Sensitivity to Initial and Boundary Perturbations in Convective-Scale Ensemble-Based Data Assimilation: Imperfect-Model OSSEs

SOLA: Scientific Online Letters on the Atmosphere

article

Paula Maldonado¹  Juan Ruiz¹  Celeste Saulo³ 

[1] Universidad de Buenos Aires - Consejo Nacional de Investigaciones Científicas y Técnicas;Universidad de Buenos Aires, Departamento de Ciencias de la Atmósfera y los Océanos (DCAO/FCEN/UBA);Consejo Nacional de Investigaciones Científics y Técnicas, Servicio Meteorológico Nacional

DOI  :  10.2151/sola.2021-015

来源: Meteorological Society of Japan

【 摘 要 】

This study investigates the impact of applying different types of initial and boundary perturbations for convective-scale ensemble data assimilation systems. Several observing system simulation experiments (OSSEs) were performed with a 2-km horizontal resolution, considering a realistic environment, taking model error into account, and combining different perturbations' types with warm/cold start initialization. Initial perturbations produce a long-lasting impact on the analysis's quality, particularly for variables not directly linked to radar observations. Warm-started experiments provide the most accurate analysis and forecasts and a more consistent ensemble spread across the different spatial scales. Random small-scale perturbations exhibit similar results, although a longer convergence time is required to up-and-downscale the initial perturbations to obtain a similar error reduction. Adding random large-scale perturbations reduce the error in the first assimilation cycles but produce a slightly detrimental effect afterward.

【 授权许可】

Unknown