Tutorial 4: Reconstructing Past Changes in Atmospheric Climate

Week 1, Day 4, Paleoclimate

Content creators: Sloane Garelick

Content reviewers: Yosmely Bermúdez, Dionessa Biton, Katrina Dobson, Maria Gonzalez, Will Gregory, Nahid Hasan, Paul Heubel, Sherry Mi, Beatriz Cosenza Muralles, Brodie Pearson, Jenna Pearson, Chi Zhang, Ohad Zivan

Content editors: Yosmely Bermúdez, Paul Heubel, Zahra Khodakaramimaghsoud, Jenna Pearson, Agustina Pesce, Chi Zhang, Ohad Zivan

Production editors: Wesley Banfield, Paul Heubel, Jenna Pearson, Konstantine Tsafatinos, Chi Zhang, Ohad Zivan

Our 2024 Sponsors: CMIP, NFDI4Earth

Tutorial Objectives

Estimated timing of tutorial: 20 minutes

In this tutorial, we’ll analyze δD and atmospheric CO₂ data from the EPICA Dome C ice core. Recall from the video that δD and δ¹⁸O measurements on ice cores record past changes in temperature and that measurements of CO₂ trapped in ice cores can be used for reconstructing past changes in Earth’s atmospheric composition.

By the end of this tutorial you will be able to:

• Plot δD and CO₂ records from the EPICA Dome C ice core

• Assess changes in temperature and atmospheric greenhouse gas concentration over the past 800,000 years

Setup

# installations ( uncomment and run this cell ONLY when using google colab or kaggle )

# !pip install pyleoclim

# imports
import pandas as pd
import matplotlib.pyplot as plt
import pooch
import os
import tempfile
import pyleoclim as pyleo

Install and import feedback gadget

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# @title Install and import feedback gadget

!pip3 install vibecheck datatops --quiet

from vibecheck import DatatopsContentReviewContainer
def content_review(notebook_section: str):
    return DatatopsContentReviewContainer(
        "",  # No text prompt
        notebook_section,
        {
            "url": "https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab",
            "name": "comptools_4clim",
            "user_key": "l5jpxuee",
        },
    ).render()


feedback_prefix = "W1D4_T4"

Figure Settings

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# @title Figure Settings
import ipywidgets as widgets  # interactive display

%config InlineBackend.figure_format = 'retina'
plt.style.use(
    "https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle"
)

Helper functions

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# @title Helper functions

def pooch_load(filelocation=None, filename=None, processor=None):
    shared_location = "/home/jovyan/shared/Data/tutorials/W1D4_Paleoclimate"  # this is different for each day
    user_temp_cache = tempfile.gettempdir()

    if os.path.exists(os.path.join(shared_location, filename)):
        file = os.path.join(shared_location, filename)
    else:
        file = pooch.retrieve(
            filelocation,
            known_hash=None,
            fname=os.path.join(user_temp_cache, filename),
            processor=processor,
        )

    return file

Video 1: Atmospheric Climate Proxies

Submit your feedback

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# @title Submit your feedback
content_review(f"{feedback_prefix}_Atmospheric_Climate_Proxies_Video")

If you want to download the slides: https://osf.io/download/szyhp/

Submit your feedback

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# @title Submit your feedback
content_review(f"{feedback_prefix}_Atmospheric_Climate_Proxies_Slides")

Section 1: Exploring past variations in atmospheric CO₂

As we learned in the video, paleoclimatologists can reconstruct past changes in atmospheric composition by measuring gases trapped in layers of ice from ice cores retrieved from polar regions and high-elevation mountain glaciers. We’ll specifically be focusing on paleoclimate records produced from the EPICA Dome C ice core from Antarctica.

Credit: Conway et al 2015, Nature Communications

Let’s start by downloading the data for the composite CO₂ record for EPICA Dome C in Antarctica:

# download the data using the url
filename_antarctica2015 = "antarctica2015co2composite.txt"
url_antarctica2015 = "https://www.ncei.noaa.gov/pub/data/paleo/icecore/antarctica/antarctica2015co2composite.txt"

data_path = pooch_load(
    filelocation=url_antarctica2015, filename=filename_antarctica2015
)  # open the file

co2df = pd.read_csv(data_path, skiprows=137, sep="\t")

co2df.head()

---------------------------------------------------------------------------
timeout                                   Traceback (most recent call last)
File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:468, in HTTPConnectionPool._make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
    464         except BaseException as e:
    465             # Remove the TypeError from the exception chain in
    466             # Python 3 (including for exceptions like SystemExit).
    467             # Otherwise it looks like a bug in the code.
--> 468             six.raise_from(e, None)
    469 except (SocketTimeout, BaseSSLError, SocketError) as e:

File <string>:3, in raise_from(value, from_value)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:463, in HTTPConnectionPool._make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
    462 try:
--> 463     httplib_response = conn.getresponse()
    464 except BaseException as e:
    465     # Remove the TypeError from the exception chain in
    466     # Python 3 (including for exceptions like SystemExit).
    467     # Otherwise it looks like a bug in the code.

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/http/client.py:1377, in HTTPConnection.getresponse(self)
   1376 try:
-> 1377     response.begin()
   1378 except ConnectionError:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/http/client.py:320, in HTTPResponse.begin(self)
    319 while True:
--> 320     version, status, reason = self._read_status()
    321     if status != CONTINUE:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/http/client.py:281, in HTTPResponse._read_status(self)
    280 def _read_status(self):
--> 281     line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1")
    282     if len(line) > _MAXLINE:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/socket.py:716, in SocketIO.readinto(self, b)
    715 try:
--> 716     return self._sock.recv_into(b)
    717 except timeout:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/ssl.py:1275, in SSLSocket.recv_into(self, buffer, nbytes, flags)
   1272         raise ValueError(
   1273           "non-zero flags not allowed in calls to recv_into() on %s" %
   1274           self.__class__)
-> 1275     return self.read(nbytes, buffer)
   1276 else:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/ssl.py:1133, in SSLSocket.read(self, len, buffer)
   1132 if buffer is not None:
-> 1133     return self._sslobj.read(len, buffer)
   1134 else:

timeout: The read operation timed out

During handling of the above exception, another exception occurred:

ReadTimeoutError                          Traceback (most recent call last)
File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/adapters.py:667, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    666 try:
--> 667     resp = conn.urlopen(
    668         method=request.method,
    669         url=url,
    670         body=request.body,
    671         headers=request.headers,
    672         redirect=False,
    673         assert_same_host=False,
    674         preload_content=False,
    675         decode_content=False,
    676         retries=self.max_retries,
    677         timeout=timeout,
    678         chunked=chunked,
    679     )
    681 except (ProtocolError, OSError) as err:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:802, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
    800     e = ProtocolError("Connection aborted.", e)
--> 802 retries = retries.increment(
    803     method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
    804 )
    805 retries.sleep()

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/util/retry.py:552, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    551 if read is False or not self._is_method_retryable(method):
--> 552     raise six.reraise(type(error), error, _stacktrace)
    553 elif read is not None:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/packages/six.py:770, in reraise(tp, value, tb)
    769         raise value.with_traceback(tb)
--> 770     raise value
    771 finally:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:716, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
    715 # Make the request on the httplib connection object.
--> 716 httplib_response = self._make_request(
    717     conn,
    718     method,
    719     url,
    720     timeout=timeout_obj,
    721     body=body,
    722     headers=headers,
    723     chunked=chunked,
    724 )
    726 # If we're going to release the connection in ``finally:``, then
    727 # the response doesn't need to know about the connection. Otherwise
    728 # it will also try to release it and we'll have a double-release
    729 # mess.

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:470, in HTTPConnectionPool._make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
    469 except (SocketTimeout, BaseSSLError, SocketError) as e:
--> 470     self._raise_timeout(err=e, url=url, timeout_value=read_timeout)
    471     raise

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:358, in HTTPConnectionPool._raise_timeout(self, err, url, timeout_value)
    357 if isinstance(err, SocketTimeout):
--> 358     raise ReadTimeoutError(
    359         self, url, "Read timed out. (read timeout=%s)" % timeout_value
    360     )
    362 # See the above comment about EAGAIN in Python 3. In Python 2 we have
    363 # to specifically catch it and throw the timeout error

ReadTimeoutError: HTTPSConnectionPool(host='www.ncei.noaa.gov', port=443): Read timed out. (read timeout=30)

During handling of the above exception, another exception occurred:

ReadTimeout                               Traceback (most recent call last)
Cell In[10], line 5
      2 filename_antarctica2015 = "antarctica2015co2composite.txt"
      3 url_antarctica2015 = "https://www.ncei.noaa.gov/pub/data/paleo/icecore/antarctica/antarctica2015co2composite.txt"
----> 5 data_path = pooch_load(
      6     filelocation=url_antarctica2015, filename=filename_antarctica2015
      7 )  # open the file
      9 co2df = pd.read_csv(data_path, skiprows=137, sep="\t")
     11 co2df.head()

Cell In[5], line 10, in pooch_load(filelocation, filename, processor)
      8     file = os.path.join(shared_location, filename)
      9 else:
---> 10     file = pooch.retrieve(
     11         filelocation,
     12         known_hash=None,
     13         fname=os.path.join(user_temp_cache, filename),
     14         processor=processor,
     15     )
     17 return file

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/pooch/core.py:239, in retrieve(url, known_hash, fname, path, processor, downloader, progressbar)
    236 if downloader is None:
    237     downloader = choose_downloader(url, progressbar=progressbar)
--> 239 stream_download(url, full_path, known_hash, downloader, pooch=None)
    241 if known_hash is None:
    242     get_logger().info(
    243         "SHA256 hash of downloaded file: %s\n"
    244         "Use this value as the 'known_hash' argument of 'pooch.retrieve'"
   (...)
    247         file_hash(str(full_path)),
    248     )

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/pooch/core.py:807, in stream_download(url, fname, known_hash, downloader, pooch, retry_if_failed)
    803 try:
    804     # Stream the file to a temporary so that we can safely check its
    805     # hash before overwriting the original.
    806     with temporary_file(path=str(fname.parent)) as tmp:
--> 807         downloader(url, tmp, pooch)
    808         hash_matches(tmp, known_hash, strict=True, source=str(fname.name))
    809         shutil.move(tmp, str(fname))

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/pooch/downloaders.py:220, in HTTPDownloader.__call__(self, url, output_file, pooch, check_only)
    218     # pylint: enable=consider-using-with
    219 try:
--> 220     response = requests.get(url, timeout=timeout, **kwargs)
    221     response.raise_for_status()
    222     content = response.iter_content(chunk_size=self.chunk_size)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/api.py:73, in get(url, params, **kwargs)
     62 def get(url, params=None, **kwargs):
     63     r"""Sends a GET request.
     64 
     65     :param url: URL for the new :class:`Request` object.
   (...)
     70     :rtype: requests.Response
     71     """
---> 73     return request("get", url, params=params, **kwargs)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/api.py:59, in request(method, url, **kwargs)
     55 # By using the 'with' statement we are sure the session is closed, thus we
     56 # avoid leaving sockets open which can trigger a ResourceWarning in some
     57 # cases, and look like a memory leak in others.
     58 with sessions.Session() as session:
---> 59     return session.request(method=method, url=url, **kwargs)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    584 send_kwargs = {
    585     "timeout": timeout,
    586     "allow_redirects": allow_redirects,
    587 }
    588 send_kwargs.update(settings)
--> 589 resp = self.send(prep, **send_kwargs)
    591 return resp

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs)
    700 start = preferred_clock()
    702 # Send the request
--> 703 r = adapter.send(request, **kwargs)
    705 # Total elapsed time of the request (approximately)
    706 elapsed = preferred_clock() - start

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/adapters.py:713, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    711     raise SSLError(e, request=request)
    712 elif isinstance(e, ReadTimeoutError):
--> 713     raise ReadTimeout(e, request=request)
    714 elif isinstance(e, _InvalidHeader):
    715     raise InvalidHeader(e, request=request)

ReadTimeout: HTTPSConnectionPool(host='www.ncei.noaa.gov', port=443): Read timed out. (read timeout=30)

Next, we can store this data as a Series in Pyleoclim:

ts_co2 = pyleo.Series(
    time=co2df["age_gas_calBP"] / 1000,
    value=co2df["co2_ppm"],
    time_name="Age",
    time_unit="kyr BP",
    value_name=r"$CO_2$",
    value_unit="ppm",
    label="EPICA Dome C CO2",
)

We can now plot age vs. CO₂ from EPICA Dome C:

ts_co2.plot(color="C1")

Notice that the x-axis is plotted with present-day (0 kyr) on the left and the past (800 kyr) on the right. This is a common practice when plotting paleoclimate time series data.

These changes in CO₂ are tracking glacial-interglacial cycles (Ice Ages) over the past 800,000 years. Recall that these Ice Ages occur as a result of changes in the orbital cycles of Earth: eccentricity (100,000 year cycle), obliquity (40,000 year cycle), and precession (21,000 year cycle). Can you observe them in the graph above?

Section 2: Exploring the relationship between δD and atmospheric CO₂

To investigate the relationship between glacial cycles, atmospheric CO₂ and temperature, we can compare CO₂ to a record of hydrogen isotopic values (δD) of ice cores, which is a proxy for temperature in this case. Remember, when interpreting isotopic measurements of ice cores, a more depleted δD value indicates cooler temperatures, and a more enriched δD value indicates warmer temperatures. This is the opposite relationship we have looked at previously with δ¹⁸O, not because we are looking at a different isotope, but because we are not looking at the isotopic composition of ice rather than the isotopic composition of the ocean.

Let’s download the EPICA Dome C δD data, store it as a Series, and plot the data:

# download the data using the url
filename_edc3deuttemp2007 = "edc3deuttemp2007.txt"
url_edc3deuttemp2007 = "https://www.ncei.noaa.gov/pub/data/paleo/icecore/antarctica/epica_domec/edc3deuttemp2007.txt"
data_path = pooch_load(
    filelocation=url_edc3deuttemp2007, filename=filename_edc3deuttemp2007
)  # open the file

dDdf = pd.read_csv(data_path, skiprows=91, encoding="unicode_escape", sep="\s+")
# remove nan values
dDdf.dropna(inplace=True)

dDdf.head()

---------------------------------------------------------------------------
timeout                                   Traceback (most recent call last)
File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:468, in HTTPConnectionPool._make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
    464         except BaseException as e:
    465             # Remove the TypeError from the exception chain in
    466             # Python 3 (including for exceptions like SystemExit).
    467             # Otherwise it looks like a bug in the code.
--> 468             six.raise_from(e, None)
    469 except (SocketTimeout, BaseSSLError, SocketError) as e:

File <string>:3, in raise_from(value, from_value)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:463, in HTTPConnectionPool._make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
    462 try:
--> 463     httplib_response = conn.getresponse()
    464 except BaseException as e:
    465     # Remove the TypeError from the exception chain in
    466     # Python 3 (including for exceptions like SystemExit).
    467     # Otherwise it looks like a bug in the code.

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/http/client.py:1377, in HTTPConnection.getresponse(self)
   1376 try:
-> 1377     response.begin()
   1378 except ConnectionError:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/http/client.py:320, in HTTPResponse.begin(self)
    319 while True:
--> 320     version, status, reason = self._read_status()
    321     if status != CONTINUE:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/http/client.py:281, in HTTPResponse._read_status(self)
    280 def _read_status(self):
--> 281     line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1")
    282     if len(line) > _MAXLINE:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/socket.py:716, in SocketIO.readinto(self, b)
    715 try:
--> 716     return self._sock.recv_into(b)
    717 except timeout:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/ssl.py:1275, in SSLSocket.recv_into(self, buffer, nbytes, flags)
   1272         raise ValueError(
   1273           "non-zero flags not allowed in calls to recv_into() on %s" %
   1274           self.__class__)
-> 1275     return self.read(nbytes, buffer)
   1276 else:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/ssl.py:1133, in SSLSocket.read(self, len, buffer)
   1132 if buffer is not None:
-> 1133     return self._sslobj.read(len, buffer)
   1134 else:

timeout: The read operation timed out

During handling of the above exception, another exception occurred:

ReadTimeoutError                          Traceback (most recent call last)
File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/adapters.py:667, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    666 try:
--> 667     resp = conn.urlopen(
    668         method=request.method,
    669         url=url,
    670         body=request.body,
    671         headers=request.headers,
    672         redirect=False,
    673         assert_same_host=False,
    674         preload_content=False,
    675         decode_content=False,
    676         retries=self.max_retries,
    677         timeout=timeout,
    678         chunked=chunked,
    679     )
    681 except (ProtocolError, OSError) as err:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:802, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
    800     e = ProtocolError("Connection aborted.", e)
--> 802 retries = retries.increment(
    803     method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
    804 )
    805 retries.sleep()

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/util/retry.py:552, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    551 if read is False or not self._is_method_retryable(method):
--> 552     raise six.reraise(type(error), error, _stacktrace)
    553 elif read is not None:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/packages/six.py:770, in reraise(tp, value, tb)
    769         raise value.with_traceback(tb)
--> 770     raise value
    771 finally:

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:716, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
    715 # Make the request on the httplib connection object.
--> 716 httplib_response = self._make_request(
    717     conn,
    718     method,
    719     url,
    720     timeout=timeout_obj,
    721     body=body,
    722     headers=headers,
    723     chunked=chunked,
    724 )
    726 # If we're going to release the connection in ``finally:``, then
    727 # the response doesn't need to know about the connection. Otherwise
    728 # it will also try to release it and we'll have a double-release
    729 # mess.

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:470, in HTTPConnectionPool._make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
    469 except (SocketTimeout, BaseSSLError, SocketError) as e:
--> 470     self._raise_timeout(err=e, url=url, timeout_value=read_timeout)
    471     raise

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/urllib3/connectionpool.py:358, in HTTPConnectionPool._raise_timeout(self, err, url, timeout_value)
    357 if isinstance(err, SocketTimeout):
--> 358     raise ReadTimeoutError(
    359         self, url, "Read timed out. (read timeout=%s)" % timeout_value
    360     )
    362 # See the above comment about EAGAIN in Python 3. In Python 2 we have
    363 # to specifically catch it and throw the timeout error

ReadTimeoutError: HTTPSConnectionPool(host='www.ncei.noaa.gov', port=443): Read timed out. (read timeout=30)

During handling of the above exception, another exception occurred:

ReadTimeout                               Traceback (most recent call last)
Cell In[13], line 4
      2 filename_edc3deuttemp2007 = "edc3deuttemp2007.txt"
      3 url_edc3deuttemp2007 = "https://www.ncei.noaa.gov/pub/data/paleo/icecore/antarctica/epica_domec/edc3deuttemp2007.txt"
----> 4 data_path = pooch_load(
      5     filelocation=url_edc3deuttemp2007, filename=filename_edc3deuttemp2007
      6 )  # open the file
      8 dDdf = pd.read_csv(data_path, skiprows=91, encoding="unicode_escape", sep="\s+")
      9 # remove nan values

Cell In[5], line 10, in pooch_load(filelocation, filename, processor)
      8     file = os.path.join(shared_location, filename)
      9 else:
---> 10     file = pooch.retrieve(
     11         filelocation,
     12         known_hash=None,
     13         fname=os.path.join(user_temp_cache, filename),
     14         processor=processor,
     15     )
     17 return file

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/pooch/core.py:239, in retrieve(url, known_hash, fname, path, processor, downloader, progressbar)
    236 if downloader is None:
    237     downloader = choose_downloader(url, progressbar=progressbar)
--> 239 stream_download(url, full_path, known_hash, downloader, pooch=None)
    241 if known_hash is None:
    242     get_logger().info(
    243         "SHA256 hash of downloaded file: %s\n"
    244         "Use this value as the 'known_hash' argument of 'pooch.retrieve'"
   (...)
    247         file_hash(str(full_path)),
    248     )

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/pooch/core.py:807, in stream_download(url, fname, known_hash, downloader, pooch, retry_if_failed)
    803 try:
    804     # Stream the file to a temporary so that we can safely check its
    805     # hash before overwriting the original.
    806     with temporary_file(path=str(fname.parent)) as tmp:
--> 807         downloader(url, tmp, pooch)
    808         hash_matches(tmp, known_hash, strict=True, source=str(fname.name))
    809         shutil.move(tmp, str(fname))

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/pooch/downloaders.py:220, in HTTPDownloader.__call__(self, url, output_file, pooch, check_only)
    218     # pylint: enable=consider-using-with
    219 try:
--> 220     response = requests.get(url, timeout=timeout, **kwargs)
    221     response.raise_for_status()
    222     content = response.iter_content(chunk_size=self.chunk_size)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/api.py:73, in get(url, params, **kwargs)
     62 def get(url, params=None, **kwargs):
     63     r"""Sends a GET request.
     64 
     65     :param url: URL for the new :class:`Request` object.
   (...)
     70     :rtype: requests.Response
     71     """
---> 73     return request("get", url, params=params, **kwargs)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/api.py:59, in request(method, url, **kwargs)
     55 # By using the 'with' statement we are sure the session is closed, thus we
     56 # avoid leaving sockets open which can trigger a ResourceWarning in some
     57 # cases, and look like a memory leak in others.
     58 with sessions.Session() as session:
---> 59     return session.request(method=method, url=url, **kwargs)

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    584 send_kwargs = {
    585     "timeout": timeout,
    586     "allow_redirects": allow_redirects,
    587 }
    588 send_kwargs.update(settings)
--> 589 resp = self.send(prep, **send_kwargs)
    591 return resp

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs)
    700 start = preferred_clock()
    702 # Send the request
--> 703 r = adapter.send(request, **kwargs)
    705 # Total elapsed time of the request (approximately)
    706 elapsed = preferred_clock() - start

File /opt/hostedtoolcache/Python/3.9.21/x64/lib/python3.9/site-packages/requests/adapters.py:713, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    711     raise SSLError(e, request=request)
    712 elif isinstance(e, ReadTimeoutError):
--> 713     raise ReadTimeout(e, request=request)
    714 elif isinstance(e, _InvalidHeader):
    715     raise InvalidHeader(e, request=request)

ReadTimeout: HTTPSConnectionPool(host='www.ncei.noaa.gov', port=443): Read timed out. (read timeout=30)

dDts = pyleo.Series(
    time=dDdf["Age"] / 1000,
    value=dDdf["Deuterium"],
    time_name="Age",
    time_unit="kyr BP",
    value_name=r"$\delta D$",
    value_unit="\u2030",
    label=r"EPICA Dome C $\delta D$",
)

dDts.plot()

When we observe the δD data, we see very similar patterns as in the atmospheric CO₂ data. To more easily compare the two records, we can plot the two series side by side by putting them into a MultipleSeries object. Since the δD and CO₂ values have different units, we can first standardize the series and then plot the data.

# combine series
ms = pyleo.MultipleSeries([dDts, ts_co2])

# standarize series and plot
ms.standardize().plot()

Now we can more easily compare the timing and magnitude of changes in CO₂ and δD at EPICA Dome C over the past 800,000 years. During glacial periods, δD was more depleted (cooler temperatures) and atmospheric CO₂ was lower. During interglacial periods, δD was more enriched (warmer temperatures) and atmospheric CO₂ was higher.

Questions 2: Climate Connection

1. Why do δD, CO₂ and glacial cycles covary so closely?

2. Can you identify glacial and interglacial periods? Today, are we in an interglacial or glacial period?

3. Do the cooling and warming periods of the cycles happen at the same rate?

4. What climate forcings do you think are driving these cycles?

# to_remove explanation

"""
1. During glacial periods, lower temperatures lead to more oceanic absorption of CO2, reducing atmospheric CO2 levels. During interglacial periods, the reverse happens. This mutual influence creates a feedback loop, resulting in the observed covariance between dD (a proxy for temperature), CO2 and glacial-interglacial cycles.
2. The glacial periods occur when dD is more negative (depleted) and atmospheric CO2 concentrations are lower, whereas interglacial periods occur when dD is more positive (enriched) and atmospheric CO2 concentrations are higher. Based on this, the most recent glacial period was ~20,000 years ago. Today, we are in an interglacial period. However, notice how the atmospheric CO2 concentration rapidly increases towards the present and exceeds the CO2 concentration of any other interglacial period over the past 800,000 years. What might be causing this?
3. The cooling periods tend to be more gradual while warming periods are relatively rapid. This pattern is especially apparent over the past 400,000 years.
4. These glacial-interglacial cycles are primarily driven by variations in Earth’s orbital parameters. These parameters include eccentricity, obliquity, and precession, which vary on timescales of ~100,000 years, ~40,000 years, and ~21,000 years, respectively. In later tutorials, we’ll learn how to identify temporal cyclicity in paleoclimate reconstructions and assess possible forcings with similar timescales of variation.

"""

'\n1. During glacial periods, lower temperatures lead to more oceanic absorption of CO2, reducing atmospheric CO2 levels. During interglacial periods, the reverse happens. This mutual influence creates a feedback loop, resulting in the observed covariance between dD (a proxy for temperature), CO2 and glacial-interglacial cycles.\n2. The glacial periods occur when dD is more negative (depleted) and atmospheric CO2 concentrations are lower, whereas interglacial periods occur when dD is more positive (enriched) and atmospheric CO2 concentrations are higher. Based on this, the most recent glacial period was ~20,000 years ago. Today, we are in an interglacial period. However, notice how the atmospheric CO2 concentration rapidly increases towards the present and exceeds the CO2 concentration of any other interglacial period over the past 800,000 years. What might be causing this?\n3. The cooling periods tend to be more gradual while warming periods are relatively rapid. This pattern is especially apparent over the past 400,000 years.\n4. These glacial-interglacial cycles are primarily driven by variations in Earth’s orbital parameters. These parameters include eccentricity, obliquity, and precession, which vary on timescales of ~100,000 years, ~40,000 years, and ~21,000 years, respectively. In later tutorials, we’ll learn how to identify temporal cyclicity in paleoclimate reconstructions and assess possible forcings with similar timescales of variation.\n\n'

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Summary

In this tutorial, we dove into the captivating world of paleoclimatology, focusing on the analysis of hydrogen isotopes (δD) and atmospheric CO₂ data from the EPICA Dome C ice core. This involved understanding how δD and δ¹⁸O measurements from ice cores can enlighten us about past temperature changes, and how trapped CO₂ in these ice cores can help us reconstruct shifts in Earth’s atmospheric composition.

By the end of the tutorial, you should be comfortable with plotting δD and CO₂ records from the EPICA Dome C ice core and assessing changes in temperature and atmospheric greenhouse gas concentrations over the past 800,000 years. In the next tutorial, we’ll introduce various paleoclimate data analysis tools.

Resources

Code for this tutorial is based on an existing notebook from LinkedEarth that explores EPICA Dome C paleoclimate records.

Data from the following sources are used in this tutorial:

• Jouzel, J., et al. Orbital and Millennial Antarctic Climate Variability over the Past 800,000 Years, Science (2007). https://doi.org/10.1126/science.1141038.

• Lüthi, D., Le Floch, M., Bereiter, B. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382 (2008). https://doi.org/10.1038/nature06949.

• Bereiter, B. et al., Revision of the EPICA Dome C CO₂ record from 800 to 600 kyr before present, Geoph. Res. Let. (2014). https://doi.org/10.1002/2014GL061957.