-
Notifications
You must be signed in to change notification settings - Fork 0
/
PS_pr.day_regrid.180x90_area.freq.mean_GISS-E2-H.historical.json
186 lines (186 loc) · 17.2 KB
/
PS_pr.day_regrid.180x90_area.freq.mean_GISS-E2-H.historical.json
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
{
"RESULTS": {
"GISS-E2-H.historical": {
"forced": {
"Land_30N50N": {
"annual": 1.1549259632229723,
"semi-annual": 0.3695792972517699
},
"Land_30S30N": {
"annual": 6.867182286952285,
"semi-annual": 1.1973130839359387
},
"Land_50S30S": {
"annual": 0.7833102360471575,
"semi-annual": 0.33415474921186844
},
"Land_50S50N": {
"annual": 4.804355868733509,
"semi-annual": 0.899283744186818
},
"Ocean_30N50N": {
"annual": 1.447189195760683,
"semi-annual": 0.3724802065559291
},
"Ocean_30S30N": {
"annual": 4.569082186991045,
"semi-annual": 1.5047969231749088
},
"Ocean_50S30S": {
"annual": 0.5919548020770594,
"semi-annual": 0.1928088759665084
},
"Ocean_50S50N": {
"annual": 3.310355604111878,
"semi-annual": 1.076677225895386
},
"Total_30N50N": {
"annual": 1.3116137610936278,
"semi-annual": 0.37113452911157135
},
"Total_30S30N": {
"annual": 5.156428181351081,
"semi-annual": 1.4262105285655087
},
"Total_50S30S": {
"annual": 0.6056973091238494,
"semi-annual": 0.2029598636798367
},
"Total_50S50N": {
"annual": 3.698557040790938,
"semi-annual": 1.0305832551729588
}
},
"unforced": {
"Land_30N50N": {
"interannual": 0.11037168355762557,
"seasonal-annual": 0.1504938958560814,
"sub-seasonal": 0.13618359698071195,
"synoptic": 0.06283897471189702
},
"Land_30S30N": {
"interannual": 0.31273408731700925,
"seasonal-annual": 0.30938138785840175,
"sub-seasonal": 0.24402021514695105,
"synoptic": 0.07556756458932476
},
"Land_50S30S": {
"interannual": 0.15285943106444666,
"seasonal-annual": 0.2042415774272863,
"sub-seasonal": 0.17215553403047001,
"synoptic": 0.07140970548940222
},
"Land_50S50N": {
"interannual": 0.24232739801284806,
"seasonal-annual": 0.25507915342816695,
"sub-seasonal": 0.20714108958572194,
"synoptic": 0.07142206771250155
},
"Ocean_30N50N": {
"interannual": 0.1324847179019073,
"seasonal-annual": 0.17559411659927668,
"sub-seasonal": 0.15438800790906432,
"synoptic": 0.0983234739839394
},
"Ocean_30S30N": {
"interannual": 0.6532431992538728,
"seasonal-annual": 0.63784160710743,
"sub-seasonal": 0.43471544075372676,
"synoptic": 0.1144667570515457
},
"Ocean_50S30S": {
"interannual": 0.0984395842657922,
"seasonal-annual": 0.1337093129524112,
"sub-seasonal": 0.12043392875811695,
"synoptic": 0.06911852119910643
},
"Ocean_50S50N": {
"interannual": 0.466928916495708,
"seasonal-annual": 0.46992093626879594,
"sub-seasonal": 0.3310183167321489,
"synoptic": 0.10256124019704362
},
"Total_30N50N": {
"interannual": 0.1222268958111772,
"seasonal-annual": 0.16395059473732418,
"sub-seasonal": 0.14594332294804857,
"synoptic": 0.08186287998113678
},
"Total_30S30N": {
"interannual": 0.5662162403574416,
"seasonal-annual": 0.5538940914679715,
"sub-seasonal": 0.38597775656598704,
"synoptic": 0.10452494256012687
},
"Total_50S30S": {
"interannual": 0.10234783558951795,
"seasonal-annual": 0.13877470420606905,
"sub-seasonal": 0.12414840140297365,
"synoptic": 0.06928306638918347
},
"Total_50S50N": {
"interannual": 0.4085683966082318,
"seasonal-annual": 0.41409638875538185,
"sub-seasonal": 0.29883002420715343,
"synoptic": 0.09447002911646334
}
}
}
},
"YAML": "name: xCDAT_cdat\nchannels:\n - conda-forge\n - defaults\ndependencies:\n - _libgcc_mutex=0.1=conda_forge\n - _openmp_mutex=4.5=2_gnu\n - anyio=3.6.1=pyhd8ed1ab_1\n - argon2-cffi=21.3.0=pyhd8ed1ab_0\n - argon2-cffi-bindings=21.2.0=py310h5764c6d_2\n - asttokens=2.0.5=pyhd8ed1ab_0\n - attrs=22.1.0=pyh71513ae_0\n - babel=2.10.3=pyhd8ed1ab_0\n - backcall=0.2.0=pyh9f0ad1d_0\n - backports=1.0=py_2\n - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0\n - beautifulsoup4=4.11.1=pyha770c72_0\n - bleach=5.0.1=pyhd8ed1ab_0\n - bokeh=2.4.3=py310hff52083_0\n - brotli=1.0.9=h166bdaf_7\n - brotli-bin=1.0.9=h166bdaf_7\n - brotlipy=0.7.0=py310h5764c6d_1004\n - bzip2=1.0.8=h7f98852_4\n - c-ares=1.18.1=h7f98852_0\n - ca-certificates=2022.6.15=ha878542_0\n - cartopy=0.20.3=py310he7eef42_1\n - cdat_info=8.2.1=pyhd8ed1ab_2\n - cdms2=3.1.5=py310h65abc81_14\n - cdp=1.7.0=pyhd8ed1ab_1\n - cdtime=3.1.4=py310h1a17f1e_7\n - cdutil=8.2.1=pyhd8ed1ab_1\n - certifi=2022.6.15=py310hff52083_0\n - cf_xarray=0.7.4=pyhd8ed1ab_0\n - cffi=1.15.1=py310h255011f_0\n - cftime=1.6.1=py310hde88566_0\n - charset-normalizer=2.1.0=pyhd8ed1ab_0\n - click=8.1.3=py310hff52083_0\n - cloudpickle=2.1.0=pyhd8ed1ab_0\n - cryptography=37.0.4=py310h597c629_0\n - curl=7.83.1=h7bff187_0\n - cycler=0.11.0=pyhd8ed1ab_0\n - cytoolz=0.12.0=py310h5764c6d_0\n - dask=2022.7.1=pyhd8ed1ab_0\n - dask-core=2022.7.1=pyhd8ed1ab_0\n - debugpy=1.6.0=py310hd8f1fbe_0\n - decorator=5.1.1=pyhd8ed1ab_0\n - defusedxml=0.7.1=pyhd8ed1ab_0\n - distarray=2.12.2=pyhd8ed1ab_2\n - distributed=2022.7.1=pyhd8ed1ab_0\n - enso_metrics=1.1.1=py310hff52083_1\n - entrypoints=0.4=pyhd8ed1ab_0\n - eofs=1.4.0=py_0\n - esmf=8.2.0=nompi_hc924415_1\n - esmpy=8.2.0=nompi_py310ha0140b2_1\n - executing=0.9.1=pyhd8ed1ab_0\n - expat=2.4.8=h27087fc_0\n - flit-core=3.7.1=pyhd8ed1ab_0\n - fonttools=4.34.4=py310h5764c6d_0\n - freeglut=3.2.2=h9c3ff4c_1\n - freetype=2.10.4=h0708190_1\n - fsspec=2022.7.1=pyhd8ed1ab_0\n - future=0.18.2=py310hff52083_5\n - g2clib=1.6.3=heb9ad7a_1\n - genutil=8.2.1=py310h96516ba_2\n - geos=3.11.0=h27087fc_0\n - giflib=5.2.1=h36c2ea0_2\n - hdf4=4.2.15=h10796ff_3\n - hdf5=1.12.2=nompi_h2386368_100\n - heapdict=1.0.1=py_0\n - icu=70.1=h27087fc_0\n - idna=3.3=pyhd8ed1ab_0\n - importlib-metadata=4.11.4=py310hff52083_0\n - importlib_metadata=4.11.4=hd8ed1ab_0\n - importlib_resources=5.9.0=pyhd8ed1ab_0\n - ipykernel=6.15.1=pyh210e3f2_0\n - ipython=8.4.0=py310hff52083_0\n - ipython_genutils=0.2.0=py_1\n - jasper=2.0.33=ha77e612_0\n - jedi=0.18.1=pyhd8ed1ab_2\n - jinja2=3.1.2=pyhd8ed1ab_1\n - jpeg=9e=h166bdaf_2\n - json5=0.9.5=pyh9f0ad1d_0\n - jsonschema=4.8.0=pyhd8ed1ab_0\n - jupyter_client=7.3.4=pyhd8ed1ab_0\n - jupyter_core=4.11.1=py310hff52083_0\n - jupyter_server=1.18.1=pyhd8ed1ab_0\n - jupyterlab=3.4.5=pyhd8ed1ab_0\n - jupyterlab_pygments=0.2.2=pyhd8ed1ab_0\n - jupyterlab_server=2.15.0=pyhd8ed1ab_0\n - keyutils=1.6.1=h166bdaf_0\n - kiwisolver=1.4.4=py310hbf28c38_0\n - krb5=1.19.3=h3790be6_0\n - lazy-object-proxy=1.7.1=py310h5764c6d_1\n - lcms2=2.12=hddcbb42_0\n - ld_impl_linux-64=2.36.1=hea4e1c9_2\n - lerc=4.0.0=h27087fc_0\n - libblas=3.9.0=15_linux64_openblas\n - libbrotlicommon=1.0.9=h166bdaf_7\n - libbrotlidec=1.0.9=h166bdaf_7\n - libbrotlienc=1.0.9=h166bdaf_7\n - libcblas=3.9.0=15_linux64_openblas\n - libcdms=3.1.2=h2973bc7_118\n - libcf=1.0.3=py310hbc577d2_114\n - libcurl=7.83.1=h7bff187_0\n - libdeflate=1.12=h166bdaf_0\n - libdrs=3.1.2=hf593df3_118\n - libdrs_f=3.1.2=h7e76ec7_114\n - libedit=3.1.20191231=he28a2e2_2\n - libev=4.33=h516909a_1\n - libffi=3.4.2=h7f98852_5\n - libgcc-ng=12.1.0=h8d9b700_16\n - libgfortran-ng=12.1.0=h69a702a_16\n - libgfortran5=12.1.0=hdcd56e2_16\n - libglu=9.0.0=he1b5a44_1001\n - libgomp=12.1.0=h8d9b700_16\n - libiconv=1.16=h516909a_0\n - liblapack=3.9.0=15_linux64_openblas\n - libllvm11=11.1.0=hf817b99_3\n - libnetcdf=4.8.1=nompi_h21705cb_103\n - libnghttp2=1.47.0=h727a467_0\n - libnsl=2.0.0=h7f98852_0\n - libopenblas=0.3.20=pthreads_h78a6416_1\n - libpng=1.6.37=h753d276_3\n - libsodium=1.0.18=h36c2ea0_1\n - libssh2=1.10.0=ha56f1ee_2\n - libstdcxx-ng=12.1.0=ha89aaad_16\n - libtiff=4.4.0=h0d92c0b_2\n - libuuid=2.32.1=h7f98852_1000\n - libwebp=1.2.3=h522a892_1\n - libwebp-base=1.2.3=h166bdaf_2\n - libxcb=1.13=h7f98852_1004\n - libxml2=2.9.14=h22db469_4\n - libxslt=1.1.35=h8affb1d_0\n - libzip=1.9.2=hc869a4a_0\n - libzlib=1.2.12=h166bdaf_2\n - llvmlite=0.38.1=py310h58363a5_0\n - locket=1.0.0=pyhd8ed1ab_0\n - lxml=4.9.1=py310h5764c6d_0\n - lz4=4.0.0=py310h5d5e884_2\n - lz4-c=1.9.3=h9c3ff4c_1\n - markupsafe=2.1.1=py310h5764c6d_1\n - matplotlib-base=3.5.2=py310h5701ce4_1\n - matplotlib-inline=0.1.3=pyhd8ed1ab_0\n - mistune=0.8.4=py310h6acc77f_1005\n - msgpack-python=1.0.4=py310hbf28c38_0\n - munkres=1.1.4=pyh9f0ad1d_0\n - nb_conda=2.2.1=unix_6\n - nb_conda_kernels=2.3.1=py310hff52083_1\n - nbclassic=0.4.3=pyhd8ed1ab_0\n - nbclient=0.6.6=pyhd8ed1ab_0\n - nbconvert=6.5.3=pyhd8ed1ab_0\n - nbconvert-core=6.5.3=pyhd8ed1ab_0\n - nbconvert-pandoc=6.5.3=pyhd8ed1ab_0\n - nbformat=5.4.0=pyhd8ed1ab_0\n - ncurses=6.3=h27087fc_1\n - nest-asyncio=1.5.5=pyhd8ed1ab_0\n - netcdf-fortran=4.5.4=nompi_hc402ea5_101\n - netcdf4=1.6.0=nompi_py310h9fd08d4_101\n - notebook=6.4.12=pyha770c72_0\n - notebook-shim=0.1.0=pyhd8ed1ab_0\n - numba=0.55.2=py310ha5257ce_0\n - numpy=1.22.4=py310h4ef5377_0\n - openblas=0.3.20=pthreads_h320a7e8_1\n - openjpeg=2.4.0=hb52868f_1\n - openssl=1.1.1q=h166bdaf_0\n - output_viewer=1.3.3=pyhd8ed1ab_1\n - packaging=21.3=pyhd8ed1ab_0\n - pandas=1.4.3=py310h769672d_0\n - pandoc=2.19=ha770c72_0\n - pandocfilters=1.5.0=pyhd8ed1ab_0\n - parso=0.8.3=pyhd8ed1ab_0\n - partd=1.2.0=pyhd8ed1ab_0\n - patsy=0.5.2=pyhd8ed1ab_0\n - pcmdi_metrics=2.4.0=pyhd8ed1ab_0\n - pexpect=4.8.0=pyh9f0ad1d_2\n - pickleshare=0.7.5=py_1003\n - pillow=9.2.0=py310he619898_0\n - pip=22.2.1=pyhd8ed1ab_0\n - proj=9.0.1=h93bde94_1\n - prometheus_client=0.14.1=pyhd8ed1ab_0\n - prompt-toolkit=3.0.30=pyha770c72_0\n - psutil=5.9.1=py310h5764c6d_0\n - pthread-stubs=0.4=h36c2ea0_1001\n - ptyprocess=0.7.0=pyhd3deb0d_0\n - pure_eval=0.2.2=pyhd8ed1ab_0\n - pycparser=2.21=pyhd8ed1ab_0\n - pygments=2.12.0=pyhd8ed1ab_0\n - pyopenssl=22.0.0=pyhd8ed1ab_0\n - pyparsing=3.0.9=pyhd8ed1ab_0\n - pyproj=3.3.1=py310hf94497c_1\n - pyrsistent=0.18.1=py310h5764c6d_1\n - pyshp=2.3.1=pyhd8ed1ab_0\n - pysocks=1.7.1=py310hff52083_5\n - python=3.10.5=h582c2e5_0_cpython\n - python-dateutil=2.8.2=pyhd8ed1ab_0\n - python-fastjsonschema=2.16.1=pyhd8ed1ab_0\n - python_abi=3.10=2_cp310\n - pytz=2022.1=pyhd8ed1ab_0\n - pyyaml=6.0=py310h5764c6d_4\n - pyzmq=23.2.1=py310h330234f_0\n - readline=8.1.2=h0f457ee_0\n - requests=2.28.1=pyhd8ed1ab_0\n - scipy=1.8.1=py310hdfbd76f_2\n - seaborn=0.11.2=hd8ed1ab_0\n - seaborn-base=0.11.2=pyhd8ed1ab_0\n - send2trash=1.8.0=pyhd8ed1ab_0\n - setuptools=63.2.0=py310hff52083_0\n - shapely=1.8.2=py310h5e49deb_3\n - six=1.16.0=pyh6c4a22f_0\n - sniffio=1.2.0=py310hff52083_3\n - sortedcontainers=2.4.0=pyhd8ed1ab_0\n - soupsieve=2.3.2.post1=pyhd8ed1ab_0\n - sparse=0.13.0=pyhd8ed1ab_0\n - sqlite=3.39.2=h4ff8645_0\n - stack_data=0.3.0=pyhd8ed1ab_0\n - statsmodels=0.13.2=py310hde88566_0\n - tblib=1.7.0=pyhd8ed1ab_0\n - terminado=0.15.0=py310hff52083_0\n - tinycss2=1.1.1=pyhd8ed1ab_0\n - tk=8.6.12=h27826a3_0\n - toolz=0.12.0=pyhd8ed1ab_0\n - tornado=6.1=py310h5764c6d_3\n - traitlets=5.3.0=pyhd8ed1ab_0\n - typing_extensions=4.3.0=pyha770c72_0\n - tzdata=2022a=h191b570_0\n - udunits2=2.2.28=hc3e0081_0\n - unicodedata2=14.0.0=py310h5764c6d_1\n - urllib3=1.26.11=pyhd8ed1ab_0\n - wcwidth=0.2.5=pyh9f0ad1d_2\n - webencodings=0.5.1=py_1\n - websocket-client=1.3.3=pyhd8ed1ab_0\n - wheel=0.37.1=pyhd8ed1ab_0\n - xarray=2022.6.0=pyhd8ed1ab_1\n - xcdat=0.3.0=pyhd8ed1ab_1\n - xesmf=0.6.3=pyhd8ed1ab_1\n - xorg-fixesproto=5.0=h7f98852_1002\n - xorg-inputproto=2.3.2=h7f98852_1002\n - xorg-kbproto=1.0.7=h7f98852_1002\n - xorg-libx11=1.7.2=h7f98852_0\n - xorg-libxau=1.0.9=h7f98852_0\n - xorg-libxdmcp=1.1.3=h7f98852_0\n - xorg-libxext=1.3.4=h7f98852_1\n - xorg-libxfixes=5.0.3=h7f98852_1004\n - xorg-libxi=1.7.10=h7f98852_0\n - xorg-xextproto=7.3.0=h7f98852_1002\n - xorg-xproto=7.0.31=h7f98852_1007\n - xz=5.2.5=h516909a_1\n - yaml=0.2.5=h7f98852_2\n - zeromq=4.3.4=h9c3ff4c_1\n - zict=2.2.0=pyhd8ed1ab_0\n - zipp=3.8.0=pyhd8ed1ab_0\n - zlib=1.2.12=h166bdaf_2\n - zstd=1.5.2=h8a70e8d_2\nprefix: /home/ahn6/anaconda3/envs/xCDAT_cdat\n",
"json_structure": [
"model+realization",
"variability type",
"domain",
"frequency"
],
"json_version": 3.0,
"provenance": {
"commandLine": "./code/variability_across_timescales_PS_driver.py -p basic_precip_variability_param.py",
"conda": {
"Platform": "linux-64",
"PythonVersion": "3.8.8.final.0",
"Version": "4.13.0",
"buildVersion": "3.21.4"
},
"date": "2022-08-18 09:55:20",
"history": "",
"openGL": {
"GLX": {
"client": {},
"server": {}
}
},
"osAccess": false,
"packages": {
"PMP": "2.0",
"PMPObs": "See 'References' key below, for detailed obs provenance information.",
"blas": "0.3.20",
"cdat_info": "8.2.1",
"cdms": "3.1.5",
"cdp": "1.7.0",
"cdtime": "3.1.4",
"cdutil": "8.2.1",
"clapack": null,
"esmf": "0.6.3",
"esmpy": "8.2.0",
"genutil": "8.2.1",
"lapack": "3.9.0",
"matplotlib": null,
"mesalib": null,
"numpy": "1.22.4",
"python": "3.10.5",
"scipy": "1.8.1",
"uvcdat": null,
"vcs": null,
"vtk": null
},
"platform": {
"Name": "gates.llnl.gov",
"OS": "Linux",
"Version": "3.10.0-1160.71.1.el7.x86_64"
},
"script": "#!/usr/bin/env python\n\nimport glob\nimport os\n\nfrom genutil import StringConstructor\n\nfrom pcmdi_metrics.driver.pmp_parser import PMPParser\nfrom pcmdi_metrics.precip_variability.lib import (\n AddParserArgument,\n # precip_variability_across_timescale,\n)\nwith open('./code/lib_variability_across_timescales.py') as source_file:\n exec(source_file.read())\n\n# Read parameters\nP = PMPParser()\nP = AddParserArgument(P)\nparam = P.get_parameter()\nmip = param.mip\nmod = param.mod\nvar = param.var\ndfrq = param.frq\nmodpath = param.modpath\nprd = param.prd\nfac = param.fac\nnperseg = param.nperseg\nnoverlap = param.noverlap\nprint(modpath)\nprint(mod)\nprint(prd)\nprint(nperseg, noverlap)\n\n# Get flag for CMEC output\ncmec = param.cmec\n\n# Create output directory\ncase_id = param.case_id\noutdir_template = param.process_templated_argument(\"results_dir\")\noutdir = StringConstructor(\n str(outdir_template(output_type=\"%(output_type)\", mip=mip, case_id=case_id))\n)\nfor output_type in [\"graphics\", \"diagnostic_results\", \"metrics_results\"]:\n if not os.path.exists(outdir(output_type=output_type)):\n try:\n os.makedirs(outdir(output_type=output_type))\n except FileExistsError:\n pass\n print(outdir(output_type=output_type))\n\n# Check data in advance\nfile_list = sorted(glob.glob(os.path.join(modpath, \"*\" + mod + \"*\")))\ndata = []\nfor file in file_list:\n if mip == \"obs\":\n model = file.split(\"/\")[-1].split(\".\")[2]\n data.append(model)\n else:\n model = file.split(\"/\")[-1].split(\".\")[2]\n ens = file.split(\"/\")[-1].split(\".\")[3]\n data.append(model + \".\" + ens)\n\nprint(\"Number of datasets:\", len(file_list))\nprint(\"Dataset:\", data)\n\n# Regridding -> Anomaly -> Power spectra -> Domain&Frequency average -> Write\nsyr = prd[0]\neyr = prd[1]\n\nfor dat, file in zip(data, file_list):\n precip_variability_across_timescale(\n file, syr, eyr, dfrq, mip, dat, var, fac, nperseg, noverlap, outdir, cmec\n )\n",
"userId": "ahn6"
}
}