Régis Borde (regis.borde@eumetsat.int) Polar Winds EUMETRAIN Polar satellite week 2012 Régis Borde (regis.borde@eumetsat.int)

After the Wind Workshop North Cape, NZ After the Wind Workshop Feb 2012 Content Wind extraction from satellite imagery Polar winds

Content Wind extraction from satellite imagery Polar winds at EUMETSAT

Why do we care about winds from satellites? For best results, models require information on both the mass field and the wind field. AMVs are the only observation type to provide good coverage of upper tropospheric wind data over oceans and at high latitudes. Sondes and wind profilers Aircraft For the AMVs each dot represents a single level wind not a wind profile AMVs

Atmospheric Motion Vectors AMV production centres: EUMETSAT NOAA-NESDIS CIMSS JMA CMA KMA AMVs from Geo. Sat.: Meteosat 7, 8 and 9 GOES 13, 15 FY2E MTSAT-2 AMVs from Polar Sat.: Metop-A (AVHRR) Terra, Aqua (MODIS) NOAA- 15, 16, 18 and 19 (AVHRR)

Polar winds Why doing polar winds ? Assimilation at ECMWF in 2002 12-h sample coverage: used AMVs at ECMWF in 2012 GOES-13 MET-9 MET-7 MTSAT-2 TERRA AQUA GOES-15 AMVs under evaluation since December 2011 Lack of observations in Polar regions

Polar winds How doing polar winds ? Needs: Low orbit polar satellites: NPP, METOP... Appropriate instruments: MODIS, AVHRR, VIIRS. But some new challenges: Large timeliness (~100 min) Small areas to track features Problems of view angles, parallax and varying pixels sizes No cloudy product (AVHRR) Polar region specificities like ground colder to air above ...

Polar winds Product history Courtesy of Dave Santek, CIMSS

Courtesy of Dave Santek, CIMSS Unlike geostationary satellites at lower latitudes, it is not be possible to obtain complete polar coverage at a snapshot in time with one or two polar-orbiters. Instead, winds must be derived for areas that are covered by two or three successive orbits, an example of which is shown here. The gray area is the overlap between three orbits.

One Day of Arctic Orbits Courtesy of Dave Santek, CIMSS MODIS band 31 (11 mm)

EUMETSAT Atmospheric Motion Vectors Algorithm description Target selection Tracking Height assignment Automatic quality control Extraction of the motion (speed, direction) Selection of the pixels used to set the altitude Height Assignment QI

Two main assumptions and ’limitations’ EUMETSAT Atmospheric Motion Vectors Physical assumptions and limitations Two main assumptions and ’limitations’ Feature tracked travels at the exactly same speed and direction than the local wind. Detected motion represents the ‘cloud top’ motion. Then CTH methods are used to set the altitude

Extraction of AMV speed and direction Target identification and tracking Initial corrections (image navigation etc.) Search Area 80 x 80 pixels centred on target box Target Box / Tracer 24x24 pixels Pixel – 3 km New location determined by best match of individual pixel counts of target with all possible locations of target in search area. T T + 15 min Infrared Imagery Need to assign a height to the derived vector

AMV Height Assignment Opaque clouds, EBBT B: Energy emitted T: Blackbody temperature k: Boltzmann‘s constant h: Planck‘s constant c: speed of light l: wavelenght

Pc AMV Height Assignment Best fit Semi-transparent clouds, CO2 slicing method Best fit Rcd : Measured cloudy radiance Rcf : Measured cloud free radiance Rbcd : Calculated Planck blackbody radiance for a cloud at level Pc Rsuf : Calculated clear air radiance e : Emissivities Pc

AMV Quality check Several independent quality test applied Forecast consistency Spatial consistency Temporal consistency (vector, speed, direction) Temporal pressure consistency Image correlation (WV 6.2 / IR 10.8) Final quality index (QI) Weighted mean of the individual tests

AMV Quality check Example of Spatial consistency red wind vector would not pass the spatial consistency test, it would therefore get a low quality indicator (in a range from 0 to 1)

How check the quality of AMVs ? DU Speed bias FC Speed at AMV pressure level AMV pressure DP Best Fit level pressure AMV AMV Speed

Collocation AMV / RS RS altitude RadioSonde AMV altitude AMV Pressure 150 km RadioSonde RS altitude AMV altitude 50 hPa AMV Pressure 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) Longitude Latitude

EUMETSAT Polar winds Image pairs or triplet ? increase the coverage loose temporal quality checks between derived vectors

EUMETSAT Polar winds Image pairs or triplet ? Example for retrieved polar cap winds for the Arctic on 19 January 2010.

EUMETSAT Polar winds How to set the AMV heights with AVHRR ? Main problems: No WV or CO2 channels on AVHRR No cloudy product Then... Use IR window channel (EBBT method) for opaque clouds No clean solution for semi-transparent clouds Possibility to use low-level correction from model fields

EUMETSAT Polar winds Opportunity to use IASI heights 24x24 AVHRR pixels 24x24 AVHRR pixels target boxes IASI foot print sometimes in the box, sometimes not. Collocation IASI foot print /feature tracked

EUMETSAT Polar winds Use of IASI heights, Validation 3 day period Nov 2011 : 060000Z and 120000Z 3 hour forecast data Use of IASI co-located heights improves a bit wind quality ARCTIC All Levels QI > 80 ANTARCTIC All Levels OLD NEW All 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 Direction Bias (deg) 0.30 -0.51 -1.91 -4.69 0.04 -0.06 Direction 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

from initial target box EUMETSAT Polar winds Necessity to use the first guess ! Altitude estimated from initial target box Main problems: Timeliness between consecutives images is very long, which makes the tracking difficult and noisy. This problem is emphasised when using only pair of images Use of the first guess improves the results, but: Needs to estimate the altitude first Refers to the model fields Source of potential errors if first estimation of altitude is wrong Speed retrieved in the model fields that is then used to locate the search area

FORECAST FIRST GUESS (GS2) FORECAST FIRST GUESS (GS2) EUMETSAT Polar winds Use of first guess, Validation PROTOTYPE FORECAST FIRST GUESS (GS2) NO FORECAST (GS3) Speed Bias (m/s) -1.21 0.87 -1.45 Speed RMS (m/s) 2.67 4.50 8.21 Direction Bias (deg) 1.00 0.45 5.05 Direction RMS (deg) 8.60 15.65 59.40 Mean Speed AMV 19.47 21.52 16.90 Mean Speed Analysis 20.69 20.65 18.35 Sample size 3988 970 1035 Statistics for Arctic winds Data of 19th January 2010, 12:00 UTC PROTOTYPE FORECAST FIRST GUESS (GS2) NO FORECAST (GS3) Speed Bias (m/s) -0.10 1.72 -0.02 Speed RMS (m/s) 2.01 3.97 5.30 Direction Bias (deg) 0.54 2.25 11.39 Direction RMS (deg) 13.33 38.45 66.91 Mean Speed AMV 14.69 12.83 7.65 Mean Speed Analysis 14.79 11.11 7.66 Sample size 1503 393 947 Statistics for Antarctic winds

5 day period May 2011 : 060000Z and 120000Z 6 hour forecast EUMETSAT Polar winds Validation against ECMWF analysis - Arctic QI > 80 Low Level (>=700 hPa) Mid Level (700-400 hPa) High Level (<=400 hPa) All Levels OLD NEW Speed Bias (m/s) 1.81 1.21 1.91 1.18 0.57 1.14 1.82 Speed RMS (m/s) 4.06 3.57 4.54 3.98 5.45 4.28 4.43 3.91 Direction Bias (deg) 0.44 2.51 0.66 0.49 2.26 -0.86 0.63 0.86 Direction RMS (deg) 16.00 18.41 12.77 13.75 10.96 10.04 13.83 14.70 Mean Speed AMV 16.64 15.43 21.62 20.21 29.23 26.51 20.33 19.53 Mean Speed 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 Sample size 3002 2111 5909 5754 393 685 9268 8508 % of Winds 32 25 64 67 4 8 100 5 day period May 2011 : 060000Z and 120000Z 6 hour forecast

5 day period May 2011 : 060000Z and 120000Z 6 hour forecast EUMETSAT Polar winds Validation against ECMWF analysis - Antarctic QI > 80 Low Level (>=700 hPa) Mid Level (700-400 hPa) High Level (<=400 hPa) All Levels 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 Direction Bias (deg) -0.71 -1.82 0.18 0.01 -0.15 1.00 0.32 Direction RMS (deg) 12.81 11.31 13.96 15.50 14.55 17.12 14.00 15.98 Mean Speed AMV 18.42 17.82 24.72 23.68 27.81 28.53 24.82 25.37 Mean Speed 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 Sample size 953 398 6554 2869 2237 2468 9714 5718 % of Winds 10 7 67 50 23 43 100 5 day period May 2011 : 060000Z and 120000Z 6 hour forecast

Polar winds EUMETSAT product from AVHRR, summary Current status AVHRR L1B IR-Window images from channel 4 (11µm) For METOP-AVHRR full spatial resolution Local Area Coverage (LAC) data are available globally Use image pairs Use IASI heights when possible Use first guess to locate search area for tracking Future Use triplet of images for METOP A and METOP B Derive dual METOP winds (global coverage)

Polar winds Example of EUMETSAT AVHRR winds

AMV Impact on FC 24 h ‘Forecast Error Contribution’ sliced by specific AMVs observations, June 2011 (C. Cardinali, ECMWF) Impact of different AMV products from MODIS, Meteosat-7, -8, -9, GOES-11, -12

AMV Impact on FC 24 h ‘Forecast Error Contribution’ of the AMVs by instrument and for altitude intervals, June 2011 (C. Cardinali, ECMWF) Impact of AMVs from MODIS, Meteosat-7, -9, GOES-11, -12 sliced by pressure intervals

Thank You Regis.borde@eumetsat.int