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

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

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

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. http://www.meted.ucar.edu/satmet/goeschan/print/6_2_4_3.htm

The microphysics RGB in NinJo Microphysics (day) [0.67, 3.7-10.7, 10.7i]

RGB examples to differentiate between water and ice clouds

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

Color enhanced imagery at 3.7 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

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

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

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.

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)

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

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).

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

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.

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

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].

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.

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

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].

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.

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

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.

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

Thank You! Questions?

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