#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Dec 1 15:01:55 2020 @author: jabadgeley """ import numpy as np # acceleration due to gravity at sea level (m/s^2) gravity = 9.81 # latent heat of vaporization (J/kg at 0 degrees Celsius) latent_heat_vaporization = 2.5e6 # specific heat of dry air (J/kgK) specific_heat_dry_air = 1004. # gas constant for dry air (J/kgK) gas_constant_dry_air = 287. # gas constant for water vapor (J/kgK) gas_constant_water_vapor = 461. # ratio: gas constant dry air / gas constant water vapor (epsilon = Rd/Rv) epsilon = gas_constant_dry_air / gas_constant_water_vapor # dry adiabatic lapse rate (K/m) adiabatic_lapse_rate_dry = gravity / specific_heat_dry_air # reference pressure (Pa) reference_pressure = 100000. # centimeters to inches conversion cm2in = 1/2.54 # ice core locations dictionary icecores = {'EDML':(360.07,-75.0), 'DF':(39.7,-77.32), 'DB':(94.92, -77.08), 'Vostok':(106.87,-78.47), 'EDC':(123.35,-75.1), 'Law':(112.83,-66.73), 'Talos':(159.18,-72.82), 'Taylor':(158.72,-77.8), 'Siple':(-148.82,-81.67), 'Byrd':(-119.52,-80.02), 'WDC':(-112.14,-79.46), 'Herc':(-105.,-86.), 'SP':[-95.1,-89.98], 'WAIS 2':['WDC','Byrd'], 'WAIS 3':['WDC','Byrd','Herc'], 'EAIS 3': ['DF', 'EDC', 'Vostok'], 'EAIS 4': ['DF', 'EDC', 'Vostok', 'EDML'], 'AIS All': ['WDC', 'SP', 'EDML', 'EDC', 'Talos', 'DF', 'Taylor', 'Vostok', 'Byrd', 'Siple', 'Law', 'DB' ]} # values for the ensemble ensemble_values = {'model_groups':['PMIP3','PMIP3','PMIP3','PMIP3','PMIP3', 'PMIP4','PMIP4','PMIP4','PMIP4', 'New_Model_Output'], 'model_names':['CNRM','FGOALS','GISS','IPSL','MRI', 'AWI','INM','MIROC','MPI','CAM5'], 'experiments_recent':['piControl','piControl', 'piControl','piControl', 'piControl','piControl', 'piControl','piControl', 'piControl','PI_control_gtopo30'], 'experiments_past':['lgm','lgm','lgm','lgm','lgm','lgm', 'lgm','lgm','lgm', 'LGM_Si_real_avg_SAT_TMP373_RVP'], #full_lgm_no_AA_120m_sea_level_gtopo30 'subexperiments_recent':['r1i1p1','r1i1p1','r1i1p1', 'r1i1p1','r1i1p1','r1i1p1f1', 'r1i1p1f1','r1i1p1f2','r1i1p1f1', ''], 'subexperiments_past':['r1i1p1','r1i1p1','r1i1p150', 'r1i1p1','r1i1p1','r1i1p1f1', 'r1i1p1f1','r1i1p1f2','r1i1p1f1',''], 'frequencies':['Aclim','Aclim','Aclim','Aclim','Aclim', 'Aclim','Aclim','Aclim','Aclim','monthly'], 'huss':['huss','hus','huss','hus','huss','huss','huss', 'huss','huss',''], 'hurs':['hurs','hur','hurs','hur','hurs','hurs','hurs', 'hurs','hurs',''], 'titles':['PMIP3: CNRM', 'PMIP3: FGOALS', 'PMIP3: GISS', 'PMIP3: IPSL', 'PMIP3: MRI', 'PMIP4: AWI', 'PMIP4: INM', 'PMIP4: MIROC', 'PMIP4: MPI', 'CAM5'] } # regrid to these lat and lons regrid_data = {'lat':np.linspace(-90,90,181), 'lon':np.linspace(0,359,360)} # The following regrid_data_irregular was computed with: # import cartopy.crs as ccrs # import numpy as np # Sample locations #sample_xs = np.linspace(-2600000, 2600000, 27) #sample_ys = np.linspace(-2600000, 2600000, 27) #meshxs, meshys = np.meshgrid(sample_xs, sample_ys) #points_meshlatlon = ccrs.Geodetic().transform_points(src_crs = ccrs.SouthPolarStereo(), # x=meshxs, y=meshys) #points_latlon = points_meshlatlon[...,:2].reshape([-1,2]) #lats = [] #lons = [] #for ii, lon in enumerate(points_latlon[:,0]): # lat = points_latlon[ii,1] # if Ant_poly.intersects(Point(lon, lat)): # lons += [lon] # lats += [lat] #regrid_data_irregular = {} #regrid_data_irregular['lat'] = lats #regrid_data_irregular['lon'] = lons regrid_data_irregular = {'lat':[-71.88563091955609, -71.46239999061652, -70.88665451705731, -70.17267271384074, -69.33599972822388, -68.39229845573956, -67.3565270104634, -73.13081092575067, -72.49647721365037, -71.71508511194318, -70.8059133908041, -69.78772502062775, -68.67782580903652, -67.49160884705043, -66.24244233890475, -74.787438394019, -74.08334405003902, -73.22350177108659, -72.23195358717996, -71.13110091544634, -69.94074739852175, -68.67782580903652, -67.3565270104634, -76.42444652319007, 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