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

Similar documents
AVHRR Global Winds Product: Validation Report

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

AMVs in the operational ECMWF system

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

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

Current status and plans of JMA operational wind product

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

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

Monitoring and Assimilation of IASI Radiances at ECMWF

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

INTRODUCTION OF THE RECURSIVE FILTER FUNCTION IN MSG MPEF ENVIRONMENT

Dissemination of global products from Metop

AMVs in the ECMWF system:

VALIDATION OF DUAL-MODE METOP AMVS

ASCAT-B Level 2 Soil Moisture Validation Report

Atmospheric Motion Vectors: Product Guide

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

JMA s atmospheric motion vectors

CURRENT STATUS OF EUMETSAT OPERATIONAL WINDS. Ken Holmlund, R. Borde, M. Carranza, and O. Hautecoeur

onboard of Metop-A COSMIC Workshop 2009 Boulder, USA

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

GLOBAL ATMOSPHERIC MOTION VECTOR INTER-COMPARISON STUDY

Introducing Actions/Recommendations from CGMS to the 14th International Winds Workshop

Use of satellite winds at Deutscher Wetterdienst (DWD)

IASI L1 NRT data quality monitoring at EUMETSAT Lars Fiedler, Yakov Livschitz, Denis Blumstein, Eric Pequignot, Tim Hultberg and Francois Montagner

Scatterometer Wind Assimilation at the Met Office

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

The Polar Wind Product Suite

Generation and Initial Evaluation of a 27-Year Satellite-Derived Wind Data Set for the Polar Regions NNX09AJ39G. Final Report Ending November 2011

NWC-SAF Satellite Application Facility in Support to Nowcasting and Very Short Range Forecasting

Polar Multi-Sensor Aerosol Product: User Requirements

A New Atmospheric Motion Vector Intercomparison Study

AMVs in the ECMWF system:

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

- an Operational Radio Occultation System

GOES-16 AMV data evaluation and algorithm assessment

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

CURRENT STATUS OF OPERATIONAL WIND PRODUCT IN JMA/MSC

STATUS OF JAPANESE METEOROLOGICAL SATELLITES AND RECENT ACTIVITIES OF MSC

Characteristics of the POD System in the new EPS GRAS Product Processing Facility

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

EARS-ATMS, EARS-CrIS and EARS-VIIRS: Three New Regional Services

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

THE POLAR WIND PRODUCT SUITE

Dissemination of Global Products from EUMETSAT

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

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

Global Instability Index: Product Guide

Generation and assimilation of IASI level 2 products. Peter Schlüssel, Thomas August, Arlindo Arriaga, Tim Hultberg,

ASCAT mission overview and current developments

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

Does the ATOVS RARS Network Matter for Global NWP? Brett Candy, Nigel Atkinson & Stephen English

High Latitude Satellite Derived Winds from Combined Geostationary and Polar Orbiting Satellite Data

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

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

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

Reprocessed Satellite Data Products for Assimilation and Validation

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

R.C.BHATIA, P.N. Khanna and Sant Prasad India Meteorological Department, Lodi Road, New Delhi ABSTRACT

STATUS AND DEVELOPMENT OF SATELLITE WIND MONITORING BY THE NWP SAF

Assimilation of GNSS Radio Occultation Data at JMA. Hiromi Owada, Yoichi Hirahara and Masami Moriya Japan Meteorological Agency

Assessment of new AMV data in the ECMWF system: First year report

DESCRIPTION AND VALIDATION RESULTS OF THE HIGH RESOLUTION WIND PRODUCT FROM HRVIS MSG CHANNEL, AT EUMETSAT NOWCASTING SAF (SAFNWC)

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

IPETSUP The ESA Aeolus mission

Andrew Bailey (NOAA, Steve Wanzong (CIMSS/SSEC,

Current Status of COMS AMV in NMSC/KMA

GEOMETRIC CLOUD HEIGHTS FROM METEOSAT AND AVHRR. G. Garrett Campbell 1 and Kenneth Holmlund 2

MONITORING WEATHER AND CLIMATE FROM SPACE

Julia Figa-Saldaña & Klaus Scipal

EUMETSAT PLANS. Dr. K. Dieter Klaes EUMETSAT Am Kavalleriesand 31 D Darmstadt Germany

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

NWCSAF/High Resolution Winds AMV Software evolution between 2012 and 2014

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

JMA s ATMOSPHERIC MOTION VECTORS In response to Action 40.22

Status report on current and future satellite systems by EUMETSAT Presented to CGMS-44, Plenary session, agenda item D.1

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

REPROCESSING OF ATMOSPHERIC MOTION VECTORS FROM METEOSAT IMAGE DATA

ECMWF snow data assimilation: Use of snow cover products and In situ snow depth data for NWP

Instrument Calibration Issues: Geostationary Platforms

Status of EUMETSAT Current and Future Programmes

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

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

Polar winds from highly elliptical orbiting satellites: a new perspective

The ATOVS and AVHRR Product Processing Facility of EPS

Use of reprocessed AMVs in the ECMWF Interim Re-analysis

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

Impact of hyperspectral IR radiances on wind analyses

EUMETSAT STATUS AND PLANS

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

OSI SAF Sea Ice products

PRECONVECTIVE SOUNDING ANALYSIS USING IASI AND MSG- SEVIRI

EUMETSAT current and future plans on product generation and dissemination

Julia Figa-Saldaña. OVWST Meeting, May 2010, Barcelona Slide: 1

ASSESSING THE QUALITY OF HISTORICAL AVHRR POLAR WIND HEIGHT ASSIGNMENT

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

Cloud Top Height Product: Product Guide

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

AMVS: PAST PROGRESS, FUTURE CHALLENGES

Lessons learnt from EPS Cal/Val. F. Montagner & H. Bonekamp EUMETSAT

Transcription:

AVHRR Polar Winds Derivation at EUMETSAT: Current Status and Future Developments Gregory Dew and Régis Borde With assistance from: Marie Doutriaux-Boucher, Manuel Carranza

Contents 1. Background 2. Status at IWW10 Meeting in Tokyo 2010 3. Evolution since IWW10 4. Future Plans

Background METOP-A polar orbiting satellite launched October 2006 (operated by EUMETSAT) EUMETSAT derives winds from AVHRR instrument All Level 2 wind products processed in NRT using 3 minute (PDU) slices of image data For each target PDU map the 3 search PDUs in the previous orbit which overlap onto the target PDU Only use 2 orbits to produce the winds for each PDU

Background

Status at IWW10 Tokyo 2010 Tracking between pairs of images (current and previous orbit) Height Assignment - IR window - no low-level correction Use of forecast guided winds Single (complete) orbit dump of data at Svalbaard EUM Polar Winds disseminated between 90 and 110 minutes after sensing time

Evolution since IWW10 Demonstration dissemination (June 24 th 2010) Upgrades for full operational v1.5 EUMETCast and GTS (Jan 25 th 2011) Minor modifications (Feb 24 th 2011) Use of GRIB 2 forecast data (May 2011) Addition of McMurdo receiver station (June 2011) Ingestion of 3-hour forecast data (Nov 8 th 2011) Major new release v2.0 (Dec 13 th 2011)

Main Upgrades for Operational Version v1.5 Process winds at latitudes above and below 55/-55 degrees Use spanning forecast data sets instead of nearest match Increase wind density More meaningful representation of tracking and height QI Larger proportion of higher quality winds Lower departure statistics but still positive speed biases Distribution predominantly medium level (400 700 hpa) Full operational release via EUMETCast and GTS on January 25 th 2011

Animation IWW-11, Auckland, New Zealand, Feb 20th - 24th 2012!

Animation

Animation

Major New Release v2.0 Main Changes Use collocated cloud top heights derived from the Metop- A IASI instrument (CO2 slicing method), when available Use cross-correlation contribution (CCC) method to relate the pixels selected for height assignment to the tracking Add parallax correction Filter out any targets if any part of the search area lies outside the PDU processing area Use full-level, instead of half-level, ECMWF forecast coefficients to apply to ECMWF forecast data

Validation - Arctic QI > 80 Low Level (>=700 hpa) Mid Level (700-400 hpa) High Level (<=400 hpa) All Levels OLD NEW OLD NEW OLD NEW OLD NEW Speed Bias (m/s) 1.81 1.21 1.91 1.18 0.57 1.14 1.82 1.14 Speed RMS (m/s) 4.06 3.57 4.54 3.98 5.45 4.28 4.43 3.91 DirecPon Bias (deg) 0.44 2.51 0.66 0.49 2.26-0.86 0.63 0.86 DirecPon RMS (deg) 16.00 18.41 12.77 13.75 10.96 10.04 13.83 14.70 Mean Spd AMV 16.64 15.43 21.62 20.21 29.23 26.51 20.33 19.53 Mean Spd Analysis 14.83 14.22 19.71 19.10 28.66 25.38 18.51 18.39 NRMS 0.27 0.25 0.23 0.21 0.19 0.17 0.24 0.21 Sample size 3002 2111 5909 5754 393 685 9268 8508 % of Winds 32 25 64 67 4 8 100 100 5 day period May 2011 : 060000Z and 120000Z 6 hour forecast

Validation - Antarctic QI > 80 Low Level (>=700 hpa) Mid Level (700-400 hpa) High Level (<=400 hpa) All Levels OLD NEW OLD NEW OLD NEW OLD NEW Speed Bias (m/s) 1.93 1.32 1.43 0.97-0.19 0.40 1.09 0.75 Speed RMS (m/s) 4.24 3.74 5.09 4.62 5.25 4.78 5.05 4.63 DirecPon Bias (deg) - 0.71-1.82 0.18 0.01-0.15 1.00 0.01 0.32 DirecPon RMS (deg) 12.81 11.31 13.96 15.50 14.55 17.12 14.00 15.98 Mean Spd AMV 18.42 17.82 24.72 23.68 27.81 28.53 24.82 25.37 Mean Spd Analysis 16.49 16.50 23.29 22.71 28.09 28.13 23.73 24.61 NRMS 0.26 0.23 0.22 0.20 0.19 0.17 0.21 0.19 Sample size 953 398 6554 2869 2237 2468 9714 5718 % of Winds 10 7 67 50 23 43 100 100 5 day period May 2011 : 060000Z and 120000Z 6 hour forecast

Validation ARCTIC Levels QI > 80 All ANTARCTIC Levels QI > 80 OLD NEW OLD NEW All Speed Bias (m/s) 1.14 0.75 2.57 1.58 Speed RMS (m/s) 5.62 4.81 5.58 4.26 DirecPon Bias (deg) 0.30-0.51-4.69 0.04 DirecPon RMS (deg) 14.95 28.20 19.28 14.55 Mean Spd AMV 26.11 25.04 23.36 20.68 Mean Spd Analysis 24.97 24.50 20.80 19.10 NRMS 0.23 0.20 0.27 0.22 Sample size 3080 2526 2511 2112 3 day period Nov 2011 : 060000Z and 120000Z 3 hour forecast

Validation v2.0 Summary Reduction of winds - filtering out of targets with incomplete search areas Heights shifted slightly upwards in the atmosphere - helped to reduce the fast wind bias Still a general fast speed bias Speed departure statistics are lower for NEW PPF Direction departure statistics are more variable

Validation Use of IASI Heights ARCTIC All Heights Mid Level QI > 80 IASI Heights All Heights High Level QI > 80 IASI Heights Speed Bias (m/s) 1.18 1.22 1.14 1.14 Speed RMS (m/s) 3.98 4.08 4.28 4.28 DirecPon Bias (deg) 0.49 0.10-0.86-0.86 DirecPon RMS (deg) 13.75 12.14 10.04 10.04 Mean Spd AMV 20.21 20.81 26.51 26.51 Mean Spd Analysis 19.10 19.59 25.37 25.37 NRMS 0.21 0.21 0.17 0.17 Sample size 5754 4111 685 685 ANTARCTIC All Heights Mid Level QI > 80 IASI Heights All Heights High Level QI > 80 IASI Heights Speed Bias (m/s) 0.97 0.97 0.40 0.37 Speed RMS (m/s) 4.62 4.67 4.78 4.81 DirecPon Bias (deg) 0.01-0.07 1.00 0.88 DirecPon RMS (deg) 15.50 11.54 17.12 11.56 Mean Spd AMV 23.68 24.66 28.53 29.58 Mean Spd Analysis 22.71 23.68 28.13 29.21 NRMS 0.20 0.20 0.17 0.16 Sample size 2869 2496 2468 2197 5 day period May 2011 : 060000Z and 120000Z 6 hour forecast data Arctic, IASI height assignment has been applied for 69% of the medium level winds and 99% of the high level winds. Antarctic, IASI height assignment has been applied for 79% of the medium level winds and 72% of the high level winds

Validation Use of IASI Heights ARCTIC All Levels QI > 80 ANTARCTIC All Levels QI > 80 OLD NEW All NEW IASI OLD NEW All NEW IASI Speed Bias (m/s) 1.14 0.75 0.80 2.57 1.58 1.72 Speed RMS (m/s) 5.62 4.81 5.11 5.58 4.26 4.53 DirecPon Bias (deg) 0.30-0.51-1.91-4.69 0.04-0.06 DirecPon RMS (deg) 14.95 28.20 15.71 19.28 14.55 11.15 NRMS 0.23 0.20 0.16 0.27 0.22 0.22 3 day period Nov 2011 : 060000Z and 120000Z 3 hour forecast data Use of IASI co-located heights improves wind quality

Validation Use of IASI Heights

Validation Parallax Correction and Satellite Zenith Angle Parallax correction - no impact on wind departure statistics Satellite zenith angle - no speed bias and direction bias dependency - speed and direction RMS dependency ( > 45 deg) - investigate further using long-term monitoring statistics (eg ECMWF, Met Office)

Validation Timeliness OLD PPF the worst timeliness was typically 70 mins for two receiver station scenario NEW PPF the worst timeliness is generally either 80 mins or occasionally 140 minutes Within the 180 minute bench-mark level even for one receiver station scenario

Status Now Version 2.0 replaced Version 1.5 on Dec 13 th 2011 Operational dissemination on EUMETCast and GTS When available both IASI (CO2 slicing method) and IR window heights for each wind written to BUFR product Feedback welcomed from users: ECMWF, Met Office - IASI height assignment impact - satellite zenith angle dependency

Future Plans Metop B launch May 2012 Metop A/B images Next software release incorporate dual Metop processing capability, scheduled mid-2012 Handling of low level heights, inc. inversions - use Concordiasi drop-sonde Antarctic data set Correlation surface peak analysis Consider triplets (at least for consistency tests)

Use of Metop A and B Capability Tracking 50 minutes separation Increased global coverage EPS GS product processor configuration - Metop A single mode, ie as current operational - Metop B single mode - dual mode combining Metop A and B images Validation - use of co-located MSG winds Validation - external users 3 sets of parallel data

THAT S ALL FOLKS!