AEMET-γSREPS, a fully operational system for high-resolution probabilistic forecasting over Iberian Pensinsula
Year: 2021
Type: conference-abstract
Abstract: Thinking in terms of uncertainty in the operational forecast is the current goal for high resolution operational predictions. Fields like precipitation with convection, surface winds or fog, are very sensitive to model uncertainties and errors, resulting in a rapid loss of predictability in such meso-scales. The best tool that can quantify this uncertainty is a Short Range Ensemble Prediction System (SREPS). Since final 2016 AEMET runs operationally such a system and names it AEMET-γSREPS. It runs currently at 00 and 12UTC time in three domains over the Iberian Peninsula, Canary Islands and the Antarctic Peninsula, up to 48/60 at 00UTC. According to our operational forecasters, the main contribution of the system is to predict strong convective precipitation and its spatial variability. Besides it is useful to see the range of change of temperature from day to day or the localization of wind gusts in orographic areas and its associated spatial variability. The combination of HARMONIE-AROME with IFS deterministic models and AEMET-γSREPS is the best tool AEMET has for the short-range forecasting. In this talk we first briefly present the design of the system and the domains and times where and when the probabilistic predictions are computed. Then we describe the current status and last updates and the latest verification results. Special emphasis is focused on introducing data assimilation in the system. Finally, the future developments are shown. Although AEMET-γSREPS is developed by the AEMET Predictability group, it wouldn’t exist without the collaboration of the international partners ECMWF, MF, NCEP, NCAR, JMA, CMC and specially the HARMONIE community.
DOI: 10.5194/ems2021-369
Authors: Alfons Callado, Pau Escribà, David Quintero, David Gil, Maria Cortès, Joan Montolio
Institution: Agencia Estatal de Meteorología
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
OpenAlex ID: W4240640686