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collocation.py
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collocation.py
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# -*- coding: utf-8 -*-
# collocation.py
# Copyright (c) 2015-2018, Likun Wang (Likun.Wang@noaa.gov)
# Copyright (c) 2015-2018, Earth System Science Interdisciplinary
# Center/Univ. of Maryland
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the copyright holders nor the names of any
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
""" Accurate and fast collocation CrIS and VIIRS two instrument.
Check this paper if you need more information:
Wang, L.; Tremblay, D.; Zhang, B.; Han, Y. Fast and Accurate
Collocation of the Visible Infrared Imaging Radiometer Suite Measurements
with Cross-Track Infrared Sounder. Remote Sens. 2016, 8, 76.
:Author:
`Likun Wang <Likun.Wang@noaa.gov>`_
:Organization:
Earth System Science Interdisciplinary Center/Univ. of Maryland
:Version: 2018.9.5
"""
import numpy as np
import multiprocessing as mp
import time
from jpss import read_cris_sdr, read_cris_geo, read_viirs_sdr, read_viirs_geo
import geolocation as geo
import pdb
def collocate_cris_viirs_tuple((cris_geo_files, cris_sdr_files, \
viirs_geo_files, viirs_sdr_files)):
data=collocate_cris_viirs(cris_geo_files, cris_sdr_files, viirs_geo_files, viirs_sdr_files)
return data
def collocate_cris_viirs(cris_geo_files, cris_sdr_files, \
viirs_geo_files, viirs_sdr_files):
# read VIIRS data
viirs_lon, viirs_lat, viirs_satAzimuth, viirs_satRange, viirs_satZenith = read_viirs_geo(viirs_geo_files)
viirs_bt, viirs_rad, viirs_sdrQa =read_viirs_sdr(viirs_sdr_files)
# read CrIS data
cris_lon, cris_lat, cris_satAzimuth, cris_satRange, cris_satZenith = read_cris_geo(cris_geo_files)
#cris_realLW, cris_realMW, cris_realSW, \
# cris_sdrQa, cris_geoQa, cris_dayFlag = read_cris_sdr(cris_sdr_files, sdrFlag=True)
# compute CrIS POS, LOS, SAT vector
cris_pos, cris_los, cris_sat = geo.GEO2ECEF(cris_lon, cris_lat, cris_satAzimuth, cris_satRange, cris_satZenith)
# compute viirs POS vector
viirs_pos, viirs_los, viirs_sat = geo.GEO2ECEF(viirs_lon, viirs_lat, viirs_satAzimuth, viirs_satRange, viirs_satZenith)
# cris_los is pointing from pixel to satellite, we need to
# change from satellite to pixel
cris_los = -1.0*cris_los
# using Kd-tree to find the closest pixel of VIIRS for each CrIS FOV
dy, dx = geo.match_cris_viirs(cris_los, cris_pos, viirs_pos, viirs_sdrQa)
if dy is None: return None
# viirs averaged radiances
cris_v_rad = np.asarray([np.mean(viirs_rad[dy[k, j, i], dx[k, j, i]]) if len(dx[k, j, i]) > 0 else 0.0 for k, j, i in np.ndindex(cris_lat.shape) ])
cris_v_std = np.asarray([np.std(viirs_rad[dy[k, j, i], dx[k, j, i]]) if len(dx[k, j, i]) > 0 else 0.0 for k, j, i in np.ndindex(cris_lat.shape) ])
cris_v_bt = np.asarray([np.mean(viirs_bt[dy[k, j, i], dx[k, j, i]]) if len(dx[k, j, i]) > 0 else 0.0 for k, j, i in np.ndindex(cris_lat.shape) ])
cris_v_rad = cris_v_rad.reshape(cris_lat.shape)
cris_v_bt = cris_v_bt.reshape(cris_lat.shape)
cris_v_std = cris_v_std.reshape(cris_lat.shape)
# collocation data field
field = dict()
field['cris_v_rad'] = cris_v_rad
field['cris_v_std'] = cris_v_std
field['cris_v_bt'] = cris_v_bt
field['cris_lat'] = cris_lat
field['cris_lon'] = cris_lon
#field['dx'] = dx
#field['dy'] = dy
field['cris_sdr_files'] = cris_sdr_files
field['cris_geo_files'] = cris_geo_files
field['viirs_sdr_files'] = viirs_sdr_files
field['viirs_geo_files'] = viirs_geo_files
return field
def cris_viirs_perturb (cris_geo_files, cris_sdr_files, viirs_geo_files, viirs_sdr_files, alpha, beta, pmw = None, psw = None):
# read VIIRS data
viirs_lon, viirs_lat, viirs_satAzimuth, viirs_satRange, viirs_satZenith = read_viirs_geo(viirs_geo_files)
viirs_bt, viirs_rad, viirs_sdrQa = read_viirs_sdr(viirs_sdr_files)
viirs_MidTime, viirs_PosECR, viirs_VelECR, viirs_Att = read_viirs_geo(viirs_geo_files, ephemeris=True)
# read CrIS data
cris_lon, cris_lat, cris_satAzimuth, cris_satRange, cris_satZenith = read_cris_geo(cris_geo_files)
cris_FORTime, cris_MidTime, cris_SCPosition, cris_SCVelocity, cris_SCAttitude = read_cris_geo(cris_geo_files, ephemeris=True)
nScan, nFor, nFov = cris_lon.shape
#cris_realLW, cris_realMW, cris_realSW, \
# cris_sdrQa, cris_geoQa, cris_dayFlag = read_cris_sdr(cris_sdr_files, sdrFlag=True)
# compute CrIS POS, LOS, SAT vector
cris_pos, cris_los, cris_sat = geo.GEO2ECEF(cris_lon, cris_lat, cris_satAzimuth, cris_satRange, cris_satZenith)
# compute viirs POS vector
viirs_pos, viirs_los, viirs_sat = geo.GEO2ECEF(viirs_lon, viirs_lat, viirs_satAzimuth, viirs_satRange, viirs_satZenith)
# cris_los is pointing from pixel to satellite, we need to
# change from satellite to pixel
cris_los = -1.0*cris_los
# compute perturbation LOS
start_time = time.time()
p_out, v_out, att_out = geo.interpolate_sat_vector(viirs_PosECR, viirs_VelECR, viirs_Att, viirs_MidTime, cris_FORTime.ravel())
att_out = np.deg2rad(att_out/3600.00)
Mat_ECItoOrb = geo.buildECIOrbFrame(cris_FORTime.ravel(), p_out, v_out)
Mat_OrbtoECI = np.transpose(Mat_ECItoOrb, [0, 2, 1])
Mat_OrbtoECI = np.broadcast_to(Mat_OrbtoECI, (nFov, nScan*nFor, 3, 3))
Mat_OrbtoECI = np.transpose(Mat_OrbtoECI, (1, 0, 2, 3))
Mat_OrbtoECI = Mat_OrbtoECI.reshape(nFov*nScan*nFor, 3, 3)
Mat_SPCtoOrb = geo.orb2sc(att_out[:, 0], att_out[:, 1], att_out[:, 2])
Mat_SPCtoOrb = np.broadcast_to(Mat_SPCtoOrb, (nFov, nScan*nFor, 3, 3))
Mat_SPCtoOrb = np.transpose(Mat_SPCtoOrb, (1, 0, 2, 3))
Mat_SPCtoOrb = Mat_SPCtoOrb.reshape(nFov*nScan*nFor, 3, 3)
cris_losECR = geo.normalize_vector(cris_los)
cris_losECR = cris_losECR.reshape(-1, 3)
cris_FOVTime = np.broadcast_to(cris_FORTime, (nFov, nScan, nFor))
cris_FOVTime = np.transpose(cris_FOVTime, (1, 2, 0))
cris_losECI, temp = geo.ECR2ECI_NOVAS(cris_FOVTime.ravel(), cris_losECR, 0.0)
cris_losOrb = geo.matrix_vector_product(Mat_OrbtoECI, cris_losECI)
cris_losSPC = geo.matrix_vector_product(Mat_SPCtoOrb, cris_losOrb)
asize = alpha.size
bsize = beta.size
alpha0, beta0 = geo.compute_alpha_beta(cris_losSPC)
alphav, betav = np.meshgrid(alpha, beta)
alpha0 = np.broadcast_to(alpha0, (bsize, asize, nScan*nFor*nFov))
beta0 = np.broadcast_to(beta0, (bsize, asize, nScan*nFor*nFov))
z = cris_losSPC[:, 2]
z = np.broadcast_to(z, (bsize, asize, nScan*nFor*nFov))
alphav = np.broadcast_to(alphav, (nScan*nFor*nFov, bsize, asize))
alphav = np.transpose(alphav, (1, 2, 0))
betav = np.broadcast_to(betav, (nScan*nFor*nFov, bsize, asize))
betav = np.transpose(betav, (1, 2, 0))
x = np.tan(alphav + alpha0)*z
y = np.tan(betav + beta0)*z
cris_losSPC_pert = np.zeros((bsize, asize, nScan*nFor*nFov, 3))
cris_losSPC_pert[:, :, :, 0] = x
cris_losSPC_pert[:, :, :, 1] = y
cris_losSPC_pert[:, :, :, 2] = z
cris_losSPC_pert = geo.normalize_vector(cris_losSPC_pert)
Mat_SPCtoECI = geo.matrix_matrix_product(Mat_SPCtoOrb, Mat_OrbtoECI)
Mat_ECItoSPC = np.transpose(Mat_SPCtoECI, (0, 2, 1))
Mat_ECItoSPC = np.broadcast_to(Mat_ECItoSPC, (bsize, asize, nScan*nFor*nFov, 3, 3))
cris_losECI_pert = geo.matrix_vector_product(Mat_ECItoSPC, cris_losSPC_pert)
cris_FOVTime_pert = np.broadcast_to(cris_FOVTime, (bsize, asize, nScan, nFor, nFov))
cris_losECR_pert, temp = geo.ECI2ECR_NOVAS(cris_FOVTime_pert.ravel(), cris_losECI_pert.reshape(-1, 3), 0.0)
cris_losECR_pert = cris_losECR_pert.reshape(bsize, asize, nScan, nFor, nFov, 3)
print("Perturb --- %s seconds ---" % (time.time() - start_time))
# using Kd-tree to find the closest pixel of VIIRS for each CrIS FOV
dy, dx = geo.match_cris_viirs_pert(cris_los, cris_pos, viirs_pos, viirs_sdrQa, cris_losECR_pert)
if dy is None:
return None
#ddy, ddx = geo.match_cris_viirs(cris_los, cris_pos, viirs_pos, viirs_sdrQa)
# viirs averaged radiances
cris_v_rad = np.asarray([np.mean(viirs_rad[dy[m, n, k, j, i], dx[m, n, k, j, i]]) for m, n, k, j, i in np.ndindex(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])])
cris_v_bt = np.asarray([np.mean(viirs_bt[dy[m, n, k, j, i], dx[m, n, k, j, i]]) for m, n, k, j, i in np.ndindex(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])])
cris_v_rad = cris_v_rad.reshape(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])
cris_v_bt = cris_v_bt.reshape(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])
if pmw is not None and psw is not None:
viirs_rad_mw = np.zeros_like(viirs_rad)
viirs_rad_sw = np.zeros_like(viirs_rad)
idx = np.where(viirs_sdrQa==0)
viirs_rad_mw[idx] = pmw(viirs_rad[idx])
viirs_rad_sw[idx] = psw(viirs_rad[idx])
cris_v_rad_mw = np.asarray([np.mean(viirs_rad_mw[dy[m, n, k, j, i], dx[m, n, k, j, i]]) for m, n, k, j, i in np.ndindex(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])])
cris_v_rad_sw = np.asarray([np.mean(viirs_rad_sw[dy[m, n, k, j, i], dx[m, n, k, j, i]]) for m, n, k, j, i in np.ndindex(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])])
cris_v_rad_mw = cris_v_rad_mw.reshape(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])
cris_v_rad_sw = cris_v_rad_sw.reshape(cris_losECR_pert.shape[0:cris_losECR_pert.ndim-1])
# collocation data feild
field = dict()
field['cris_v_rad'] = cris_v_rad
field['cris_v_bt'] = cris_v_bt
field['cris_lat'] = cris_lat
field['cris_lon'] = cris_lon
field['cris_sdr_files'] = cris_sdr_files
field['cris_geo_files'] = cris_geo_files
field['viirs_sdr_files'] = viirs_sdr_files
field['viirs_sdr_files'] = viirs_sdr_files
field['alpha'] = alpha
field['beta'] = beta
#field['dx'] = dx
#field['dy'] = dy
if pmw is not None and psw is not None:
field['cris_v_rad_mw'] = cris_v_rad_mw
field['cris_v_rad_sw'] = cris_v_rad_sw
return field