Centre Étude et simulation du climat à l'échelle régionale (ESCER), Département des Sciences de la Terre et de l'atmosphère, Université du Québec à Montréal, Montréal, QC, Canada
Alejandro Di Luca
Centre Étude et simulation du climat à l'échelle régionale (ESCER), Département des Sciences de la Terre et de l'atmosphère, Université du Québec à Montréal, Montréal, QC, Canada
René Laprise
Centre Étude et simulation du climat à l'échelle régionale (ESCER), Département des Sciences de la Terre et de l'atmosphère, Université du Québec à Montréal, Montréal, QC, Canada
Centre Étude et simulation du climat à l'échelle régionale (ESCER), Département des Sciences de la Terre et de l'atmosphère, Université du Québec à Montréal, Montréal, QC, Canada
Julie Thériault
Centre Étude et simulation du climat à l'échelle régionale (ESCER), Département des Sciences de la Terre et de l'atmosphère, Université du Québec à Montréal, Montréal, QC, Canada
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Viewed (geographical distribution)
Total article views: 3,594 (including HTML, PDF, and XML)
Thereof 3,571 with geography defined
and 23 with unknown origin.
Total article views: 1,715 (including HTML, PDF, and XML)
Thereof 1,704 with geography defined
and 11 with unknown origin.
Total article views: 1,879 (including HTML, PDF, and XML)
Thereof 1,867 with geography defined
and 12 with unknown origin.
Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Our study addresses a challenge in dynamical downscaling using regional climate models, focusing...
