Academic Journal

Technical note: Surface fields for global environmental modelling.

التفاصيل البيبلوغرافية
العنوان: Technical note: Surface fields for global environmental modelling.
المؤلفون: Choulga, Margarita, Moschini, Francesca, Mazzetti, Cinzia, Grimaldi, Stefania, Disperati, Juliana, Beck, Hylke, Salamon, Peter, Prudhomme, Christel
المصدر: EGUsphere; 8/21/2023, p1-30, 30p
مصطلحات موضوعية: EMERGENCY management, SOURCE code, HYDROLOGIC models, GROUND vegetation cover, EMERGENCY medical services
مصطلحات جغرافية: ANTARCTICA
مستخلص: Climate change has resulted in more frequent occurrences of extreme events, such as flooding and heavy snowfall, which can have a significant impact on densely populated or industrialised areas. Numerical models are used to simulate and predict these extreme events, enabling informed decision-making and planning to minimise human casualties and protect costly infrastructure. LISFLOOD is an integrated hydrological model underpinning the European and Global Flood Awareness Systems (EFAS and GloFAS, respectively) developed by the Copernicus Emergency Management Service (CEMS). The CEMS_SurfaceFields_2022 dataset is a new set of high-resolution surface fields at 1 and 3 arc min (approximately 2 and 6 km at the Equator respectively) covering Europe and the global land surface (excluding Antarctica) respectively, based on a wide variety of high-resolution and up-to-date data sources. The dataset has been created together with upgrades to the open source LISFLOOD code. The set encompasses (i) catchment morphology and river network, (ii) land use, (iii) vegetation cover type and properties, (iv) soil properties, (v) lake information, and (vi) water demand. This manuscript details the complete workflow to generate CEMS_SurfaceFields_2022 fields, including data sources and methodology. The use of these fields is expected to significantly improve accuracy, detail, and realism of LISFLOOD simulations. CEMS_SurfaceFields_2022 can also be used as input for other Earth system models or for carrying out general statistical analyses across various spatial scales, ranging from global and regional to local levels. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
DOI:10.5194/egusphere-2023-1306