RGB Products: an easy and practical way to display multispectral satellite data (in combination with derived products)
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1 RGB Products: an easy and practical way to display multispectral satellite data (in combination with derived products) Dr. Jochen Kerkmann Training Officer EUMETSAT
2 Multi-channel GEO satellites today Him-08 (140.7 E) GOES-16 (89.5 W) Met-10 (0) Met-08 (41.5 E) Credits: HP Roesli 20 March 2017, First Global Airmass RGB Composite
3 How to display multispectral data? Why do we need RGB products, when we have derived (cloud) products?
4 Multispectral view of tomatoes & clouds No rain Rain Credits: Prof. Danny Rosenfeld, Jerusalem (HUJ)
5 MODIS Airborne Simulator-L1B Jul :44 GMT Caribbean Sea Flight level 20 km Resolution 50 m at NADIR Swath ± 45, With=37 km Red: 0.63 mm Green: 2.06 mm Blue: 2.11/2.21 mm Credits: Prof. Danny Rosenfeld, Jerusalem (HUJ) 12/20/2017
6 Cloud Properties seen in Day Microphysics RGB Cirrus with large crystals Nimbus Layer clouds of large water drops Dissipating Nimbus warm large ice particles snow surface Mixed phase layer clouds Snow in the air downhill the stau cloud after its supercooled cloud drops evaporated 8 October 2003, 12:00 UTC Source: D. Rosenfeld
7 Comparison 1: RGBs vs Cloud Type Product 2 1 Cloud Type Product Texture gets lost, no cloud phase info Met-8, 21 March 2007, 12:00 UTC Day Microphysics RGB
8 Comparison 2: RGBs + Ash Product Best use: RGBs + Derived Product Derived product (ash mask) overlaid on Ash RGB 15 April 2010, 09:00-15:00 UTC Source: M. Pavolonis
9 Main Improvements from multi-channel (GEO) Imagers
10 New Generation Improvements: Clouds at Night India Fog/Low Stratus (night) AHI IR10.4 Channel AHI Night Micro RGB
11 New Generation Improvements: Vegetation Grassland Rice Fields MFG VIS Channel MSG Natural Colours RGB
12 New Generation Improvements: Cloud / Snow Discrimination Fog MFG VIS Channel MSG RGB NIR1.6, HRV, HRV
13 New Generation Improvements: Haze, Dust, Ash, Smoke Dust Cloud MFG IR Channel MSG Dust RGB
14 New Generation Improvements: Cloud Particle Size Small Ice Particles MFG IR Channel MSG Convection RGB
15 New Generation Improvements: Thin Clouds Thin Ci Clouds GOES-16 Nat. Colour RGB (non-operational data) GOES-16 Dust RGB
16 New Generation Improvements: Cloud Classification Thin High Clouds Thick High Clouds Low Clouds GOES-16 Cloud Type RGB (non-operational data) GOES-16 Dust RGB
17 New Generation Improvements: Moisture Boundaries Diurnal development of the sea-breeze front in Yemen
18 New Generation Improvements: Wind Shear Observation Himawari-8 product courtesy JMA/CIMSS Ash RGB Himawari-8 data (2km resolution) MTSAT images courtesy JMA/BOM 11 micron IR MTSAT data (4km resolution) Klyuchevskoy 3.7 micron NIR MTSAT data (4km resolution) micron IR MTSAT data (4km resolution) Raung Plume, Java (10 th July 2015)
19 GUIDELINES FOR CREATING RGBs
20 Rules for Creating Good RGB Products Channel Select three channels or channel differences that represent three different physical properties!!! Example: MSG Window Channels Main Cloud Physical Properties (clouds, NADIR viewing) 01 (VIS 0.6) optical thickness, amount of cloud water and ice 02 (VIS 0.8) optical thickness, amount of cloud water and ice 03 (NIR 1.6) optical thickness, particle size & shape, phase 04 (MIR 3.9) Day-time: top temperature, particle size & shape, phase Night-time: top temperature (very noisy below -50 C) 07 (IR 8.7) top temperature 09 (IR 10.8) top temperature 10 (IR 12.0) top temperature
21 Not Recommended RGB IR8.7, IR10.8, IR /12/ MSG-1, 21 January 2005, 12:00 UTC
22 Recommended RGB VIS0.8, IR3.9r, IR /12/ MSG-1, 21 January 2005, 12:00 UTC
23 RGB PRODUCTS FOR OPERATIONAL FORECASTING
24 Most important RGBs (for Operational Forecasting) 24-h Microphysics (Dust) RGB Airmass RGB 28 January 2013, 12:00 UTC
25 High PV Anomaly Deformation Zone Jet (polar) Jet (subtropical)
26 Example: Jet Streaks Him-08, 17 October 2017, 12:00 UTC
27 Example: Jet Streaks + Moisture Rivers Him-08, 17 October 2017, 12:00 UTC
28 Example: Deformation Zone
29 Example: Deformation Zone COL X COL X X N X N X N N N N
30 Example: Deformation Zone Ash cloud from Iceland as tracer Source: HP. Roesli
31 Example: Two PV anomalies merge over Europe (Fujiwhara effect) Met-10, 5-6 April 2017
32 Example: Low Clouds Comparison Met-8 vs Met-9 1 May 2007, 14:00 UTC Source: HP. Roesli
33 Example: Dust crosses the Atlantic Ocean Source: HP. Roesli June 2014
34 Example: Volcanic Ash (Etna, Italy) Source: HP. Roesli 12 August 2011, 09:00-13:00 UTC
35 Example: Thin Ice Clouds (Lee Clouds) MSG-1, 12 November 2006, 23:00 UTC
36 Example: Cloud Phase 20/12/ Ice Water cloud cloud Met-8, 16 Aug 2006, 04:00 UTC
37 OTHER RGB PRODUCTS
38 Day Microphysics RGB, 19 January 2017, Example of polluted airmasses L H Snow L
39 Convection RGB, dust changes cloud microphysics small ice particles (IR3.9r > 10%) 24-h Dust Day Microphysics Convective Storms Met-8, 22 February 2007, 12:00 UTC
40 Night Microphysics RGB, 19 January 2017, snow detection at night Snow Stratus Mid-level water clouds Snow 17 January 2006, 16:00 UTC
41 Convection RGB, small ice particles in severe thunderstorms Multispectral View of Convective Storms HRV Met-8, 29 June 2006 RGB Convective Storms
42 New Developments Presented at 2017 RGB workshop
43 Standard Tropical
44 Tropical Airmass RGB (tuned for OTs) Overshooting Tops in Typhoon Koppu (Pacific) 15 October 2015, HIM-08, AHI, Tropical Airmass RGB 2 km / 2.5 minutes
45 Tuning of AHI Dust RGB (for dust, cloud phase, moisture) Red: IR12.4 IR10.4, Green: IR11.2 IR8.6, Blue: IR10.4 (uses 4 (not 3) IR channels) G B A F A: thick dust B: thin dust C thin Cirrus D: Thick Cirrus E: Mid clouds F: Low clouds G: thin dust C D E Credits: D. Gencic
46 Him-08 Tuned Dust RGB Convective outflow boundary India
47 Him-08 Ash RGB (source: CIRA) Kamchatka
48 Him-08 Ash RGB (source: CIRA) Animation of volcanic plume and contrails
49 Him-08 Tuned Dust RGB moist Australia thin ice dry ice water water ice
50 New Him-08 RGB: Cloud Phase RGB The dilemma of 4 IR window channels - Tuning of the Dust RGB to ABI / AHI - J. Kerkmann, EUMETSAT Red: IR12.4-IR10.4 (-6, +4 K) Green : IR11.2-IR8.6 (0, +10 K) Blue: IR10.4 (273, 300 K) AHI, Dust RGB (tuned) Him-08, AHI, Cloud Phase RGB ( )
51 Animation Cloud Phase RGB, Australia
52 GOES-16 Cloud Phase RGB (non-operational data) Cloud Phase RGB Convection RGB Supercell, Texas, 16 May 2017, 21:27 23:02 UTC (5 min intervals)
53 Fires in Australia, AHI, New Fire Temperature RGB October 2017 Temperature Level Credits: CIRA
54 Him-08 True Colour RGB (source: CIRA) A wall of pollution crosses the Sea of Japan May 2017
55 Him-08 True Colour RGB (source: CIRA) Spiegel Online: Smog alarm in India 7 November 2017, 03:20 UTC
56 Smog in India Him-08 Geo Colour RGB (source: CIRA)
57 Him-08 True Colour RGB (source: CIRA) Spiegel Online: Smog alarm in India 7 November 2017, 09:30 UTC
58 GOES-16 True Colour RGB (source: CIRA) (non-operational data) Jose Maria dust smoke 21 September 2017, 13:45 UTC
59 MODIS image (NASA) Him-08 Dust RGB (source: eport, EUMeTrain) High level smoke Lake Baikal 23 June 2017, 12:00 UTC
60 Him-08 Dust RGB (source: eport, EUMeTrain) Russia (Siberia) Very cold land surfaces 27 January 20176, 06:00 UTC
61 Him-08, Convection RGB (source: JMA) High-base convection India 2 May 2016, 02:30-12:00 UTC
62 Him-08, Convection RGB (source: eport, EUMeTrain) Australia High Supercooled Clouds 28 September 2017, 00:00 UTC
63 Impact of viewing angle on dust detection Source: eport Pro (EUMeTrain) Thin Dust Senegal Met-08 4 July 2017, 06:00 UTC Met-10 Dust (and smoke) often better detected at high viewing angles (NADIR view is not always the best one)
64 Impact of viewing angle on fog detection Source: eport Pro (EUMeTrain) Qatar Low viewing angle High viewing angle Met-08 Met-10 Thin low clouds look thicker (better contrast) when viewed at high viewing angles!
65 Limb cooling in Airmass RGB India Met-08 5 September 2016, 12:00 UTC Him-08 Bluish limb area In Met-08 on eastern side In Him-08 on western side
66 Summary (Dust RGB Animation, source: CIRA) High winds produce massive dust storm along China-Mongolia border - 3 May
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