{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import xarray as xr\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from netCDF4 import num2date\n", "#import func as f\n", "import pandas as pd\n", "from scipy.interpolate import BSpline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Copy for changing path for files local mac" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "path = '/Users/johannemehren/Desktop/filer/'\n", "era5 = xr.open_dataset(path + 'FULL-ERA5.tp.monzonmean.2000-2018.nc4')\n", "obs = xr.open_dataset(path + 'GPS-RO__CP_LR_5x5_2007-2018.nc')\n", "erai = xr.open_dataset(path + 'erai_latlon_regrid_2006-2018_3030.nc')\n", "\n", "#obs_lonav = xr.open_dataset('GPS-RO_cdo_zonmean.nc')\n", "era5_latlon = xr.open_dataset(path + 'FULL-ERA5.monthmean.2007-2018.concat_new.nc')\n", "\n", "#obs_monmean = xr.open_dataset('GPS-RO_CP_monmean_2007-2017.nc')\n", "\n", "#obs_old = xr.open_dataset('GPS-RO__LR-CP__gridded_ALL_MISSIONS_2002-2018.nc', decode_times=False)\n", "\n", "\n", "era5_regrid = xr.open_dataset(path + 'gridfile_test.nc')\n", "erai_regrid = xr.open_dataset(path + 'erai_regrid_5x5.nc')" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Wed Jan 22 11:31:46 2020: cdo remapbil,gridfile.txt FULL-ERA5.monthmean.2007-2018.concat_new.nc gridfile_test.nc\\nMon Jan 13 16:48:29 2020: ncrcat FULL-ERA5.tp.monthmean.2007-2010.nc4 FULL-ERA5.tp.monthmean.2010-2018.nc test.nc\\nGenerated from the ERA5 ECMWF 6-hourly archive on model levels\\ncreated on 07-10-2019 15:18 at LMD \\n(Bernard Legras: legras@lmd.ens.fr)\\ngenerating code: SRIP-TTL4N.py'" ] }, "execution_count": 93, "metadata": {}, "output_type": "execute_result" } ], "source": [ "era5_regrid.history" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "## Prøver gps-ro fila med grov oppløsning fra 2002-2018\n", "#ds_obs_old = obs_old.sel(lat=slice(-20,20))\n", "#ds_obs_old['time'] = pd.date_range('2002-01-01', '2018-12-31', freq='M')\n", "#obs_lonav_old = ds_obs_old.CP_T[:,:,:].mean(axis=(1,2))" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
<xarray.Dataset>\n", "Dimensions: (time: 144)\n", "Coordinates:\n", " * time (time) datetime64[ns] 2007-01-31 2007-02-28 ... 2018-12-31\n", "Data variables:\n", " CP_T (time) float32 190.36124 190.4264 191.04292 ... 190.86308 190.54231\n", " CP_z (time) float32 17.576189 17.54867 17.34725 ... 17.406546 17.607016\n", " LR_T (time) float32 191.0509 191.12128 191.66704 ... 191.44356 191.29237\n", " LR_z (time) float32 17.023983 16.95944 16.81543 ... 16.905666 16.976511" ], "text/plain": [ "
<xarray.Dataset>\n", "Dimensions: (lat: 9, lon: 72, time: 144)\n", "Coordinates:\n", " * time (time) datetime64[ns] 2007-01-16T09:00:00 ... 2018-12-16T09:00:00\n", " * lon (lon) float64 -177.5 -172.5 -167.5 ... 167.5 172.5 177.5\n", " * lat (lat) float64 -20.0 -15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0\n", "Data variables:\n", " tpp (time, lat, lon) float32 ...\n", " tpt (time, lat, lon) float32 ...\n", " tpz (time, lat, lon) float32 ...\n", " tpp2 (time, lat, lon) float32 ...\n", " tpt2 (time, lat, lon) float32 ...\n", " tpz2 (time, lat, lon) float32 ...\n", " ctpp (time, lat, lon) float32 ...\n", " ctpt (time, lat, lon) float32 ...\n", " ctpz (time, lat, lon) float32 ...\n", " zlrp (time, lat, lon) float32 ...\n", " zlrt (time, lat, lon) float32 ...\n", " zlrz (time, lat, lon) float32 ...\n", " splinezlrp (time, lat, lon) float32 ...\n", " splinezlrt (time, lat, lon) float32 ...\n", " splinezlrz (time, lat, lon) float32 ...\n", " dthetadzminp (time, lat, lon) float32 ...\n", " dthetadzmint (time, lat, lon) float32 ...\n", " dthetadzminz (time, lat, lon) float32 ...\n", " cpsmr (time, lat, lon) float32 ...\n", " occ2nd (time, lat, lon) float64 ...\n", " tpp2mtpp (time, lat, lon) float32 ...\n", " tpt2mtpt (time, lat, lon) float32 ...\n", " tpz2mtpz (time, lat, lon) float32 ...\n", " zlrsmr (time, lat, lon) float32 ...\n", "Attributes:\n", " CDI: Climate Data Interface version 1.9.6 (http://...\n", " Conventions: CF-1.6\n", " history: Wed Jan 22 12:16:51 2020: cdo remapbil,gridfi...\n", " title: ERA-Interim tropopause pressure, temperature,...\n", " NCO: netCDF Operators version 4.7.9 (Homepage = ht...\n", " history_of_appended_files: Mon Sep 30 14:13:22 2019: Appended file tp-19...\n", " CDO: Climate Data Operators version 1.9.6 (http://..." ], "text/plain": [ "