diff --git "a/data_read.ipynb" "b/data_read.ipynb" --- "a/data_read.ipynb" +++ "b/data_read.ipynb" @@ -22,7 +22,9 @@ "from pathlib import Path\n", "import torch\n", "import xarray as xr\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "\n", + "import dataset" ] }, { @@ -57,11 +59,11 @@ { "data": { "text/plain": [ - "[PosixPath('igra/igra_full_0.25deg_19790101.nc'),\n", - " PosixPath('igra/igra_full_0.25deg_19790102.nc'),\n", - " PosixPath('igra/igra_full_0.25deg_19790103.nc'),\n", - " PosixPath('igra/igra_full_0.25deg_19790104.nc'),\n", - " PosixPath('igra/igra_full_0.25deg_19790105.nc')]" + "[PosixPath('igra/igra_full_0.25deg_20110101.nc'),\n", + " PosixPath('igra/igra_full_0.25deg_20110102.nc'),\n", + " PosixPath('igra/igra_full_0.25deg_20110103.nc'),\n", + " PosixPath('igra/igra_full_0.25deg_20110104.nc'),\n", + " PosixPath('igra/igra_full_0.25deg_20110105.nc')]" ] }, "execution_count": 3, @@ -464,27 +466,27 @@ "Coordinates:\n", " * lat (lat) float64 -89.88 -89.62 -89.38 ... 89.62 89.88\n", " * lon (lon) float64 -179.9 -179.6 -179.4 ... 179.6 179.9\n", - " * time (time) datetime64[ns] 1979-01-01 ... 1979-01-01T...\n", + " * time (time) datetime64[ns] 2011-01-01 ... 2011-01-01T...\n", "Data variables:\n", " air_temperature (lat, lon, time) float64 ...\n", " relative_humidity (lat, lon, time) float64 ...\n", " wind_speed (lat, lon, time) float64 ...\n", " geopotential_height (lat, lon, time) float64 ...\n", - " air_dewpoint_depression (lat, lon, time) float64 ...
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875])
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875])
array(['1979-01-01T00:00:00.000000000', '1979-01-01T06:00:00.000000000',\n", - " '1979-01-01T12:00:00.000000000', '1979-01-01T18:00:00.000000000'],\n", - " dtype='datetime64[ns]')
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", + " air_dewpoint_depression (lat, lon, time) float64 ...
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875])
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875])
array(['2011-01-01T00:00:00.000000000', '2011-01-01T06:00:00.000000000',\n", + " '2011-01-01T12:00:00.000000000', '2011-01-01T18:00:00.000000000'],\n", + " dtype='datetime64[ns]')
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", " -87.875, -87.625,\n", " ...\n", " 87.625, 87.875, 88.125, 88.375, 88.625, 88.875, 89.125, 89.375,\n", " 89.625, 89.875],\n", - " dtype='float64', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", + " dtype='float64', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", " -178.125, -177.875, -177.625,\n", " ...\n", " 177.625, 177.875, 178.125, 178.375, 178.625, 178.875, 179.125,\n", " 179.375, 179.625, 179.875],\n", - " dtype='float64', name='lon', length=1440))
PandasIndex(DatetimeIndex(['1979-01-01 00:00:00', '1979-01-01 06:00:00',\n", - " '1979-01-01 12:00:00', '1979-01-01 18:00:00'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
PandasIndex(DatetimeIndex(['2011-01-01 00:00:00', '2011-01-01 06:00:00',\n", + " '2011-01-01 12:00:00', '2011-01-01 18:00:00'],\n", + " dtype='datetime64[ns]', name='time', freq=None))
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875],\n", - " dtype=float32)
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875],\n", - " dtype=float32)
[1 values with dtype=datetime64[ns]]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", + " license: The CM SAF data are owned by EUMETSAT and are...
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875],\n", + " dtype=float32)
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875],\n", + " dtype=float32)
[1 values with dtype=datetime64[ns]]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", " -87.875, -87.625,\n", " ...\n", " 87.625, 87.875, 88.125, 88.375, 88.625, 88.875, 89.125, 89.375,\n", " 89.625, 89.875],\n", - " dtype='float32', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", + " dtype='float32', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", " -178.125, -177.875, -177.625,\n", " ...\n", " 177.625, 177.875, 178.125, 178.375, 178.625, 178.875, 179.125,\n", " 179.375, 179.625, 179.875],\n", - " dtype='float32', name='lon', length=1440))
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875],\n", - " dtype=float32)
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875],\n", - " dtype=float32)
[1 values with dtype=datetime64[ns]]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", + " license: The CM SAF data are owned by EUMETSAT and are...
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875],\n", + " dtype=float32)
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875],\n", + " dtype=float32)
[1 values with dtype=datetime64[ns]]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
[1036800 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", " -87.875, -87.625,\n", " ...\n", " 87.625, 87.875, 88.125, 88.375, 88.625, 88.875, 89.125, 89.375,\n", " 89.625, 89.875],\n", - " dtype='float32', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", + " dtype='float32', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", " -178.125, -177.875, -177.625,\n", " ...\n", " 177.625, 177.875, 178.125, 178.375, 178.625, 178.875, 179.125,\n", " 179.375, 179.625, 179.875],\n", - " dtype='float32', name='lon', length=1440))
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875],\n", - " dtype=float32)
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875],\n", - " dtype=float32)
[1 values with dtype=datetime64[ns]]
array([[100., 96., 96., ..., 100., 96., 100.],\n", - " [100., 100., 100., ..., 100., 100., 100.],\n", - " [100., 100., 100., ..., 100., 100., 100.],\n", + " license: The CM SAF data are owned by EUMETSAT and are...
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875],\n", + " dtype=float32)
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875],\n", + " dtype=float32)
[1 values with dtype=datetime64[ns]]
array([[ 9., 10., 10., ..., 11., 10., 10.],\n", + " [16., 14., 15., ..., 16., 14., 14.],\n", + " [ 2., 2., 2., ..., 1., 0., 0.],\n", " ...,\n", - " [ 75., 83., 95., ..., 100., 98., 80.],\n", - " [ 91., 89., 89., ..., 89., 89., 96.],\n", - " [ 85., 80., 71., ..., 88., 86., 86.]])
array([[251.400004, 251.400004, 251.500004, ..., 251.400004, 251.500004,\n", - " 251.500004],\n", - " [249.900004, 249.800004, 250.000004, ..., 250.200004, 249.900004,\n", - " 249.900004],\n", - " [249.500004, 249.200004, 249.300004, ..., 249.500004, 249.600004,\n", - " 249.500004],\n", + " [33., 31., 31., ..., 27., 26., 29.],\n", + " [71., 66., 66., ..., 56., 64., 70.],\n", + " [52., 49., 49., ..., 51., 51., 52.]])
array([[244.800004, 244.800004, 244.800004, ..., 244.800004, 244.800004,\n", + " 244.800004],\n", + " [244.500004, 244.500004, 244.300004, ..., 244.500004, 244.400004,\n", + " 244.400004],\n", + " [244.000004, 244.000004, 244.000004, ..., 243.900004, nan,\n", + " nan],\n", " ...,\n", - " [222.800003, 228.100003, 224.600003, ..., 223.200003, 217.700003,\n", - " 218.100003],\n", - " [225.400003, 228.400003, 228.600003, ..., 220.600003, 223.600003,\n", - " 226.200003],\n", - " [230.800003, 230.100003, 230.900003, ..., 229.100003, 229.100003,\n", - " 230.200003]])
array([[1279., 1275., 1261., ..., 1271., 1253., 1262.],\n", - " [1397., 1439., 1411., ..., 1345., 1386., 1386.],\n", - " [1389., 1437., 1419., ..., 1379., 1370., 1387.],\n", + " [228.200003, 227.800003, 228.600003, ..., 225.900003, 226.500003,\n", + " 227.000003],\n", + " [226.900003, 226.500003, 227.500003, ..., 227.100003, 227.100003,\n", + " 227.900003],\n", + " [231.500003, 230.600003, 230.700003, ..., 230.900003, 230.600003,\n", + " 231.300003]])
array([[ 424., 442., 442., ..., 428., 416., 435.],\n", + " [ 389., 357., 384., ..., 380., 397., 397.],\n", + " [ 408., 408., 408., ..., 515., nan, nan],\n", " ...,\n", - " [7219., 6427., 7020., ..., 7068., 7853., 7825.],\n", - " [6334., 6038., 6050., ..., 7090., 6598., 6245.],\n", - " [5349., 5606., 5797., ..., 5567., 5679., 5485.]])
array([[585.300009, 585.700009, 586.800009, ..., 585.700009, 587.200009,\n", - " 586.600009],\n", - " [572.800009, 569.500008, 571.700009, ..., 577.100009, 573.800009,\n", - " 573.800009],\n", - " [568.300008, 564.800008, 566.200008, ..., 568.900008, 569.700008,\n", - " 568.300008],\n", + " [5447., 5531., 5439., ..., 5972., 5819., 5714.],\n", + " [5808., 5886., 5700., ..., 5792., 5782., 5619.],\n", + " [4968., 5121., 5087., ..., 5081., 5139., 5009.]])
array([[646.60001 , 645.00001 , 645.10001 , ..., 646.30001 , 647.50001 ,\n", + " 645.70001 ],\n", + " [648.60001 , 651.40001 , 648.70001 , ..., 649.50001 , 648.10001 ,\n", + " 648.10001 ],\n", + " [640.30001 , 640.30001 , 640.30001 , ..., 629.300009, nan,\n", + " nan],\n", " ...,\n", - " [375.800006, 430.000006, 394.900006, ..., 386.300006, 335.400005,\n", - " 338.200005],\n", - " [433.700006, 452.000007, 451.400007, ..., 388.400006, 418.600006,\n", - " 440.800007],\n", - " [507.300008, 489.300007, 475.200007, ..., 493.700007, 487.700007,\n", - " 498.900007]])
array([[ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [1.793, nan, nan, ..., 1.793, 1.793, 1.793],\n", + " [481.700007, 476.300007, 482.000007, ..., 447.600007, 457.400007,\n", + " 463.900007],\n", + " [456.700007, 452.100007, 466.200007, ..., 459.100007, 458.800007,\n", + " 470.100007],\n", + " [516.500008, 503.500008, 507.300008, ..., 507.600008, 504.100008,\n", + " 513.400008]])
array([[0.249, 0.24 , 0.221, ..., 0.314, 0.238, 0.228],\n", + " [0.262, 0.294, 0.281, ..., 0.344, 0.293, 0.293],\n", + " [0.012, 0.012, 0.012, ..., 0.007, nan, nan],\n", " ...,\n", " [ nan, nan, nan, ..., nan, nan, nan],\n", " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan]])
array([[ nan, nan, nan, ..., nan, nan,\n", - " nan],\n", - " [ nan, nan, nan, ..., nan, nan,\n", - " nan],\n", - " [149.999997, nan, nan, ..., 149.999997, 149.999997,\n", - " 149.999997],\n", - " ...,\n", - " [ nan, nan, nan, ..., nan, nan,\n", - " nan],\n", - " [ nan, nan, nan, ..., nan, nan,\n", - " nan],\n", - " [ nan, nan, nan, ..., nan, nan,\n", - " nan]])
array([[ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [1.928e-05, nan, nan, ..., 1.928e-05, 1.928e-05, 1.928e-05],\n", - " ...,\n", - " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan]])
array([[0.018, 0.018, 0.017, ..., 0.027, 0.028, 0.023],\n", - " [0.363, 0.332, 0.021, ..., 0.412, 0.41 , 0.41 ],\n", - " [0.612, 0.534, 0.456, ..., 0.066, 0.348, 0.589],\n", + " [ nan, nan, nan, ..., nan, nan, nan]])
array([[10.35, 9.92, 9.13, ..., 11.47, 9.97, 9.58],\n", + " [11.31, 12.71, 12.11, ..., 13.56, 12.67, 12.67],\n", + " [ 0.46, 0.46, 0.46, ..., 0.3 , nan, nan],\n", " ...,\n", " [ nan, nan, nan, ..., nan, nan, nan],\n", " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan]])
array([[ 1.69 , 1.68 , 1.55 , ..., 2.18 , 2.19 , 1.94 ],\n", - " [23.249999, 21.34 , 1.64 , ..., 26.439999, 26.179999, 26.179999],\n", - " [37.209999, 35.289999, 29.739999, ..., 4.2 , 21. , 35.789999],\n", + " [ nan, nan, nan, ..., nan, nan, nan]])
array([[3.436e-05, 3.562e-05, 3.599e-05, ..., 3.695e-05, 3.461e-05, 3.373e-05],\n", + " [3.122e-05, 3.033e-05, 3.143e-05, ..., 3.139e-05, 3.036e-05, 3.036e-05],\n", + " [4.223e-05, 4.223e-05, 4.223e-05, ..., 3.707e-05, nan, nan],\n", " ...,\n", " [ nan, nan, nan, ..., nan, nan, nan],\n", " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan]])
array([[1.344e-05, 1.341e-05, 1.371e-05, ..., 1.483e-05, 1.546e-05, 1.474e-05],\n", - " [1.753e-05, 1.833e-05, 1.879e-05, ..., 1.853e-05, 1.856e-05, 1.856e-05],\n", - " [1.988e-05, 1.861e-05, 1.998e-05, ..., 2.003e-05, 1.944e-05, 1.998e-05],\n", + " [ nan, nan, nan, ..., nan, nan, nan]])
array([[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", " ...,\n", - " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan],\n", - " [ nan, nan, nan, ..., nan, nan, nan]])
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]])
array([[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]])
array([[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]])
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", " -87.875, -87.625,\n", " ...\n", " 87.625, 87.875, 88.125, 88.375, 88.625, 88.875, 89.125, 89.375,\n", " 89.625, 89.875],\n", - " dtype='float32', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", + " dtype='float32', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", " -178.125, -177.875, -177.625,\n", " ...\n", " 177.625, 177.875, 178.125, 178.375, 178.625, 178.875, 179.125,\n", " 179.375, 179.625, 179.875],\n", - " dtype='float32', name='lon', length=1440))
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875])
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875])
array(['1979-01-01T00:00:00.000000000', '1979-01-01T06:00:00.000000000',\n", - " '1979-01-01T12:00:00.000000000', '1979-01-01T18:00:00.000000000'],\n", - " dtype='datetime64[ns]')
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", + " air_dewpoint_depression (lat, lon, time) float64 ...
array([-89.875, -89.625, -89.375, ..., 89.375, 89.625, 89.875])
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875])
array(['2011-01-01T00:00:00.000000000', '2011-01-01T06:00:00.000000000',\n", + " '2011-01-01T12:00:00.000000000', '2011-01-01T18:00:00.000000000'],\n", + " dtype='datetime64[ns]')
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
[4147200 values with dtype=float64]
PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n", " -87.875, -87.625,\n", " ...\n", " 87.625, 87.875, 88.125, 88.375, 88.625, 88.875, 89.125, 89.375,\n", " 89.625, 89.875],\n", - " dtype='float64', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", + " dtype='float64', name='lat', length=720))
PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n", " -178.125, -177.875, -177.625,\n", " ...\n", " 177.625, 177.875, 178.125, 178.375, 178.625, 178.875, 179.125,\n", " 179.375, 179.625, 179.875],\n", - " dtype='float64', name='lon', length=1440))
PandasIndex(DatetimeIndex(['1979-01-01 00:00:00', '1979-01-01 06:00:00',\n", - " '1979-01-01 12:00:00', '1979-01-01 18:00:00'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
PandasIndex(DatetimeIndex(['2011-01-01 00:00:00', '2011-01-01 06:00:00',\n", + " '2011-01-01 12:00:00', '2011-01-01 18:00:00'],\n", + " dtype='datetime64[ns]', name='time', freq=None))
array(['cfc', 'ctt', 'cth', 'ctp', 'iwp', 'cot_ice', 'cre_ice', 'lwp',\n", - " 'cot_liq', 'cre_liq'], dtype='<U7')
[10 values with dtype=float64]
[10 values with dtype=float64]
PandasIndex(Index(['cfc', 'ctt', 'cth', 'ctp', 'iwp', 'cot_ice', 'cre_ice', 'lwp',\n", + " sigma (param) float64 ...
array(['cfc', 'ctt', 'cth', 'ctp', 'iwp', 'cot_ice', 'cre_ice', 'lwp',\n", + " 'cot_liq', 'cre_liq'], dtype='<U7')
[10 values with dtype=float64]
[10 values with dtype=float64]
PandasIndex(Index(['cfc', 'ctt', 'cth', 'ctp', 'iwp', 'cot_ice', 'cre_ice', 'lwp',\n", " 'cot_liq', 'cre_liq'],\n", - " dtype='object', name='param'))