1. RGB Applications for Cloud Microphysical Analysis in NinJo
Victor Chung
SAAWSO Project Workshop
April 22-24, 2013
National Lab for Nowcasting and Remote Sensing Meteorology
MSC Ontario
Environment Canada

2. Objective
To demonstrate how to use RGB imageries in NinJo to perform daytime cloud microphysical analysis

3. Why do we need RGB?
...because you can see more with an RGB.....

4. Role of 3.9 µm in RGB
Reflection at 3.9 µm is sensitive to cloud phase and cloud particle sizes.
Continental cloud droplet size: a few µm to up to 15 µm. Note: cloud drop sizes varies horizontally and vertically.
Maritime cloud droplet size: 10 µm to up to 25 µm.
Cloud ice crystal size: ~ 50 µm (?). Sizes varies horizontally and vertically. Tiny ice crystals can easily be carried to a higher altitude by updraft.
Clouds (such as St, Sc) are much darker (i.e. warmer, more reflective) than ice clouds.
Marine Sc (large water droplets) is brighter (i.e cooler, less reflective) than Sc (smaller) over land.

5. The microphysics RGB in NinJo
Microphysics (day)
[0.67, , 10.7i]

6. RGB examples to differentiate between water and ice clouds

7. Color enhanced imagery at 10.7 µm.B F
A: IR (-23 to -29C); NIR (12 to 20C); Diff (~50 C).
B: IR (-25 to -35C); NIR (8 to 20C); Diff (~17 to 48 C).
C: IR (-15 to -20C); NIR (10 to 20C); Diff (~23 to 45 C).
D: IR (-20 to -25C); NIR (~15C); Diff (~23 to 30 C).
E: IR (-20 to -25C); NIR (-13 to -15C); Diff (7 to 10 C).
F: IR (-10 to -22C); NIR (-14 to -23C); Diff (6 to 15 C). D C E

8. Color enhanced imagery at 3.7 µmB F
A: IR (-23 to -29C); NIR (12 to 20C); Diff (~50 C).
B: IR (-25 to -35C); NIR (8 to 20C); Diff (~17 to 48 C).
C: IR (-15 to -20C); NIR (10 to 20C); Diff (~23 to 45 C).
D: IR (-20 to -25C); NIR (~15C); Diff (~23 to 30 C).
E: IR (-20 to -25C); NIR (-13 to -15C); Diff (7 to 10 C).
F: IR (-10 to -22C); NIR (-14 to -23C); Diff (6 to 15 C). D C E

9. Let us look at cloud masses A, D, E, and B

10. Cloud mass A Appearance in channel 10.7 and 3.7 µm
cold at IR but quite warm at NIR  super-cooled water droplets
T_10.7: -23 to -29 C
3.7 µm
IR (-23, -29)C; NIR (12, 20)C.
Possible embedded instability (ACC) with tops extending to mid levels (cold).
Very warm at 3.9 µm which implies that clouds consists of super cooled small water droplets.
T_3.9: 12 to 20 C

11. Cloud mass A Appearance in RGB
Super-cooled
water droplets
1. Albedo in the range of 60 to 70 %.
2. RGB: strong red (vis), very strong green (nir-ir), and mid to high blue (ir). Final color is yellowish green.
3. It should be noted that small water droplets will produce a very large nir-ir difference and thus very strong green.

12. Cloud mass D & E Appearance in 10.7 and 3.7 µm
D: cold at IR, warm at NIR
 Super-cooled droplets
E: cold at IR, cold at NIR
 Ice particles
D (-20 to -25 C)
E (-20 to -25 C)
3.7 µm D:
IR (-20, -25)C; NIR (around 15)C.
Clouds associated with the passage of a cold front. Possible embedded ACC with tops extending to mid levels (cold).
Warm at 3.9 µm which implies that clouds consist of super cooled small water droplets.
Implication of icing. E:
IR (-20, -25)C; NIR (-13, -15)C.
Cold at 3.9 µm which likely means that clouds consisting of ice crystals. Ice nucleation has already taken place.
D (~15 C)
E (-13 to -15 C)

13. Histogram Plots for 10. 7 and 3
Histogram Plots for 10.7 and 3.7 µm Channels for a Line Across Cloud Masses D and E
10.7 µm (IR)
3.9 µm (NIR)
Small temperature
Range at IR
Two distinct peak at
NIR
Ice
Water

14. Cloud masses D & E Appearance in RGB
E: ice
RGB D E
D: super-cooled water D:
1. Albedo in the range of 70 to 90 %.
2. RGB: strong red (vis), very strong green (nir-ir), and mid to high blue (ir). Final color is yellowish green.
3. It should be noted that small water droplets will produce a very large nir-ir difference and thus very strong green. E:
Albedo in the range of 80 to 90 %.
2. RGB: Very strong red (vis), lower green (nir-ir), and mid to high blue (ir). Final color is pink.
3. It is likely that ice nucleation has already taken place. Consequently the nir-ir difference will be much smaller because of low reflectance at nir for ice crystals (unless for very small ice crystal size, see slide 2).

15. Let us look at cloud mass B evolution from 19 to 21z

16. Cloud mass B evolution from 19 to 21Z (at 19Z)
Ice or water?
10.7 µm
3.7 µm
It is water!
0.65 µm
RGB2
Extensive line of clouds are associated with the passage of a cold front.
IR (-20, -30)C; NIR (10, 20)C, VIS (60, 75).
Cloud tops are pretty cold (near -30 C), but it is very warm at 3.9 µm. This likely implies that ice nucleation has not started and clouds consists of mainly small water droplets.
4. RGB: strong red (vis), very strong green (nir-ir), and mid to high blue (ir). Final color is yellowish green.
5. It should be noted that small water droplets will produce a very large nir-ir difference and thus very strong green.

17. Scatter Plots of 3. 7 versus 10
Scatter Plots of 3.7 versus 10.7 µm Channels for an Area over Cloud Mass B at 19Z
IR  well below freezing
NIR  warm  water
Conclusion: super-cooled
cloud droplets

18. Histogram Plots for 10. 7 and 3
Histogram Plots for 10.7 and 3.7 µm Channels for an Area over Cloud Mass B at 19Z
10.7 µ
3.7 µm
Ch4 – range [-32, -19]; Mean [-29]; Std [1.9].
Ch2 – range [8, 21]; Mean [15]; Std [2.2].

19. Ice nucleation is underway!
Cloud mass B at 20Z
Ice nucleation is underway!
10.7 µm (IR)
3.7 µm (NIR)
0.65 µm
RGB
As cold front continues to advance eastwards, note the “brightness temperatures” change at 3.9 µm. Two bands of much colder (-10, -15) signals just develop at 2000Z. This sharp drop at the 3.9 µm signal is likely a hint of the start of ice nucleation.
The RGB2 images also give the ice nucleation signal as two bands of pink lines develop.

20. Scatter Plots of 3.7 vs 10.7 µm Channels for an Area over Cloud Mass B at 20Z
Large NIR
spread
Ice nucleation in process
(water drops + ice crystals)
Small IR
spread

21. Histogram Plots for 10. 7 and 3
Histogram Plots for 10.7 and 3.7 µm Channels for an Area over Cloud Mass B at 20Z
10.7 µm
3.7 µm
Ch4 – range [-32, -15]; Mean [-27]; Std [2.5].
Ch2 – range [-16, 18]; Mean [-0.6]; Std [9.8].

22. Clouds consists of mainly ice crystals
Cloud mass B at 21Z
Clouds consists of mainly ice crystals
10.7 µm
3.7 µm
0.65 µm
RGB
More widespread of cold signals (~ -15C) at the 3.9 µm suggesting of more ice nucleation.
Same signal of ice nucleation can also found in the RGB2 image.

23. Scatter Plots of 3.7 vs 10.7 µm Channels for an Area over Cloud Mass B at 21Z
More pixels with NIR
temperature shift to
The colder side

24. Histogram Plots for 10. 7 and 3
Histogram Plots for 10.7 and 3.7 µm Channels for an Area over Cloud Mass B at 21Z
10.7 µm
3.7 µm
Ch4 – range [-29, --17]; Mean [-25]; Std [2.1].
Ch2 – range [-17, 7]; Mean [-9.4]; Std [5.6].
Is the warming of 10.7 µm an indication of latent heat release during the ice nucleation processes? Hard to draw a solid conclusion. We need to track the same cloud mass and also need to consider adiabatic cooling or warming due to vertical motion.

25. Conclusion
The special characteristics of the 3.7 um allows us to create a useful RGB for cloud microphysical analysis
Several examples have been used to demonstrate how to use this RGB operationally to differentiate between water and ice clouds
This RGB can be applied for summer storm analysis, for example ice nucleation and lightning
This RGB can be used in conjunction with other icing products for better cloud icing detection
Ice
Water

26. Thank You!
Questions?

28. Outline --- this slide will not be shown
Thesis (idea convey)
RGB imagery helps forecasters to monitoring cloud microphysical properties
Good microphysical analysis helps detecting icing, and convective storm analysis
The Body
A list of examples for cloud microphysical analysis
Conclusion
Restate the thesis
- RGB should be used more for cloud top microphysical analysis to improve our weather monitoring capability
Action for future works
Real-time applications for summer and winter storms
Use in conjunction with icing product
Objective
To demonstrate how to perform cloud microphysical analysis using RGB imageries in NinJo
Introduction
Opener
With RGB imagery, you can see things that can not be seen with a single channel imagery
Characteristics of 3.9 um and its role on RGB imagery
Topic
- Use of RGB in NinJo for cloud microphysics analysis