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An Estimate of Contrail Coverage over the Contiguous United States David Duda, Konstantin Khlopenkov, Thad Chee SSAI, Hampton, VA Patrick Minnis NASA LaRC,

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Presentation on theme: "An Estimate of Contrail Coverage over the Contiguous United States David Duda, Konstantin Khlopenkov, Thad Chee SSAI, Hampton, VA Patrick Minnis NASA LaRC,"— Presentation transcript:

1 An Estimate of Contrail Coverage over the Contiguous United States David Duda, Konstantin Khlopenkov, Thad Chee SSAI, Hampton, VA Patrick Minnis NASA LaRC, Hampton, VA

2 Contrail climatology Goal: Create data set of contrail coverage, optical depth and radiative forcing over Continental US (CONUS) from MODIS data 23 February 2011ACCRI Symposium 20112 Purpose: Case study for developing globally homogeneous data set of contrail coverage and cloud properties necessary for quantifying global contrail RF more accurately

3 Modified Mannstein et al. CDA Mannstein et al. (1999) developed automated 2- channel contrail detection algorithm (CDA) to detect linear contrails in AVHRR IR imagery 23 February 2011ACCRI Symposium 20113 Requires only brightness temperatures, T 11 & T 12 ; no ancillary information Contrails appear as bright lines in 11 minus 12 μm brightness temperature difference (BTD) images

4 Cloud Detection Algorithm (CDA) 23 February 2011ACCRI Symposium 20114 To reduce false detections, additional IR channels (6.7, 8.6, 13.3 μm) available on MODIS are added BTD 11-12 BTD 11-12 + BTD 8.6-12 + BTD 8.6-13.3 Additional channels sometimes allow better discrimination of contrails than BTD 11-12

5 23 February 2011ACCRI Symposium 20115 Cloud Detection Algorithm (CDA) Visual analysis of 44 MODIS granules by 4 independent reviewers to determine best balance between detection efficiency and false alarms Set of 6 binary check masks developed to reduce false detections (mask00 – least sensitive, mask05 – most sensitive) [Day: mask03, Night: mask02] presentation by S. Bedka

6 QC of satellite images MODIS consists of an array of independent scanning sensors that may induce striping in raw images Striping is especially apparent in BTD imagery 23 February 2011ACCRI Symposium 20116

7 23 February 2011ACCRI Symposium 20117 Destriping Original: BT difference (8.6–12  m) from MODIS Terra 01/01/2006 13:45UTC over North Atlantic. Interpolated: data from 2 failing detectors (#1 and #6) with neighboring lines. FFT filtered: Image is processed as overlapping blocks of pixels. For each block, the Fourier frequency spectrum is corrected to suppress frequencies that are multiples of 10. The restored image has almost no striping noise.

8 Remapping of MODIS imagery 23 February 2011ACCRI Symposium 20118 To reduce effects of image distortion at large (> 50°) viewing angles (including MODIS “bow-tie” effects), each granule of data is re- projected onto a standard map (Lambert Azimuthal Equal-Area projection). Re-projected data allow more accurate contrail detections at viewing angles greater than 50°

9 Visual analysis of contrail mask Following Palikonda et al. (2004), subjective visual analyses of contrail mask over several overpasses by 4 independent analysts estimate error in CDA contrail coverage using interactive software 23 February 2011ACCRI Symposium 20119

10 Annual cycle of contrail coverage 23 February 2011ACCRI Symposium 201110

11 Annual daytime coverage from Terra MODIS 23 February 2011ACCRI Symposium 201111

12 Annual nighttime coverage from Terra MODIS 23 February 2011ACCRI Symposium 201112 Sampling problem recently discovered in Terra nighttime results. Correct coverage available in near future.

13 23 February 2011ACCRI Symposium 201113 Heterogeneity correction for MODIS-derived contrail coverage

14 Contrail coverage maps show low amounts of detected contrail coverage over parts of western US… 23 February 201114ACCRI Symposium 2011 …when compared to air traffic density over CONUS

15 Mannstein et al. (1999) – thermal heterogeneity in 12 micron images caused by ground features and clouds influences contrail detection efficiency 23 February 201115ACCRI Symposium 2011

16 Mannstein et al. – Figure 15 (computed standard deviation of AVHRR channel 5 (12 micron) BT – [SDT5]) 23 February 201116ACCRI Symposium 2011

17 SDT5 computed from Terra MODIS for 2006 23 February 201117ACCRI Symposium 2011

18 US terrain 23 February 201118ACCRI Symposium 2011

19 Loop of SDT5 for 2006 23 February 201119ACCRI Symposium 2011

20 One step correction based on Mannstein et al. (1999) heterogeneity correction and 2006 Terra MODIS data Regions with SDT5 > 1.20 K are undefined. Heterogeneity correction increases overall contrail coverage by roughly 1.4X 23 February 201120ACCRI Symposium 2011

21 Meyer et al. introduced new three step heterogeneity correction False alarm-corrected coverage computed from spatially averaged contrail overage Correlating and leads to homogenized contrail coverage Contrail coverage derived from homogenized contrail coverage after determining an overall detection efficiency 23 February 201121ACCRI Symposium 2011

22 Meyer et al. (1999) – original CDA algorithm has false alarm rate (FAR) that is related to SDT5 (Corrected for FAR effects) FAR determined for 2 regions w/ little air traffic 23 February 201122ACCRI Symposium 2011

23 What is FAR for present work? Majority of grid boxes have coverage above a threshold (function of SDT5) 23 February 201123ACCRI Symposium 2011 Approximate threshold represented as dashed green line.

24 44 analyzed 5-minute MODIS granules Small crosses: each granule Large plus signs: data averaged over SDT5 bins (<0.4, 0.4-0.6, 0.6-0.8, >0.8). FAR = percentage of ‘delete’ pixels in analysts’ composite from each granule. 23 February 201124ACCRI Symposium 2011

25 After subtracting FAR, present work has slightly different slope and intercept compared to Meyer et al. Meyer et al (2001): 0.29 – 0.17 SDT5 Present work: 0.16 – 0.07 SDT5 23 February 201125ACCRI Symposium 2011

26 Detection Efficiency (DEF) DEF computed from 44 analyzed granules DEF = (confirmed pixels) divided by (confirmed + added pixels) Large plus signs indicate bin averages 23 February 201126ACCRI Symposium 2011 Meyer et al. (2001): DEF = 0.4 ± 0.2. Present work: DEF = 0.56 ± 0.21.

27 Three step correction based on Meyer et al (2001) heterogeneity correction and 2006 Terra MODIS data Regions with SDT5 > 1.20 K are undefined. Heterogeneity correction increases overall contrail coverage by roughly 1.6X. 23 February 201127ACCRI Symposium 2011

28 Compare uncorrected and corrected coverage 23 February 201128ACCRI Symposium 2011

29 More data soon to be available… Aqua MODIS data over CONUS for 2006 Four months of Terra MODIS data over CONUS from 2008 (Jan, Apr, Jul, and Oct) 23 February 2011ACCRI Symposium 201129

30 Terra/Aqua comparison 23 February 2011ACCRI Symposium 201130

31 Future plans Process remaining months of MODIS data over CONUS region After 6 month period of further validation, begin processing of NH contrail coverage 23 February 2011ACCRI Symposium 201131


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