# Copyright 2016 Cambridge Environmental Research Consultants Ltd.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0
#
# **************************************************************************
# Function : compute_geopotential_on_ml_netcdf
#
# Author (date) : Mark Jackson (1/12/2016)
#
# Category : COMPUTATION
#
# OneLineDesc : Computes geopotential and height on model levels using netCDF files
#
# Description : Computes geopotential on model levels using netCDF files.
# Based on the Python script by Cristian Simarro which uses GRIB files:
# https://software.ecmwf.int/wiki/display/GRIB/Compute+geopotential+on+model+levels
# Which was based on the code of the Metview function mvl_geopotential_on_ml:
# https://software.ecmwf.int/metview/mvl_geopotential_on_ml
# This in turn was based on code from Nils Wedi, the IFS documentation:
# https://software.ecmwf.int/wiki/display/IFS/CY41R1+Official+IFS+Documentation
# part III. Dynamics and numerical procedures
# and an optimised implementation by Dominique Lucas.
# Ported to Python by Cristian Simarro
#
# Parameters : FileA.nc - netCDF file with the levelist of t and q. Does not require all levels
# but does require a contiguous set of levels all the way to the bottom.
# FileB.nc - netCDF file with levelist 1 for params z and lnsp
#
# Return Value : outputs CSV files
# with geopotential and height (relative to terrain) on each model level.
#
# Dependencies : netCDF4, numpy, scipy
#
from __future__ import print_function # make sure print behaves the same in Python 2.7 and 3.x
import netCDF4
from netCDF4 import num2date
import numpy as np
from scipy import interpolate
import datetime
import sys
import io
import math
#Variable names in the netCDF
#(File A - model levels)
# level = model level numbers, posssible values 1-60
# t = temperature K
# q = specific humidity kg/kg
#(File B)
# lnsp = log surface pressure
# z = surface geopotential
#arguments
#ONEDAY - read these from the command line
FILE_A_PATH="G:\\MiscProjects\\ERA-Interim-Python\\20160922-InvestigateProfiles-netCDF\\FileA.nc"
FILE_B_PATH="G:\\MiscProjects\\ERA-Interim-Python\\20160922-InvestigateProfiles-netCDF\\FileB.nc"
GRID_LAT=55.875 #(degrees N)
GRID_LONG=-4.5 #(degrees E)
OUT_DIR_PATH="G:\\MiscProjects\\ERA-Interim-Python\\20161101-Check MarkJ geopotentials against ECMWF geopotentials\\output\\"
#Routine to Read File A data file for t, q values at a particular grid point
def readfa(fileapath):
#Connect to data file for reading
print()
print("==================================================")
print("File A information")
print("Filename{}".format(fileapath))
fa = netCDF4.Dataset(fileapath, 'r')
#Variables as netCDF variable objects
print()
print("--------------------------------------------------")
print("Variables")
print(fa.variables.keys()) # get all variable names
fanclongs = fa.variables['longitude']
print(fanclongs)
fanclats = fa.variables['latitude']
print(fanclats)
fanclevels = fa.variables['level']
print(fanclevels)
fanctimes = fa.variables['time']
print(fanctimes)
fancts = fa.variables['t']
print(fancts)
fancqs = fa.variables['q']
print(fancqs)
#Get level values (either model levels or pressure levels) and number of levels
falevels=fanclevels[:]
print()
print("--------------------------------------------------")
print("Model levels")
fanlevels=falevels.shape[0]
print("There are {} levels: {} - {}".format(fanlevels, falevels[0], falevels[fanlevels-1]))
#Get time values and number of times
fatimes=fanctimes[:]
print()
print("--------------------------------------------------")
print("File A Times")
print(fatimes)
fantimes=fatimes.shape[0]
#Get python datetime for each time
fapydts=num2date(fatimes, fanctimes.units)
#Output first 10 datetimes
print()
print("First 10 times as date-time")
print([pydt.strftime('%Y-%m-%d %H:%M:%S') for pydt in fapydts[:10]])
#Get lat and long values
falats = fanclats[:]
print()
print("--------------------------------------------------")
print("File A Latitudes")
print(falats)
falongs = fanclongs[:]
print()
print("--------------------------------------------------")
print("File A Longitudes")
print(falongs)
#Get index of grid point of interest
failat=np.where(falats==GRID_LAT)[0]
failong=np.where(falongs==GRID_LONG)[0]
print()
print("==================================================")
print("Grid point location: latitude and longitude indexes for lat {} and long {}".format(GRID_LAT, GRID_LONG))
print(failat)
print(failong)
#Get t, q values for specified grid point for all levels (slicing)
#The result is still a 4D array with 1 latitude and 1 longitude
print()
print("==================================================")
print("Get t, q values for all levels")
fats=fancts[range(fantimes),range(fanlevels),failat,failong]
faqs=fancqs[range(fantimes),range(fanlevels),failat,failong]
return (fats, faqs, falevels, fapydts)
#Routine to Read File B data file for z, lnsp values at a particular grid point
def readfb(fbfilepath):
#Connect to file for reading
print()
print("==================================================")
print("fb File information")
print("Filename{}".format(fbfilepath))
fbf = netCDF4.Dataset(fbfilepath, 'r')
print(fbf)
print()
#Variables as netCDF variable objects
print()
print("--------------------------------------------------")
print("Variables")
print(fbf.variables.keys()) # get all variable names
fbnclongs = fbf.variables['longitude']
print(fbnclongs)
fbnclats = fbf.variables['latitude']
print(fbnclats)
fbnctimes = fbf.variables['time']
print(fbnctimes)
fbnczs = fbf.variables['z']
print(fbnczs)
fbnclnsps = fbf.variables['lnsp']
print(fbnclnsps)
#Get time values and number of times
fbtimes=fbnctimes[:]
print()
print("--------------------------------------------------")
print("fb Times")
print(fbtimes)
fbntimes=fbtimes.shape[0]
#Get python datetime for each time
fbpydts=num2date(fbtimes, fbnctimes.units)
#Output first 10 datetimes
print()
print("fb First 10 times as date-time")
print([pydt.strftime('%Y-%m-%d %H:%M:%S') for pydt in fbpydts[:10]])
#Get lat and long values
fblats = fbnclats[:]
print()
print("--------------------------------------------------")
print("fb Latitudes")
print(fblats)
fblongs = fbnclongs[:]
print()
print("--------------------------------------------------")
print("fb Longitudes")
print(fblongs)
#Get index of grid point of interest
fbilat=np.where(fblats==GRID_LAT)[0]
fbilong=np.where(fblongs==GRID_LONG)[0]
print()
print("==================================================")
print("Grid point location: fb latitude and longitude indexes for lat {} and long {}".format(GRID_LAT, GRID_LONG))
print(fbilat)
print(fbilong)
#Get z, lnsp values for specified grid point (slicing)
#The result is still a 3D array with 1 latitude and 1 longitude
print()
print("==================================================")
print("Get z, lnsp values ")
fbzs=fbnczs[range(fbntimes),fbilat,fbilong]
print('shape of z slice: %s' % repr(fbzs.shape))
fblnsps=fbnclnsps[range(fbntimes),fbilat,fbilong]
return (fbzs, fblnsps, fbpydts)
#Read File A file
fats, faqs, falevels, fapydts = readfa(FILE_A_PATH)
fanlevels=falevels.shape[0]
fantimes=fapydts.shape[0]
#Read File B file
fbzs, fblnsps, fbpydts = readfb(FILE_B_PATH)
print()
print("==================================================")
print("Running...")
#Calculation of geopotential and height
def calculategeoh(z, lnsp, ts, qs, levels):
heighttoreturn=np.full(ts.shape[0], -999, np.double)
geotoreturn=np.full(ts.shape[0], -999, np.double)
Rd = 287.06
z_h = 0
#surface pressure
sp = math.exp(lnsp)
# A and B parameters to calculate pressures for model levels,
# extracted from an ECMWF ERA-Interim GRIB file and then hardcoded here
pv = [
0.0000000000e+000, 2.0000000000e+001, 3.8425338745e+001, 6.3647796631e+001, 9.5636962891e+001,
1.3448330688e+002, 1.8058435059e+002, 2.3477905273e+002, 2.9849584961e+002, 3.7397192383e+002,
4.6461816406e+002, 5.7565112305e+002, 7.1321801758e+002, 8.8366040039e+002, 1.0948347168e+003,
1.3564746094e+003, 1.6806403809e+003, 2.0822739258e+003, 2.5798886719e+003, 3.1964216309e+003,
3.9602915039e+003, 4.9067070313e+003, 6.0180195313e+003, 7.3066328125e+003, 8.7650546875e+003,
1.0376125000e+004, 1.2077445313e+004, 1.3775324219e+004, 1.5379804688e+004, 1.6819472656e+004,
1.8045183594e+004, 1.9027695313e+004, 1.9755109375e+004, 2.0222203125e+004, 2.0429863281e+004,
2.0384480469e+004, 2.0097402344e+004, 1.9584328125e+004, 1.8864750000e+004, 1.7961359375e+004,
1.6899468750e+004, 1.5706449219e+004, 1.4411125000e+004, 1.3043218750e+004, 1.1632757813e+004,
1.0209500000e+004, 8.8023554688e+003, 7.4388046875e+003, 6.1443164063e+003, 4.9417773438e+003,
3.8509133301e+003, 2.8876965332e+003, 2.0637797852e+003, 1.3859125977e+003, 8.5536181641e+002,
4.6733349609e+002, 2.1039389038e+002, 6.5889236450e+001, 7.3677425385e+000, 0.0000000000e+000,
0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000,
0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000,
0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000,
0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000,
0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000, 0.0000000000e+000,
7.5823496445e-005, 4.6139489859e-004, 1.8151560798e-003, 5.0811171532e-003, 1.1142909527e-002,
2.0677875727e-002, 3.4121163189e-002, 5.1690407097e-002, 7.3533833027e-002, 9.9674701691e-002,
1.3002252579e-001, 1.6438430548e-001, 2.0247590542e-001, 2.4393314123e-001, 2.8832298517e-001,
3.3515489101e-001, 3.8389211893e-001, 4.3396294117e-001, 4.8477154970e-001, 5.3570991755e-001,
5.8616840839e-001, 6.3554745913e-001, 6.8326860666e-001, 7.2878581285e-001, 7.7159661055e-001,
8.1125342846e-001, 8.4737491608e-001, 8.7965691090e-001, 9.0788388252e-001, 9.3194031715e-001,
9.5182150602e-001, 9.6764522791e-001, 9.7966271639e-001, 9.8827010393e-001, 9.9401944876e-001,
9.9763011932e-001, 1.0000000000e+000 ]
levelSize=60
A = pv[0:levelSize+1]
B = pv[levelSize+1:]
Ph_levplusone = A[levelSize] + (B[levelSize]*sp)
#Get a list of level numbers in reverse order
reversedlevels=np.full(levels.shape[0], -999, np.int32)
for iLev in list(reversed(range(levels.shape[0]))):
reversedlevels[levels.shape[0] - 1 - iLev] = levels[iLev]
#Integrate up into the atmosphere from lowest level
for lev in reversedlevels:
#lev is the level number 1-60, we need a corresponding index into ts and qs
ilevel=np.where(levels==lev)[0]
t_level=ts[ilevel]
q_level=qs[ilevel]
#compute moist temperature
t_level = t_level * (1.+0.609133*q_level)
#compute the pressures (on half-levels)
Ph_lev = A[lev-1] + (B[lev-1] * sp)
if lev == 1:
dlogP = math.log(Ph_levplusone/0.1)
alpha = math.log(2)
else:
dlogP = math.log(Ph_levplusone/Ph_lev)
dP = Ph_levplusone-Ph_lev
alpha = 1. - ((Ph_lev/dP)*dlogP)
TRd = t_level*Rd
# z_f is the geopotential of this full level
# integrate from previous (lower) half-level z_h to the full level
z_f = z_h + (TRd*alpha)
#Convert geopotential to height
heighttoreturn[ilevel] = z_f / 9.80665
#Geopotential (add in surface geopotential)
geotoreturn[ilevel] = z_f + z
# z_h is the geopotential of 'half-levels'
# integrate z_h to next half level
z_h=z_h+(TRd*dlogP)
Ph_levplusone = Ph_lev
return geotoreturn, heighttoreturn
#Output all the values for the specified grid point
#Iterate over all the times and write out the data
for itime in range(fantimes):
if fapydts[itime]!=fbpydts[itime]:
print("ERROR! Mismatching times in the files. Time number {}: File A = {} and File B = {}".format(
itime, fapydts[itime].strftime('%Y-%m-%d %H:%M:%S'), fbpydts[itime].strftime('%Y-%m-%d %H:%M:%S')))
sys.exit()
pydt=fapydts[itime]
print(" Processing {}/{} : {} ...".format(itime, fantimes, pydt.strftime('%Y-%m-%d %H:%M:%S')))
z, lnsp = fbzs[itime,0,0], fblnsps[itime,0,0]
sline="{}, {}, {}".format(pydt.strftime('%Y-%m-%d %H:%M:%S'), z, lnsp)
#Calculate geopotentials and heights for the model levels
geo, h = calculategeoh(z, lnsp, fats[itime,range(fanlevels),0,0],
faqs[itime,range(fanlevels),0,0], falevels)
with io.open(OUT_DIR_PATH + pydt.strftime('%Y%m%d-%H') + ".csv", 'w', newline='\r\n') as writer:
sheader1 = "lat, long, geopotential, h\n"
writer.write(unicode(sheader1))
#Iterate over levels for this time
for ilevel in range(fanlevels):
sline="{}, {}, {}, {}".format(
GRID_LAT, GRID_LONG, geo[ilevel], h[ilevel])
sline+="\n"
writer.write(unicode(sline))
print("Finished")
|