Progress in development of HARMONIE 3D-Var and 4D-Var Contributions from Magnus Lindskog, Roger Randriamampianina, Ulf Andrae, Ole Vignes, Carlos Geijo,

Slides:



Advertisements
Similar presentations
Assimilation of radar data - research plan
Advertisements

Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
COSMO-SREPS COSMO Priority Project C. Marsigli, A. Montani and T. Paccagnella ARPA-SIM, Bologna, Italy.
Status and performance of HIRLAM 4D-Var Nils Gustafsson.
Towards Rapid Update Cycling for Short Range NWP Forecasts in the HIRLAM Community WMO/WWRP Workshop on Use of NWP for Nowcasting UCAR Center Green Campus,
The use of the NWCSAF High Resolution Wind product in the mesoscale AROME model at the Hungarian Meteorological Service Máté Mile, Mária Putsay and Márta.
Brian Ancell, Cliff Mass, Gregory J. Hakim University of Washington
Overview of the present HIRLAM surface assimilation Mainly taken from: HIRLAM Technical Report No. 58.
ISDA 2014, Feb 24 – 28, Munich 1 Impact of ensemble perturbations provided by convective-scale ensemble data assimilation in the COSMO-DE model Florian.
NWP Activities at INM Bartolomé Orfila Estrada Area de Modelización - INM 28th EWGLAM & 13th SRNWP Meetings Zürich, October 2005.
Meso-γ 3D-Var Assimilation of Surface measurements : Impact on short-range high-resolution simulations Geneviève Jaubert, Ludovic Auger, Nathalie Colombon,
Data assimilation and observing systems strategies Pierre Gauthier Data Assimilation and Satellite Meteorology Division Meteorological Service of Canada.
Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu.
Progress in the joint HIRLAM/ALADIN mesoscale data assimilation activities Nils Gustafsson and Claude Fischer.
Outline Background Highlights of NCAR’s R&D efforts A proposed 5-year plan for CWB Final remarks.
HIRLAM 3/4D-Var developments Nils Gustafsson, SMHI.
26 th EWGLAM & 11 th SRNWP meetings, Oslo, Norway, 4 th - 7 th October 2004 Stjepan Ivatek-Šahdan RC LACE Data Manager Croatian Meteorological and Hydrological.
Plans for Short-Range Ensemble Forecast at INM José A. García-Moya SMNT – INM Workshop on Short Range Ensemble Forecast Madrid, October,
Ensemble data assimilation in an operational context: the experience at the Italian Weather Service Massimo Bonavita and Lucio Torrisi CNMCA-UGM, Rome.
DATA ASSIMILATION M. Derkova, M. Bellus, M. Nestiak.
Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia.
WP 3: DATA ASSIMILATION SMHI/FMI Status report 3rd CARPE DIEM meeting, University of Essex, Colchester, 9-10 January 2003 Structure SMHI/FMI plans for.
INTERCOMPARISON – HIRLAM vs. ARPA-SIM CARPE DIEM AREA 1 Per Kållberg Magnus Lindskog.
Introduction of temperature observation of radio-sonde in place of geopotential height to the global three dimensional variational data assimilation system.
NWP Activities at INM José A. García-Moya SMNT – INM 27th EWGLAM & 12th SRNWP Meetings Ljubljana, October 2005.
Progress Update of Numerical Simulation for OSSE Project Yongzuo Li 11/18/2008.
Preliminary results from assimilation of GPS radio occultation data in WRF using an ensemble filter H. Liu, J. Anderson, B. Kuo, C. Snyder, A. Caya IMAGe.
The Impact of Data Assimilation on a Mesoscale Model of the New Zealand Region (NZLAM-VAR) P. Andrews, H. Oliver, M. Uddstrom, A. Korpela X. Zheng and.
Progress Report!for 2003 INM Operational system in use at the end of 2003 (I) The operational system is still based on HIRLAM version.
NCAR April 1 st 2003 Mesoscale and Microscale Meteorology Data Assimilation in AMPS Dale Barker S. Rizvi, and M. Duda MMM Division, NCAR
1 INM’s contribution to ELDAS project E. Rodríguez and B. Navascués INM.
CWB Midterm Review 2011 Forecast Applications Branch NOAA ESRL/GSD.
Status of the NWP-System & based on COSMO managed by ARPA-SIM COSMO I77 kmBCs from IFSNudgingCINECA COSMO I22.8 kmBCs from COSMO I7 Interpolated from COSMO.
Global vs mesoscale ATOVS assimilation at the Met Office Global Large obs error (4 K) NESDIS 1B radiances NOAA-15 & 16 HIRS and AMSU thinned to 154 km.
ALADIN 3DVAR at the Hungarian Meteorological Service 1 _____________________________________________________________________________________ 27th EWGLAM.
OSEs with HIRLAM and HARMONIE for EUCOS Nils Gustafsson, SMHI Sigurdur Thorsteinsson, IMO John de Vries, KNMI Roger Randriamampianina, met.no.
Mesoscale Assimilation of Rain-Affected Observations Clark Amerault National Research Council Postdoctoral Associate - Naval Research Laboratory, Monterey,
Highlights of recent HIRLAM activities Jeanette Onvlee ASM/Workshop
E. Bazile, C. Soci, F. Besson & ?? UERRA meeting Exeter, March 2014 Surface Re-Analysis and Uncertainties for.
Impact of a Hybrid Ensemble-Variational Data Assimilation System on the Performance of an ETKF-based EPS System Åke Johansson, Jelena Bojarova and Nils.
© Crown copyright Met Office Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting Jean-François Caron … or why limited-area.
Recent data assimilation activities at the Hungarian Meteorological Service Gergely Bölöni, Edit Adamcsek, Alena Trojáková, László Szabó ALADIN WS /
ASCAT soil moisture data assimilation with SURFEX
Use of radar data in the HIRLAM modelling consortium
Meteorological and Hydrological Service of Croatia
Assimilation of radar data in HARMONIE Activities and plans
met.no – SMHI experiences with ALARO
WRF Four-Dimensional Data Assimilation (FDDA)
4D-Var HARMONIE Developments
Rapid Update Cycle-RUC
Update on the Northwest Regional Modeling System 2013
Data Assimilation Training
Operational HIRLAM NWP & Status of the Reference Systems Xiaohua Yang
Studies in HARMONIE 3D-Var with 3 hourly rapid update cycling
Highlights of activities
Some discussion points on dynamics
Meteorological and Hydrological Service of Croatia
Radar Data Assimilation
Winter storm forecast at 1-12 h range
Presented by: David Groff NOAA/NCEP/EMC IM Systems Group
Rapid Update Cycle-RUC Rapid Refresh-RR High Resolution Rapid Refresh-HRRR RTMA.
FSOI adapted for used with 4D-EnVar
Lidia Cucurull, NCEP/JCSDA
Integration of NCAR DART-EnKF to NCAR-ATEC multi-model, multi-physics and mutli- perturbantion ensemble-RTFDDA (E-4DWX) forecasting system Linlin Pan 1,
Comparison of different combinations of ensemble-based and variational data assimilation approaches for deterministic NWP Mark Buehner Data Assimilation.
NWP Strategy of DWD after 2006 GF XY DWD Feb-19.
Development of an advanced ensemble-based ocean data assimilation approach for ocean and coupled reanalyses Eric de Boisséson, Hao Zuo, Magdalena Balmaseda.
Project Team: Mark Buehner Cecilien Charette Bin He Peter Houtekamer
NWP activities in Austria in 2006/2007 Y. Wang
P2.5 Sensitivity of Surface Air Temperature Analyses to Background and Observation Errors Daniel Tyndall and John Horel Department.
Presentation transcript:

Progress in development of HARMONIE 3D-Var and 4D-Var Contributions from Magnus Lindskog, Roger Randriamampianina, Ulf Andrae, Ole Vignes, Carlos Geijo, .... Collected and presented by Nils Gustafsson

High priority tasks during 2010 3D-Var: Installation of HARMONIE 3D-Var within the HIRLAM community 3D-Var: Background error statistics and large scale error constraint at mesoscale resolution (3-)4D-Var: A solution to the large extension problem Adjustment of 4D-Var to “simpler” ECMWF and HIRLAM algorithms; Improved 4D-Var physics Rapid update cycling Use of radar wind and reflectivity data

Pre-operational tests at SMHI Cy35t1 5.5 km, 60 levels ALARO physics 3D-Var + CANARI B from downscaled ECMWF ensemble assim. ECMWF SST:s ECMWF LBC Incremental DFI

Forecast verification scores - comparison with HIRLAM

Problems with cold temperatures HIRLAM AROME ALARO

Met.no experiences (from a radar wind impact study by Roger)

Tests at AEMET AEMET testing the HARMONIE 3D-Var on a CRAY SV2. Recently (April 2010) we have completed the installation of the 35h1.2 version at 11 km horizontal resolution and 60 levels. The results showed that forecasts verify somewhat worse than those initialized from interpolated HIRLAM 7.2 analyses. The testing mode was extended to the surface analysis (CANARI). The results indicated that the impact of the surface analyses is retained not long in the forecast. After a few hours of integration the verification parameters reach values similar to those from forecasts initialized with interpolated fields.

Use of HARMONIE for EUCOS – comparison with HIRLAM 6 different upper air network scenarios were simulated with both HIRLAM and HARMONIE For a summer period 1 June – 15 July 2007 it was possible to compare: HIRLAM at 11 km with 4D-Var Non-hydrostatic HARMONIE with ALADIN physics at 4 km (LBCs from HIRLAM) with 3D-Var (Nils Gustafsson, Roger Randriamampianina, Sigurdur Thorsteinsson and John de Vries)

Model domains for the EUCOS studies: HIRLAM 17 km and 11 km HARMONIE 4 km

Verification of temperature profiles in the “best” and “worst” scenarios

Verification of surface pressure and 2 meter temperature in the “best” and the “worst” scenarios

2 meter temperature, scatter plots HIRLAM HARMONIE

IPY study: IASI and polar lows (Roger R.)

Improved forecasts with IASI and campaign data

AMSU impact study (Magnus L.) Verification of temperature profiles Efficiency of variational bias correction

Large extension zone test (Magnus L.) CRL

Verification of temperature and windprofiles with large and small extension zone

Example of assimilation increments from first AROME 3D-Var run (Magnus L. and Ulf A.)

Ensemble assimilation to generate background error statistics (Roger L Ensemble assimilation to generate background error statistics (Roger L. and Magnus L.) So far, most work has been based on downscaling of global ensembles Software for assimilation based on perturbation of observations and use of global ensembles on the lateral boundaries has been prepared

HARMONIE 4D-Var A first version of HARMONIE 4D-Var has been prepared, mainly during 3 “working weeks” One of these of these working weeks in Dec. 2009 was with participation of ALADIN staff We now have a “running” HARMONIE 4D-Var including Multi-incremental minimization Weak digital filter constraint Very simple 4D-Var physics (Buizza)

Comparison of 4D-Var and 3D-Var assimilation increments 4D-Var start of window 4D-Var middle of window 3D-Var

AMSU-A channel 10 single obs experiment with 4D-Var Temperature Wind

Next HARMONIE 4D-Var working week 3 – 7 May at met.no Will be devoted to testing and validation, example of tasks: Clean and validate code developments for multi-incremental 4D-Var Evaluate the functionality of Jc-dfi and removal of multiple dfi:s Test different more informative minimizer. Evaluate simplified physics (presently Buizza) and introduce new, as proposed and partially prepared by Olivier during last ww. External Jbstat converter from one area to another Start up extented exp with 3d-var vs 4dvar and case studies. Start to develope 4d-var with larger extension zone. Further generalisation of 4dvar namelists Phasing of present developments into cy 36

Summary HARMONIE 3D-Var has been installed at several HIRLAM member institutes – pre- operational at SMHI 3D-Var (and surface assimilation with CANARI + OI-Main) works technically, also for AROME on the mesoscale Problems with forecast quality => emphasis on validation for the remainder of HIRLAM A A basic 4D-Var exists No (Few) activities so far on rapid update cycles