使用R的持续时间和强度的历史图

Question

我有以下数据文件。这是一个有四列（YY,MM,DD,RR）的每日降雨量数据。抱歉，这是我能生成的最小的数据。

structure(list(YY = c(1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1980L, 1980L, 
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 
1980L, 1980L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1982L, 1982L, 1982L, 
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 
1982L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 
1983L, 1983L, 1983L, 1983L, 1983L, 1984L, 1984L, 1984L, 1984L, 
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 
1985L, 1985L, 1985L, 1985L, 1986L, 1986L, 1986L, 1986L, 1986L, 
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1987L, 
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 
1987L, 1987L, 1987L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1989L, 1989L, 
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 
1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 
1990L, 1990L, 1990L, 1990L, 1990L, 1990L), MM = c(10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L), DD = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 
30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 
26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 
27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 
28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 
29L, 30L, 31L), RR = c(65.3, 2.6, 3.8, 93.5, 0, 0, 1, 0, 0, 0, 
20.6, 3.4, 0, 0, 0, 0, 0, 0, 29.2, 6.6, 0.5, 1, 18.5, 3.3, 0, 
2, 2.8, 0, 0, 12.8, 15.8, 0, 1.6, 0.3, 25, 3.6, 0, 19.6, 1.8, 
0, 0, 0, 0, 25.9, 0, 6.6, 15.7, 1.3, 30, 0, 0, 0, 0.5, 17, 14.7, 
6.1, 0.5, 67.6, 133.8, 114.6, 0, 0, 0, 25.1, 1.8, 1.4, 0, 0, 
0, 0, 0, 2, 55.7, 36.9, 65, 3.1, 0, 0, 0, 0, 0, 0, 0, 41.4, 13.2, 
29.8, 1, 170.7, 115, 72.9, 25.9, 18, 15.7, 1.3, 4, 0, 0, 0, 8.9, 
0, 1, 0, 0, 6.1, 9.4, 21.6, 11, 13.1, 2.3, 0, 11.3, 4.9, 0.8, 
0, 0.3, 0, 0, 0, 0.3, 6.4, 0, 0, 2.3, 6.9, 21.4, 57.7, 0.3, 35.5, 
2.3, 0, 8.1, 0, 0, 108.2, 7.1, 8.2, 9.4, 14.2, 42.7, 0, 0, 1.3, 
0, 45.2, 203.2, 14.5, 9.2, 22.2, 2.9, 0, 59.5, 19.9, 162.9, 0, 
1, 0, 0, 0, 1.8, 9.9, 54, 8.1, 9.4, 0, 0.8, 0, 0, 0, 0, 0.3, 
0, 0, 7.4, 28.5, 101.2, 87.9, 26.9, 128.9, 78.1, 3.6, 0, 0, 77.5, 
130.1, 262.5, 105.5, 14.9, 0, 0, 0, 2.5, 2.3, 15.5, 28.8, 4.6, 
34.8, 22.1, 60.5, 0.5, 24.1, 0, 0, 37, 128.3, 26, 27.8, 2.3, 
2.3, 195.9, 227.7, 0.8, 2.8, 0, 0, 5.1, 0.3, 0, 0, 0, 0, 9.7, 
125.9, 64.9, 78.3, 3.3, 0, 0, 46.2, 52.6, 3, 24.9, 22.1, 14.2, 
0, 0, 170.6, 64.5, 30.3, 35.8, 204.5, 5.3, 0.5, 3.1, 0, 0, 17.2, 
136.6, 37.9, 0.8, 0, 0.3, 5.1, 2.4, 0, 9.8, 0, 0, 0, 0.2, 0, 
0.3, 0, 0.3, 1.5, 1, 0, 0, 0, 0, 0, 0.8, 1.3, 7.8, 0, 12, 25.2, 
74.3, 26.5, 1.6, 11.2, 0, 0, 0, 0, 5.4, 186.1, 99.7, 46.3, 2.8, 
7.6, 5.6, 22.9, 81, 2, 0, 7.1, 24, 68, 121.8, 10.4, 0, 24.4, 
77.1, 18, 8.9, 0.8, 0, 18.6, 0, 2, 1.3, 0, 18.8, 0, 0, 8.6, 5.6, 
0, 0.5, 61.8, 146.6, 16.5, 0, 18.6, 0, 0, 0, 8.1, 59.4, 8.5, 
1, 54.8, 0, 21.6, 0, 0, 0, 0, 0, 0, 0, 44.2, 0.5, 0, 1.3, 0, 
1.8, 1, 0, 9.7, 93.5, 48.5, 158.3, 78.5, 2.8, 4.1, 13, 98.8, 
55.2, 76.3, 56.3, 0, 6.1, 0, 0, 0, 0, 5.3, 0, 14.5, 0, 0)), row.names =             
c(274L, 
275L, 276L, 277L, 278L, 279L, 280L, 281L, 282L, 283L, 284L, 285L, 
286L, 287L, 288L, 289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 
297L, 298L, 299L, 300L, 301L, 302L, 303L, 304L, 640L, 641L, 642L, 
643L, 644L, 645L, 646L, 647L, 648L, 649L, 650L, 651L, 652L, 653L, 
654L, 655L, 656L, 657L, 658L, 659L, 660L, 661L, 662L, 663L, 664L, 
665L, 666L, 667L, 668L, 669L, 670L, 1005L, 1006L, 1007L, 1008L, 
1009L, 1010L, 1011L, 1012L, 1013L, 1014L, 1015L, 1016L, 1017L, 
1018L, 1019L, 1020L, 1021L, 1022L, 1023L, 1024L, 1025L, 1026L, 
1027L, 1028L, 1029L, 1030L, 1031L, 1032L, 1033L, 1034L, 1035L, 
1370L, 1371L, 1372L, 1373L, 1374L, 1375L, 1376L, 1377L, 1378L, 
1379L, 1380L, 1381L, 1382L, 1383L, 1384L, 1385L, 1386L, 1387L, 
1388L, 1389L, 1390L, 1391L, 1392L, 1393L, 1394L, 1395L, 1396L, 
1397L, 1398L, 1399L, 1400L, 1735L, 1736L, 1737L, 1738L, 1739L, 
1740L, 1741L, 1742L, 1743L, 1744L, 1745L, 1746L, 1747L, 1748L, 
1749L, 1750L, 1751L, 1752L, 1753L, 1754L, 1755L, 1756L, 1757L, 
1758L, 1759L, 1760L, 1761L, 1762L, 1763L, 1764L, 1765L, 2101L, 
2102L, 2103L, 2104L, 2105L, 2106L, 2107L, 2108L, 2109L, 2110L, 
2111L, 2112L, 2113L, 2114L, 2115L, 2116L, 2117L, 2118L, 2119L, 
2120L, 2121L, 2122L, 2123L, 2124L, 2125L, 2126L, 2127L, 2128L, 
2129L, 2130L, 2131L, 2466L, 2467L, 2468L, 2469L, 2470L, 2471L, 
2472L, 2473L, 2474L, 2475L, 2476L, 2477L, 2478L, 2479L, 2480L, 
2481L, 2482L, 2483L, 2484L, 2485L, 2486L, 2487L, 2488L, 2489L, 
2490L, 2491L, 2492L, 2493L, 2494L, 2495L, 2496L, 2831L, 2832L, 
2833L, 2834L, 2835L, 2836L, 2837L, 2838L, 2839L, 2840L, 2841L, 
2842L, 2843L, 2844L, 2845L, 2846L, 2847L, 2848L, 2849L, 2850L, 
2851L, 2852L, 2853L, 2854L, 2855L, 2856L, 2857L, 2858L, 2859L, 
2860L, 2861L, 3196L, 3197L, 3198L, 3199L, 3200L, 3201L, 3202L, 
3203L, 3204L, 3205L, 3206L, 3207L, 3208L, 3209L, 3210L, 3211L, 
3212L, 3213L, 3214L, 3215L, 3216L, 3217L, 3218L, 3219L, 3220L, 
3221L, 3222L, 3223L, 3224L, 3225L, 3226L, 3562L, 3563L, 3564L, 
3565L, 3566L, 3567L, 3568L, 3569L, 3570L, 3571L, 3572L, 3573L, 
3574L, 3575L, 3576L, 3577L, 3578L, 3579L, 3580L, 3581L, 3582L, 
3583L, 3584L, 3585L, 3586L, 3587L, 3588L, 3589L, 3590L, 3591L, 
3592L, 3927L, 3928L, 3929L, 3930L, 3931L, 3932L, 3933L, 3934L, 
3935L, 3936L, 3937L, 3938L, 3939L, 3940L, 3941L, 3942L, 3943L, 
3944L, 3945L, 3946L, 3947L, 3948L, 3949L, 3950L, 3951L, 3952L, 
3953L, 3954L, 3955L, 3956L, 3957L, 4292L, 4293L, 4294L, 4295L, 
4296L, 4297L, 4298L, 4299L, 4300L, 4301L, 4302L, 4303L, 4304L, 
4305L, 4306L, 4307L, 4308L, 4309L, 4310L, 4311L, 4312L, 4313L, 
4314L, 4315L, 4316L, 4317L, 4318L, 4319L, 4320L, 4321L, 4322L
), class = "data.frame")

我想做的是

[1]得到超过长期月度第95百分位数的天数。

2] 绘制持续时间的直方图（即连续事件的数量，所以计数与持续时间的关系）。

3]绘制强度直方图（即出现频率与降雨量值的关系图

我有什么到目前为止。

代码：

thresh<-quantile(dat$RR,0.95,na.rm=T)
extreme<-dat[which(dat$RR>=thresh),]
hist(extreme$RR)

我可以做[1]和[3]，但我在绘制[2]时遇到了麻烦。我如何获得独特事件的长度并绘制其直方图？

我想统计有多少事件的持续时间是1天，2天的连续持续时间，3天的连续持续时间。然后绘制这个直方图。

Answer 1

我想 rle 就能达到您的要求。但是，您目前没有按月计算分位数，我们可以使用 group_by 从 dplyr 的。

library(dplyr)
dat2 <- dat %>%
  group_by(YY,MM) %>%
  mutate(extreme = RR > quantile(RR,0.95,na.rm=TRUE))
# A tibble: 372 x 5
# Groups:   YY, MM [12]
      YY    MM    DD    RR extreme
   <int> <int> <int> <dbl> <lgl>  
 1  1979    10     1  65.3 TRUE   
 2  1979    10     2   2.6 FALSE  
 3  1979    10     3   3.8 FALSE  
 4  1979    10     4  93.5 TRUE   
 5  1979    10     5   0   FALSE  
 6  1979    10     6   0   FALSE  
 7  1979    10     7   1   FALSE  
 8  1979    10     8   0   FALSE  
 9  1979    10     9   0   FALSE  
10  1979    10    10   0   FALSE  
# … with 362 more rows

现在我们可以使用 rle 以获得事件之间的长度。

result <- rle(dat2$extreme)
result
#Run Length Encoding
#  lengths: int [1:36] 1 2 1 54 2 27 2 16 1 1 ...
#  values : logi [1:36] TRUE FALSE TRUE FALSE TRUE FALSE ...
result$lengths[result$values]
 [1] 1 1 2 2 1 1 1 1 2 2 1 1 2 1 1 2 1 1
hist(result$lengths[result$values],breaks = c(0:5), xlab = "Length of extreme events", main = "")