ITU-R P 841-4-2005 Conversion of annual statistics to worst-month statistics《年统计到最坏月统计的转换》.pdf

1、 Rec. ITU-R P.841-4 1 RECOMMENDATION ITU-R P.841-4 Conversion of annual statistics to worst-month statistics (Question ITU-R 201/3) (1992-1999-2001-2003-2005) The ITU Radiocommunication Assembly, considering a) that for design of radiocommunication systems the required statistics of propagation effe

2、cts pertain to the worst-month period of reference; b) that the reference statistics for many radiometeorological data and propagation prediction methods is “the long-term average annual” distribution; c) that consequently there is a need for a model that provides for the conversion of the “annual”

3、to the “worst-month” statistics, recommends 1 that the model given in Annex 1 be used for the conversion of the average annual time percentage of excess to the average annual worst-month time percentage of excess. Annex 1 1 The average annual worst-month time percentage of excess, pw, is calculated

4、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 pwrefer to the same threshold levels. 2 Q is a two parameter (Q1, ) function of p (%): ()=ppQpQpQpQQpQQp%30for303%30%3for3%312for%12for12)3.0log(3log1111111)(1(2) 2 Rec. IT

5、U-R P.841-4 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 relationship: p = pw / Q (3) and the dependence of Q on pwcan be easily derived from the above given dependence o

6、f Q on p. The resulting relationship for 12 p0 pw(%) Q13(1)is ( p0= (Q1/12)1/): )1/()1/(11=wpQQ (4) 4 For global planning purposes the following values for the parameters Q1and should be used: Q1= 2.85, = 0.13 (see Fig. 1). This leads to the following relationship between p and pw: 15.1(%)30.0(%)wpp

7、 = (5) for 1.9 104 pw(%) 7.8. Rec. ITU-R P.841-4 3 For global rain rate applications, the following values for the parameters Q1and 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 regio

8、ns (see Fig. 2). This leads to the following relationship between p and pw: 18.1(%)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. 5

9、For more precision the values of Q1and for the different climatic regions and various propagation effects given in Table 1 should be used where appropriate. 6 For trans-horizon mixed paths, the and Q1values are calculated from those values for sea and land given in Table 1, through linear interpolat

10、ion using the fractions of the link traversing sea and land respectively as weights. 4 Rec. ITU-R P.841-4 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

11、region 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. TABLE 1 and Q1values for various propagation effects and locations Rain effect te

12、rrestrial attenuation Rain effectslant path attenuationRain rate Multipath Trans-horizon land Trans-horizon sea Global 0.13, 2.85 0.13, 2.85 0.13, 2.85 0.13, 2.85 0.13, 2.85 Tropical, subtropical and temperate climate regions with frequent rain 0.15, 2.82 Dry temperate, polar and desert regions 0.11

13、, 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, 3.8 Europe Poland 0.18, 2.6 Europe Russian Federa

14、tion 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 Rec. ITU-R P.841-4 5 TABLE 1 (continued) Rain effect terrestrial attenuation Rain effectslant path attenuationRain rate Multipath Trans-horizon land Trans-horizon sea Canada Coast and Great Lake 0.10

15、, 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 South Ural 0.10, 4.27 Russian Federation Central Step

16、pe 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 Australia Subtropical/ coastal 0.15, 3.15 6 Rec. ITU-R P.8

17、41-4 TABLE 1 (end) Rain effect terrestrial attenuation Rain effectslant path attenuationRain 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 Brazil Tropical inland 0.13, 3.00 Brazil Subtropical 0.

18、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