Monday, January 21, 2019

09:00- Registration

1 Opening, Keynote 1 Takemasa Miyoshi

09:30-09:40 Opening Opening Talk Takemasa Miyoshi RIKEN
9:40-10:40 Keynote 1-1 Potential of iterative ensemble methods for solving the nonlinear state and parameter-estimation problem Geir Evensen NORCE Norwegian Research Center

2 Broad Applications Henry Abarbanel

10:40-11:10 Invited 2-1 Predicting neutrino flavor evolution in supernova astrophysics, and acoustic structure in birdsong: two unconventional applications of data assimilation Eve Armstrong University of Pennsylvania
11:10-11:30 2-2 Adaptive Ensemble Optimal Interpolation for efficient data assimilation in the Red Sea Peng Zhan KAUST
11:30-11:50 2-3 Data Assimilation and Kernel Reconstruction for Nonlocal Field Dynamics Roland Potthast Deutscher Wetterdienst
11:50-12:10 2-4 Data assimilation in thermoacoustic instabilities and flame dynamics Luca Magri University of Cambridge
12:10-12:20 Group Photo
12:20-13:20 Lunch

3 Observation and Diagnostics Nancy Nichols

13:20-13:50 Invited 3-1 The implications of accounting for observation error correlations on network design. Alison M. Fowler University of Reading
13:50-14:10 3-2 Improving the conditioning of estimated observation error covariance matrices Nancy K Nichols University of Reading
14:10-14:30 3-3 Ensemble sensitivity and sampling error correction evaluated using a convective-scale 1000 member ensemble Tobias Marcel Necker LMU Munich
14:30-14:50 3-4 Using Spatial Gradient Information to Extract Small Scale Information from Observations with Correlated Errors Joel Bedard Environment and Climate Change Canada
14:50-15:10 Break

p1 Poster Session 1

14:30-15:50 Poster Session 1

4 Multi-scale Shu-Chih Yang

16:10-16:40 Invited 4-1 Multi-scale aspects of incremental 4D-Var at ECMWF Elias Valur Holm ECMWF
16:40-17:00 4-2 Accounting for multi-scale vertical error correlation within ETKF through spectral-space covariance localization Daisuke Hotta Meteorological Research Institute, JMA
17:00-17:20 4-3 Efficient Dynamical Downscaling of General Circulation Models Using Continuous Data Assimilation Ibrahim Hoteit King Abdullah University of Science and Technology
17:20-17:40 4-4 Scale-dependent weighting and localization for global numerical weather prediction Catherine Thomas IMSG @ NOAA/NWS/NCEP

Ice Breaker

18:00-20:00 Ice Breaker

Tuesday, January 22, 2019

09:00- Registration

5 Keynote 2 Martin Weissmann

9:30-10:30 Keynote 5-1 Applications of EFSO to Improve NWP Eugenia Kalnay University of Maryland
10:30-10:50 Break

6 Satellite DA Martin Weissmann

10:50-11:20 Invited 6-1 Dealing with observation error correlations and non-Gaussianity in all-sky assimilation Alan Geer ECMWF
11:20-11:40 6-2 All-sky assimilation of ATMS observations with correlated error Kristen Bathmann I.M. Systems Group at NCEP/EMC
11:40-12:00 6-3 Assimilating visible satellite images for convective scale numerical weather prediction Leonhard Scheck Hans-Ertel Centre for Weather Research / German Weather Service
12:00-12:20 6-4 Assimilation of ATMS at ECMWF: NOAA-20 data quality assessment and correlated errors Peter Weston ECMWF
12:20-13:20 Lunch

7 Satellite DA Martin Weissmann

13:20-13:40 7-1 Evaluating Impact of GNSS Radio Occultation Observations from CubeSats in a Hybrid Ensemble-Variational Data Assimilation System Dusanka Zupanski Spire Global, Inc.
13:40-14:00 7-2 Initial observation impact assessment of GOES/GLM lightning in NOAA/NCEP systems Karina Apodaca Colorado State University (CSU) and NOAA/Atlantic Oceanographic and Marine Laboratory (AOML)
14:00-14:20 7-3 Model Parameter Estimation with Data Assimilation using NICAM-LETKF Shunji Kotsuki RIKEN Center for Computational Science
14:20-14:40 Break

p2 Poster Session 2

14:30-15:50 Poster Session 2

8 Nonlinear and Non-Gaussian Takemasa Miyoshi

15:40-16:10 Invited 8-1 EFFICIENT IMPLEMENTATION OF ENSEMBLE BASED METHODS IN SEQUENTIAL DATA ASSIMILATION: ACCOUNTING FOR LOCALIZATION Elias David Nino-Ruiz Department of Computer Science, Universidad del Norte, BAQ 080001, Colombia.
16:10-16:30 8-2 A Localised Markov Chain Particle Filter (LMCPF) for the Global Weather Prediction Model ICON Anne Sophie Walter German Meteorological Service (DWD)
16:30-16:50 8-3 Algorithms for high-dimensional non-linear filtering and smoothing problems Jana de Wiljes Uni Potsdam
16:50-17:10 8-4 Evaluating the mapping particle filter in high-dimensional state spaces Manuel Pulido University of Reading
17:10-17:30 8-5 Nonlinear filtering with local couplings Alessio Spantini Massachusetts Institute of Technology

Wednesday, January 23, 2019

09:00- Registration

9 Keynote 3 Serge Guillas

9:30-10:30 Keynote 9-1 Ensemble Kalman Inversion Andrew Mark Stuart California Institute of Technology
10:30-10:50 Break

10 Uncertainty Quantification Serge Guillas

10:50-11:20 Invited 10-1 Dynamic Bayesian Influenza Forecasting James Gattiker Los Alamos National Laboratory
11:20-11:40 10-2 Bayesian Inference of Spatially-Varying Manning’s n Coefficients in the Coastal Ocean Using Ensemble Kalman Filter and Polynomial Chaos-Based MCMC Adil Siripatana KAUST
11:40-12:00 10-3 Model Uncertainty Quantification for Data Assimilation in partially observed multi-scale systems Sahani Pathiraja Universitaet Potsdam
12:00-12:20 10-4 Tikhonov regularization for ensemble Kalman inversion Neil Chada National Univerity of Singapore
12:20-13:20 Lunch

11 Coupled DA Ibrahim Hoteit

13:20-13:50 Invited 11-1 Coupled assimilation developments for operational NWP at ECMWF Patricia de Rosnay ECMWF
13:50-14:10 11-2 Coupled Data Assimilation for Ocean-Biogeochemical Models Lars Nerger Alfred Wegener Institute
14:30-14:50 11-3 Ensemble Kalman Filtering with One-Step-Ahead Smoothing for Efficient Data Assimilation into One-Way Coupled Models Naila Raboudi KAUST
14:30-14:50 Break

p3 Poster Session 3

14:50-15:50 Poster Session 3

12 DA Theory and Mathematics Sebastian Reich

15:50-16:20 Invited 12-1 Model error treatment in data assimilation Alberto Carrassi Nansen Environmental and Remote Sensing Center and University of Bergen, Norway
16:20-16:40 12-2 Analysis and design of covariance inflation methods from functional viewpoint Le Duc Japan Agency for Marine-Earth Science and Technology
16:40-17:00 12-3 Block methods for solving an ensemble of data assimilations Yann Eric MICHEL Meteo France and CNRS
17:00-17:20 12-4 High-dimensional estimation of nonlinear transformations for Bayesian filtering Ricardo Baptista Massachusetts Institute of Technology
17:20-18:00 Discussion


18:30-19:30 Banquet

Thursday, January 24, 2019

09:00- Registration

13 Keynote 4 Roland Potthast

9:30-10:30 Keynote 13-1 The challenge of bounded, non-Gaussian, non-linear and multi-scale variables Craig H Bishop The University of Melbourne
10:30-10:50 Break

14 Convective DA Roland Potthast

10:50-11:20 Invited 14-1 Non-Parametric Ensemble Analyses with Examples from Advective Flow Data Assimilation Jeffrey Anderson National Center for Atmospheric Research
11:20-11:40 14-2 Direct Assimilation of Radar Reflectivity Data using a Convective-scale EnKF System Jingyao Luo Shanghai Typhoon Institute
11:40-12:00 14-3 Assimilation of 3D radar data and derived objects on the convective scale with an ensemble-based data assimilation system Christian Andreas Welzbacher Deutscher Wetterdienst
12:00-12:20 14-4 Development of Optimized Radar Data Assimilation Capability within the Fully Coupled EnKF-EnVar Hybrid System for Convective-Permitting Ensemble Forecasting and Testing via NOAA Hazardous Weather Testbed Spring Forecasting Experiments Chengsi Liu University of Oklahoma, USA
12:20-13:20 Lunch
13:20-14:00 K-computer tour

15 Big Data Assimilation Takemasa Miyoshi

14:00-14:30 15-1 TBU Takemasa Miyoshi RIKEN
14:30-14:45 15-2 Current status of SCALE and its future toward the accurate numerical weather prediction Hirofumi Tomita RIKEN
14:45-15:00 15-3 An Overview of DTF for Coupling Software Components Yutaka Ishikawa RIKEN
15:00-15:15 15-4 On the improvement of the Phased Array Weather Radar data Tomoo Ushio Tokyo Metropolitan University
15:15-15:30 15-5 Real-time quality control of Phased Array Weather Radar data every 30 seconds Shinsuke Satoh National Institute of Information and Communications Technology
15:30-16:00 15-6 Data Assimilation Studies using Big Observation Data in the Projects of Post K and BDA Hiromu Seko Meteorological Research Institute
16:00-16:20 Break

16 Convective DA Roland Potthast

16:20-16:40 16-1 30-second cycle LETKF assimilation of dual phased array weather radar observations to short-range convective forecasts James Taylor RIKEN
16:40-17:00 16-2 Comparing and Combining the EnVar and EnKF Methods in a Limited-Area Deterministic Context Jean-Francois Caron Environment and Climate Change Canada (ECCC)
17:00-17:20 16-3 LETKF Perturbations by Ensemble Transform in a Cloud Resolving Model Kazuo Saito University of Tokyo
17:20-17:40 16-4 Ultra Rapid Data Assimilation for Real Time Weather Walter Acevedo German Meteorological Service (DWD)
17:30-17:40 Closing

Poster Session

Poster Session 1 (January 21)

p1-1 Assimilating every 30-second phased array weather radar data in a torrential rainfall event on July 6, 2018 around Kobe city Yasumitsu Maejima RIKEN
p1-2 Application of data assimilation method on quantification of pollutant load from watershed in SWAT model Yosuke Horie Nippon Koei Co., Ltd
p1-3 Withdrawn
p1-4 Locally Optimal Weighting of Global Precipitation Forecasts from Precipitation Nowcasting and Numerical Weather Prediction Kenta Kurosawa RIKEN Center for Computational Science
p1-5 Towards hyperresolution land data assimilation to monitor terrestrial water, energy, ecosystem, and hydrological disasters Yohei Sawada Meteorological Research Institute, Japan Meteorologial Agency
p1-6 Application of the Multi-scale Blending Scheme on Continuous Cycling Radar Data Assimilation Siou-Ying Jiang Central Weather Bureau (CWB), Taiwan
p1-7 Ensemble-based Singular Value Decomposition Analysis to Clarify Relationship between the Atmospheric State and the Hydrometeors Sho Yokota Meteorological Research Institute, Japan Meteorological Agency
p1-8 Improving tropical cyclone forecasts with ensemble data assimilation of radar and geostationary satellite data Hong Li Shanghai Typhoon Institute of CMA
p1-9 Representation of multiscale model error in convective - scale data assimilation Yuefei Zeng DWD / LMU
p1-10 UK regional hybrid variational data assimilation developments Gordon Inverarity Met Office
p1-11 Coupled Ensemble Data Assimilation with AWI-CM and PDAF Lars Nerger Alfred Wegener Institute
p1-12 Estimating forecast error covariances for strongly coupled atmosphere-ocean 4D-Var data assimilation Nancy K Nichols University of Reading
p1-13 Data assimilation methods for the passive impurity transfer-diffusion problem Platonova Vladimirovna Marina Novosibirsk State University
p1-14 Ensemble Kalman Filtering with One-Step-Ahead Smoothing Ibrahim Hoteit Earth Science and Engineering
p1-15 Withdrawn
p1-16 Single-precision in 4D-Var: The impact of rounding errors on the tangent-linear and adjoint models Sam Hatfield University of Oxford
p1-17 How does DA address scale interactions in truncated models? Javier Amezcua University of Reading
p1-18 Comparisons of non-Gaussian with Gaussian based observational quality control measures and their impacts on data assimilation systems Steven James Fletcher Colorado State University
p1-19 Non-Gaussian measure in Gaussian Filtering Problem Hideyuki Sakamoto RIKEN
p1-20 Using nonlinear variable transformations to assimilate land surface albedo observations Gernot Geppert University of Reading/NCEO
p1-21 Adaptive covariance relaxation methods for ensemble data assimilation based on innovation statistics Shunji Kotsuki RIKEN Center for Computational Science
p1-22 On the Properties of Ensemble Forecast Sensitivity to Observations Shunji Kotsuki RIKEN Center for Computational Science
p1-23 Withdrawn
p1-24 A retrieval-based approach to obs-space localization of solar satellite channels Lilo Bach Deutscher Wetterdienst
p1-25 Assimilation of cloud-affected satellite observations in idealized experiments of summer-time convection Martin Weissmann DWD / LMU
p1-26 Impact of assimilation of satellite winds on simulating evolution of the tropical cyclone Titli Jyoti Narayan Bhate National Atmospheric Research Laboratory
p1-27 The impact of using reconditioned correlated observation error covariance matrices in the Met Office 1D-Var system Jemima M. Tabeart University of Reading & National Centre for Earth Observation
p1-28 Model error covariances estimation in the mapping particle filter using an online expectation-maximization algorithm Manuel Pulido University of Reading

Poster Session 2 (January 22)

p2-1 Development of long-term high-resolution regional reanalysis system over Japan with NHM-LETKF nested in JRA-55 Shin Fukui Tohoku University
p2-2 Challenges in unsaturated zone data assimilation Harrie-Jan Hendricks-Franssen Forschungszentrum Julich, Germany
p2-3 Data-driven and data-assimilation approaches to individual human brain dynamics Takumi Sase RIKEN Center for Brain Science
p2-4 Optimizing Hydroelectric Dam Operations with Machine Learning Marimo Ohhigashi RIKEN
p2-5 Addressing model error related to surface fluxes by estimating roughness lengths in COSMO-KENDA with the augmented state approach Yvonne Muriel Ruckstuhl Ludwig Maximilian University of Munich (LMU)
p2-6 Current and Future Reanalysis Activities at DWD Thomas Roesch DWD
p2-7 How important is a 4-d approach in the LETKF framework? Hendrik Reich German Weather Service (DWD)
p2-8 Radar Data Assimilation in Idealized Experiments Kevin Bachmann DWD / LMU
p2-9 Sampling Error in the Ensemble-Based Radar Data Assimilation System and Its Impact on Convective-Scale Precipitation Prediction - A Case Study of IOP#8 During SoWMEX Pin-Ying Wu Kyoto University, Japan
p2-10 Withdrawn
p2-11 Development of a global ocean 4DVAR system for coupled predictions and a plan of applying it for coupled data assimilation Yosuke Fujii JMA/MRI
p2-12 Regional atmospheric data assimilation coupled with an ocean mixed layer model: a case of typhoon Soudelor (2015) Kohei Takatama RIKEN
p2-13 Application of the model space vertical localization in a global LETKF at JMA Yoichiro Ota Japan Meteorological Agency
p2-14 Exploring the impacts of orthogonal updates in Hybrid Gain Data Assimilation algorithm Chih-Chien Chang National Central University, Taiwan
p2-15 Withdrawn
p2-16 Spatial structure of weights in the Local Ensemble Transform Kalman Filter: A case with an intermediate AGCM Shunji Kotsuki RIKEN Center for Computational Science
p2-17 4DEnVar with Iterative Calculation of Nonlinear Nonhydrostatic Model Compared to En4DVar Sho Yokota Meteorological Research Institute, Japan Meteorological Agency
p2-18 Exploring Non-Gaussian Approaches for Deterministic Data Assimilation Mark Buehner Environment and Climate Change Canada
p2-19 On Non-Gaussian Probability Densities on Convection Initiation and Development using a Particle Filter with a Storm-Scale Numerical Weather Prediction Model Takuya Kawabata Meteorological Research Institute
p2-20 Variational filtering and smoothing with low-rank transports Daniele Bigoni Massachusetts Institute of Technology
p2-21 Characteristics of analysis increments from a convective-scale ensemble data assimilation system Claire Merker MeteoSwiss
p2-22 Evaluation of GLM Lightning Flash Rate Observation Operators for HWRF Ting-Chi Wu Colorado State University
p2-23 The effect of Observation Data Assimilation on TC quantitative precipitation prediction over Khonkaen, Thailand Chatchai Chaiyasaen 4353 Sukhumvit Rd. Bang-na, Bangkok, Thailand
p2-24 Accounting for the horizontal observation error correlation of precipitation observation Koji Terasaki RIKEN, Center for Computational Sciences
p2-25 Deconvolution of passive microwave brightness temperatures Jeff Steward University of California, Los Angeles
p2-26 Impacts of Rapid Scan Atmospheric Motion Vector and Sea Surface Temperature Obtained by Himawari 8 on the Predictions of Typhoon and Heavy Rainfalls Hiromu Seko Meteorological Research Institute
p2-27 Use of inter-channel correlations for assimilation of IASI Raw Radiances and Reconstructed Radiances in the DWD EnVar Silke May DWD
p2-28 Inversion of landslide parameters for the 1945 Makran tsunami Mariya Mamajiwala University College London
p2-29 Towards a climatological background error covariance matrix for a regional, convective-scale NWP system Claire Merker MeteoSwiss

Poster Session 3 (January 23)

p3-1 A study on the optimal data assimilation system for the whole neutral atmosphere Dai Koshin The University of Tokyo
p3-2 Data assimilation experiments with MODIS LAI observations and the dynamic global vegetation model SEIB-DGVM over Siberia Hazuki Arakida RIKEN
p3-3 Four-Dimensional Ensemble Variational Data Assimilation for parameter estimation with the JULES land surface model Ewan Pinnington University of Reading
p3-4 Withdrawn
p3-5 Analysis and Forecast Using Dropsonde Data from the Inner-Core Region of Tropical Cyclone Lan (2017) Obtained during Aircraft Missions of T-PARCII Kosuke Ito University of the Ryukyus
p3-6 Developments in the Met Office hourly 4D-Var system Gareth Dow Met Office
p3-7 Impact of surface data assimilation on afternoon thunderstorm prediction in Taiwan Ihan Chen Central Weather Bureau (CWB)
p3-8 Real time weather for autonomous driving based on seamless integration of Ultra Rapid Data Assimilation and Nowcasting Zoi Paschalidi German Meteorological Service (DWD)
p3-9 Sensitive and Mechanism Study of Surface Data Assimilation to a Local Torrential Rain Forecast in Shandong Province Chunyan Sheng Shandong Meteorological Bureau
p3-10 A preliminary analysis of a newly-developed regional ocean data assimilation system: a case of Tokyo Bay in summer Kohei Takatama RIKEN
p3-11 Ensemble-Based Atmospheric Reanalysis Using a Global Coupled Atmosphere-Ocean GCM Nobumasa Komori Japan Agency for Marine-Earth Science and Technology
p3-12 Towards Coupled DA in NASA GEOS System - Developments in the Ocean context Rahul Mahajan NASA Goddard Space Flight Center
p3-13 Development and validation of a diagonal ensemble transform Kalman filter Le Duc Japan Agency for Marine-Earth Science and Technology
p3-14 Hierarchical ensemble Kalman filters for stochastic parameters and hyper-parameters inference Guillermo Scheffler CIMA-CONICET/UBA, Argentina
p3-15 On the continuous time limit of the Ensemble Kalman Filter Theresa Lange Technical University Berlin (TU Berlin)
p3-16 An ensemble Kalman filter using potential vorticity for atmospheric multiscale data assimilation Tadashi Tsuyuki Meteorological Colledge
p3-17 Assimilating fractions of precipitation area: an idealized study with an intermediate AGCM Shigenori Otsuka RIKEN
p3-18 Non-Gaussian ensemble-mean update in the ensemble Kalman filter: experiments with an intermediate AGCM Keiichi Kondo Meteorological Research Institute
p3-19 Sequential Bayesian inference for drift estimation in nonlinear stochastic differential equations Paul Joseph Rozdeba University of Potsdam
p3-20 A global ocean state estimation using tidal mixing parameterizations and observed turbulent mixing data Satoshi Osafune JAMSTEC
p3-21 Comparison of the Ensemble and Hybrid Approaches for Estimating Observation Impact Ping Du Environment and Climate Change Canada
p3-22 Near-real-time SCALE-LETKF forecasts of the record breaking rainfall in Japan in July 2018 Takumi Honda RIKEN
p3-23 A comparison study between 1D Abel integral and ray tracing radio occultation observation operators Razvan Stefanescu Spire Global
p3-24 Assimilating remotely sensed white-sky and black-sky albedos for the retrieval of terrestrial canopy leaf area index and the clumping factor Natalie Douglas University of Surrey
p3-25 Ensemble-Based Data Assimilation of GPM/DPR Reflectivity into the Nonhydrostatic Icosahedral Atmospheric Model NICAM Shunji Kotsuki RIKEN Center for Computational Science
p3-26 Precipitation radar data assimilation with an ensemble Kalman filter: an observing system simulation experiment for a typhoon case Atsushi Okazaki RIKEN
p3-27 Bayesian Inference of Grain Growth Prediction via Multi-Phase-Field Models Shin-ichi Ito The University of Tokyo
p3-28 MLCSPG: An efficient and (provably!) accurate solver for high-dimensional parametric PDEs Jean-Luc Bouchot Beijing Institute of Technology
p3-29 Can hydrological observations improve global NWP in land-atmosphere-coupled data assimilation? Kenta Kurosawa RIKEN Center for Computational Science

Organized by

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Organizing Committees

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This Symposium is a part of RIKEN Symposium Series
and is supported by FOCUS Establishing Supercomputing Center of Excellence and JST/CREST.


Local Organizing Committee (LOC):

RIKEN R-CCS Data Assimilation Research Team

7-1-26, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan

Team Website

E-mail: isda2019-staff(please remove here)

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