contrail detection and optical properties derived using infrared satellite data from modis

Contrail Detection and Optical Properties Derived Using Infrared Satellite Data from MODIS

Sarah Bedka1, Patrick Minnis2, David P. Duda1, Rabindra Palikonda1, Robyn Boeke1 and Kristopher Bedka1

1 Science Systems and Applications Inc., Hampton VA2 NASA Langley Research Center, Hampton VA

Objectives

• Develop an automated Contrail Detection Algorithm (CDA) for identifying linear contrail features in MODIS data

• Determine appropriate brightness temperature difference (BTD) thresholds for CDA, and provide error estimates

• Retrieve contrail optical properties from MODIS observations and estimate the errors in the retrieved properties resulting from errors in the contrail mask

Contrail Detection Algorithm (CDA)

See talk by Dave Duda tomorrow morning for more details

10.8 μm BT10.8 – 12 μm BTD Contrail Mask

• Based on Mannstein et. al (1999)

• Contrails are minimally visible in the 10.8 μm image but quite visible in the 10.8-12 μm BTD image.

• Uses two IR channels (10.8 μm and 12 μm on MODIS) and applies a scene-invariant BTD threshold to identify possible contrail linear features

• Additional IR information from MODIS removes non-contrail linear features (e.g. cloud edges, surface features)

CDA Visual Analysis

Contrail Mask

• GUI-based tool allowed reviewers to examine MODIS IR and VIS information, as well as BTDs

• All cases contained contrails (223366 daytime, 68189 nighttime)

• A composite mask was created from the consensus of the 4 analyses, and is used as “truth”

Composite Contrail Mask

RED = Confirmed ContrailsGREEN = Added ContrailsBLUE = Deleted Contrails

Accuracy of the CDA was determined by visual analysis of 44 (21 daytime, 23 nighttime) MODIS granules by 4 reviewers

CDA Accuracy AssessmentProbability of Detection (POD): What fraction of the observed contrail pixels were correctly identified? Range = 0 -> 1 Perfect = 1

False Alarm Rate (FAR): What fraction of the predicted contrail pixels were incorrectly identified? Range = 0 -> 1 Perfect = 0

Frequency Bias: What is the relative frequency of predicted contrail pixels to observed contrail pixels? Range = 0 -> ∞ Perfect = 1

BIAS =hits + misses

hits + false alarms

FAR =hits + false alarms

false alarms

POD =hits + misses

hits hits: truth=Y mask=Ymisses: truth=Y mask=Nfalse alarms: truth=N mask=Y

POD/FAR/BIAS were calculated for each of 6 BTD thresholds

Probability of Detection/False Alarm RateDaytime Nighttime

cons00 cons01 cons02 cons03 cons04 cons050

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POD - JanuaryPOD - AprilPOD - JulyPOD - October


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POD - JanuaryPOD - AprilPOD - JulyPOD - October


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1FAR - JanuaryFAR - AprilFAR - JulyFAR - October


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1FAR - JanuaryFAR - AprilFAR - JulyFAR - October

# CasesJan = 8Apr = 9Jul = 1Oct = 3


more conservative more sensitivethresholds used thresholds used

POD =hits + misses

hits

hits + false alarmsFAR = false alarms

mask00 mask01 mask02 mask03 mask04 mask05mask00 mask01 mask02 mask03 mask04 mask05

mask00 mask01 mask02 mask03 mask04 mask05


mask00 mask01 mask02 mask03 mask04 mask05

Frequency Bias


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Frequency Bias - JanuaryFrequency Bias - AprilFrequency Bias - JulyFrequency Bias - October


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Frequency Bias - JanuaryFrequency Bias - AprilFrequency Bias - JulyFrequency Bias - October

Daytime Observations Only Nighttime Observations Only



A frequency bias of 1 indicates that the mask neither overestimates nor underestimates the number of contrails.



mask00 mask01 mask02 mask03 mask04 mask05 mask00 mask01 mask02 mask03 mask04 mask05

Monthly CDA Performance Statistics

Jan Apr Jul Oct# Granules 6 5 7 5

% Contrail 0.371 0.491 0.181 0.277

POD 0.535 0.589 0.590 0.616FAR 0.455 0.345 0.389 0.413Frequency Bias 0.981 0.900 0.965 1.049% Added 47.43 45.61 42.54 36.59% Deleted 45.48 34.51 38.89 41.27


% Contrail 0.070 0.086 0.156 0.148


Daytime Observations Only Nighttime Observations OnlyJan Apr Jul Oct

# Granules 6 5 7 5

% Contrail 0.371 0.491 0.181 0.277

POD 0.535 0.589 0.590 0.616FAR 0.455 0.345 0.389 0.413Frequency Bias

0.981 0.900 0.965 1.049% Added 47.43 45.61 42.54 36.59% Deleted 45.48 34.51 38.89 41.27


% Contrail 0.371 0.491 0.181 0.277



% Contrail 0.070 0.086 0.156 0.148


1.625 1.193 0.922 1.854% Added 29.59 37.76 54.18 11.33% Deleted 68.06 53.93 45.78 57.39


% Contrail 0.070 0.086 0.156 0.148


In general, a higher percentage of contrails were added during the daytime than at night. A higher percentage of contrails were deleted at night.

The contrail mask slightly underestimates the number of contrails during the day, and slightly overestimates it at night.The Probability of Detection (POD) was slightly lower in the winter than in the summer, due to lower contrast of contrails over a colder and/or possibly snow-covered surface. False Alarm Rate (FAR) was also slightly higher in the winter, and was significantly higher at night than during the day.


% Contrail 0.371 0.491 0.181 0.277


0.981 0.900 0.965 1.049% Added 47.43 45.61 42.54 36.59% Deleted 45.48 34.51 38.89 41.27


% Contrail 0.070 0.086 0.156 0.148


1.625 1.193 0.922 1.854% Added 29.59 37.76 54.18 11.33% Deleted 68.06 53.93 45.78 57.39

• Uses 9 ice cloud models (Minnis et.al 1998).

• Accurate contrail temperature and clear-sky BTDs are key to accurate retrievals

• 2-channel retrieval (11, 12 μm) may capture the data better than the traditional 3-channel retrieval

predicted clear-sky value

Retrieval of Contrail Optical PropertiesTechnique is to minimize the difference between the observed and calculated BTDs for 3 IR bands (3.9, 11, and 12 μm).

Contrail Retrieved Optical PropertiesOverall Averages – 23 Daytime Granules

Confirmed Added DeletedMean τ (2-channel IR) 0.46 0.70 0.78

Mean τ (3-channel IR) 0.40 0.93 0.85

Mean De (2-channel IR) 77.1 92.3 89.6


• 223366 total contrail observations (116789(52%) confirmed, 82118(37%) added, 24459(11%) deleted)

• Total τ (Pc*τc+Pa*τa-Pd*τd) is 0.58 for the 2-channel IR retrieval and 0.64 for the 3-channel

• Total De is 84.1 (60.1) for the 2-channel (3-channel) retrieval

Contrail Retrieved Optical PropertiesOverall Averages – 21 Nighttime Granules

Confirmed Added DeletedMean τ (2-channel IR)Mean τ (3-channel IR) 0.90 0.81 0.84

Mean De (2-channel IR)


• Average of 21 nighttime cases• 4-reviewer composite mask used• 68189 total contrail observations (31941

confirmed, 18159 added, 19240 deleted)

Future Work• Improve contrail optical property retrievals by:

better characterizing background temperature improving contrail temperature estimates expanding model parameterizations (from P. Yang)

• Apply CDA to a larger data set to get an estimate of annual contrail coverage and trends over the Northern Hemisphere

• Use CDA performance statistics from visual analysis to estimate errors in long term data sets

contrail detection and optical properties derived using infrared satellite data from modis

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