little picture - global mean sea level

Background on this little picture

a Little Picture reveals the global mean sea level trend

Sea level rise is one of the clearest indicators of climate change and puts millions living in coastal zone under threat of inundation. For this reason, the "classic curve" of the rise is presented in this Little Picture. Global mean sea level has been increasing 3.2mm over the satellite altimetry record. The Copernicus Sentinel-6 mission is extending sea- surface height measurements until at least 2030.

https://climate.esa.int/en/little-pictures-gallery/Global-mean-sea-level/

Data Sources

The CLIP uses the following dataset:

• ESA Sea Level CCI: Oceanic Indicators of Mean Sea Level Changes (MSL), Version 2.0, Cate dataset identifier: esacci.SEALEVEL.mon.IND.MSL.multi-sensor.multi-platform.MERGED.2-0.r1.

Data Preparation

Description

Data preparation comprises the following steps:

• Opening the Sea Level CCI dataset esacci.SEALEVEL.mon.IND.MSL.multi-sensor.multi-platform.MERGED.2-0.r1.
• Select time-series variable "Global mean sea level variations" (global_msl).
• Convert time-series into a data frame and save a CSV file data/global_msl.csv. The units are meters.

One-time script setup

If you do not have a Cate account yet, please visit Cate App, select Cate Cloud Service and register. Using the Cate credentials, login to the Cate JupyterLab. From the JupyterLab's Launcher, open a Terminal window and type

cd ~/work
git clone https://github.com/trevalabs/pytrevalabs.git
git clone https://github.com/trevalabs/clip_02_we_live_in_a_world_of_rising_seas.git

Note you can also use the JupyterLab's Git extension (left side bar) to clone the repos.

Running the script

In JupyterLab's File Browser navigate to /clip_02_we_live_in_a_world_of_rising_seas/scripts/dataprep and open the Notebook extract-sea-level.ipynb and run it.

To stay in sync with the repos, open a Terminal window and

cd ~/work/pytrevalabs
git pull --rebase
cd ~/work/clip_02_we_live_in_a_world_of_rising_seas.git
git pull --rebase

Note you can also use the JupyterLab's Git extension (left side bar) to update the repos.

Creating Visualisations

Work in Progress

CREDITS & LICENSE

• Idea by: Philipp Eales
• Processing Scripts by: Brockmann Consult
• Visualisation by: Ubilabs

The code in this repository is published under CC BY-SA 4.0 license