Impact of the Window Length of Four-Dimensional Local Ensemble Transform Kalman Filter: A Case of Convective Rain Event-Reference-Cited by-同舟云学术

Impact of the Window Length of Four-Dimensional Local Ensemble Transform Kalman Filter: A Case of Convective Rain Event

Published:2020 Issue:0 Volume:16 Page:37-42
ISSN:1349-6476
Container-title:SOLA
language:en
Short-container-title:SOLA

Author:

Maejima Yasumitsu¹,Miyoshi Takemasa¹²³⁴⁵

Affiliation:

1. RIKEN Center for Computational Science

2. RIKEN interdisciplinary Theoretical and Mathematical Sciences Program

3. RIKEN Cluster for Pioneering Research

4. Department of Atmospheric and Oceanic Science, University of Maryland, College Park

5. Application Laboratory, Japan Agency for Marine-Earth Science and Technology

Publisher

Meteorological Society of Japan

Subject

Atmospheric Science

Link

https://www.jstage.jst.go.jp/article/sola/16/0/16_2020-007/_pdf

Reference19 articles.

1. Deardorff, J. W., 1973: The use of subgrid transport equations in a three-dimensional model of atmospheric turbulence. J. Fluids Eng., 95, 429-438.

2. Hunt, B. R., E. Kalnay, E. J. Kostelich, E. Ott, D. J. Patil, T. Sauer, I. Szunyogh, J. A. Yorke, and A. V. Zimin, 2004: Four-dimensional ensemble Kalman filtering. Tellus A, 56, 273-277.

3. Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D, 230, 112-126.

4. Ikawa, M., and K. Saito 1991: Description of a non-hydrostatic model developed at the Forecast Research Department of the MRI. Tec. Rep. MRI, 28, 238 pp.

5. Kalman, R. E., 1960: A new approach to linear filtering and prediction problems. Trans. ASME J. Basic. Eng., 82, 35-45.

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