DERIVED MOTION FIELDS from the GOES SATELLITES

March 9, 1999 Comet Class: SatMet 99-1 1

DERIVED MOTION FIELDS from the DERIVED MOTION FIELDS from the GOES SATELLITESGOES SATELLITES

Jaime DanielsJaime DanielsNOAA/NESDISNOAA/NESDIS

Office of Research and ApplicationsOffice of Research and ApplicationsForecast Products Development TeamForecast Products Development Team

andandDonald G. GrayDonald G. GrayNOAA/NESDISNOAA/NESDIS

GOES Products ManagerGOES Products ManagerOffice of Systems DevelopmentOffice of Systems Development


Satellite Derived Motion Fields:Satellite Derived Motion Fields:TOPICSTOPICS

PhilosophyPhilosophy Review of GOES visible, IR, WV channelsReview of GOES visible, IR, WV channels Basic methodologyBasic methodology GOES-Next optimized data processing GOES-Next optimized data processing

strategiesstrategies GOES wind products - What’s new ?GOES wind products - What’s new ? VerificationVerification


Satellite Derived Motion Fields:Satellite Derived Motion Fields:TOPICS cont’dTOPICS cont’d

Current and new/planned applicationsCurrent and new/planned applications SummarySummary Product availability and recommended Product availability and recommended

readingreading Discussion/questionsDiscussion/questions


Satellite Derived Motion Fields:PHILOSOPHY

Clouds are “passive” tracers of winds at a Clouds are “passive” tracers of winds at a single levelsingle level– use infrared and visible radiancesuse infrared and visible radiances

Water vapor features (ie., moisture Water vapor features (ie., moisture gradients are “passive” tracers of winds)gradients are “passive” tracers of winds)– both in clear air and cloudy conditionsboth in clear air and cloudy conditions– use water vapor infrared radiancesuse water vapor infrared radiances

We can properly assign height of tracerWe can properly assign height of tracer


Satellite Derived Motion Fields:GOES Visible, IR, WV

Channels ImagerImager

– Water vapor channel (6.7um) Water vapor channel (6.7um) Band 3Band 3– Longwave IR window chan. (10.7um) Longwave IR window chan. (10.7um) Band 4Band 4– Visible Channel (0.65um) Visible Channel (0.65um) Band 1Band 1

SounderSounder– Water vapor channel (7.3um) Water vapor channel (7.3um) Band 10Band 10– Water vapor channel (7.0um) Water vapor channel (7.0um) Band 11Band 11


Satellite Derived Motion Fields:BASIC METHODOLOGY

Image acquisitionImage acquisition

Automated registration of imageryAutomated registration of imagery

Target selection processTarget selection process

Height assignment of targetsHeight assignment of targets

Target tracking Target tracking

Quality control (Autoeditor)Quality control (Autoeditor)


Satellite Derived Motion Fields: Image Acquisition

Select 3 consecutive images in timeSelect 3 consecutive images in time Which channels are selected is a function of Which channels are selected is a function of

which wind product (cloud-drift, water vapor, which wind product (cloud-drift, water vapor, visible) is to be generatedvisible) is to be generated

Extended Northern Hemisphere Extended Northern Hemisphere Southern HemisphereSouthern Hemisphere

Coverage Diagrams


Satellite Derived Motion Fields:Auto-registration of Imagery

Registration is a measure of Registration is a measure of consistencyconsistency of of navigation between successive imagesnavigation between successive images

Landmark features (ie., coastlines) Landmark features (ie., coastlines) mustmust remain remain stationary from image to imagestationary from image to image

Satellite-derived winds are much more sensitive Satellite-derived winds are much more sensitive to to changes in registrationchanges in registration than to errors in than to errors in navigationnavigation

Navigation of the 3-axis stabilized GOES Navigation of the 3-axis stabilized GOES satellites much more difficultsatellites much more difficult


Satellite Derived Motion Fields:Auto-registration (Cont’d)

Manual registration corrections applied Manual registration corrections applied operationally to imagery 5% of the timeoperationally to imagery 5% of the time

New automatedNew automated registration QC : registration QC : – hundreds of landmarks usedhundreds of landmarks used– each landmark is sought in all imageseach landmark is sought in all images– middle image in loop is assumed to have “perfect” middle image in loop is assumed to have “perfect”

navigationnavigation– mean line and element correction is computed and mean line and element correction is computed and

possibly appliedpossibly applied for the 1st and 3rd image for the 1st and 3rd image


Satellite Derived Motion Fields:TARGET SELECTION PROCESS

Consider small sub-areas (target area) of Consider small sub-areas (target area) of

an image in successionan image in succession

Perform a spatial coherence analysis of all Perform a spatial coherence analysis of all

targets. targets. Filter outFilter out targets where: targets where:– scene is too “coherent”scene is too “coherent”

– multi-deck cloud signatures are evidentmulti-deck cloud signatures are evident


Satellite Derived Motion Fields:TARGET SELECTION PROCESS (Cont’d)

Locate maxima in brightnessLocate maxima in brightness

Select target/feature associated with Select target/feature associated with

strongest gradientstrongest gradient

Target density is controlled by size of Target density is controlled by size of

target selector areatarget selector area


Satellite Derived Motion Fields:Height Assignment of Targets

Infrared window techniqueInfrared window technique– oldest method of assigning heights to cloud-oldest method of assigning heights to cloud-

motion windsmotion winds– not suitablenot suitable for assigning heights of semi- for assigning heights of semi-

transparent cloud (ie., thin cirrus)transparent cloud (ie., thin cirrus)– still provides a still provides a suitable fallbacksuitable fallback to other to other

methodsmethods


Satellite Derived Motion Fields:Target Height Assignment (Cont’d) COCO22 Slicing Technique Slicing Technique

– most accuratemost accurate means of assigning heights to means of assigning heights to semi-transparent tracerssemi-transparent tracers

– utilizes IR window and COutilizes IR window and CO22 (13um) absorption (13um) absorption

channels viewing the same FOV channels viewing the same FOV

– However, COHowever, CO22 absorption band absorption band absentabsent on on

current GOES imagerscurrent GOES imagers


Satellite Derived Motion Fields:Satellite Derived Motion Fields:Target Height Assignment (Cont’d)Target Height Assignment (Cont’d) HH22O Intercept MethodO Intercept Method

– Utilizes WV channel (6.7um) Utilizes WV channel (6.7um) Band 3 Band 3 and and longwave IR window chan. (10.7um) longwave IR window chan. (10.7um) Band 4Band 4

– Algorithm: these two sets of radiances from a Algorithm: these two sets of radiances from a single-level cloud decksingle-level cloud deck vary linearly with cloud vary linearly with cloud amountamount

– Adequate replacementAdequate replacement of CO of CO22 slicing method slicing method


Satellite Derived Motion Fields:Satellite Derived Motion Fields:TARGET TRACKING ALGORITHMTARGET TRACKING ALGORITHM

Define tracking area centered over each targetDefine tracking area centered over each target Search area in second image which best Search area in second image which best

matches radiances in tracking areamatches radiances in tracking area Confine search to “search” area centered Confine search to “search” area centered

around guess (AVN Forecast) displacement of around guess (AVN Forecast) displacement of targettarget

Two vectors per target: 1 for image 1&2; 1 for Two vectors per target: 1 for image 1&2; 1 for image 2&3image 2&3


Satellite Derived Motion Fields:Quality Control (Autoeditor)

FunctionsFunctions– Target height reassignmentTarget height reassignment– Wind quality estimation flagWind quality estimation flag

Method (4 Steps)Method (4 Steps)– 1)1) 3-dimensional objective analysis 3-dimensional objective analysis of of

model forecast wind field on 1st passmodel forecast wind field on 1st pass– 2)2) Incorporate satwinds into analysis on Incorporate satwinds into analysis on 2nd 2nd

pass. pass. Remove those differing Remove those differing significantlysignificantly from from analysisanalysis


Satellite Derived Motion Fields:Quality Control (Cont’d)

Method (Cont’d)Method (Cont’d)– 3)3) Target heights readjusted by minimizing Target heights readjusted by minimizing

a penalty function which seeks the a penalty function which seeks the optimum optimum “fit”“fit” of the vector to the of the vector to the analysisanalysis

– 4)4) Perform another 3-dimensional Perform another 3-dimensional objective objective analysis (analysis (at reassigned at reassigned pressurespressures) and assign ) and assign quality flagquality flag


Height Assignment Related to Satellite Wind Type (Approximations)

Imager Cloud Drift Winds

Imager Water Vapor Winds

Imager Visible Winds

Sounder Water Vapor Winds

100mb - 250mb - 400mb - 600mb - 250mb 400mb 600mb 1000mb35% 30% 20% 15%

55% 40% <5% <5%

N/A N/A N/A 30% 600-800 70% 800-1000

<5% 55% 40% <5%


GOES High Density Water Vapor Winds

100mb - 250mb

250mb - 400mb

400mb - 700mb


GOES High Density Cloud Drift Winds

100mb - 400mb

400mb - 700mb

Below 700mb


GOES High Density Winds(Cloud Drift, Imager H2O, Sounder H2O)


GOES High Density Visible Winds


GOES High Density Visible WindsTropical System Circulations

Hurricane Earl

800mb-1000mb

> 34 Knots(Tropical Storm

Strength)


Satellite Derived Motion Fields:Optimal Data Processing Strategies Take advantage of new sensor technologyTake advantage of new sensor technology

– silicon photodiode detectors (improved signal-to-noise)silicon photodiode detectors (improved signal-to-noise)– higher spatial resolution and bit depthhigher spatial resolution and bit depth– improved spectral sampling & sampling ratesimproved spectral sampling & sampling rates

Take advantage of automation techniques and Take advantage of automation techniques and processing powerprocessing power– eliminate manual labor-intensive taskseliminate manual labor-intensive tasks– increase data volumeincrease data volume


Satellite Derived Motion Fields:Optimal Data Processing Strategies Take advantage of improved viewing capabilityTake advantage of improved viewing capability

– temporal sampling (including rapid scans)temporal sampling (including rapid scans)– independent imager and sounderindependent imager and sounder

OptimizeOptimize processing strategy processing strategy– high data volume/density (x,y,z,t) coveragehigh data volume/density (x,y,z,t) coverage– multi-spectral data integration (Hmulti-spectral data integration (H2 2 O winds)O winds)– multi-satellite (data fusion)multi-satellite (data fusion)


Satellite Derived Motion Fields:Satellite Derived Motion Fields:Optimal Data Processing StrategiesOptimal Data Processing Strategies Focus processing strategy Focus processing strategy towards the towards the

meteorologymeteorology– circulations and environmental featurescirculations and environmental features

AdaptAdapt the data quality control the data quality control Take advantage of improved Take advantage of improved

communicationscommunications– timely data disseminationtimely data dissemination


GOES-10 Visible WindsImpact of Higher Sampling Rates


Satellite Derived Motion Fields: GOES Wind Products: What’s New ?

Product Coverage FrequencyCloud-drift*10.7 um (Band 4)High Density

NH,SH 8x/day

Water vapor*

6.7 um (Band 3)High Density

NH,SH 8x/day

Sounder WV7.3 um (Band

10)7.0 um (Band 11)

Tropical Scans 4x/day

Visible0.65 um (Band 1)

Atlantic/Pacific

4x/day


Satellite Derived Motion Fields:Current and New/Planned Applications Mid-latitude Oceanic AnalysesMid-latitude Oceanic Analyses

– NWS offices have access to high density wind productsNWS offices have access to high density wind products via internet; AWIPS access to follow via internet; AWIPS access to follow

Numerical Weather Prediction (NWP) and Data Numerical Weather Prediction (NWP) and Data AssimilationAssimilation– What’s happening at NCEP/EMC ?What’s happening at NCEP/EMC ?– ECMWF is utilizing GOES high density wind productsECMWF is utilizing GOES high density wind products

Tropical Cyclone Analysis and ForecastingTropical Cyclone Analysis and Forecasting– Tropical Prediction Center (TPC) has access to the GOES multi-Tropical Prediction Center (TPC) has access to the GOES multi-

spectral wind data setsspectral wind data sets– GFDL & NRL are performing model impact studies using the GFDL & NRL are performing model impact studies using the

GOES multi-spectral winds to improve tropical storm track GOES multi-spectral winds to improve tropical storm track forecastsforecasts

– CIMSS routinely generating water vapor and visible winds from CIMSS routinely generating water vapor and visible winds from GMS-5GMS-5


Satellite Derived Motion Fields:NWP and Data Assimilation

EMC Status/PlansEMC Status/PlansOperational use of high density Cloud Drift winds Operational use of high density Cloud Drift winds in Global and Regional forecast models began in in Global and Regional forecast models began in December 1997.December 1997.

Evaluation of high density Water Vapor (imager Evaluation of high density Water Vapor (imager and sounder) and Visible winds planned for 1999 - and sounder) and Visible winds planned for 1999 - focus on assimilation of focus on assimilation of layerlayer wind estimates. wind estimates.


Satellite Derived Motion Fields:NWP and Data Assimilation

NESDIS Status/PlansNESDIS Status/Plans– Routine production of GOES sounder WV and VIS Routine production of GOES sounder WV and VIS

winds began in late 1997. Work with EMC to winds began in late 1997. Work with EMC to support evaluation in EMC operational database in support evaluation in EMC operational database in 1999.1999.

– NESDIS/CIMSS and FSL will coordinate on model NESDIS/CIMSS and FSL will coordinate on model impact study involving the generation of multi-impact study involving the generation of multi-spectral (vis,ir,wv) windsspectral (vis,ir,wv) winds and their assimilation into and their assimilation into the MAPS/RUC modelsthe MAPS/RUC models.


Satellite Derived Motion Fields:Satellite Derived Motion Fields:VVerificationerification

Sources of errors in satellite-derived Sources of errors in satellite-derived windswinds

Satellite winds vs. rawinsondes vs. model Satellite winds vs. rawinsondes vs. model colocation statisticscolocation statistics

Model impact studiesModel impact studies Satellite minus forecast wind fieldSatellite minus forecast wind fieldMean tropical storm track forecast errorsMean tropical storm track forecast errors


Comparison of Model Forecast and Satellite Derived Wind FieldsAVN Forecast

AVN Forecast + Sat Winds


Impact of GOES Winds - Hurricane Edouard 1996


Impact of GOES Winds - Hurricane Fran 1996


Satellite Derived Motion Fields:Satellite Derived Motion Fields:Sources of ErrorsSources of Errors

Assumption that clouds and water vapor Assumption that clouds and water vapor features are passive tracers of the wind features are passive tracers of the wind fieldfield

Image registration errorsImage registration errors Target identification and tracking errorsTarget identification and tracking errors Inaccurate height assignment of targetInaccurate height assignment of target


Satellite Derived Motion Fields:Satellite Derived Motion Fields:SummarySummary

Higher resolution data, improved science, and full automationHigher resolution data, improved science, and full automation - resulted in satwinds which are superior in both quality and - resulted in satwinds which are superior in both quality and quantity to any done previously at NOAA/NESDISquantity to any done previously at NOAA/NESDIS

Improved automated QCImproved automated QC is the most significant change in the is the most significant change in the winds processing system over the past 5 yearswinds processing system over the past 5 years

Improved target selectionImproved target selection avoids mix-level scenes and avoids mix-level scenes and concentrates on providing greater targeting density for concentrates on providing greater targeting density for features of interest. features of interest. Water vapor intercept method.Water vapor intercept method.

Numerous applicationsNumerous applications


Satellite Derived Motion Fields:Product Availability & References

E-mail: E-mail: [email protected]@nesdis.noaa.gov

[email protected]@noaa.gov Web SitesWeb Sites

– http://cimss.ssec.wisc.edu http://cimss.ssec.wisc.edu – http://orbit-net.nesdis.noaa.gov/goes/wind.htmlhttp://orbit-net.nesdis.noaa.gov/goes/wind.html

Reference MaterialReference Material– Nieman et al., 1997: Fully automated cloud-drift winds in NESDIS Nieman et al., 1997: Fully automated cloud-drift winds in NESDIS

operations. Bull. Amer. Meteor. Soc., 78, 1121-1133.operations. Bull. Amer. Meteor. Soc., 78, 1121-1133.– Veldon et. al., 1997: Upper-tropospheric winds derived from geostationary Veldon et. al., 1997: Upper-tropospheric winds derived from geostationary

satellite water vapor observations. Bull. Amer. Meteor. Soc., 78, 173-195.satellite water vapor observations. Bull. Amer. Meteor. Soc., 78, 173-195.

DERIVED MOTION FIELDS from the GOES SATELLITES

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