Poster program
On the morning of your poster presentation, please come to the desk registration where you will be allocated one specific and numbered poster board. You can append your poster already from the morning. Posters MUST BE REMOVED at the end of the session.
POSTER SESSION I - Tuesday 17th October - from 17:20 to 19:45
Name |
Surname |
Title of the contribution |
|
1 | Jelena | Bojarova | Study of the Adjustment Processes and Error propagation in the HybridEnVar Framework in the HARMONIE-Atrome Forecasting System |
2 | Mareike | Burba | DWD's CONTRAILS project: variational assimilation of satellite reflectances |
3 | Luca | Cantarello | Assessing the atmospheric flux inversion system at ECMWF using Observation System Simulation Experiments |
4 | Ying-Jhen | Chen | Comparing the Partial Cycling and Continuous Cycling Data Assimilation Strategies in a High-Resolution Regional Forecast System |
5 | Sandy | Chkeir | Preparing AROME assimilation experiments for cloud-affected satellite observations |
6 | Filipe Bitencourt | Costa | Assessing Impacts of Ensemble Kalman Filter (EnKF) on the Remo Ocean Data Assimilation System (RODAS) Over the South Western Atlantic |
7 | Massimo | D'Isidoro | Data assimilation experiments over Europe with the Chemical Transport Model FARM |
8 | Thomas | Deppisch | Studying the Interaction between NWP Models and Data Assimilation with Observing System Simulation Experiments – Case Studies with SEVIRI Data in ICON-LAM |
9 | Giorgio | Doglioni | Implementation and testing of a WRF/WRFDA-based operational regional NWP routine for Italy. |
10 | Hassnae | Erraji | High-resolution air quality analyses assimilating unmanned aerial vehicle (UAV) observations |
11 | Keenan | Eure | Simultaneous Assimilation of Polarimetric and All-Sky Satellite Data for Ensemble Convection Forecasts |
12 | Luca | Facheris | Tropospheric water vapor observations from space through a new measurement concept and the impact on weather forecasts: the SATCROSS project |
13 | Magdalena | Fritz | Parameter estimation for boundary-layer turbulence models over heterogeneous terrain |
14 | Kensuke | Fujimura | Ensemble Kalman Filtering with perturbed rainfall for improving flush flood predictions by a Rainfall-Runoff-Inundation Model |
15 | Lilian | Garcia-Oliva |
Intercomparison of initialization methods for |
16 | Thomas | Gastaldo | Assimilation of radar observations in the ICON-KENDA system at Arpae-SIMC |
17 | Hugo | Georgenthum | Short-term forecast of sea surface height from NADIR and SWOT altimetry data with 4DVarNets |
18 | Azadeh | Gholoubi Khonacha | Development in All-Sky Microwave Radiance Assimilation over Land in NCEP Global Model |
19 | Nicole | Girardot | Experimentation of model perturbations in Météo-France global EDA |
20 | Luis Gustavo | Goncalves | Assimilation of Land Surface States at CMCC using SPREADS/Ensemble Kalman Filter |
21 | Oliver | Guillet | A C++ implementation of the diffusion method to account for correlated observation errors in OOPS-QG |
22 | Selime | Gurol | Randomized numerical linear algebra for variational data assimilation |
23 | Soyoung | Ha | Coupled data assimilation for the operational air quality forecasting in Korea |
24 | Ieuan | Higgs | Ecosystem connections in the shelf sea environment using complex networks |
25 | Helen | Hooker | Flood inundation forecast improvement by assimilating satellite SAR-derived probabilistic observations |
26 | Bruce | Ingleby | Improved 2m temperature forecasts from assimilation changes at ECMWF |
27 | Bruce | Ingleby | ECMWF use of Mode-S winds and changes to aircraft thinning |
28 | Tijana | Janjic | Ensemble Kalman Filter based Data Assimilation for Tropical Waves in the MJO Skeleton Model |
29 | Kaushambi | Jyoti | Testing Hybrid-3DEnVar in the convective-scale NWP model AROME over Austria |
30 | |||
31 | Yu-Shin | Kim | Impact of Microphysics Parameterization Schemes on the Assimilation of GOES-16 All-Sky Infrared Radiances for a Bow Echo Analysis and Prediction |
32 | Mathieu | Le Provost | An ensemble filter for heavy-tailed t-distributions |
33 | Konstantin | Krüger | The influence of radiosonde observations on the sharpness and altitude of the tropopause |
34 | Martin | Lange | Development of a 2d-Var system for surface analysis at DWD |
35 | Florian | Le Guillou | Parallel long-window weak-constraint 4D variational assimilation for the reconstruction of ocean surface dynamics |
36 | Rakesh Teja | Konduru | Challenges in Assimilation of High-Frequency Satellite Observations Using NICAM-LETKF in the OSSE framework |
37 | Hong | Li | Assimilation of Radar reflectivity data for the analysis and forecast of landfalling typhoon: OSSEs and Real data application |
38 | Guo-Yuan | Lien | The GFS-GSI based Global Forecast System Adapted at Central Weather Bureau of Taiwan: Data Assimilation Development and Performance Evaluation |
39 | Sujeong | Lim | Assimilation Impact of Soil Moisture in a Strongly Coupled Atmosphere-Land Data Assimilation System |
40 | Cristian | Lussana | MET Nordic dataset: post-processing of model output near-surface fields with unconventional observations |
41 | Cory | Martin | Progress Towards Transition of NCEP’s Global Data Assimilation System to JEDI |
42 | Akhilesh S. | Nair | Improving subseasonal prediction with land surface initialisation in NorCPM |
43 | Annika | Oertel | The ‘Swabian MOSES’ field campaign - a testbed for the near real-time assimilation of campaign observations |
44 | Alberto | Ortolani | MC-FORUM: the ASI-funded project for the meteorological and climatological exploitation of FORUM |
45 | Mariam | Petrosyan | Assessing Climate Risk in an Urban Environment: Integrating Remote Sensing Data for a Case Study of Yerevan City |
46 | Hendrik | Reich | Use of high-density Mode-S aircraft observations in ICON regional and global data assimilation system |
47 | Bernd | Schalge | Towards a coupled convection permitting reanalysis for the European CORDEX domain |
48 | Nora | Schenk | Coupled Data Assimilation at DWD: Development of an Ocean Data Assimilation System |
49 | Stefano | Serafin | Probabilistic observation pre-processing for ensemble-based data assimilation: An application to surface temperature observations in Alpine terrain |
50 | Daiya | Shiojiri | Investigating appropriate inflation methods for assimilating soil moisture data into a land surface model |
51 | Anna | Shlyaeva | Developing and using JEDI for Earth system prediction |
52 | Michael | Sitwell | An Ensemble-Variational Inversion System for the Estimation of Ammonia Emissions using CrIS Satellite Ammonia Retrievals |
53 | Sergey | Skachko | A new daily SST analysis system at ECCC |
54 | Martin | Sprengel | Coupled Data Assimilation at DWD: Use of satellite observations for the ocean |
55 | Thorsten | Steinert | Data assimilation for a combined ICON/ICON-ART NWP system at DWD |
56 | Clemente Augusto Souza | Tanajura | Observing System Simulation Experiments with SWOT into HYCOM+RODAS over the Southwest Atlantic |
57 | Ricardo | Todling | Preliminary Results Cycling GEOS-JEDI with GSI-based Background Error Covariances |
58 | Maria | Toporov | Assimilation of ground-based microwave radiometer observations into the convection resolving ICON model: observing system simulation experiments. |
59 | Arianna | Valmassoi | Towards a new generation of regional reanalyses for Europe |
60 | Sophie | Vliegen | Assessment of weakly and strongly coupled data assimilation in ocean-biogeochemical modeling |
61 | Nicholas | Williams | Enhancing sea ice prediction in NorCPM using assimilation of sea ice thickness from ENVISAT and C2SMOS |
62 | Richard | Williams | Coupled Data Assimilation at DWD: Impact of conventional observations on the ocean |
63 | Marek | Wlasak | The development of a static spectral background error covariance model within JCSDA (Joint Centre for Satellite Data Assimilation) JEDI (Joint Effort for Data assimilation Integration) framework. |
64 | Ting-Chi | Wu | Evaluation of an Ensemble Partial Cycle Framework for Use in the Regional Ensemble Prediction System at the Central Weather Bureau of Taiwan |
65 | Youlong | Xia | Assessment and application of the UFS Land DA System at NCEP/EMC |
66 | Hongqin | Zhang | Integral correction of initial and model errors in system of multigrid NLS-4DVar data assimilation for numerical weather prediction (SNAP) |
67 | Lijian | Zhu | Direct Assimilation of All-Sky GOES-R ABI Radiances in GSI EnKF for the Analysis and Forecasting of a Mesoscale Convective System |
68 | Alexander | Kelbch | Ensemble-based regional reanalysis system for Central Europe: ICON model setup, test experiments and outlook |
POSTER SESSION II - Thursday 19th October - from 17:20 to 19:45
Name |
Surname |
Title of the contribution |
|
1 | Brian | Ancell | Ensemble Sensitivity-Based Subsetting: Progress Toward Operational Use |
2 | Maxime | Beauchamp | Towards a stochastic formulation of neural variational scheme for learning SPDE-based priors and solvers |
3 | Michele | Bendoni | The impact of 4D-Var data assimilation of HF-Radar and SST observations on the surface circulation of the North-Western Mediterranean Sea |
4 | Diksha | Bhandari | Affine Invariant Ensemble Transform Methods to improve predictive uncertainty in ReLU networks |
5 | Matteo | Broccoli | Towards an Observation Operator for Satellite Retrievals of Sea Surface Temperature with Convolutional Neural Network |
6 | Adam | Clayton | Development of existing and future DA systems at KIAPS |
7 | Deepjyoti | Deka | Physics-informed Neural Networks for Localization in Stochastic Power Grids |
8 | Theresa | Diefenbach | How to use partial analysis increments in an LETKF data assimilation system |
9 | Simon | Driscoll | A data driven emulator of sea ice melt pond processes |
10 | Connor | Duffin | Statistical finite elements for ocean dynamic processes |
11 | Charlotte | Durand | Deep learning for surrogate modeling to facilitate data assimilation in sea-ice models |
12 | Léo | Edel | Reconstruction of Arctic sea ice thickness (2000-2010) based on a hybrid machine learning and data assimilation approach |
13 | Ehouarn | Simon | Lp-norm regularization - with 1<p<2 - in variational data assimilation |
14 | Jie | Feng | Spatiotemporal estimation of analysis errors in the operational global data assimilation system at the China Meteorological Administration using a modified SAFE method |
15 | Tobias | Finn | Generating ensembles from single realizations with denoising diffusion models |
16 | Francesco | Fossella | Nudging and Ensemble Kalman Filter at high Reynolds numbers |
17 | Alison | Fowler | On the robustness of methods to account for background bias in data assimilation to uncertainties in the bias estimates |
18 | Yukiko | Fujisawa | Series of Observation System Simulation Experiments for the Venusian atmosphere |
19 | Olivier | Goux | Accounting for correlated observation error is variational ocean data assimilation |
20 | Philipp | Griewank | Localizing ensemble observation impact estimates |
21 | Zdenko | Heyvaert | Assessment of multi-layer increment distributions in an EnKF system for land data assimilation |
22 | Ieuan | Higgs | Machine learning for multivariate data assimilation in marine biogeochemistry |
23 | Daisuke | Hotta | VAE as a Stochastic Multidimensional Extension to Gaussian Anamorphosis (Part 2) |
24 | Chih-Chi | Hu |
Observing system simulation experiments (OSSE) using the Particle Flow Filter (PFF) in a high-dimensional atmospheric model in the Data Assimilation Research Testbed (DART) |
25 | Tijana | Janjic | Learning model parameters from observations by combining data assimilation and machine learning |
26 | Takuya | Kawabata | The impact-based forecasting with a large-ensemble DA |
27 | Fumitoshi | Kawasaki | Solving Data Assimilation on Quantum Annealing Machines |
28 | Fumitoshi | Kawasaki | Leading the Lorenz system toward the prescribed regime by model predictive control combined with data assimilation |
29 | Junkyung | Kay | UAS observation error estimation for data assimilation and its impact on predictive skill |
30 | Yu-Shin | Kim | Scale-Dependent Inflation for Multiscale Ensemble based Data Assimilation |
31 | Shunji | Kotsuki | Exploring weather control technology to steer the atmosphere towards favorable directions |
32 | Shunji | Kotsuki | Combining Data Assimilation and Data-driven Sparse Sensing Placement Method For Designing Better Observation Locations for NWP |
33 | Monika | Krysta | National Analysis System for Australia |
34 | Mathieu | Le Provost | Regularization of the ensemble Kalman filter for non-local observations: application to elliptic observations |
35 | César Magno | Leite de Oliveira Júnior | Radiance Data Assimilation by Cellular Neural Networks |
36 | Jianyu (Richard) | Liang | Understanding the Dynamics of Venus’ Atmosphere using Bred Vectors |
37 | Shun | Liu | Data Assimilation System Development and Testing for Rapid Refresh Forecast System |
38 | Alexander | Lobbe | Noise calibration for the stochastic rotating shallow water model |
39 | Anqi | Lyu | Compare online versus offline assimilation for paleoclimate reanalysis |
40 | Richard | Ménard | A critical view on research in chemical data assimilation and inverser modeling. A 5-day workshop summary overview |
41 | Yuka | Muto | Climatologically augmented local ensemble transform Kalman filter for estimating global precipitation from gauge observations |
42 | Saori | Nakashita | Observation-space localization methods for the maximum likelihood ensemble filter |
43 | Andrea | Orlandi | Studies on breeding-driven adaptive Data Assimilation applied to Low Order Models |
44 | Mao | Ouyang | A hybrid data assimilation with reservoir computing to advance the control simulation experiment |
45 | Mao | Ouyang | Producing balanced analysis ensemble in local particle filter using a differential resampling method |
46 | Ivo | Pasmans | Ensemble Kalman filter in latent space using a variational autoencoder pair |
47 | Naila | Raboudi | Ensemble Kalman Smoothing with Exact Second-Order Observation Perturbations Sampling For Ocean Reanalyses |
48 | Laura | Risley | On the choice of velocity variables for variational ocean data assimilation |
49 | Vanya | Romanova | Integrated atmosphere-ocean-land data assimilation for climate analysis and seasonal predictions. |
50 | Yvonne | Ruckstuhl | Combining the Stochastic Galerkin with data assimilation for parameter estimation |
51 | Hamza | Ruzayqat | A Class of Filtering Problems with Unknown Spatial Observations |
52 | Takumi | Saito | Designing Effective Observing Network for Data Assimilation based on Sparse Sensor Placement Method |
53 | Yohei | Sawada | An efficient estimation of spatio-temporally distributed parameters in dynamic models by an ensemble Kalman filter |
54 | Francine | Schevenhoven | Supermodelling: improving predictions with an interactive ensemble |
55 | Daiya | Shiojiri | Introducing data-driven sparse sensor placement to determine rain gauge locations |
56 | Simone | Spada | A Gauss-Hermite high-order sampling hybrid filter for data assimilation in geoscience |
57 | Olaf | Stiller | Applying covariance based cross-validation diagnostics for improving the localization of non-local observations |
58 | Norihiko | Sugimoto | AFES (GCM) LETKF Data Assimilation System for Venus |
59 | Victor | Trappler | State-dependent preconditioning for Variational DA |
60 | Peter Jan | van Leeuwen | Estimating Model Error Covariances from weak-constraint variational data assimilation |
61 | Senne | Van Loon | Nongaussian Ensemble Data Assimilation |
62 | |||
63 | Pin-Ying | Wu | Investigation of error growth and non-Gaussianity in severe weather predictions using large-ensemble DA |
64 | Ting-Chi | Wu | Recent Development and Evaluation of a Global Atmospheric Ensemble Data Assimilation using NICAM global model and Maximum Likelihood Ensemble Filter with State Space Localization |
65 | Yue (Michael) | Ying | Improving vortex position accuracy with a new multiscale alignment ensemble filter |
67 | Takemasa | Miyoshi | PREVENIR: Japan-Argentina Cooperation Project for Heavy Rain and Urban Flood Disaster Prevention |