tobac example: Tracking of precipitation features

This example notebook demonstrates the use of tobac to track precipitation features from isolated deep convective clouds.

The simulation results used in this example were performed as part of the ACPC deep convection intercomparison case study (http://acpcinitiative.org/Docs/ACPC_DCC_Roadmap_171019.pdf) with WRF using the Morrison microphysics scheme.

The data used in this example is downloaded from “zenodo link” automatically as part of the notebooks (This only has to be done once for all the tobac example notebooks).

Import necessary python libraries:

[1]:

### a development hack
### !pip install --upgrade ../../../../tobac/

[2]:

# Import libraries:
import xarray
import numpy as np
import pandas as pd
import os
from six.moves import urllib
from glob import glob

import matplotlib.pyplot as plt
%matplotlib inline

[3]:

# Import tobac itself
import tobac

[4]:

# Disable a few warnings:
import warnings
warnings.filterwarnings('ignore', category=UserWarning, append=True)
warnings.filterwarnings('ignore', category=RuntimeWarning, append=True)
warnings.filterwarnings('ignore', category=FutureWarning, append=True)
warnings.filterwarnings('ignore',category=pd.io.pytables.PerformanceWarning)

Download example data:

Actual download has to be performed only once for all example notebooks!

[5]:

data_out='../'

[6]:

# # Download the data: This only has to be done once for all tobac examples and can take a while
# file_path='https://zenodo.org/record/3195910/files/climate-processes/tobac_example_data-v1.0.1.zip'
# #file_path='http://zenodo..'
# tempfile='temp.zip'
# print('start downloading data')
# request=urllib.request.urlretrieve(file_path,tempfile)
# print('start extracting data')
# shutil.unpack_archive(tempfile,data_out)
# #zf = zipfile.ZipFile(tempfile)
# #zf.extractall(data_out)
# os.remove(tempfile)
# print('data extracted')

Load Data from downloaded file:

[7]:

data_file = os.path.join(data_out,'*','data','Example_input_Precip.nc')
data_file = glob(data_file)[0]

[8]:

Precip=xarray.open_dataset(data_file)['surface_precipitation_average']

[9]:

#display information about the iris cube containing the surface precipitation data:
display(Precip)
Show/Hide data repr Show/Hide attributes
xarray.DataArray
'surface_precipitation_average'
  • time: 47
  • south_north: 198
  • west_east: 198
  • ...
    [1842588 values with dtype=float32]
    • time
      (time)
      datetime64[ns]
      2013-06-19T20:05:00 ... 2013-06-19T23:55:00
      axis :
      T
      standard_name :
      time
      array(['2013-06-19T20:05:00.000000000', '2013-06-19T20:10:00.000000000',
       '2013-06-19T20:15:00.000000000', '2013-06-19T20:20:00.000000000',
       '2013-06-19T20:25:00.000000000', '2013-06-19T20:30:00.000000000',
       '2013-06-19T20:35:00.000000000', '2013-06-19T20:40:00.000000000',
       '2013-06-19T20:45:00.000000000', '2013-06-19T20:50:00.000000000',
       '2013-06-19T20:55:00.000000000', '2013-06-19T21:00:00.000000000',
       '2013-06-19T21:05:00.000000000', '2013-06-19T21:10:00.000000000',
       '2013-06-19T21:15:00.000000000', '2013-06-19T21:20:00.000000000',
       '2013-06-19T21:25:00.000000000', '2013-06-19T21:30:00.000000000',
       '2013-06-19T21:35:00.000000000', '2013-06-19T21:40:00.000000000',
       '2013-06-19T21:45:00.000000000', '2013-06-19T21:50:00.000000000',
       '2013-06-19T21:55:00.000000000', '2013-06-19T22:00:00.000000000',
       '2013-06-19T22:05:00.000000000', '2013-06-19T22:10:00.000000000',
       '2013-06-19T22:15:00.000000000', '2013-06-19T22:20:00.000000000',
       '2013-06-19T22:25:00.000000000', '2013-06-19T22:30:00.000000000',
       '2013-06-19T22:35:00.000000000', '2013-06-19T22:40:00.000000000',
       '2013-06-19T22:45:00.000000000', '2013-06-19T22:50:00.000000000',
       '2013-06-19T22:55:00.000000000', '2013-06-19T23:00:00.000000000',
       '2013-06-19T23:05:00.000000000', '2013-06-19T23:10:00.000000000',
       '2013-06-19T23:15:00.000000000', '2013-06-19T23:20:00.000000000',
       '2013-06-19T23:25:00.000000000', '2013-06-19T23:30:00.000000000',
       '2013-06-19T23:35:00.000000000', '2013-06-19T23:40:00.000000000',
       '2013-06-19T23:45:00.000000000', '2013-06-19T23:50:00.000000000',
       '2013-06-19T23:55:00.000000000'], dtype='datetime64[ns]')
    • south_north
      (south_north)
      int64
      281 282 283 284 ... 475 476 477 478
      units :
      1
      long_name :
      south_north
      array([281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
       295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308,
       309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322,
       323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336,
       337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350,
       351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364,
       365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378,
       379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392,
       393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406,
       407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420,
       421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434,
       435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448,
       449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462,
       463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476,
       477, 478])
    • west_east
      (west_east)
      int64
      281 282 283 284 ... 475 476 477 478
      units :
      1
      long_name :
      west_east
      array([281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
       295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308,
       309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322,
       323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336,
       337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350,
       351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364,
       365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378,
       379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392,
       393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406,
       407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420,
       421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434,
       435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448,
       449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462,
       463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476,
       477, 478])
    • latitude
      (south_north, west_east)
      float32
      ...
      units :
      degrees_north
      standard_name :
      latitude
      FieldType :
      104
      MemoryOrder :
      XY
      description :
      LATITUDE, SOUTH IS NEGATIVE
      stagger :
      array([[29.62032 , 29.620296, 29.620296, ..., 29.615593, 29.615551, 29.615501],
       [29.624874, 29.624874, 29.624859, ..., 29.620167, 29.620113, 29.620071],
       [29.629444, 29.629429, 29.629429, ..., 29.624718, 29.624683, 29.624634],
       ...,
       [30.510818, 30.51081 , 30.51081 , ..., 30.506065, 30.506023, 30.505974],
       [30.515388, 30.51538 , 30.51538 , ..., 30.510628, 30.510586, 30.510536],
       [30.519962, 30.51995 , 30.519936, ..., 30.515198, 30.51514 , 30.515106]],
      dtype=float32)
    • longitude
      (south_north, west_east)
      float32
      ...
      units :
      degrees_east
      standard_name :
      longitude
      FieldType :
      104
      MemoryOrder :
      XY
      description :
      LONGITUDE, WEST IS NEGATIVE
      stagger :
      array([[-94.90857 , -94.90332 , -94.89807 , ..., -93.88428 , -93.87903 ,
        -93.87378 ],
       [-94.90857 , -94.90332 , -94.89807 , ..., -93.88422 , -93.87897 ,
        -93.87372 ],
       [-94.90857 , -94.90332 , -94.89807 , ..., -93.884186, -93.87894 ,
        -93.87366 ],
       ...,
       [-94.907776, -94.902466, -94.897156, ..., -93.874176, -93.868866,
        -93.86359 ],
       [-94.907745, -94.902466, -94.897156, ..., -93.874115, -93.868805,
        -93.863525],
       [-94.907745, -94.902466, -94.897156, ..., -93.874054, -93.868774,
        -93.863464]], dtype=float32)
    • x
      (west_east)
      float64
      ...
      bounds :
      x_bnds
      units :
      m
      standard_name :
      projection_x_coordinate
      long_name :
      x
      array([140750., 141250., 141750., 142250., 142750., 143250., 143750., 144250.,
       144750., 145250., 145750., 146250., 146750., 147250., 147750., 148250.,
       148750., 149250., 149750., 150250., 150750., 151250., 151750., 152250.,
       152750., 153250., 153750., 154250., 154750., 155250., 155750., 156250.,
       156750., 157250., 157750., 158250., 158750., 159250., 159750., 160250.,
       160750., 161250., 161750., 162250., 162750., 163250., 163750., 164250.,
       164750., 165250., 165750., 166250., 166750., 167250., 167750., 168250.,
       168750., 169250., 169750., 170250., 170750., 171250., 171750., 172250.,
       172750., 173250., 173750., 174250., 174750., 175250., 175750., 176250.,
       176750., 177250., 177750., 178250., 178750., 179250., 179750., 180250.,
       180750., 181250., 181750., 182250., 182750., 183250., 183750., 184250.,
       184750., 185250., 185750., 186250., 186750., 187250., 187750., 188250.,
       188750., 189250., 189750., 190250., 190750., 191250., 191750., 192250.,
       192750., 193250., 193750., 194250., 194750., 195250., 195750., 196250.,
       196750., 197250., 197750., 198250., 198750., 199250., 199750., 200250.,
       200750., 201250., 201750., 202250., 202750., 203250., 203750., 204250.,
       204750., 205250., 205750., 206250., 206750., 207250., 207750., 208250.,
       208750., 209250., 209750., 210250., 210750., 211250., 211750., 212250.,
       212750., 213250., 213750., 214250., 214750., 215250., 215750., 216250.,
       216750., 217250., 217750., 218250., 218750., 219250., 219750., 220250.,
       220750., 221250., 221750., 222250., 222750., 223250., 223750., 224250.,
       224750., 225250., 225750., 226250., 226750., 227250., 227750., 228250.,
       228750., 229250., 229750., 230250., 230750., 231250., 231750., 232250.,
       232750., 233250., 233750., 234250., 234750., 235250., 235750., 236250.,
       236750., 237250., 237750., 238250., 238750., 239250.])
    • y
      (south_north)
      float64
      ...
      bounds :
      y_bnds
      units :
      m
      standard_name :
      projection_y_coordinate
      long_name :
      y
      array([140750., 141250., 141750., 142250., 142750., 143250., 143750., 144250.,
       144750., 145250., 145750., 146250., 146750., 147250., 147750., 148250.,
       148750., 149250., 149750., 150250., 150750., 151250., 151750., 152250.,
       152750., 153250., 153750., 154250., 154750., 155250., 155750., 156250.,
       156750., 157250., 157750., 158250., 158750., 159250., 159750., 160250.,
       160750., 161250., 161750., 162250., 162750., 163250., 163750., 164250.,
       164750., 165250., 165750., 166250., 166750., 167250., 167750., 168250.,
       168750., 169250., 169750., 170250., 170750., 171250., 171750., 172250.,
       172750., 173250., 173750., 174250., 174750., 175250., 175750., 176250.,
       176750., 177250., 177750., 178250., 178750., 179250., 179750., 180250.,
       180750., 181250., 181750., 182250., 182750., 183250., 183750., 184250.,
       184750., 185250., 185750., 186250., 186750., 187250., 187750., 188250.,
       188750., 189250., 189750., 190250., 190750., 191250., 191750., 192250.,
       192750., 193250., 193750., 194250., 194750., 195250., 195750., 196250.,
       196750., 197250., 197750., 198250., 198750., 199250., 199750., 200250.,
       200750., 201250., 201750., 202250., 202750., 203250., 203750., 204250.,
       204750., 205250., 205750., 206250., 206750., 207250., 207750., 208250.,
       208750., 209250., 209750., 210250., 210750., 211250., 211750., 212250.,
       212750., 213250., 213750., 214250., 214750., 215250., 215750., 216250.,
       216750., 217250., 217750., 218250., 218750., 219250., 219750., 220250.,
       220750., 221250., 221750., 222250., 222750., 223250., 223750., 224250.,
       224750., 225250., 225750., 226250., 226750., 227250., 227750., 228250.,
       228750., 229250., 229750., 230250., 230750., 231250., 231750., 232250.,
       232750., 233250., 233750., 234250., 234750., 235250., 235750., 236250.,
       236750., 237250., 237750., 238250., 238750., 239250.])
    • x_0
      (west_east)
      int64
      ...
      units :
      1
      long_name :
      x
      array([281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
       295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308,
       309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322,
       323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336,
       337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350,
       351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364,
       365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378,
       379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392,
       393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406,
       407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420,
       421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434,
       435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448,
       449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462,
       463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476,
       477, 478])
    • y_0
      (south_north)
      int64
      ...
      units :
      1
      long_name :
      y
      array([281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
       295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308,
       309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322,
       323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336,
       337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350,
       351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364,
       365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378,
       379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392,
       393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406,
       407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420,
       421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434,
       435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448,
       449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462,
       463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476,
       477, 478])
  • long_name :
    surface_precipitation_average
    units :
    mm h-1
[10]:

#Set up directory to save output and plots:
savedir='Save'
if not os.path.exists(savedir):
    os.makedirs(savedir)
plot_dir="Plot"
if not os.path.exists(plot_dir):
    os.makedirs(plot_dir)

Feature detection:

Feature detection is perfomed based on surface precipitation field and a range of thresholds

[11]:

# Dictionary containing keyword options (could also be directly given to the function)
parameters_features={}
parameters_features['position_threshold']='weighted_diff'
parameters_features['sigma_threshold']=0.5
parameters_features['min_num']=3
parameters_features['min_distance']=0
parameters_features['sigma_threshold']=1
parameters_features['threshold']=[1,2,3,4,5,10,15] #mm/h
parameters_features['n_erosion_threshold']=0
parameters_features['n_min_threshold']=3

[12]:

# get temporal and spation resolution of the data
dxy,dt=tobac.utils.get_spacings(Precip)

[13]:

# Feature detection based on based on surface precipitation field and a range of thresholds
print('starting feature detection based on multiple thresholds')
Features=tobac.themes.tobac_v1.feature_detection_multithreshold(Precip,dxy,**parameters_features)
print('feature detection done')
Features.to_netcdf(os.path.join(savedir,'Features.nc'))
print('features saved')

starting feature detection based on multiple thresholds
      frame  idx      hdim_1      hdim_2  num  threshold_value  feature  \
0         0    1   50.065727  139.857477    9                1        1
1         0   15  120.527119  172.500325    4                1        2
2         0   18  126.779273  145.368401   15                1        3
3         0   34  111.611369  155.452030    4                2        4
4         0   35  111.765231  164.938866    8                2        5
...     ...  ...         ...         ...  ...              ...      ...
1124     46   90  163.334480   35.049366   47               15     1125
1125     46   91  177.119093    1.938903   50               15     1126
1126     46   92  183.889436  100.054108   36               15     1127
1127     46   93  196.870749  177.405664   10               15     1128
1128     46   94  196.936190  191.649040    4               15     1129

                     time              timestr  south_north   west_east  \
0     2013-06-19 20:05:00  2013-06-19 20:05:00   331.065727  420.857477
1     2013-06-19 20:05:00  2013-06-19 20:05:00   401.527119  453.500325
2     2013-06-19 20:05:00  2013-06-19 20:05:00   407.779273  426.368401
3     2013-06-19 20:05:00  2013-06-19 20:05:00   392.611369  436.452030
4     2013-06-19 20:05:00  2013-06-19 20:05:00   392.765231  445.938866
...                   ...                  ...          ...         ...
1124  2013-06-19 23:55:00  2013-06-19 23:55:00   444.334480  316.049366
1125  2013-06-19 23:55:00  2013-06-19 23:55:00   458.119093  282.938903
1126  2013-06-19 23:55:00  2013-06-19 23:55:00   464.889436  381.054108
1127  2013-06-19 23:55:00  2013-06-19 23:55:00   477.870749  458.405664
1128  2013-06-19 23:55:00  2013-06-19 23:55:00   477.936190  472.649040

      projection_y_coordinate           y              latitude  \
0               165782.863285  331.065727   [29.84636174574229]
1               201013.559414  401.527119   [30.16692908466767]
2               204139.636582  407.779273  [30.196498834397495]
3               196555.684682  392.611369  [30.126870992779423]
4               196632.615461  392.765231  [30.127221395688906]
...                       ...         ...                   ...
1124            222417.240247  444.334480   [30.36594369270744]
1125            229309.546339  458.119093   [30.42915134198937]
1126            232694.717873  464.889436   [30.45864828495059]
1127            239185.374437  477.870749  [30.515366411726458]
1128            239218.094905  477.936190  [30.515049777191315]

                 longitude  projection_x_coordinate           x
0     [-94.17201509872564]            210678.738492  420.857477
1     [-93.99689187482306]            227000.162468  453.500325
2     [-94.13995972549196]            213434.200454  426.368401
3     [-94.08731650871061]            218476.015240  436.452030
4     [-94.03722567369418]            223219.433218  445.938866
...                    ...                      ...         ...
1124    [-94.722384409394]            158274.683059  316.049366
1125  [-94.89756987871436]            141719.451486  282.938903
1126   [-94.3777372958404]            190777.054179  381.054108
1127  [-93.96733386588102]            229452.832088  458.405664
1128  [-93.89182112542963]            236574.520064  472.649040

[1129 rows x 17 columns]
['time', 'south_north', 'west_east', 'latitude', 'longitude', 'x', 'y', 'x_0', 'y_0']
feature detection done
features saved

Segmentation:

Segmentation is performed based on a watershedding and a threshold value:

[14]:

# Dictionary containing keyword arguments for segmentation step:
parameters_segmentation={}
parameters_segmentation['method']='watershed'
parameters_segmentation['threshold']=1  # mm/h mixing ratio

[15]:

# Perform Segmentation and save resulting mask to NetCDF file:
print('Starting segmentation based on surface precipitation')
Mask,Features_Precip=tobac.themes.tobac_v1.segmentation(Features,Precip,dxy,**parameters_segmentation)
print('segmentation based on surface precipitation performed, start saving results to files')
Mask.to_netcdf(os.path.join(savedir,'Mask_Segmentation_precip.nc'))
Features_Precip.to_netcdf(os.path.join(savedir,'Features_Precip.nc'))
print('segmentation surface precipitation performed and saved')

Starting segmentation based on surface precipitation
<xarray.DataArray 'surface_precipitation_average' (time: 47, south_north: 198, west_east: 198)>
array([[[0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00],
        [0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00],
        ...,
        [0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00],
        [0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00]],

       [[0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00],
        [0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00],
        ...,
        [0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00],
        [0.000000e+00, 0.000000e+00, ..., 0.000000e+00, 0.000000e+00]],

       ...,

       [[1.162095e-03, 1.237040e-03, ..., 0.000000e+00, 0.000000e+00],
        [1.077846e-03, 1.167705e-03, ..., 0.000000e+00, 0.000000e+00],
        ...,
        [0.000000e+00, 0.000000e+00, ..., 1.475261e-01, 7.602954e-02],
        [0.000000e+00, 0.000000e+00, ..., 1.065946e-01, 4.400021e-02]],

       [[3.334880e-05, 2.312288e-05, ..., 0.000000e+00, 0.000000e+00],
        [1.528859e-05, 8.571893e-06, ..., 0.000000e+00, 0.000000e+00],
        ...,
        [6.988572e-03, 1.184124e-03, ..., 1.278359e-01, 2.074599e-02],
        [3.475464e-04, 2.722412e-05, ..., 1.691269e-01, 1.051712e-02]]],
      dtype=float32)
Coordinates:
  * time         (time) datetime64[ns] 2013-06-19T20:05:00 ... 2013-06-19T23:55:00
  * south_north  (south_north) int64 281 282 283 284 285 ... 474 475 476 477 478
  * west_east    (west_east) int64 281 282 283 284 285 ... 474 475 476 477 478
    latitude     (south_north, west_east) float32 29.62032 ... 30.515106
    longitude    (south_north, west_east) float32 -94.90857 ... -93.863464
    x            (west_east) float64 1.408e+05 1.412e+05 ... 2.388e+05 2.392e+05
    y            (south_north) float64 1.408e+05 1.412e+05 ... 2.392e+05
    x_0          (west_east) int64 281 282 283 284 285 ... 474 475 476 477 478
    y_0          (south_north) int64 281 282 283 284 285 ... 474 475 476 477 478
Attributes:
    long_name:  surface_precipitation_average
    units:      mm h-1

/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,
/home/senf/TROPOS/tmp/tobac-dev-2020-07-09/test-env/lib/python3.7/site-packages/skimage/morphology/_deprecated.py:5: skimage_deprecation: Function ``watershed`` is deprecated and will be removed in version 0.19. Use ``skimage.segmentation.watershed`` instead.
  def watershed(image, markers=None, connectivity=1, offset=None, mask=None,

segmentation based on surface precipitation performed, start saving results to files
segmentation surface precipitation performed and saved

Trajectory linking:

Trajectory linking is performed using the trackpy library (http://soft-matter.github.io/trackpy). This takes the feature positions determined in the feature detection step into account but does not include information on the shape of the identified objects.

[16]:

# Dictionary containing keyword arguments for the linking step:
parameters_linking={}
parameters_linking['method_linking']='predict'
parameters_linking['adaptive_stop']=0.2
parameters_linking['adaptive_step']=0.95
parameters_linking['extrapolate']=0
parameters_linking['order']=1
parameters_linking['subnetwork_size']=100
parameters_linking['memory']=0
parameters_linking['time_cell_min']=5*60
parameters_linking['method_linking']='predict'
parameters_linking['v_max']=10
parameters_linking['d_min']=2000

[17]:

# Perform trajectory linking using trackpy and save the resulting DataFrame:
Track=tobac.themes.tobac_v1.linking_trackpy(Features,Precip,dt=dt,dxy=dxy,**parameters_linking)
Track.to_netcdf(os.path.join(savedir,'Track.nc'))

Frame 46: 18 trajectories present.

Visualistation:

[18]:

# Set extent for maps plotted in the following cells ( in the form [lon_min,lon_max,lat_min,lat_max])
axis_extent=[-95,-93.8,29.5,30.6]

[19]:

# Plot map with all individual tracks:
import cartopy.crs as ccrs
fig_map,ax_map=plt.subplots(figsize=(10,10),subplot_kw={'projection': ccrs.PlateCarree()})
ax_map=tobac.plot.map_tracks(Track,axis_extent=axis_extent,axes=ax_map)

[20]:

# Create animation showing tracked cells with outline of precipitation features and the and surface precipitation as a background field:
animation_tobac=tobac.plot.animation_mask_field(Track, Features, Precip, Mask,
                                          axis_extent=axis_extent,#figsize=figsize,orientation_colorbar='horizontal',pad_colorbar=0.2,
                                          vmin=0,vmax=60,extend='both',cmap='Blues',
                                          interval=500,figsize=(10,10),
                                          plot_outline=True,plot_marker=True,marker_track='x',plot_number=True,plot_features=True);

[21]:

# Display animation:
from IPython.display import HTML, Image, display
HTML(animation_tobac.to_html5_video())

[21]:

[22]:

# # Save animation to file
# savefile_animation=os.path.join(plot_dir,'Animation.mp4')
# animation_tobac.save(savefile_animation,dpi=200)
# print(f'animation saved to {savefile_animation}')

[23]:

# Lifetimes of tracked features:
fig_lifetime,ax_lifetime=plt.subplots()
tobac.plot.plot_lifetime_histogram_bar(Track,axes=ax_lifetime,bin_edges=np.arange(0,120,10),density=False,width_bar=8)
ax_lifetime.set_xlabel('lifetime (min)')
ax_lifetime.set_ylabel('counts')

[23]:

Text(0, 0.5, 'counts')