物候模式识别在生态动力预报中的应用

应用生态学报 ›› 2005, Vol. 16 ›› Issue (9): 1661-1666.

物候模式识别在生态动力预报中的应用

裴铁璠, 金昌杰

中国科学院沈阳应用生态研究所, 沈阳 110016

收稿日期:2005-04-06 修回日期:2005-05-05 出版日期:2005-09-15 发布日期:2005-09-15
通讯作者: 裴铁璠,男,1942年生,研究员.主要从事生态水文和生态气候研究,发表研究论文近百篇,出版专著4部,参编专著7部.Tel:024-83970337;E-mail:TFPei@iae.ac.cn
基金资助:
中国科学院知识创新工程重要方向项目(YCXZY0203)和国家重点基础研究发展规划资助项目(2002CB111503).

Application of phenological pattern recognition in ecological dynamic forecasting

PEI Tiefan, JIN Changjie

Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China

Received:2005-04-06 Revised:2005-05-05 Online:2005-09-15 Published:2005-09-15

摘要/Abstract

摘要： 以物候资料和数值天气预报模式输出图为基础,应用模式识别和数理逻辑判断的自动化技术,阐述制作生态动力预报的原理、方法和步骤.生态动力预报技术使传统的物候学在气象学和自动化技术支持下,扩展应用到生态预报业务领域,使物候预报从单站预报阶段发展到区域预报阶段,同时促进了农业气象预报方法从定性、统计阶段向动力预报阶段发展.该方法在农作物播种、长势、灌溉与施肥、病虫害防治等方面具有广阔的应用前景.

关键词: 生态动力预报, 物候学, 数值天气预报, 数理逻辑, 模式识别

Abstract: This paper described the principles,methods,and procedures of ecological dynamic forecasting by the automation techniques of pattern recognition and mathematical logic judgment on the basis of phenological data and model output maps from T42L9 numerical weather prediction model.This new forecasting method proposed on the basis of modern meteorology and automation techniques enables the classic phenology to apply to a new field ecological forecasting.It enables phenological forecasting to develop from single-station forecasting stage to regional forecasting stage,which is greatly corresponded to the development stage from single station forecasting stage to synoptic stage in weather forecasting,and enables agro-meteorological forecasting to develop from qualitative and statistical forecasting stage to ecological dynamic forecasting stage.With this new qualitative forecasting method,both the predicted objective and predictors are of considerable bio-physical interests.The ecological dynamic forecasting method could be applied to crop sowing,crop growth,irrigation and fertilization,and diseases and pests control.

Key words: Ecological dynamic forecasting, Phenology, Numerical weather prediction, Mathematical logic, Pattern recognition

中图分类号:

S165

裴铁璠, 金昌杰. 物候模式识别在生态动力预报中的应用[J]. 应用生态学报, 2005, 16(9): 1661-1666.

PEI Tiefan, JIN Changjie . Application of phenological pattern recognition in ecological dynamic forecasting[J]. Chinese Journal of Applied Ecology, 2005, 16(9): 1661-1666.

参考文献

[1] Beaubien EG, Freeland HJ. 2000. Spring phenology trends in Alberta Canada:Links to ocean temperature. Int J Biometeorol, 44 (1):53～59
[2] Bradley NL, Leopold AC, Ross J, et al. 1999. Phenological changes reflect climate change in Wisconsin. Proc Nat Acad Sci United States America, 96:9701～9704
[3] Chemielewski FM, Rotzer T. 2002. Annual and spatial variability of the beginning growing season in Europe in relation to air temperature changes. Clim Res, 19 (1):257～264
[4] China Meteorological Bureau (中国气象局). 1993. Agrometeorological Observation Standard. Beijing:Meteorological Press. 1～4(in Chinese)
[5] Chmielewski FM, Müller A, Bruns E. 2004. Climate changes and trends in phenology of fruit trees and field crops in Germany, 1961～2000. Agric For Meteorol, 121(1) :69～78
[6] Chou J-F(丑纪范), Du X-Y(杜行远), Guo B-R(郭秉荣). 1980.Numerical Weather Prediction. Beijing:Meteorological Press. 1～10(in Chinese)
[7] Chou J-F(丑纪范). 1986. Long-Range Numerical Weather Prediction. Beijing:Meteorological Press. 1～3 (in Chinese)
[8] Chuine I, Bour P, Rousseau DD. 1999. Selecting models to predict the tiraing of flowering of temperate trees:Implication for tree phenology modeling. Plant Cell Environ, 22 (1) :1～13
[9] Fornaciari MF, Orland CA, Bomano B. 2003. Technigues for reconstructing data on flowering. Ekologiya, 13 (1):63～65 (in Russian)
[10] Hense A, Glowienka-Hense R, Muller M, et al. 2002. Spatial modelling of phenological observations to analyse their interannual vaitions in Germany. Agric For Meteorol, 112(2):161～178
[11] Hu G-L(胡广隆).2002.Practical Medium-Range and Long-Range Weather Forecasting. Beijing:Nation Defence Industry Press. 1～21(in Chinese)
[12] Kramer K, Leinonen I, Loustau D. 2000. The importance of phenology for the evaluation of impact of climate change on growth of boreal temperate and Mediterranean forest ecosystems:An overview.Int J Biometeorol, 44(1) :67～75
[13] Liu DL, Kingston G, Bull TA. 1998. A new technique for determining the thermal parameters of phenological development in sugarcane, including subopimum and supra-optimum temperature regimes. Agric For Meteorol, 90(2):119～139
[14] Liu X-Z(刘秀珍), Yu X-M(于系民). 1999. Language of the Nature. Beijing:Meteorolagical Press. 1～25 (in Chinese)
[15] Olsen JK, McMahon CR, Hammet GL. 1993. Prediction of sweet corn phenology in subtropical environments. Agron J, 85 (3):410～415
[16] Pei TF, Jin CJ, Guan DX. 2004. Ecological Dynamics and Cybernetics Principle. Beijing:Science Press; Monmouth Junction:Science Press USA Inc. 25,199～204
[17] Qi R-Y(祁如英), Ning X-J(宁新江), Yan J-R(严进瑞).2004.Phenologico-season division and its application in Normuhong Region, Qinghai Province. Chin Agrometeorol (中国农业气象), 23(2):33～35 (in Chinese)
[18] Schwartz MD. 1999. Advancing to full bloom:Planning phenological research for the 21st century. Int J Biometeorol, 42(1):113～118
[19] Theodoridis S, Koutroumbas K. 2003. Pattern Recognition. 2nd edition. New York:Elsevier Science Ltd. 1～5
[20] Zeng Q-C(曾庆存).1979. Mathematico-physical Basis of Numerical Weather Prediction. Beijing:Science Press. 1～25 (in Chinese)
[21] Zhu K-Z(竺可桢), Wan M-W(宛敏谓). 1999. Phenology. Changsha:Hunan Education Press. 1～15 (in Chinese)