DERIVED MOTION FIELDS from the
GOES SATELLITES
Jaime Daniels
NOAA/NESDIS
Office of Research and Applications
Forecast Products Development Team
and
Donald G. Gray
NOAA/NESDIS
GOES Products Manager
Office of Systems Development
March 9, 1999 Comet Class: SatMet 99-1 1
Satellite Derived Motion Fields:
TOPICS
Philosophy
Review of GOES visible, IR, WV
channels
Basic methodology
GOES-Next optimized data processing
strategies
GOES wind products - What’s new ?
Verification
March 9, 1999 Comet Class: SatMet 99-1 2
Satellite Derived Motion Fields:
TOPICS cont’d
Current and new/planned applications
Summary
Product availability and recommended
reading
Discussion/questions
March 9, 1999 Comet Class: SatMet 99-1 3
Satellite Derived Motion Fields:
PHILOSOPHY
Clouds are “passive” tracers of winds at
a single level
– use infrared and visible radiances
Water vapor features (ie., moisture
gradients are “passive” tracers of winds)
– both in clear air and cloudy conditions
– use water vapor infrared radiances
We can properly assign height of tracer
March 9, 1999 Comet Class: SatMet 99-1 4
Satellite Derived Motion Fields:
GOES Visible, IR, WV Channels
Imager
– Water vapor channel (6.7um) Band 3
– Longwave IR window chan. (10.7um) Band 4
– Visible Channel (0.65um) Band 1
Sounder
– Water vapor channel (7.3um) Band 10
– Water vapor channel (7.0um) Band 11
March 9, 1999 Comet Class: SatMet 99-1 5
Satellite Derived Motion Fields:
BASIC METHODOLOGY
Image acquisition
Automated registration of imagery
Target selection process
Height assignment of targets
Target tracking
Quality control (Autoeditor)
March 9, 1999 Comet Class: SatMet 99-1 6
Satellite Derived Motion Fields:
Image Acquisition
Select 3 consecutive images in time
Which channels are selected is a function
of which wind product (cloud-drift, water
vapor, visible) is to be generated
Extended Northern Hemisphere
Southern Hemisphere
Coverage Diagrams
March 9, 1999 Comet Class: SatMet 99-1 7
Satellite Derived Motion Fields:
Auto-registration of Imagery
Registration is a measure of consistency
of navigation between successive images
Landmark features (ie., coastlines) must
remain stationary from image to image
Satellite-derived winds are much more
sensitive to changes in registration than to
errors in navigation
Navigation of the 3-axis stabilized GOES
satellites much more difficult
March 9, 1999 Comet Class: SatMet 99-1 8
Satellite Derived Motion Fields:
Auto-registration (Cont’d)
Manual registration corrections applied
operationally to imagery 5% of the time
New automated registration QC :
– hundreds of landmarks used
– each landmark is sought in all images
– middle image in loop is assumed to have
“perfect” navigation
– mean line and element correction is computed
and possibly applied for the 1st and 3rd image
March 9, 1999 Comet Class: SatMet 99-1 9
Satellite Derived Motion Fields:
TARGET SELECTION PROCESS
Consider small sub-areas (target area) of
an image in succession
Perform a spatial coherence analysis of
all targets. Filter out targets where:
– scene is too “coherent”
– multi-deck cloud signatures are evident
March 9, 1999 Comet Class: SatMet 99-1 10
Satellite Derived Motion Fields:
TARGET SELECTION PROCESS (Cont’d)
Locate maxima in brightness
Select target/feature associated with
strongest gradient
Target density is controlled by size of
target selector area
March 9, 1999 Comet Class: SatMet 99-1 11
Satellite Derived Motion Fields:
Height Assignment of Targets
Infrared window technique
– oldest method of assigning heights to cloud-
motion winds
– not suitable for assigning heights of semi-
transparent cloud (ie., thin cirrus)
– still provides a suitable fallback to other
methods
March 9, 1999 Comet Class: SatMet 99-1 12
Satellite Derived Motion Fields:
Target Height Assignment (Cont’d)
CO2 Slicing Technique
– most accurate means of assigning heights to
semi-transparent tracers
– utilizes IR window and CO2 (13um) absorption
channels viewing the same FOV
– However, CO2 absorption band absent on
current GOES imagers
March 9, 1999 Comet Class: SatMet 99-1 13
Satellite Derived Motion Fields:
Target Height Assignment (Cont’d)
H 2O Intercept Method
– Utilizes WV channel (6.7um) Band 3 and
longwave IR window chan. (10.7um) Band 4
– Algorithm: these two sets of radiances from a
single-level cloud deck vary linearly with cloud
amount
– Adequate replacement of CO2 slicing method
March 9, 1999 Comet Class: SatMet 99-1 14
Satellite Derived Motion Fields:
TARGET TRACKING ALGORITHM
Define tracking area centered over each
target
Search area in second image which best
matches radiances in tracking area
Confine search to “search” area centered
around guess (AVN Forecast)
displacement of target
Two vectors per target: 1 for image 1&2;
1 for image 2&3
March 9, 1999 Comet Class: SatMet 99-1 15
Satellite Derived Motion Fields:
Quality Control (Autoeditor)
Functions
– Target height reassignment
– Wind quality estimation flag
Method (4 Steps)
– 1) 3-dimensional objective analysis
of model forecast wind field on 1st pass
– 2) Incorporate satwinds into analysis on
2nd pass. Remove those differing
significantly from analysis
March 9, 1999 Comet Class: SatMet 99-1 16
Satellite Derived Motion Fields:
Quality Control (Cont’d)
Method (Cont’d)
– 3) Target heights readjusted by minimizing
a penalty function which seeks the
optimum “fit” of the vector to the
analysis
– 4) Perform another 3-dimensional
objective analysis (at reassigned
pressures) and assign quality flag
March 9, 1999 Comet Class: SatMet 99-1 17
Height Assignment Related to
Satellite Wind Type (Approximations)
100mb - 250mb - 400mb - 600mb -
250mb 400mb 600mb 1000mb
Imager Cloud Drift Winds 35% 30% 20% 15%
Imager Water Vapor Winds 55% 40% 34 Knots
(Tropical Storm
Strength)
March 9, 1999 Comet Class: SatMet 99-1 23
Satellite Derived Motion Fields:
Optimal Data Processing Strategies
Take advantage of new sensor technology
– silicon photodiode detectors (improved signal-to-noise)
– higher spatial resolution and bit depth
– improved spectral sampling & sampling rates
Take advantage of automation techniques and
processing power
– eliminate manual labor-intensive tasks
– increase data volume
March 9, 1999 Comet Class: SatMet 99-1 24
Satellite Derived Motion Fields:
Optimal Data Processing Strategies
Take advantage of improved viewing capability
– temporal sampling (including rapid scans)
– independent imager and sounder
Optimize processing strategy
– high data volume/density (x,y,z,t) coverage
– multi-spectral data integration (H2 O winds)
– multi-satellite (data fusion)
March 9, 1999 Comet Class: SatMet 99-1 25
Satellite Derived Motion Fields:
Optimal Data Processing Strategies
Focus processing strategy towards the
meteorology
– circulations and environmental features
Adapt the data quality control
Take advantage of improved
communications
– timely data dissemination
March 9, 1999 Comet Class: SatMet 99-1 26
GOES-10 Visible Winds
Impact of Higher Sampling Rates
March 9, 1999 Comet Class: SatMet 99-1 27
Satellite Derived Motion Fields:
GOES Wind Products: What’s New ?
Product Coverage Frequency
Cloud-drift* NH,SH 8x/day
10.7 um (Band 4)
High Density
Water vapor* NH,SH 8x/day
6.7 um (Band 3)
High Density
Sounder WV Tropical Scans 4x/day
7.3 um (Band
10)
7.0 um (Band 11)
Visible Atlantic/ 4x/day
0.65 um (Band 1) Pacific
March 9, 1999 Comet Class: SatMet 99-1 28
Satellite Derived Motion Fields:
Current and New/Planned Applications
Mid-latitude Oceanic Analyses
– NWS offices have access to high density wind products
via internet; AWIPS access to follow
Numerical Weather Prediction (NWP) and
Data Assimilation
– What’s happening at NCEP/EMC ?
– ECMWF is utilizing GOES high density wind products
Tropical Cyclone Analysis and Forecasting
– Tropical Prediction Center (TPC) has access to the
GOES multi-spectral wind data sets
– GFDL & NRL are performing model impact studies
using the GOES multi-spectral winds to improve
tropical storm track forecasts
– CIMSS routinely generating water vapor and visible
winds from GMS-5
March 9, 1999 Comet Class: SatMet 99-1 29
Satellite Derived Motion Fields:
NWP and Data Assimilation
EMC Status/Plans
Operational use of high density Cloud Drift winds
in Global and Regional forecast models began in
December 1997.
Evaluation of high density Water Vapor (imager
and sounder) and Visible winds planned for 1999 -
focus on assimilation of layer wind estimates.
March 9, 1999 Comet Class: SatMet 99-1 30
Satellite Derived Motion Fields:
NWP and Data Assimilation
NESDIS Status/Plans
– Routine production of GOES sounder WV and
VIS winds began in late 1997. Work with
EMC to support evaluation in EMC operational
database in 1999.
– NESDIS/CIMSS and FSL will coordinate on
model impact study involving the generation of
multi-spectral (vis,ir,wv) winds and their
assimilation into the MAPS/RUC models.
March 9, 1999 Comet Class: SatMet 99-1 31
Satellite Derived Motion Fields:
Verification
Sources of errors in satellite-derived
winds
Satellite winds vs. rawinsondes vs.
model colocation statistics
Model impact studies
Satellite minus forecast wind field
Mean tropical storm track forecast
errors
March 9, 1999 Comet Class: SatMet 99-1 32
Comparison of Model Forecast and
AVN Forecast
AVN Forecast + Sat Winds Satellite Derived Wind Fields
March 9, 1999 Comet Class: SatMet 99-1 33
Impact of GOES Winds - Hurricane Edouard 1996
March 9, 1999 Comet Class: SatMet 99-1 34
Impact of GOES Winds - Hurricane Fran 1996
March 9, 1999 Comet Class: SatMet 99-1 35
Satellite Derived Motion Fields:
Sources of Errors
Assumption that clouds and water vapor
features are passive tracers of the wind
field
Image registration errors
Target identification and tracking errors
Inaccurate height assignment of target
March 9, 1999 Comet Class: SatMet 99-1 36
Satellite Derived Motion Fields:
Summary
Higher resolution data, improved science, and full
automation - resulted in satwinds which are superior in
both quality and quantity to any done previously at
NOAA/NESDIS
Improved automated QC is the most significant change
in the winds processing system over the past 5 years
Improved target selection avoids mix-level scenes and
concentrates on providing greater targeting density for
features of interest. Water vapor intercept method.
Numerous applications
March 9, 1999 Comet Class: SatMet 99-1 37
Satellite Derived Motion Fields:
Product Availability & References
E-mail: jdaniels@nesdis.noaa.gov
Donald.G.Gray@noaa.gov
Web Sites
– http://cimss.ssec.wisc.edu
– http://orbit-net.nesdis.noaa.gov/goes/wind.html
Reference Material
– Nieman et al., 1997: Fully automated cloud-drift winds in NESDIS
operations. Bull. Amer. Meteor. Soc., 78, 1121-1133.
– Veldon et. al., 1997: Upper-tropospheric winds derived from
geostationary satellite water vapor observations. Bull. Amer. Meteor.
Soc., 78, 173-195.
March 9, 1999 Comet Class: SatMet 99-1 38