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本文(ITU-R P 841-5-2016 Conversion of annual statistics to worst-month statistics《将年度统计数字转换为最坏月份统计数字》.pdf)为本站会员(李朗)主动上传,麦多课文库仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对上载内容本身不做任何修改或编辑。 若此文所含内容侵犯了您的版权或隐私,请立即通知麦多课文库(发送邮件至master@mydoc123.com或直接QQ联系客服),我们立即给予删除!

ITU-R P 841-5-2016 Conversion of annual statistics to worst-month statistics《将年度统计数字转换为最坏月份统计数字》.pdf

1、 Recommendation ITU-R P.841-5 (09/2016) Conversion of annual statistics to worst-month statistics P Series Radiowave propagation ii Rec. ITU-R P.841-5 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum

2、 by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Con

3、ferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Annex 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements

4、 and licensing declarations by patent holders are available from http:/www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also availa

5、ble online at http:/www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite s

6、ervices P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and

7、 frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1. Electronic Publication Geneva, 2016 ITU 2016 All rights reserved. No part of this publication may be reproduced, by any means w

8、hatsoever, without written permission of ITU. Rec. ITU-R P.841-5 1 RECOMMENDATION ITU-R P.841-5 Conversion of annual statistics to worst-month statistics (Question ITU-R 201/3) (1992-1999-2001-2003-2005-2016) Scope This Recommendation provides a methods for the conversion of annual percentage of exc

9、ess into worst-month percentage of excess for propagation related parameters. Keywords Worst-month statistics, annual statistics, conversion method The ITU Radiocommunication Assembly, considering a) that for design of radiocommunication systems the required statistics of propagation effects pertain

10、 to the worst-month period of reference; b) that the concept of worst-month is defined in Recommendation ITU-R P.581; c) that the reference statistics for many radiometeorological data and propagation prediction methods is “the long-term average annual” distribution; d) that consequently there is a

11、need for a method that provides for the conversion of the “annual” to the “worst-month” statistics, recommends 1 that, when monthly statistics are not available, the method given in Annex 1 be used for the conversion of the average annual time percentage of excess to the average annual worst-month t

12、ime percentage of excess. Annex 1 1 The average annual worst-month time percentage of excess, pw, is calculated from the average annual time percentage of excess p by use of the conversion factor Q: pw Q p (1) where 1 Q 12, and both p and pw refer to the same threshold levels. 2 Rec. ITU-R P.841-5 2

13、 Q is a two parameter (Q1, ) function of p (%): ppQpQpQpQQpQQp%30fo r303%30%3fo r3%312fo r%12fo r12)3.0log(3log1111111)(1 (2) 3 The calculation of the average annual time percentage of excess from the given value of the average annual worst-month time percentage of excess is done through the inverse

14、 relationship: p pw / Q (3) and the dependence of Q on pw can be easily derived from the above given dependence of Q on p. The resulting relationship for 12 p0 pw(%) Q1 3(1) is ( p0 (Q1/12)1/): )1/()1/(11 wpQQ (4) 4 For global planning purposes the following values for the parameters Q1 and should b

15、e used: Q1 2.85, 0.13 (see Fig. 1). This leads to the following relationship between p and pw: 15.1(% )30.0(% ) wpp (5) for 1.9 104 pw(%) 7.8. Rec. ITU-R P.841-5 3 FIGURE 1 Example of the dependence of Q on p (solid line) with parameter values Q1 = 2.85 and = 0.13 For global rain rate applications,

16、the following values for the parameters Q1 and should be used: Q1 = 2.82, = 0.15, for tropical, subtropical and temperate climate regions with frequent rain Q1 = 4.48, = 0.11, for dry temperate, polar and desert regions (see Fig. 2). This leads to the following relationship between p and pw: 18.1(%

17、)30.0(% ) wpp (6) where 7.7 104 pw(%) 7.17, for tropical, subtropical and temperate climate regions with frequent rain: 12.1(% )19.0(% ) wpp (7) where 1.5 103 pw(%) 11.91, for dry temperate, polar and desert regions. 4 Rec. ITU-R P.841-5 FIGURE 2 Example of the dependence of Q on p with global subre

18、gion parameters 5 For more precision the values of Q1 and for the different climatic regions and various propagation effects given in Table 1 should be used where appropriate. 6 For trans-horizon paths of land or sea, the and Q1 values are calculated from those values for sea and land given in Table

19、 1, where Ns is the local surface refractivity of the Earth lying in the troposcatter common volume. 7 Entries under rain rate for Australia are based on 6-min time interval measurements taken from 20 sites over periods lasting from 25 to 101 years. Examples of site locations for each climatic regio

20、n in Australia are given in the first column of Table 1. Entries under rain rate for Brazil have been derived for measurements of rainfall rates at nine sites over a 46-year period using fast response rain gauges. Rec. ITU-R P.841-5 5 TABLE 1 and Q1 values for various propagation effects and locatio

21、ns Rain effect terrestrial attenuation Rain effect slant path attenuation Rain rate Multipath Trans-horizon land Trans-horizon sea Global 0.13, 2.85 0.13, 2.85 0.13, 2.85 0.13, 5.8-0.03exp (Ns/75) 0.13, 5.8-0.03exp (Ns/75) Tropical, subtropical and temperate climate regions with frequent rain 0.15,

22、2.82 Dry temperate, polar and desert regions 0.11, 4.48 Europe North West 0.13, 3.0 0.16, 3.1 0.13, 4.0 0.18, 3.3 Europe North West 1.3 GHz 0.11, 4.9 Europe North West 11 GHz 0.19, 3.7 Europe Mediterranean 0.14, 2.6 0.16, 3.1 Europe Nordic 0.15, 3.0 0.16, 3.8 0.12, 5.0 Europe alpine 0.15, 3.0 0.16,

23、3.8 Europe Poland 0.18, 2.6 Europe Russian Federation 0.14, 3.6 Europe UK 40 and 50 GHz 0.13, 2.54 Congo 0.25, 1.5 Canada Prairie and North 0.08, 4.3 6 Rec. ITU-R P.841-5 TABLE 1 (continued) Rain effect terrestrial attenuation Rain effect slant path attenuation Rain rate Multipath Trans-horizon land

24、 Trans-horizon sea Canada Coast and Great Lake 0.10, 2.7 Canada Central and Mountains 0.13, 3.0 United States of America Virginia 0.15, 2.7 Russian Federation North European region 0.10, 4.57 Russian Federation Central and West European region 0.16, 2.38 Russian Federation Middle Volga region and So

25、uth Ural 0.10, 4.27 Russian Federation Central Steppe and South European region 0.15, 2.69 Russian Federation West Siberian region 0.14, 3.72 Russian Federation Middle Siberian Plateau and Jakutia 0.11, 5.04 Russian Federation South Far East 0.13, 3.53 Australia Temperate/ coastal 0.17, 2.65 Austral

26、ia Subtropical/ coastal 0.15, 3.15 Rec. ITU-R P.841-5 7 TABLE 1 (end) Rain effect terrestrial attenuation Rain effect slant path attenuation Rain rate Multipath Trans-horizon land Trans-horizon sea Australia Tropical/arid 0.12, 4.35 Brazil Equatorial 0.13, 2.85 Brazil Tropical maritime 0.21, 2.25 Br

27、azil Tropical inland 0.13, 3.00 Brazil Subtropical 0.13, 2.85 Indonesia 0.22, 1.7 Japan Tokyo 0.20, 3.0 Japan Yamaguchi 0.15, 4.0 Japan Kashima 0.15, 2.7 South Korea 0.12, 4.6 Kyrgyzstan Flat regions 0.09, 5.95 Kyrgyzstan Mountainous regions 0.10, 6.70 Kyrgyzstan Coastal region of Ysyk-Kol lake 0.14, 4.73 China South 0.15, 3.12 China North 0.13, 4.12 China Desert 0.10, 5.40

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