1. Objective Overshooting Top and Cold V Detection
Overshooting tops and the cold (“enhanced”) U/V signature are important indicators of storm severity and aviation turbulence
Objective detection algorithms for these two signatures are required for the GOES-R ABI Aviation Algorithm Working Group
2 km WRF Simulated Total Hydrometeor Mixing Ratio Isosurface
Colored By 3-D WRF Temperature Field
K. Bedka and GOES-R ABI Proxy Data Team (UW-CIMSS)

2. Difference Between OT and Surrounding Anvil: 50 Cases
Minimum OT Temperature: 450 Cases

3. Objective Day/Night Overshooting Top Detection
1 km AVHRR
Objective Day/Night Overshooting Top Detection
IR window imagery is used to identify overshooting tops occurring during both day and night
A study of 450 enhanced-V producing overshooting top cases (Brunner et al. (WAF, 2007)) shows that tops are:
isolated clusters of pixels (< 12 km2 area) colder than 215 K and NWP tropopause temp
significantly colder (> 6.5 K) than the surrounding anvil cloud
Higher ABI spatial resolution leads to better observation of cold BT minima and improved overshooting detection
Overshooting Detection Using 2 km ABI
Overshooting Detection Using 4 km GOES-12
Summer 2006
Turbulence Frequency
0-25 km Radius: 25%
26-50 km Radius: 15%
km Radius: 9%
K. Bedka and R. Dworak (UW-CIMSS)

4. Objective Overshooting Top Turbulence Validation
Match Distance
# Matches
Frequency of Light
Frequency of Moderate
Frequency of Severe
0-25 km
1710
17.5%
7.1%
.23%
26-50 km
3112
12.4%
2.2%
.06% km
16056
7.9%
1.2%
Next step is to identify frequency of turbulence associated with non-overshooting cold pixels that failed OT detection algorithm criteria...i.e. those not significantly colder than surrounding pixels

5. Toward Objective Mountain Wave Detection in WV Imagery
Pattern recognition techniques are being investigated to objectively isolate interference patterns
MODIS cloud mask being used to screen out wave patterns than can occur in jet stream cirrus clouds
MODIS WV Imagery