1st Snow Data Assimilation Workshop in the framework of COST HarmoSnow ESSEM 1404

Helmert, J.; Lange, M.; Jiarui, D.; de Rosnay, P.; Gustafsson, D.; Churulin, E.; Kurzeneva, E.; Muller, R.; Trentmann, J.; Souverijns, N.; Koch, R.; Bohm, U.; Bartik, M.; Osuch, M.; Rozinkina, I.; Bettems, J.; Samuelsson, P.; Marcucci, F.; Milelli, M.

Авторы: Helmert J., Lange M., Jiarui D., de Rosnay P., Gustafsson D., Churulin E., Kurzeneva E., Muller R., Trentmann J., Souverijns N., Koch R., Bohm U., Bartik M., Osuch M., Rozinkina I., Bettems J-M, Samuelsson P., Marcucci F., Milelli M.
Журнал: Meteorologische Zeitschrift
Том: 27
Номер: 4
Год издания: 2018
Издательство: Gebruder Borntraeger Verlagsbuchhandlung
Местоположение издательства: Germany
Первая страница: 325
Последняя страница: 333
DOI: 10.1127/metz/2018/0906
Аннотация: The 1st Snow Data Assimilation Workshop, organized under the COST Action ESSEM 1404 HarmoSnow, took place in Offenbach, Germany, on 8–9 March 2017. Of particular relevance for the workshop were thematic sessions on i) data assimilation methods and the use of snow observations, ii) snow observations and evaluation, iii) snow observations and physical snow models, and iv) snow observations and hydrological models. This report summarizes the scientific contributions presented at the workshop. The discussions mainly focused on methods for combining satellite observations with conventional in-situ snow measurements and modeling results, as well as on errors in the spatial and temporal representation of snow measurements for data assimilation in NWP and hydrological models. It has been shown that the assimilation of in-situ and satellite-based snow observations improves the quality of the snow analysis and forecast. However, in order to achieve this positive impact, a thorough quality control of the observational data is necessary, in particular because of the automation of the ground-based networks.
Добавил в систему: Чурюлин Евгений Викторович

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