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mip_seasonal_cycle.py
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mip_seasonal_cycle.py
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from numpy import *
# Calculate the average amplitude of the seasonal cycle in total basal mass
# loss over 2002-2016, in MetROMS, low-res FESOM, and high-res FESOM, for the
# entire continent as well as the Amery. Print results to the screen.
def mip_seasonal_cycle (roms_logfile, fesom_logfile_lr, fesom_logfile_hr):
# Year simulations start
year_start = 1992
# Years to avearge over
calc_start = 2002
calc_end = 2016
# Number of output steps per year in FESOM
peryear = 365/5
# Name of each ice shelf
names = ['Total Mass Loss', 'Larsen D Ice Shelf', 'Larsen C Ice Shelf', 'Wilkins & George VI & Stange Ice Shelves', 'Ronne-Filchner Ice Shelf', 'Abbot Ice Shelf', 'Pine Island Glacier Ice Shelf', 'Thwaites Ice Shelf', 'Dotson Ice Shelf', 'Getz Ice Shelf', 'Nickerson Ice Shelf', 'Sulzberger Ice Shelf', 'Mertz Ice Shelf', 'Totten & Moscow University Ice Shelves', 'Shackleton Ice Shelf', 'West Ice Shelf', 'Amery Ice Shelf', 'Prince Harald Ice Shelf', 'Baudouin & Borchgrevink Ice Shelves', 'Lazarev Ice Shelf', 'Nivl Ice Shelf', 'Fimbul & Jelbart & Ekstrom Ice Shelves', 'Brunt & Riiser-Larsen Ice Shelves', 'Ross Ice Shelf']
num_shelves = len(names)
i_total = 0
i_amery = 16
# Read ROMS logfile
roms_time = []
f = open(roms_logfile, 'r')
# Skip the first line (header for time array)
f.readline()
for line in f:
try:
roms_time.append(float(line))
except(ValueError):
# Reached the header for the next variable
break
# Set up array for mass loss values at each ice shelf
roms_massloss = empty([num_shelves, len(roms_time)])
index = 0
# Loop over ice shelves
while index < num_shelves:
t = 0
for line in f:
try:
roms_massloss[index, t] = float(line)
t += 1
except(ValueError):
# Reached the header for the next ice shelf
break
index +=1
f.close()
# Add start year to ROMS time array
roms_time = array(roms_time) + year_start
# Calculate amplitude for each year
#roms_amplitude_total = []
roms_min_total = []
roms_max_total = []
#roms_amplitude_amery = []
roms_min_amery = []
roms_max_amery = []
for year in range(calc_start, calc_end):
# Find the first index after the beginning of this year
t_start = nonzero(roms_time >= year)[0][0]
# Find the first index after the beginning of next year
tmp2 = nonzero(roms_time >= year+1)[0]
if len(tmp2)==0:
# No such index, but we might not have run out of data
# eg simulation that ends on 31 December 2016
t_end = len(roms_time)
else:
t_end = tmp2[0]
# Total Antarctica
# Get min and max between these bounds
curr_min = amin(roms_massloss[i_total,t_start:t_end])
curr_max = amax(roms_massloss[i_total,t_start:t_end])
roms_min_total.append(curr_min)
roms_max_total.append(curr_max)
# Save amplitude
#roms_amplitude_total.append(curr_max-curr_min)
# Amery
curr_min = amin(roms_massloss[i_amery,t_start:t_end])
curr_max = amax(roms_massloss[i_amery,t_start:t_end])
#roms_amplitude_amery.append(curr_max-curr_min)
roms_min_amery.append(curr_min)
roms_max_amery.append(curr_max)
# Calculate average amplitude
#roms_val_total = mean(array(roms_amplitude_total))
#roms_val_amery = mean(array(roms_amplitude_amery))
#print 'Average amplitude of seasonal cycle in total basal mass loss: '
#print 'ROMS (Total Antarctica): ' + str(roms_val_total)
#print 'ROMS (Amery): ' + str(roms_val_amery)
print 'Average min/max in total basal mass loss: '
print 'ROMS (Total Antarctica): ' + str(mean(array(roms_min_total))) + ' Gt/y min, ' + str(mean(array(roms_max_total))) + ' Gt/y max'
print 'ROMS (Amery): ' + str(mean(array(roms_min_amery))) + ' Gt/y min, ' + str(mean(array(roms_max_amery))) + ' Gt/y max'
# Read FESOM logfiles
# Low-res
f = open(fesom_logfile_lr, 'r')
# Skip the first line (header)
f.readline()
# Read total mass loss
tmp = []
num_time = 0
for line in f:
try:
tmp.append(float(line))
num_time += 1
except(ValueError):
# Reached the header for the first individual ice shelf
break
# Set up array for mass loss values at each ice shelf
fesom_massloss_lr = empty([num_shelves, num_time])
# Save the total values in the first index
fesom_massloss_lr[0,:] = array(tmp)
# Loop over ice shelves
index = 1
while index < num_shelves:
t = 0
for line in f:
try:
fesom_massloss_lr[index,t] = float(line)
t += 1
except(ValueError):
# Reached the header for the next ice shelf
break
index += 1
f.close()
# Calculate amplitude for each year
#fesom_amplitude_total_lr = []
fesom_min_total_lr = []
fesom_max_total_lr = []
#fesom_amplitude_amery_lr = []
fesom_min_amery_lr = []
fesom_max_amery_lr = []
for year in range(calc_start, calc_end):
t_start = peryear*(year-year_start)
t_end = peryear*(year+1-year_start)
# Total Antarctica
# Get min and max between these bounds
curr_min = amin(fesom_massloss_lr[i_total,t_start:t_end])
curr_max = amax(fesom_massloss_lr[i_total,t_start:t_end])
# Save amplitude
#fesom_amplitude_total_lr.append(curr_max-curr_min)
fesom_min_total_lr.append(curr_min)
fesom_max_total_lr.append(curr_max)
# Amery
curr_min = amin(fesom_massloss_lr[i_amery,t_start:t_end])
curr_max = amax(fesom_massloss_lr[i_amery,t_start:t_end])
#fesom_amplitude_amery_lr.append(curr_max-curr_min)
fesom_min_amery_lr.append(curr_min)
fesom_max_amery_lr.append(curr_max)
# Calculate average amplitude
#fesom_val_total_lr = mean(array(fesom_amplitude_total_lr))
#fesom_val_amery_lr = mean(array(fesom_amplitude_amery_lr))
#print 'FESOM low-res (Total Antarctica): ' + str(fesom_val_total_lr)
#print 'FESOM low-res (Amery): ' + str(fesom_val_amery_lr)
print 'FESOM low-res (Total Antarctica): ' + str(mean(array(fesom_min_total_lr))) + ' Gt/y min, ' + str(mean(array(fesom_max_total_lr))) + ' Gt/y max'
print 'FESOM low-res (Amery): ' + str(mean(array(fesom_min_amery_lr))) + ' Gt/y min, ' + str(mean(array(fesom_max_amery_lr))) + ' Gt/y max'
# High-res
f = open(fesom_logfile_hr, 'r')
f.readline()
tmp = []
num_time = 0
for line in f:
try:
tmp.append(float(line))
num_time += 1
except(ValueError):
break
fesom_massloss_hr = empty([num_shelves, num_time])
fesom_massloss_hr[0,:] = array(tmp)
index = 1
while index < num_shelves:
t = 0
for line in f:
try:
fesom_massloss_hr[index,t] = float(line)
t += 1
except(ValueError):
break
index += 1
f.close()
#fesom_amplitude_total_hr = []
fesom_min_total_hr = []
fesom_max_total_hr = []
#fesom_amplitude_amery_hr = []
fesom_min_amery_hr = []
fesom_max_amery_hr = []
for year in range(calc_start, calc_end):
t_start = peryear*(year-year_start)
t_end = peryear*(year+1-year_start)
curr_min = amin(fesom_massloss_hr[i_total,t_start:t_end])
curr_max = amax(fesom_massloss_hr[i_total,t_start:t_end])
fesom_min_total_hr.append(curr_min)
fesom_max_total_hr.append(curr_max)
#fesom_amplitude_total_hr.append(curr_max-curr_min)
curr_min = amin(fesom_massloss_hr[i_amery,t_start:t_end])
curr_max = amax(fesom_massloss_hr[i_amery,t_start:t_end])
#fesom_amplitude_amery_hr.append(curr_max-curr_min)
fesom_min_amery_hr.append(curr_min)
fesom_max_amery_hr.append(curr_max)
#fesom_val_total_hr = mean(array(fesom_amplitude_total_hr))
#fesom_val_amery_hr = mean(array(fesom_amplitude_amery_hr))
#print 'FESOM high-res (Total Antarctica): ' + str(fesom_val_total_hr)
#print 'FESOM high-res (Amery): ' + str(fesom_val_amery_hr)
print 'FESOM high-res (Total Antarctica): ' + str(mean(array(fesom_min_total_hr))) + ' Gt/y min, ' + str(mean(array(fesom_max_total_hr))) + ' Gt/y max'
print 'FESOM high-res (Amery): ' + str(mean(array(fesom_min_amery_hr))) + ' Gt/y min, ' + str(mean(array(fesom_max_amery_hr))) + ' Gt/y max'
# Command-line interface
if __name__ == "__main__":
roms_logfile = raw_input("Path to ROMS logfile from timeseries_massloss.py: ")
fesom_logfile_lr = raw_input("Path to FESOM low-res logfile from timeseries_massloss.py: ")
fesom_logfile_hr = raw_input("Path to FESOM high-res logfile from timeseries_massloss.py: ")
mip_seasonal_cycle(roms_logfile, fesom_logfile_lr, fesom_logfile_hr)