دورية أكاديمية
Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships
| العنوان: | Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
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| المؤلفون: | Jonathan J. Day, Gabriele Arduini, Irina Sandu, Linus Magnusson, Anton Beljaars, Gianpaolo Balsamo, Mark Rodwell, David Richardson |
| المصدر: | Journal of Advances in Modeling Earth Systems, Vol 12, Iss 12, Pp n/a-n/a (2020) |
| بيانات النشر: | American Geophysical Union (AGU), 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Physical geography LCC:Oceanography |
| مصطلحات موضوعية: | multi‐layer snow, Arctic, snow modelling, forecast diagnostics, Greenland, atmosphere‐land coupling, Physical geography, GB3-5030, Oceanography, GC1-1581 |
| الوصف: | Abstract Energy exchange at the snow‐atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth's surface in an Earth System Model, from a process‐based perspective, using in situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process‐oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user‐relevant properties, such as 2 m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step toward achieving more skilful weather forecasts and climate projections. These diagnostic techniques are applied to assess the impact of a new multi‐layer snow scheme in the European Centre for Medium‐Range Weather Forecasts'‐Integrated Forecast System at two high‐Arctic sites (Summit, Greenland and Sodankylä, Finland). A previous study showed that it will enhance 2 m temperature forecast skill across the Northern Hemisphere in boreal winter compared to forecasts with the single layer model, reducing a warm bias. In this study we use the diagnostics to show that the bias is improved for the right reasons. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1942-2466 |
| Relation: | https://doaj.org/toc/1942-2466 |
| DOI: | 10.1029/2020MS002144 |
| URL الوصول: | https://doaj.org/article/0aab5bf6477a47f181f838056da6b688 |
| رقم الأكسشن: | edsdoj.0aab5bf6477a47f181f838056da6b688 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19422466 |
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| DOI: | 10.1029/2020MS002144 |