Loading TempestExtremes data#
If you are running TempestExtremes, we would recommend outputting your tracks as CSV. However, if you use the default output or want to read output that has been produced in this format then huracanpy can load that.
[1]:
import huracanpy
Basic functionnality#
The tracks can be loaded providing the file path and the tracker=tempestextremes option.
[2]:
# Embedded TempestExtremes example file
filename = huracanpy.example_TE_file
# Load the tracks
huracanpy.load(filename, source="tempestextremes")
[2]:
<xarray.Dataset> Size: 13kB
Dimensions: (record: 210)
Dimensions without coordinates: record
Data variables:
i (record) float64 2kB 605.0 604.0 602.0 ... 237.0 236.0 235.0
j (record) float64 2kB 36.0 37.0 39.0 40.0 ... 45.0 47.0 48.0 48.0
lon (record) float64 2kB 302.5 302.0 301.0 ... 118.5 118.0 117.5
lat (record) float64 2kB 18.0 18.5 19.5 20.0 ... 22.5 23.5 24.0 24.0
feature_0 (record) float64 2kB 1.004e+05 1.002e+05 ... 1.002e+05 1.004e+05
feature_1 (record) float64 2kB 19.19 23.98 22.35 26.91 ... 28.46 29.49 24.0
track_id (record) int64 2kB 0 0 0 0 0 0 0 0 0 0 0 ... 7 7 7 7 7 7 7 7 7 7
time (record) datetime64[ns] 2kB 1999-09-10 ... 1999-10-09T06:00:00xarray.Dataset
- record: 210
- i(record)float64605.0 604.0 602.0 ... 236.0 235.0
array([605., 604., 602., 601., 599., 598., 597., 594., 592., 590., 588., 585., 583., 580., 577., 574., 572., 570., 568., 566., 565., 563., 562., 562., 563., 564., 567., 570., 574., 577., 581., 583., 586., 677., 671., 669., 665., 660., 656., 652., 649., 646., 641., 639., 636., 633., 630., 628., 625., 624., 622., 620., 618., 617., 614., 613., 612., 610., 608., 607., 607., 606., 605., 605., 604., 603., 601., 600., 599., 597., 595., 595., 594., 595., 595., 596., 597., 599., 601., 603., 607., 611., 615., 620., 238., 237., 235., 234., 234., 235., 234., 233., 231., 232., 231., 230., 229., 229., 227., 226., 225., 224., 225., 257., 259., 260., 259., 258., 257., 255., 254., 253., 252., 251., 250., 249., 248., 248., 246., 245., 244., 260., 260., 261., 261., 259., 260., 258., 255., 255., 253., 250., 251., 251., 251., 251., 251., 252., 252., 253., 254., 254., 254., 254., 254., 255., 257., 259., 263., 268., 273., 280., 286., 294., 300., 305., 502., 500., 500., 497., 496., 495., 495., 495., 494., 492., 492., 491., 491., 491., 491., 491., 545., 545., 545., 545., 545., 547., 548., 550., 552., 554., 564., 262., 260., 259., 257., 255., 254., 251., 249., 248., 245., 243., 240., 240., 237., 237., 236., 236., 236., 236., 237., 237., 236., 237., 237., 237., 236., 235.]) - j(record)float6436.0 37.0 39.0 ... 47.0 48.0 48.0
array([36., 37., 39., 40., 41., 42., 43., 45., 45., 45., 46., 46., 47., 47., 48., 48., 49., 50., 51., 52., 54., 56., 59., 61., 64., 67., 71., 76., 81., 84., 87., 89., 90., 21., 25., 26., 26., 27., 29., 30., 30., 31., 31., 32., 33., 33., 33., 34., 35., 35., 35., 35., 36., 36., 36., 37., 38., 39., 40., 40., 42., 43., 44., 46., 47., 48., 49., 51., 53., 54., 55., 56., 58., 60., 62., 65., 69., 72., 77., 81., 84., 89., 93., 97., 37., 37., 38., 38., 39., 41., 40., 41., 41., 43., 43., 43., 43., 44., 45., 45., 46., 47., 47., 52., 52., 54., 54., 58., 59., 60., 59., 60., 60., 60., 59., 60., 61., 62., 63., 64., 65., 41., 40., 40., 40., 39., 39., 42., 44., 46., 47., 49., 48., 49., 48., 48., 49., 49., 49., 50., 51., 52., 53., 54., 56., 58., 60., 64., 69., 74., 79., 85., 89., 93., 95., 97., 33., 33., 33., 34., 34., 35., 37., 39., 42., 44., 45., 46., 47., 48., 49., 49., 51., 52., 52., 52., 53., 53., 54., 54., 53., 51., 61., 35., 36., 36., 37., 36., 37., 37., 37., 38., 37., 37., 38., 38., 37., 38., 38., 39., 39., 40., 41., 42., 44., 45., 45., 47., 48., 48.]) - lon(record)float64302.5 302.0 301.0 ... 118.0 117.5
array([302.5, 302. , 301. , 300.5, 299.5, 299. , 298.5, 297. , 296. , 295. , 294. , 292.5, 291.5, 290. , 288.5, 287. , 286. , 285. , 284. , 283. , 282.5, 281.5, 281. , 281. , 281.5, 282. , 283.5, 285. , 287. , 288.5, 290.5, 291.5, 293. , 338.5, 335.5, 334.5, 332.5, 330. , 328. , 326. , 324.5, 323. , 320.5, 319.5, 318. , 316.5, 315. , 314. , 312.5, 312. , 311. , 310. , 309. , 308.5, 307. , 306.5, 306. , 305. , 304. , 303.5, 303.5, 303. , 302.5, 302.5, 302. , 301.5, 300.5, 300. , 299.5, 298.5, 297.5, 297.5, 297. , 297.5, 297.5, 298. , 298.5, 299.5, 300.5, 301.5, 303.5, 305.5, 307.5, 310. , 119. , 118.5, 117.5, 117. , 117. , 117.5, 117. , 116.5, 115.5, 116. , 115.5, 115. , 114.5, 114.5, 113.5, 113. , 112.5, 112. , 112.5, 128.5, 129.5, 130. , 129.5, 129. , 128.5, 127.5, 127. , 126.5, 126. , 125.5, 125. , 124.5, 124. , 124. , 123. , 122.5, 122. , 130. , 130. , 130.5, 130.5, 129.5, 130. , 129. , 127.5, 127.5, 126.5, 125. , 125.5, 125.5, 125.5, 125.5, 125.5, 126. , 126. , 126.5, 127. , 127. , 127. , 127. , 127. , 127.5, 128.5, 129.5, 131.5, 134. , 136.5, 140. , 143. , 147. , 150. , 152.5, 251. , 250. , 250. , 248.5, 248. , 247.5, 247.5, 247.5, 247. , 246. , 246. , 245.5, 245.5, 245.5, 245.5, 245.5, 272.5, 272.5, 272.5, 272.5, 272.5, 273.5, 274. , 275. , 276. , 277. , 282. , 131. , 130. , 129.5, 128.5, 127.5, 127. , 125.5, 124.5, 124. , 122.5, 121.5, 120. , 120. , 118.5, 118.5, 118. , 118. , 118. , 118. , 118.5, 118.5, 118. , 118.5, 118.5, 118.5, 118. , 117.5]) - lat(record)float6418.0 18.5 19.5 ... 23.5 24.0 24.0
array([18. , 18.5, 19.5, 20. , 20.5, 21. , 21.5, 22.5, 22.5, 22.5, 23. , 23. , 23.5, 23.5, 24. , 24. , 24.5, 25. , 25.5, 26. , 27. , 28. , 29.5, 30.5, 32. , 33.5, 35.5, 38. , 40.5, 42. , 43.5, 44.5, 45. , 10.5, 12.5, 13. , 13. , 13.5, 14.5, 15. , 15. , 15.5, 15.5, 16. , 16.5, 16.5, 16.5, 17. , 17.5, 17.5, 17.5, 17.5, 18. , 18. , 18. , 18.5, 19. , 19.5, 20. , 20. , 21. , 21.5, 22. , 23. , 23.5, 24. , 24.5, 25.5, 26.5, 27. , 27.5, 28. , 29. , 30. , 31. , 32.5, 34.5, 36. , 38.5, 40.5, 42. , 44.5, 46.5, 48.5, 18.5, 18.5, 19. , 19. , 19.5, 20.5, 20. , 20.5, 20.5, 21.5, 21.5, 21.5, 21.5, 22. , 22.5, 22.5, 23. , 23.5, 23.5, 26. , 26. , 27. , 27. , 29. , 29.5, 30. , 29.5, 30. , 30. , 30. , 29.5, 30. , 30.5, 31. , 31.5, 32. , 32.5, 20.5, 20. , 20. , 20. , 19.5, 19.5, 21. , 22. , 23. , 23.5, 24.5, 24. , 24.5, 24. , 24. , 24.5, 24.5, 24.5, 25. , 25.5, 26. , 26.5, 27. , 28. , 29. , 30. , 32. , 34.5, 37. , 39.5, 42.5, 44.5, 46.5, 47.5, 48.5, 16.5, 16.5, 16.5, 17. , 17. , 17.5, 18.5, 19.5, 21. , 22. , 22.5, 23. , 23.5, 24. , 24.5, 24.5, 25.5, 26. , 26. , 26. , 26.5, 26.5, 27. , 27. , 26.5, 25.5, 30.5, 17.5, 18. , 18. , 18.5, 18. , 18.5, 18.5, 18.5, 19. , 18.5, 18.5, 19. , 19. , 18.5, 19. , 19. , 19.5, 19.5, 20. , 20.5, 21. , 22. , 22.5, 22.5, 23.5, 24. , 24. ]) - feature_0(record)float641.004e+05 1.002e+05 ... 1.004e+05
array([100390.6 , 100208.9 , 100261.1 , 100048.2 , 99948.3 , 99610.6 , 99471.6 , 99216.8 , 99096.5 , 99056.1 , 99066.5 , 98718. , 98677.2 , 98373. , 98430.3 , 97954. , 97668.9 , 97571.2 , 97283.9 , 97242.9 , 97257.6 , 97331.3 , 97453.4 , 97676.3 , 97823.4 , 97930.9 , 98259.2 , 98389.8 , 98552.7 , 98782.9 , 98821.8 , 98856.2 , 99155.3 , 100624.5 , 100705.8 , 100448.9 , 100724.9 , 100525.5 , 100503.5 , 100401.8 , 100553.2 , 100316. , 100420.4 , 100216.1 , 100240.2 , 100118. , 100227.7 , 100078.8 , 100108.6 , 99942.3 , 99990. , 99841.4 , 99628.8 , 99415.7 , 99271.2 , 98864.9 , 99069.3 , 98945.5 , 99014.3 , 98728.1 , 98856.2 , 98732.7 , 98720.3 , 98408. , 98239.5 , 98182.6 , 98377.6 , 98181.9 , 98003.01, 97629.4 , 97911.34, 97625.07, 97869.94, 97538.01, 97563.91, 97597.15, 97560.04, 97666.98, 98111.55, 97944.37, 98209.01, 98095.3 , 98502.95, 98330.41, 99867.1 , 99797.8 , 99711.4 , 99660.2 , 99625.8 , 99650. , 99486. , 99507. , 99438.4 , 99435.3 , 99113.2 , 99267.6 , 99232.1 , 99171.3 , 99129.6 , 99362.2 , 99695.2 , 99930.7 , 100058.1 , 100280.4 , 100265.6 , 100185.3 , 100246.7 , 100209.9 , 100178.2 , 100053.3 , 100233.3 , 100093.4 , 100124.1 , 100005.5 , 100091.9 , 100097.5 , 100270.3 , 100184.3 , 100344. , 100274.4 , 100405.1 , 100285.4 , 100306.6 , 100157.3 , 100116.4 , 99898.9 , 99958.5 , 99999.6 , 99938. , 99809. , 100002.8 , 99847. , 99700.3 , 99498.4 , 99636.3 , 99269.91, 99172.58, 99019.04, 99021.48, 98834.6 , 98627.38, 98536.16, 98532.83, 98416.23, 98586.25, 98561.41, 98773.48, 98643.54, 98686.69, 98469.89, 98712.34, 98529.96, 98155.89, 97915. , 97876.4 , 97772.12, 100425.1 , 100237.9 , 100371.8 , 100304.2 , 100025.4 , 100203.2 , 100089.3 , 100287.9 , 100086.5 , 100364.1 , 100362.7 , 100580.1 , 100430.5 , 100790.3 , 100761.4 , 100860.6 , 100517.4 , 100516.5 , 100533.2 , 100376.4 , 100468.2 , 100351.4 , 100348.9 , 100227.4 , 100222.6 , 99955.27, 100086. , 100720.3 , 100740.5 , 100471.4 , 100578.7 , 100484. , 100534.8 , 100325.4 , 100408.2 , 100346.1 , 100304.8 , 100128.6 , 100245.9 , 100109.6 , 100039.6 , 99831.35, 99823.93, 99647.07, 99560.75, 99266.83, 99288.91, 99259.18, 99448.27, 99574.18, 99747.53, 99932. , 100229. , 100374.2 ]) - feature_1(record)float6419.19 23.98 22.35 ... 29.49 24.0
array([19.18985, 23.98492, 22.35224, 26.90826, 27.50533, 31.18364, 32.1996 , 34.60081, 36.4915 , 29.48343, 31.20796, 31.97615, 35.46924, 36.09361, 36.85016, 42.51232, 42.04105, 40.12502, 43.06615, 43.7938 , 39.23645, 37.196 , 37.63824, 33.99412, 37.23064, 34.92445, 34.94477, 30.33454, 26.8233 , 29.50756, 24.02386, 24.95165, 19.56871, 16.7392 , 18.59002, 16.00923, 21.33407, 26.22552, 31.18109, 26.15887, 24.28046, 23.72366, 24.00429, 21.72011, 19.76423, 23.42978, 23.32998, 20.51053, 22.8318 , 25.24761, 24.53733, 24.22697, 26.00603, 28.10243, 30.00279, 35.90297, 34.32436, 32.74491, 36.2213 , 37.98975, 33.16766, 33.68 , 35.5895 , 35.98536, 35.68467, 37.05834, 34.73214, 35.1641 , 35.17509, 35.34668, 30.66424, 33.90965, 28.46963, 33.26746, 34.34739, 35.47733, 32.00605, 35.49304, 33.12074, 32.75121, 34.88742, 32.85145, 24.99283, 28.38784, 13.65836, 16.77113, 16.66007, 17.6269 , 16.81011, 17.50349, 21.22919, 17.42041, 21.41555, 23.87017, 24.50488, 18.87269, 23.18603, 21.85361, 21.45043, 14.14297, 15.21913, 10.60578, 10.92136, 19.20937, 14.53198, 15.40195, 15.39481, 16.86433, 19.75441, 19.09442, 17.80792, 16.434 , 16.78942, 19.96662, 18.84933, 19.40402, 16.94845, 17.52589, 18.08043, 18.60233, 15.069 , 21.25313, 17.20279, 15.59046, 17.5232 , 19.3918 , 16.35783, 17.69504, 14.2623 , 16.55783, 14.87412, 15.86024, 16.01548, 19.73091, 17.37797, 21.07894, 21.71711, 23.04605, 24.34716, 25.28706, 26.34804, 28.2776 , 28.97628, 29.50313, 32.56705, 30.07445, 31.47043, 28.00058, 24.58562, 29.94864, 26.41283, 27.70418, 22.7516 , 23.70507, 23.26904, 25.6965 , 14.76586, 15.97 , 15.37615, 15.26979, 16.06854, 16.23434, 13.89363, 17.38725, 15.97975, 16.8503 , 14.56097, 18.05339, 15.79011, 14.56496, 12.56123, 14.75282, 17.61386, 16.58701, 17.36127, 17.06537, 16.70218, 16.42355, 17.93953, 14.25376, 14.60214, 19.08302, 19.57972, 15.22646, 15.47471, 14.9519 , 14.63627, 16.7234 , 16.19164, 20.06562, 17.52813, 19.75764, 20.53392, 21.00083, 21.14198, 21.94942, 19.44231, 21.75446, 22.53184, 23.13234, 24.70052, 26.01181, 27.35748, 27.2337 , 26.60604, 26.10235, 25.44478, 28.46053, 29.48693, 24.00239]) - track_id(record)int640 0 0 0 0 0 0 0 ... 7 7 7 7 7 7 7 7
- cf_role :
- trajectory_id
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]) - time(record)datetime64[ns]1999-09-10 ... 1999-10-09T06:00:00
array(['1999-09-10T00:00:00.000000000', '1999-09-10T06:00:00.000000000', '1999-09-10T12:00:00.000000000', '1999-09-10T18:00:00.000000000', '1999-09-11T00:00:00.000000000', '1999-09-11T06:00:00.000000000', '1999-09-11T12:00:00.000000000', '1999-09-11T18:00:00.000000000', '1999-09-12T00:00:00.000000000', '1999-09-12T06:00:00.000000000', '1999-09-12T12:00:00.000000000', '1999-09-12T18:00:00.000000000', '1999-09-13T00:00:00.000000000', '1999-09-13T06:00:00.000000000', '1999-09-13T12:00:00.000000000', '1999-09-13T18:00:00.000000000', '1999-09-14T00:00:00.000000000', '1999-09-14T06:00:00.000000000', '1999-09-14T12:00:00.000000000', '1999-09-14T18:00:00.000000000', '1999-09-15T00:00:00.000000000', '1999-09-15T06:00:00.000000000', '1999-09-15T12:00:00.000000000', '1999-09-15T18:00:00.000000000', '1999-09-16T00:00:00.000000000', '1999-09-16T06:00:00.000000000', '1999-09-16T12:00:00.000000000', '1999-09-16T18:00:00.000000000', '1999-09-17T00:00:00.000000000', '1999-09-17T06:00:00.000000000', '1999-09-17T12:00:00.000000000', '1999-09-17T18:00:00.000000000', '1999-09-18T00:00:00.000000000', '1999-09-11T06:00:00.000000000', '1999-09-11T12:00:00.000000000', '1999-09-11T18:00:00.000000000', '1999-09-12T00:00:00.000000000', '1999-09-12T06:00:00.000000000', '1999-09-12T12:00:00.000000000', '1999-09-12T18:00:00.000000000', ... '1999-09-19T06:00:00.000000000', '1999-09-19T12:00:00.000000000', '1999-09-19T18:00:00.000000000', '1999-09-20T00:00:00.000000000', '1999-09-20T06:00:00.000000000', '1999-09-20T12:00:00.000000000', '1999-09-20T18:00:00.000000000', '1999-09-21T00:00:00.000000000', '1999-09-21T06:00:00.000000000', '1999-09-21T12:00:00.000000000', '1999-09-21T18:00:00.000000000', '1999-10-02T18:00:00.000000000', '1999-10-03T00:00:00.000000000', '1999-10-03T06:00:00.000000000', '1999-10-03T12:00:00.000000000', '1999-10-03T18:00:00.000000000', '1999-10-04T00:00:00.000000000', '1999-10-04T06:00:00.000000000', '1999-10-04T12:00:00.000000000', '1999-10-04T18:00:00.000000000', '1999-10-05T00:00:00.000000000', '1999-10-05T06:00:00.000000000', '1999-10-05T12:00:00.000000000', '1999-10-05T18:00:00.000000000', '1999-10-06T00:00:00.000000000', '1999-10-06T06:00:00.000000000', '1999-10-06T12:00:00.000000000', '1999-10-06T18:00:00.000000000', '1999-10-07T00:00:00.000000000', '1999-10-07T06:00:00.000000000', '1999-10-07T12:00:00.000000000', '1999-10-07T18:00:00.000000000', '1999-10-08T00:00:00.000000000', '1999-10-08T06:00:00.000000000', '1999-10-08T12:00:00.000000000', '1999-10-08T18:00:00.000000000', '1999-10-09T00:00:00.000000000', '1999-10-09T06:00:00.000000000'], dtype='datetime64[ns]')
Dealing with metadata#
TempestExtremes files can include more data than just time, longitude and latitude. However, the ASCII format does not embed metadata, you need to obtain the name of the variables that were appended to the file from the person that produced it. Then, you can give them to the load function to be used as variable names, as illustrated below.
[3]:
# Load the tracks with metadata
huracanpy.load(
filename,
source="tempestextremes",
variable_names=[
"mslp",
"vmax",
],
)
[3]:
<xarray.Dataset> Size: 13kB
Dimensions: (record: 210)
Dimensions without coordinates: record
Data variables:
i (record) float64 2kB 605.0 604.0 602.0 601.0 ... 237.0 236.0 235.0
j (record) float64 2kB 36.0 37.0 39.0 40.0 ... 45.0 47.0 48.0 48.0
lon (record) float64 2kB 302.5 302.0 301.0 300.5 ... 118.5 118.0 117.5
lat (record) float64 2kB 18.0 18.5 19.5 20.0 ... 22.5 23.5 24.0 24.0
mslp (record) float64 2kB 1.004e+05 1.002e+05 ... 1.002e+05 1.004e+05
vmax (record) float64 2kB 19.19 23.98 22.35 26.91 ... 28.46 29.49 24.0
track_id (record) int64 2kB 0 0 0 0 0 0 0 0 0 0 0 ... 7 7 7 7 7 7 7 7 7 7 7
time (record) datetime64[ns] 2kB 1999-09-10 ... 1999-10-09T06:00:00xarray.Dataset
- record: 210
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