A Nonlinear Statistical Model for Extracting a Climatic Signal From Glacier Mass Balance Measurements

• Published in: Journal of Geophysical Research: Earth Surface
• Main Authors: Vincent, C., Soruco, A., Azam, M., Basantes-Serrano, R., Jackson, M., Kjøllmoen, B., Thibert, Emmanuel, Wagnon, P., Six, D., Rabatel, A., Ramanathan, A., Berthier, E., Cusicanqui, D., Vincent, P., Mandal, A.
• Other Authors: Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ), Universidad Mayor de San Andrés (UMSA), Centro de Estudios Científicos (CECs), Norwegian Water Resources and Energy Directorate (NVE), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Jawaharlal Nehru University (JNU), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Institut de Recherche pour le Develppement (IRD), Programme National de Teledetection Spatiale : PNTS-2016-01, Base Financing Program of CONICYT-Chile, Institut des Sciences de l'Univers (INSU), Statkraft AS, Department of Science & Technology (India), IFCPAR/CEFIPRA : 3900-W1, INDICE project by Norwegian Research Council, INSPIRE Faculty award from DST (India) : IFA-14-EAS-22, INDICE - Norwegian Research Council from 2013 to 2015, French Space Agency (CNES) through TOSCA program
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2018
• Subjects: [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces; environment; glacier
• Online Access: https://hal.science/hal-01894285; https://hal.science/hal-01894285/document; https://hal.science/hal-01894285/file/2018JF004702.pdf; https://doi.org/10.1029/2018jf004702

[Departement_IRSTEA]Eaux [ADD1_IRSTEA]Hydrosystèmes et risques naturels International audience Understanding changes in glacier mass balances is essential for investigating climate changes. However, glacier‐wide mass balances determined from geodetic observations do not provide a relevant climatic signal as they depend on the dynamic response of the glaciers. In situ point mass balance measurements provide a direct signal but show a strong spatial variability that is difficult to assess from heterogeneous in situ measurements over several decades. To address this issue, we propose a nonlinear statistical model that takes into account the spatial and temporal changes in point mass balances. To test this model, we selected four glaciers in different climatic regimes (France, Bolivia, India, and Norway) for which detailed point annual mass balance measurements were available over a large elevation range. The model extracted a robust and consistent signal for each glacier. We obtained explained variances of 87.5, 90.2, 91.3, and 75.5% on Argentière, Zongo, Chhota Shigri, and Nigardsbreen glaciers, respectively. The standard deviations of the model residuals are close to measurement uncertainties. The model can also be used to detect measurement errors. Combined with geodetic data, this method can provide a consistent glacier‐wide annual mass balance series from a heterogeneous network. This model, available to the whole community, can be used to assess the impact of climate change in different regions of the world from long‐term mass balance series.