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CloudSat Calipso Heating Rates
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Climate
CloudSat Calipso Heating Rates
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ea7a633f
Commit
ea7a633f
authored
1 year ago
by
Aiko Voigt
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Adds plot of time-mean zonal-mean climatology of CRH
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plot_zonaltimemean_crh.ipynb
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ea7a633f
{
"cells": [
{
"cell_type": "markdown",
"id": "eb6a3095-fd76-401c-92f2-ed5c3473ccea",
"metadata": {},
"source": [
"# Plot zonal-mean time-mean cloud-radiative heating"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "9ead3a66-83ff-44bb-a8e0-4ae0de8d489d",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import xarray as xr\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"import warnings\n",
"warnings.filterwarnings(\"ignore\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "bc390f59-7338-4e56-8982-baa95ad74a16",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ds=xr.open_dataset(\"/jetfs/scratch/avoigt/CLOUDSAT/2B-FLXHR-LIDAR.P2_R05.heatingrates_binned.2006-2017.nc\")"
]
},
{
"cell_type": "markdown",
"id": "4e65bec4-04a2-4087-b088-5f839107ffd6",
"metadata": {},
"source": [
"Group by years. Average over years 2007-2016 as well as longitude. Do not use years 2006 and 2017 as these might not be complete."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "6645d248-4adb-4a1e-aad8-026d2fcfa2ac",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ds_mean=ds.groupby(ds.time.dt.year).mean(\"time\").sel(year=slice(2007,2016)).mean([\"year\",\"lon\"])"
]
},
{
"cell_type": "markdown",
"id": "f1ebaa8b-cb41-4fca-b4e7-37bbe1325aa9",
"metadata": {},
"source": [
"Plotting."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "31f754fd-b6df-4e64-a667-14ff91548e10",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"(0.0, 20.0)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.contourf(ds_mean.lat, ds_mean.height/1000, ds_mean[\"HR_allsky_sw\"]+ds_mean[\"HR_allsky_lw\"]\n",
" -(ds_mean[\"HR_clrsky_sw\"]+ds_mean[\"HR_clrsky_lw\"]), cmap=\"RdBu_r\", levels=np.linspace(-1,1,21), extend=\"both\")\n",
"plt.colorbar()\n",
"plt.xlabel(\"latitude\")\n",
"plt.ylabel(\"height / km\")\n",
"plt.title(\"2B-FLXHR-LIDAR.P2_R05 CRH 2007-2016\")\n",
"plt.ylim(0,20)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "cloudsat-calipso",
"language": "python",
"name": "cloudsat-calipso"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
%% Cell type:markdown id:eb6a3095-fd76-401c-92f2-ed5c3473ccea tags:
# Plot zonal-mean time-mean cloud-radiative heating
%% Cell type:code id:9ead3a66-83ff-44bb-a8e0-4ae0de8d489d tags:
```
python
import
xarray
as
xr
import
matplotlib.pyplot
as
plt
import
numpy
as
np
import
warnings
warnings
.
filterwarnings
(
"
ignore
"
)
```
%% Cell type:code id:bc390f59-7338-4e56-8982-baa95ad74a16 tags:
```
python
ds
=
xr
.
open_dataset
(
"
/jetfs/scratch/avoigt/CLOUDSAT/2B-FLXHR-LIDAR.P2_R05.heatingrates_binned.2006-2017.nc
"
)
```
%% Cell type:markdown id:4e65bec4-04a2-4087-b088-5f839107ffd6 tags:
Group by years. Average over years 2007-2016 as well as longitude. Do not use years 2006 and 2017 as these might not be complete.
%% Cell type:code id:6645d248-4adb-4a1e-aad8-026d2fcfa2ac tags:
```
python
ds_mean
=
ds
.
groupby
(
ds
.
time
.
dt
.
year
).
mean
(
"
time
"
).
sel
(
year
=
slice
(
2007
,
2016
)).
mean
([
"
year
"
,
"
lon
"
])
```
%% Cell type:markdown id:f1ebaa8b-cb41-4fca-b4e7-37bbe1325aa9 tags:
Plotting.
%% Cell type:code id:31f754fd-b6df-4e64-a667-14ff91548e10 tags:
```
python
plt
.
contourf
(
ds_mean
.
lat
,
ds_mean
.
height
/
1000
,
ds_mean
[
"
HR_allsky_sw
"
]
+
ds_mean
[
"
HR_allsky_lw
"
]
-
(
ds_mean
[
"
HR_clrsky_sw
"
]
+
ds_mean
[
"
HR_clrsky_lw
"
]),
cmap
=
"
RdBu_r
"
,
levels
=
np
.
linspace
(
-
1
,
1
,
21
),
extend
=
"
both
"
)
plt
.
colorbar
()
plt
.
xlabel
(
"
latitude
"
)
plt
.
ylabel
(
"
height / km
"
)
plt
.
title
(
"
2B-FLXHR-LIDAR.P2_R05 CRH 2007-2016
"
)
plt
.
ylim
(
0
,
20
)
```
%% Output
(0.0, 20.0)
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