Data Assimilation Seminar Series

Next Seminar

Date & Time

09:30 - 11:00 Wednesday 6th April 2022

Place & Contact Zoom (Online only)
To join the meeting, please contact the following address in advance.
da-seminar(please remove here)
Language English

Prof. Craig H. Bishop (University of Melbourne, Australia)


The Bounded Variable Ensemble Transform Filter: A non-linear, non-Gaussian extension of the LETKF


Initial condition estimates and model representations of clouds, precipitation, relative humidity, ice, and aerosols are a major source of weather and climate prediction error. Forecasts and observations of these variables often result in values that are just a few error standard deviations from their bounds. For example, ensemble precipitation forecasts can produce distributions in which the mean is roughly one ensemble standard deviation bigger than precipitation’s lower bound of zero. In such cases, distributions tend to be highly skewed, and poorly approximated by Gaussian distributions. Remote sensors of cloud/rain typically yield observations that are non-linear functions of the model variables used to predict them. Here, we present new methodologies that enable the Local Ensemble Transform Kalman Filter (LETKF) to better approximate a fully non-linear Bayesian data assimilation scheme for observations of these variables. The method is based around a deterministic ensemble Kalman filter that, unlike the LETKF, assimilates observations one after the other. However, we have discovered how to express the results in terms of a symmetric transformation of the original ensemble perturbations. Such symmetric transformations are important to the LETKF approach because they maximize the spatial continuity of analysis perturbations. The approach allows the standard LETKF assumption of a Gaussian prior and a Gaussian observation likelihood to be replaced by, for example, gamma prior and inverse-gamma observation likelihood for variables bounded on one side and a Beta prior and Binomial observation likelihood for variables bounded on two sides. When the observation operator is non-linear, the LETKF often produces an analysis ensemble of the observed variable that is inconsistent with the underlying model variables. Our new approach eliminates this inconsistency with a Gauss-Newton iteration. Localization is achieved through ensemble “squeezing”. In idealized data assimilation experiments, the Bounded Variable Ensemble Transform (BVET) enhanced LETKF profoundly out-performs the unenhanced LETKF.


Number Date Speaker Title (click the title to see abstract & PDF)



February 18,
Prof. Bo-Wen Shen (San Diego State University, USA) Coexisting Chaotic and Non-chaotic Attractors, Multistability, Multiscale Instability, and Predictability within Lorenz Models



January 20,
Prof. Avelino F. Arellano (University of Arizona, USA) The Impact of Precipitable Water Vapor Data Assimilation on North American Monsoon Precipitation Forecast in Northern Mexico



January 7,
Prof. Keiya Yumimoto (Kyushu Univesrsity) Integration of aerosol satellite retrieval and data assimilation



Novermber 29,
Prof. Naoki Hirose (Kyushu Univesrsity) Moderately-determined data assimilation with coastal ocean models



Novermber 5,
Dr. Philippe Baron (NICT) Study of 3D recurrent neural networks for very short-term prediction of torrential rains with a Multi-Parameter Phased-Array Radar (MP-PAWR)



September 30,
Dr. Shunsuke Noguchi (JAMSTEC) Gravity wave resolving prediction experiments by using a Japanese Atmospheric GCM for Upper Atmosphere Research (JAGUAR) and its data assimilation product



July 16,
Dr. Milija Zupanski
(Cooperative Institute for Research in the Atmosphere)
An ensemble data assimilation method with state-space covariance localization and global numerical optimization



June 23,
Dr. Akira Yamazaki
EFSO at different geographical locations verified with observing-system experiments



April 14,
Dr. Pierre Tandeo
(IMT Atlantique)
Narrowing uncertainties in climate projections using data science tools



April 9,
Mr. Thomas Hitchcock
(University of St Andrews)
Conflicts and trade-offs in relation to sex



March 31,
Dr. Yicun Zhen
(Ifremer & IMT Atlantique) &
Dr. Arata Amemiya
Location uncertainty from another point of view/ Connecting Data Assimilation and Neural ODE



March 18,
Dr. Maha Mdini
(R-CCS) &
Dr. Simon Benaichouche
(IMT Atlantique & e-odyn)
Accelerating Climate Model Computation by Neural Networks/ Variational learning of sea surface current reconstructions from AIS data streams



March 3,
Mr. Aurelien Colin
(IMT Atlantique & CLS, France) &
Dr. Hirotaka Hachiya
(Wakayama University, Japan)
Semantic Segmentation of Metocean Processes and Estimation of Ancillary Data/ Spatio-temporal integration of forecast guidance outputs using U-Net



February 17,
Dr. Takemasa Miyoshi
(R-CCS, Japan)
Big Data, Big Computation, and Machine Learning in Numerical Weather Prediction.



December 8,
Dr. Maha Mdini
(R-CCS, Japan)
Accelerating Climate Model Computation by Neural Networks: A comparative study.



November 20,
Dr. Koji Terasaki
(R-CCS, Japan)
Including the horizontal observation error correlation in the assimilation of AMSU-A data.



October 1,
Prof. Shu-Chih Yang
(NCU, Taiwan)
Recent improvements of the NCU convective-scale ensemble data assimilation system and their impact on short-term precipitation prediction in Taiwan.



September 11,
Prof. Shunji Kotsuki and Dr. Keiichi Kondo
(Chiba University and JMA-MRI)
A local particle filter based on non-Gaussian statistics using an intermediate AGCM (Dr. Kondo). A Local Particle Filter and Its Gaussian Mixture Extension: Experiments with an Intermediate AGCM (Prof. Kotsuki)



July 20,
Prof. Yohei Sawada
(University of Tokyo)
Advancing hydrometerological prediction by the integration of process-based simulation and machine learning



June 10,
Dr. Guo-Yuan Lien
(CWB, Taiwan)
Recent data assimilation work at Taiwan's Central Weather Bureau (CWB) and perspectives on its global NWP development



May 1,
Dr. James Taylor
Oversampling Reflectivity Observations from a Geostationary Precipitation Radar Satellite: Impact on Typhoon Forecasts within an OSSE Framework



Dec 2,
Dr. Shun Ohishi
(Nagoya University)
An LETKF-based ocean data assimilation system for the Asia-Oceania region



Oct 25,
Dr. Naoto Nakano
(Kyoto University)
Data driven modeling using reservoir dynamics



Sep 30,
Prof. Michael Ng
(Hong Kong University)
Robust Tensor Completion and Its Applications



Sep 10,
Prof. Shu-Chih Yang
(National Central University, Taiwan)
Recent developments and challenges of the regional ensemble data assimilation system for high-impact weather prediction in Taiwan



Aug 21,
Dr. Shigenori Otsuka
RIKEN Nowcast: optical flow and machine learning



July 3,
Dr. Tse-Chun Chen
(University of Maryland)
How to improve forecasts by identifying and deleting detrimental observations



May 31,
Professor Serge Guillas
(U College London)
Statistical emulation to quantify uncertainties in tsunami modelling using high performance computing



May 7,


Prof. Ming-Cheng Shiue
Mathematical analysis of data assimilation algorithms based on synchronization of truth and models



Apr 25,


Dr. Atsushi Okazaki
Impact of geostationary satellite borne precipitation radar on numerical weather prediction: An observing system simulation experiment with an ensemble Kalman filter for a typhoon case



Feb 1,


Dr. Tie Dai
Development and application of aerosol data assimilation in NICAM



Jan 28,


Ms. Jemima Tabeart
(U of Reading)

Using reconditioning to study the impact of correlated observation errors in the Met Office 1D-Var system



Jan 28,


Dr. Alison Fowler
(U of Reading)

Data compression in the presence of observation error correlations



Jan 18,


Prof. Eugenia Kalnay
(U of Maryland)

Can large-scale solar and wind farms create a significant climate change? A model experiment in the Sahara



Dec 19,


Dr. Tetsuo Nakazawa

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



Nov 13,


Prof. Roland Potthast
(DWD/U of Reading)

New Observations and Algorithmic Developments for Convective Scale Ensemble Data Assimilation



Oct 25,


Dr. Jing-Shan Hong
(CWB, Taiwan)

Re-Center algorithm on the Continuous Cycling Radar Data Assimilation: Multi-scale Blending Scheme



Jul 27,


Prof. Pierre Tandeo

(IMT Atlantique)

Data-driven methods in geophysics
2018-07 (48th)

Jul 27,


Dr. Hironori Arai

(U Tokyo)

Establishing an integrated MRV system of Greenhouse gas emission from wetlands with Japanese earth-observation/modelling technologies and a data assimilation technique
2018-06 (47th) Jun 28, 2018 Prof. John C. Wells
(Ritsumeikan U)
Towards nowcasting in Lake Biwa: field tests of acoustic tomography, and discussion of some theorems relating the flow at a water surface to that below
2018-05 (46th) Apr 17, 2018 Dr. Kohei Takatama
Regional atmospheric data assimilation coupled with an ocean mixed layer model: a case of typhoon Soudelor (2015)
2018-04 (45th) Feb 16, 2018 Prof. Pierre Tandeo
(IMT Atlantique)
The analog data assimilation: method, applications and implementation
2018-03 (44th) Feb 9, 2018 Prof. Roland Potthast
(DWD/U of Reading)
Data Assimilation From Minutes to Days
2018-02 (43rd) Jan 29, 2018 Dr. Shinsuke Satoh
Three-dimensional precipitation data measured by phased array weather radar every 30 seconds
2018-01 (42nd) Jan 18, 2018 Prof. David J. Stensrud
(Penn State U)
2017-16 (41st) Dec 11, 2017 Dr. Tsuyoshi Thomas Sekiyama
(Meteorological Research Institute, Japan Meteorological Agency)
Data assimilation of atmospheric chemistry: past, present, and future
2017-15 (40th) Nov 17, 2017 Prof. Yusuke Uchiyama
(Kobe U)
Challenges and issues in forward regional ocean modeling: Eddies, terrestrial influences, and surface gravity waves
2017-14 (39th) Oct 12, 2017 Mr. Krishnamoorthy Chandramouli
(IIT Madras)
Dr. Koji Terasaki
Impact of assimilating humidity sounder radiances with the NICAM-LETKF system
2017-13 (38th) Sep 26, 2017 Mr. Cheng Da
(U of Maryland)
Dr. Guo-Yuan Lien
Assimilation of the GSMaP Precipitation Data with the SCALE-LETKF System
2017-12 (37th) Aug 16, 2017 Ms. Paula Maldonado
(CONICET-U of Buenos Aires)
Radar Data Assimilation in a Case of Deep Convection in Argentina
2017-11 (36th) Aug 16, 2017 Mr. Sam Hatfield
(Oxford U)
How low can you go? Reducing the precision of data assimilation to improve forecast skill
2017-10 (35th) Aug 4, 2017 Dr. Chih-Chien Tsai
(TTFRI, Taiwan)
Preliminary Experimental Results of Polarimetric Radar Data Assimilation in the Case of Typhoon Soudelor (2015)
2017-09 (34th) Jun 26, 2017 Dr. Toshio Iguchi
Radar Measurement of Precipitation from Space: TRMM/PR and GPM/DPR rain retrieval algorithms data
2017-08 (33rd) May 18, 2017 Dr. Guo-Yuan Lien
30-second-cycle convection-resolving data assimilation of dense phased array weather radar data
2017-07 (32nd) Mar 7, 2017 Dr. Alison Fowler
(U of Reading)
On the interaction of observation and a-priori error correlations in data assimilation
2017-06 (31st) Mar 7, 2017 Dr. Joanne A. Waller
(U of Reading)
Diagnosing observation error statistics for numerical weather prediction
2017-05 (30th) Mar 7, 2017 Prof. Nancy K. Nichols
(U of Reading)
New applications and challenges in data assimilation
2017-04 (29th) Mar 6, 2017 Prof. Steven J. Greybush
(Penn State U)
Ensembles, Data Assimilation, and Predictability for Winter Storms
2017-03 (28th) Mar 6, 2017 Prof. Eugenia Kalnay
(U of Maryland)
Modeling Sustainability: Coupling Earth and Human System Models
2017-02 (27th) Feb 7, 2017 Prof. Hiromichi Nagao
(U of Tokyo)
Promises and Challenges in Assimilation of Infrared and Microwave All-sky Satellite Radiances for Convection-Permitting Analysis and Prediction
2017-01 (26th) Jan 13, 2017 Prof. Fuqing Zhang
(Penn State U)
Data assimilation for massive autonomous systems based on a second-order adjoint method
2016-09 (25th) Dec 22, 2016 Dr. Takahiro Nishimichi
(Kavli IPMU, U of Tokyo)
Dark Emulator: cosmic large-scale structures and parameter estimate
2016-08 (24th) Dec 21, 2016 Dr. Takumi Honda
Assimilating All-Sky Himawari-8 Satellite Infrared Radiances: Preliminary Case Studies
2016-07 (23rd) Nov 24, 2016 Mr. Yasumitsu Maejima
Impacts of dense and frequent surface observations on a sudden severe rainstorm forecast: A case of an isolated convective system
2016-06 (22nd) June 13, 2016 Mr. Yasutaka Ikuta
Assimilation of GPM/DPR at JMA
2016-05 (21st) Apr 14, 2016 Dr. Yohei Sawada
Advancing land data assimilation science to monitor terrestrial water and vegetation dynamics
2016-04 (20th) Mar 16, 2016 Dr. Juan Ruiz
(U Buenos Aires (CIMA)/RIKEN AICS)
Implementation and evaluation of a regional data assimilation system based on WRF-LETKF
2016-03 (19th) Mar 7, 2016 Prof. Roland Potthast
(DWD/U of Reading)
On Ensemble and Particle Filters for Large-Scale Data Assimilation
2016-02 (18th) Mar 2, 2016 Ms. Chang Yaping
Dr. Shunji Kotsuki
Ensemble data assimilation of MODIS surface temperature into land surface model
2016-01 (17th) Feb 17, 2016 Mr. Sho Yokota
Comparison between LETKF and EnVAR with observation localization
2015-10 (16th) Dec 25, 2015 Dr. Shunji Kotsuki
Ensemble Data Assimilation of GSMaP precipitation into the nonhydrostatic global atmospheric model NICAM
2015-09 (15th) Dec 15, 2015 Dr. Kozo Okamoto
Assimilation of cloud-affected infrared radiances
2015-08 (14th) Oct 21, 2015 Prof. Kosuke Ito
(U of the Ryukyus)
Advanced data assimilation techniques for predicting tropical cyclone intensities
2015-07 (13th) Sep 16, 2015 Mr. Shumpei Terauchi
(U of Tsukuba)
Dr. Guo-Yuan Lien
Verification of the near-real-time weather forecasts and study on 2015 typhoon Nangka with the SCALE-LETKF system
2015-06 (12th) Sep 2, 2015 Dr. Daisuke Hotta
Diagnostic methods for ensemble data assimilation
2015-05 (11th) Jun 25, 2015 Dr. Koji Terasaki
Applying the Local Transform Ensemble Kalman Filter to the non-hydrostatic atmospheric model NICAM
2015-04 (10th) Jun 5, 2015 Prof. S. Lakshmivarahan
(U of Oklahoma)
Nonlinear dynamics and Predicitability
2015-03 (9th) Apr 17, 2015 Prof. Takeshi Enomoto
Assimilation and forecast experiments using bright band heights
2015-02 (8th) Mar 24, 2015 Dr. Shigenori Otsuka
Towards 100-m resolution prediction of local convective storms: predictability and nowcasting
2015-01 (7th) Jan 20, 2015 Dr. Nobumasa Komori
Development of an ensemble-based data assimilation system with a coupled atmosphere-ocean GCM
2014-06 (6th) Dec 26, 2014 Dr. Keiichi Kondo
The 10,240-member ensemble Kalman filtering with an intermediate AGCM without localization
2014-05 (5th) Nov 26, 2014 Prof. Shin-ichiro Shima
(U of Hyogo/RIKEN AICS)
Data assimilation experiments of the dynamic global vegetation model SEIB-DGVM with simulated GPP observations
2014-04 (4th) Nov 26, 2014 Prof. Takeshi Ise
(Kyoto U)
Simulating terrestrial ecosystems: current progress and future perspectives
2014-03 (3rd) Oct 31, 2014 Prof. Masayuki Yokozawa
(Shizuoka U)
Evaluating the productivities of major crops at the global scale using process-based crop model
2014-02 (2nd) Sep 10, 2014 Dr. Guo-Yuan Lien
Ensemble Assimilation of Global Large-scale Precipitation
2014-01 (1st) July 23, 2014 Dr. Juan Ruiz
(U of Buenos Aires (CIMA)/RIKEN AICS)
Efficient parameter estimation for numerical weather prediction models using data assimilation

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