- Jan 2023
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notebooksharing.space notebooksharing.spaceNotebook11
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plt.title('precipitation anomalies 2010/11', fontsize='14')
Normally blue is for wet and red for dry
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Lots of carbon dioxide is stored in the regeons which are covered with permafrost. This carbon dioxide comes from dead organic plant matter which froze into the permfrost.If the temperatures are rising, so that the permafrost on the Earth's surface is melting, the plant matter starts to decay and CO2
OK yes but still the main source of increasing CO2 concentrations are our emissions
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result from this geostrophic wind
Close to the surface the wind is not geostrophic, yet it still follows these rules.
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source 1/PhysicalGeography(Lenkeit-Meezan)/04:_Global_Circulation/4.04:_Global_Circulation])
something broken here
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https://studyflix.de/erdkunde/monsun-3334
I'm learning a lot of new sources with you ;-)
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In contrast, at higher latitudes the solar radiation hits at a smaller angle leading to the energy being spread over a larger area
what does this have to do with the temperarture range?
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t2.groupby("time.month").mean()
No need to recompute here - not wrong either
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due to the absence of an overturning circulation.
This is the important bit of information - northern heat transport in the pacific is much lower than atlantic because no conveyor belt there
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atmosphere plays a huge role
Be more precise. You could mention "continentality" for example.
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(https://www.youtube.com/watch?v=mQr8Ixp8ZAE)
Youtube migtht be a good source to get acquainted with a subject, but be careful as it is also full of disinformation and exaggerated claims. How did you decide that this source was trustworthy?
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North America or Russia, like the winds, mountains, heat storage, atmospheric heat transport, the gulf stream,
This is a little bit qualitative, and you don't explain what you mean below. The part about the Gulf stream is correct.
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- Jun 2022
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notebooksharing.space notebooksharing.spaceNotebook2
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Add a marker for each station s = df.loc[df['Höhe [m]'] < 1000] ax.scatter(s['Länge [°E]'], s['Breite [°N]'], marker='o', color='C0', transform=ccrs.Geodetic(), s=40, edgecolors='k', linewidths=1, zorder=99, label='h < 1000 m a.s.l.');
Code duplication
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import cartopy.io.img_tiles as cimgt
Is this import really needed?
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