Ensemble Kalman Filter Algorithmic Questions

Similar documents
Developing ICON Data Assimilation and Ensemble Data Assimilation

On Ensemble and Particle Filters for Numerical Weather Prediction

Update on the KENDA project

Nonlinear Bias Correction for Satellite Data Assimilation using A Taylor Series Polynomial Expansion of the Observation Departures

C. Gebhardt, S. Theis, R. Kohlhepp, E. Machulskaya, M. Buchhold. developers of KENDA, ICON-EPS, ICON-EDA, COSMO-D2, verification

Representation of model error for data assimilation on convective scale

Assimilation of cloud information into the COSMO model with an Ensemble Kalman Filter. Annika Schomburg, Christoph Schraff

Status Overview on PP KENDA Km-scale ENsemble-based Data Assimilation

Status of KENDA WG1 activities

Deutscher Wetterdienst

Improving the use of satellite winds at the Deutscher Wetterdienst (DWD)

Cross-validation methods for quality control, cloud screening, etc.

Overview on Data Assimilation Activities in COSMO

Assimilating cloud information from satellite cloud products with an Ensemble Kalman Filter at the convective scale

Deutscher Wetterdienst

DWD report. 30 th WGNE-meeting March 2015, NCEP, Washington. Michael Baldauf, Günther Zängl, Michael Buchhold, Roland Potthast

Workshop: Stochastic Modelling in GFD, data assimilation, & non-equilibrium phenomena

The convection-permitting COSMO-DE-EPS and PEPS at DWD

Assimilation of radar reflectivity

Report on the Joint SRNWP workshop on DA-EPS Bologna, March. Nils Gustafsson Alex Deckmyn.

Assimilation of Wind Power Data to Improve Numerical Weather Prediction and Wind Power Prediction

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATH- ER PREDICTION RESEARCH ACTIVITIES FOR

ICON. Limited-area mode (ICON-LAM) and updated verification results. Günther Zängl, on behalf of the ICON development team

WG1 Overview. PP KENDA for km-scale EPS: LETKF. current DA method: nudging. radar reflectivity (precip): latent heat nudging 1DVar (comparison)

Experiences from implementing GPS Radio Occultations in Data Assimilation for ICON

Deutscher Wetterdienst

KENDA at MeteoSwiss. Operational implementation and results. Daniel Leuenberger and the COSMO-NExT team MeteoSwiss, Zürich, Switzerland

Assimilation of MSG visible and near-infrared reflectivity in KENDA/COSMO

Development and applications of regional reanalyses for Europe and Germany based on DWD s NWP models: Status and outlook

Impact studies with the global model GME. Impact studies with the local model COSMO EU/DE

Variational soil assimilation at DWD

Height correction of atmospheric motion vectors (AMVs) using lidar observations

ISDA Poster Presentations

Optimal Localization for Ensemble Kalman Filter Systems

State of the art of wind forecasting and planned improvements for NWP Helmut Frank (DWD), Malte Mülller (met.no), Clive Wilson (UKMO)

Seminar: Data Assimilation

CTTH Cloud Top Temperature and Height

1. Current atmospheric DA systems 2. Coupling surface/atmospheric DA 3. Trends & ideas

Developments at DWD: Integrated water vapour (IWV) from ground-based GPS

Fundamentals of Data Assimilation

Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres

An overview of the assimilation of AIRS and IASI Radiances at operational NWP Centres

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2016

EnKF Review. P.L. Houtekamer 7th EnKF workshop Introduction to the EnKF. Challenges. The ultimate global EnKF algorithm

Introduction. Recent changes in the use of AMV observations. AMVs over land. AMV impact study. Use of Scatterometer data (Ascat, Oceansat-2)

Improved analyses and forecasts with AIRS retrievals using the Local Ensemble Transform Kalman Filter

Global Impact Studies at the German Weather Service (DWD)

Satellite Data Assimilation in Regional Numerical Weather Prediction as a Key for Better Cloud Cover Forecasts in Tropical Environments

An Ensemble Kalman Filter for NWP based on Variational Data Assimilation: VarEnKF

4DEnVar. Four-Dimensional Ensemble-Variational Data Assimilation. Colloque National sur l'assimilation de données

Nonlinear error dynamics for cycled data assimilation methods

HErZ TB4 Climate Monitoring and Diagnostics

Can hybrid-4denvar match hybrid-4dvar?

WRF Model Simulated Proxy Datasets Used for GOES-R Research Activities

Assimilation of 3D radar reflectivities with an ensemble Kalman filter on the convective scale

Relative Merits of 4D-Var and Ensemble Kalman Filter

Assimilation of Wind Power Data to Improve Numerical Weather Prediction and Wind Power Prediction

ON DIAGNOSING OBSERVATION ERROR STATISTICS WITH LOCAL ENSEMBLE DATA ASSIMILATION

Convective-scale data assimilation at the UK Met Office

Contents. Upcoming events. W2W Newsletter Vol.02, No. 01, Jan/Mar Welcome to the spring edition of the W2W Newsletter.

Assimilation of cloud/precipitation data at regional scales

Assimilation of Satellite Infrared Brightness Temperatures and Doppler Radar Observations in a High-Resolution OSSE

THORPEX Data Assimilation and Observing Strategies Working Group: scientific objectives

Variational data assimilation of lightning with WRFDA system using nonlinear observation operators

Comparison of ICON- and COSMO-EU forecast quality

4. DATA ASSIMILATION FUNDAMENTALS

Use of satellite winds at Deutscher Wetterdienst (DWD)

Enhancing information transfer from observations to unobserved state variables for mesoscale radar data assimilation

Ensemble Kalman Filter based snow data assimilation

New developments for the use of microphysical variables for the assimilation of IASI radiances in convective scale models

GUEDJ Stephanie KARBOU Fatima RABIER Florence LSA-SAF User Workshop 2010, Toulouse

Report of the Scientific Project Manager

Consortium for Small- Scale Modelling

SMHI activities on Data Assimilation for Numerical Weather Prediction

Assimilation of the IASI data in the HARMONIE data assimilation system

Satellite section P. Bauer E. Moreau J.-N. Thépaut P. Watts. Physical aspects section M. Janiskova P. Lopez J.-J. Morcrette A.

Introduction to Data Assimilation

Representation of inhomogeneous, non-separable covariances by sparse wavelet-transformed matrices

Radiance Data Assimilation with an EnKF

Verification of ECMWF products at the Deutscher Wetterdienst (DWD)

Summary of activities with SURFEX data assimilation at Météo-France. Jean-François MAHFOUF CNRM/GMAP/OBS

Observation minus Background Statistics for Humidity and Temperature from Raman lidar, microwave radiometer and COSMO-2

Soil moisture analysis at DWD

Comparisons between 4DEnVar and 4DVar on the Met Office global model

Data Assimilation Development for the FV3GFSv2

Optimal combination of NWP Model Forecasts for AutoWARN

Deutscher Wetterdienst

16. Data Assimilation Research Team

Title: Monitoring the observation impact with Taiwan Central Weather Bureau operational analysis/forecast system

Environment Canada s Regional Ensemble Kalman Filter

The Nowcasting Demonstration Project for London 2012

All-sky observations: errors, biases, representativeness and gaussianity

On the assimilation of hyperspectral infrared sounder radiances in cloudy skies

Initial trials of convective-scale data assimilation with a cheaply tunable ensemble filter

Ensemble Kalman filter assimilation of transient groundwater flow data via stochastic moment equations

Jidong Gao and David Stensrud. NOAA/National Severe Storm Laboratory Norman, Oklahoma

Gaussian Mixture Filter in Hybrid Navigation

Applications of an ensemble Kalman Filter to regional ocean modeling associated with the western boundary currents variations

ITSC-16 Conference. May 2008 Using AVHRR radiances analysis for retrieving atmospheric profiles with IASI in cloudy conditions

Development and Research of GSI-based EnVar System to Assimilate Radar Observations for Convective Scale Analysis and Forecast

Transcription:

Ensemble Kalman Filter Algorithmic Questions KENDA Mini Workshop Roland Potthast Deutscher Wetterdienst, Offenbach, Germany 28.02.2014, LMU Munich EnKF Angorithmic Questions Roland.potthast@dwd.de 1

Contents (Speed Dating) 1. EnKF Migration Concept and BACY Testbed Schraff, Reich, Rhodin, Cress, Anlauf, Köpken- Watts, Faulwetter, Stiller, 2. Adaptive Localization Analytical Approach Perianez, Reich, P. (PhD Uni Reading) 3. Multistep Analysis for EnKF Rhodin, Perianez, Reich, P. (DWD) 4. Transformed Localization Rhodin (his talk); Nadeem and P. PhD Project Uni Göttingen 5. Analysis of a Multi-Scale Localization Perianez, Reich, P. 6. Analysis of Retrieval Assimilation, Tomography + EDA Altuntac and P. PhD Project with Uni Göttingen 7. Nonlinearity, Zero Gradient and EnKF Schomburg, Schraff, Perianez, P. EnKF Angorithmic Questions Roland.potthast@dwd.de 2

1. BACY Basic Cycling Testbed EnKF Angorithmic Questions Roland.potthast@dwd.de 3

2. Adaptive Localization Analytical Approach The optimal localization radius depends on The density of observations The observation error The background covariances The number of ensemble members Analytical estimates of the assimilation error Analytical formula to calculate the localization radius Publications in Progress: Perianez, Reich, P. Adaptive Localization: Formula with Instructive Examples Estimate Localization Error: mathematical paper EnKF Angorithmic Questions Roland.potthast@dwd.de 4

3. Multistep Analysis Carry out the analysis in several steps = successive assimilation or multistep analysis Equivalence of this approach based on Bayes Formula B Matrix stays the same after multistep analysis Equivalence of Analysis Ensemble under certain conditions (in general the analysis ensemble is changed) Work/Publications in Progress: Perianez, Reich, Rhodin, P. Multistep Analysis: basic mathematics paper being finished Application in NWP: algorithmical issues implemented in KENDA EnKF Angorithmic Questions Roland.potthast@dwd.de 5

4. Transformed Localization Employ a transformation of the state space or/and the observation space before localization Algebraic Properties of this approach Efficient localization of B Matrix via wavelet space transformation Transformation of Nonlocal Operators (e.g. Radiances) U H x = U y U H T T -1 x = U y Transformed equation H x = y Work/Publications in Progress: Rhodin; Aamir Nadeem and P. Transformed Localization: basic mathematics paper in progress Application to Localization of B Matrix: implementation in progress Application to NWP: radiance assimilation in a second step EnKF Angorithmic Questions Roland.potthast@dwd.de 6

5. Analysis of Multi-Scale Localization Analysis of multi-scale localization with error estimates Showing improvement for instructive Examples Application to ENKF for NWP Work/Publications in Progress: Analysis of Multiscale Localization: basic mathematics paper in progress EnKF Angorithmic Questions Roland.potthast@dwd.de 7

6. Retrieval Assimilation and Tomography Investigate the assimilation of retrievals in contrast to direct assimilation of the observations Equivalence of this approach based on Bayes Formula Equivalence for full EnKF Instructive negative Examples: what goes wrong with retrievals assimilation GPS/GNSS Tomography as a key application Publications in Progress: Altuntac and P.; Bender et al Retrieval Assimilation: basic mathematics paper being finished Direct GNSS Tomography: KENDA implementation by Bender GNSS Tomography: Total Variation Regularization by Altuntac EnKF Angorithmic Questions Roland.potthast@dwd.de 8

7. Nonlinearity, Zero Gradient and EnKF Basic Questions: Analyse the treatment of strong nonlinearities in the EnKF: linear method right? Zero Gradient Question: is it a problem? Examples: cloudy radiances, positive quantities, Cloud Products and the right observation operator? Non-local Norms and the stochasticity of processes RTTOV with opaque cloud at height h Work/Publications in Progress: Schomburg, Schraff, P., Perianez Seviri Cloud Products in NWP: see Annikas talk Seviri direct radiances: Perianez, Schomburg, Schraff, Otkin, P., EnKF Angorithmic Questions Roland.potthast@dwd.de 9

Many Thanks! EnKF Angorithmic Questions Roland.potthast@dwd.de 10

1. Background Migration Concept (1) 1st Step: ICON replaces GME (2) Refined Region over Europe 2nd step: ICON replaces COSMO-EU (3) VarEnKF replaces 3dVAR (4) KENDA replaces Nudging for Cosmo-DE (5) 3rd step: ICON replaces COSMO-DE EnKF Angorithmic Questions Roland.potthast@dwd.de 11

VarEnKF Migration EnKF Angorithmic Questions Roland.potthast@dwd.de 12

KENDA Migration EnKF Angorithmic Questions Roland.potthast@dwd.de 13

2024 © sciencedocbox.com Privacy Policy | Terms of Service | Feedback