- 著者
- Paula Maldonado Juan Ruiz Celeste Saulo
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.17, pp.96-102, 2021 (Released:2021-05-19)
- 参考文献数
- 34
- 被引用文献数
- 4
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.
- 著者
- Paula Maldonado Juan Ruiz Celeste Saulo
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- pp.2021-015, (Released:2021-04-14)
- 被引用文献数
- 4
This study investigates the impact of applying different types of initial and boundary perturbations for convective-scale ensemble data assimilation systems. Several 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.