Experiences with the ALADIN 3D VAR system

Similar documents
DA experiences and plans in Tunisia

ALADIN-HARMONIE/Norway and its assimilation system

Assimilation of the IASI data in the HARMONIE data assimilation system

SMHI activities on Data Assimilation for Numerical Weather Prediction

Progress on the CORE programme on DA

Improved structure functions for 3D VAR

Data Assimilation at CHMI

MAP Re-Analysis with IFS/ARPEGE/ALADIN

HIRLAM Regional 3D-VAR and MESAN downscaling re-analysis for the recent. 20 year period in the FP7 EURO4M project SMHI

Implementation of LM assimilation suite at MeteoSwiss

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2007

Swedish Meteorological and Hydrological Institute

Snow Analysis for Numerical Weather prediction at ECMWF

Assimilation of Cloud Affected Infrared Radiances in HIRLAM 4D Var

Assimilation of SEVIRI data II

Impact of an improved Backgrund-error covariance matrix with AROME 3Dvar system over Tunisia

Numerical Weather Prediction at high latitudes. Nils Gustafsson, SMHI

Overview of LACE data assimilation systems (with a certain regard) Contributions from many DA colleagues

Land Surface Data Assimilation

HIRLAM upper-air data assimilation

Accounting for non-gaussian observation error

Migration from TAC to BUFR for TEMP observations

The assimilation of AMSU-A radiances in the NWP model ALADIN. The Czech Hydrometeorological Institute Patrik Benáček 2011

IMPACT OF IASI DATA ON FORECASTING POLAR LOWS

Observation usage in Météo-France data assimilation systems

SLOVAKIA. Slovak Hydrometeorological Institute

Estimation of satellite observations bias correction for limited area model

SPECIAL PROJECT PROGRESS REPORT

Current Limited Area Applications

Bias Correction Issues in Limited Area Models: Strategy for HIRLAM

Bias correction of satellite data at Météo-France

The hybrid ETKF- Variational data assimilation scheme in HIRLAM

Assimilating Binary Cloud Cover Observations in Variational Data Assimilation Systems

Merging of the observation sources. Sami Saarinen, Niko Sokka. ECMWF, Reading/UK. Conventional data sources Merging process into the PREODB

Extending the use of surface-sensitive microwave channels in the ECMWF system

On the importance of land surface emissivity to assimilate low level humidity and temperature observations over land

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2007

Assimilation of Geostationary WV Radiances within the 4DVAR at ECMWF

Ninth Workshop on Meteorological Operational Systems. Timeliness and Impact of Observations in the CMC Global NWP system

Handling Biases in Surface Pressure (Ps) Observations in Data Assimilation

Progress Report. Data Manager Activity. Regional Cooperation for Limited Area Modeling in Central Europe. Prepared by: Period: Date:

Presentation of met.no s experience and expertise related to high resolution reanalysis

LAM-EPS activities in RC LACE

Introduction. Tilly Driesenaar

The satellite winds in the operational NWP system at Météo-France

Status report on DA for AROME-PT2. Maria Monteiro

Data assimilation in mesoscale modeling and numerical weather prediction Nils Gustafsson

Data impact studies in the global NWP model at Meteo-France

Numerical Weather prediction at the European Centre for Medium-Range Weather Forecasts

Re-analysis activities at SMHI

LAM-EPS activities in LACE

ASSIMILATION OF ATOVS RETRIEVALS AND AMSU-A RADIANCES AT THE ITALIAN WEATHER SERVICE: CURRENT STATUS AND PERSPECTIVES

Towards the assimilation of AIRS cloudy radiances

Latest developments and performances in ARPEGE and ALADIN-France

Hirlam implementations and ideas on RUC/RAP

Actual coordination activities within C-SRNWP

Changes in the Arpège 4D-VAR and LAM 3D-VAR. C. Fischer With contributions by P. Brousseau, G. Kerdraon, J.-F. Mahfouf, T.

Scatterometer winds in rapidly developing storms (SCARASTO) First experiments on data assimilation of scatterometer winds

Portugal. Instituto de Meteorologia

Recent experience at Météo-France on the assimilation of observations at high temporal frequency Cliquez pour modifier le style du titre

Satellite data assimilation for Numerical Weather Prediction (NWP)

Introduction to Data Assimilation. Saroja Polavarapu Meteorological Service of Canada University of Toronto

Overview of HIRLAM data assimilation activities On algorithmic developments and Use of Observations

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

CERA-SAT: A coupled reanalysis at higher resolution (WP1)

OSSE to infer the impact of Arctic AMVs extracted from highly elliptical orbit imagery

Radar data assimilation at met.no and OMSZ

HR-DDS and Pilot Wave Forecast Verification Scheme Extension. Interactive on-demand analysis David Poulter, National Oceanography Centre

Impact of combined AIRS and GPS- RO data in the new version of the Canadian global forecast model

General description of CANARI analysis software

LAM-EPS activities in RC LACE

Tour d ALADIN.

Performance and Application of Observation Sensitivity to Global Forecasts on the KMA Cray XE6

CANARI summer problem. Antonio Stanešić and Stjepan Ivatek-Šahdan

István Ihász, Hungarian Meteorological Service, Budapest, Hungary

Use and impact of ATOVS in the DMI-HIRLAM regional weather model

Harmonie suite at KNMI and future plans

Assimilation of IASI data at the Met Office. Fiona Hilton Nigel Atkinson ITSC-XVI, Angra dos Reis, Brazil 07/05/08

METinfo Verification of Operational Weather Prediction Models December 2017 to February 2018 Mariken Homleid and Frank Thomas Tveter

Use of satellite data in ALADIN HARMONIE/Norway

WRF 4D-Var The Weather Research and Forecasting model based 4-Dimensional Variational data assimilation system

METinfo Verification of Operational Weather Prediction Models June to August 2017 Mariken Homleid and Frank Thomas Tveter

The Nowcasting Demonstration Project for London 2012

Assimilating only surface pressure observations in 3D and 4DVAR

Technical Report on the Global Data Processing and Forecast System MAROC-METEO 2006 status

Convective Scale Data Assimilation and Nowcasting

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2006

Contents Introduction European wind proler data assimilation. HIRLAM variational data assimilation Processing of the EWP data....

Current and Future Experiments to Improve Assimilation of Surface Winds from Satellites in Global Models

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2007

Comparison of ensemble and NMC type of background error statistics for the ALADIN/HU model

Report on stay at ZAMG. IC and model perturbations for new ALADIN-LAEF

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2006

V A R P A C K. Ludovic Auger METEO-FRANCE / CNRM/ GMAP 42, av. G. Coriolis, Toulouse Cedex, France

Application of ALADIN/AROME at the Hungarian Meteorological Service

Data Short description Parameters to be used for analysis SYNOP. Surface observations by ships, oil rigs and moored buoys

OBSERVING SYSTEM EXPERIMENTS ON ATOVS ORBIT CONSTELLATIONS

Application and verification of ECMWF products 2009

Use of satellite soil moisture information for NowcastingShort Range NWP forecasts

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

Transcription:

Experiences with the ALADIN 3D VAR system Andrea Storto and Magnus Lindskog

WHAT WE HAVE DONE Set up of the ALADIN forecast model Computation of B matrix (NMC) Set up of the ALADIN 3DVAR system Support to BUFR format for conventional observations 1 obs experiments Started full (conventional) observations experiments (last week!)

TECHNICAL ASPECTS ASSIMILATION PLATFORM: ECMWF HPCE CYCLE: 30T1 CONFIGURATION: 1 processor, 1 ODB pool FORECAST PLATFORM: ECMWF HPCE CYCLE: 30T1 CONFIGURATION: 48 processors, 30 min for 48h forecast

Domain Configuration at (Forecast model) 11 km horizontal resolution, (270x405 nodes) and 40 vertical eta levels Domain centred over Norway, same as HIRLAM10 Static data (physiographic and climatological) from Météo France archive LBC and initial conditions from ECMWF analysis for the forecast model

Domain Configuration at SMHI (Forecast model) 60 vertical levels, smaller domain (256x288 nodes) Same resolution 11km LBC and initial conditions from ECMWF analysis for the forecast model

ALADIN 3DVAR overview, cycle 30T1 Conv. obs. Blacklist OBSOUL (conv. obs) Non conv. obs. First guess Coarse resol. B (GRIB) RTM coeffs OULAN Collecting the conv. obs. Write to ASCII (OBSOUL) Collecting non conv obs. BATORLAMFLAG Blacklisting, Init obs.errors Populating ODB ODB shuffle Obs. extraction SCREENING Quality check ODB compression First guess Background errors RTM coeffs MINIM ANALYSIS 3DVAR minimization

OBSERVATIONS FORMAT (CY30T1) EXPORT VERSION (Meteo France) OULAN BDM (French meteo database): conventional observations BATOR BUFR GRIB : AIRS, AMSU A, AMSU B, GEOWIND, QSCAT : SEVIRI WHICH IS THE BEST STRATEGY TO ASSIMILATE OBSERVATIONS IN BUFR FORMAT? (as from MARS or HIRLAM) NEW OULAN: added support to SYNOP, TEMP, PILOT, DRIBU in BUFR format Instead of using BUFR2ODB or CMA2ODB or similar Because of independence from cycle, and better observations check

BACKGROUND ERROR STATISTICS (Norway) NMC method using 36 12hr ALADIN forecast differences on 90 daily runs from 20051201 to 20060228. (Forecast initialized by ECMWF analysis) Coupling of divergence and balanced geopotential Mean vertical crosscovariance Mean vertical crosscovariance, scale 700 to 100 km Mean vertical crosscovariance, scale 100 to 10 km

BACKGROUND ERROR STATISTICS (Norway) Coupling of temperature and unbalanced divergence Mean vertical crosscovariance Mean vertical crosscovariance, scale 700 to 100 km Mean vertical crosscovariance, scale 100 to 10 km

BACKGROUND ERROR STATISTICS (Sweden) Coupling of temperature and unbalanced divergence Coupling of humidity and unbalanced divergence

1 observation EXPERIMENT Norwegian domain 1 temperature measurement (TEMP) at 850 mb, Innovation +6o C Analysis increment, temperature at 850 mb Analysis increment, cross section, temperature

1 observation EXPERIMENT Norwegian domain 1 temperature measurement (TEMP) at 850 mb, Innovation +6o C Analysis increment, wind at 850 mb Analysis increment, cross section, parallel wind intensity

1 observation EXPERIMENT Swedish domain 1 temperature measurement (TEMP) at 500 mb Analysis increment, temperature at 500 mb

PROBLEMS WITH SCREENING... Screening crashed because of the wrong counting of observations. There were some observations discarded by the domain check in the SCREENING task (OBATABS), even if accepted by LAMFLAG (domain check before ODB feeding) Norwegian domain has his central meridian parallel to the 40o meridian (very rotated domain) in order to be comparable to the HIRLAM10 model

PROBLEMS WITH SCREENING... The rough latitude check caused a crash (only obs whose latitude was > LAT1 15o and < LAT2+15o were taken). By using this domain, SYNOP obs in Svalbard Islands (>74o N) were not taken into account in SCREENING. For the

A FIRST 3DVAR EXPERIMENT Observations: SYNOP Pp TEMP T, q, u, v

A FIRST 3DVAR EXPERIMENT ANALYSIS INCREMENT MSLP

FUTURE PLANS SHORT TERM Cycling with SYNOP, SHIP, TEMP, PILOT Comparison of 3DVAR/ALADIN10 against ECMWF/ALADIN10 and HIRLAM20/HIRLAM10 Recomputation of B matrix Add support for EUROPROFILER and AMSDAR/AIREP LONG TERM Introduction of satellite data (?) Move to FGAT (?)

THANK YOU!