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updated remaining tutorials to oggm v16 #156

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caced13
updated remaining tutorials to oggm v16
lilianschuster Mar 18, 2026
9c12357
removed cell output
lilianschuster Mar 18, 2026
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45 changes: 38 additions & 7 deletions notebooks/tutorials/inversion.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -66,6 +66,9 @@
"# This is useful here\n",
"cfg.PARAMS['use_multiprocessing'] = True\n",
"\n",
"# continue if some individual glaciers give errors\n",
"cfg.PARAMS['continue_on_error'] = True\n",
"\n",
"# RGI file\n",
"path = utils.get_rgi_region_file(rgi_region)\n",
"rgidf = gpd.read_file(path)\n",
Expand All @@ -82,7 +85,7 @@
"# (we specifically need `geometries.pkl` in the gdirs)\n",
"cfg.PARAMS['border'] = 80\n",
"base_url = ('https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/'\n",
" 'L3-L5_files/2025.6/centerlines/W5E5/per_glacier_spinup') # todo<-- here is an issue with preprocessed gdir...todo\n",
" 'L3-L5_files/2025.6/centerlines/W5E5/per_glacier_spinup')\n",
"gdirs = workflow.init_glacier_directories(rgidf, from_prepro_level=3,\n",
" prepro_base_url=base_url)\n",
"\n",
Expand Down Expand Up @@ -181,6 +184,27 @@
"There are only 35 glaciers in the Pyrenees! That's why the run was relatively fast."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# is there any glacier that is failing?\n",
"failing_glaciers = df[df.isna().any(axis=1)].index\n",
"df[df.isna().any(axis=1)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# if yes, remove that glacier, for the further analysis \n",
"df = df.dropna()"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -441,8 +465,9 @@
"# The default path of the geotiff file is in the glacier directory with the name \"distributed_thickness.tif\"\n",
"# Let's check if the file exists\n",
"for gdir in gdirs:\n",
" path = os.path.join(gdir.dir, 'distributed_thickness.tif')\n",
" assert os.path.exists(path)"
" if gdir.rgi_id not in failing_glaciers:\n",
" path = os.path.join(gdir.dir, 'distributed_thickness.tif')\n",
" assert os.path.exists(path)"
]
},
{
Expand Down Expand Up @@ -482,7 +507,8 @@
"metadata": {},
"outputs": [],
"source": [
"rgi_ids = ['RGI60-11.0{}'.format(i) for i in range(3205, 3211)]\n",
"# 'RGI60-11.03207' is failing for OGGM v1.6.3, so we only show 3208 to 3211, instead of 3205 to 3211\n",
"rgi_ids = ['RGI60-11.0{}'.format(i) for i in range(3208, 3211)] \n",
"sel_gdirs = [gdir for gdir in gdirs if gdir.rgi_id in rgi_ids]\n",
"graphics.plot_googlemap(sel_gdirs)\n",
"# you might need to install motionless if it is not yet in your environment\n",
Expand All @@ -509,7 +535,7 @@
"metadata": {},
"outputs": [],
"source": [
"graphics.plot_distributed_thickness(sel_gdirs)"
"graphics.plot_distributed_thickness(sel_gdirs);"
]
},
{
Expand All @@ -532,7 +558,7 @@
"metadata": {},
"outputs": [],
"source": [
"graphics.plot_inversion(sel_gdirs, extend_plot_limit=True)"
"graphics.plot_inversion(sel_gdirs, extend_plot_limit=True);"
]
},
{
Expand Down Expand Up @@ -627,6 +653,11 @@
],
"metadata": {
"hide_input": false,
"kernelspec": {
"display_name": "Python [conda env:oggm_v16]",
"language": "python",
"name": "conda-env-oggm_v16-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
Expand All @@ -637,7 +668,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.4"
"version": "3.11.3"
},
"metadata": {
"interpreter": {
Expand Down
100 changes: 77 additions & 23 deletions notebooks/tutorials/preprocessing_errors.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@
"outputs": [],
"source": [
"# W5E5 centerlines\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/centerlines/W5E5/per_glacier_spinup/RGI62/b_080/L5/summary/' #todo-wait-until-gdir-ready"
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/centerlines/W5E5/per_glacier_spinup/RGI62/b_080/L5/summary/'"
]
},
{
Expand Down Expand Up @@ -171,7 +171,7 @@
"outputs": [],
"source": [
"# W5E5 elevation bands\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2023.3/elev_bands/W5E5/RGI62/b_080/L5/summary/'\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/elev_bands/W5E5/per_glacier_spinup/RGI62/b_080/L5/summary/'\n",
"# this can take some time\n",
"df_elev = []\n",
"# we don't look at RGI19 (Antarctic glaciers), because no climate available for CRU\n",
Expand Down Expand Up @@ -218,8 +218,10 @@
"metadata": {},
"source": [
"- **Compare different climate datasets**\n",
" - this works only when using OGGM v1.4 urls (comparing **CRU vs ERA5**)\n",
" - in OGGM v1.6 (state: March 2023), only GSWP3_W5E5 exists"
" - comparing **ERA5 vs GSWP3_W5E5** (using OGGM v1.6.3 2025.6 gdirs) \n",
" - comparing **ERA5 vs CRU** (using OGGM v1.4) \n",
"\n",
"*CRU not available for region 19, so we exclude this region from the intercomparison*"
]
},
{
Expand All @@ -228,17 +230,50 @@
"metadata": {},
"outputs": [],
"source": [
"# attention here OGGM_v1.4 is used and this is just for demonstration purposes how to compare\n",
"# attention here OGGM_v1.6 is used and this is just for demonstration purposes how to compare\n",
"# different preprocessed directories!\n",
"# This is CRU + centerlines. But you can try CRU+elev_bands, or ERA5+elev_bands, etc!\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.4/L3-L5_files/CRU/centerlines/qc3/pcp2.5/no_match/RGI62/b_040/L5/summary/'\n",
"# This is ERA5 + elevation bands ... \n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/elev_bands/ERA5/per_glacier_spinup/RGI62/b_080/L5/summary/'\n",
"# this can take some time\n",
"df_cru_v14 = []\n",
"# we don't look at RGI19 (Antarctic glaciers), because no climate available for CRU\n",
"df_era5_v16 = []\n",
"for rgi_reg in range(1, 19):\n",
" fpath = utils.file_downloader(url + f'glacier_statistics_{rgi_reg:02d}.csv')\n",
" df_cru_v14.append(pd.read_csv(fpath, index_col=0, low_memory=False))\n",
"df_cru_v14 = pd.concat(df_cru_v14, sort=False).sort_index()"
" df_era5_v16.append(pd.read_csv(fpath, index_col=0, low_memory=False))\n",
"df_era5_v16 = pd.concat(df_era5_v16, sort=False).sort_index()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# The same for W5E5 \n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/elev_bands/W5E5/per_glacier_spinup/RGI62/b_080/L5/summary/'\n",
"df_w5e5_v16 = []\n",
"for rgi_reg in range(1, 19):\n",
" fpath = utils.file_downloader(url + f'glacier_statistics_{rgi_reg:02d}.csv')\n",
" df_w5e5_v16.append(pd.read_csv(fpath, index_col=0, low_memory=False))\n",
"df_w5e5_v16 = pd.concat(df_w5e5_v16, sort=False).sort_index()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rel_area_cent_era5_v16 = df_era5_v16.loc[~df_era5_v16['error_task'].isnull()].rgi_area_km2.sum() / df_era5_v16.rgi_area_km2.sum() * 100\n",
"rel_area_cent_w5e5_v16 = df_w5e5_v16.loc[~df_w5e5_v16['error_task'].isnull()].rgi_area_km2.sum() / df_w5e5_v16.rgi_area_km2.sum() * 100\n",
"print(f\"% area errors all sources for W5E5 is {rel_area_cent_w5e5_v16:.2f}% compared to {rel_area_cent_era5_v16:.2f}% for ERA5\")\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*overall, similar amount of failing area between W5E5 and ERA5*"
]
},
{
Expand All @@ -247,15 +282,22 @@
"metadata": {},
"outputs": [],
"source": [
"# Now OGGM v1.4\n",
"# This is CRU + elev_bands. But you can try CRU+elev_bands, or ERA5+elev_bands, etc!\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.4/L3-L5_files/CRU/elev_bands/qc3/pcp2.5/no_match/RGI62/b_080/L5/summary/'\n",
"df_cru_v14 = []\n",
"for rgi_reg in range(1, 19):\n",
" fpath = utils.file_downloader(url + f'glacier_statistics_{rgi_reg:02d}.csv')\n",
" df_cru_v14.append(pd.read_csv(fpath, index_col=0, low_memory=False))\n",
"df_cru_v14 = pd.concat(df_cru_v14, sort=False).sort_index()\n",
"\n",
"# ERA5 uses a different precipitation factor in OGGM_v1.4\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.4/L3-L5_files/ERA5/centerlines/qc3/pcp1.6/no_match/RGI62/b_040/L5/summary/'\n",
"# this can take some time\n",
"url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.4/L3-L5_files/ERA5/elev_bands/qc3/pcp1.6/no_match/RGI62/b_080/L5/summary/'\n",
"df_era5_v14 = []\n",
"# we don't look at RGI19 (Antarctic glaciers), because no climate available for CRU\n",
"for rgi_reg in range(1, 19):\n",
" fpath = utils.file_downloader(url + f'glacier_statistics_{rgi_reg:02d}.csv')\n",
" df_era5_v14.append(pd.read_csv(fpath, index_col=0, low_memory=False))\n",
"df_era5_v14 = pd.concat(df_era5_v14, sort=False).sort_index()"
"df_era5_v14 = pd.concat(df_era5_v14, sort=False).sort_index()\n"
]
},
{
Expand All @@ -266,15 +308,14 @@
"source": [
"rel_area_cent_era5_v14 = df_era5_v14.loc[~df_era5_v14['error_task'].isnull()].rgi_area_km2.sum() / df_era5_v14.rgi_area_km2.sum() * 100\n",
"rel_area_cent_cru_v14 = df_cru_v14.loc[~df_cru_v14['error_task'].isnull()].rgi_area_km2.sum() / df_cru_v14.rgi_area_km2.sum() * 100\n",
"print(f\"% area errors all sources for ERA5 is {rel_area_cent_era5_v14:.2f}% compared to {rel_area_cent_cru_v14:.2f}% for CRU\")\n",
" "
"print(f\"% area errors all sources for ERA5 is {rel_area_cent_era5_v14:.2f}% compared to {rel_area_cent_cru_v14:.2f}% for CRU\") "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*more than three times fewer errors from the climate tasks occur when using ERA5 than when using CRU* !"
"*more than three times fewer errors from the climate tasks occur when using ERA5 than when using CRU* ! (not the E"
]
},
{
Expand All @@ -293,8 +334,8 @@
"print('% area errors from all sources for centerlines is: \\n'+\n",
" f'{rel_area_cent_cru_v14:.2f}% for CRU and OGGM_v14 \\n'+\n",
" f'{rel_area_cent_era5_v14:.2f}% for ERA5 and OGGM_v14 \\n'+\n",
" f'{rel_area_cent:.2f}% for W5E5 and OGGM_v16')\n",
" "
" f'{rel_area_cent_w5e5_v16:.2f}% for W5E5 and OGGM_v16 \\n' +\n",
" f'{rel_area_cent_era5_v16:.2f}% for ERA5 and OGGM_v16') "
]
},
{
Expand All @@ -312,15 +353,28 @@
"source": [
"## What's next?\n",
"\n",
"- A more detailed analysis of the type, amount and relative failing glacier area (in total and per RGI region) can be found in [this error analysis jupyter notebook](https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~lschuster/error_analysis/error_analysis_v1.ipynb?flush_cache=true). It also includes an error analysis for different [MB calibration and climate quality check methods](https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~lschuster/error_analysis/error_analysis_v1.ipynb?flush_cache=true#Analysis-for-Level-5-pre-processing-directories!).\n",
"- If you are interested in how the “common” non-failing glaciers differ in terms of historical volume change, total mass change and specific mass balance between different pre-processed glacier directories, you can check out [this jupyter notebook](https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~lschuster/error_analysis/working_glacier_gdirs_comparison.ipynb?flush_cache=true).\n",
"- A more detailed analysis of the type, amount and relative failing glacier area (in total and per RGI region) can be found in [this OGGM v1.6.3 error analysis jupyter notebook](https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~oggm/oggm-standard-projections/analysis_notebooks/1.6.3_2025_6_gdirs_proj_comparisons/0_error_analysis_gdirs_oggm_v16_2025.6.ipynb)\n",
"- If you are interested in how the “common” non-failing glaciers differ in terms of historical volume change, total mass change and specific mass balance between different pre-processed glacier directories, you can check out [this jupyter notebook](https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~oggm/oggm-standard-projections/analysis_notebooks/1.6.3_2025_6_gdirs_proj_comparisons/3_volume_projection_differences.ipynb)\n",
"- Reasons for the different error, calibration and projection differences between preprocessed glacier directories of OGGM v1.6. are summarised in this [OGGM blogpost](https://oggm.org/2026/01/07/oggm_v16-gdirs-and-projection-options/).\n",
"- return to the [OGGM documentation](https://docs.oggm.org)\n",
"- back to the [table of contents](../welcome.ipynb)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"hide_input": false,
"kernelspec": {
"display_name": "Python [conda env:oggm_v16]",
"language": "python",
"name": "conda-env-oggm_v16-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
Expand All @@ -331,7 +385,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.11.3"
},
"toc": {
"base_numbering": 1,
Expand Down
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