SOLA
Online ISSN : 1349-6476
ISSN-L : 1349-6476
Article
Sensitivity to Initial and Boundary Perturbations in Convective-Scale Ensemble-Based Data Assimilation: Imperfect-Model OSSEs
Paula MaldonadoJuan RuizCeleste Saulo
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JOURNAL OPEN ACCESS
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2021 Volume 17 Pages 96-102

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Abstract

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.

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© The Author(s) 2021. This is an open access article published by the Meteorological Society of Japan under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
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