Programming project

/100

round(a * T + b, 6)

e('Average daily cycle of soil temperature')

%

/100

Programming project

100

np.allclose(df.iloc[:6].mean(), dfh.head(1))

>>> round(temperature_change_with_hysteresis(292, 100)[1],1) 288.0 >>> round(temperature_change_with_hysteresis(265, 100)[1],1) 233.0

>>> a = (0.7 - 0.3) / (250 - 280) >>> b = 0.7 - a * 250 >>> alpha_from_temperature(249) 0.7 >>> alpha_from_temperature(281) 0.3 >>> abs(alpha_from_temperature(265) - 0.5) <= 0.00001 True >>> abs(alpha_from_temperature(275) - 0.366666) <= 0.00001 True

Programming project

18 rain days.

13 rain days.

61368

2015-01-01 00:00:00.

dfh["RR"]

annual_precip = pd.DataFrame() annual_precip["Average Precipitation"] = df["RR"].resample("7D").sum().resample("Y").mean() annual_precip.set_index(annual_precip.index.year) # As DataFrame for the looks!

# Split the DataFram into 3 DataFrames either using sum or average and merge them back together # This is a design choice for the columns to stay in their current order. dfh = pd.concat([df.resample('H').mean()[['DD', 'FF', 'GSX', 'P', 'RF']], df[['RR', 'SO']].resample('H').sum(), df.resample('H').mean()[['TB1', 'TB2', 'TB3', 'TL', 'TP']]], axis = 1) dfh

1 hours

pr_99 = dfh['RR'].replace(0, np.NaN).quantile(0.99)

df['RR'].resample('H').sum()

a = dfh.iloc[0, 0:9] b = df.iloc[0:6, [0,1,2,3,4,7,8,9,10]].mean() for i in range(len(a)): print(f'{a.index[i]} is close to? {np.isclose(a[i], b[i])}')

explore the dfh dataframe. Explain, in plain words, what the purpose of .resample('H') followed by mean() is. Explain what .resample('H').max() and .resample('H').sum() would do.

i actually dont know exactli what its doing

File "__main__", line 23, in __main__.temperature_change_with_hysteresis Failed example: np.isclose(t[100], 233, atol=10e-02) Expected: True Got: True

Programming project

TypeError

KeyError Traceback

920.56 (m/year)

def asr(alpha=0.3): s = 1362 return (1 - alpha) * s / 4 def olr(t, tau=0.611): sigma = 5.67 10 ** (-8) return tau sigma * t ** 4 def temperature_change_with_hysteresis(t0, n_years, tau=0.611): """Temperature change scenario after change of transmissivity.

def to_hourly(x): return x*6 dfh["RR"]=dfh["RR"].apply(to_hourly) dfh["SO"]=dfh["SO"].apply(to_hourly)

>>> print(f'{alpha_from_temperature(0)}') 0.7 >>> print(f'{alpha_from_temperature(1000)}') 0.3

Programming project

.drop() with that command you you keep the Index station from appearing in the dataframe. axis=1 the axis 1 is the index column of the station thath you want to drop.

Programming project

m

dfmeta is the name of the Data Frame. The command .loc orders a group of columns or rows (here columns of df). It checks which names are in the first data frame and reads them out. So that you get a short describtion.

row label of the data frame

Names: Marcela Violeta Lauria

axs.set_title('Soil temperatures 2020')

#I change your variable dfh dfh = df.resample('H').sum()

so we can see all the Table of the DataFrame

first column related to a number asociated with the station where the data is colected.

alpha = alpha_from_temperature()

dfh_DJF

ModuleNotFoundError: No module named 'matplotlib'

def to_hourly(x): return x * 6 dfh["RR"] = dfh["RR"].apply(to_hourly) dfh["SO"] = dfh["SO"].apply(to_hourly)

temperature_change_with_hysteresis

>>> print(f'{alpha_from_temperature(0)}') 0.7 >>> print(f'{alpha_from_temperature(1000)}') 0.3

Programming project

winddirection varies a lot at Patscherkofel, t

Seasonal cycle of snow height at Pitztaler Gletscher (2863m)

.sum()

Instructions

Programming project

Bachelor Thesis where this study originates from.

.sum()

5:6

In our case (df.meta.loc[df.columns]), all columns are returned.

(which would be axis=2)

the stabilization temperature with t0 = 292 and default tau is approximately 288K the stabilization temperature with t0 = 265 and default tau is approximately 233K

round(alpha, 4)

Programming project

daily cycle

dfh

<

dfh["RR"]

dfm= df.resample('M').mean()

according to 'H'

returns a series

this inturn increases the speed of parsing them.

defines the first column of the dataframe as 1.

# Task 01-04

if temperatures[i] < 273.15:

return a * T + b

Programming project

Programming project

dfTB1_20 = dfh.TB1[dfh.TB1.index.year == 2020] plt.plot(dfTB1_20, linewidth=0.5, label='10cm') dfTB2_20 = dfh.TB2[dfh.TB2.index.year == 2020] plt.plot(dfTB2_20, linewidth=0.5, label='20cm') dfTB3_20 = dfh.TB3[dfh.TB3.index.year == 2020] plt.plot(dfTB3_20, linewidth=0.5, label='50cm')

Verify that the three soil temperatures have approximately the same average value over the entire period

DJF_ave_RR_per_day = round(dfDJF.RR.mean(), 0) JJA_ave_RR_per_day = round(dfJJA.RR.mean(), 0)

bins=round(bs)

919.84

(dfwRR*24*365).resample('Y').mean()

".resample('H')" reduces the dataframe to only the hourly data. ".mean()" returns the average of our data across a specified axis. In our cas the hourly data to the 10-min-data we had before. ".resample('H').max()" would take the 10-min data and display it as a dataframe with the maximums of the hourly values. ".resample('H').sum()" would take the sum and compute the hourly values from the 10-min data.

.loc[] is primarily label based, but may also be used with a boolean array and accesses a group of rows and columns by label(s) or a boolean array.

An integer index starting from 1 is assigned to the DataFrame by default.

print(temperature_change_with_hysteresis(292, 100, tau = 0.611)) print(temperature_change_with_hysteresis(265, 100, tau = 0.611))

Examples >>> alpha_from_temperature(249) 0.7 >>> alpha_from_temperature(281) 0.3 """

alpha : float, optional the planetary albedo

As we experience everyday, we see from the windrose that the strongest wind comes from the North (Nordkette) and blows southwoards.

plt.xlabel('time')

'crimson'

6

6

bins=120

for v in df.columns:

Bonus

the stabilization temperature with t0 = 292 and default tau is approximately 288K the stabilization temperature with t0 = 265 and default tau is approximately 233K

Group project: the Climate System

variability and ENSO (open research question)

A very big volcano erruption . The eruptions must inject over 100,000 tons of SO 2 into the stratosphere are considered to be large enough to affect the Earth's climate on a scale of more than 1 year. This is due to the optical properties of SO 2 and sulfate aerosols, which strongly absorb or scatter solar radiation, creating a global layer of sulfuric acid haze. Another process that can influence temperature variability and change at the global scale is the the distance between earth and sun. These orbital changes modify the total amount of sunlight reaching the Earth by up to 25% at midlatitudes. This effect is called Milankovitch cycle. Solar radiation can also influence temperature variability at global scale. Every 11 years the number of sunspots changes from a maximum number to a minimum number. The sun emits slightly more radiation during active periods of sunspots. While more sunspots may contribute to warmer global climate, less sunspots appear to be associated with a cooler global climate.

If every year the CO 2 concentration in the atmosphere will increase, the global temperature will rise.

The increase between 1980 and 1985 was from 339ppm to 346ppm. The increase between 2016 and 2021 was from 403ppm to 415ppm

absorb more CO 2 from the atmosphere than in winter.

tundra

ax1.plot(co2average, label = 'co2 concentration')

onal means "along a latitudinal circle" or in the west–east direction. Zonal flow is a meteorological term regarding atmospheric circulation following a general flow pattern along latitudinal lines. Meridional means "along a longitudinal circle" (a.k.a. meridian) or in the north–south direction. Meridional flow is a general air flow pattern from north to south, or from south to north, along the Earth's longitude lines (perpendicular to a zonal flow). Extratropical cyclones in this environment tend to be stronger and move slower

In the north pole and south pole we find the polar highs system. Between 40° and 55° latitude we find the middle-latitude cyclonic storms. Areas of high pressure systems are about 30°, called the subtropical highs. In the zone of the equator we find the ITCZ, where several low pressure system are located.

January and February t

https://homework.study.com/explanation/why-does-siberia-have-such-a-large-annual-temperature-range.html

has a circular current.

Instructions

Group project: the Climate System

calculated in the next cel

Questions

no sea

almost the same

is less direct solar radiatio

north atlantic drift.

cmap

Instructions

Group project: the Climate System

ax2.set_title('sea surface and 2m temperature - ERA5 1995-2005');

rising oscillating CO2

Polar Jet and suptropical Jet

The gulf stream has not only a bigger flow rate than the Kuroshio but also the geographic circumstances do not let the Kuroshio flow as far north as the gulf stream.

Instructions

Group project: the Climate System

print(co2_increase_1980_1985["average"]) print(co2_increase_2016_2021["average"])

[(co2_annual_avg.index.year >= 1980) & (co2_annual_avg.index.year <= 1985)

westwards wind

blowing towards the ITCZ

In the southern hemisphere between about -90° and -80° north the polar high is visible, in the south it still is lower than the global mean sea level pressure. Between -80° and about -45° the sup-polar low is visible causing precipitation year round. Between -45° and -15° there is the subtropical high and then between about -15° and 15° the equatorial low is visible, which causes year round precipitation. In the northern hemisphere the same pattern is visible (Ban 2022, Chapter 1, Slide 20)

During the summer months the continents are warming faster than the ocean, which causes a low pressure area over the continent that induces a flow from the sea to the continent which transports a lot of moist air, that is responsible for the precipitation, this effect reverses during winter (Goosse et al., 2010, Chapter 1 p. 7).

The temperature range is the largest in east russia and north canada. The cause for this is the tilt of the earth axis and the presence of land in this regions in comparison to the southern hemisphere. During winter this regions have the polar night and dont get any energy by the sunlight. In summertime this regeions are influenced by monthlong sun irradiance which is absorbed by the dark surface of the ground.

The tropics have a smaller temperature range than higher latitudes due to factors such as the distribution of heat by the Earth's atmosphere and oceans, the intensity of solar radiation, and atmospheric circulation patterns. In the tropics, the sun's rays are more directly overhead, causing the surface to heat up more quickly and be more effectively cooled by the warm, moist tropical air and the ocean. This heat stored in the ocean also helps maintain a stable temperature throughout the year. In contrast, higher latitudes have less direct sunlight, slower surface heating, less effective cooling, and more variable atmospheric circulation patterns, leading to greater seasonal temperature variation.

why the Northern Pacific Ocean does not have a similar pattern

he topography of North America, being more rugged and mountainous, also disrupts the flow of warm air and causes colder temperatures in the Pacific Northwest.

Aleutian Low

Northern Europe and the North Atlantic region have a relatively flat and low-lying topography which allows for the easy flow of warm air from the south, while North America and Russia have much more rugged and mountainous topography which can disrupt the flow of warm air and cause colder temperatures. Additionally, natural barriers such as the Scandinavian Mountains, the Atlantic Ocean, and the British Isles block cold Arctic air from reaching Europe, keeping the region warmer.

The North Atlantic Oscillation

Group project: the Climate System

Anomaly

An so called internal driver of climate change could be any form of ocean current change.

Rising CO2

Answer No. 1

get deviated

his is why we can see an accumulation of low-pressure systems between certain logitudes and high-pressure systems in others.

Singular pressure systems can't (hardly can) overcome such a cellborde

Both precipitation mixima are called monsoon. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

with continental climate

heating capacit

¶(Maps below) The temperature range is way higher in higher latitudes, beacuase there are cold (low temperatures) and warm seasons (high temperatures). As a comparison, in the temperature differences in the Tropics between the seasonal changes (rain- and dry-periods) are not that high, therefore the total range is not that big.

Answers for No. 1

positioning of the continents how they are

'bwr'

Instructions

6

Answer:

by anthropogenic sources

hese form due to the air from the polar cells moving to the equator

orm these strong lows.

As the ITCZ approaches these locations, it brings strong precipitation due to the lifting of the moist air in the convergence in the ITCZ.

Over the eastern pacific it is just slightly north of the equator. Over south America it diverges further south due to the land. Over the Atlantic it is again closer to the equator before going drastically to the south over Africa to almost 20 deg. Over the Indian ocean and Australia, it stays in that range with the same tendencies land vs sea.

Answer:

big body of water nearby

is bigger in the higher latitudes

The gulf stream brings heat from the tropics to these latitudes whereas in the Pacific or east Russia there is no such ocean current. In the Pacific the current transporting heat from the tropics exist east of Japan but due to the huge extent of the Pacific that heat doesn’t reach Alaska for example but is distributed in the water before (see slide 26, Lecture 01).

cmap= 'seismic'

Group project: the Climate System

ds.t2m.mean(dim='time'))

ator by the Coriolis force,

Between 75°N - 90°N are the cold highs. There the weak zonal wind (ZW) blows to the east and the weak meridional wind (MW) to the north. In the southern hemisphere 75°S - 90°S the outlets of the low pressure areas can be seen. In this area, ZW blows mostly to the west and MW to the north. At the poles, the strength of the two winds is fairly balanced.

Thus, certain latitude zones are characterized by different air pressure and wind conditions depending on the season.

Inner

Siberia, where the effect of low heat capacity over land is amplified by the strong Siberian High during winter, allowing for net energy loss because of the missing cloud cover due to subsidence. (Britannica) Also, there can be strong temperature inversions in winter, leading to stable conditions, therefore strong cooling and very cold temperatures.

balancing each other

North Atlantic Oscillation / Gulf stream

Group project: the Climate System

Regarding to this source, we chose the time range 1995 to 2003. Firstly we plotted the gloabl average to get an overview of our data and the global impact of ENSO. Thereby we found it striking, how clearly a temperature and percipitation rise can be seen during the winter of 1997/98. Based on this plot, we decided to pick the month November to April for the anamoly map for El Niño. On the other hand the effect of La Niña cannot be seen so clearly in a global average map. After some research, we also didn't find any particular months, which are very typical or representive for La Niña. That's why we decided to choose the entire 3 years (1999-2001) for the anomaly map.

sst_a = weighted_sst_c sst_a.sel(time = slice('1995', '2002')).plot(color = 'deepskyblue') sst_a.sel(time = slice('1997-11', '1998-04')).plot(color = 'red', label = 'Wintermonate El Niño' ) sst_a.sel(time = slice('1999', '2001')).plot(color = 'darkblue', label = 'La Niña Jahre' ) #peaks.sel(time = slice('1995', '2002')).plot() plt.title('Global mean sea surface temperature') plt.ylabel('degrees in °C') plt.legend();

6

All the cells of the general atmospheric circulation and the deflection of the winds due to coriolis can be seen in the plot.

the right of their heading.

and moister

January and Febuary

In the polar region the temperature range is the largest. During the polar night there is no solar radiation up to half of a year resulting in low temperatures. That's why the temperature anaomlies can get very big, as solar radiation in the summer can lead to melting of ice, seasonal snow covers and in general higher temperatures.

more exposed to solar radiation.

it is closely related to the Arcitc oscillation, which also takes place over the Pacific ocean

Due to the Thermohaline circulation, the northern Atlcatnic ocean is much warmer than at comparable latitudes in the northern Pacific

. Due to the fact that the Arctic Circle had a much greater warming (factor 4) than the surroundings (Rantanen et al. 2022), the range in temperature is much greater

Due to the North atlantic oscilation there is a higher air pressure above the Azores than to the surroundings (Azores high), near Greenland and Icleand we can find lower air pressure than to surrounding regions (sub-polar low).

t2m_annualcycle_max = dst2m.t2m.groupby('time.month').max() t2m_annualcycle_min = dst2m.t2m.groupby('time.month').min() t2m_annualcycle_range = (t2m_annualcycle_max - t2m_annualcycle_min).mean(dim = 'month')

Group project: the Climate System

probably global warming.

Group project: the Climate System

wind directions at ground level: due to cell circulation directions (two neighboring cells i.e. warm/cold air masses of two cells move in opposite direction)

This is due to the greater distance to the oceans (continental weather)

stable air masses, persistent winds