STUDY ON THE CREATION OF DAILY CLIMATIC VARIATION SCENARIOS WITH A STOCHASTIC WEATHER GENERATOR AND VARIOUS INTERPOLATIONS

Wu Jindong; Wang Futang

Vol.11, NO.2, 2000

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2000 > 11(2): 129-136

Wu Jindong, Wang Futang. Study on the creation of daily climatic variation scenarios with a stochastic weather generator and various interpolations. J Appl Meteor Sci, 2000, 11(2): 129-136.

Citation:

Wu Jindong, Wang Futang. Study on the creation of daily climatic variation scenarios with a stochastic weather generator and various interpolations. J Appl Meteor Sci, 2000, 11(2): 129-136.

Wu Jindong, Wang Futang. Study on the creation of daily climatic variation scenarios with a stochastic weather generator and various interpolations. J Appl Meteor Sci, 2000, 11(2): 129-136.

Citation:

Wu Jindong, Wang Futang. Study on the creation of daily climatic variation scenarios with a stochastic weather generator and various interpolations. J Appl Meteor Sci, 2000, 11(2): 129-136.

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STUDY ON THE CREATION OF DAILY CLIMATIC VARIATION SCENARIOS WITH A STOCHASTIC WEATHER GENERATOR AND VARIOUS INTERPOLATIONS

Chinese Academy of Meteorological Sciences, Beijing 100081

Received Date: 1999-04-29
Rev Recd Date: 1999-06-14
Publish Date: 2000-05-31

Abstract

Abstract

In view of the lower temporal resolution of general circulation models (GCMs) in assessing the impacts of climatic variation, the requirements of climatic variation scenarios and the studies on the potential implication of climatic variation, a stochastic weather generator WGEN is used to produce daily climatic variation scenario which also embodies possible climatic variability in Northeast China in accordance with commonly available information from GCMs. It could be applied to couple with climatic impact models, such as crop growth and development models in order to study the variation of crop growth and development and their yields, and possible impacts of variation of climatic variability.
- Daily climatic variation scenario;
- Stochastic simulation;
- Interpolation

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References(11)

Figures and Tables

图 1 气候要素时间尺度插值效果分析 (沈阳) (a) 最高气温 (b) 最低气温 (c) 降水量

(实线: 实测值虚线: 反插值)

DownLoad: Full-Size Img PowerPoint

图 2 WGEN模拟的逐日最高、最低气温和降水量情景相对于基准气候的变化 (沈阳)

DownLoad: Full-Size Img PowerPoint

表 1 DKRZ OPYC模拟的东亚气候区域平均变化^[9]

表 2 DKRZ OPYC输出及其插值订正前后最高气温 (T_max) 最低气温 (T_min) 和降水量 (p) 增量对比分析 (沈阳)

表 3 WGEN模拟试验与DKRZ OPYC试验结果对比分析

References

[1]	Parry M L.Climate Change and World Agriculture.London: Earths can publications Ltd., IIASA, UNEP, 1990.157. doi: 10.1080/00139157.1991.9931405?journalCode=venv20
[2]	Smith J B, Tirpak D, et al.The Potential Effects of Global Climate Change on the United States.U.S./EPA, EPA-230-05-89-050, 1989.413. https://www.osti.gov/scitech/biblio/5474372-potential-effects-global-climate-change-united-states
[3]	Carter T R, Parry M L, Nishioka S, et al.Climate Change: Preliminary Guidelines for Assessing Impacts of Climate Change.ECU/CGER, 1992.28.
[4]	Katz R W, Brown B G.Extreme events in a changing climate: Variability is more important than averages.Clim.Change, 1992, 21: 289~302. doi: 10.1007/BF00139728
[5]	IPCC.Climate Change 1995: The Science of Climate Change.Eds: by Houghton J T, Meira Filho L G, Callander B A, et al.Cambridge University Press, 1996.572.
[6]	Wilks D S.Adapting stochastic weather generation algorithms for climate change studies.Clim.Change, 1992, 22: 67~84. doi: 10.1007%2FBF00143344
[7]	Richardson C W, Wright D A.WGEN: A Model for Generating Daily Weather Variables.U.S.Dept.of Agriculture, Agricultural Res.Service, 1984, ARS-8, pp83.
[8]	吴金栋, 王馥棠.随机天气模式参数化方案的研究及其模拟能力评估.气象学报, 2000, 58 (1): 42~51. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXB200001004.htm
[9]	赵宗慈, 丁一汇, 李晓东, 等.海气耦合模式在东亚地区的可靠性评估.应用气象学报, 1995, 6 (增刊): 9~18. http://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFD9495&filename=YYQX5S1.001&v=MDgyMDlPZHVGeXpsV3c9PVBEVGFkcmJiSDgvTXI0NHFGNTRPZmdnNXpoQVU0amg0T1g2VHJIMDNlYk9UUmI2ZVo=
[10]	侯景儒, 郭光裕.矿床统计预测及地质统计学的理论与应用.北京:冶金工业出版社, 1993.354~385.
[11]	Mearns L O, Resorvzzweigc, Goldberg R, et al.Mean and variance change in climate scenarios: method s, agriculture applications, and measures of uncertainty.Clim.Change, 1997, 35: 367~396. doi: 10.1023/A:1005358130291