GB/T 33669-2017 Extreme precipitation monitoring indicators GB/T33669-2017 |tt||Standard compression package decompression password: www.bzxz.net
This standard specifies the daily precipitation extreme monitoring indicators of a single station and their calculation methods. ? This standard is applicable to extreme precipitation monitoring, assessment and service work.

ICS07.060
National Standard of the People's Republic of China
GB/T33669—2017
Monitoring indices of precipitation extremes2017-05-12Issued
General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of ChinaStandardization Administration of the People's Republic of China
2017-12-01Implementation
1 Scope
2 Terms and definitions
3 Monitoring indicators
Data and calculation methods
Appendix A (Normative Appendix)
Generalized extreme value distribution (GEV) method
References
GB/T33669—2017
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This standard was drafted in accordance with the rules given in GB/T1.1-2009. This standard was proposed by the China Meteorological Administration.
This standard is under the jurisdiction of the National Technical Committee for Climate and Climate Change Standardization (SAC/TC540). The drafting unit of this standard: National Climate Center. The main drafters of this standard: Zou Xukai, Gao Rong, Wang Zunya, Chen Xianyan. GB/T33669—2017
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1 Scope
Extreme precipitation monitoring indicators
This standard specifies the extreme monitoring indicators of daily precipitation at a single station and their calculation methods. This standard applies to extreme precipitation monitoring, assessment and service work. 2 Terms and definitions
The following terms and definitions apply to this document. 2.1
Precipitation amount
The depth of precipitation accumulated on the horizontal surface without evaporation, infiltration or loss in a certain period of time. 2.2
Climate normal period climate normal period The three consecutive whole years used to calculate the multi-year average of meteorological elements. Example: 1981-2010 is the climate standard period used for 2011-2020. 2.3
Percentile
percentilebZxz.net
GB/T33669—2017
Sort a set of data from small to large and calculate the corresponding cumulative percentile. The value of the data corresponding to a certain percentile is the percentile of this percentile.
extreme percentile value
Extreme value
The critical value of a statistic reaching an extreme condition. The 95th percentile is used as the extreme threshold for extreme precipitation. 2.5
extremum
The maximum or minimum value of a statistic or monitoring indicator within a certain period of time. 2.6
Continuous precipitation
consecutive precipitation
The phenomenon that the daily precipitation is greater than or equal to 0.1mm for multiple consecutive days (greater than or equal to 2 days). 2.7
Continuous days of precipitation
consecutive days of precipitation The total number of consecutive days with daily precipitation greater than or equal to 0.1mm. 2.8
Continuous precipitation
consecutive precipitation amounts The accumulated precipitation within consecutive precipitation days. 2.9
monthreturn period
recurrence period
the time interval between the recurrence of a specific value of a statistic, measured in years. Hii KAoNi KAca
GB/T33669—2017
3 Monitoring indicators
3.1 Extreme daily precipitation
Daily precipitation greater than or equal to the daily precipitation extreme threshold. 3.2 Extreme continuous precipitation days
The number of continuous precipitation days greater than or equal to the continuous precipitation extreme threshold. 3.3 Extreme continuous precipitation
The cumulative amount of continuous precipitation greater than or equal to the continuous precipitation extreme reading value. 3.4 Extreme precipitation recurrence period
The recurrence period of extreme precipitation index greater than or equal to the extreme precipitation recurrence period threshold. Data and calculation method
4.1 Data used
Daily precipitation observation data (the statistical period uses Beijing time 20:00-20:00 or 08:00-08:00). 4.2 Calculation method
4.2.1 Determination of extreme precipitation threshold
Use percentile to determine the extreme precipitation threshold, that is, take the extreme value and sub-extreme value of a precipitation index in each year during the climate standard period (such as 1981-2010), and construct a sequence containing 60 samples; sort the sequence from small to large, and take the 95th percentile as the extreme threshold of excessive (large) precipitation. Events greater than or equal to this threshold are extreme excessive (large) events. 4.2.2 Calculation method of extreme precipitation return period The generalized extreme value distribution (GEV) theoretical probability model is used to calculate the return period of each extreme precipitation index. The method is shown in Appendix A. 2
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A.1 Generalized Extreme Value Distribution
Appendix A
(Normative Appendix)
Generalized Extreme Value Distribution (GEV) Method
GB/T33669—2017
In meteorological probability statistics, three extreme value distribution functions, Gumbel, Fréchet and Weibull, are often used to fit the extreme values ​​of climate elements. These three distribution models can be written as a general formula , that is, the extreme value distribution function with three parameters, is called the generalized extreme value distribution (GEV). Its theoretical distribution function is shown in formula (A.1):
[F()=exp[-(1-ky)k0
[F()=exp[-exp(—y)]
where y is shown in formula (A.2):
where:
random variable;
scale parameter;
β-location parameter;
shape parameter.
When k≠0, the GEV distribution function is shown in formula (A.3):F(r)=exH
where ko, it obeys Weibull distribution. When k=0, it obeys Gumbel distribution, see formula (A.4): F(r)=exp
A,2Use generalized extreme value distribution function to calculate the return period exp
For the quantile I of the return period T, there is a distribution function, see formula (A.5): F(T)=1-
From this, the corresponding quantile I can be solved to see formula (A.6): =β+[1-(-1n(1-))
=βaln[-In(1-)]
Where:
Return period.
.（A.4)
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References
GB/T28592—2012 Precipitation levels
QX/T52—2007 Specifications for surface meteorological observations Part 8: Precipitation observations [3] Ding Yuguo, Jiang Zhihong. Introduction to extreme climate research methods [M]. Beijing: Meteorological Press. 2009 [4]
Shi Daoji. Practical extreme value statistical methods [M]. Tianjin: Tianjin Science and Technology Press, 2005 [5] Gao Rong, Zou Xukai, Wang Zunya, Zhang Qiang, etc. Atlas of Extreme Weather and Climate Events in China[M. Beijing: Meteorological Press. 2012[6] Alexander LV et al, Global observed changes in daily climatic extremes of temperature and precipitation.JGeophysRes2006,111.D05109.doi:10.1020/2005JD006290[7J Jones PD, Horton EB, Folland CK, et al. The use of indices to identify changes in climaticextremes.ClimaticChange，199942,131-149[8]J Zhai P., Zhang X, .Wan H, Pan X. Trends in Total Precipitation and Frequency of DailyPrecipitationExtremesoverChina,J.Climat.,2005,18(7),1096-1108[9] Zhang, X., Alexander, L., Hegerl, GC, et al. Indices for monitoring changes inextremes based on daily temperature and precipitation data. WIREs Clim Change, 201l, 2: 851-870.doi:10.1002/wcc.147
GB/T33669-2017
People's Republic of China
National Standard
Extreme Precipitation Monitoring Index
GB/T33669—2017
Published and distributed by China Standards Press
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Printed by China Standard Press, Taihuangdao Printing Factory Distributed by Xinhua Bookstores in various regions
Format 880X12301/16
Printing Sheet 0.75
Word Count 10,000
First Edition in May 2017
First Printing in May 2017
Book Number: 155066·1-55982 Price 16.00 RMB
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