Share Email Print

Proceedings Paper

Observing system simulation experiments with multiple methods
Author(s): Toshiyuki Ishibashi
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

An observing System Simulation Experiment (OSSE) is a method to evaluate impacts of hypothetical observing systems on analysis and forecast accuracy in numerical weather prediction (NWP) systems. Since OSSE requires simulations of hypothetical observations, uncertainty of OSSE results is generally larger than that of observing system experiments (OSEs). To reduce such uncertainty, OSSEs for existing observing systems are often carried out as calibration of the OSSE system. The purpose of this study is to achieve reliable OSSE results based on results of OSSEs with multiple methods. There are three types of OSSE methods. The first one is the sensitivity observing system experiment (SOSE) based OSSE (SOSEOSSE). The second one is the ensemble of data assimilation cycles (ENDA) based OSSE (ENDA-OSSE). The third one is the nature-run (NR) based OSSE (NR-OSSE). These three OSSE methods have very different properties. The NROSSE evaluates hypothetical observations in a virtual (hypothetical) world, NR. The ENDA-OSSE is very simple method but has a sampling error problem due to a small size ensemble. The SOSE-OSSE requires a very highly accurate analysis field as a pseudo truth of the real atmosphere. We construct these three types of OSSE methods in the Japan meteorological Agency (JMA) global 4D-Var experimental system. In the conference, we will present initial results of these OSSE systems and their comparisons.

Paper Details

Date Published: 18 November 2014
PDF: 10 pages
Proc. SPIE 9265, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions V, 926508 (18 November 2014); doi: 10.1117/12.2069087
Show Author Affiliations
Toshiyuki Ishibashi, Japan Meteorological Agency (Japan)

Published in SPIE Proceedings Vol. 9265:
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions V
Tiruvalam N. Krishnamurti; Guosheng Liu, Editor(s)

© SPIE. Terms of Use
Back to Top