S
Stef Lhermitte
Researcher at Delft University of Technology
Publications - 110
Citations - 3943
Stef Lhermitte is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Snow & Geology. The author has an hindex of 29, co-authored 82 publications receiving 2810 citations. Previous affiliations of Stef Lhermitte include Royal Netherlands Meteorological Institute & University of La Serena.
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Journal ArticleDOI
Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016)
Brice Noël,Willem Jan van de Berg,J. Melchior van Wessem,Erik van Meijgaard,Dirk van As,Jan T. M. Lenaerts,Stef Lhermitte,Peter Kuipers Munneke,C. J. P. Paul Smeets,Lambertus H. van Ulft,Roderik S. W. van de Wal,Michiel R. van den Broeke +11 more
TL;DR: In this paper, the authors evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958-2016).
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Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016)
Jan Melchior van Wessem,Willem Jan van de Berg,Brice Noël,Erik van Meijgaard,Charles Amory,Gerit Birnbaum,Constantijn L. Jakobs,Konstantin Krüger,Jan T. M. Lenaerts,Stef Lhermitte,Stefan R. M. Ligtenberg,Brooke Medley,Carleen Reijmer,Kristof Van Tricht,Luke D. Trusel,Lambertus H. van Ulft,Bert Wouters,Jan Wuite,Michiel R. van den Broeke +18 more
TL;DR: In this article, the authors evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surfacemass balance (SMB) and surface energy balance (SEB) from the updated polar version of the regional atmospheric climate model, RACMO2 (1979-2016).
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A comparison of time series similarity measures for classification and change detection of ecosystem dynamics
Stef Lhermitte,Stef Lhermitte,Jan Verbesselt,Willem Verstraeten,Willem Verstraeten,Pol Coppin +5 more
TL;DR: In this article, a quantitative comparison of the similarity measures in function of varying time series and ecosystem characteristics, such as amplitude, timing, and noise effects, is presented, and the performance of the commonly used similarity measures (D), ranging from Manhattan (DMan), Euclidean (DE) and Mahalanobis (DMah) distance measures, to correlation (DCC), Principal Component Analysis (PCA; DPCA) and Fourier based (DFFT,Dξ,DFk) similarities.
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A model quantifying global vegetation resistance and resilience to short‐term climate anomalies and their relationship with vegetation cover
TL;DR: In this article, the authors developed a standardized indicator of short-term vegetation resilience and resistance to drought and temperature anomalies, and to improve our understanding of vegetation resistance and resilience in drought-sensitive areas by linking metrics of vegetation stability to the percentage of tree cover, non-tree vegetation and bare soil.
Journal ArticleDOI
Clouds enhance Greenland ice sheet meltwater runoff
K. Van Tricht,Stef Lhermitte,Jan T. M. Lenaerts,Irina Gorodetskaya,Tristan L'Ecuyer,Brice Noël,M. R. van den Broeke,David D. Turner,N. P. M. van Lipzig +8 more
TL;DR: It is shown that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations to better predict future contributions of the Greenland ice sheet to global sea level rise.