IMPROVEMENTS TO EUMETSAT AMVS. Régis Borde, Greg Dew, Arthur de Smet and Jörgen Bertil Gustaffson

Similar documents
OPERATIONAL RETRIEVAL OF MSG AMVS USING THE NEW CCC METHOD FOR HEIGHT ASSIGNMENT.

AN OVERVIEW OF 10 YEARS OF RESEARCH ACTIVITIES ON AMVs AT EUMETSAT

GLOBAL ATMOSPHERIC MOTION VECTOR INTER-COMPARISON STUDY

ATMOSPHERIC MOTION VECTORS DERIVED FROM MSG RAPID SCANNING SERVICE DATA AT EUMETSAT

Recent Changes in the Derivation of Geostationary AMVs at EUMETSAT. Manuel Carranza Régis Borde Marie Doutriaux-Boucher

RECENT UPGRADES OF AND ACTIVITIES FOR ATMOSPHERIC MOTION VECTORS AT JMA/MSC

A New Atmospheric Motion Vector Intercomparison Study

JMA s ATMOSPHERIC MOTION VECTORS In response to Action 40.22

GENERATION OF HIMAWARI-8 AMVs USING THE FUTURE MTG AMV PROCESSOR

AMVs in the ECMWF system:

Current status and plans of JMA operational wind product

INTRODUCTION OF THE RECURSIVE FILTER FUNCTION IN MSG MPEF ENVIRONMENT

Reprocessed Satellite Data Products for Assimilation and Validation

CGMS 36 is invited to discuss the outcome and recommendations from the 9 th International Winds Workshop.

TOWARDS IMPROVED HEIGHT ASSIGNMENT AND QUALITY CONTROL OF AMVS IN MET OFFICE NWP

AVHRR Polar Winds Derivation at EUMETSAT: Current Status and Future Developments

COMPARISON OF AMV CLOUD TOP PRESSURE DERIVED FROM MSG WITH SPACE BASED LIDAR OBSERVATIONS (CALIPSO)

CLOUD TOP, CLOUD CENTRE, CLOUD LAYER WHERE TO PLACE AMVs?

REPROCESSING OF ATMOSPHERIC MOTION VECTORS FROM METEOSAT IMAGE DATA

ACCOUNTING FOR THE SITUATION-DEPENDENCE OF THE AMV OBSERVATION ERROR IN THE ECMWF SYSTEM

COMPARISON OF THE OPTIMAL CLOUD ANALYSIS PRODUCT (OCA) AND THE GOES-R ABI CLOUD HEIGHT ALGORITHM (ACHA) CLOUD TOP PRESSURES FOR AMVS

VALIDATION OF DUAL-MODE METOP AMVS

JMA s atmospheric motion vectors

MSG Indian Ocean Data Coverage (IODC) Jochen Grandell & Sauli Joro

Use of satellite winds at Deutscher Wetterdienst (DWD)

AMVs in the operational ECMWF system

WHAT CAN WE LEARN FROM THE NWP SAF ATMOSPHERIC MOTION VECTOR MONITORING?

Maryland 20746, U.S.A. Engineering Center (SSEC), University of Wisconsin Madison, Wisconsin 53706, U.S.A ABSTRACT

Wind tracing from SEVIRI clear and overcast radiance assimilation

NWP SAF AMV monitoring: the 7th Analysis Report (AR7)

RECENT ADVANCES TO EXPERIMENTAL GMS ATMOSPHERIC MOTION VECTOR PROCESSING SYSTEM AT MSC/JMA

GOES-16 AMV data evaluation and algorithm assessment

Atmospheric Motion Vectors: Product Guide

Tracer quality identifiers for accurate Cloud Motion Wind

CURRENT STATUS OF THE EUMETSAT METEOSAT-8 ATMOSPHERIC MOTION VECTOR QUALITY CONTROL SYSTEM

Use of reprocessed AMVs in the ECMWF Interim Re-analysis

USE, QUALITY CONTROL AND MONITORING OF SATELLITE WINDS AT UKMO. Pauline Butterworth. Meteorological Office, London Rd, Bracknell RG12 2SZ, UK ABSTRACT

AMVs in the ECMWF system:

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

Niels Bormann, Graeme Kelly, and Jean-Noël Thépaut

STATUS AND DEVELOPMENT OF SATELLITE WIND MONITORING BY THE NWP SAF

Assimilation of Geostationary WV Radiances within the 4DVAR at ECMWF

Instrument Calibration Issues: Geostationary Platforms

Masahiro Kazumori, Takashi Kadowaki Numerical Prediction Division Japan Meteorological Agency

NESDIS Atmospheric Motion Vector (AMV) Nested Tracking Algorithm: Exploring its Performance

HIGH SPATIAL AND TEMPORAL RESOLUTION ATMOSPHERIC MOTION VECTORS GENERATION, ERROR CHARACTERIZATION AND ASSIMILATION

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

NUMERICAL EXPERIMENTS USING CLOUD MOTION WINDS AT ECMWF GRAEME KELLY. ECMWF, Shinfield Park, Reading ABSTRACT

EXPERIENCE IN THE HEIGHT ATTRIBUTION OF PURE WATER VAPOUR STRUCTURE DISPLACEMENT VECTORS

NWP SAF AMV monitoring: the 8th Analysis Report (AR8)

STATUS AND DEVELOPMENT OF OPERATIONAL METEOSAT WIND PRODUCTS. Mikael Rattenborg. EUMETSAT, Am Kavalleriesand 31, D Darmstadt, Germany ABSTRACT

THE ATMOSPHERIC MOTION VECTOR RETRIEVAL SCHEME FOR METEOSAT SECOND GENERATION. Kenneth Holmlund. EUMETSAT Am Kavalleriesand Darmstadt Germany

Ninth International Winds Workshop (9IWW)

COMPARISON OF AMV HEIGHT ASSIGNMENT BIAS ESTIMATES FROM MODEL BEST-FIT PRESSURE AND LIDAR CORRECTIONS

AVHRR Global Winds Product: Validation Report

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

AN OBSERVING SYSTEM EXPERIMENT OF MTSAT RAPID SCAN AMV USING JMA MESO-SCALE OPERATIONAL NWP SYSTEM

Assessment of a new quality control technique in the retrieval of atmospheric motion vectors

Current Status of COMS AMV in NMSC/KMA

Assimilation of GOES Hourly and Meteosat winds in the NCEP Global Forecast System (GFS)

Assimilation of Himawari-8 data into JMA s NWP systems

Assimilation of Himawari-8 Atmospheric Motion Vectors into the Numerical Weather Prediction Systems of Japan Meteorological Agency

SEVIRI - Cloud Top Height Factsheet

ASSESSING THE QUALITY OF HISTORICAL AVHRR POLAR WIND HEIGHT ASSIGNMENT

PRECONVECTIVE SOUNDING ANALYSIS USING IASI AND MSG- SEVIRI

EVALUATION OF TWO AMV POLAR WINDS RETRIEVAL ALGORITHMS USING FIVE YEARS OF REPROCESSED DATA

IMPACTS OF SPATIAL OBSERVATION ERROR CORRELATION IN ATMOSPHERIC MOTION VECTORS ON DATA ASSIMILATION

Meteorological product extraction: Making use of MSG imagery

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

IMPACT STUDIES OF AMVS AND SCATTEROMETER WINDS IN JMA GLOBAL OPERATIONAL NWP SYSTEM

Use of DFS to estimate observation impact in NWP. Comparison of observation impact derived from OSEs and DFS. Cristina Lupu

Observing system experiments of MTSAT-2 Rapid Scan Atmospheric Motion Vector for T-PARC 2008 using the JMA operational NWP system

MODIS- and AVHRR-derived Polar Winds Experiments using the NCEP GDAS/GFS NA10NES

Polar winds from highly elliptical orbiting satellites: a new perspective

The Contribution of Locally Generated MTSat-1R Atmospheric Motion Vectors to Operational Meteorology in the Australian Region

Atmospheric motion vector retrieval using improved tracer selection algorithm

Towards the assimilation of AIRS cloudy radiances

Atmospheric Motion Vectors from Kalpana-1: An ISRO status

An Evaluation of FY-3C MWHS-2 and its potential to improve forecast accuracy at ECMWF

COMPARISON OF VERIFICATION TECHNIQUES, IS IT TIME FOR CONVERGENCE? DR. DONALD E. HINSMAN Senior Scientific Officer Satellite Activities Office

Cloud Top Height Product: Product Guide

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

STATUS ON THE USE OF SCATTEROMETER DATA AT METEO FRANCE

Introducing Atmospheric Motion Vectors Derived from the GOES-16 Advanced Baseline Imager (ABI)

IMPROVEMENTS IN FORECASTS AT THE MET OFFICE THROUGH REDUCED WEIGHTS FOR SATELLITE WINDS. P. Butterworth, S. English, F. Hilton and K.

ESTIMATION OF THE SEA SURFACE WIND IN THE VICINITY OF TYPHOON USING HIMAWARI-8 LOW-LEVEL AMVS

DERIVING ATMOSPHERIC MOTION VECTORS FROM AIRS MOISTURE RETRIEVAL DATA

Assimilating only surface pressure observations in 3D and 4DVAR

Which AMVs for which model? Chairs: Mary Forsythe, Roger Randriamampianina IWW14, 24 April 2018

Rosemary Munro*, Graeme Kelly, Michael Rohn* and Roger Saunders

Cloud Top Height Product: Product Guide

Feature-tracked 3D Winds from Satellite Sounders: Derivation and Impact in Global Models

Reanalysis applications of GPS radio occultation measurements

by Howard Berger University of Wisconsin-CIMSS NWP SAF visiting scientist at the Met Office, UK

ALGORITHM AND SOFTWARE DEVELOPMENT OF ATMOSPHERIC MOTION VECTOR (AMV) PRODUCTS FOR THE FUTURE GOES-R ADVANCED BASELINE IMAGER (ABI)

ERA-CLIM2-WP3: Satellite data reprocessing and inter-calibration

The JRA-55 Reanalysis: quality control and reprocessing of observational data

Assimilation of hyperspectral infrared sounder radiances in the French global numerical weather prediction ARPEGE model

Atmospheric Motion Vectors: Past, Present and Future

STATUS OF JAPANESE METEOROLOGICAL SATELLITES AND RECENT ACTIVITIES OF MSC

Transcription:

IMPROVEMENTS TO EUMETSAT AMVS Régis Borde, Greg Dew, Arthur de Smet and Jörgen Bertil Gustaffson

BACKGROUND Create a direct link between feature tracked and Height Assignment of AMV. References: Borde R., and R. Oyama, (2008), A Direct Link between Feature Tracking and Height Assignment of Operational Atmospheric Motion Vectors, Ninth Int. Winds Workshop, Annapolis, USA. Oyama, R., R. Borde J. Schmetz and T. Kurino (2008), Development of AMV height assignment directly linked to feature tracking at JMA, Ninth Int. Winds Workshop, Annapolis, USA. Borde R., A., De Smet and G. Dew, (2008), Better Better use of correlation information in AMV extraction scheme,, EUMETSAT conference, Darmstadt, Germany

Description of CCij graphs Average contribution <CC Cloudy ij > Clear sky Clear sky ST clouds Low level Fractional Cloud edges Cloud tops Opaque Highest

Calculation of CCij weighted pressure and STD from CLA-CTH P = cold _ branch CC > CC i, j CC i, j i, j. CLA _ cold _ branch CC > CC i, j CC i, j i, j CTH i, j

Example: Few coldest pixels contribute

Operational Tests Configuration - Period 1 from 24 December 2008 00:00 UTC to 21 January 2009 00:00 UTC - Period 2 from 22 January 2009 00:00 UTC to 18 February 2009 00:00 UTC OPE : Usual operational code - Image enhancement switched on - Operational CLA-CTH (period 1) ; CO2 slicing method (period 2) - Use of histogram analysis as pixel selection method for HA New : Test new scheme - Image enhancement switched off - Use of CCij weighted pressure Test Image Enhancement Pixel selection scheme CLA-CTH Parameter Period 1 Period 2 OPE On Current Current OPE Current OPE OPE_noIE Off Current Current OPE CO2 slicing New Off New Current OPE CO2 slicing

AMVs (QI > 80) with FC test; IR10.8

AMVs (QI > 80) with FC test; IR10.8 Relative increase of AMVs with QI with FC-consistency > 80) (New OPE) / OPE (in %) Period 1 Period 2 All levels 10 17 IR-10.8 High levels -3 23 Mid Levels 102 48 Low levels 11 8 VIS-0.8 4 4 HRV 5 3 Relative increase of good AMVs (QI with FC-consistency > 80) using IE (in %) (OPE_noIE OPE) / OPE (OPE_noIE - New) / New Period 1 Period 2 Period 1 Period 2 IR-10.8 All levels 14 8 3-8 High levels 15 6 18-13 Mid Levels 24 30-38 -12 Low levels 12 7 1-1

Comparison against Radiosonde Observations CGMS Reference HOR. DIST. < 150 (Km) - VERT. DIST. < 25 (hpa) QUALITY (Without FC test) >= 80 SPEED DIFF. < 30 (m/s) - DIRECTION DIFF. < 60 (deg) AMV SPEED > 2.5 (m/s)

NEW versus OPE Period 1 Speed Biases

NEW versus OPE Period 2 Speed Biases

NEW versus OPE_noIE Period 1 Speed Biases

NEW versus OPE_noIE Period 2 Speed Biases

NEW versus OPE AMV / RS RMS AMV / RS RMS New (OPE) (in m/s) Period 1 Period 2 Global NH SH TR Global NH SH TR IR-10.8 All levels 7.75 (7.58) 7.99 (7.87) 8.05 (7.44) 7.13 (7.09) 8.31 (7.74) 8.90 (8.33) 7.23 (6.61) 6.61 (6.31) High levels 8.47 (8.12) 9.16 (8.57) 8.52 (7.89) 7.52 (7.61) 8.75 (8.16) 9.55 (8.91) 7.36 (6.89) 6.86 (6.83) Mid Levels 7.83 (7.80) 7.76 (8.03) 7.41 (6.03) 8.68 (4.47) 8.44 (7.96) 8.44 (8.12) 8.34 (5.50) 8.43 (5.71) Low levels 4.99 (4.57) 5.36 (4.97) 5.49 (4.52) 3.36 (3.42) 5.49 (4.92) 5.93 (5.47) 5.49 (4.89) 3.21 (3.37) VIS 0.8 4.65 (4.21) 5.22 (4.64) 3.84 (3.98) 3.40 (3.43) 5.13 (4.40) 5.80 (5.02) 4.67 (3.98) 3.29 (3.44) HRV 5.12 (4.58) 5.20 (4.68) 4.74 (3.39) 3.29 (-3.12) 5.54 (5.00) 5.65 (5.10) 4.69 (5.44) 2.56 (2.89)

Conclusions on Operational Tests Results very dependant on CLA-CTH. New scheme gives more good AMVs (QI >80). Slow bias and RMS at high levels a bit degraded but estimated on a larger data set of good collocations AMVs / RS dataset with new scheme. Assimilation test at ECMWF gave mainly a neutral impact on FC (See Iliana Genkova s talk).

Prospectives Use this method together with the future OCA product (Watts et al, 1998). Estimate and test the potential use of weighted pressure STD (in hpa) in assimilation. It gives an information on the variability within the group of pixels used for HA. OCA product also allows to get an information about the reliability of the HA retrieval. Opportunity to estimate quality information for HA based on these two informations

Preliminary results using OCA A way towards concrete AMV Height Error R. Borde Thanks to Phil Watts for help on OCA product

Comparisons OCA-CTH versus CLA-CTH 03/08/2006 12h45 UTC Meteosat-8

Comparisons OCA-CTH versus CLA-CTH 03/08/2006 ; 12h45 UTC ; Meteosat-8

Comparisons AMV-OCA versus AMV-CLA 03/08/2006 ; 12h45 UTC ; Meteosat-8 JM < 80 AMV Pressure histograms Scatter plot P oca versus P cla

Comparisons AMV-OCA versus AMV-CLA 03/08/2006 ; 12h45 UTC ; Meteosat-8 JM < 80 Pressure STD histograms Nb pixels used for HA

THANKS