Outline of RGB Composite Imagery
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1 Outline of RGB Composite Imagery Data Processing Division, Data Processing Department Meteorological Satellite Center (MSC) JMA Akihiro SHIMIZU 29 September, 2014 Updated 6 July,
2 Contents What s RGB composite imagery? How to create RGB composite imagery RGB composite imagery presented by EUMETSAT RGB composite imagery which are possible to create by traditional images of MTSAT satellites RGB composite imagery which are possible to create by Himawari-8 and -9 imagery RGB composite imagery by Himawari-8 and -9 Practical training to create RGB composite imagery by SATAID 2
3 What s RGB composite imagery? 3
4 What s RGB composite imagery? Red (R), green (G) and blue (B) which are the three primary colors of light constitute color space expressing additive color composite The RGB composite imagery is a technique to display a color using this property of the three primary colors of light 4
5 What s RGB composite imagery? RGB sub-pixels in an LCD TV RGB phosphor dots in a CRT monitor 5 Ref: Wikipedia RGB color model:
6 What s RGB composite imagery? List of satellites/imagers specifications Channel Himawari-8/ -9 MTSAT-1R/-2 MSG Physical Properties μm vegetation, aerosol B μm vegetation, aerosol G μm 0.68 μm µm low cloud, fog R μm 0.81 µm vegetation, aerosol μm 1.64 µm cloud phase μm particle size μm 3.7 μm 3.92 µm low cloud, fog, forest fire μm 6.8 μm 6.25 µm mid- and upper level moisture μm mid- level moisture μm 7.35 µm mid- and lower level moisture μm 8.70 µm cloud phase, SO μm 9.66 µm ozone content μm 10.8 μm 10.8 µm cloud imagery, information of cloud top μm cloud imagery, sea surface temperature μm 12.0 μm 12.0 µm cloud imagery, sea surface temperature μm 13.4 µm cloud top height Visible Near Infrared Infrared There are different properties in each channel, as shown in the left figure. 6
7 What s RGB composite imagery? 16 bands Images by Himawari-8/AHI B01 B01: B02 B02: B03 B03: B μm 0.51 μm 0.64 μm Visible Visible Visible B04: 0.86 μm Near infrared Vegetation, aerosol Vegetation, aerosol Low cloud, fog Vegetation, aerosol B05 B05: B06 B06: B07 B07: B μm 2.3 μm 3.9 μm Near infrared Near infrared Infrared B08: 6.2 μm Infrared Cloud phase Particle size Low cloud, fog, forest fire Mid- and upper level moisture B09 B09: B10 B10: B11 B11: B μm 7.3 μm 8.6 μm Infrared Infrared Infrared B12: 9.6 μm Infrared Mid level moisture Mid- and lower level moisture Cloud phase, SO2 Ozone content B13 B13: B14 B14: B15 B15: B μm 11.2 μm 12.4 μm Infrared Infrared Infrared B16: 13.3 μm Infrared Cloud imagery, information of cloud top cloud imagery, sea surface temperature Cloud imagery, sea surface temperature Cloud top height 7
8 There are too many channels! The RGB technique is Simple process by composition of images enable to create RGB imagery. Various information are derivable by one RGB image. RGB imagery retain natural texture of single channel images. Various information can be derived by colorizing and composing imagery. 8
9 How to create RGB composite imagery 9
10 How to create RGB composite imagery RGB composite imagery can be displayed by three individual colorized (red, blue or green) images of 2 or 3 channels (or channel differences) and by composing them. IR10.8-IR12.0 IR3.7-IR10.8 IR10.8 By compositing these three images, what will happen? 10
11 How to create RGB composite imagery Hereby a RGB image is created. Information can be derived from coloration by overlapping plural images. In this example, low cloud or fog, thin high cloud and thick Cb cloud etc. 11
12 How to create RGB composite imagery Adjustment of gradation o For extracting and enhancing specific phenomenon o Requirement to adjust visual aspects when compositing images o The visual aspects of RGB composite imagery are manipulated by adjusting gradation (gray-scale) range and gamma correction 12
13 How to create RGB composite imagery Example of gradation (gray-scale) adjustment (emphasis on Cb ) IR10.8 Range : 180~340K Gamma: 1 IR10.8 Range : 180~233K Gamma : 1 13
14 How to create RGB composite imagery Example of gradation (gray-scale) adjustment (emphasis on dust ) IR12.0-IR10.8 Range : -15~5K Gamma : 1 IR12.0-IR10.8 Range : -4~2K Gamma : 1 14
15 How to create RGB composite imagery Gradation (gray-scale) vs gamma value bright Mapping function for different gamma corrections with calibration of (8 bit) dark It s not easy to imagine this concept. Let s move on to the next slide! 15
16 How to create RGB composite imagery Examples of gradation (gray-scale) adjustment (emphasis on land ) VIS0.6 Range : 0~100% Gamma : 0.5 VIS0.6 Range : 0~100% Gamma : 1.0 VIS0.6 Range : 0~100% Gamma :
17 RGB composite imagery presented by EUMETSAT 17
18 RGB composite imagery presented by EUMETSAT RGB composite imagery which are possible to create by traditional images of MTSAT satellites o Limited combinations by VIS IR10.8 IR12.0 IR6.8 IR3.7 RGB composite imagery which will be possible to create by Himawari-8 and -9 imagery Various combinations are covered almost all RGB composite imagery schemes presented by EUMETSAT Let s see some examples on the following slide! 18
19 RGB composite imagery which are possible to create by traditional images of MTSAT satellites 19
20 RGB composite imagery which are possible to create by traditional images of MTSAT satellites Night Microphysics Day Microphysics Clouds Convection Severe Storms 20
21 Night Microphysics (for night-time cloud analysis) R : IR12.0 IR10.8 Range : -4~2 [K] Gamma : 1.0 G : IR10.8 IR3.9 Range : 0~10[K] Gamma : 1.0 B : IR10.8 Range : 243~293[K] Gamma : 1.0 Applications o night-time cloud analysis o Fog/low cloud distinction for night-time 21
22 Night Microphysics MSG 2003/11/9 02:45UTC 22
23 Interpretation of Colors for Night Microphysics Cold, thick, high-level cloud Very cold (< -50 C), thick, high-level cloud Thin Cirrus cloud Thick, mid-level cloud Thin, mid-level cloud Low-level cloud (high latitudes) Low-level cloud (low latitudes) Ocean Land 23
24 Night Microphysics(St/Fog) St/Fog MSG 2005/3/14 00:00UTC 24
25 Night Microphysics(Cb/Cirrus) Cb Cirrus MSG 2005/4/19 03:15UTC 25
26 Night Microphysics (summary) This RGB scheme is effective for low cloud distinction in night time (especially St/Fog) effective for thick Cb cloud distinction in night time viewable by SATAID (the details will follow later) available on MSC website for the Southeast Asia and the South Pacific Islands in real time the web site is here! 26
27 Day Microphysics (for day-time cloud analysis) R : VIS0.8 Range : 0~100 [%] Gamma : 1.0 G : IR3.9 Solar reflectance component Range : 0~60[%] Gamma : 2.5 (summer) Range : 0~25[%] Gamma : 1.5 (winter) B : IR10.8 Range : 203~323[K] Gamma : 1.0 Applications Day-time cloud analysis Convective cloud with strong updrafts Vegetation Fire (hot spot) 27
28 Day Microphysics (for day-time cloud analysis) MSG 2003/9/8 12:00UTC 28
29 Interpretation of Colors for Day Microphysics Deep precipitating cloud (precip. not necessarily reaching the ground) - Bright, thick - Large ice particles - Cold cloud Deep precipitating cloud (Cb cloud with strong updrafts and severe weather)* - Bright, thick - Small ice particles - Cold cloud Thin Cirrus cloud (Large ice particles) Thin Cirrus cloud (Small ice particles) *or thick, high-level lee cloudiness with small ice particles Ocean Vegetation Fires(Hot Spot)/Desert Snow 29
30 Interpretation of Colors for Day Microphysics Supercooled, thick water cloud - Bright, thick - Large droplets Supercooled, thick water cloud - Bright, thick - Small droplets Supercooled thin water cloud - Large droplets Supercooled, thin water cloud - Small droplets Thick water cloud (warm rain cloud) - Bright, thick - Large droplets Thick water cloud (no precipitation) - Bright, thick - Small droplets Thin water cloud - Large droplets Thin water cloud - Small droplets Ocean Vegetation Fires(Hot Spot)/Desert Snow 30
31 Day Microphysics (Severe Convection) Cb cloud with strong updrafts Cloud top with small ice particles MSG 2003/5/20 13:30UTC 31
32 Day Microphysics(Fires) MSG 2003/9/7 11:45UTC 32
33 Day Microphysics (summary) This RGB scheme is effective for convective cloud distinction in day time (especially particle size distinction in rough) effective to distinguish the distribution of fires so far, unavailable for SATAID, because this includes the solar reflectance component 33
34 R : VIS0.8 Clouds Convection Range : 0~100 [%] Gamma : 1.0 G : VIS0.8 Range : 0~100 [%] Gamma : 1.0 B : IR10.8 Range : 323~203 [K] Gamma : 1.0 Applications Day-time cloud analysis Convective cloud distinction 34
35 Clouds Convection MSG 2003/6/12 14:00UTC 35
36 Interpretation of Colors for Clouds Convection 36
37 Clouds Convection vs. VIS Middle/low clouds Cb Ci Distinction between convective clouds and other clouds is easy. VIS RGB 37
38 Clouds Convection (summary) This RGB scheme makes easy to distinguish clouds even in case that the distinction is difficult by switching individual IR and VIS imagery is viewable by SATAID (the details will follow later) is being used by relevant aviation office 38
39 R : VIS0.8 Range : 0~100 [%] Gamma : 1.0 G : VIS0.8 Range : 0~100 [%] Gamma : 1.0 B : IR10.8-IR3.9 Severe Storms Range : -60~-40 [K] Gamma : 2.0 Applications distinction for severe convection 39
40 Severe Storms MSG 2003/6/12 14:00UTC 40
41 Interpretation of Colors for Severe Storms 41
42 Severe Storms vs. VIS Yellowish color indicates convection with strong updraft VIS RGB 42
43 Severe Storms (summary) This RGB scheme is available to distinguish strong updraft location from convective clouds but in day-time only viewable by SATAID 43
44 RGB composite imagery which will be possible to create by Himawari-8 and -9 imagery 44
45 RGB composite imagery which will be possible to create by Himawari-8 and -9 imagery Natural Colors Day Snow-Fog Day Convective Storms Dust Airmass 45
46 R : NIR1.6 Range : 0~100 [%] Gamma : 1.0 G : VIS0.8 Range : 0~100 [%] Gamma : 1.0 B : VIS0.6 Range : 0~100 [%] Gamma : 1.0 Natural Colors Applications Day-time cloud analysis Distinction for snow and ice Vegetation 46
47 Natural Colors MSG 2003/10/31 11:30UTC 47
48 Interpretation of Colors for Natural Colors High-level ice clouds Low-level water clouds Ocean Vegetation Desert Snow 48
49 Natural Colors (snow) MSG 2003/2/18 13:00UTC 49
50 Natural Colors (vegetation) MSG 2012/1/1 11:57UTC MSG 2012/7/1 11:57UTC By comparison, seasonal changes are obvious. 50
51 Natural Colors (summary) This RGB scheme will make easy to distinguish between high-level ice clouds and low-level water clouds be available to distinguish vegetation, desert and snow/ice but in day-time only 51
52 R : VIS0.8 Range : 0~100 [%] Gamma : 1.7 G : NIR1.6 Range : 0~70 [%] Gamma : 1.7 Day Snow-Fog B : IR3.9 Solar reflectance component Range : 0~30 [%] Gamma : 1.7 Applications distinction between low clouds and snow/ice 52
53 Day Solar MSG 2004/2/24 11:00UTC 53
54 Interpretation of Colors for Day Snow-Fog Deep precipitating cloud (precip. not necessarily reaching the ground) - Bright, thick - Large ice particles Deep precipitating cloud* - Bright, thick - Small ice particles *or thick, high-level lee cloudiness with small ice particles Thick water cloud - Large droplets Thick water cloud - Small droplets Ocean Vegetation Desert Snow 54
55 Day Snow-Fog (low clouds and ice) Sea ice Snow low-level clouds appear in whitish colors MSG 2010/4/14 11:57UTC 55
56 Day Snow-Fog (summary) This RGB scheme will make easy to distinguish between low clouds and snow/ice rather than only VIS but in day-time only 56
57 Day Convective Storms R : WV6.2-WV7.3 Range : -35~5 [K] Gamma : 1.0 G : IR3.9-IR10.8 Range : -5~60 [K] Gamma : 0.5 B : NIR1.6-VIS0.6 Range : -75~25 [%] Gamma : 1.0 Applications distinction of convective clouds with severe phenomenon such as gust and tornado etc. 57
58 Day Convective Storms MSG 2003/9/8 12:00UTC 58
59 Interpretation of Colors for Day Convective Storms Deep precipitating cloud (precip. not necessarily reaching the ground) - High level Cloud - Large ice particles Deep precipitating cloud (Cb cloud with strong updrafts and severe weather)* - High level Cloud - Small ice particles Thin Cirrus cloud - Large ice particles Thin Cirrus cloud - Small ice particles *or thick, high-level lee cloudiness with small ice particles Ocean Land 59
60 Day Convective Storms (Cb) Yellowish color indicates convection with strong updraft MSG 2003/5/20 13:30UTC 60
61 Day Convective Storms (Cb) MSG 2003/6/13 12:00UTC 61
62 Day Convective Storms (summary) This RGB scheme will be available to distinguish convective clouds with severe phenomenon (gust, tornado etc.) but in day-time only 62
63 R : IR12.0-IR10.8 Range : -4~2 [K] Gamma : 1.0 G : IR10.8-IR8.7 Range : 0~15 [K] Gamma : 2.5 B : IR10.8 Dust Range : 261~289 [K] Gamma : 1.0 Applications Dust/ Yellow sand Volcanic ash Cloud analysis 63
64 Dust MSG 2004/3/3 01:00UTC 64
65 Interpretation of Colors for Dust Cold, thick, high-level clouds Thin Cirrus clouds Contrails Thick, mid-level cloud Thin, mid-level cloud Low-level cloud (cold atmosphere, High latitude) Low-level cloud (warm atmosphere, Low latitude) Dust/Yellow sand Ocean Warm Desert Cold Desert Warm Land Cold Land 65
66 Dust MSG 2004/3/3 10:00UTC 66
67 Dust (volcanic ash) MSG 2010/4/15 The 2010 eruptions of Eyjafjallajökull (Iceland) This eruptions caused enormous disruption to air travel across western and northern Europe. 67
68 Dust (summary) This RGB scheme will be available to distinguish dust storm or yellow sand available for cloud analysis for day and night also available to distinguish volcanic ash The same RGB combination named Ash which is adjusted gradation for focusing on volcanic ash had been contrived. 68
69 R : WV6.2-WV7.3 Range : -25~0 [K] Gamma : 1.0 G : IR9.7-IR10.8 Range : -40~5 [K] Gamma : 1.0 B : WV6.2 Airmass Range : 243~208 [K] Gamma : 1.0 Applications Air mass(cold/warm) analysis Jet stream analysis Analysis of troughs and upper vortices 69
70 Airmass MSG 2005/1/7 03:00UTC 70
71 Interpretation of Colors for Airmass Thick, high-level clouds Thick, mid-level clouds Thick, low-level clouds (low latitude) Thick, low-level clouds (high latitude) JET Cold Airmass Warm Airmass (High humidity at upper tropopause) Warm Airmass (low humidity at upper tropopause) 71
72 Airmass Cold Airmass JET Advection Warm Airmass MSG 2005/1/7 22:00UTC 72
73 Airmass (summary) This RGB scheme will be available for air mass analysis available for jet stream analysis available day and night 73
74 RGB composite imagery by Himawari-8 and -9 74
75 R : VIS0.6 Range : 0~100 [%] Gamma : 1.0 G : VIS0.5 Range : 0~100 [%] Gamma : 1.0 B : VIS0.4 Range : 0~100 [%] Gamma : 1.0 True Color Applications Day-time cloud analysis Distinction for snow and ice Vegetation 75
76 True Color RGB R : B03(VS 0.64) Range : 0~100 [%] Gamma : 1.0 G : B02(V2 0.51) Range : 0~100 [%] Gamma : 1.0 B : B01(V1 0.46) Range : 0~100 [%] Gamma : 1.0
77 True Color Fog/Low Clouds of Setonai-kai (Inland Sea of Japan) Himawari-8 True Color UTC (Lower right) Fog/ low-clouds were observed at some stations (around red oval). However, fog/ lowclouds are not clear in the IR image. Fog or Low clouds (Upper and lower left) Smooth, whitish areas correspond to fog/ low-clouds in true color RGB and B03 visible image. Himawari-8 B03 VIS UTC Himawari-8 B13+Synop UTC
78 True Color Fog/Low Clouds of Setonai-kai (Inland Sea of Japan) Himawari-8 True Color UTC Comparison with standard RGB schemes The distinction between fog/low-clouds and other layer clouds is easier in Day Snow-Fog RGB and Natural color RGB imagery. In True color RGB, all clouds including fog/ low-clouds appear in whitish. It is required to discriminate them based on texture and movement of clouds. However, the True color RGB will be easy to use for traditional single band imagery user and RGB beginner. Himawari-8 Day Snow-Fog UTC Himawari-8 Natural Colors UTC Fog or lowclouds
79 True Color RGB (summary) This RGB scheme will be available to display "true colored" image that is nearly visible with the naked eye, by composition of "three visible images" corresponding to red, green and blue colors with human's naked eye easy to use for traditional single band imagery user and RGB beginner available day time only second-best compared with other specific RGB scheme in the specific case such as nephanalysis and volcanic ash 79
80 Practical training to create RGB composite imagery by SATAID 80
81 Practical training to create RGB composite imagery by SATAID SATAID has a function of coloring and compositing the plural imagery. SATAID, however, doesn t have configurations of gamma value. Some simple compositions are available even by SATAID. Let s move on to the next slide! 81
82 Practical training to create RGB composite imagery by SATAID Procedure for coloring and compositing imagery by SATAID 4 Select type of images and colors 1 Select Gray 2 Push Color 3 Hold down Ctrl and then select Mix 82
83 Practical training to create RGB composite imagery by SATAID Let s try to make following two RGB composite imagery by SATAID! o o Clouds Convection R : VIS0.8 G : VIS0.8 B : IR10.8 Night Microphysics R : IR12.0 IR10.8 indicated as "SP" on SATAID G : IR10.8 IR3.9 indicated as "S2" on SATAID B : IR10.8 (Reverse) 83
84 Summary of RGB composite imagery Pros & cons Drawbacks A phenomenon does not always correspond to the allocated color. Distinction by movement and shift on imagery is required according to the situation. The skill for analysis is required. The examples introduced to you this time are the schemes adjusted for EUMETSAT's MSG to see easily. The gradation adjustment and gamma correction will be required for imagery of the next Himawari satellites. Advantages o Simple process by composition of images enable to create RGB imagery. o Various information are derivable by one RGB image. o RGB imagery retain natural texture of single channel images. 84
85 References EUMETSAT, 2005 : METEOSAT SECOND GENERATION SATELLITES Innovation for a reliable service,eumetsat,darmstadt, 2-9. Kerkmann, J., 2004 : APPLICATIONS OF METEOSAT SECOND GENERATION (MSG) RGB IMAGES: PART 02 INTRODUCTION TO RGB COLOURS (PowerPoint, Personal donation). Kerkmann, J., D. Rosenfeld and M. König, 2005 : APPLICATIONS OF METEOSAT SECOND GENERATION (MSG) RGB IMAGES: PART 03 CHANNEL SELECTION AND ENHANCEMENTS (PowerPoint, Personal donation). Kerkmann, J., D. Rosenfeld and G. Bridge, 2005 : APPLICATIONS OF METEOSAT SECOND GENERATION (MSG) RGB IMAGES: PART 04 RGB COMPOSITES WITH CHANNELS AND THEIR INTERPRETATION (PowerPoint,Personal donation). Kerkmann, J., 2005 : APPLICATIONS OF METEOSAT SECOND GENERATION (MSG) RGB IMAGES: PART 05 RGB COMPOSITES WITH CHANNEL 12 AND THEIR INTERPRETATION (PowerPoint, Personal donation). Kidder, S. Q. and T. H. V. Harr, 1995: Satellite Meteorology: An Introduction, Academic Press, Lensky, I., 2005 : User Guide for MSG_RGB Version 1.1 A Windows -based interactive software for research of cloud microphysics and cloud aerosol interaction with MSG SEVIRI data, Hebrew University of Jerusalem, Jerusalem, Roesli, H., J. Kerkmann, D. Rosenfeld and M. König, 2004 : Introduction to RGB image composites (PowerPoint, Personal donation). Rosenfeld, D. and I. M. Lensky, 1998: Satellite-based insights into precipitation formation processes in continental and maritime convective clouds, The Bulletin of American Meteorological Society 79, EUMETSAT website (The reference date: October 1, 2013) 85
86 Thank you! The End 86
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