Surrogate Models for Rainfall Nowcasting

التفاصيل البيبلوغرافية
العنوان: Surrogate Models for Rainfall Nowcasting
المؤلفون: Cabrera-Gutiérrez, Naty Citlali, Godé, Hadrien, Jouhaud, Jean-Christophe, Bakkay, Mohamed Chafik, Burdá, Valentin Kivachuk, Dupuy, Florian, Mader, Maud-Alix, Mestre, Olivier, Oller, Guillaume, Serrurier, Mathieu, Zamo, Michaël
سنة النشر: 2020
المجموعة: Physics (Other)
مصطلحات موضوعية: Physics - Computational Physics, Physics - Atmospheric and Oceanic Physics
الوصف: Nowcasting (or short-term weather forecasting) is particularly important in the case of extreme events as it helps prevent human losses. Many of our activities, however, also depend on the weather. Therefore, nowcasting has shown to be useful in many different domains. Currently, immediate rainfall forecasts in France are calculated using the Arome-NWC model developed by M\'et\'eo-France, which is a complex physical model. Arome-NWC forecasts are stored with a 15 minute time interval. A higher time resolution is, however, desirable for other meteorological applications. Complex model calculations, such as Arome-NWC, can be very expensive and time consuming. A surrogate model aims at producing results which are very close to the ones obtained using a complex model, but with largely reduced calculation times. Building a surrogate model requires only a few calculations with the real model. Once the surrogate model is built, further calculations can be quickly realized. In this study, we propose to build surrogate models for immediate rainfall forecasts with two different approaches: combining Proper Orthogonal Decomposition (POD) and Kriging, or combining POD and Random Forest (RF). We show that results obtained with our surrogate models are not only close to the ones obtained by Arome-NWC, but they also have a higher time resolution (1 minute) with a reduced calculation time.
Comment: 17 pages, 8 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2006.14515
رقم الأكسشن: edsarx.2006.14515
قاعدة البيانات: arXiv