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#!/usr/bin/env python |
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# vim: set fileencoding=utf-8 |
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"""SCIAMACHY level 2 data post processing |
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Main script for SCIAMACHY orbital retrieval post processing |
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and data combining (to netcdf). |
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Copyright (c) 2018 Stefan Bender |
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This file is part of sciapy. |
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sciapy is free software: you can redistribute it or modify it |
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under the terms of the GNU General Public License as published by |
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the Free Software Foundation, version 2. |
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See accompanying LICENSE file or http://www.gnu.org/licenses/gpl-2.0.html. |
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""" |
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from __future__ import absolute_import, division, print_function |
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import glob |
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import os |
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import argparse as ap |
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import datetime as dt |
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import logging |
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import numpy as np |
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import pandas as pd |
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import xarray as xr |
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from scipy.interpolate import interp1d |
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try: |
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import pysolar.solar as sol |
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sun_alt_func = sol.get_altitude |
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except ImportError: # pysolar 0.6 (for python 2) |
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import Pysolar.solar as sol |
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sun_alt_func = sol.GetAltitude |
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import sciapy.level1c as sl |
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from sciapy.level2 import density_pp as sd |
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from sciapy.level2 import scia_akm as sa |
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from sciapy.level2.igrf import gmag_igrf |
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from sciapy.level2.aacgm2005 import gmag_aacgm2005 |
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from nrlmsise00 import msise_flat as msise |
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try: |
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from sciapy.level2.noem import noem_cpp |
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except ImportError: |
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noem_cpp = None |
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this_dir = os.path.realpath(os.path.dirname(__file__)) |
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f107_data = dict(np.genfromtxt( |
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os.path.join(this_dir, "../data/indices/f107_noontime_flux_obs.txt"), |
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usecols=[0, 2], dtype=None)) |
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f107a_data = dict(np.genfromtxt( |
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os.path.join(this_dir, "../data/indices/f107a_noontime_flux_obs.txt"), |
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usecols=[0, 2], dtype=None)) |
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ap_data = dict(np.genfromtxt( |
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os.path.join(this_dir, "../data/indices/spidr_ap_2000-2012.dat"), |
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usecols=[0, 2], dtype=None)) |
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f107_adj = dict(np.genfromtxt( |
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os.path.join(this_dir, "../data/indices/spidr_f107_2000-2012.dat"), |
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usecols=[0, 2], dtype=None)) |
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kp_data = dict(np.genfromtxt( |
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os.path.join(this_dir, "../data/indices/spidr_kp_2000-2012.dat"), |
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usecols=[0, 2], dtype=None)) |
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phi_fac = 11.91 |
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lst_fac = -0.62 |
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View Code Duplication |
def read_spectra(year, orbit, spec_base=None, skip_upleg=True): |
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"""Read and examine SCIAMACHY orbit spectra |
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Reads the limb spactra and extracts the dates, times, latitudes, |
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longitudes to be used to re-assess the retrieved geolocations. |
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Parameters |
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---------- |
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year: int |
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The measurement year to select the corresponding subdir |
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below `spec_base` (see below). |
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orbit: int |
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SCIAMACHY/Envisat orbit number of the spectra. |
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spec_base: str, optional |
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The root path to the level 1c spectra. Uses the current |
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dir if not set or set to `None` (default). |
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skip_upleg: bool, optional |
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Skip upleg limb scans, i.e. night time scans. For NO retrievals, |
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those are not used and should be not used here. |
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Default: True |
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Returns |
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------- |
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(dts, times, lats, lons, mlsts, alsts, eotcorr) |
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""" |
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fail = (None,) * 7 |
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if spec_base is None: |
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spec_base = os.curdir |
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spec_path = "{0}/{1}".format(spec_base.rstrip('/'), year) |
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spec_path2 = "{0}/{1}".format(spec_base.rstrip('/'), int(year) + 1) |
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logging.debug("spec_path: %s", spec_path) |
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logging.debug("spec_path2: %s", spec_path) |
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if not (os.path.isdir(spec_path) or os.path.isdir(spec_path2)): |
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return fail |
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# the star stands for the (optional) date subdir |
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# to find all spectra for the orbit |
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spfiles = glob.glob( |
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'{0}/*/SCIA_limb_*_1_0_{1:05d}.dat.l_mpl_binary' |
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.format(spec_path, orbit)) |
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# sometimes for whatever reason the orbit ends up in the wrong year subdir |
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# looks in the subdir for the following year as well. |
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spfiles += glob.glob( |
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'{0}/*/SCIA_limb_*_1_0_{1:05d}.dat.l_mpl_binary' |
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.format(spec_path2, orbit)) |
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spdict = dict([(fn, os.path.basename(fn).split('_')[2:4]) |
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for fn in spfiles]) |
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logging.debug("spdict: %s", spdict) |
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if len(spfiles) < 2: |
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return fail |
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sorted_spdkeys = sorted(spdict.keys()) |
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slscans = [sl.scia_limb_scan() for _ in spdict] |
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[s.read_from_file(f) for s, f in zip(slscans, sorted_spdkeys)] |
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lsts = [(s.cent_lat_lon[:2], |
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s.local_solar_time(False), |
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s.limb_data.tp_lat) |
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for s in slscans] |
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lstdict = dict(zip(sorted_spdkeys, lsts)) |
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logging.debug("lstdict: %s", lstdict) |
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dts = [] |
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times = [] |
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lats = [] |
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lons = [] |
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mlsts = [] |
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alsts = [] |
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for key in sorted_spdkeys: |
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(lat, lon), (mlst, alst, eotcorr), tp_lats = lstdict[key] |
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logging.debug("lat: %s, lon: %s", lat, lon) |
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if skip_upleg and ((tp_lats[1] - tp_lats[-2]) < 0.5): |
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# Exclude non-downleg measurements where the latitude |
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# of the last real tangent point (the last is dark sky) |
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# is larger than or too close to the first latitude. |
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# Requires an (empirical) separation of +0.5 degree. |
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logging.debug("excluding upleg point at: %s, %s", lat, lon) |
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continue |
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dtdate = pd.to_datetime(''.join(spdict[key]), |
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format="%Y%m%d%H%M%S", utc=True) |
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time_hour = dtdate.hour + dtdate.minute / 60.0 + dtdate.second / 3600.0 |
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logging.debug("mean lst: %s, apparent lst: %s, EoT: %s", mlst, alst, eotcorr) |
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dts.append(dtdate) |
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times.append(time_hour) |
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lats.append(lat) |
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lons.append(lon) |
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mlsts.append(mlst) |
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alsts.append(alst) |
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if len(lats) < 2: |
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# interpolation will fail with less than 2 points |
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return fail |
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return (np.asarray(dts), |
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np.asarray(times), |
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np.asarray(lats), |
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np.asarray(lons), |
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np.asarray(mlsts), |
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np.asarray(alsts), eotcorr) |
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View Code Duplication |
def process_orbit(orbit, |
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ref_date="1950-01-01", |
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dens_path=None, spec_base=None): |
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"""Post process retrieved SCIAMACHY orbit |
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Parameters |
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---------- |
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orbit: int |
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SCIAMACHY/Envisat orbit number of the results to process. |
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ref_date: str, optional |
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Base date to calculate the relative days from, |
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of the format "%Y-%m-%d". Default: 1950-01-01 |
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dens_path: str, optional |
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The path to the level 2 data. Uses the current |
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dir if not set or set to `None` (default). |
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spec_base: str, optional |
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The root path to the level 1c spectra. Uses the current |
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dir if not set or set to `None` (default). |
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Returns |
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------- |
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(dts0, time0, lst0, lon0, sdd): tuple |
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dts0 - days since ref_date at equator crossing (float) |
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time0 - utc hour into the day at equator crossing (float) |
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lst0 - apparent local solar time at the equator (float) |
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lon0 - longitude of the equator crossing (float) |
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sdd - `scia_density_pp` instance of the post-processed data |
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""" |
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fail = (None,) * 5 |
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logging.debug("processing orbit: %s", orbit) |
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dtrefdate = pd.to_datetime(ref_date, format="%Y-%m-%d", utc=True) |
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dfiles = glob.glob( |
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"{0}/000NO_orbit_{1:05d}_*_Dichten.txt" |
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.format(dens_path, orbit)) |
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if len(dfiles) < 1: |
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return fail |
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logging.debug("dfiles: %s", dfiles) |
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logging.debug("splits: %s", [fn.split('/') for fn in dfiles]) |
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ddict = dict([(fn, (fn.split('/')[-3:-1] + fn.split('/')[-1].split('_')[3:4])) |
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for fn in dfiles]) |
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logging.debug("ddict: %s", ddict) |
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year = ddict[sorted(ddict.keys())[0]][-1][:4] |
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logging.debug("year: %s", year) |
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dts, times, lats, lons, mlsts, alsts, eotcorr = \ |
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read_spectra(year, orbit, spec_base) |
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if dts is None: |
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# return early if reading the spectra failed |
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return fail |
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dts = pd.to_datetime(dts) - dtrefdate |
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dts = np.array([dtd.days + dtd.seconds / 86400. for dtd in dts]) |
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logging.debug("lats: %s, lons: %s, times: %s", lats, lons, times) |
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sdd = sd.scia_densities_pp(ref_date=ref_date) |
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sdd.read_from_file(dfiles[0]) |
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logging.debug("density lats: %s, lons: %s", sdd.lats, sdd.lons) |
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# longitudes |
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clons_retr_interpf = interp1d(lats[::-1], np.cos(np.radians(lons[::-1])), fill_value="extrapolate") |
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slons_retr_interpf = interp1d(lats[::-1], np.sin(np.radians(lons[::-1])), fill_value="extrapolate") |
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# apparent local solar time (EoT corrected) |
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clst_retr_interpf = interp1d(lats[::-1], np.cos(np.pi / 12. * alsts[::-1]), fill_value="extrapolate") |
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slst_retr_interpf = interp1d(lats[::-1], np.sin(np.pi / 12. * alsts[::-1]), fill_value="extrapolate") |
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# mean local solar time |
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cmst_retr_interpf = interp1d(lats[::-1], np.cos(np.pi / 12. * mlsts[::-1]), fill_value="extrapolate") |
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smst_retr_interpf = interp1d(lats[::-1], np.sin(np.pi / 12. * mlsts[::-1]), fill_value="extrapolate") |
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# utc time (day) |
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ctime_retr_interpf = interp1d(lats[::-1], np.cos(np.pi / 12. * times[::-1]), fill_value="extrapolate") |
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stime_retr_interpf = interp1d(lats[::-1], np.sin(np.pi / 12. * times[::-1]), fill_value="extrapolate") |
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dts_retr_interpf = interp1d(lats[::-1], dts[::-1], fill_value="extrapolate") |
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# equator values |
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lon0 = np.degrees(np.arctan2(slons_retr_interpf(0.), clons_retr_interpf(0.)) % (2. * np.pi)) |
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lst0 = (np.arctan2(slst_retr_interpf(0.), clst_retr_interpf(0.)) % (2. * np.pi)) * 12. / np.pi |
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mst0 = (np.arctan2(smst_retr_interpf(0.), cmst_retr_interpf(0.)) % (2. * np.pi)) * 12. / np.pi |
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time0 = (np.arctan2(stime_retr_interpf(0.), ctime_retr_interpf(0.)) % (2. * np.pi)) * 12. / np.pi |
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dts_retr_interp0 = dts_retr_interpf(0.) |
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logging.debug("utc day at equator: %s", dts_retr_interp0) |
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logging.debug("mean LST at equator: %s, apparent LST at equator: %s", mst0, lst0) |
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sdd.utchour = (np.arctan2(stime_retr_interpf(sdd.lats), |
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ctime_retr_interpf(sdd.lats)) % (2. * np.pi)) * 12. / np.pi |
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sdd.utcdays = dts_retr_interpf(sdd.lats) |
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if sdd.lons is None: |
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# recalculate the longitudes |
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# estimate the equatorial longitude from the |
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# limb scan latitudes and longitudes |
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lon0s_tp = lons - phi_fac * np.tan(np.radians(lats)) |
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clon0s_tp = np.cos(np.radians(lon0s_tp)) |
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slon0s_tp = np.sin(np.radians(lon0s_tp)) |
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lon0_tp = np.arctan2(np.sum(slon0s_tp[1:-1]), np.sum(clon0s_tp[1:-1])) |
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lon0_tp = np.degrees((lon0_tp + 2. * np.pi) % (2. * np.pi)) |
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logging.info("lon0: %s", lon0) |
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266
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|
logging.info("lon0 tp: %s", lon0_tp) |
|
267
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|
|
# interpolate to the retrieval latitudes |
|
268
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|
|
tg_retr_lats = np.tan(np.radians(sdd.lats)) |
|
269
|
|
|
calc_lons = (tg_retr_lats * phi_fac + lon0) % 360. |
|
270
|
|
|
calc_lons_tp = (tg_retr_lats * phi_fac + lon0_tp) % 360. |
|
271
|
|
|
sdd.lons = calc_lons_tp |
|
272
|
|
|
logging.debug("(calculated) retrieval lons: %s, %s", |
|
273
|
|
|
calc_lons, calc_lons_tp) |
|
274
|
|
|
else: |
|
275
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|
#sdd.lons = sdd.lons % 360. |
|
276
|
|
|
logging.debug("(original) retrieval lons: %s", sdd.lons) |
|
277
|
|
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|
278
|
|
|
sdd.mst = (sdd.utchour + sdd.lons / 15.) % 24. |
|
279
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|
sdd.lst = sdd.mst + eotcorr / 60. |
|
280
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281
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dt_date_this = dt.timedelta(np.asscalar(dts_retr_interp0)) + dtrefdate |
|
282
|
|
|
logging.info("date: %s", dt_date_this) |
|
283
|
|
|
# caclulate geomagnetic coordinates |
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284
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|
|
sdd.gmlats, sdd.gmlons = gmag_igrf(dt_date_this, sdd.lats, sdd.lons, alt=100.) |
|
285
|
|
|
logging.debug("geomag. lats: %s, lons: %s", sdd.gmlats, sdd.gmlons) |
|
286
|
|
|
sdd.aacgmgmlats, sdd.aacgmgmlons = gmag_aacgm2005(sdd.lats, sdd.lons) |
|
287
|
|
|
logging.debug("aacgm geomag. lats: %s, lons: %s", |
|
288
|
|
|
sdd.aacgmgmlats, sdd.aacgmgmlons) |
|
289
|
|
|
|
|
290
|
|
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# current day for MSIS input |
|
291
|
|
|
msis_dtdate = dt.timedelta(np.asscalar(dts_retr_interp0)) + dtrefdate |
|
292
|
|
|
msis_dtdate1 = msis_dtdate - dt.timedelta(days=1) |
|
293
|
|
|
msis_date = msis_dtdate.strftime("%Y-%m-%d").encode() |
|
294
|
|
|
msis_date1 = msis_dtdate1.strftime("%Y-%m-%d").encode() |
|
295
|
|
|
msis_f107 = f107_data[msis_date1] |
|
296
|
|
|
msis_f107a = f107a_data[msis_date] |
|
297
|
|
|
msis_ap = ap_data[msis_date] |
|
298
|
|
|
logging.debug("MSIS date: %s, f10.7a: %s, f10.7: %s, ap: %s", |
|
299
|
|
|
msis_date, msis_f107a, msis_f107, msis_ap) |
|
300
|
|
|
|
|
301
|
|
|
# previous day for NOEM input |
|
302
|
|
|
noem_date = (dt.timedelta(np.asscalar(dts_retr_interp0) - 1) + |
|
303
|
|
|
dtrefdate).strftime("%Y-%m-%d").encode() |
|
304
|
|
|
noem_f107 = f107_adj[noem_date] |
|
305
|
|
|
noem_kp = kp_data[noem_date] |
|
306
|
|
|
logging.debug("NOEM date: %s, f10.7: %s, kp: %s", |
|
307
|
|
|
noem_date, noem_f107, noem_kp) |
|
308
|
|
|
|
|
309
|
|
|
if sdd.noem_no is None: |
|
310
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|
|
sdd.noem_no = np.zeros_like(sdd.densities) |
|
311
|
|
|
if sdd.temperature is None: |
|
312
|
|
|
sdd.temperature = np.zeros_like(sdd.densities) |
|
313
|
|
|
if sdd.sza is None: |
|
314
|
|
|
sdd.sza = np.zeros_like(sdd.lats) |
|
315
|
|
|
if sdd.akdiag is None: |
|
316
|
|
|
sdd.akdiag = np.zeros_like(sdd.densities) |
|
317
|
|
|
akm_filename = glob.glob( |
|
318
|
|
|
"{0}/000NO_orbit_{1:05d}_*_AKM*" |
|
319
|
|
|
.format(dens_path, orbit))[0] |
|
320
|
|
|
logging.debug("ak file: %s", akm_filename) |
|
321
|
|
|
ak = sa.read_akm(akm_filename, sdd.nalt, sdd.nlat) |
|
322
|
|
|
logging.debug("ak data: %s", ak) |
|
323
|
|
|
sdd.akdiag = ak.diagonal(axis1=1, axis2=3).diagonal(axis1=0, axis2=1) |
|
324
|
|
|
|
|
325
|
|
|
_msis_d_t = msise( |
|
326
|
|
|
msis_dtdate, |
|
327
|
|
|
sdd.alts[None, :], sdd.lats[:, None], sdd.lons[:, None] % 360., |
|
328
|
|
|
msis_f107a, msis_f107, msis_ap, |
|
329
|
|
|
lst=sdd.lst[:, None], |
|
330
|
|
|
) |
|
331
|
|
|
sdd.dens_tot = np.sum(_msis_d_t[:, :, np.r_[:5, 6:9]], axis=2) |
|
332
|
|
|
sdd.temperature = _msis_d_t[:, :, -1] |
|
333
|
|
|
for i, lat in enumerate(sdd.lats): |
|
334
|
|
|
if noem_cpp is not None: |
|
335
|
|
|
sdd.noem_no[i] = noem_cpp(noem_date.decode(), sdd.alts, |
|
336
|
|
|
[lat], [sdd.lons[i]], noem_f107, noem_kp)[:] |
|
337
|
|
|
else: |
|
338
|
|
|
sdd.noem_no[i][:] = np.nan |
|
339
|
|
|
sdd.sza[i] = 90. - sun_alt_func(lat, sdd.lons[i], |
|
340
|
|
|
dt.timedelta(np.asscalar(sdd.utcdays[i])) + dtrefdate, |
|
341
|
|
|
elevation=sdd.alts.mean() * 1000.) |
|
342
|
|
|
sdd.vmr = sdd.densities / sdd.dens_tot * 1.e9 # ppb |
|
343
|
|
|
return dts_retr_interp0, time0, lst0, lon0, sdd |
|
344
|
|
|
|
|
345
|
|
View Code Duplication |
def get_orbits_from_date(date, mlt=False, path=None, L2_version="v6.2"): |
|
|
|
|
|
|
346
|
|
|
"""Find SCIAMACHY orbits with retrieved data at a date |
|
347
|
|
|
|
|
348
|
|
|
Parameters |
|
349
|
|
|
---------- |
|
350
|
|
|
date: str |
|
351
|
|
|
The date in the format "%Y-%m-%d". |
|
352
|
|
|
mlt: bool, optional |
|
353
|
|
|
Look for MLT mode data instead of nominal mode data. |
|
354
|
|
|
Increases the heuristics to find all MLT orbits. |
|
355
|
|
|
path: str, optional |
|
356
|
|
|
The path to the level 2 data. If `None` tries to infer |
|
357
|
|
|
the data directory from the L2 version using |
|
358
|
|
|
'./*<L2_version>'. Default: None |
|
359
|
|
|
|
|
360
|
|
|
Returns |
|
361
|
|
|
------- |
|
362
|
|
|
orbits: list |
|
363
|
|
|
List of found orbits with retrieved data files |
|
364
|
|
|
""" |
|
365
|
|
|
logging.debug("pre-processing: %s", date) |
|
366
|
|
|
if path is None: |
|
367
|
|
|
density_base = os.curdir |
|
368
|
|
|
path = "{0}/*{1}".format(density_base, L2_version) |
|
369
|
|
|
logging.debug("path: %s", path) |
|
370
|
|
|
|
|
371
|
|
|
dfiles = glob.glob("{0}/000NO_orbit_*_{1}_Dichten.txt".format( |
|
372
|
|
|
path, date.replace("-", ""))) |
|
373
|
|
|
orbits = sorted([int(os.path.basename(df).split('_')[2]) for df in dfiles]) |
|
374
|
|
|
if mlt: |
|
375
|
|
|
orbits.append(orbits[-1] + 1) |
|
376
|
|
|
return orbits |
|
377
|
|
|
|
|
378
|
|
View Code Duplication |
def combine_orbit_data(orbits, |
|
|
|
|
|
|
379
|
|
|
ref_date="1950-01-01", |
|
380
|
|
|
L2_version="v6.2", file_version="2.3", |
|
381
|
|
|
dens_path=None, spec_base=None, |
|
382
|
|
|
use_xarray=False, save_nc=False): |
|
383
|
|
|
"""Combine post-processed SCIAMACHY retrieved orbit data |
|
384
|
|
|
|
|
385
|
|
|
Parameters |
|
386
|
|
|
---------- |
|
387
|
|
|
orbits: list |
|
388
|
|
|
List of SCIAMACHY/Envisat orbit numbers to process. |
|
389
|
|
|
ref_date: str, optional |
|
390
|
|
|
Base date to calculate the relative days from, |
|
391
|
|
|
of the format "%Y-%m-%d". Default: 1950-01-01 |
|
392
|
|
|
L2_version: str, optional |
|
393
|
|
|
SCIAMACHY level 2 data version to process |
|
394
|
|
|
file_version: str, optional |
|
395
|
|
|
Postprocessing format version of the output data |
|
396
|
|
|
dens_path: str, optional |
|
397
|
|
|
The path to the level 2 data. If `None` tries to infer |
|
398
|
|
|
the data directory from the L2 version looking for anything |
|
399
|
|
|
in the current directory that ends in <L2_version>: './*<L2_version>'. |
|
400
|
|
|
Default: None |
|
401
|
|
|
spec_base: str, optional |
|
402
|
|
|
The root path to the level 1c spectra. Uses the current |
|
403
|
|
|
dir if not set or set to `None` (default). |
|
404
|
|
|
use_xarray: bool, optional |
|
405
|
|
|
Uses xarray (if available) to combine the orbital data. |
|
406
|
|
|
save_nc: bool, optional |
|
407
|
|
|
Save the intermediate orbit data sets to netcdf files |
|
408
|
|
|
for debugging. |
|
409
|
|
|
|
|
410
|
|
|
Returns |
|
411
|
|
|
------- |
|
412
|
|
|
(sdday, sdday_ds): tuple |
|
413
|
|
|
`sdday` contains the combined data as a `scia_density_day` instance, |
|
414
|
|
|
`sdday_ds` contains the same data as a `xarray.Dataset`. |
|
415
|
|
|
""" |
|
416
|
|
|
if dens_path is None: |
|
417
|
|
|
# try some heuristics |
|
418
|
|
|
density_base = os.curdir |
|
419
|
|
|
dens_path = "{0}/*{1}".format(density_base, L2_version) |
|
420
|
|
|
|
|
421
|
|
|
sdday = sd.scia_density_day(ref_date=ref_date) |
|
422
|
|
|
sddayl = [] |
|
423
|
|
|
sdday_ds = None |
|
424
|
|
|
for orbit in sorted(orbits): |
|
425
|
|
|
dateo, timeo, lsto, lono, sdens = process_orbit(orbit, |
|
426
|
|
|
ref_date=ref_date, dens_path=dens_path, spec_base=spec_base) |
|
427
|
|
|
logging.info("orbit: %s, eq. date: %s, eq. hour: %s, eq. app. lst: %s, eq. lon: %s", |
|
428
|
|
|
orbit, dateo, timeo, lsto, lono) |
|
429
|
|
|
if sdens is not None: |
|
430
|
|
|
sdens.version = file_version |
|
431
|
|
|
sdens.data_version = L2_version |
|
432
|
|
|
sdday.append_data(dateo, orbit, timeo, sdens) |
|
433
|
|
|
if use_xarray: |
|
434
|
|
|
sd_xr = sdens.to_xarray(dateo, orbit) |
|
435
|
|
|
if sd_xr is not None: |
|
436
|
|
|
logging.debug("orbit %s dataset: %s", orbit, sd_xr) |
|
437
|
|
|
sddayl.append(sd_xr) |
|
438
|
|
|
if save_nc: |
|
439
|
|
|
sdens.write_to_netcdf(sdens.filename[:-3] + "nc") |
|
440
|
|
|
if use_xarray and sddayl: |
|
441
|
|
|
sdday_ds = xr.concat(sddayl, dim="time") |
|
442
|
|
|
return sdday, sdday_ds |
|
443
|
|
|
|
|
444
|
|
View Code Duplication |
def sddata_xr_set_attrs(sdday_xr, ref_date="1950-01-01", rename=True): |
|
|
|
|
|
|
445
|
|
|
"""Customize xarray Dataset variables and attributes |
|
446
|
|
|
|
|
447
|
|
|
Changes the variable names to match those exported from the |
|
448
|
|
|
`scia_density_day` class. |
|
449
|
|
|
|
|
450
|
|
|
Parameters |
|
451
|
|
|
---------- |
|
452
|
|
|
sdday_xr: xarray.Dataset instance |
|
453
|
|
|
ref_date: str, optional |
|
454
|
|
|
Base date to calculate the relative days from, |
|
455
|
|
|
of the format "%Y-%m-%d". Default: 1950-01-01 |
|
456
|
|
|
rename: bool, optional |
|
457
|
|
|
Rename the dataset variables to match the |
|
458
|
|
|
`scia_density_day` exported ones. |
|
459
|
|
|
""" |
|
460
|
|
|
if rename: |
|
461
|
|
|
sdday_xr = sdday_xr.rename({ |
|
462
|
|
|
"density": "NO_DENS", "density_air": "TOT_DENS", |
|
463
|
|
|
"apriori": "NO_APRIORI", "error_meas": "NO_ERR", |
|
464
|
|
|
"error_tot": "NO_ETOT", |
|
465
|
|
|
"NOEM_density": "NO_NOEM", "akm_diagonal": "NO_AKDIAG", |
|
466
|
|
|
"VMR": "NO_VMR", "temperature": "T_MSIS", |
|
467
|
|
|
"utc_hour": "UTC", "mean_sza": "mean_SZA", |
|
468
|
|
|
"app_lst": "app_LST", "mean_lst": "mean_LST", |
|
469
|
|
|
}) |
|
470
|
|
|
sdday_xr["NO_RSTD"] = 100 * np.abs(sdday_xr.NO_ERR / sdday_xr.NO_DENS) |
|
471
|
|
|
sdday_xr["NO_RSTD"].attrs = dict(units='%', |
|
472
|
|
|
long_name='NO relative standard deviation') |
|
473
|
|
|
# fix coordinate attributes |
|
474
|
|
|
sdday_xr["time"].attrs = dict(axis='T', standard_name='time', |
|
475
|
|
|
calendar='standard', long_name='equatorial crossing time', |
|
476
|
|
|
units="days since {0}".format( |
|
477
|
|
|
pd.to_datetime(ref_date).isoformat(sep=" "))) |
|
478
|
|
|
sdday_xr["orbit"].attrs = dict(axis='T', calendar='standard', |
|
479
|
|
|
long_name='SCIAMACHY/Envisat orbit number', units='1') |
|
480
|
|
|
sdday_xr["altitude"].attrs = dict(axis='Z', positive='up', |
|
481
|
|
|
long_name='altitude', standard_name='altitude', units='km') |
|
482
|
|
|
sdday_xr["latitude"].attrs = dict(axis='Y', long_name='latitude', |
|
483
|
|
|
standard_name='latitude', units='degrees_north') |
|
484
|
|
|
sdday_xr["longitude"].attrs = dict(long_name='longitude', |
|
485
|
|
|
standard_name='longitude', units='degrees_east') |
|
486
|
|
|
dateo = (pd.to_datetime( |
|
487
|
|
|
xr.conventions.decode_cf_variable("date", sdday_xr.time).data[0]) |
|
488
|
|
|
.strftime("%Y-%m-%d")) |
|
489
|
|
|
logging.debug("date %s dataset: %s", dateo, sdday_xr) |
|
490
|
|
|
return sdday_xr |
|
491
|
|
|
|
|
492
|
|
View Code Duplication |
def main(): |
|
|
|
|
|
|
493
|
|
|
logging.basicConfig(level=logging.WARNING, |
|
494
|
|
|
format="[%(levelname)-8s] (%(asctime)s) " |
|
495
|
|
|
"%(filename)s:%(lineno)d %(message)s", |
|
496
|
|
|
datefmt="%Y-%m-%d %H:%M:%S %z") |
|
497
|
|
|
|
|
498
|
|
|
parser = ap.ArgumentParser() |
|
499
|
|
|
parser.add_argument("file", default="SCIA_NO.nc", help="the filename of the output netcdf file") |
|
500
|
|
|
parser.add_argument("-M", "--month", metavar="YEAR-MM", |
|
501
|
|
|
help="infer start and end dates for month") |
|
502
|
|
|
parser.add_argument("-D", "--date_range", metavar="START_DATE:END_DATE", |
|
503
|
|
|
help="colon-separated start and end dates") |
|
504
|
|
|
parser.add_argument("-d", "--dates", help="comma-separated list of dates") |
|
505
|
|
|
parser.add_argument("-f", "--orbit_file", help="the file containing the input orbits") |
|
506
|
|
|
parser.add_argument("-p", "--path", default=None, help="path containing the L2 data") |
|
507
|
|
|
parser.add_argument("-r", "--retrieval_version", default="v6.2", |
|
508
|
|
|
help="SCIAMACHY level 2 data version to process") |
|
509
|
|
|
parser.add_argument("-R", "--file_version", default="2.3", |
|
510
|
|
|
help="Postprocessing format version of the output file") |
|
511
|
|
|
parser.add_argument("-s", "--spectra", default=None, |
|
512
|
|
|
help="path containing the L1c spectra") |
|
513
|
|
|
parser.add_argument("-m", "--mlt", action="store_true", default=False, |
|
514
|
|
|
help="indicate nominal (False, default) or MLT data (True)") |
|
515
|
|
|
parser.add_argument("-X", "--xarray", action="store_true", default=False, |
|
516
|
|
|
help="use xarray to prepare the dataset (experimental, default %(default)s)") |
|
517
|
|
|
loglevels = parser.add_mutually_exclusive_group() |
|
518
|
|
|
loglevels.add_argument("-l", "--loglevel", default="WARNING", |
|
519
|
|
|
choices=['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'], |
|
520
|
|
|
help="change the loglevel (default: 'WARNING')") |
|
521
|
|
|
loglevels.add_argument("-q", "--quiet", action="store_true", default=False, |
|
522
|
|
|
help="less output, same as --loglevel=ERROR (default: False)") |
|
523
|
|
|
loglevels.add_argument("-v", "--verbose", action="store_true", default=False, |
|
524
|
|
|
help="verbose output, same as --loglevel=INFO (default: False)") |
|
525
|
|
|
args = parser.parse_args() |
|
526
|
|
|
if args.quiet: |
|
527
|
|
|
logging.getLogger().setLevel(logging.ERROR) |
|
528
|
|
|
elif args.verbose: |
|
529
|
|
|
logging.getLogger().setLevel(logging.INFO) |
|
530
|
|
|
else: |
|
531
|
|
|
logging.getLogger().setLevel(args.loglevel) |
|
532
|
|
|
|
|
533
|
|
|
logging.info("processing L2 version: %s", args.retrieval_version) |
|
534
|
|
|
logging.info("writing data file version: %s", args.file_version) |
|
535
|
|
|
|
|
536
|
|
|
pddrange = [] |
|
537
|
|
|
if args.month is not None: |
|
538
|
|
|
d0 = pd.to_datetime(args.month + "-01") |
|
539
|
|
|
pddrange += pd.date_range(d0, d0 + pd.tseries.offsets.MonthEnd()) |
|
540
|
|
|
if args.date_range is not None: |
|
541
|
|
|
pddrange += pd.date_range(*args.date_range.split(':')) |
|
542
|
|
|
if args.dates is not None: |
|
543
|
|
|
pddrange += pd.to_datetime(args.dates.split(',')) |
|
544
|
|
|
logging.debug("pddrange: %s", pddrange) |
|
545
|
|
|
|
|
546
|
|
|
olist = [] |
|
547
|
|
|
for date in pddrange: |
|
548
|
|
|
try: |
|
549
|
|
|
olist += get_orbits_from_date(date.strftime("%Y-%m-%d"), |
|
550
|
|
|
mlt=args.mlt, path=args.path, L2_version=args.retrieval_version) |
|
551
|
|
|
except: # handle NaT |
|
552
|
|
|
pass |
|
553
|
|
|
if args.orbit_file is not None: |
|
554
|
|
|
olist += np.genfromtxt(args.orbit_file, dtype=np.int32).tolist() |
|
555
|
|
|
logging.debug("olist: %s", olist) |
|
556
|
|
|
|
|
557
|
|
|
if not olist: |
|
558
|
|
|
logging.warn("No orbits to process.") |
|
559
|
|
|
return |
|
560
|
|
|
|
|
561
|
|
|
sdlist, sdxr_ds = combine_orbit_data(olist, |
|
562
|
|
|
ref_date="2000-01-01", |
|
563
|
|
|
L2_version=args.retrieval_version, file_version=args.file_version, |
|
564
|
|
|
dens_path=args.path, spec_base=args.spectra, use_xarray=args.xarray, |
|
565
|
|
|
save_nc=False) |
|
566
|
|
|
|
|
567
|
|
|
if args.xarray and sdxr_ds is not None: |
|
568
|
|
|
sd_xr = sddata_xr_set_attrs(sdxr_ds, ref_date="2000-01-01") |
|
569
|
|
|
sd_xr2 = sdlist.to_xarray() |
|
570
|
|
|
logging.debug(sd_xr) |
|
571
|
|
|
logging.debug(sd_xr2) |
|
572
|
|
|
logging.debug("equal datasets: %s", sd_xr.equals(sd_xr2)) |
|
573
|
|
|
xr.testing.assert_allclose(sd_xr, sd_xr2) |
|
574
|
|
|
if sd_xr2 is not None: |
|
575
|
|
|
logging.debug("xarray dataset: %s", sd_xr2) |
|
576
|
|
|
sd_xr2.to_netcdf(args.file, unlimited_dims=["time"]) |
|
577
|
|
|
else: |
|
578
|
|
|
if sdlist.no_dens is not None: |
|
579
|
|
|
sdlist.write_to_netcdf(args.file) |
|
580
|
|
|
else: |
|
581
|
|
|
logging.warn("Processed data is empty.") |
|
582
|
|
|
|
|
583
|
|
|
|
|
584
|
|
|
if __name__ == "__main__": |
|
585
|
|
|
main() |
|
586
|
|
|
|
st-bender /
sciapy
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