Notebook

CMIP6_CVs vs output¶

Notes¶

PJD 15 May 2024 - updated to poll atmos coordinates CMIP6:historical:Amon:cl PJD 15 May 2024 - updated to catch ALL atmos models, rather than starting at index 22

imports¶

In [1]:

%%time
import glob
import json
import os
os.sys.path.insert(0, "/p/user_pub/xclim/persist/software/xsearch/")
import xcdat as xc
import xsearch as xs

import logging
logging.getLogger("xcdat").setLevel(logging.ERROR)

CPU times: user 5.92 s, sys: 1.62 s, total: 7.54 s
Wall time: 5.89 s

read CMIP6_source_id.json¶

In [2]:

%%time
path = "/home/durack1/git/CMIP6_CVs"
file = "CMIP6_source_id.json"
with open(os.path.join(path, file), 'r') as f:
    js = json.load(f)
js.keys()
srcIds = js["source_id"]
srcIds.keys()

CPU times: user 1.15 ms, sys: 2.04 ms, total: 3.19 ms
Wall time: 13 ms

Out[2]:

dict_keys(['4AOP-v1-5', 'ACCESS-CM2', 'ACCESS-ESM1-5', 'ACCESS-OM2', 'ACCESS-OM2-025', 'ARTS-2-3', 'AWI-CM-1-1-HR', 'AWI-CM-1-1-LR', 'AWI-CM-1-1-MR', 'AWI-ESM-1-1-LR', 'AWI-ESM-1-REcoM', 'AWI-ESM-2-1-LR', 'BCC-CSM2-HR', 'BCC-CSM2-MR', 'BCC-ESM1', 'CAM-MPAS-HR', 'CAM-MPAS-LR', 'CAMS-CSM1-0', 'CAS-ESM2-0', 'CESM1-1-CAM5-CMIP5', 'CESM1-CAM5-SE-HR', 'CESM1-CAM5-SE-LR', 'CESM1-WACCM-SC', 'CESM2', 'CESM2-FV2', 'CESM2-WACCM', 'CESM2-WACCM-FV2', 'CIESM', 'CMCC-CM2-HR4', 'CMCC-CM2-SR5', 'CMCC-CM2-VHR4', 'CMCC-ESM2', 'CNRM-CM6-1', 'CNRM-CM6-1-HR', 'CNRM-ESM2-1', 'CanESM5', 'CanESM5-1', 'CanESM5-CanOE', 'E3SM-1-0', 'E3SM-1-1', 'E3SM-1-1-ECA', 'E3SM-2-0', 'E3SM-2-0-NARRM', 'E3SM-2-1', 'EC-Earth3', 'EC-Earth3-AerChem', 'EC-Earth3-CC', 'EC-Earth3-ESM-1', 'EC-Earth3-GrIS', 'EC-Earth3-HR', 'EC-Earth3-LR', 'EC-Earth3-Veg', 'EC-Earth3-Veg-LR', 'EC-Earth3P', 'EC-Earth3P-HR', 'EC-Earth3P-VHR', 'ECMWF-IFS-HR', 'ECMWF-IFS-LR', 'ECMWF-IFS-MR', 'FGOALS-f3-H', 'FGOALS-f3-L', 'FGOALS-g3', 'FIO-ESM-2-0', 'GFDL-AM4', 'GFDL-CM4', 'GFDL-CM4C192', 'GFDL-ESM2M', 'GFDL-ESM4', 'GFDL-GRTCODE', 'GFDL-OM4p5B', 'GFDL-RFM-DISORT', 'GISS-E2-1-G', 'GISS-E2-1-G-CC', 'GISS-E2-1-H', 'GISS-E2-2-G', 'GISS-E2-2-H', 'GISS-E3-G', 'HadGEM3-GC31-HH', 'HadGEM3-GC31-HM', 'HadGEM3-GC31-LL', 'HadGEM3-GC31-LM', 'HadGEM3-GC31-MH', 'HadGEM3-GC31-MM', 'HiRAM-SIT-HR', 'HiRAM-SIT-LR', 'ICON-ESM-LR', 'IITM-ESM', 'INM-CM4-8', 'INM-CM5-0', 'INM-CM5-H', 'IPSL-CM5A2-INCA', 'IPSL-CM6A-ATM-HR', 'IPSL-CM6A-ATM-ICO-HR', 'IPSL-CM6A-ATM-ICO-LR', 'IPSL-CM6A-ATM-ICO-MR', 'IPSL-CM6A-ATM-ICO-VHR', 'IPSL-CM6A-ATM-LR-REPROBUS', 'IPSL-CM6A-LR', 'IPSL-CM6A-LR-INCA', 'IPSL-CM6A-MR1', 'KACE-1-0-G', 'KIOST-ESM', 'LBLRTM-12-8', 'MCM-UA-1-0', 'MIROC-ES2H', 'MIROC-ES2H-NB', 'MIROC-ES2L', 'MIROC6', 'MPI-ESM-1-2-HAM', 'MPI-ESM1-2-HR', 'MPI-ESM1-2-LR', 'MPI-ESM1-2-XR', 'MRI-AGCM3-2-H', 'MRI-AGCM3-2-S', 'MRI-ESM2-0', 'NESM3', 'NICAM16-7S', 'NICAM16-8S', 'NICAM16-9S', 'NorCPM1', 'NorESM1-F', 'NorESM2-LM', 'NorESM2-MM', 'PCMDI-test-1-0', 'RRTMG-LW-4-91', 'RRTMG-SW-4-02', 'RTE-RRTMGP-181204', 'SAM0-UNICON', 'TaiESM1', 'TaiESM1-TIMCOM', 'TaiESM1-TIMCOM2', 'UKESM1-0-LL', 'UKESM1-1-LL', 'UKESM1-ice-LL'])

Ocean¶

extract ocean level info¶

In [3]:

native = {}
for count, srcId in enumerate(srcIds):
    tmp = srcIds[srcId]["model_component"]["ocean"]["description"]
    tmp = tmp.split(";")
    for val in tmp:
        if "levels" in val:
            #print(srcId, val[:3])
            native[srcId] = int(val[:3])

search for thetao¶

In [4]:

%%time
dpaths = xs.findPaths('historical', 'thetao', 'mon', realm='ocean', cmipTable='Omon', deduplicate=True)
#for count, sim in enumerate(dpaths):
#    print("{:03d}".format(count), sim)
#print(dpaths.keys())
#sims = xs.getValuesForFacet(dpaths, 'model', 'IPSL-CM5A2-INCA') ## 'E3SM-2-0')  # also E3SM-1-0 (E3SM-Project (1-5), UCSB, E3SM-Project), E3SM-1-1 + ECA, E3SM-2-0-NARRM
#sims

CPU times: user 49.3 ms, sys: 5.09 ms, total: 54.4 ms
Wall time: 95.2 ms

In [5]:

%%time
exp = "historical"
var = "thetao"
freq = "mon"
cmipTable = "Omon"
mipEra = "CMIP6"
firstMemberOnly = True

dpaths = xs.findPaths(exp, var, freq, cmipTable=cmipTable, mip_era=mipEra)
models = xs.natural_sort(xs.getGroupValues(dpaths, 'model'))
#print('models:', models)
#print('number of models:', len(models))

badFilesTime = [
    "/p/css03/esgf_publish/CMIP6/CMIP/EC-Earth-Consortium/EC-Earth3-AerChem/historical/r1i1p1f1/Omon/thetao/gn/v20200624/thetao_Omon_EC-Earth3-AerChem_historical_r1i1p1f1_gn_185001-185012.nc",
    "/p/css03/esgf_publish/CMIP6/CMIP/EC-Earth-Consortium/EC-Earth3-CC/historical/r1i1p1f1/Omon/thetao/gn/v20210113/thetao_Omon_EC-Earth3-CC_historical_r1i1p1f1_gn_185001-185012.nc",
    "/p/css03/esgf_publish/CMIP6/CMIP/EC-Earth-Consortium/EC-Earth3-Veg-LR/historical/r1i1p1f1/Omon/thetao/gn/v20200919/thetao_Omon_EC-Earth3-Veg-LR_historical_r1i1p1f1_gn_185001-185012.nc",
    "/p/css03/esgf_publish/CMIP6/CMIP/EC-Earth-Consortium/EC-Earth3-Veg/historical/r1i1p1f1/Omon/thetao/gn/v20211207/thetao_Omon_EC-Earth3-Veg_historical_r1i1p1f1_gn_185001-185012.nc",
    "/p/css03/scratch/cmip6/CMIP/CAS/FGOALS-f3-L/historical/r1i1p1f1/Omon/thetao/gn/v20191007/thetao_Omon_FGOALS-f3-L_historical_r1i1p1f1_gn_185001-189912.nc",
];

aveLvls = []

for count, model in enumerate(models):
    dpaths_model = xs.retainDataByFacetValue(dpaths, 'model', model)
    members = xs.natural_sort(xs.getGroupValues(dpaths_model, 'member'))
    if firstMemberOnly:
        members = members[0:1]
    #print(count, model, members)
    for member in members:
        dpaths_model_member_list = xs.getValuesForFacet(dpaths_model, 'member', member)
        if len(dpaths_model_member_list) > 1:
            print('Error: multiple paths detected for ', model, member, ': ', dpaths_model_member_list)
        else:
            dpath = dpaths_model_member_list[0]
            ncfile = xs.natural_sort(glob.glob(os.path.join(dpath, '*.nc')))[0]
        # now poll vertical axis
        ds = xc.open_dataset(ncfile, decode_times=False)
        z = xc.get_dim_coords(ds, "Z")
        natZ = int(native[model])
        if natZ < len(z):
            s = "-- misreported --"
        elif len(z) != natZ:
            s = "-- decimated --"

        else:
            s = ""
        print(count, model, members, "output:", len(z), "reported native:", natZ, s)
        aveLvls.append(len(z))

print(aveLvls)

0 ACCESS-CM2 ['r1i1p1f1'] output: 50 reported native: 50 
1 ACCESS-ESM1-5 ['r1i1p1f1'] output: 50 reported native: 50 
2 AWI-CM-1-1-MR ['r1i1p1f1'] output: 46 reported native: 46 
3 AWI-ESM-1-1-LR ['r1i1p1f1'] output: 46 reported native: 46 
4 BCC-CSM2-MR ['r1i1p1f1'] output: 40 reported native: 40 
5 BCC-ESM1 ['r1i1p1f1'] output: 40 reported native: 40 
6 CAMS-CSM1-0 ['r1i1p1f1'] output: 50 reported native: 50 
7 CanESM5 ['r1i1p1f1'] output: 45 reported native: 45 
8 CanESM5-1 ['r1i1p1f1'] output: 45 reported native: 45 
9 CanESM5-CanOE ['r1i1p2f1'] output: 45 reported native: 45 
10 CAS-ESM2-0 ['r1i1p1f1'] output: 30 reported native: 30 
11 CESM2 ['r1i1p1f1'] output: 33 reported native: 60 -- decimated --

/home/durack1/mambaforge/envs/xcd061nctax/lib/python3.11/site-packages/xarray/conventions.py:436: SerializationWarning: variable 'thetao' has multiple fill values {1e+20, 1e+20}, decoding all values to NaN.
  new_vars[k] = decode_cf_variable(

12 CESM2-FV2 ['r1i1p1f1'] output: 33 reported native: 60 -- decimated --
13 CESM2-WACCM ['r1i1p1f1'] output: 33 reported native: 60 -- decimated --
14 CESM2-WACCM-FV2 ['r1i1p1f1'] output: 33 reported native: 60 -- decimated --
15 CIESM ['r1i1p1f1'] output: 60 reported native: 46 -- misreported --
16 CMCC-CM2-HR4 ['r1i1p1f1'] output: 50 reported native: 50 
17 CMCC-CM2-SR5 ['r1i1p1f1'] output: 50 reported native: 50 
18 CMCC-ESM2 ['r1i1p1f1'] output: 50 reported native: 50 
19 CNRM-CM6-1 ['r1i1p1f2'] output: 75 reported native: 75 
20 CNRM-CM6-1-HR ['r1i1p1f2'] output: 75 reported native: 75 
21 CNRM-ESM2-1 ['r1i1p1f2'] output: 75 reported native: 75 
22 E3SM-1-0 ['r1i1p1f1'] output: 60 reported native: 60 
23 E3SM-1-1 ['r1i1p1f1'] output: 60 reported native: 60 
24 E3SM-1-1-ECA ['r1i1p1f1'] output: 60 reported native: 60 
25 E3SM-2-0 ['r1i1p1f1'] output: 60 reported native: 60 
26 E3SM-2-0-NARRM ['r1i1p1f1'] output: 60 reported native: 60 
27 EC-Earth3 ['r1i1p1f1'] output: 75 reported native: 75 
28 EC-Earth3-AerChem ['r1i1p1f1'] output: 75 reported native: 75 
29 EC-Earth3-CC ['r1i1p1f1'] output: 75 reported native: 75 
30 EC-Earth3-Veg ['r1i1p1f1'] output: 75 reported native: 75 
31 EC-Earth3-Veg-LR ['r1i1p1f1'] output: 75 reported native: 75 
32 FGOALS-f3-L ['r1i1p1f1'] output: 30 reported native: 30 
33 FGOALS-g3 ['r1i1p1f1'] output: 30 reported native: 30 
34 FIO-ESM-2-0 ['r1i1p1f1'] output: 60 reported native: 60 
35 GFDL-CM4 ['r1i1p1f1'] output: 35 reported native: 75 -- decimated --
36 GFDL-ESM4 ['r1i1p1f1'] output: 35 reported native: 75 -- decimated --
37 GISS-E2-1-G ['r1i1p1f1'] output: 40 reported native: 40 
38 GISS-E2-1-H ['r1i1p1f1'] output: 33 reported native: 33 
39 GISS-E2-2-G ['r1i1p1f1'] output: 40 reported native: 40 
40 GISS-E2-2-H ['r1i1p1f1'] output: 33 reported native: 33 
41 HadGEM3-GC31-LL ['r1i1p1f3'] output: 75 reported native: 75 
42 HadGEM3-GC31-MM ['r1i1p1f3'] output: 75 reported native: 75 
43 ICON-ESM-LR ['r1i1p1f1'] output: 64 reported native: 40 -- misreported --
44 INM-CM4-8 ['r1i1p1f1'] output: 33 reported native: 40 -- decimated --
45 INM-CM5-0 ['r1i1p1f1'] output: 33 reported native: 40 -- decimated --
46 IPSL-CM5A2-INCA ['r1i1p1f1'] output: 31 reported native: 31 
47 IPSL-CM6A-LR ['r1i1p1f1'] output: 75 reported native: 75 
48 IPSL-CM6A-LR-INCA ['r1i1p1f1'] output: 75 reported native: 75 
49 KIOST-ESM ['r1i1p1f1'] output: 52 reported native: 52 
50 MCM-UA-1-0 ['r1i1p1f1'] output: 18 reported native: 18 
51 MIROC6 ['r1i1p1f1'] output: 63 reported native: 63 
52 MIROC-ES2H ['r1i1p4f2'] output: 63 reported native: 63 
53 MIROC-ES2L ['r1i1p1f2'] output: 63 reported native: 63 
54 MPI-ESM1-2-HR ['r1i1p1f1'] output: 40 reported native: 40 
55 MPI-ESM1-2-LR ['r1i1p1f1'] output: 40 reported native: 40 
56 MPI-ESM-1-2-HAM ['r1i1p1f1'] output: 40 reported native: 40 
57 MRI-ESM2-0 ['r1i1p1f1'] output: 61 reported native: 61 
58 NESM3 ['r1i1p1f1'] output: 46 reported native: 46 
59 NorCPM1 ['r1i1p1f1'] output: 35 reported native: 53 -- decimated --
60 NorESM2-LM ['r1i1p1f1'] output: 70 reported native: 70 
61 NorESM2-MM ['r1i1p1f1'] output: 53 reported native: 70 -- decimated --
62 SAM0-UNICON ['r1i1p1f1'] output: 60 reported native: 60 
63 TaiESM1 ['r1i1p1f1'] output: 60 reported native: 60 
64 UKESM1-0-LL ['r1i1p1f2'] output: 75 reported native: 75 
65 UKESM1-1-LL ['r1i1p1f2'] output: 75 reported native: 75 
[50, 50, 46, 46, 40, 40, 50, 45, 45, 45, 30, 33, 33, 33, 33, 60, 50, 50, 50, 75, 75, 75, 60, 60, 60, 60, 60, 75, 75, 75, 75, 75, 30, 30, 60, 35, 35, 40, 33, 40, 33, 75, 75, 64, 33, 33, 31, 75, 75, 52, 18, 63, 63, 63, 40, 40, 40, 61, 46, 35, 70, 53, 60, 60, 75, 75]
CPU times: user 2.37 s, sys: 616 ms, total: 2.99 s
Wall time: 41.3 s

In [6]:

print("Average ocean levels:", (sum(aveLvls) // len(aveLvls) + 1))

Average ocean levels: 53

Atmos¶

extract atmos level info¶

In [7]:

native = {}
counter = 1
for count, srcId in enumerate(srcIds):
    tmp = srcIds[srcId]["model_component"]["atmos"]["description"]
    if tmp == "none":
        print(count, srcId, "none")
        continue
    tmp = tmp.split(";")
    for val in tmp:
        #print(srcId, val)
        if "levels" in val:
            #print(count, val)
            native[srcId] = int(val[:3])
        elif "72 vertical layers" in val:  # fudge E3SM-2-0, E3SM-2-1
            #print(count, srcId, val)
            native[srcId] = 72
        elif ". 72 vertical layers " in val:  # E3SM-2-0-NARRM
            #print(count, srcId, val)
            native[srcId] = 72

0 4AOP-v1-5 none
3 ACCESS-OM2 none
4 ACCESS-OM2-025 none
5 ARTS-2-3 none
68 GFDL-GRTCODE none
69 GFDL-OM4p5B none
70 GFDL-RFM-DISORT none
102 LBLRTM-12-8 none
124 RRTMG-LW-4-91 none
125 RRTMG-SW-4-02 none
126 RTE-RRTMGP-181204 none

search for cl¶

In [8]:

%%time
exp = "historical"
var = "cl"
freq = "mon"
cmipTable = "Amon"
mipEra = "CMIP6"
firstMemberOnly = True

dpaths = xs.findPaths(exp, var, freq, cmipTable=cmipTable, mip_era=mipEra)
models = xs.natural_sort(xs.getGroupValues(dpaths, 'model'))
#print('models:', models)
#print('number of models:', len(models))

badFilesTime = [
];

aveLvls = []

for count, model in enumerate(models):
    #if model in ["E3SM-2-0", "E3SM-2-0-NARRM"]:
    #    continue # problem with variable
    dpaths_model = xs.retainDataByFacetValue(dpaths, 'model', model)
    members = xs.natural_sort(xs.getGroupValues(dpaths_model, 'member'))
    if firstMemberOnly:
        members = members[0:1]
    #print(count, model, members)
    for member in members:
        dpaths_model_member_list = xs.getValuesForFacet(dpaths_model, 'member', member)
        if len(dpaths_model_member_list) > 1:
            print('Error: multiple paths detected for ', model, member, ': ', dpaths_model_member_list)
        else:
            dpath = dpaths_model_member_list[0]
            ncfile = xs.natural_sort(glob.glob(os.path.join(dpath, '*.nc')))[0]
        # now poll vertical axis
        ds = xc.open_dataset(ncfile, decode_times=False)
        # deal with IPSL-CM6A-LR
        if model == "IPSL-CM6A-LR":
            z = ds["presnivs"]
        else:
            z = xc.get_dim_coords(ds, "Z")
        natZ = int(native[model])
        if natZ < len(z):
            s = "-- misreported --"
        elif len(z) != natZ:
            s = "-- decimated --"

        else:
            s = ""
        print(count, model, members, "output:", len(z), "reported native:", natZ, s)
        aveLvls.append(len(z))

print(aveLvls)

0 ACCESS-CM2 ['r1i1p1f1'] output: 85 reported native: 85 
1 ACCESS-ESM1-5 ['r1i1p1f1'] output: 38 reported native: 38 
2 AWI-ESM-1-1-LR ['r1i1p1f1'] output: 47 reported native: 47 
3 BCC-CSM2-MR ['r1i1p1f1'] output: 46 reported native: 46 
4 BCC-ESM1 ['r1i1p1f1'] output: 26 reported native: 26 
5 CAMS-CSM1-0 ['r1i1p1f1'] output: 31 reported native: 31 
6 CanESM5 ['r1i1p1f1'] output: 49 reported native: 49 
7 CanESM5-1 ['r1i1p1f1'] output: 49 reported native: 49 
8 CAS-ESM2-0 ['r1i1p1f1'] output: 35 reported native: 35 
9 CESM2 ['r1i1p1f1'] output: 32 reported native: 32

/home/durack1/mambaforge/envs/xcd061nctax/lib/python3.11/site-packages/xarray/conventions.py:436: SerializationWarning: variable 'cl' has multiple fill values {1e+20, 1e+20}, decoding all values to NaN.
  new_vars[k] = decode_cf_variable(

10 CESM2-FV2 ['r1i1p1f1'] output: 32 reported native: 32 
11 CESM2-WACCM ['r1i1p1f1'] output: 70 reported native: 70 
12 CESM2-WACCM-FV2 ['r1i1p1f1'] output: 70 reported native: 70 
13 CIESM ['r1i1p1f1'] output: 30 reported native: 30 
14 CMCC-CM2-HR4 ['r1i1p1f1'] output: 26 reported native: 26 
15 CMCC-CM2-SR5 ['r1i1p1f1'] output: 30 reported native: 30 
16 CMCC-ESM2 ['r1i1p1f1'] output: 30 reported native: 30 
17 CNRM-CM6-1 ['r1i1p1f2'] output: 91 reported native: 91 
18 CNRM-CM6-1-HR ['r1i1p1f2'] output: 91 reported native: 91 
19 CNRM-ESM2-1 ['r1i1p1f2'] output: 91 reported native: 91 
20 E3SM-1-0 ['r1i1p1f1'] output: 72 reported native: 72 
21 E3SM-1-1 ['r1i1p1f1'] output: 72 reported native: 72 
22 E3SM-1-1-ECA ['r1i1p1f1'] output: 72 reported native: 72 
23 E3SM-2-0 ['r1i1p1f1'] output: 72 reported native: 72 
24 E3SM-2-0-NARRM ['r1i1p1f1'] output: 72 reported native: 72 
25 EC-Earth3 ['r10i1p1f1'] output: 91 reported native: 91 
26 EC-Earth3-AerChem ['r1i1p1f1'] output: 91 reported native: 91 
27 FGOALS-f3-L ['r1i1p1f1'] output: 32 reported native: 32 
28 FGOALS-g3 ['r1i1p1f1'] output: 26 reported native: 26 
29 GFDL-CM4 ['r1i1p1f1'] output: 33 reported native: 33 
30 GFDL-ESM4 ['r1i1p1f1'] output: 49 reported native: 49 
31 GISS-E2-1-G ['r1i1p1f1'] output: 29 reported native: 40 -- decimated --
32 GISS-E2-1-H ['r1i1p1f1'] output: 29 reported native: 40 -- decimated --
33 GISS-E2-2-G ['r1i1p1f1'] output: 102 reported native: 10 -- misreported --
34 GISS-E2-2-H ['r1i1p1f1'] output: 102 reported native: 10 -- misreported --
35 HadGEM3-GC31-LL ['r1i1p1f3'] output: 85 reported native: 85 
36 HadGEM3-GC31-MM ['r1i1p1f3'] output: 85 reported native: 85 
37 IPSL-CM6A-LR ['r1i1p1f1'] output: 79 reported native: 79 
38 IPSL-CM6A-LR-INCA ['r1i1p1f1'] output: 79 reported native: 79 
39 KACE-1-0-G ['r1i1p1f1'] output: 85 reported native: 85 
40 MCM-UA-1-0 ['r1i1p1f1'] output: 19 reported native: 14 -- misreported --
41 MIROC6 ['r1i1p1f1'] output: 81 reported native: 81 
42 MIROC-ES2H ['r1i1p1f2'] output: 81 reported native: 81 
43 MIROC-ES2L ['r1i1p1f2'] output: 40 reported native: 40 
44 MPI-ESM1-2-HR ['r1i1p1f1'] output: 95 reported native: 95 
45 MPI-ESM1-2-LR ['r1i1p1f1'] output: 47 reported native: 47 
46 MPI-ESM-1-2-HAM ['r1i1p1f1'] output: 47 reported native: 47 
47 MRI-ESM2-0 ['r1i1p1f1'] output: 80 reported native: 80 
48 NESM3 ['r1i1p1f1'] output: 47 reported native: 47 
49 NorESM2-LM ['r1i1p1f1'] output: 32 reported native: 32 
50 NorESM2-MM ['r1i1p1f1'] output: 32 reported native: 32 
51 SAM0-UNICON ['r1i1p1f1'] output: 30 reported native: 30 
52 TaiESM1 ['r1i1p1f1'] output: 30 reported native: 30 
53 UKESM1-0-LL ['r1i1p1f2'] output: 85 reported native: 85 
[85, 38, 47, 46, 26, 31, 49, 49, 35, 32, 32, 70, 70, 30, 26, 30, 30, 91, 91, 91, 72, 72, 72, 72, 72, 91, 91, 32, 26, 33, 49, 29, 29, 102, 102, 85, 85, 79, 79, 85, 19, 81, 81, 40, 95, 47, 47, 80, 47, 32, 32, 30, 30, 85]
CPU times: user 1.53 s, sys: 521 ms, total: 2.05 s
Wall time: 47.3 s

In [9]:

print("Average atmos levels:", (sum(aveLvls) // len(aveLvls) + 1))

Average atmos levels: 58