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seasonal_climatology_cice.py
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seasonal_climatology_cice.py
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from netCDF4 import Dataset, num2date
from numpy import *
from os import listdir
# Calculate the seasonal climatology (DJF, MAM, JJA, SON) of sea ice
# concentration and thickness during a CICE simulation and save to a NetCDF
# file.
# Input:
# directory = path to CICE output history directory containing files of the
# form iceh.*.nc, assuming 5-day averages with one time index per
# file. The script will process all these files.
# out_file = path to desired output file
def seasonal_climatology_cice (directory, out_file):
# Starting and ending months (1-based) for each season
start_month = [12, 3, 6, 9]
end_month = [2, 5, 8, 11]
# Starting and ending days of the month (1-based) for each season
# Assume no leap years, we'll fix this later if we need
start_day = [1, 1, 1, 1]
end_day = [28, 31, 31, 30]
# Find the first output file
for file in listdir(directory):
if file.startswith('iceh.') and file.endswith('.nc'):
# Read the grid
id = Dataset(directory + file, 'r')
lon = id.variables['TLON'][:,:]
lat = id.variables['TLAT'][:,:]
id.close()
break
# Set up arrays to integrate seasonal climatology of aice and hi
seasonal_aice = ma.empty([4, size(lon,0), size(lon,1)])
seasonal_hi = ma.empty([4, size(lon,0), size(lon,1)])
seasonal_aice[:,:,:] = 0.0
seasonal_hi[:,:,:] = 0.0
# Also integrate number of days in each season
ndays = zeros(4)
# Total number of days for a final check
total_days = 0
# Loop over files
for file in listdir(directory):
if file.startswith('iceh.') and file.endswith('.nc'):
print 'Processing ' + directory + file
# Read aice and hi
id = Dataset(directory+file, 'r')
aice = id.variables['aice'][0,:,:]
hi = id.variables['hi'][0,:,:]
# Read the time value and convert to Date object
time_id = id.variables['time']
time = num2date(time_id[0], units=time_id.units, calendar=time_id.calendar.lower())
id.close()
total_days += 5
# 5-day averages marked with next day's date
year = time.year
month = time.month
day = time.day
# Get the season of this day
if month in [12, 1, 2]:
# DJF
season = 0
elif month in [3, 4, 5]:
# MAM
season = 1
elif month in [6, 7, 8]:
# JJA
season = 2
elif month in [9, 10, 11]:
# SON
season = 3
# Check for leap years
leap_year = False
if mod(year, 4) == 0:
leap_year = True
if mod(year, 100) == 0:
leap_year = False
if mod(year, 400) == 0:
leap_year = True
# Update last day in February
if leap_year:
end_day[0] = 29
else:
end_day[0] = 28
if month == start_month[season]:
# We are in the first month of the season
if day-5 < start_day[season]:
# Spills over into the previous season
prev_season = mod(season-1, 4)
# How many days does it spill over by?
spill_days = start_day[season]-day+5
# Should be between 1 and 5
if spill_days < 1 or spill_days > 5:
print 'Problem: spill_days is ' + str(spill_days)
print 'Timestep ' + str(t+1)
print 'Year ' + str(year)
print 'Month ' + str(month+1)
print 'Day ' + str(day)
return
# Split between previous season and this season
seasonal_aice[prev_season,:,:] += aice*spill_days
seasonal_hi[prev_season,:,:] += hi*spill_days
ndays[prev_season] += spill_days
seasonal_aice[season,:,:] += aice*(5-spill_days)
seasonal_hi[season,:,:] += hi*(5-spill_days)
ndays[season] += 5-spill_days
else:
# Entirely within the season
seasonal_aice[season,:,:] += aice*5
seasonal_hi[season,:,:] += hi*5
ndays[season] += 5
else:
# Not in the first month of the season
# The 5 days will be entirely within the season
seasonal_aice[season,:,:] += aice*5
seasonal_hi[season,:,:] += hi*5
ndays[season] += 5
# Convert from sums to averages
for season in range(4):
seasonal_aice[season,:,:] = seasonal_aice[season,:,:]/ndays[season]
seasonal_hi[season,:,:] = seasonal_hi[season,:,:]/ndays[season]
if sum(ndays) != total_days:
print 'Problem: files have ' + str(total_days) + ' days, but climatology has ' + str(sum(ndays))
return
# Write to file
print 'Writing ' + out_file
id = Dataset(out_file, 'w')
id.createDimension('ni', size(lon,1))
id.createDimension('nj', size(lon,0))
id.createDimension('time', 4)
id.createVariable('TLON', 'f8', ('nj', 'ni'))
id.variables['TLON'].long_name = 'T grid center longitude'
id.variables['TLON'].units = 'degrees_east'
id.variables['TLON'][:,:] = lon
id.createVariable('TLAT', 'f8', ('nj', 'ni'))
id.variables['TLAT'].long_name = 'T grid center latitude'
id.variables['TLAT'].units = 'degrees_north'
id.variables['TLAT'][:,:] = lat
id.createVariable('time', 'f8', ('time'))
id.variables['time'].units = 'season'
id.variables['time'].long_name = 'DJF, MAM, JJA, SON'
id.variables['time'][:] = arange(1,4+1)
id.createVariable('aice', 'f8', ('time', 'nj', 'ni'))
id.variables['aice'].units = '1'
id.variables['aice'][:,:,:] = seasonal_aice
id.createVariable('hi', 'f8', ('time', 'nj', 'ni'))
id.variables['hi'].units = 'm'
id.variables['hi'][:,:,:] = seasonal_hi
id.close()
# Command-line interface
if __name__ == "__main__":
directory = raw_input("Path to CICE output history directory: ")
out_file = raw_input("Path to desired output file: ")
seasonal_climatology_cice(directory, out_file)