Assignment: future glacier change

Assignment: future glacier change#

In this assignment, you will explore how glaciers are projected to evolve over the 21st century under different climate scenarios. Using real model output from CMIP6-based glacier projections, your task is to load, analyze, and visualize ensemble data to assess both the magnitude and climate forcing uncertainty of future glacier change.

An important goal of the assignment is to practice working with multi-model ensemble data using xarray and `pandas. The other goal is to understand the concept of scenario dependence, glacier mass loss trajectories, and glacier runoff changes.

Recommended resources:

Import the packages#

import numpy as np
import matplotlib.pyplot as plt
import xarray as xr
import pandas as pd
import glob

Part 1: Rhone projections - volume and runoff for ssp126 and ssp585#

Generating the plots#

For this part, we will use the Rhone basin files we used in lesson 1. I’ll use the “for loop” method here to open all ssp126 files:

# The * indicates that we allow all kinds of patters here - i.e. all GCMs, but still ssp126
file_pattern = "../data/glaciers/6243/basin_6243_run_hydro_w5e5_gcm_merged_endyr2100_CMIP6_bc_2000_2019_*_ssp126.nc"

# Get all matching files
files = glob.glob(file_pattern)

# Create the containers
df_runoff_ssp126 = pd.DataFrame()
df_volume_ssp126 = pd.DataFrame()

for f in files:
    # Extract the GCM name from the file name
    gcm_name = f.split('2000_2019_')[1].split('_ssp')[0]

    # Open and compute
    with xr.open_dataset(f) as ds_tmp:
        ds_tmp = ds_tmp.sel(time=slice(2000, 2099)).load()
        tmp_volume = ds_tmp.volume.sum(dim='rgi_id') * 1e-9
        tmp_runoff = ds_tmp.runoff.sum(dim='rgi_id') * 1e-12

    # Store for later
    df_runoff_ssp126[gcm_name] = tmp_runoff.squeeze().to_series()
    df_volume_ssp126[gcm_name] = tmp_volume.squeeze().to_series()

Your task:

  • Load the SSP585 scenario data, just like we did for SSP126.

  • For both SSP126 and SSP585:

    • Calculate the relative glacier volume change, using 2020 as the baseline.

    • Calculate the relative glacier runoff change, using the 2000–2019 average as the baseline.

  • Then:

    • Plot both scenarios on the same graph (one color per scenario).

    • Show the median and 10–90% spread (interquartile range) across models.

    • Do this once for relative volume, and once for relative runoff (two plots total).

# Your answer here

Interpretation questions#

Volume change#

  • Why do we express glacier volume as a percentage of the 2020 value? What is the advantage of doing this?

  • How do the SSP126 and SSP585 projections differ in terms of median glacier volume change over the 21st century?

  • By how much does glacier volume decrease under each scenario by 2050? By 2100?

  • Median volume declines steeply until about 2050, then levels off in SSP126. What might cause this flattening?

  • The shaded bands represent the 10–90% range across the model ensemble. In which time periods is the climate forcing uncertainty the largest?

  • Is it appropriate to interpret the ensemble spread as a probability range? Why or why not?

  • Is the spread wider under SSP585 or SSP126 in 2100? Why might that be?

Glacier runoff#

  • Runoff appears more “noisy” than volume. What might explain these year-to-year fluctuations?

  • Are the fluctuations larger in one scenario compared to the other?

  • Describe the general patterns of runoff evolution: when is the runoff largest, is it increasing or decreasing in the future? By how many %?

  • Are there substantial differences between the scenarios?

  • What are the possible implications of these projections for downstream water availability in the Rhone basin?

  • How might this information be useful for decision-makers and water managers? What other information might they need?

# Your answer here

Part 2: Aral Sea projections#

Generating the plots#

Go to the data download page and download the tar file for basin number 2902 (Aral Sea). Repeat the reading in and the plots we did for the Rhone.

# Your answer here

Interpretation questions: Aral Sea vs Rhone#

Please take a careful look at the Aral Sea glacier volume and runoff projections, and compare them with the ones from the Rhone basin. Start by having a look at a map of the Aral Sea basin and do a quick search about the importance of water and the “water towers” (the mountains) there.

  • In which basin (Rhone or Aral) does the difference between SSP126 and SSP585 appear larger by the end of the century?

  • What might explain this stronger scenario dependence in one basin over the other? Think about the glaciers’ size, elevation, or climate setting.

  • Are glaciers still melting in the Aral Sea basin by 2100, for each scenario? How does this compare to the Rhone basin? What could explain the differences in end-of-century behaviour?

  • In both basins, runoff increases at first — but how do the timing and magnitude of these changes differ?

  • When is the maximum runoff reached in the Aral basin? And in the Rhone? How about the scenario dependance?

  • What do you think happens in the decades after this maximum? Why might runoff decline even as glaciers are still present?

  • Could the shape of the runoff curve be used as a warning for water managers?

  • Looking at the Aral Sea basin map, where are the glaciers located relative to population centres or rivers?

  • Why might changes in glacier runoff be especially important in this region?

  • Based on what you observe, how might the water resource challenges differ between the two basins?

  • Which basin appears more vulnerable to long-term glacier loss, and why?

# Your answer here