Development of Objective Overshooting Top and
Enhanced-V Detection Algorithms for GOES-R ABI
JP7.5
Kristopher M. Bedka, Jason C. Brunner, Wayne F. Feltz, and Richard Dworak
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison
Why Are Overshooting Tops and the Enhanced-V Signature Important?
Introduction
• Overshooting convective cloud tops and the enhanced-V signature are inter-related and often identify a strong
thunderstorm capable of producing severe weather such as hail, damaging winds, and tornadoes, as well as
significant aviation turbulence
• Day/night objective detection of the enhanced-V signature and overshooting tops are product requirements that
were assigned to the GOES-R Advanced Baseline Imager (ABI) Aviation Algorithm Working Group (AWG)
• UW-CIMSS received funding in Spring 2008 to investigate existing algorithms for identifying these two signatures,
to develop alternative approaches, and to compare algorithm performance. There are currently no operational
algorithms for detection of overshooting tops and the enhanced-V signature.
GOES-R ABI Enhanced-V and Overshooting Top Product Requirements
Algorithm Descriptions, Datasets, and Methodology
Light Intensity Turbulence from EDR
Moderate Intensity Turbulence from EDR
Overshooting Top: A domelike protrusion above a cumulonimbus anvil,
representing the intrusion of an updraft though its equilibrium level or the
tropopause (from the AMS Glossary)
Frequency and Intensity of
Turbulence Increases Significantly
When Aircraft Fly Close to an
Overshooting Top
1)Indicative of a storm with a very strong updraft, hazardous for aviation
operations if a plane were to fly through an overshooting top
2)Correlates well with radar reflectivity maxima and storm severity
3)Interaction of updraft with stable tropopause layer generates turbulent gravity
waves which can propagate far away from their source region
4)Responsible for obstructing upper-level jet stream flow, producing the
enhanced-V signature
The appearance of an enhanced-V in infrared imagery resembles a V- or
boomerang-shaped area of cold IR window channel brightness temperatures
(BT), and is bordered by an area of warm BT downwind. One explanation for
the origin of this signature is thought to be related to a circulation forced by the
overshooting top (OT). As upper-level flow approaches the OT, it is diverted
around the OT as if it were a solid obstacle (like water in a stream flowing
around a boulder). Downwind of the OT, the air subsides and warms, producing
the warm wake characteristically observed in tandem with the enhanced-V.
(Ackerman and Knox (Meteorology: Understanding the Atmosphere, 2001)
The relationship between objectively-detected overshooting tops (OT) and non-overshooting cold IR
pixels (< 215 K, non-OT) in GOES-12 imagery, and objective eddy dissipation rate (EDR) turbulence
observations from May-August 2005-2007. EDR observations are collected every minute during the flight
of many United Airlines Boeing 757 aircraft, allowing precise temporal and spatial co-location of satellite
and turbulence observations.
Overshooting Top
Downstream
Warm Region
Unique Characteristics of Overshooting Tops in Multispectral Satellite Imagery
Visible/Near-Infrared Characteristics
• “Lumpy” texture relative to smooth anvil cloud and shadowing at lower solar zenith angles
• Variability in ice crystal effective radius and ~4 μm channel reflectance, with smaller ice crystals and higher reflectance
indicating an active updraft of a severe storm (Rosenfeld et al. 2008)
Day/Night Infrared-only Characteristics
• Positive upper-level water vapor (WV)- IR window channel BT differences, as tropospheric water vapor content is injected
into the lower stratosphere by updrafts associated with overshooting convective cloud tops, which radiates at a warmer
temperature than the colder cloud-top in IR window imagery (Ackerman et al. 1996, Schmetz et al. 1997, Setvak et al. 2007)
• An isolated region (< 15 km diameter) of very cold IR window channel BT relative to the surrounding warmer anvil cloud.
Anomalously cold BTs are caused by persistent moist adiabatic ascent, allowing the BT to be much colder than any
temperature that would be found in a co-located sounding.
Due to their often rapid development and potential for causing loss of life,
severe thunderstorms present a constant challenge to the forecaster. Methods
for detecting the precursors of and signatures associated with severe weather
are vital. The enhanced-V is often seen in infrared satellite imagery before the
onset of severe weather and is an important indicator of a severe thunderstorm.
McCann (MWR, 1983) found that the median lead time (time from the initial
identification of the feature on satellite imagery to the first reports of severe
weather on the ground) is about 30 minutes.
2 km ABI proxy (AVHRR and MODIS) ~11 micron IR window channel imagery from 8 different
enhanced-V events with identical domain sizes and color enhancements, showing the variability of
enhanced-V temperature characteristics and appearance.
Product Examples and Validation
WV-IR Brightness Temperature Difference
(i.e. Global Convective Diagnostic)
Since the GOES-R ABI overshooting top and enhanced-V detection algorithms are required to operate during both
day and night, the two IR-only characteristics are being evaluated as candidate algorithms by the GOES-R Aviation
Algorithm Working Group.
IR Window “Texture” Overshooting Top Detection Methodology
1)Identify pixels with cold IR window channel BTs (< 215 K) that are also
colder than an NWP tropopause temperature
2)Identify candidate overshooting top (OT) pixels which represent isolated BT
minima that are not within a specified distance threshold of other candidate
pixels
2 km Terra MODIS: 1655 UTC
2 km Aqua MODIS: 1840 UTC
3)Determine the BT difference between the candidate OT pixel and the
surrounding anvil. Those that are > 6.5 K colder than the surrounding anvil
are OT pixels
4)Identify neighboring pixels which are also part of the same OT
OT Detection Criteria=215 K
95% of All OTs Could Be
Detected
OT Detection Criteria=6.5 K
98% of All OTs Could Be Detected
6.5 K Corresponds to a 1 km
Overshoot
(above) A schematic of the IR “texture” overshooting
top detection methodology with the associated
AVHRR 1 km Visible channel image at 1257 UTC on 3
June 2005. (left) Cumulative frequency diagrams for
the minimum OT IR window BT from the 450 enhancedV cases identified by Brunner et al. (2007) and
(right) the difference between the minimum OT and
surrounding anvil BT for 50 of these 450 cases.
(upper-left) Aqua MODIS imagery at 1840 UTC on 8 June 2008. (upper-middle) Color enhanced IR window channel imagery degraded to
a 2 km resolution with cool colors representing the colder cloud tops. (upper-right) IR window channel pixels that are colder than both
215 K and the GFS tropopause temperature. (lower-left) Candidate OT pixels, which are a subset of the points in the upper-right, but
none are closer than 15 km from one another. (lower-middle) Final OT locations from the IR window texture method. (lower-right) WV-IR
BT differences of > +2 K (blue) and > +4 (cyan).
AVHRR 1 km IR Window BT
(Left column) Terra MODIS imagery at 1655 UTC on 8 June 2008. (top) Color enhanced
IR window channel imagery with cool colors representing the colder cloud tops.
(bottom) WV-IR BT differences of > +2 K (blue) and > +4 (cyan). (Right column) The
same imagery and products, but from Aqua MODIS at 1840 UTC on the same day.
Which WV-IR difference value will always identify overshooting top
pixels (0, +2, +4)? This uncertainty and inconsistency is the reason that
the IR window texture method is being developed as a candidate ABI
OT detection algorithm.
GOES-12 4 km IR Window BT
AVHRR 1 km Visible Brightness
Characteristics of Enhanced-V Producing Storms in IR Window Channel Imagery
• An OT is present with a coupled warm region within a 25 km distance downstream and the eastern semicircle of the OT.
The warm region is bounded by the “arms” of the V-shaped pattern.
• A large anvil cloud, ~75 km in length, due to the presence of strong jet stream winds
• The 8 enhanced-V events shown in the upper-left illustrate that the enhanced-V signature is highly variable in terms of
temperature characteristics, V-orientation, and the angle and length of the V-arms. This makes direct pattern recognition of
an enhanced-V very difficult and prone to false alarm
One (near) constant is the presence of a temperature couplet between the coldest OT BT and the warm region
maximum BT. Brunner et al. (WAF, 2007) shows that the presence of a cold OT minimum BT and a large BT couplet
is directly related to the occurrence of significant severe weather at the surface. Detection of a thermal couplet is
far more tangible than V detection via pattern recognition and will be the focus of the ABI algorithm.
Overshooting Tops in 1 km AVHRR
Overshooting Tops in 2 km “ABI”
Overshooting Tops in 4 km GOES-12
Enhanced-V/Anvil Thermal Couplet Detection Methodology
1)Search pixels within 25 km in the eastern direction from an OT pixel for
candidate warm areas. Enhanced-V‘s are oriented to the east of OTs
over CONUS.
2)Compute mean IR window BT around candidate warm area. The mean
must be at least 10 K warmer than the coldest OT pixel.
The IR window texture method is applied here to imagery of varying resolution at 2255 UTC on 11 June 2008. A comparison of IR window imagery from AVHRR and GOES-12 shows that
the 4 km resolution of GOES-12 cannot capture the isolated locations of very cold BT, which has a significant impact on the number of OTs that are detected. Comparison to groundbased radar reflectivity shows that overshooting top locations are well correlated with precipitation maxima
3)Search around candidate warm area to ensure that all pixels in box
have BT at or colder than warm area, eliminating false couplet detections
along an anvil edge.
4)Compute warm area minus surrounding anvil BT difference to ensure
the presence of a focused warm area characteristic of the enhanced-V
signature.
5)Investigate BTs along a ray starting from the OT pixel, through the
warm area, and 15 pixels beyond to ensure the presence of a relatively
large continuous anvil cloud produced by strong winds aloft. Pixels along
ray can be no warmer than the max warm area BT.
Overshooting Top Detection Method
False Alarm Rate
Percentage of Total High
Confidence OT Pixels Identified
IR Texture
OT ≥ 6.5 K Colder Than Surrounding Anvil
20.2 %
43.2 %
IR Texture
OT ≥ 8.5 K Colder Than Surrounding Anvil
17.5 %
39.4 %
IR Texture
OT ≥ 10.5 K Colder Than Surrounding Anvil
7.6 %
35.5 %
WV-IR Difference > 2 K
5.1 %
25.0 %
WV-IR Difference > 3 K
2.3 %
1.8 %
(top) The minimum overshooting top BT (x-axis) versus the thermal
couplet magnitude (y-axis) for tornadic storms with enhanced-V
signatures during Summer 2003 and 2004. (bottom) A schematic
diagram of the anvil thermal couplet detection methodology
Input Datasets
(upper-left panel) WRF-based simulated GOES-R ABI proxy 11.2 micron channel imagery for 4 June 2005 at 2340 UTC.
Pixels warmer than 260 K are transparent. (upper-right panel) Overshooting top locations based upon WRF total
hydrometeor mixing ratio (THMR, see Methodology section). Green areas are high confidence overshooting locations
with black being of lesser confidence. Note: The size of dots are significantly larger than an 2 km ABI pixel for easier
visualization. (lower-left panel) WV-IR channel BT differences > 2 K. (lower-right) Overshooting top identifications by
the IR window texture method using an OT-surrounding anvil BT difference threshold of 6.5 K. (table above) Validation
statistics relative to WRF THMR for various OT detection methods/settings using 25 images over the domain shown to the
left. These 25 images cover a 2-hour period of very active convective activity with ~1000 “truth” OT pixels.
1)IR window and upper-level water vapor channel BTs from MODIS, AVHRR, MSG SEVIRI, or WRF-based simulated
GOES-R ABI proxy remapped to the 2 km ABI resolution
2)NWP tropopause temperature field remapped to the ABI resolution and projection
Validation Datasets
Overshooting Top
1)CALIPSO and CloudSat overpasses of overshooting tops with NASA GEOS-5 NWP tropopause heights
2)Qualitative comparison of IR-based objective overshooting detections to Visible channel imagery
3)Total hydrometeor mixing ratio (THMR) in the lower stratosphere from the Weather Research and Forecast (WRF) NWP
simulation(s) used to produce GOES-R ABI proxy simulated brightness temperature fields (see below). THMR represents a
sum of the mixing ratio from all WRF microphyscial species (pristine ice, graupel, snow, rain, cloud water). Anomalously high
THMR values in the lower stratosphere indicate the presence of strong updrafts consistent with the presence of an
overshooting top.
2 km WRF THMR Isosurface Colored
by the WRF 3-D Temperature Field
MODIS IR Window With CALIPSO/CloudSat Overpass
MODIS IR Window With CALIPSO/CloudSat Overpass
2 km WRF THMR Isosurface Colored by Simulated
ABI IR Window Brightness Temperatures
Accurate Overshooting Top Detection
Accurate Overshooting Top Detection
2-3 km Above
Surrounding Anvil
Cloud
MODIS IR Window With CALIPSO/CloudSat Overpass
MODIS IR Window With CALIPSO/CloudSat Overpass
200 hPa WRF THMR
175 hPa WRF THMR
0-50 km
Range Rings
from OT
150 hPa WRF THMR
Anvil Too Small For Detection
Accurate Non-Detection
(upper-left) A side view of an isosurface of WRF-generated total hydrometeor mixing ratio (THMR) colored by the WRF 3-D temperature field. The WRF simulation has
a horizontal resolution of 2 km. (upper-right) A top view of the same isosurface colored by the simulated ABI 11.2 micron IR window channel BT field. (bottom) WRF
total hydrometeor mixing ratio at 200 hPa (left), 175 hPa (middle), and 150 hPa (right). Pixels exceeding the 75th percentile of THMR at 175 hPa are considered
overshooting top pixels and those exceeding the 90th percentile at 150 hPa are considered high confidence overshooting top pixels. Overshooting top
identifications using simulated ABI imagery can be directly compared to these “truth” overshooting pixels to evaluate the accuracy of the satellite algorithm.
Enhanced-V
1)Brunner et al. (WAF, 2007) have manually identified 450 enhanced-V
cases that had occurred during summer 2003 and 2004 over the U.S. in
AVHRR and MODIS imagery.
The enhanced-V/thermal couplet
detection algorithm will be run over the entire image granule for each of
these cases, in addition to other more recently identified cases.
Probability of detection and false alarm ratio statistics will be computed,
in addition to the frequency of severe weather associated with each of
the detected enhanced-V’s based on the NCDC “Storm Data” severe
weather event database.
Couplet Overshooting Top
Couplet Warm Region
5 Total Enhanced-V Storms
4 Detected by ABI Algorithm
Total Number of
Anvil Thermal
Couplets
False Alarm
Ratio
Probability of
Enhanced-V
Detection
(Including
Missed OT
Events)
Probability of
Enhanced-V
Detection
(Excluding
Missed OT
Events)
Percent of
Detected
Thermal
Couplets
Associated With
Severe Weather
Percent of All
Thermal
Couplets (Both
Detected and
Non-Detected)
Associated With
Severe Weather
140
26.8 %
66.4 %
72.7 %
74.2 %
68.6 %
(left panels) MODIS IR window imagery degraded to the 2 km ABI resolution showing thermal couplet detections from the
ABI algorithm. (table above) Validation statistics of the ABI algorithm for 140 enhanced-V producing storms. The term
“excluding missed OT events” means that the total number of couplets was reduced in the POD statistic because an OT
was not detected for several V-cases and therefore a thermal couplet could not possibly have been found. The severe
weather relationship statistics shows that the ABI algorithm is identifying a greater than average number of storms
producing severe weather.