Publications related to OGGM

Publications making use of the OGGM model

(that we are aware of)

Submitted / In review

  • Aguayo, R., Maussion, F., Schuster, L., Schaefer, M., Caro, A., Schmitt, P., Mackay, J., Ultee, L., Leon-Muñoz, J., and Aguayo, M.: Assessing the glacier projection uncertainties in the Patagonian Andes (40–56° S) from a catchment perspective, EGUsphere [preprint], doi:10.5194/egusphere-2023-232, 2023.
  • Hanus, S., Schuster, L., Burek, P., Maussion, F., Wada, Y., and Viviroli, D.: Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – Towards an improved representation of mountain water resources in global assessments, EGUsphere [preprint], doi:10.5194/egusphere-2023-2562, 2024.
  • van der Laan, L., Vlug, A., Scaife, A. A., Maussion, F., and Förster, K.: Decadal re-forecasts of glacier climatic mass balance, EGUsphere [preprint], doi:10.5194/egusphere-2024-387, 2024.
  • Mackay, J. D., Barrand, N. E., Hannah, D. M., Potter, E., Montoya, N., and Buytaert, W.: Physically-based modelling of glacier evolution under climate change in the tropical Andes, EGUsphere [preprint], doi:10.5194/egusphere-2024-863, 2024.
  • Zekollari, H., Huss, M., Schuster, L., Maussion, F., Rounce, D. R., Aguayo, R., Champollion, N., Compagno, L., Hugonnet, R., Marzeion, B., Mojtabavi, S., and Farinotti, D.: 21st century global glacier evolution under CMIP6 scenarios and the role of glacier-specific observations, EGUsphere [preprint], doi:10.5194/egusphere-2024-1013, 2024.


  • Caro, A., Condom, T., Rabatel, A., Champollion, N., García, N., and Saavedra, F.: Hydrological response of Andean Catchments to recent glacier mass loss, The Cryosphere, 18, 2487–2507, doi:10.5194/tc-18-2487-2024, 2024.
  • Chen, X., Yang, W., Li, Y., Yang, Y., Liu, J., Liu, Q.: Timing and extent of glacial fluctuations around Mt. Noijin Kangsang on the southern Tibetan Plateau during the Little Ice Age, Palaeogeogr. Palaeoclimatol. Palaeoecol., 640, 112092, doi:10.1016/j.palaeo.2024.112092, 2024.
  • Diaconu, C. -A., and Gottschling, N. M.: Uncertainty-Aware Learning with Label Noise for Glacier Mass Balance Modelling, IEEE Geoscience and Remote Sensing Letters, doi:10.1109/LGRS.2024.3356160, 2024.
  • Li, T., Heidler, K., Mou, L., Ignéczi, Á., Zhu, X. X., Bamber, J. L.: A high-resolution calving front data product for marine-terminating glaciers in Svalbard, Earth System Science Data, 16, 2, 919-939, doi:10.5194/essd-16-919-2024, 2024.
  • Möller, M., Recinos, B., Rastner, P., Marzeion, B.: Heterogeneous impacts of ocean thermal forcing on ice discharge from Greenland’s peripheral tidewater glaciers over 2000–2021, Scientific Reports, 14, 11316, doi:10.1038/s41598-024-61930-6, 2024.
  • Xiao, L., Li, S., Wu, K., Liu, S., Zhu, Y., Afzal, M.M., Zhou, J., Yi, Y., Wei, J., Duan, Y. and Shen, Y.: Geodetic-Data-Calibrated Ice Flow Model to Simulate Historical and Future Response of Glaciers in Southeastern Tibetan Plateau, Remote Sens., 16, 522, doi:10.3390/rs16030522, 2024.
  • Wang L, Yang S, Chen K, Liu S, Jin X, and Xie Y.: A Long-Duration Glacier Change Analysis for the Urumqi River Valley, a Representative Region of Central Asia., Remote Sens., 16(9), 1489, doi:10.3390/rs16091489, 2024.


  • Afzal, M. M., Wang, X., Sun, L., Jiang, T., Kong, Q., Luo, Y: Hydrological and dynamical response of glaciers to climate change based on their dimensions in the Hunza Basin, Karakoram, J. Hydrol., 617(PB), 128948, doi:10.1016/j.jhydrol.2022.128948, 2023.
  • Bolibar, J., Sapienza, F., Maussion, F., Lguensat, R., Wouters, B., and Pérez, F.: Universal Differential Equations for glacier ice flow modelling, Geosci. Model Dev., 16, 6671–6687, doi:10.5194/gmd-16-6671-2023, 2023.
  • Hock, R., Maussion, F., Marzeion, B. and Nowicki, S.: What is the global glacier ice volume outside the ice sheets?, J. Glaciol., 1–7, doi:10.1017/jog.2023.1, 2023.
  • Li, F., Maussion, F., Wu, G., Chen, W., Yu, Z., Li, Y. and Liu, G.: Influence of glacier inventories on ice thickness estimates and future glacier change projections in the Tian Shan range, Central Asia, J. Glaciol., 69(274), 266–280, doi:10.1017/jog.2022.60, 2023.
  • Malles, J., Maussion, F., Ultee, L., Kochtitzky, W., Copland, L. and Marzeion, B.: Exploring the impact of a frontal ablation parameterization on projected 21st-century mass change for Northern Hemisphere glaciers, J. Glaciol., 1–16, doi:10.1017/jog.2023.19, 2023.
  • O’Kane, T. J., Scaife, A. A., Kushnir, Y., Brookshaw, A., Buontempo, C., Carlin, D., Connell, R. K., Doblas-Reyes, F., Dunstone, N., Förster, K., Graça, A., Hobday, A. J., Kitsios, V., van der Laan, L., Lockwood, J., Merryfield, W. J., Paxian, A., Payne, M. R., Reader, M. C., Saville, G. R., Smith, D., Solaraju-Murali, B., Caltabiano, N., Carman, J., Hawkins, E., Keenlyside, N., Kumar, A., Matei, D., Pohlmann, H., Power, S., Raphael, M., Sparrow, M. and Wu, B.: Recent applications and potential of near-term (interannual to decadal) climate predictions, Frontiers in Climate, 5, doi:10.3389/fclim.2023.1121626, 2023.
  • Pesci, M. H., Schulte Overberg, P., Bosshard, T., and Förster, K.: From global glacier modeling to catchment hydrology: bridging the gap with the WaSiM-OGGM coupling scheme, Frontiers in Water, 5., doi:10.3389/frwa.2023.1296344, 2023.
  • Recinos, B., Maussion, F., Marzeion, B.: Advances in data availability to constrain and evaluate ice dynamical models of Greenland’s tidewater peripheral glaciers, Annals of Glaciol., 1–7, doi:10.1017/aog.2023.11, 2023.
  • Ross, A. C., Mendoza, M. M., Drenkhan, F., Montoya, N., Baiker, J. R., Mackay, J. D., Hannah, D. M., Buytaert, W.: Seasonal water storage and release dynamics of bofedal wetlands in the Central Andes, Hydrol. Process., 37(8), 1–14, doi:10.1002/hyp.14940, 2023.
  • Rounce, D. R., Hock, R., Maussion, F., Hugonnet, R., Kochtitzky, W., Huss, M., Berthier, E., Brinkerhoff, D., Compagno, L., Copland, L., Farinotti, D., Menounos, B. and McNabb, R. W.: Global glacier change in the 21st century: Every increase in temperature matters, Science (80-. )., 379(6627), 78–83, doi:10.1126/science.abo1324, 2023. [download from the authors website].
  • Schuster, L., Rounce, D., Maussion, F.: Glacier projections sensitivity to temperature-index model choices and calibration strategies, Annals of Glaciol., 1–16, doi:10.1017/aog.2023.57, 2023.
  • Tang, S., Vlug, A., Piao, S., Li, F., Wang, T., Krinner, G., Li, L. Z. X., Wang, X., Wu, G., Li, Y., Zhang, Y., Xu, H., and Yao, T.: Regional and tele-connected impacts of the Tibetan Plateau surface darkening., Nat. Commun., 14, 32, doi:10.1038/s41467-022-35672-w, 2023.
  • Yang, L., Zhao, G., Mu, X., Liu, Y., Tian, P., and Danzengbandian, P.: Historical and projected evolutions of glaciers in response to climate change in High Mountain Asia, Environ. Res., 237(2), 117037, doi:10.1016/j.envres.2023.117037, 2023.
  • Zhao, H., Su, B., Lei, H., Zhang, T., Xiao, C.: A new projection for glacier mass and runoff changes over High Mountain Asia, Science Bulletin, 68(1), 43-47, doi:10.1016/j.scib.2022.12.004, 2023.


  • Bouchayer, C., Aiken, J. M., Thøgersen, K., Renard, F. and Schuler, T. V.: A machine learning framework to automate the classification of surge‐type glaciers in Svalbard, J. Geophys. Res. Earth Surf., doi:10.1029/2022JF006597, 2022.
  • Chen, W., Yao, T., Zhang, G., Li, F., Zheng, G., Zhou, Y., and Xu, F.: Towards ice-thickness inversion: an evaluation of global digital elevation models (DEMs) in the glacierized Tibetan Plateau, The Cryosphere, 16, 197–218, doi:10.5194/tc-16-197-2022, 2022.
  • Furian, W., Maussion, F., and Schneider, C.: Projected 21st-Century Glacial Lake Evolution in High Mountain Asia, Front. Earth Sci., 10, doi:10.3389/feart.2022.821798, 2022.
  • Nidheesh, G., Goosse, H., Parkes, D., Goelzer, H., Maussion, F., and Marzeion, B.: Process-based Estimate of Global-mean Sea-level Changes in the Common Era, Earth Syst. Dynam., 13, 1417–1435, doi:10.5194/esd-13-1417-2022, 2022.
  • Yang, M., Li, Z., Anjum, M. N., Kayastha, R., Kayastha, R. B., Rai, M., Zhang, X., and Xu, C.: Projection of streamflow changes under CMIP6 scenarios in the Urumqi river head watershed, Tianshan Mountain, China, Front. Earth Sci., 10, 1-14, doi:10.3389/feart.2022.857854, 2022.
  • Yang, W., Chu W., and Liu, G.: Importance of the seasonal temperature and precipitation variation on glacial evolutions during the LGM at monsoonal Himalaya based on Cogarbu valley, Palaeogeogr. Palaeoclimatol. Palaeoecol., 601, 111132, doi:10.1016/j.palaeo.2022.111132, 2022.
  • Yang, W., Li, Y., Lui, G., and Chu, W.: Timing and climatic-driven mechanisms of glacier advances in Bhutanese Himalaya during the Little Ice Age, The Cryosphere, 16, 3739–3752, doi:10.5194/tc-16-3739-2022, 2022.


  • Dixit, A., Sahany, S. and Kulkarni, A. V.: Glacial changes over the Himalayan Beas basin under global warming, J. Environ. Manage., 295(May), 113101, doi:10.1016/j.jenvman.2021.113101, 2021.
  • Edwards, T. et al.: Projected land ice contributions to twenty-first-century sea level rise, Nature, 593(7857), 74–82, doi:10.1038/s41586-021-03302-y, 2021.
  • Eis, J., van der Laan, L., Maussion, F. and Marzeion, B.: Reconstruction of Past Glacier Changes with an Ice-Flow Glacier Model: Proof of Concept and Validation, Front. Earth Sci., 9(March), 1–16, doi:10.3389/feart.2021.595755, 2021.
  • Hartl, L., Helfricht, K., Stocker-Waldhuber, M., Seiser, B., & Fischer, A.: Classifying disequilibrium of small mountain glaciers from patterns of surface elevation change distributions, Journal of Glaciology, 1-16, doi:10.1017/jog.2021.90, 2021.
  • Pronk, J. B., Bolch, T., King, O., Wouters, B., and Benn, D. I.: Contrasting surface velocities between lake- and land-terminating glaciers in the Himalayan region, The Cryosphere, doi:10.5194/tc-15-5577-2021, 2021.
  • Recinos, B., Maussion, F., Noël, B., Möller, M., Marzeion, B.: Calibration of a frontal ablation parameterization applied to Greenland’s peripheral calving glaciers, J. Glaciol., 1–13, doi:10.1017/jog.2021.63, 2021.
  • Rounce, D. R., Hock, R., McNabb, R. W., Millan, R., Sommer, C., Braun, M. H., Malz, P., Maussion, F., Mouginot, J., Seehaus, T. C. and Shean, D. E.: Distributed global debris thickness estimates reveal debris significantly impacts glacier mass balance, Geophys. Res. Lett., doi:10.1029/2020GL091311, 2021.
  • Shafeeque, M. and Luo, Y.: A multi-perspective approach for selecting CMIP6 scenarios to project climate change impacts on glacio-hydrology with a case study in Upper Indus river basin, J. Hydrol., 599, 126466, doi:10.1016/j.jhydrol.2021.126466, 2021.


  • Khadka, M., Kayastha, R. B. and Kayastha, R.: Future projection of cryospheric and hydrologic regimes in Koshi River basin, Central Himalaya, using coupled glacier dynamics and glacio-hydrological models, J. Glaciol., 1–15, doi:10.1017/jog.2020.51, 2020.
  • Marzeion, B., Hock, R., Anderson, B., Bliss, A., Champollion, N., Fujita, K., Huss, M., Immerzeel, W., Kraaijenbrink, P., Malles, J., Maussion, F., Radić, V., Rounce, D. R., Sakai, A., Shannon, S., Wal, R. and Zekollari, H.: Partitioning the Uncertainty of Ensemble Projections of Global Glacier Mass Change, Earth’s Futur., 8(7), doi:10.1029/2019ef001470, 2020.
  • Parkes, D. and Goosse, H.: Modelling regional glacier length changes over the last millennium using the Open Global Glacier Model, The Cryosphere, 14, 3135–3153, doi:10.5194/tc-14-3135-2020, 2020.
  • Pelto, B. M., Maussion, F., Menounos, B., Radić, V. and Zeuner, M.: Bias-corrected estimates of glacier thickness in the Columbia River Basin, Canada, J. Glaciol., 1–13, doi:10.1017/jog.2020.75, 2020.


  • Eis, J., Maussion, F., and Marzeion, B.: Initialization of a global glacier model based on present-day glacier geometry and past climate information: an ensemble approach, The Cryosphere, 13, 3317–3335, doi:10.5194/tc-13-3317-2019, 2019.
  • Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H., Maussion, F., & Pandit, A.: A consensus estimate for the ice thickness distribution of all glaciers on Earth, Nature Geoscience, 1., doi:10.1038/s41561-019-0300-3, 2019.
  • Maussion, F., Butenko, A., Champollion, N., Dusch, M., Eis, J., Fourteau, K., Gregor, P., Jarosch, A. H., Landmann, J., Oesterle, F., Recinos, B., Rothenpieler, T., Vlug, A., Wild, C. T., and Marzeion, B.: The Open Global Glacier Model (OGGM) v1.1, Geosci. Model Dev., 12, 909-931, doi:10.5194/gmd-12-909-2019, 2019.
  • Recinos, B., Maussion, F., Rothenpieler, T., and Marzeion, B.: Impact of frontal ablation on the ice thickness estimation of marine-terminating glaciers in Alaska, The Cryosphere, 13, 2657–2672, doi:10.5194/tc-13-2657-2019, 2019.


  • Goosse, H., Barriat, P.-Y., Dalaiden, Q., Klein, F., Marzeion, B., Maussion, F., Pelucchi, P., and Vlug, A.: Testing the consistency between changes in simulated climate and Alpine glacier length over the past millennium, Clim. Past, 14, 1119-1133, doi:10.5194/cp-14-1119-2018, 2018.


  • Farinotti, D. et al.: How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment, The Cryosphere, 11, 949-970, doi:10.5194/tc-11-949-2017, 2017.
  • Marzeion, B., Kaser, G., Maussion, F., and Champollion, N.: Limited influence of climate change mitigation on short-term glacier mass loss, Nature Climate Change, doi:10.1038/s41558-018-0093-1, 2018.
  • Marzeion, B., Cogley, J.G., Richter, K., and Parkes, D.: Attribution of global glacier mass loss to anthropogenic and natural causes, Science, 345, 919-921, doi:10.1126/science.1254702, 2014.
  • Marzeion, B., Jarosch, A. H., and Hofer, M.: Past and future sea-level change from the surface mass balance of glaciers, The Cryosphere, 6, 1295-1322, doi:10.5194/tc-6-1295-2012, 2012.

Theses making use of OGGM

(that we are aware of)


  • Eis, J., Reconstructing glacier evolution using a flowline model, doi:10.26092/elib/432, 2020.
  • van der Laan, L., Near-Term Global Glacier Mass Balance Modelling, doi:10.15488/14171, 2023.
  • Malles, J., Past to Future and Land to Sea: constraining global glacier models by observations and exploring ice-ocean interactions, doi:10.26092/elib/2323, 2023.
  • Recinos, B., Ocean-glacier interaction on the large regional scale, doi:10.26092/elib/434, 2020.
  • Vlug, A., The influence of climate variability on the mass balance of Canadian Arctic land-terminating glaciers, in simulations of the last millennium, doi:10.26092/elib/1501, 2021.
  • Pelto, B., An approach to remotely monitor glacier mass balance at seasonal to annual time scales, Columbia and Rocky Mountains, Canada, doi:10.24124/2020/59097, 2020.


  • Holmgren, E. 21st century glacier runoff and how it buffers drought in 75 large-scale basins, link, 2022.
  • Oberrauch, M. Testing the importance of explicit glacier dynamics for mountain glacier change projections, link, 2021.
  • Schmitt, P., Flowline glacier bed estimation with numerical modelling and cost minimization: Extending the open source model COMBINE 1D, link, 2021.
  • Castellani, M. Estimating Glacier Ice Thickness with Machine Learning, link, 2020.
  • Schuster, L., Response time sensitivity of glaciers using the Open Global Glacier Model, link, 2020.
  • Gregor, P., Inversion of Glacier Bed from Surface Observations by Cost Minimization: Introducing the Open Source Model COMBINE, link, 2019.
  • Thorlaksson, D., Calibrating a glacier ice thickness model from in-situ point measurements, link, 2017.

Bachelor / Undergrad

  • Arndt, M., On Thin Ice: The future of glacial runoff in La Paz, Bolivia, doi:10.5281/zenodo.7946884, 2023.
  • Schwienbacher, F., Model sensitivity of the mass-balance module of the OGGM model, 2017.