A QUESTION WHEN USING OBSERVATION DATA TO GET REGIONAL AVERAGED VALUE

Niu Tao; Liu Hong li; Chen Longxun

Vol.15, NO.2, 2004

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2004 > 15(2): 192-199

Niu Tao, Liu Hongli, Chen Longxun. A question when using observation data to get regional averaged value. J Appl Meteor Sci, 2004, 15(2): 192-199.

Citation:

Niu Tao, Liu Hongli, Chen Longxun. A question when using observation data to get regional averaged value. J Appl Meteor Sci, 2004, 15(2): 192-199.

Niu Tao, Liu Hongli, Chen Longxun. A question when using observation data to get regional averaged value. J Appl Meteor Sci, 2004, 15(2): 192-199.

Citation:

Niu Tao, Liu Hongli, Chen Longxun. A question when using observation data to get regional averaged value. J Appl Meteor Sci, 2004, 15(2): 192-199.

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A QUESTION WHEN USING OBSERVATION DATA TO GET REGIONAL AVERAGED VALUE

Chinese Academy of Meteorological Sciences, Beijing 100081

Received Date: 2003-01-02
Rev Recd Date: 2003-06-17
Publish Date: 2004-04-30

Abstract

Abstract

In order to get a time series that represent the total characteristics of some regions, objective analysis and regional-averaged method are widely used to handle observation data. Barnes objective analysis method is a convergent weighted-averaging interpolation scheme which is most generally used in meteorological and ocean field. The characteristics of the elements such as soil temperature, air temperature (include max and min temperature), air pressure etc. On the Tibetan-Qinghai Plateau were analyzed by using these two methods. It is found that when data are not good in continuity, the influence caused by the different region of observe station must be removed in order to get a reliable conclusion, otherwise an erroneous conclusion is got, so this question should be paid attention to.
- Objective analysis method;
- Territory dif ference;
- Data discontinui ty

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References(8)

Figures and Tables

图 1 本文所用青藏高原120个观测站位置分布

(圆圈为测站位置,虚线为海拔高度等值线)

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图 2 青藏高原平均气温(a)和地温(b)时间序列以地温有效起始年分布(c)

(实线为Baners方法得到的曲线，虚线为区域化方法得到的曲线)

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图 3 缺测处理后应用Baners方法再求平均得到的气温序列

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图 4 (a)实线为先将各站气温资料标准化,再用Barnes方法得到的高原平均气温序列,虚线为将缺测处理后的气温序列标准化,再用Barnes方法得到的高原平均气温序列,(b)为先将各站地温资料标准化,再用Barnes方法得到的高原平均地温序列

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图 5 (a)序列A(实线)，序列B(长虚线)，序列C(短虚线)曲线；(b)表 1中的平均值序列曲线(虚线为线性拟合线)；(c)表 2中的平均值序列曲线(虚线为二次拟合线)

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图 6 中文表 3中的平均值序列曲线标题

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图 7 各站0 cm地温(a)、气温(b)的线性趋势分布

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表 1 任意给出的3个具有“ 数值增大线性倾向” 的序列

表 2 在假设表 1 中的“ 序列C” 前3次缺测情况下得到的新序列

表 3 将表 1 中的序列标准化后得到的新序列

References

[1]	Mitchell J M. Recent secular changes of global temperature. Ann. N. Y. Acad. Sci., 1961, 95: 235～250.
[2]	Hansen J, Lebedeff S. Global trend of measured surface air temperature. J. Geophy. Rev., 1987, 92(D11): 13345～13372.
[3]	Jones P D. The influence of ENSO on global temperatures. Climate Monitor, 1988, 17: 80～89.
[4]	Vinnikov K Ya, et al. Empirical on contemporary global climate changes (temperature and precipitation). J. Climate., 1990, 3: 662～677.
[5]	严中伟,季劲钧,叶笃正. 60年代北半球夏季气候跃变. 中国科学B辑,1990, 1: 97～103. http://www.cnki.com.cn/Article/CJFDTOTAL-JBXK199001014.htm
[6]	王绍武, 叶瑾琳. 近百年全球气候变暖的分析. 大气科学,1995,19(5): 545～553.
[7]	翟盘茂, 任福民. 中国近四十年最高、最低温度变化. 气象学报,1997,55(4): 418～429. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXB704.003.htm
[8]	Barnes S L. A technique for maximizing details in numerical weather map analysis. J. Appl. Met., 3: 396～409.