diff --git a/FrevaFutures/FuturesExample.ipynb b/FrevaFutures/FuturesExample.ipynb index 9d87337..2f53448 100644 --- a/FrevaFutures/FuturesExample.ipynb +++ b/FrevaFutures/FuturesExample.ipynb @@ -18,6 +18,9 @@ "execution_count": 15, "id": "864ce272-5d89-4719-a55a-6e5d8d011863", "metadata": { + "slideshow": { + "slide_type": "skip" + }, "tags": [] }, "outputs": [], @@ -1589,18 +1592,11 @@ { "cell_type": "markdown", "id": "1c8c690e-4bfd-402d-8ac6-c68c73286a4b", - "metadata": {}, - "source": [ - "## How can we check if the data is physically present?\n", - "\n", - "Sometimes it might be useful to check if we can use the data straight away or the data has to be re-created.\n", - "The databrowser doesn't get informed about the deletion of data automoatically. For example if we delete the data again:" - ] - }, - { - "cell_type": "markdown", - "id": "b3f0f75a-d088-48e1-ba11-df84a0550c2c", - "metadata": {}, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, "source": [ "## How can we check if the data is physically present?\n", "\n", @@ -1613,6 +1609,9 @@ "execution_count": 24, "id": "fb1ec4d0-1dfb-42ab-8551-50e7d5669947", "metadata": { + "slideshow": { + "slide_type": "-" + }, "tags": [] }, "outputs": [], @@ -1623,7 +1622,11 @@ { "cell_type": "markdown", "id": "faa8f2a2-6b0a-4d0e-8fa2-70cd39809890", - "metadata": {}, + "metadata": { + "slideshow": { + "slide_type": "-" + } + }, "source": [ "the databrowser still shows the location on disk although the data doesn't exist anymore:" ] @@ -1633,6 +1636,9 @@ "execution_count": 25, "id": "e07a664b-f8c9-4cdc-b65e-0d22e195cc64", "metadata": { + "slideshow": { + "slide_type": "-" + }, "tags": [] }, "outputs": [ @@ -1654,7 +1660,11 @@ { "cell_type": "markdown", "id": "0e258208-e931-4cd1-981d-53c7989c76f7", - "metadata": {}, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, "source": [ "We can use the `check_future` method to check for the existence for futures. Every dataset that doesn't exsit anymore will be deleted from the databrowser and replaced by the special `future://` url, indicating that this dataset doesn't exist but can be recreated. We can use a `key=value` pair search facet like for the databrowser method to sub select only certain datasets:" ] @@ -1664,6 +1674,9 @@ "execution_count": 27, "id": "c1898a81-6ea2-4bf3-82b3-bfdef6a66419", "metadata": { + "slideshow": { + "slide_type": "-" + }, "tags": [] }, "outputs": [], @@ -1674,7 +1687,11 @@ { "cell_type": "markdown", "id": "d354f092-13f4-45f8-89fa-09375b35990d", - "metadata": {}, + "metadata": { + "slideshow": { + "slide_type": "-" + } + }, "source": [ "Let's search for the data again:" ] @@ -1684,6 +1701,9 @@ "execution_count": 28, "id": "6cc598f8-37ec-4da7-bd65-e5532f849847", "metadata": { + "slideshow": { + "slide_type": "-" + }, "tags": [] }, "outputs": [ diff --git a/FrevaFutures/index.slides.html b/FrevaFutures/index.slides.html index 493e315..2239647 100644 --- a/FrevaFutures/index.slides.html +++ b/FrevaFutures/index.slides.html @@ -98,6 +98,3262 @@ .highlight .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ .highlight .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ + @@ -14678,7 +17934,7 @@
import freva
import xarray as xr
-from freva._futures import Futures
hist_id = 3085 # We can get this ID using the freva.history command
-_ = Futures.register_future_from_history_id(hist_id)
+_ = freva.register_future_from_history_id(hist_id)
list(freva.databrowser(variable="tx90petccdi"))
@@ -14753,9 +18008,11 @@ Let's search for the data
-
+
+
+
- Out[23]:
+ Out[18]:
@@ -14770,7 +18027,7 @@ Let's search for the data
@@ -14786,7 +18043,7 @@ The data do
-In [25]:
+In [19]:
dset = xr.open_mfdataset(
@@ -14808,7 +18065,9 @@ The data do
+
+
@@ -14818,17 +18077,19 @@ The data do
-
+
+
+
@@ -14840,9 +18101,11 @@ The data do
-
+
+
+
- Out[25]:
+ Out[19]:
@@ -15211,75 +18474,68 @@ The data do
fill: currentColor;
}
<xarray.Dataset>
-Dimensions: (time: 3, bnds: 2, lon: 192, lat: 96)
+Dimensions: (time: 3, lon: 192, lat: 96, bnds: 2)
Coordinates:
* time (time) datetime64[ns] 1990-07-02 1991-07-02 1992-07-01T12:00:00
- * lon (lon) float64 -179.1 -177.2 -175.3 -173.4 ... 175.3 177.2 179.1
- * lat (lat) float64 -89.06 -87.19 -85.31 -83.44 ... 85.31 87.19 89.06
- height float64 ...
+ * lon (lon) float64 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1
+ * lat (lat) float64 -88.57 -86.72 -84.86 -83.0 ... 84.86 86.72 88.57
Dimensions without coordinates: bnds
Data variables:
- time_bnds (time, bnds) datetime64[ns] dask.array<chunksize=(3, 2), meta=np.ndarray>
+ time_bnds (time, bnds) float64 dask.array<chunksize=(3, 2), meta=np.ndarray>
tx90pETCCDI (time, lat, lon) float32 dask.array<chunksize=(3, 96, 192), meta=np.ndarray>
-Attributes: (12/36)
+Attributes: (12/13)
CDI: Climate Data Interface version 2.0.5 (https://m...
Conventions: CF-1.4
- source: MPI-ESM-LR 2011; URL: http://svn.zmaw.de/svn/co...
institution: Max Planck Institute for Meteorology
- institute_id: MPI-M
- experiment_id: historical
- ... ...
+ ETCCDI_institution: UNSW Australia & FUB Berlin
+ ETCCDI_institution_id: UNSW-CCRC,FUB-IfM
ETCCDI_software: climdex.pcic
- ETCCDI_software_version: 1.1.11
+ ... ...
+ contact: k204230
frequency: yr
- creation_date: 2023-09-11T19:57:50Z
- title: ETCCDI indices computed on MPI-ESM-LR model out...
- CDO: Climate Data Operators version 2.0.5 (https://m...
xarray.Dataset- time: 3
- bnds: 2
- lon: 192
- lat: 96
- time(time)datetime64[ns]1990-07-02 ... 1992-07-01T12:00:00
- standard_name :
- time
- long_name :
- time
- bounds :
- time_bnds
- axis :
- T
array(['1990-07-02T00:00:00.000000000', '1991-07-02T00:00:00.000000000',
- '1992-07-01T12:00:00.000000000'], dtype='datetime64[ns]')
- lon(lon)float64-179.1 -177.2 ... 177.2 179.1
- standard_name :
- longitude
- long_name :
- longitude
- units :
- degrees_east
- axis :
- X
array([-179.0625, -177.1875, -175.3125, -173.4375, -171.5625, -169.6875,
- -167.8125, -165.9375, -164.0625, -162.1875, -160.3125, -158.4375,
- -156.5625, -154.6875, -152.8125, -150.9375, -149.0625, -147.1875,
- -145.3125, -143.4375, -141.5625, -139.6875, -137.8125, -135.9375,
- -134.0625, -132.1875, -130.3125, -128.4375, -126.5625, -124.6875,
- -122.8125, -120.9375, -119.0625, -117.1875, -115.3125, -113.4375,
- -111.5625, -109.6875, -107.8125, -105.9375, -104.0625, -102.1875,
- -100.3125, -98.4375, -96.5625, -94.6875, -92.8125, -90.9375,
- -89.0625, -87.1875, -85.3125, -83.4375, -81.5625, -79.6875,
- -77.8125, -75.9375, -74.0625, -72.1875, -70.3125, -68.4375,
- -66.5625, -64.6875, -62.8125, -60.9375, -59.0625, -57.1875,
- -55.3125, -53.4375, -51.5625, -49.6875, -47.8125, -45.9375,
- -44.0625, -42.1875, -40.3125, -38.4375, -36.5625, -34.6875,
- -32.8125, -30.9375, -29.0625, -27.1875, -25.3125, -23.4375,
- -21.5625, -19.6875, -17.8125, -15.9375, -14.0625, -12.1875,
- -10.3125, -8.4375, -6.5625, -4.6875, -2.8125, -0.9375,
- 0.9375, 2.8125, 4.6875, 6.5625, 8.4375, 10.3125,
- 12.1875, 14.0625, 15.9375, 17.8125, 19.6875, 21.5625,
- 23.4375, 25.3125, 27.1875, 29.0625, 30.9375, 32.8125,
- 34.6875, 36.5625, 38.4375, 40.3125, 42.1875, 44.0625,
- 45.9375, 47.8125, 49.6875, 51.5625, 53.4375, 55.3125,
- 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,
- 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125,
- 79.6875, 81.5625, 83.4375, 85.3125, 87.1875, 89.0625,
- 90.9375, 92.8125, 94.6875, 96.5625, 98.4375, 100.3125,
- 102.1875, 104.0625, 105.9375, 107.8125, 109.6875, 111.5625,
- 113.4375, 115.3125, 117.1875, 119.0625, 120.9375, 122.8125,
- 124.6875, 126.5625, 128.4375, 130.3125, 132.1875, 134.0625,
- 135.9375, 137.8125, 139.6875, 141.5625, 143.4375, 145.3125,
- 147.1875, 149.0625, 150.9375, 152.8125, 154.6875, 156.5625,
- 158.4375, 160.3125, 162.1875, 164.0625, 165.9375, 167.8125,
- 169.6875, 171.5625, 173.4375, 175.3125, 177.1875, 179.0625])
- lat(lat)float64-89.06 -87.19 ... 87.19 89.06
- standard_name :
- latitude
- long_name :
- latitude
- units :
- degrees_north
- axis :
- Y
array([-89.0625, -87.1875, -85.3125, -83.4375, -81.5625, -79.6875, -77.8125,
- -75.9375, -74.0625, -72.1875, -70.3125, -68.4375, -66.5625, -64.6875,
- -62.8125, -60.9375, -59.0625, -57.1875, -55.3125, -53.4375, -51.5625,
- -49.6875, -47.8125, -45.9375, -44.0625, -42.1875, -40.3125, -38.4375,
- -36.5625, -34.6875, -32.8125, -30.9375, -29.0625, -27.1875, -25.3125,
- -23.4375, -21.5625, -19.6875, -17.8125, -15.9375, -14.0625, -12.1875,
- -10.3125, -8.4375, -6.5625, -4.6875, -2.8125, -0.9375, 0.9375,
- 2.8125, 4.6875, 6.5625, 8.4375, 10.3125, 12.1875, 14.0625,
- 15.9375, 17.8125, 19.6875, 21.5625, 23.4375, 25.3125, 27.1875,
- 29.0625, 30.9375, 32.8125, 34.6875, 36.5625, 38.4375, 40.3125,
- 42.1875, 44.0625, 45.9375, 47.8125, 49.6875, 51.5625, 53.4375,
- 55.3125, 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,
- 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125, 79.6875,
- 81.5625, 83.4375, 85.3125, 87.1875, 89.0625])
- height()float64...
- standard_name :
- height
- long_name :
- height
- units :
- m
- positive :
- up
- axis :
- Z
[1 values with dtype=float64]
- time_bnds(time, bnds)datetime64[ns]dask.array<chunksize=(3, 2), meta=np.ndarray>
+ creation_date: 2023-09-28T11:10:27Z
+ title: ETCCDI indices computed on 0
+ history: Thu Sep 28 13:11:53 2023: cdo -s setlevel,0 cac...
+ CDO: Climate Data Operators version 2.0.5 (https://m...xarray.Dataset- time: 3
- lon: 192
- lat: 96
- bnds: 2
- time(time)datetime64[ns]1990-07-02 ... 1992-07-01T12:00:00
- standard_name :
- time
- long_name :
- time
- axis :
- T
array(['1990-07-02T00:00:00.000000000', '1991-07-02T00:00:00.000000000',
+ '1992-07-01T12:00:00.000000000'], dtype='datetime64[ns]')
- lon(lon)float640.0 1.875 3.75 ... 356.2 358.1
- standard_name :
- longitude
- long_name :
- lon
- units :
- degrees_east
- axis :
- X
array([ 0. , 1.875, 3.75 , 5.625, 7.5 , 9.375, 11.25 , 13.125,
+ 15. , 16.875, 18.75 , 20.625, 22.5 , 24.375, 26.25 , 28.125,
+ 30. , 31.875, 33.75 , 35.625, 37.5 , 39.375, 41.25 , 43.125,
+ 45. , 46.875, 48.75 , 50.625, 52.5 , 54.375, 56.25 , 58.125,
+ 60. , 61.875, 63.75 , 65.625, 67.5 , 69.375, 71.25 , 73.125,
+ 75. , 76.875, 78.75 , 80.625, 82.5 , 84.375, 86.25 , 88.125,
+ 90. , 91.875, 93.75 , 95.625, 97.5 , 99.375, 101.25 , 103.125,
+ 105. , 106.875, 108.75 , 110.625, 112.5 , 114.375, 116.25 , 118.125,
+ 120. , 121.875, 123.75 , 125.625, 127.5 , 129.375, 131.25 , 133.125,
+ 135. , 136.875, 138.75 , 140.625, 142.5 , 144.375, 146.25 , 148.125,
+ 150. , 151.875, 153.75 , 155.625, 157.5 , 159.375, 161.25 , 163.125,
+ 165. , 166.875, 168.75 , 170.625, 172.5 , 174.375, 176.25 , 178.125,
+ 180. , 181.875, 183.75 , 185.625, 187.5 , 189.375, 191.25 , 193.125,
+ 195. , 196.875, 198.75 , 200.625, 202.5 , 204.375, 206.25 , 208.125,
+ 210. , 211.875, 213.75 , 215.625, 217.5 , 219.375, 221.25 , 223.125,
+ 225. , 226.875, 228.75 , 230.625, 232.5 , 234.375, 236.25 , 238.125,
+ 240. , 241.875, 243.75 , 245.625, 247.5 , 249.375, 251.25 , 253.125,
+ 255. , 256.875, 258.75 , 260.625, 262.5 , 264.375, 266.25 , 268.125,
+ 270. , 271.875, 273.75 , 275.625, 277.5 , 279.375, 281.25 , 283.125,
+ 285. , 286.875, 288.75 , 290.625, 292.5 , 294.375, 296.25 , 298.125,
+ 300. , 301.875, 303.75 , 305.625, 307.5 , 309.375, 311.25 , 313.125,
+ 315. , 316.875, 318.75 , 320.625, 322.5 , 324.375, 326.25 , 328.125,
+ 330. , 331.875, 333.75 , 335.625, 337.5 , 339.375, 341.25 , 343.125,
+ 345. , 346.875, 348.75 , 350.625, 352.5 , 354.375, 356.25 , 358.125])
- lat(lat)float64-88.57 -86.72 ... 86.72 88.57
- standard_name :
- latitude
- long_name :
- lat
- units :
- degrees_north
- axis :
- Y
array([-88.572166, -86.722534, -84.861969, -82.99894 , -81.134979, -79.270561,
+ -77.405891, -75.541061, -73.676132, -71.811134, -69.946083, -68.080994,
+ -66.215874, -64.350731, -62.485569, -60.620396, -58.755211, -56.890015,
+ -55.024807, -53.159595, -51.294376, -49.429153, -47.563927, -45.698692,
+ -43.833458, -41.96822 , -40.102978, -38.237736, -36.37249 , -34.507244,
+ -32.641994, -30.776745, -28.911493, -27.04624 , -25.180986, -23.315731,
+ -21.450476, -19.585218, -17.719961, -15.854704, -13.989446, -12.124187,
+ -10.258928, -8.393669, -6.528409, -4.66315 , -2.79789 , -0.93263 ,
+ 0.93263 , 2.79789 , 4.66315 , 6.528409, 8.393669, 10.258928,
+ 12.124187, 13.989446, 15.854704, 17.719961, 19.585218, 21.450476,
+ 23.315731, 25.180986, 27.04624 , 28.911493, 30.776745, 32.641994,
+ 34.507244, 36.37249 , 38.237736, 40.102978, 41.96822 , 43.833458,
+ 45.698692, 47.563927, 49.429153, 51.294376, 53.159595, 55.024807,
+ 56.890011, 58.755211, 60.620396, 62.485569, 64.350731, 66.215874,
+ 68.080994, 69.946083, 71.811134, 73.676132, 75.541061, 77.405891,
+ 79.270561, 81.134979, 82.99894 , 84.861969, 86.722534, 88.572166])
- time_bnds(time, bnds)float64dask.array<chunksize=(3, 2), meta=np.ndarray>
@@ -15309,7 +18565,7 @@ The data do
Data type
- datetime64[ns] numpy.ndarray
+ float64 numpy.ndarray
@@ -15334,7 +18590,7 @@ The data do
-
- tx90pETCCDI(time, lat, lon)float32dask.array<chunksize=(3, 96, 192), meta=np.ndarray>
- long_name :
- Percentage of Days when Daily Maximum Temperature is Above the 90th Percentile
- units :
- %
- cell_methods :
- time: maximum
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MPI-ESM-LR_historical_r0i0p0.nc areacella: areacella_fx_MPI-ESM-LR_historical_r0i0p0.nc
- history :
- Created by climdex.pcic 1.1.11 on Mon Sep 11 21:57:50 2023
- base_period :
- 1991-1991
+
- tx90pETCCDI(time, lat, lon)float32dask.array<chunksize=(3, 96, 192), meta=np.ndarray>
- long_name :
- Percentage of Days when Daily Maximum Temperature is Above the 90th Percentile
- units :
- %
- CDI_grid_type :
- gaussian
- CDI_grid_num_LPE :
- 48
- history :
- Created by climdex.pcic 1.1.11 on Thu Sep 28 13:10:27 2023
- base_period :
- 1991-1991
@@ -15412,32 +18668,46 @@ The data do
-
- timePandasIndex
PandasIndex(DatetimeIndex(['1990-07-02 00:00:00', '1991-07-02 00:00:00',
+
- timePandasIndex
PandasIndex(DatetimeIndex(['1990-07-02 00:00:00', '1991-07-02 00:00:00',
'1992-07-01 12:00:00'],
- dtype='datetime64[ns]', name='time', freq=None))
- lonPandasIndex
PandasIndex(Index([-179.0625, -177.1875, -175.3125, -173.4375, -171.5625, -169.6875,
- -167.8125, -165.9375, -164.0625, -162.1875,
+ dtype='datetime64[ns]', name='time', freq=None))
- lonPandasIndex
PandasIndex(Index([ 0.0, 1.875, 3.75, 5.625, 7.5, 9.375, 11.25, 13.125,
+ 15.0, 16.875,
...
- 162.1875, 164.0625, 165.9375, 167.8125, 169.6875, 171.5625,
- 173.4375, 175.3125, 177.1875, 179.0625],
- dtype='float64', name='lon', length=192))
- latPandasIndex
PandasIndex(Index([-89.0625, -87.1875, -85.3125, -83.4375, -81.5625, -79.6875, -77.8125,
- -75.9375, -74.0625, -72.1875, -70.3125, -68.4375, -66.5625, -64.6875,
- -62.8125, -60.9375, -59.0625, -57.1875, -55.3125, -53.4375, -51.5625,
- -49.6875, -47.8125, -45.9375, -44.0625, -42.1875, -40.3125, -38.4375,
- -36.5625, -34.6875, -32.8125, -30.9375, -29.0625, -27.1875, -25.3125,
- -23.4375, -21.5625, -19.6875, -17.8125, -15.9375, -14.0625, -12.1875,
- -10.3125, -8.4375, -6.5625, -4.6875, -2.8125, -0.9375, 0.9375,
- 2.8125, 4.6875, 6.5625, 8.4375, 10.3125, 12.1875, 14.0625,
- 15.9375, 17.8125, 19.6875, 21.5625, 23.4375, 25.3125, 27.1875,
- 29.0625, 30.9375, 32.8125, 34.6875, 36.5625, 38.4375, 40.3125,
- 42.1875, 44.0625, 45.9375, 47.8125, 49.6875, 51.5625, 53.4375,
- 55.3125, 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,
- 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125, 79.6875,
- 81.5625, 83.4375, 85.3125, 87.1875, 89.0625],
- dtype='float64', name='lat'))
- CDI :
- Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)
- Conventions :
- CF-1.4
- source :
- MPI-ESM-LR 2011; URL: http://svn.zmaw.de/svn/cosmos/branches/releases/mpi-esm-cmip5/src/mod; atmosphere: ECHAM6 (REV: 4603), T63L47; land: JSBACH (REV: 4603); ocean: MPIOM (REV: 4603), GR15L40; sea ice: 4603; marine bgc: HAMOCC (REV: 4603);
- institution :
- Max Planck Institute for Meteorology
- institute_id :
- MPI-M
- experiment_id :
- historical
- model_id :
- MPI-ESM-LR
- forcing :
- GHG Oz SD Sl Vl LU
- parent_experiment_id :
- piControl
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 10957.0
- contact :
- k204230
- history :
- Mon Sep 11 21:59:05 2023: cdo -s setlevel,0 cachedir/3099/tx90pETCCDI_yr_MPI-ESM-LR_historical_r1i1p1_1990-1992.nc outdir/3099/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/tx90petccdi/r1i1p1//tx90petccdi_yr_mpi-esm-lr_historical_r1i1p1_1990-1992.nc
-Mon Sep 11 21:57:21 2023: cdo -s -f nc4 -remapbil,global_1.875 cachedir/3099/merge/tasmax/tasmax_day_MPI-ESM-LR_historical_r1i1p1_19900101-19921231.nc cachedir/3099/merge/tasmax/tmp.nc
-Mon Sep 11 21:57:20 2023: cdo -s selyear,1990/1992 cachedir/3099/merge/tasmax/merged.nc cachedir/3099/merge/tasmax/sel-merged.nc
-Mon Sep 11 21:57:20 2023: cdo -O -s mergetime /work/kd0956/CMIP5/data/cmip5/output1/MPI-M/MPI-ESM-LR/historical/day/atmos/day/r1i1p1/v20111006/tasmax/tasmax_day_MPI-ESM-LR_historical_r1i1p1_19900101-19991231.nc cachedir/3099/merge/tasmax/merged.nc
-Model raw output postprocessing with modelling environment (IMDI) at DKRZ: URL: http://svn-mad.zmaw.de/svn/mad/Model/IMDI/trunk, REV: 3185 2011-05-28T07:10:01Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- references :
- ECHAM6: n/a; JSBACH: Raddatz et al., 2007. Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty first century? Climate Dynamics, 29, 565-574, doi 10.1007/s00382-007-0247-8; MPIOM: Marsland et al., 2003. The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modelling, 5, 91-127; HAMOCC: http://www.mpimet.mpg.de/fileadmin/models/MPIOM/HAMOCC5.1_TECHNICAL_REPORT.pdf;
- initialization_method :
- 1
- physics_version :
- 1
- input_tracking_id :
- a8852ce6-e2c4-401b-a28b-566c1d5c733b
- product :
- output
- experiment :
- historical
- input_frequency :
- day
- input_creation_date :
- 2011-05-28T07:10:01Z
- project_id :
- CMIP5
- table_id :
- Table day (27 April 2011) 86d1558d99b6ed1e7a886ab3fd717b58
- input_title :
- MPI-ESM-LR model output prepared for CMIP5 historical
- parent_experiment :
- pre-industrial control
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.5.9
- ETCCDI_institution :
- UNSW Australia & FUB Berlin
- ETCCDI_institution_id :
- UNSW-CCRC,FUB-IfM
- ETCCDI_software :
- climdex.pcic
- ETCCDI_software_version :
- 1.1.11
- frequency :
- yr
- creation_date :
- 2023-09-11T19:57:50Z
- title :
- ETCCDI indices computed on MPI-ESM-LR model output prepared for CMIP5 historical
- CDO :
- Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)
+ 341.25, 343.125, 345.0, 346.875, 348.75, 350.625, 352.5, 354.375,
+ 356.25, 358.125],
+ dtype='float64', name='lon', length=192))- latPandasIndex
PandasIndex(Index([ -88.5721664428711, -86.7225341796875, -84.86196899414062,
+ -82.99893951416016, -81.13497924804688, -79.27056121826172,
+ -77.40589141845703, -75.54106140136719, -73.67613220214844,
+ -71.8111343383789, -69.94608306884766, -68.08099365234375,
+ -66.21587371826172, -64.3507308959961, -62.48556900024414,
+ -60.62039566040039, -58.755210876464844, -56.8900146484375,
+ -55.02480697631836, -53.15959548950195, -51.294376373291016,
+ -49.42915344238281, -47.563926696777344, -45.698692321777344,
+ -43.833457946777344, -41.96821975708008, -40.10297775268555,
+ -38.237735748291016, -36.37248992919922, -34.50724411010742,
+ -32.64199447631836, -30.776744842529297, -28.9114933013916,
+ -27.046239852905273, -25.180986404418945, -23.315731048583984,
+ -21.450475692749023, -19.58521842956543, -17.719961166381836,
+ -15.854703903198242, -13.989445686340332, -12.124187469482422,
+ -10.258928298950195, -8.393669128417969, -6.528409481048584,
+ -4.663149833679199, -2.7978897094726562, -0.9326300024986267,
+ 0.9326298832893372, 2.7978899478912354, 4.663149833679199,
+ 6.528409481048584, 8.393669128417969, 10.258928298950195,
+ 12.124187469482422, 13.989445686340332, 15.854703903198242,
+ 17.719961166381836, 19.58521842956543, 21.450475692749023,
+ 23.315731048583984, 25.180986404418945, 27.046239852905273,
+ 28.9114933013916, 30.776744842529297, 32.64199447631836,
+ 34.50724411010742, 36.37248992919922, 38.237735748291016,
+ 40.10297775268555, 41.96821975708008, 43.833457946777344,
+ 45.698692321777344, 47.563926696777344, 49.42915344238281,
+ 51.294376373291016, 53.15959548950195, 55.02480697631836,
+ 56.890010833740234, 58.755210876464844, 60.62039566040039,
+ 62.48556900024414, 64.3507308959961, 66.21587371826172,
+ 68.08099365234375, 69.94608306884766, 71.8111343383789,
+ 73.67613220214844, 75.54106140136719, 77.40589141845703,
+ 79.27056121826172, 81.13497924804688, 82.99893951416016,
+ 84.86196899414062, 86.7225341796875, 88.5721664428711],
+ dtype='float64', name='lat'))
- CDI :
- Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)
- Conventions :
- CF-1.4
- institution :
- Max Planck Institute for Meteorology
- ETCCDI_institution :
- UNSW Australia & FUB Berlin
- ETCCDI_institution_id :
- UNSW-CCRC,FUB-IfM
- ETCCDI_software :
- climdex.pcic
- ETCCDI_software_version :
- 1.1.11
- contact :
- k204230
- frequency :
- yr
- creation_date :
- 2023-09-28T11:10:27Z
- title :
- ETCCDI indices computed on 0
- history :
- Thu Sep 28 13:11:53 2023: cdo -s setlevel,0 cachedir/3113/tx90pETCCDI_yr_MPI-ESM-LR_historical_r1i1p1_1990-1992.nc outdir/3113/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/tx90petccdi/r1i1p1//tx90petccdi_yr_mpi-esm-lr_historical_r1i1p1_1990-1992.nc
- CDO :
- Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)
@@ -15446,14 +18716,14 @@ The data do
-
+
@@ -15462,7 +18732,7 @@ The data has bee
-In [36]:
+In [20]:
dset.sum(dim="time")["tx90pETCCDI"].plot()
@@ -15479,19 +18749,23 @@ The data has bee
-
+
+
+
- Out[36]:
+ Out[20]:
-<matplotlib.collections.QuadMesh at 0x7fff430ff450>
+<matplotlib.collections.QuadMesh at 0x7fffb7fa21d0>
+
+
@@ -15499,7 +18773,7 @@ The data has bee
-
@@ -15511,7 +18785,7 @@ The data has bee
-
+
@@ -15528,7 +18802,7 @@ What happens if the data get's los
-In [32]:
+In [21]:
!rm -fr /scratch/b/b380001/futures/6def5135a687932d27f419a3e993b5bd68aa03425ff0378cfb7745c0aef497a5
@@ -15556,7 +18830,7 @@ What happens if the data get's los
-In [37]:
+In [22]:
list(freva.databrowser(variable="tx90petccdi"))
@@ -15573,15 +18847,17 @@ What happens if the data get's los
-
+
+
+
- Out[37]:
+ Out[22]:
-['/scratch/b/b380001/futures/6def5135a687932d27f419a3e993b5bd68aa03425ff0378cfb7745c0aef497a5/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/yr/r1i1p1/v20230911/tx90pETCCDI/tx90pETCCDI_yr_mpi-esm-lr_historical_r1i1p1_199007020000-199207011200.nc']
+['/scratch/b/b380001/futures/6def5135a687932d27f419a3e993b5bd68aa03425ff0378cfb7745c0aef497a5/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/yr/r1i1p1/v20230928/tx90pETCCDI/tx90pETCCDI_yr_mpi-esm-lr_historical_r1i1p1_199007020000-199207011200.nc']
@@ -15590,7 +18866,7 @@ What happens if the data get's los
-
+
@@ -15607,7 +18883,7 @@ What happens if the data get's los
-In [35]:
+In [23]:
dset = xr.open_mfdataset(
@@ -15629,7 +18905,9 @@ What happens if the data get's los
+
+
@@ -15639,17 +18917,19 @@ What happens if the data get's los
-
+
+
+
@@ -15661,9 +18941,11 @@ What happens if the data get's los
-
+
+
+
- Out[35]:
+ Out[23]:
@@ -16032,75 +19314,68 @@ What happens if the data get's los
fill: currentColor;
}
<xarray.Dataset>
-Dimensions: (time: 3, bnds: 2, lon: 192, lat: 96)
+Dimensions: (time: 3, lon: 192, lat: 96, bnds: 2)
Coordinates:
* time (time) datetime64[ns] 1990-07-02 1991-07-02 1992-07-01T12:00:00
- * lon (lon) float64 -179.1 -177.2 -175.3 -173.4 ... 175.3 177.2 179.1
- * lat (lat) float64 -89.06 -87.19 -85.31 -83.44 ... 85.31 87.19 89.06
- height float64 ...
+ * lon (lon) float64 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1
+ * lat (lat) float64 -88.57 -86.72 -84.86 -83.0 ... 84.86 86.72 88.57
Dimensions without coordinates: bnds
Data variables:
- time_bnds (time, bnds) datetime64[ns] dask.array<chunksize=(3, 2), meta=np.ndarray>
+ time_bnds (time, bnds) float64 dask.array<chunksize=(3, 2), meta=np.ndarray>
tx90pETCCDI (time, lat, lon) float32 dask.array<chunksize=(3, 96, 192), meta=np.ndarray>
-Attributes: (12/36)
+Attributes: (12/13)
CDI: Climate Data Interface version 2.0.5 (https://m...
Conventions: CF-1.4
- source: MPI-ESM-LR 2011; URL: http://svn.zmaw.de/svn/co...
institution: Max Planck Institute for Meteorology
- institute_id: MPI-M
- experiment_id: historical
- ... ...
+ ETCCDI_institution: UNSW Australia & FUB Berlin
+ ETCCDI_institution_id: UNSW-CCRC,FUB-IfM
ETCCDI_software: climdex.pcic
- ETCCDI_software_version: 1.1.11
+ ... ...
+ contact: k204230
frequency: yr
- creation_date: 2023-09-11T20:05:11Z
- title: ETCCDI indices computed on MPI-ESM-LR model out...
- CDO: Climate Data Operators version 2.0.5 (https://m...
xarray.Dataset- time: 3
- bnds: 2
- lon: 192
- lat: 96
- time(time)datetime64[ns]1990-07-02 ... 1992-07-01T12:00:00
- standard_name :
- time
- long_name :
- time
- bounds :
- time_bnds
- axis :
- T
array(['1990-07-02T00:00:00.000000000', '1991-07-02T00:00:00.000000000',
- '1992-07-01T12:00:00.000000000'], dtype='datetime64[ns]')
- lon(lon)float64-179.1 -177.2 ... 177.2 179.1
- standard_name :
- longitude
- long_name :
- longitude
- units :
- degrees_east
- axis :
- X
array([-179.0625, -177.1875, -175.3125, -173.4375, -171.5625, -169.6875,
- -167.8125, -165.9375, -164.0625, -162.1875, -160.3125, -158.4375,
- -156.5625, -154.6875, -152.8125, -150.9375, -149.0625, -147.1875,
- -145.3125, -143.4375, -141.5625, -139.6875, -137.8125, -135.9375,
- -134.0625, -132.1875, -130.3125, -128.4375, -126.5625, -124.6875,
- -122.8125, -120.9375, -119.0625, -117.1875, -115.3125, -113.4375,
- -111.5625, -109.6875, -107.8125, -105.9375, -104.0625, -102.1875,
- -100.3125, -98.4375, -96.5625, -94.6875, -92.8125, -90.9375,
- -89.0625, -87.1875, -85.3125, -83.4375, -81.5625, -79.6875,
- -77.8125, -75.9375, -74.0625, -72.1875, -70.3125, -68.4375,
- -66.5625, -64.6875, -62.8125, -60.9375, -59.0625, -57.1875,
- -55.3125, -53.4375, -51.5625, -49.6875, -47.8125, -45.9375,
- -44.0625, -42.1875, -40.3125, -38.4375, -36.5625, -34.6875,
- -32.8125, -30.9375, -29.0625, -27.1875, -25.3125, -23.4375,
- -21.5625, -19.6875, -17.8125, -15.9375, -14.0625, -12.1875,
- -10.3125, -8.4375, -6.5625, -4.6875, -2.8125, -0.9375,
- 0.9375, 2.8125, 4.6875, 6.5625, 8.4375, 10.3125,
- 12.1875, 14.0625, 15.9375, 17.8125, 19.6875, 21.5625,
- 23.4375, 25.3125, 27.1875, 29.0625, 30.9375, 32.8125,
- 34.6875, 36.5625, 38.4375, 40.3125, 42.1875, 44.0625,
- 45.9375, 47.8125, 49.6875, 51.5625, 53.4375, 55.3125,
- 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,
- 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125,
- 79.6875, 81.5625, 83.4375, 85.3125, 87.1875, 89.0625,
- 90.9375, 92.8125, 94.6875, 96.5625, 98.4375, 100.3125,
- 102.1875, 104.0625, 105.9375, 107.8125, 109.6875, 111.5625,
- 113.4375, 115.3125, 117.1875, 119.0625, 120.9375, 122.8125,
- 124.6875, 126.5625, 128.4375, 130.3125, 132.1875, 134.0625,
- 135.9375, 137.8125, 139.6875, 141.5625, 143.4375, 145.3125,
- 147.1875, 149.0625, 150.9375, 152.8125, 154.6875, 156.5625,
- 158.4375, 160.3125, 162.1875, 164.0625, 165.9375, 167.8125,
- 169.6875, 171.5625, 173.4375, 175.3125, 177.1875, 179.0625])
- lat(lat)float64-89.06 -87.19 ... 87.19 89.06
- standard_name :
- latitude
- long_name :
- latitude
- units :
- degrees_north
- axis :
- Y
array([-89.0625, -87.1875, -85.3125, -83.4375, -81.5625, -79.6875, -77.8125,
- -75.9375, -74.0625, -72.1875, -70.3125, -68.4375, -66.5625, -64.6875,
- -62.8125, -60.9375, -59.0625, -57.1875, -55.3125, -53.4375, -51.5625,
- -49.6875, -47.8125, -45.9375, -44.0625, -42.1875, -40.3125, -38.4375,
- -36.5625, -34.6875, -32.8125, -30.9375, -29.0625, -27.1875, -25.3125,
- -23.4375, -21.5625, -19.6875, -17.8125, -15.9375, -14.0625, -12.1875,
- -10.3125, -8.4375, -6.5625, -4.6875, -2.8125, -0.9375, 0.9375,
- 2.8125, 4.6875, 6.5625, 8.4375, 10.3125, 12.1875, 14.0625,
- 15.9375, 17.8125, 19.6875, 21.5625, 23.4375, 25.3125, 27.1875,
- 29.0625, 30.9375, 32.8125, 34.6875, 36.5625, 38.4375, 40.3125,
- 42.1875, 44.0625, 45.9375, 47.8125, 49.6875, 51.5625, 53.4375,
- 55.3125, 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,
- 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125, 79.6875,
- 81.5625, 83.4375, 85.3125, 87.1875, 89.0625])
- height()float64...
- standard_name :
- height
- long_name :
- height
- units :
- m
- positive :
- up
- axis :
- Z
[1 values with dtype=float64]
- time_bnds(time, bnds)datetime64[ns]dask.array<chunksize=(3, 2), meta=np.ndarray>
+ creation_date: 2023-09-28T11:13:07Z
+ title: ETCCDI indices computed on 0
+ history: Thu Sep 28 13:14:21 2023: cdo -s setlevel,0 cac...
+ CDO: Climate Data Operators version 2.0.5 (https://m...xarray.Dataset- time: 3
- lon: 192
- lat: 96
- bnds: 2
- time(time)datetime64[ns]1990-07-02 ... 1992-07-01T12:00:00
- standard_name :
- time
- long_name :
- time
- axis :
- T
array(['1990-07-02T00:00:00.000000000', '1991-07-02T00:00:00.000000000',
+ '1992-07-01T12:00:00.000000000'], dtype='datetime64[ns]')
- lon(lon)float640.0 1.875 3.75 ... 356.2 358.1
- standard_name :
- longitude
- long_name :
- lon
- units :
- degrees_east
- axis :
- X
array([ 0. , 1.875, 3.75 , 5.625, 7.5 , 9.375, 11.25 , 13.125,
+ 15. , 16.875, 18.75 , 20.625, 22.5 , 24.375, 26.25 , 28.125,
+ 30. , 31.875, 33.75 , 35.625, 37.5 , 39.375, 41.25 , 43.125,
+ 45. , 46.875, 48.75 , 50.625, 52.5 , 54.375, 56.25 , 58.125,
+ 60. , 61.875, 63.75 , 65.625, 67.5 , 69.375, 71.25 , 73.125,
+ 75. , 76.875, 78.75 , 80.625, 82.5 , 84.375, 86.25 , 88.125,
+ 90. , 91.875, 93.75 , 95.625, 97.5 , 99.375, 101.25 , 103.125,
+ 105. , 106.875, 108.75 , 110.625, 112.5 , 114.375, 116.25 , 118.125,
+ 120. , 121.875, 123.75 , 125.625, 127.5 , 129.375, 131.25 , 133.125,
+ 135. , 136.875, 138.75 , 140.625, 142.5 , 144.375, 146.25 , 148.125,
+ 150. , 151.875, 153.75 , 155.625, 157.5 , 159.375, 161.25 , 163.125,
+ 165. , 166.875, 168.75 , 170.625, 172.5 , 174.375, 176.25 , 178.125,
+ 180. , 181.875, 183.75 , 185.625, 187.5 , 189.375, 191.25 , 193.125,
+ 195. , 196.875, 198.75 , 200.625, 202.5 , 204.375, 206.25 , 208.125,
+ 210. , 211.875, 213.75 , 215.625, 217.5 , 219.375, 221.25 , 223.125,
+ 225. , 226.875, 228.75 , 230.625, 232.5 , 234.375, 236.25 , 238.125,
+ 240. , 241.875, 243.75 , 245.625, 247.5 , 249.375, 251.25 , 253.125,
+ 255. , 256.875, 258.75 , 260.625, 262.5 , 264.375, 266.25 , 268.125,
+ 270. , 271.875, 273.75 , 275.625, 277.5 , 279.375, 281.25 , 283.125,
+ 285. , 286.875, 288.75 , 290.625, 292.5 , 294.375, 296.25 , 298.125,
+ 300. , 301.875, 303.75 , 305.625, 307.5 , 309.375, 311.25 , 313.125,
+ 315. , 316.875, 318.75 , 320.625, 322.5 , 324.375, 326.25 , 328.125,
+ 330. , 331.875, 333.75 , 335.625, 337.5 , 339.375, 341.25 , 343.125,
+ 345. , 346.875, 348.75 , 350.625, 352.5 , 354.375, 356.25 , 358.125])
- lat(lat)float64-88.57 -86.72 ... 86.72 88.57
- standard_name :
- latitude
- long_name :
- lat
- units :
- degrees_north
- axis :
- Y
array([-88.572166, -86.722534, -84.861969, -82.99894 , -81.134979, -79.270561,
+ -77.405891, -75.541061, -73.676132, -71.811134, -69.946083, -68.080994,
+ -66.215874, -64.350731, -62.485569, -60.620396, -58.755211, -56.890015,
+ -55.024807, -53.159595, -51.294376, -49.429153, -47.563927, -45.698692,
+ -43.833458, -41.96822 , -40.102978, -38.237736, -36.37249 , -34.507244,
+ -32.641994, -30.776745, -28.911493, -27.04624 , -25.180986, -23.315731,
+ -21.450476, -19.585218, -17.719961, -15.854704, -13.989446, -12.124187,
+ -10.258928, -8.393669, -6.528409, -4.66315 , -2.79789 , -0.93263 ,
+ 0.93263 , 2.79789 , 4.66315 , 6.528409, 8.393669, 10.258928,
+ 12.124187, 13.989446, 15.854704, 17.719961, 19.585218, 21.450476,
+ 23.315731, 25.180986, 27.04624 , 28.911493, 30.776745, 32.641994,
+ 34.507244, 36.37249 , 38.237736, 40.102978, 41.96822 , 43.833458,
+ 45.698692, 47.563927, 49.429153, 51.294376, 53.159595, 55.024807,
+ 56.890011, 58.755211, 60.620396, 62.485569, 64.350731, 66.215874,
+ 68.080994, 69.946083, 71.811134, 73.676132, 75.541061, 77.405891,
+ 79.270561, 81.134979, 82.99894 , 84.861969, 86.722534, 88.572166])
- time_bnds(time, bnds)float64dask.array<chunksize=(3, 2), meta=np.ndarray>
@@ -16130,7 +19405,7 @@ What happens if the data get's los
Data type
- datetime64[ns] numpy.ndarray
+ float64 numpy.ndarray
@@ -16155,7 +19430,7 @@ What happens if the data get's los
-
- tx90pETCCDI(time, lat, lon)float32dask.array<chunksize=(3, 96, 192), meta=np.ndarray>
- long_name :
- Percentage of Days when Daily Maximum Temperature is Above the 90th Percentile
- units :
- %
- cell_methods :
- time: maximum
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MPI-ESM-LR_historical_r0i0p0.nc areacella: areacella_fx_MPI-ESM-LR_historical_r0i0p0.nc
- history :
- Created by climdex.pcic 1.1.11 on Mon Sep 11 22:05:11 2023
- base_period :
- 1991-1991
+
- tx90pETCCDI(time, lat, lon)float32dask.array<chunksize=(3, 96, 192), meta=np.ndarray>
- long_name :
- Percentage of Days when Daily Maximum Temperature is Above the 90th Percentile
- units :
- %
- CDI_grid_type :
- gaussian
- CDI_grid_num_LPE :
- 48
- history :
- Created by climdex.pcic 1.1.11 on Thu Sep 28 13:13:07 2023
- base_period :
- 1991-1991
@@ -16233,32 +19508,209 @@ What happens if the data get's los
-
- timePandasIndex
PandasIndex(DatetimeIndex(['1990-07-02 00:00:00', '1991-07-02 00:00:00',
+
- timePandasIndex
PandasIndex(DatetimeIndex(['1990-07-02 00:00:00', '1991-07-02 00:00:00',
'1992-07-01 12:00:00'],
- dtype='datetime64[ns]', name='time', freq=None))
- lonPandasIndex
PandasIndex(Index([-179.0625, -177.1875, -175.3125, -173.4375, -171.5625, -169.6875,
- -167.8125, -165.9375, -164.0625, -162.1875,
+ dtype='datetime64[ns]', name='time', freq=None))
- lonPandasIndex
PandasIndex(Index([ 0.0, 1.875, 3.75, 5.625, 7.5, 9.375, 11.25, 13.125,
+ 15.0, 16.875,
...
- 162.1875, 164.0625, 165.9375, 167.8125, 169.6875, 171.5625,
- 173.4375, 175.3125, 177.1875, 179.0625],
- dtype='float64', name='lon', length=192))
- latPandasIndex
PandasIndex(Index([-89.0625, -87.1875, -85.3125, -83.4375, -81.5625, -79.6875, -77.8125,
- -75.9375, -74.0625, -72.1875, -70.3125, -68.4375, -66.5625, -64.6875,
- -62.8125, -60.9375, -59.0625, -57.1875, -55.3125, -53.4375, -51.5625,
- -49.6875, -47.8125, -45.9375, -44.0625, -42.1875, -40.3125, -38.4375,
- -36.5625, -34.6875, -32.8125, -30.9375, -29.0625, -27.1875, -25.3125,
- -23.4375, -21.5625, -19.6875, -17.8125, -15.9375, -14.0625, -12.1875,
- -10.3125, -8.4375, -6.5625, -4.6875, -2.8125, -0.9375, 0.9375,
- 2.8125, 4.6875, 6.5625, 8.4375, 10.3125, 12.1875, 14.0625,
- 15.9375, 17.8125, 19.6875, 21.5625, 23.4375, 25.3125, 27.1875,
- 29.0625, 30.9375, 32.8125, 34.6875, 36.5625, 38.4375, 40.3125,
- 42.1875, 44.0625, 45.9375, 47.8125, 49.6875, 51.5625, 53.4375,
- 55.3125, 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,
- 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125, 79.6875,
- 81.5625, 83.4375, 85.3125, 87.1875, 89.0625],
- dtype='float64', name='lat'))
- CDI :
- Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)
- Conventions :
- CF-1.4
- source :
- MPI-ESM-LR 2011; URL: http://svn.zmaw.de/svn/cosmos/branches/releases/mpi-esm-cmip5/src/mod; atmosphere: ECHAM6 (REV: 4603), T63L47; land: JSBACH (REV: 4603); ocean: MPIOM (REV: 4603), GR15L40; sea ice: 4603; marine bgc: HAMOCC (REV: 4603);
- institution :
- Max Planck Institute for Meteorology
- institute_id :
- MPI-M
- experiment_id :
- historical
- model_id :
- MPI-ESM-LR
- forcing :
- GHG Oz SD Sl Vl LU
- parent_experiment_id :
- piControl
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 10957.0
- contact :
- k204230
- history :
- Mon Sep 11 22:06:20 2023: cdo -s setlevel,0 cachedir/3100/tx90pETCCDI_yr_MPI-ESM-LR_historical_r1i1p1_1990-1992.nc outdir/3100/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/tx90petccdi/r1i1p1//tx90petccdi_yr_mpi-esm-lr_historical_r1i1p1_1990-1992.nc
-Mon Sep 11 22:04:42 2023: cdo -s -f nc4 -remapbil,global_1.875 cachedir/3100/merge/tasmax/tasmax_day_MPI-ESM-LR_historical_r1i1p1_19900101-19921231.nc cachedir/3100/merge/tasmax/tmp.nc
-Mon Sep 11 22:04:42 2023: cdo -s selyear,1990/1992 cachedir/3100/merge/tasmax/merged.nc cachedir/3100/merge/tasmax/sel-merged.nc
-Mon Sep 11 22:04:41 2023: cdo -O -s mergetime /work/kd0956/CMIP5/data/cmip5/output1/MPI-M/MPI-ESM-LR/historical/day/atmos/day/r1i1p1/v20111006/tasmax/tasmax_day_MPI-ESM-LR_historical_r1i1p1_19900101-19991231.nc cachedir/3100/merge/tasmax/merged.nc
-Model raw output postprocessing with modelling environment (IMDI) at DKRZ: URL: http://svn-mad.zmaw.de/svn/mad/Model/IMDI/trunk, REV: 3185 2011-05-28T07:10:01Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- references :
- ECHAM6: n/a; JSBACH: Raddatz et al., 2007. Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty first century? Climate Dynamics, 29, 565-574, doi 10.1007/s00382-007-0247-8; MPIOM: Marsland et al., 2003. The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modelling, 5, 91-127; HAMOCC: http://www.mpimet.mpg.de/fileadmin/models/MPIOM/HAMOCC5.1_TECHNICAL_REPORT.pdf;
- initialization_method :
- 1
- physics_version :
- 1
- input_tracking_id :
- a8852ce6-e2c4-401b-a28b-566c1d5c733b
- product :
- output
- experiment :
- historical
- input_frequency :
- day
- input_creation_date :
- 2011-05-28T07:10:01Z
- project_id :
- CMIP5
- table_id :
- Table day (27 April 2011) 86d1558d99b6ed1e7a886ab3fd717b58
- input_title :
- MPI-ESM-LR model output prepared for CMIP5 historical
- parent_experiment :
- pre-industrial control
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.5.9
- ETCCDI_institution :
- UNSW Australia & FUB Berlin
- ETCCDI_institution_id :
- UNSW-CCRC,FUB-IfM
- ETCCDI_software :
- climdex.pcic
- ETCCDI_software_version :
- 1.1.11
- frequency :
- yr
- creation_date :
- 2023-09-11T20:05:11Z
- title :
- ETCCDI indices computed on MPI-ESM-LR model output prepared for CMIP5 historical
- CDO :
- Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)
+ 341.25, 343.125, 345.0, 346.875, 348.75, 350.625, 352.5, 354.375,
+ 356.25, 358.125],
+ dtype='float64', name='lon', length=192))- latPandasIndex
PandasIndex(Index([ -88.5721664428711, -86.7225341796875, -84.86196899414062,
+ -82.99893951416016, -81.13497924804688, -79.27056121826172,
+ -77.40589141845703, -75.54106140136719, -73.67613220214844,
+ -71.8111343383789, -69.94608306884766, -68.08099365234375,
+ -66.21587371826172, -64.3507308959961, -62.48556900024414,
+ -60.62039566040039, -58.755210876464844, -56.8900146484375,
+ -55.02480697631836, -53.15959548950195, -51.294376373291016,
+ -49.42915344238281, -47.563926696777344, -45.698692321777344,
+ -43.833457946777344, -41.96821975708008, -40.10297775268555,
+ -38.237735748291016, -36.37248992919922, -34.50724411010742,
+ -32.64199447631836, -30.776744842529297, -28.9114933013916,
+ -27.046239852905273, -25.180986404418945, -23.315731048583984,
+ -21.450475692749023, -19.58521842956543, -17.719961166381836,
+ -15.854703903198242, -13.989445686340332, -12.124187469482422,
+ -10.258928298950195, -8.393669128417969, -6.528409481048584,
+ -4.663149833679199, -2.7978897094726562, -0.9326300024986267,
+ 0.9326298832893372, 2.7978899478912354, 4.663149833679199,
+ 6.528409481048584, 8.393669128417969, 10.258928298950195,
+ 12.124187469482422, 13.989445686340332, 15.854703903198242,
+ 17.719961166381836, 19.58521842956543, 21.450475692749023,
+ 23.315731048583984, 25.180986404418945, 27.046239852905273,
+ 28.9114933013916, 30.776744842529297, 32.64199447631836,
+ 34.50724411010742, 36.37248992919922, 38.237735748291016,
+ 40.10297775268555, 41.96821975708008, 43.833457946777344,
+ 45.698692321777344, 47.563926696777344, 49.42915344238281,
+ 51.294376373291016, 53.15959548950195, 55.02480697631836,
+ 56.890010833740234, 58.755210876464844, 60.62039566040039,
+ 62.48556900024414, 64.3507308959961, 66.21587371826172,
+ 68.08099365234375, 69.94608306884766, 71.8111343383789,
+ 73.67613220214844, 75.54106140136719, 77.40589141845703,
+ 79.27056121826172, 81.13497924804688, 82.99893951416016,
+ 84.86196899414062, 86.7225341796875, 88.5721664428711],
+ dtype='float64', name='lat'))
- CDI :
- Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)
- Conventions :
- CF-1.4
- institution :
- Max Planck Institute for Meteorology
- ETCCDI_institution :
- UNSW Australia & FUB Berlin
- ETCCDI_institution_id :
- UNSW-CCRC,FUB-IfM
- ETCCDI_software :
- climdex.pcic
- ETCCDI_software_version :
- 1.1.11
- contact :
- k204230
- frequency :
- yr
- creation_date :
- 2023-09-28T11:13:07Z
- title :
- ETCCDI indices computed on 0
- history :
- Thu Sep 28 13:14:21 2023: cdo -s setlevel,0 cachedir/3114/tx90pETCCDI_yr_MPI-ESM-LR_historical_r1i1p1_1990-1992.nc outdir/3114/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/tx90petccdi/r1i1p1//tx90petccdi_yr_mpi-esm-lr_historical_r1i1p1_1990-1992.nc
- CDO :
- Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+How can we check if the data is physically present?¶
Sometimes it might be useful to check if we can use the data straight away or the data has to be re-created.
+The databrowser doesn't get informed about the deletion of data automoatically. For example if we delete the data again:
+
+
+
+
+
+
+
+
+
+In [24]:
+
+
+!rm -fr /scratch/b/`b380001/futures/6def5135a687932d27f419a3e993b5bd68aa03425ff0378cfb7745c0aef497a5
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+the databrowser still shows the location on disk although the data doesn't exist anymore:
+
+
+
+
+
+
+
+
+
+In [25]:
+
+
+list(freva.databrowser(variable="tx90petccdi"))
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Out[25]:
+
+
+
+
+
+['/scratch/b/b380001/futures/6def5135a687932d27f419a3e993b5bd68aa03425ff0378cfb7745c0aef497a5/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/yr/r1i1p1/v20230928/tx90pETCCDI/tx90pETCCDI_yr_mpi-esm-lr_historical_r1i1p1_199007020000-199207011200.nc']
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+We can use the check_future
method to check for the existence for futures. Every dataset that doesn't exsit anymore will be deleted from the databrowser and replaced by the special future://
url, indicating that this dataset doesn't exist but can be recreated. We can use a key=value
pair search facet like for the databrowser method to sub select only certain datasets:
+
+
+
+
+
+
+
+
+
+In [27]:
+
+
+freva.check_futures(variable="tx90petccdi")
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+Let's search for the data again:
+
+
+
+
+
+
+
+
+
+In [28]:
+
+
+list(freva.databrowser(variable="tx90petccdi"))
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Out[28]:
+
+
+
+
+
+['future:///scratch/b/b380001/futures/6def5135a687932d27f419a3e993b5bd68aa03425ff0378cfb7745c0aef497a5/cmip5/output1/mpi-m/mpi-esm-lr/historical/yr/atmos/1day/r1i1p1/tx90pETCCDI/tx90pETCCDI_1day_mpi-esm-lr_historical_r1i1p1_199007020000-199207011200']
@@ -16276,7 +19728,7 @@ What happens if the data get's los