The 48th and 49th Data Assimilation Seminar 27 July

We held the 48th and 49th Data Assimilation Seminars at RIKEN Center for Computational Science (R-CCS) on July 27.

The first talk was given by Dr. Hironori Arai from the Institute of Industrial Science, University of Tokyo. He has been a visiting scientist with the Data Assimilation team here at RIKEN since May. He discussed his work in developing monitoring systems of greenhouse gas emissions in tropical rice cropping systems based on satellite remote sensing data.

The second talk was given by Professor Pierre Tandeo from IMT Atlantique in France. He presented his work on a review paper he is currently writing about the different methods in data assimilation to estimate the observation error covariance matrix (R) and model error (Q). He also discussed various applications on data-driven methods in geophysics, including a future project where he will be trying to predict the development of rogue ocean waves.

DA seminar group photo

For details, please see the following DA seminar page:

平成30年7月豪雨に関する緊急対応研究会 (8月17日) のご案内






Dr. Hironori Arai (Institute of Industrial Science, The University of Tokyo)
Prof. Pierre Tandeo (IMT Atlantique)

da-seminar(please remove here)




Date:  July 27, 15:30-16:30
Place:   Room – C107 at R-CCS
Language:  English
15:30-16:00 Dr. Hironori Arai (Institute of Industrial Science, The University of Tokyo)
16:00-16:30 Prof. Pierre Tandeo (IMT Atlantique)

– Dr. Hironori Arai –

Establishing an integrated MRV system of Greenhouse gas emission from wetlands
with Japanese earth-observation/modelling technologies and a data assimilation technique

Greenhouse gas (GHG) emission observation/reduction technologies are attracting
greater deal of attention from policy makers to achieve Sustainable Development
Goals. In terms of GHG accounting, Monitoring, Reporting and Verification (MRV)
systems have become significantly important for the countries which ratified
Paris Agreement by promising Intended Nationally Determined Contributions (INDC).
Not only evaluation of the amount of GHG emitted from the countries, but also
the mitigation’s effect and its dissemination status need to be monitored by
the policy makers. In this regard, the societies require the MRV systems with
transparency and high cost-performance. To address such concern, the authors
are building an efficient/transparent MRV system in a tropical rice cropping
system based on satellite remote sensing data. We are developing a long-term
consistent bottom-up approaching method with high spatio-temporal resolution,
based on the Japanese earth observation technology (e.g., ALOS-2, AMSR-E/2,
GCOM-C). In order to validate the outputs from the bottom-up approaching method,
Now we are also challenging to build an independent top-down approaching
method based on the other satellites data (GOSAT,SCIAMACHY,AIRS) using
NICAM-LETKF with 1way-multivariate variable localization, which can estimate
the surface fluxes without requiring any direct observation or a-priori information of the fluxes with K-computer. In this presentation, we would like
to discuss the development plan and expected collaboration with further
cross-disciplinary collaboration.

– Prof. Pierre Tandeo –

Data-driven methods in geophysics

This seminar will be divided in two parts. Firstly, I will present some
recent results about a review paper I am preparing. It deals with the
different methods we find in the data assimilation literature to jointly
estimate Q and R. These error covariance matrices are crucial because
they control the relative weights of the model forecasts and the
observations in filtering methods. I will remind the different methods
and present some numerical comparisons on toy-models.
Secondly, I plan to present various applications of data-driven methods
in geophysics, not especially for data assimilation. I will show some
applications of the analog method and deep learning in environmental
problems, e.g. the nowcasting of solar irradiance using geostationary
satellites and the classification of oceanic and atmospheric phenomena
using SAR images.


The 47th Data Assimilation Seminar (June 28)

We held the 47th Data Assimilation Seminar at RIKEN Center for Computational Science (R-CCS) on June 28.

The seminar talk was given by Prof. John C. Wells from Ritsumeikan University. He has stayed in our team as a visiting scientist for two months since May. During this stay, he has been working on research aiming for nowcasting of water current and temperature of Lake Biwa.

In this seminar, we learned the water flow measurement in Lake Biwa using the method called Coastal Acoustic Tomography (CAT) and a comprehensive review of the methods to estimate subsurface flow from the fluctuating velocities and height at the surface of a river or sea.

DA seminar, Lecture, 28th Jun. 2018
DA seminar, Group photo, 28th Jun. 2018

For details, please see the following DA seminar page:

第47回 データ同化セミナーを行いました(6月28日)


講演者は、立命館大学の John C. Wells 教授です.ウェルズ先生は、理研の客員研究員として5月から2か月間当チームに滞在され、琵琶湖の水流・水温のナウキャストを目指した研究を進めてこられました.

今回のセミナーでは、Coastal Acoustic Tomography (海洋音響トモグラフィー)という手法を用いた琵琶湖における水流測定や、水流を推定するための既往の理論研究の紹介をいただきました.

DA seminar, Lecture, 28th Jun. 2018

DA seminar, Group photo, 28th Jun. 2018




森下喜弘 理化学研究所 生命システム研究センター
鎌谷研吾 大阪大学 大学院基礎工学研究科
小槻峻司 理化学研究所 計算科学研究センター

詳細は こちら です。
参加ご希望の方は、7月13日(金)までに da-ws-staff(please remove here) へご連絡ください。

チーム Web サイト リニューアル

本日,データ同化チームの Web サイト (日本語版)をリニューアルしました.

PC から閲覧した場合は従来のデザインとほとんど変わりはないはずですが,スマートフォン等の画面サイズが小さな環境から閲覧した場合はいわゆるレスポンシブデザインで表示されます(ただし,過去に行われたイベントのページは除きます).




リンク切れや表示の不具合等を見つけましたら,チーム Web ページ担当の高玉(kohei.takatama(please remove here)までお知らせください.



Prof. John C. Wells(立命館大学、理研R-CCS客員研究員) に、ご講演頂きます。

da-team-desk(please remove here)




Date:      June 28, 15:30-16:30
Place:     Room – C107 at R-CCS
Language:  English
Speakers:  Prof. John C. Wells (Department of Civil Engineering,
Ritsumeikan University)

Towards nowcasting in Lake Biwa: field tests of acoustic tomography, and
discussion of some theorems relating the flow at a water surface to that

I will discuss two topics that are motivated by my lab’s objective to
establish a nowcasting system that can track the current and temperature
fields in Lake Biwa, Japan.

First, I will present results from a test of Coastal Acoustic Tomography
(CAT) in Lake Biwa in November 2017. Three 5 kHz transducers were deployed
along a 10.2 km line from the West Shore of the lake to Takeshima. Acoustic
travel times between transducers are computed from correlograms of the
emitted “M11” quasi-random code with the received signal. Small but
consistent differences in travel times between reciprocal paths were
observed, whence we estimate path-averaged currents along the dominant
acoustic path on the order of 5 cm/s, which is not inconsistent with
expected magnitudes at this site. For the temperature profile in November,
ray paths pass almost entirely below the thermocline. To my knowledge this
is the first reported estimate of currents by Acoustic Tomography in a lake.

Second I will consider how to estimate subsurface flow from the fluctuating
velocities and height at the surface of a river or sea, supposed to be
accessible from high resolution, high-speed video recordings, perhaps by a
stereo pair of bank-mounted cameras. Restricting attention to
constant-density flow, a kinematic relation will first be derived that can
be considered to extend the classical Biot-Savart law between vorticity and
velocity. Next, the Navier-Stokes equations for constant-density liquid
lead to dynamical relations between quantities at the surface with the flow
field below. Empirical relations might also be used to estimate subsurface
flow. For example, Large Eddy Simulation (LES) permits statistical
correlations between the surface and subsurface flow to be estimated. Some
relevant results by my laboratory, based on the Proper Orthogonal
Decomposition, have been presented in Nguyen et al. (2011). A weakness of
such empirical estimation methods is that if the actual flow includes
events are not “spanned” by samples in the LES database, the predictions
will fail. Thus it is important to have other tools available, such as the
kinematic and dynamical relations derived here.

TD Nguyen, TX Dinh, JC Wells, P Mokhasi, D Rempfer 2011 “POD-Based
Estimation of the Flow Field from Free-Surface Velocity in the
Backward-Facing Step” – TSFP DIGITAL LIBRARY ONLINE, 2011


第2回 理研・気象庁データ同化研究会を行いました(4月25-26日)

4月25-26日に気象庁東京管区気象台で第2回 理研・気象庁データ同化研究会を行いました.


第2回 理研・気象庁データ同化研究会 集合写真