Create arctic_forcing repo to cite in the thesis

percurnicus · Apr 4, 2019 · 96055c5 · 96055c5
commit 96055c5
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diff --git a/Albedos.csv b/Albedos.csv
@@ -0,0 +1,93 @@
+Cloud Over Bright Sea Ice X,Cloud Over Bright Sea Ice Y,Cloud Over Dark Sea Ice X,Cloud Over Dark Sea Ice Y,Clear Sky Over Bright Ice X,Clear Sky Over Bright Ice Y,Cloud Over Ocean X,Cloud Over Ocean Y,Clear Sky Over Dark Ice X,Clear Sky Over Dark Ice Y,Clear Sky Over Ocean X,Clear Sky Over Ocean Y
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diff --git a/README.md b/README.md
@@ -0,0 +1,9 @@
+# Arctic Forcing
+
+This repo was made for Perry Vargas's Senior Thesis for the School of Earth and
+Space Exploration at Arizona State University. The point is to simply model the
+affect an ice free summer has on the global annual radiative forcing. It was
+found that it increased the global annual radiative forcing by $0.41\pm0.04
+Wm^{-2}$
+
+![results](ice_free.png)
diff --git a/albedos.py b/albedos.py
@@ -0,0 +1,114 @@
+import numpy as np
+import pandas as pd
+
+
+class Albedo:
+
+    def __init__(self, zeniths, albedos):
+        zeniths = np.array(zeniths)
+        albedos = np.array(albedos)
+        self._zeniths = zeniths[~np.isnan(zeniths)].copy()
+        self._albedos = albedos[~np.isnan(albedos)].copy()
+        sort_inds = np.argsort(self._zeniths)
+        self._zeniths = self._zeniths[sort_inds]
+        self._albedos = self._albedos[sort_inds]
+
+    @property
+    def zeniths(self):
+        return self._zeniths.copy()
+
+    @property
+    def albedos(self):
+        return self._albedos.copy()
+
+    def get_albedo(self, zeniths):
+        mask = zeniths <= 90
+        albedo = np.zeros(zeniths.shape)
+        albedo[mask] = np.interp(
+            x=zeniths[mask],
+            xp=self._zeniths,
+            fp=self._albedos,
+        )
+        return albedo
+
+
+class Albedos:
+
+    def __init__(self, filepath=None):
+        if filepath is None:
+            filepath = 'Albedos.csv'
+        self._filepath = filepath
+        self._albedos = pd.read_csv(filepath)
+        self._clear_ocean = Albedo(
+            zeniths=self._albedos['Clear Sky Over Ocean X'].values,
+            albedos=self._albedos['Clear Sky Over Ocean Y'].values
+        )
+        self._cloud_bright_ice = Albedo(
+            zeniths=self._albedos['Cloud Over Bright Sea Ice X'].values,
+            albedos=self._albedos['Cloud Over Bright Sea Ice Y'].values
+        )
+        self._cloud_ocean = Albedo(
+            zeniths=self._albedos['Cloud Over Ocean X'].values,
+            albedos=self._albedos['Cloud Over Ocean Y'].values
+        )
+        self._cloud_dark_ice = Albedo(
+            zeniths=self._albedos['Cloud Over Dark Sea Ice X'].values,
+            albedos=self._albedos['Cloud Over Dark Sea Ice Y'].values)
+        self._clear_bright_ice = Albedo(
+            zeniths=self._albedos['Clear Sky Over Bright Ice X'].values,
+            albedos=self._albedos['Clear Sky Over Bright Ice Y'].values
+        )
+        self._clear_dark_ice = Albedo(
+            zeniths=self._albedos['Clear Sky Over Dark Ice X'].values,
+            albedos=self._albedos['Clear Sky Over Dark Ice Y'].values,
+        )
+
+    def get_ice_albedo(self, zeniths, ice_thickness, temperature,
+                       clear_sky=True, sea_albedo=None):
+        if clear_sky:
+            bright_ice = self._clear_bright_ice
+            dark_ice = self._clear_dark_ice
+        else:
+            bright_ice = self._cloud_bright_ice
+            dark_ice = self._cloud_dark_ice
+
+        if sea_albedo is None:
+            sea_albedo = self.get_sea_albedo(zeniths, clear_sky)
+
+        bright_albedo = bright_ice.get_albedo(zeniths)
+        dark_albedo = dark_ice.get_albedo(zeniths)
+
+        albedo = np.zeros(zeniths.shape)
+
+        has_melt = temperature >= (-1 + 273.15)
+        is_thin_ice = ice_thickness < 0.5
+
+        thin_dry = ~has_melt & is_thin_ice
+        thin_melt = has_melt & is_thin_ice
+        thick_dry = ~has_melt & ~is_thin_ice
+        thick_melt = has_melt & ~is_thin_ice
+
+        fh = np.arctan(4 * ice_thickness) / np.arctan(4 * .5)
+        fh[fh > 1] = 1
+
+        albedo[thick_melt] = dark_albedo[thick_melt]
+        albedo[thick_dry] = bright_albedo[thick_dry]
+
+        albedo[thin_dry] = (
+            sea_albedo[thin_dry] * (1 - fh[thin_dry]) +
+            bright_albedo[thin_dry] * fh[thin_dry]
+        )
+        albedo[thin_melt] = (
+            sea_albedo[thin_melt] * (1 - fh[thin_melt]) +
+            bright_albedo[thin_melt] * fh[thin_melt]
+        )
+
+        return albedo
+
+    def get_sea_albedo(self, zeniths, clear_sky=True):
+        if clear_sky:
+            ocean = self._clear_ocean
+        else:
+            ocean = self._cloud_ocean
+        albedo = ocean.get_albedo(zeniths)
+        return albedo
diff --git a/baseline.py b/baseline.py
@@ -0,0 +1,54 @@
+import json
+from datetime import datetime
+
+import dateutil
+import numpy as np
+
+from albedos import Albedos
+from data_set import DataSet
+from net_forcing import get_radiative_forcing
+
+SIC_PATH = 'sic_day_GFDL-CM3_historical*'
+SIT_PATH = 'sit_day_GFDL-CM3_historical*'
+TAS_PATH = 'tas_3hr_GFDL-CM3_historical_r1i1p1_*.nc'
+CLT_PATH = 'tcdc.eatm.gauss.19[89]*.nc'
+
+BEGIN_DATE = datetime(1979, 1, 1, 0, 0, 0)
+NUM_YEARS = 20
+
+DELTA_T = 150
+
+
+if __name__ == '__main__':
+    print('Creating DataSet')
+    data_set = DataSet(
+        sic_path=SIC_PATH,
+        sit_path=SIT_PATH,
+        tas_path=TAS_PATH,
+        clt_path=CLT_PATH,
+        sic_scale=.01,
+        clt_scale=.01,
+    )
+    print('Getting Albedos')
+    albedos = Albedos()
+    year = dateutil.relativedelta.relativedelta(years=1)
+    rad_start_dates = [BEGIN_DATE + year * n for n in range(NUM_YEARS)]
+    forcings = []
+    for rad_start_date in rad_start_dates:
+        forcing = get_radiative_forcing(
+            start_date=rad_start_date,
+            delta_t=DELTA_T,
+            data_set=data_set,
+            albedos=albedos,
+        )
+        print(rad_start_date, forcing)
+        forcings.append(forcing)
+
+    out = {
+        date.isoformat(): forcing for date, forcing
+        in zip(rad_start_dates, forcings)
+    }
+    out['mean'] = np.mean(forcings)
+    out['std'] = np.std(forcings)
+    with open(f'baseline_delta_t_{DELTA_T}.json', 'w') as stream:
+        json.dump(out, stream, indent=4)
diff --git a/baseline_delta_t_150.json b/baseline_delta_t_150.json
@@ -0,0 +1,24 @@
+{
+    "1979-01-01T00:00:00": 2.626554012824042,
+    "1980-01-01T00:00:00": 2.637702032013413,
+    "1981-01-01T00:00:00": 2.670209941207299,
+    "1982-01-01T00:00:00": 2.6661356616010035,
+    "1983-01-01T00:00:00": 2.6157039161827953,
+    "1984-01-01T00:00:00": 2.5831371748325216,
+    "1985-01-01T00:00:00": 2.5715710441032873,
+    "1986-01-01T00:00:00": 2.6195439435319443,
+    "1987-01-01T00:00:00": 2.690760220332738,
+    "1988-01-01T00:00:00": 2.6981319543326383,
+    "1989-01-01T00:00:00": 2.696278090722977,
+    "1990-01-01T00:00:00": 2.6797325158619607,
+    "1991-01-01T00:00:00": 2.680042391514541,
+    "1992-01-01T00:00:00": 2.6721925880527713,
+    "1993-01-01T00:00:00": 2.6739578414839777,
+    "1994-01-01T00:00:00": 2.6462272576530164,
+    "1995-01-01T00:00:00": 2.657076583093866,
+    "1996-01-01T00:00:00": 2.6602427708709993,
+    "1997-01-01T00:00:00": 2.6732931864751706,
+    "1998-01-01T00:00:00": 2.651039782597768,
+    "mean": 2.653476645464437,
+    "std": 0.03430686844697131
+}