Ma, L., Liu, T., et al.: A coupled simulation and forecast model of mean generating function and BP neural network (MGF-BP-I). Journal of China Hydrology. 36(6), 7-15 (2016) |
32 | Stensrud, D.J., Bao, J.,Warner, T.: Using initial condition and model physics perturbation in short-range ensemble simulations of mesoscale connective system. Mon. Weather Rev. 128, 2077-2107 (2000) DOI |
33 | Ma, J., Lu, J., Zhao, J.-b.: Application of EMD method in prediction of summer precipitation in Guangxi. Journal of Meteorological Research and Application. 35(3), 31-35 (2014) |
34 | Ma, X., Shi, Y., He, J., et al.: The combined descending averaging bias correction based on the Kalman filter for ensemble forecast. Acta Meteorologica Sinica. 73(5), 952-964 (2015) |
35 | Qin, Z.: Application of stepwise regression model based on mean-valued generated function in the forecast of long-term temperature decreasing and precipitation. Journal of Guangxi Meteorology. 24(1), 15-17 (2003) |
36 | Rong, Q., Liu, F.: Ce Su. HHT dense mode identification method based on improved empirical mode decomposition. Application Research of Computers. 35(12), 1-7 (2018) |
37 | Shen, Y., Huang, F., Zhang, D., Yang, X., Chen, X.: Support vector Machines for Short Range Climate Prediction during Main Rainy Season in Sanming. Guangdong Meteorology. 02, 23-25 (2009) |
38 | Wei, Fengying, Cao, Hongxing.: Mathematical models of long-term prediction and its application. Meteorological Press, Beijing (1990) |
39 | Wu, W., Li, C., Tai, W., Han, C., Guo, Y., Shao, X.: Application of optimal climate-value method for short-term climate prediction. Meteorology Journal of Inner Mongolia. 01, 12-13 (2008) |
40 | Ma, J., Zhu, Y.,Wang, P., et al.: A review on the developments of NCEP, ECMWF and CMC global ensemble forecast system. Trans. Atmos. Sci. 34(3), 370-380 (2011) |
41 | Xiong, M.: Calibrating daily 2mmaximum and minimum air temperature forecasts in the ensemble prediction system. Acta Meteorologica Sinica. 75(2), 211-222 (2017) |
![]() |