はっけん号

琵琶湖の観測(4月13日)

JST SICORP(戦略的国際プログラム)によるイスラエルとの共同研究プロジェクト「先進 ICT を用いた淡水生態系復元力の監視」にデータ同化研究チームも参加しています.

このプロジェクトの目的は,日本の琵琶湖とイスラエルのキネレット湖(ガリラヤ湖)を主な対象として ICT を用いた水環境の迅速監視手法を開発することです.データ同化の技術は,湖内の流れ場やプランクトンのふるまいについて,それらの再現性や予報精度の向上に寄与すると期待されています.

4月13日(土)にはイスラエル側の研究者も交えて琵琶湖の観測を行いました.大津港から「はっけん号」に搭乗し,琵琶湖北湖に設置していた観測用の係留ブイを回収するとともに,数か所で SASV(Solar-powered Autonomous Surface Vehicle)を運用しました.

はっけん号はっけん号

SASVSASV

SASV琵琶湖上で運用中の SASV


データ同化手法を活用した観測システムの影響評価に関する研究会(4/18-19)のご案内

海洋研究開発機構(JAMSTEC) アプリケーションラボおよびR-CCS データ同化研究チームの共催による「データ同化手法を活用した観測システムの影響評価に関する研究会」が、
来週4月18日(木)、19日(金)にJAMSTEC横浜研究所にて行われます。
開催概要は以下の通りです。

日時 2019年4月18日(木)-4月19日(金)
場所 海洋研究開発機構 横浜研究所 交流棟2F小会議室
神奈川県横浜市金沢区昭和町3173番25
対象 主に大気・海洋分野の観測・シミュレーション・データ同化研究者
言語 日本語
参加費 無料

詳しいプログラムおよび参加申し込みは以下をご参照ください。
http://www.data-assimilation.riken.jp/jp/events/oreda_2019spring/index.html

Data Assimilation Seminar – Dr. Tie Dai [LASG]

We held the 56th Data Assimilation Seminar at RIKEN Center for Computational Science (R-CCS) on 1 February.

The talk was given by Dr. Tie Dai from State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics at the Chinese Academy of Sciences.

Dr Dai talked about his work developing an aerosol data assimilation system based on the NICAM model and LETKF. He showed how he has been able to successfully assimilate observations from both the MODIS satellite and Himawari 8 satellite to produce an aerosol analysis for the improvement of short-range aerosol forecasting over Eastern Asia.

We would like to thank Dr Dai very much for visiting us here in Kobe and for the lively discussion about his work! We wish him well with his research in the future.

For more information about this and all our DA seminars at RIKEN R-CCS, please see the DA seminar page:

http://www.data-assimilation.riken.jp/en/events/da_seminar/index.html

Data Assimilation Seminar – Dr Alison Fowler/Ms. Jemima Tabeart [U Reading UK]

We held the 54th and 55th Data Assimilation Seminars at RIKEN Center for Computational Science (R-CCS) on January 28.

The first talk was given by Dr. Alison Fowler from the University of Reading (UK), who spoke about observation error correlations and how we might apply data compression techniques that retain maximum information content of the observations, allowing us to use more observations in our data assimilation.

The second talk was given by Jemima Tabeart, also from the University of Reading. She spoke about available reconditioning methods that can be used to improve the condition number of correlated matrices. She found that she could improve the convergence by introducing correlated observation error covariance matrices with only small changes to retrieved variables.

We would like to thank Alison and Jemima for visiting us here at RIKEN R-CCS and giving two very interesting talks on observation error covariance matrix estimation – a very important topic in this era of Big Data!  

For details, please see the following DA seminar page:

http://www.data-assimilation.riken.jp/en/events/da_seminar/index.html

53rd DA Seminar – Dr Eugenia Kalnay

We held the 53rd Data Assimilation Seminar at RIKEN Center for Computational Science (R-CCS) on January 18. The seminar talk was given by Dr Eugenia Kalnay from the University of Maryland.

Dr Kalnay spoke about how wind and solar farms may lead to unintended climate changes caused by changes to land surface properties. She showed using a climate model how a large scale installation of wind and solar farms across the Sahara would lead to a local temperature increase and precipitation increase, which could have a positive impact on vegetation.

We would like to thank Dr Kalnay very much for visiting us again in Kobe and for the many great discussions we had with her during her stay. We look forward to welcoming her again to R-CCS soon!

52nd Data Assimilation Seminar – Dr. Tetsuo Nakazawa

We held the 52nd Data Assimilation Seminar at RIKEN Center for Computational Science (R-CCS) on December 19. The seminar talk was given by Dr Tetsuo Nakazawa from Meteorological Research Institute (MRI), Japan Meteorological Agency (JMA).

Dr Nakazawa spoke about his research on tropical cyclone frequency under a warmer climate scenario and why it may be expected that the annual number of tropical cyclones may decrease in the future.

We would like to thank Dr Nakazawa very much for visiting us at RIKEN. We look forward to his next visit!

第52回 データ同化セミナー(12/19)のご案内

12/19のデータ同化セミナーについてのご案内です。
今回のセミナーでは、
気象庁気象研究所の中澤哲夫氏よりご講演頂きます。

※どなたでもご参加いただけますが、入館に手続きが必要なため、
事前に下記までご連絡をお願い致します。
da-seminar(please remove here)@riken.jp
以下URLに随時情報を更新しています。
http://data-assimilation.riken.jp/en/events/da_seminar/

以下、詳細です。

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Date:    *Wednesday 19 December 2018, 15:30-16:30 *
Place:   Seminar Room at R-CCS
Language:  English
Speaker:  Dr. Tetsuo Nakazawa (Meteorological Research Institute (MRI))

*Title: Is the Trend in Tropical Cyclone Formation Frequency due to Global
Warming?*

*Abstract: *

Under the warmer climate projection, several models simulate that the
annual number of tropical cyclone formation will decrease, but the intense
tropical cyclone number will increase globally. The former may be related
with the stabler condition of the atmosphere, and the latter may be related
with the possible rapid intensification under the more humid condition near
the surface.  To understand the former hypothesis, Arakawa and Schubert’s
cumulus parameterization method has been utilized to estimate all possible
cloud types at each grid, using the ECMWF reanalysis dataset (ERA20C) from
1900 to 2010. The result shows that the tropical atmosphere is getting
stabler and the cloud top height of the deepest cloud type is getting
lower. This may explain why the annual number the tropical cyclone
formation will decrease in future.

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理研データ同化合宿2018(基礎編)を開催しました

理研データ同化合宿2018(基礎編) 修了式の様子

12/3~12/7に理研データ同化合宿2018(基礎編)を開催しました.今年度は21名の方が受講され,定員満員の盛況となりました.

合宿はLorenz-96 モデルを題材としたデータ同化について,午前中には座学で,午後には各自がプログラミングの実習を行うという形式で進んでいきました.講義の冒頭では毎日,受講者の皆さま全員から進捗報告をしていただき,それをもとに実装における「罠」なども議論しています.

最終日までに多くの方がカルマンフィルタと3次元変分法の実装を完了し,一部の方はアンサンブルカルマンフィルタや4次元変分法についても結果を示すところまで進みました.合宿の最後には皆さまに修了書をお渡しすることができました.

データ同化合宿2018(基礎編)の講義の様子 データ同化合宿2018(基礎編)の実習の様子

51st Data Assimilation Seminar – Prof. Roland Potthast

We held the 51st Data Assimilation Seminar at RIKEN Center for Computational Science (R-CCS) on November 13. The seminar talk was given by Professor Roland Potthast from Deutscher Wetterdienst (DWD), the German National Meteorological Service, and University of Reading.

Prof. Potthast spoke about the ICON global and mesoscale model under development at DWD and alongside COSMO partners.

We would like to thank Prof. Potthast very much for visiting us at RIKEN and providing us with a good overview of all the interesting research happening at DWD. We look forward to his next visit to RIKEN.

For details on upcoming DA seminars, please see the following DA seminar page:
http://www.data-assimilation.riken.jp/en/events/da_seminar/index.html.

第51回データ同化セミナー (11月13日)のご案内

11/13のデータ同化セミナーについてのご案内です。
今回のセミナーでは、
Prof. Roland Potthast (DWD/U of Reading)
よりご講演頂きます。

※どなたでもご参加いただけますが、入館に手続きが必要なため、
事前に下記までご連絡をお願い致します。
da-seminar(please remove here)@riken.jp

以下URLに随時情報を更新しています。
http://data-assimilation.riken.jp/en/events/da_seminar/

以下、詳細です。

##############################

Date: *Tuesday 13 November 2018, 10:30-12:00 *
Place: Room – R104-2 at R-CCS
Language: English
Speaker: Prof. Roland Potthast (DWD/U of Reading)

*Title: New Observations and Algorithmic Developments for Convective Scale
Ensemble Data Assimilation*

*Abstract: *
We first present the setup of the ensemble data assimilation (EDA) and
forecasting systems (EPS) which have been developed and are under
development at the German Weather Service DWD and its COSMO partners. This
is first the ICON global+mesoscale model (two-way nested), 13km/6.5km
resolution, with its hybrid ensemble variational data assimilation
(LETKF+EnVAR) run on a 3h cycle,and the ensemble prediction system ICON
EPS. Second, this system drives the high-resolution ensemble data
assimilation system COSMO-KENDA (Kilometer Scale Ensemble Data
Assimilation) with 2.2km operational resolution at DWD and up to 1km
resolution at further members of the COSMO consortium (Germany,
Switzerland, Italy, Russia, Poland, Romania, Greece and Israel) to provide
initial conditions for the high-resolution ensemble forecasting systems,
e.g. the operational COSMO-D2-EPS or experimental ICON-LAM EPS. The system
is also successfully run on GPU based supercomputers.

The core task of the talk is to discuss recent and current developments on
new observations and on new algorithmic developments on the convective
scale, but many of them relevant for global NWP as well. We discuss recent
insight into the importance of quality control, report on the large success
and positive impact of Mode-S data assimilation, discuss the assimilation
of RADAR radial winds and reflectivity with an ensemble Kalman filter and
finally report on some initial tests on the assimilation of visible
channels SEVIRI VIS on the convective scale.

Second, we will discuss new algorithmical developments, in particular
aspects of 4D-LETKF versus 3D-LETKF and initial tests on the ICON-LAM data
assimilation with the KENDA system. Then, we present the particle filter
for global or convective scale EDA as well as ultra-rapid data assimilation
(URDA) on a scale of minutes imbedded into an operational rapid update
cycle (RUC) of a convection resolving model.

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