使用 R 从 vobjtovarid4 读取 netCDF 文件时出错
Error reading netCDF file from vobjtovarid4 using R
我想使用 R 代码从 netCDF 文件中获取我的气候模型的维度，即经度、纬度和时间变量
tas1 <- ncvar_get(climate_output, 'tas')
dim(tas1)
但是我收到错误
Error in vobjtovarid4(nc, varid, verbose = verbose, allowdimvar = TRUE) :
Variable not found
谁能帮我解决这个问题？谢谢
我访问了您提到的网站，并从该网站成功检索到仅包含 10 metre U wind component 变量的 netCDF 数据集。您可以下载数据here。文件大小约为 28 MB。
然后我在R中打开数据
library(ncdf4)
wind_data <- nc_open('wind_speed.nc')
wind_data
## File wind_speed.nc (NC_FORMAT_64BIT):
##
## 1 variables (excluding dimension variables):
## short u10[longitude,latitude,time]
## scale_factor: 0.000982868773831028
## add_offset: -0.745013529113478
## _FillValue: -32767
## missing_value: -32767
## units: m s**-1
## long_name: 10 metre U wind component
##
## 3 dimensions:
## longitude Size:480
## units: degrees_east
## long_name: longitude
## latitude Size:241
## units: degrees_north
## long_name: latitude
## time Size:124 *** is unlimited ***
## units: hours since 1900-01-01 00:00:00.0
## long_name: time
## calendar: gregorian
您可以使用$dim获取全面的维度数据：
wind_data$dim
## $longitude
## $name
## [1] "longitude"
##
## $len
## [1] 480
##
## $unlim
## [1] FALSE
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $id
## [1] 0
##
## $dimvarid
## $id
## [1] 0
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $list_index
## [1] -1
##
## $isdimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncid4"
##
## $units
## [1] "degrees_east"
##
## $vals
## [1] 0.00 0.75 1.50 2.25 3.00 3.75 4.50 5.25 6.00 6.75
## [11] 7.50 8.25 9.00 9.75 10.50 11.25 12.00 12.75 13.50 14.25
## [21] 15.00 15.75 16.50 17.25 18.00 18.75 19.50 20.25 21.00 21.75
## [31] 22.50 23.25 24.00 24.75 25.50 26.25 27.00 27.75 28.50 29.25
## [41] 30.00 30.75 31.50 32.25 33.00 33.75 34.50 35.25 36.00 36.75
## [51] 37.50 38.25 39.00 39.75 40.50 41.25 42.00 42.75 43.50 44.25
## [61] 45.00 45.75 46.50 47.25 48.00 48.75 49.50 50.25 51.00 51.75
## [71] 52.50 53.25 54.00 54.75 55.50 56.25 57.00 57.75 58.50 59.25
## [81] 60.00 60.75 61.50 62.25 63.00 63.75 64.50 65.25 66.00 66.75
## [91] 67.50 68.25 69.00 69.75 70.50 71.25 72.00 72.75 73.50 74.25
## [101] 75.00 75.75 76.50 77.25 78.00 78.75 79.50 80.25 81.00 81.75
## [111] 82.50 83.25 84.00 84.75 85.50 86.25 87.00 87.75 88.50 89.25
## [121] 90.00 90.75 91.50 92.25 93.00 93.75 94.50 95.25 96.00 96.75
## [131] 97.50 98.25 99.00 99.75 100.50 101.25 102.00 102.75 103.50 104.25
## [141] 105.00 105.75 106.50 107.25 108.00 108.75 109.50 110.25 111.00 111.75
## [151] 112.50 113.25 114.00 114.75 115.50 116.25 117.00 117.75 118.50 119.25
## [161] 120.00 120.75 121.50 122.25 123.00 123.75 124.50 125.25 126.00 126.75
## [171] 127.50 128.25 129.00 129.75 130.50 131.25 132.00 132.75 133.50 134.25
## [181] 135.00 135.75 136.50 137.25 138.00 138.75 139.50 140.25 141.00 141.75
## [191] 142.50 143.25 144.00 144.75 145.50 146.25 147.00 147.75 148.50 149.25
## [201] 150.00 150.75 151.50 152.25 153.00 153.75 154.50 155.25 156.00 156.75
## [211] 157.50 158.25 159.00 159.75 160.50 161.25 162.00 162.75 163.50 164.25
## [221] 165.00 165.75 166.50 167.25 168.00 168.75 169.50 170.25 171.00 171.75
## [231] 172.50 173.25 174.00 174.75 175.50 176.25 177.00 177.75 178.50 179.25
## [241] 180.00 180.75 181.50 182.25 183.00 183.75 184.50 185.25 186.00 186.75
## [251] 187.50 188.25 189.00 189.75 190.50 191.25 192.00 192.75 193.50 194.25
## [261] 195.00 195.75 196.50 197.25 198.00 198.75 199.50 200.25 201.00 201.75
## [271] 202.50 203.25 204.00 204.75 205.50 206.25 207.00 207.75 208.50 209.25
## [281] 210.00 210.75 211.50 212.25 213.00 213.75 214.50 215.25 216.00 216.75
## [291] 217.50 218.25 219.00 219.75 220.50 221.25 222.00 222.75 223.50 224.25
## [301] 225.00 225.75 226.50 227.25 228.00 228.75 229.50 230.25 231.00 231.75
## [311] 232.50 233.25 234.00 234.75 235.50 236.25 237.00 237.75 238.50 239.25
## [321] 240.00 240.75 241.50 242.25 243.00 243.75 244.50 245.25 246.00 246.75
## [331] 247.50 248.25 249.00 249.75 250.50 251.25 252.00 252.75 253.50 254.25
## [341] 255.00 255.75 256.50 257.25 258.00 258.75 259.50 260.25 261.00 261.75
## [351] 262.50 263.25 264.00 264.75 265.50 266.25 267.00 267.75 268.50 269.25
## [361] 270.00 270.75 271.50 272.25 273.00 273.75 274.50 275.25 276.00 276.75
## [371] 277.50 278.25 279.00 279.75 280.50 281.25 282.00 282.75 283.50 284.25
## [381] 285.00 285.75 286.50 287.25 288.00 288.75 289.50 290.25 291.00 291.75
## [391] 292.50 293.25 294.00 294.75 295.50 296.25 297.00 297.75 298.50 299.25
## [401] 300.00 300.75 301.50 302.25 303.00 303.75 304.50 305.25 306.00 306.75
## [411] 307.50 308.25 309.00 309.75 310.50 311.25 312.00 312.75 313.50 314.25
## [421] 315.00 315.75 316.50 317.25 318.00 318.75 319.50 320.25 321.00 321.75
## [431] 322.50 323.25 324.00 324.75 325.50 326.25 327.00 327.75 328.50 329.25
## [441] 330.00 330.75 331.50 332.25 333.00 333.75 334.50 335.25 336.00 336.75
## [451] 337.50 338.25 339.00 339.75 340.50 341.25 342.00 342.75 343.50 344.25
## [461] 345.00 345.75 346.50 347.25 348.00 348.75 349.50 350.25 351.00 351.75
## [471] 352.50 353.25 354.00 354.75 355.50 356.25 357.00 357.75 358.50 359.25
##
## $create_dimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncdim4"
##
## $latitude
## $name
## [1] "latitude"
##
## $len
## [1] 241
##
## $unlim
## [1] FALSE
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $id
## [1] 1
##
## $dimvarid
## $id
## [1] 1
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $list_index
## [1] -1
##
## $isdimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncid4"
##
## $units
## [1] "degrees_north"
##
## $vals
## [1] 90.00 89.25 88.50 87.75 87.00 86.25 85.50 84.75 84.00 83.25
## [11] 82.50 81.75 81.00 80.25 79.50 78.75 78.00 77.25 76.50 75.75
## [21] 75.00 74.25 73.50 72.75 72.00 71.25 70.50 69.75 69.00 68.25
## [31] 67.50 66.75 66.00 65.25 64.50 63.75 63.00 62.25 61.50 60.75
## [41] 60.00 59.25 58.50 57.75 57.00 56.25 55.50 54.75 54.00 53.25
## [51] 52.50 51.75 51.00 50.25 49.50 48.75 48.00 47.25 46.50 45.75
## [61] 45.00 44.25 43.50 42.75 42.00 41.25 40.50 39.75 39.00 38.25
## [71] 37.50 36.75 36.00 35.25 34.50 33.75 33.00 32.25 31.50 30.75
## [81] 30.00 29.25 28.50 27.75 27.00 26.25 25.50 24.75 24.00 23.25
## [91] 22.50 21.75 21.00 20.25 19.50 18.75 18.00 17.25 16.50 15.75
## [101] 15.00 14.25 13.50 12.75 12.00 11.25 10.50 9.75 9.00 8.25
## [111] 7.50 6.75 6.00 5.25 4.50 3.75 3.00 2.25 1.50 0.75
## [121] 0.00 -0.75 -1.50 -2.25 -3.00 -3.75 -4.50 -5.25 -6.00 -6.75
## [131] -7.50 -8.25 -9.00 -9.75 -10.50 -11.25 -12.00 -12.75 -13.50 -14.25
## [141] -15.00 -15.75 -16.50 -17.25 -18.00 -18.75 -19.50 -20.25 -21.00 -21.75
## [151] -22.50 -23.25 -24.00 -24.75 -25.50 -26.25 -27.00 -27.75 -28.50 -29.25
## [161] -30.00 -30.75 -31.50 -32.25 -33.00 -33.75 -34.50 -35.25 -36.00 -36.75
## [171] -37.50 -38.25 -39.00 -39.75 -40.50 -41.25 -42.00 -42.75 -43.50 -44.25
## [181] -45.00 -45.75 -46.50 -47.25 -48.00 -48.75 -49.50 -50.25 -51.00 -51.75
## [191] -52.50 -53.25 -54.00 -54.75 -55.50 -56.25 -57.00 -57.75 -58.50 -59.25
## [201] -60.00 -60.75 -61.50 -62.25 -63.00 -63.75 -64.50 -65.25 -66.00 -66.75
## [211] -67.50 -68.25 -69.00 -69.75 -70.50 -71.25 -72.00 -72.75 -73.50 -74.25
## [221] -75.00 -75.75 -76.50 -77.25 -78.00 -78.75 -79.50 -80.25 -81.00 -81.75
## [231] -82.50 -83.25 -84.00 -84.75 -85.50 -86.25 -87.00 -87.75 -88.50 -89.25
## [241] -90.00
##
## $create_dimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncdim4"
##
## $time
## $name
## [1] "time"
##
## $len
## [1] 124
##
## $unlim
## [1] TRUE
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $id
## [1] 2
##
## $dimvarid
## $id
## [1] 2
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $list_index
## [1] -1
##
## $isdimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncid4"
##
## $units
## [1] "hours since 1900-01-01 00:00:00.0"
##
## $calendar
## [1] "gregorian"
##
## $vals
## [1] 1008078 1008084 1008090 1008102 1008108 1008114 1008126 1008132 1008138
## [10] 1008150 1008156 1008162 1008174 1008180 1008186 1008198 1008204 1008210
## [19] 1008222 1008228 1008234 1008246 1008252 1008258 1008270 1008276 1008282
## [28] 1008294 1008300 1008306 1008318 1008324 1008330 1008342 1008348 1008354
## [37] 1008366 1008372 1008378 1008390 1008396 1008402 1008414 1008420 1008426
## [46] 1008438 1008444 1008450 1008462 1008468 1008474 1008486 1008492 1008498
## [55] 1008510 1008516 1008522 1008534 1008540 1008546 1008558 1008564 1008570
## [64] 1008582 1008588 1008594 1008606 1008612 1008618 1008630 1008636 1008642
## [73] 1008654 1008660 1008666 1008678 1008684 1008690 1008702 1008708 1008714
## [82] 1008726 1008732 1008738 1008750 1008756 1008762 1008774 1008780 1008786
## [91] 1008798 1008804 1008810 1008087 1008111 1008135 1008159 1008183 1008207
## [100] 1008231 1008255 1008279 1008303 1008327 1008351 1008375 1008399 1008423
## [109] 1008447 1008471 1008495 1008519 1008543 1008567 1008591 1008615 1008639
## [118] 1008663 1008687 1008711 1008735 1008759 1008783 1008807
##
## $create_dimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncdim4"
您可以这样使用 ncvar_get(nc, varid) 功能：
wind_get <- ncvar_get(wind_data, wind_data$var[[1]])
wind_get
## , , 1
##
## [,1] [,2] [,3] [,4] [,5]
## [1,] 0.2152493 -10.17858802 -10.50981480 -10.050815080 -9.19277064
## [2,] 0.2152493 -10.17957089 -10.50981480 -10.042952130 -9.19571925
## [3,] 0.2152493 -10.17957089 -10.50981480 -10.036072048 -9.19965072
## [4,] 0.2152493 -10.17957089 -10.50981480 -10.029191967 -9.20358220
## [5,] 0.2152493 -10.17858802 -10.50981480 -10.023294754 -9.20849654
## [6,] 0.2152493 -10.17858802 -10.50981480 -10.017397541 -9.21341088
## [7,] 0.2152493 -10.17858802 -10.50981480 -10.012483198 -9.21930810
然后，您可以使用dim()
获取经度、纬度和时间的大小
dim(wind_get)
## [1] 480 241 124
我想使用 R 代码从 netCDF 文件中获取我的气候模型的维度，即经度、纬度和时间变量
tas1 <- ncvar_get(climate_output, 'tas')
dim(tas1)
但是我收到错误
Error in vobjtovarid4(nc, varid, verbose = verbose, allowdimvar = TRUE) : Variable not found
谁能帮我解决这个问题？谢谢
我访问了您提到的网站，并从该网站成功检索到仅包含 10 metre U wind component 变量的 netCDF 数据集。您可以下载数据here。文件大小约为 28 MB。
然后我在R中打开数据
library(ncdf4)
wind_data <- nc_open('wind_speed.nc')
wind_data
## File wind_speed.nc (NC_FORMAT_64BIT):
##
## 1 variables (excluding dimension variables):
## short u10[longitude,latitude,time]
## scale_factor: 0.000982868773831028
## add_offset: -0.745013529113478
## _FillValue: -32767
## missing_value: -32767
## units: m s**-1
## long_name: 10 metre U wind component
##
## 3 dimensions:
## longitude Size:480
## units: degrees_east
## long_name: longitude
## latitude Size:241
## units: degrees_north
## long_name: latitude
## time Size:124 *** is unlimited ***
## units: hours since 1900-01-01 00:00:00.0
## long_name: time
## calendar: gregorian
您可以使用$dim获取全面的维度数据：
wind_data$dim
## $longitude
## $name
## [1] "longitude"
##
## $len
## [1] 480
##
## $unlim
## [1] FALSE
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $id
## [1] 0
##
## $dimvarid
## $id
## [1] 0
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $list_index
## [1] -1
##
## $isdimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncid4"
##
## $units
## [1] "degrees_east"
##
## $vals
## [1] 0.00 0.75 1.50 2.25 3.00 3.75 4.50 5.25 6.00 6.75
## [11] 7.50 8.25 9.00 9.75 10.50 11.25 12.00 12.75 13.50 14.25
## [21] 15.00 15.75 16.50 17.25 18.00 18.75 19.50 20.25 21.00 21.75
## [31] 22.50 23.25 24.00 24.75 25.50 26.25 27.00 27.75 28.50 29.25
## [41] 30.00 30.75 31.50 32.25 33.00 33.75 34.50 35.25 36.00 36.75
## [51] 37.50 38.25 39.00 39.75 40.50 41.25 42.00 42.75 43.50 44.25
## [61] 45.00 45.75 46.50 47.25 48.00 48.75 49.50 50.25 51.00 51.75
## [71] 52.50 53.25 54.00 54.75 55.50 56.25 57.00 57.75 58.50 59.25
## [81] 60.00 60.75 61.50 62.25 63.00 63.75 64.50 65.25 66.00 66.75
## [91] 67.50 68.25 69.00 69.75 70.50 71.25 72.00 72.75 73.50 74.25
## [101] 75.00 75.75 76.50 77.25 78.00 78.75 79.50 80.25 81.00 81.75
## [111] 82.50 83.25 84.00 84.75 85.50 86.25 87.00 87.75 88.50 89.25
## [121] 90.00 90.75 91.50 92.25 93.00 93.75 94.50 95.25 96.00 96.75
## [131] 97.50 98.25 99.00 99.75 100.50 101.25 102.00 102.75 103.50 104.25
## [141] 105.00 105.75 106.50 107.25 108.00 108.75 109.50 110.25 111.00 111.75
## [151] 112.50 113.25 114.00 114.75 115.50 116.25 117.00 117.75 118.50 119.25
## [161] 120.00 120.75 121.50 122.25 123.00 123.75 124.50 125.25 126.00 126.75
## [171] 127.50 128.25 129.00 129.75 130.50 131.25 132.00 132.75 133.50 134.25
## [181] 135.00 135.75 136.50 137.25 138.00 138.75 139.50 140.25 141.00 141.75
## [191] 142.50 143.25 144.00 144.75 145.50 146.25 147.00 147.75 148.50 149.25
## [201] 150.00 150.75 151.50 152.25 153.00 153.75 154.50 155.25 156.00 156.75
## [211] 157.50 158.25 159.00 159.75 160.50 161.25 162.00 162.75 163.50 164.25
## [221] 165.00 165.75 166.50 167.25 168.00 168.75 169.50 170.25 171.00 171.75
## [231] 172.50 173.25 174.00 174.75 175.50 176.25 177.00 177.75 178.50 179.25
## [241] 180.00 180.75 181.50 182.25 183.00 183.75 184.50 185.25 186.00 186.75
## [251] 187.50 188.25 189.00 189.75 190.50 191.25 192.00 192.75 193.50 194.25
## [261] 195.00 195.75 196.50 197.25 198.00 198.75 199.50 200.25 201.00 201.75
## [271] 202.50 203.25 204.00 204.75 205.50 206.25 207.00 207.75 208.50 209.25
## [281] 210.00 210.75 211.50 212.25 213.00 213.75 214.50 215.25 216.00 216.75
## [291] 217.50 218.25 219.00 219.75 220.50 221.25 222.00 222.75 223.50 224.25
## [301] 225.00 225.75 226.50 227.25 228.00 228.75 229.50 230.25 231.00 231.75
## [311] 232.50 233.25 234.00 234.75 235.50 236.25 237.00 237.75 238.50 239.25
## [321] 240.00 240.75 241.50 242.25 243.00 243.75 244.50 245.25 246.00 246.75
## [331] 247.50 248.25 249.00 249.75 250.50 251.25 252.00 252.75 253.50 254.25
## [341] 255.00 255.75 256.50 257.25 258.00 258.75 259.50 260.25 261.00 261.75
## [351] 262.50 263.25 264.00 264.75 265.50 266.25 267.00 267.75 268.50 269.25
## [361] 270.00 270.75 271.50 272.25 273.00 273.75 274.50 275.25 276.00 276.75
## [371] 277.50 278.25 279.00 279.75 280.50 281.25 282.00 282.75 283.50 284.25
## [381] 285.00 285.75 286.50 287.25 288.00 288.75 289.50 290.25 291.00 291.75
## [391] 292.50 293.25 294.00 294.75 295.50 296.25 297.00 297.75 298.50 299.25
## [401] 300.00 300.75 301.50 302.25 303.00 303.75 304.50 305.25 306.00 306.75
## [411] 307.50 308.25 309.00 309.75 310.50 311.25 312.00 312.75 313.50 314.25
## [421] 315.00 315.75 316.50 317.25 318.00 318.75 319.50 320.25 321.00 321.75
## [431] 322.50 323.25 324.00 324.75 325.50 326.25 327.00 327.75 328.50 329.25
## [441] 330.00 330.75 331.50 332.25 333.00 333.75 334.50 335.25 336.00 336.75
## [451] 337.50 338.25 339.00 339.75 340.50 341.25 342.00 342.75 343.50 344.25
## [461] 345.00 345.75 346.50 347.25 348.00 348.75 349.50 350.25 351.00 351.75
## [471] 352.50 353.25 354.00 354.75 355.50 356.25 357.00 357.75 358.50 359.25
##
## $create_dimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncdim4"
##
## $latitude
## $name
## [1] "latitude"
##
## $len
## [1] 241
##
## $unlim
## [1] FALSE
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $id
## [1] 1
##
## $dimvarid
## $id
## [1] 1
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $list_index
## [1] -1
##
## $isdimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncid4"
##
## $units
## [1] "degrees_north"
##
## $vals
## [1] 90.00 89.25 88.50 87.75 87.00 86.25 85.50 84.75 84.00 83.25
## [11] 82.50 81.75 81.00 80.25 79.50 78.75 78.00 77.25 76.50 75.75
## [21] 75.00 74.25 73.50 72.75 72.00 71.25 70.50 69.75 69.00 68.25
## [31] 67.50 66.75 66.00 65.25 64.50 63.75 63.00 62.25 61.50 60.75
## [41] 60.00 59.25 58.50 57.75 57.00 56.25 55.50 54.75 54.00 53.25
## [51] 52.50 51.75 51.00 50.25 49.50 48.75 48.00 47.25 46.50 45.75
## [61] 45.00 44.25 43.50 42.75 42.00 41.25 40.50 39.75 39.00 38.25
## [71] 37.50 36.75 36.00 35.25 34.50 33.75 33.00 32.25 31.50 30.75
## [81] 30.00 29.25 28.50 27.75 27.00 26.25 25.50 24.75 24.00 23.25
## [91] 22.50 21.75 21.00 20.25 19.50 18.75 18.00 17.25 16.50 15.75
## [101] 15.00 14.25 13.50 12.75 12.00 11.25 10.50 9.75 9.00 8.25
## [111] 7.50 6.75 6.00 5.25 4.50 3.75 3.00 2.25 1.50 0.75
## [121] 0.00 -0.75 -1.50 -2.25 -3.00 -3.75 -4.50 -5.25 -6.00 -6.75
## [131] -7.50 -8.25 -9.00 -9.75 -10.50 -11.25 -12.00 -12.75 -13.50 -14.25
## [141] -15.00 -15.75 -16.50 -17.25 -18.00 -18.75 -19.50 -20.25 -21.00 -21.75
## [151] -22.50 -23.25 -24.00 -24.75 -25.50 -26.25 -27.00 -27.75 -28.50 -29.25
## [161] -30.00 -30.75 -31.50 -32.25 -33.00 -33.75 -34.50 -35.25 -36.00 -36.75
## [171] -37.50 -38.25 -39.00 -39.75 -40.50 -41.25 -42.00 -42.75 -43.50 -44.25
## [181] -45.00 -45.75 -46.50 -47.25 -48.00 -48.75 -49.50 -50.25 -51.00 -51.75
## [191] -52.50 -53.25 -54.00 -54.75 -55.50 -56.25 -57.00 -57.75 -58.50 -59.25
## [201] -60.00 -60.75 -61.50 -62.25 -63.00 -63.75 -64.50 -65.25 -66.00 -66.75
## [211] -67.50 -68.25 -69.00 -69.75 -70.50 -71.25 -72.00 -72.75 -73.50 -74.25
## [221] -75.00 -75.75 -76.50 -77.25 -78.00 -78.75 -79.50 -80.25 -81.00 -81.75
## [231] -82.50 -83.25 -84.00 -84.75 -85.50 -86.25 -87.00 -87.75 -88.50 -89.25
## [241] -90.00
##
## $create_dimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncdim4"
##
## $time
## $name
## [1] "time"
##
## $len
## [1] 124
##
## $unlim
## [1] TRUE
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $id
## [1] 2
##
## $dimvarid
## $id
## [1] 2
##
## $group_index
## [1] 1
##
## $group_id
## [1] 65536
##
## $list_index
## [1] -1
##
## $isdimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncid4"
##
## $units
## [1] "hours since 1900-01-01 00:00:00.0"
##
## $calendar
## [1] "gregorian"
##
## $vals
## [1] 1008078 1008084 1008090 1008102 1008108 1008114 1008126 1008132 1008138
## [10] 1008150 1008156 1008162 1008174 1008180 1008186 1008198 1008204 1008210
## [19] 1008222 1008228 1008234 1008246 1008252 1008258 1008270 1008276 1008282
## [28] 1008294 1008300 1008306 1008318 1008324 1008330 1008342 1008348 1008354
## [37] 1008366 1008372 1008378 1008390 1008396 1008402 1008414 1008420 1008426
## [46] 1008438 1008444 1008450 1008462 1008468 1008474 1008486 1008492 1008498
## [55] 1008510 1008516 1008522 1008534 1008540 1008546 1008558 1008564 1008570
## [64] 1008582 1008588 1008594 1008606 1008612 1008618 1008630 1008636 1008642
## [73] 1008654 1008660 1008666 1008678 1008684 1008690 1008702 1008708 1008714
## [82] 1008726 1008732 1008738 1008750 1008756 1008762 1008774 1008780 1008786
## [91] 1008798 1008804 1008810 1008087 1008111 1008135 1008159 1008183 1008207
## [100] 1008231 1008255 1008279 1008303 1008327 1008351 1008375 1008399 1008423
## [109] 1008447 1008471 1008495 1008519 1008543 1008567 1008591 1008615 1008639
## [118] 1008663 1008687 1008711 1008735 1008759 1008783 1008807
##
## $create_dimvar
## [1] TRUE
##
## attr(,"class")
## [1] "ncdim4"
您可以这样使用 ncvar_get(nc, varid) 功能：
wind_get <- ncvar_get(wind_data, wind_data$var[[1]])
wind_get
## , , 1
##
## [,1] [,2] [,3] [,4] [,5]
## [1,] 0.2152493 -10.17858802 -10.50981480 -10.050815080 -9.19277064
## [2,] 0.2152493 -10.17957089 -10.50981480 -10.042952130 -9.19571925
## [3,] 0.2152493 -10.17957089 -10.50981480 -10.036072048 -9.19965072
## [4,] 0.2152493 -10.17957089 -10.50981480 -10.029191967 -9.20358220
## [5,] 0.2152493 -10.17858802 -10.50981480 -10.023294754 -9.20849654
## [6,] 0.2152493 -10.17858802 -10.50981480 -10.017397541 -9.21341088
## [7,] 0.2152493 -10.17858802 -10.50981480 -10.012483198 -9.21930810
然后，您可以使用dim()
dim(wind_get)
## [1] 480 241 124