Farewell lunch for Dr. Juan Ruiz

On March 6, 2014, we had a joyful farewell lunch at Kachoen for Dr. Juan Ruiz with a lot of smiles! Juan's second visit to our lab for a month this time has been very successful as always. He has been making amazing progress on the quality control and observation operator for Phased Array Weather Radar and Doppler Lidar observations. I am hoping that we will be ready sometime soon to publicize these wonderful achievements.

Team Logo!

We are very excited about our new team logo of the Data Assimilation Research Team. Dr. Hazuki Arakida is in charge of the team webpage and designed the team logo. The circle on top right and the square at bottom left are merging (assimilating?). The bright red square/circle is my idea, adding a good spice to the logo (in my opinion).

My comments in the top news of Kobe local newspaper

On February 12, 2014, the top news of the Kobe local newspaper reports the Phased Array Weather Radar being built in the western part of Kobe city. The radar will start observing the 3-dimensional structure of rain particles and their motions in the air by the end of March, 2014. The article includes my comments on the innovative aspect and potential utility of the new-type weather radar in numerical weather prediction.

Here is the link to the news article (sorry, only in Japanese!)

http://www.kobe-np.co.jp/news/bousai/201402/0006701977.shtml

RIKEN Science Seminar VII in Kobe

On Wednesday, January 29, 2014, the RIKEN Science Seminar VII, an outreach event organized by RIKEN, took place at the Kobe International House. Hana-san, our featured guest, Kawai-san of RIKEN HQ, and I (Takemasa Miyoshi) enjoyed talking in front of more than 100 audiences about our cutting-edge research on future weather forecasting. Hana-san was keen to learn how the current weather forecasting works, and whether or not we can have 100% accurate forecasts in the future. I showed weather charts of the day and demonstrated how to read them to understand the tomorrow's weather forecast. Also, I talked about how we obtain these weather charts in real time, and what we could do in the future with more powerful computers and more advanced weather observing instruments. I hope that we could convey our scientific excitement to the enthusiastic audiences. Thank you very much for those who joined the enjoyable event, and the staff who kindly helped organize.

http://www.riken.jp/pr/blog/2014/140218_1/

Lab members in January 2014

This picture includes our new members, Drs. Steve Penny and Shunji Kotsuki. Dr. Penny is visiting from the University of Maryland for a month, generously supported by a very competitive JSPS fellowship program. He is studying particle filtering methods suitable for high-dimensional spatio-temporal chaos. Dr. Kotsuki just started in January as a full-time team member. He studies data assimilation for hydrological cycle.

Lab members in December 2013

We have more rapid changes in my lab than the quarterly updates. Africa Perianez (fourth from left) of German Weather Service (DWD) is visiting from Thursday, December 5 to Friday 13, 2013. We started collaborations on theoretical developments of localization methods and other topics in ensemble data assimilation. Also, Ms. Yukie Komori (second from right) is our new assistant. This picture includes everyone in the lab except for some Visiting Researchers, Drs. Juan Ruiz, Shu-Chih Yang, and Masahiro Sawada.

A multi-scale localization method was developed

We developed a new approach to error-covariance localization that considers multi-scale structure of the forecast error covariance in ensemble data assimilation methods. We found that this new approach is practical and very effective in improving accuracy of ensemble data assimilation.

With higher-resolution models, we tend to have more sampling noise in the shorter range due to limited ensemble size. This limits the use of observation data only in a limited range even though the data should impact a larger area. The figure above illustrates how the proposed multi-scale localization works. The patterns indicate what impact the observation data at the star point have. We mix the shorter-range impact (top left) with the longer-range impact (bottom left) to obtain a hybrid of both (right). This way, we preserve more structure in the shorter range, while we still include impact on an extended area using the smoothed error covariance (or smoothed ensemble perturbations). For more details, please refer to our recent publications:

• Miyoshi, T. and K. Kondo, 2013: A multi-scale localization approach to an ensemble Kalman filter. SOLA, 9, 170-173. doi:10.2151/sola.2013-038
• Kondo, K., T. Miyoshi and H. L. Tanaka, 2013: Parameter sensitivities of the dual-localization approach in the local ensemble transform Kalman filter SOLA, 9, 174-177. doi:10.2151/sola.2013-039