Day Snow-Fog RGB Detection of low-level clouds and snow/ice covered area

Similar documents
Day Microphysics RGB Nephanalysis in daytime. Meteorological Satellite Center, JMA

Himawari-8 True Color RGB

Ash RGB Detection of Volcanic Ash

How to display RGB imagery by SATAID

Applications of multi-spectral satellite data

Fog detection product

Introduction of JMA VLab Support Site on RGB Composite Imagery and tentative RGBs

New capabilities with high resolution cloud micro-structure facilitated by MTG 2.3 um channel

Applications of the SEVIRI window channels in the infrared.

Overview of Himawari-8/9

RGB in Broadcast Meteorology

Lecture 19: Operational Remote Sensing in Visible, IR, and Microwave Channels

Benefits of the new-generation Himawari-8 geostationary satellite for the Asia-Pacific region. Toshihiko HASHIDA Japan Meteorological Agency (JMA)

4.1 New Generation Satellite Data and Nowcasting Products: Himawari

Himawari 8/9 data distribution/dissemination plan

" The usefulness of RGB products: the perspective of the Australian Bureau of Meteorology "

RGB Products: an easy and practical way to display multispectral satellite data (in combination with derived products)

Meteorological Satellite Image Interpretations, Part III. Acknowledgement: Dr. S. Kidder at Colorado State Univ.

Preparation for Himawari 8

Advanced Geostationary Observations for the OzEWEX Community. Leon Majewski Bureau of Meteorology

Aviation Hazards: Thunderstorms and Deep Convection

INTERPRETATION OF MSG IMAGES, PRODUCTS AND SAFNWC OUTPUTS FOR DUTY FORECASTERS

Moisture, Clouds, and Precipitation: Clouds and Precipitation. Dr. Michael J Passow

FUTURE PLAN AND RECENT ACTIVITIES FOR THE JAPANESE FOLLOW-ON GEOSTATIONARY METEOROLOGICAL SATELLITE HIMAWARI-8/9

RGB Experts and Developers Workshop - Introduction Tokyo, Japan 7-9 Nov 2017

Inter-comparison MTSAT-2 & Himawari-8

NOWCASTING PRODUCTS BASED ON MTSAT-1R RAPID SCAN OBSERVATION. In response to CGMS Action 38.33

Recent Update on MODIS C6 and VIIRS Deep Blue Aerosol Products

MSG/SEVIRI CHANNEL 4 Short-Wave IR 3.9 m IR3.9 Tutorial

JMA s atmospheric motion vectors

P3.24 EVALUATION OF MODERATE-RESOLUTION IMAGING SPECTRORADIOMETER (MODIS) SHORTWAVE INFRARED BANDS FOR OPTIMUM NIGHTTIME FOG DETECTION

International Cooperation in Operational Environmental Satellites: The U.S. Experience

Monitoring Sand and Dust Storms from Space

Remote Sensing of Precipitation

RGB Experts and Developers Workshop 2017 Tokyo, Japan

Fog Detection(FOG) Algorithm Theoretical Basis Document

Ice fog: T~<-10C RHi>100%

McIDAS support of Suomi-NPP /JPSS and GOES-R L2

Climate Dynamics (PCC 587): Feedbacks & Clouds

SAFNWC/MSG SEVIRI CLOUD PRODUCTS

THE FEASIBILITY OF EXTRACTING LOWLEVEL WIND BY TRACING LOW LEVEL MOISTURE OBSERVED IN IR IMAGERY OVER CLOUD FREE OCEAN AREA IN THE TROPICS

Climate Change: Global Warming Claims

Himawari-8/9 and GCOM-C Non-Meteorological Application Opportunities

Rapidly Developing Cumulus Area RDCA detection using Himawari-8 data

ECNU WORKSHOP LAB ONE 2011/05/25)

LANDSAF SNOW COVER MAPPING USING MSG/SEVIRI DATA

Improvement of Himawari-8 observation data quality

Current status and plans of JMA operational wind product

Remote Sensing in Meteorology: Satellites and Radar. AT 351 Lab 10 April 2, Remote Sensing

Satellite observation of atmospheric dust

INTERPRETATION GUIDE TO MSG WATER VAPOUR CHANNELS

A) usually less B) dark colored and rough D) light colored with a smooth surface A) transparency of the atmosphere D) rough, black surface

VALIDATION OF INSAT-3D DERIVED RAINFALL. (Submitted by Suman Goyal, IMD) Summary and Purpose of Document

Unit 4 Lesson 2 Clouds and Cloud Formation. Copyright Houghton Mifflin Harcourt Publishing Company

Climate & Earth System Science. Introduction to Meteorology & Climate. Chapter 05 SOME OBSERVING INSTRUMENTS. Instrument Enclosure.

Usage of McIDAS V with GOES R AWG products

Clouds on Mars Cloud Classification

Condensation: Dew, Fog, & Clouds. Chapter 5

Basic cloud Interpretation using Satellite Imagery

MSG system over view

Meteorology Today. 1 Aug st Lt Libby Haynes Capt Kim Mevers

Lecture 2-07: The greenhouse, global heat engine.

Comparison of cloud statistics from Meteosat with regional climate model data

The use of Direct Broadcast Processing System in Poland

Operational Uses of Bands on the GOES-R Advanced Baseline Imager (ABI) Presented by: Kaba Bah

Recent Improvement of Integrated Observation Systems in JMA

Observations needed for verification of additional forecast products

Answers to Clicker Questions

Tonga Country Report

Weather Forecasts and Climate AOSC 200 Tim Canty. Class Web Site: Lecture 27 Dec

ESTIMATION OF THE SEA SURFACE WIND IN THE VICINITY OF TYPHOON USING HIMAWARI-8 LOW-LEVEL AMVS

AOMSUC-6 Training Event

A 2016 CEOS Chair Initiative. Non-meteorological Applications for Next Generation Geostationary Satellites

Condensation Nuclei. Condensation Nuclei 2/10/11. Hydrophobic Water-repelling Oils, gasoline, paraffin Resist condensation, even above 100% RH

Khalid Y. Muwembe UGANDA NATIONAL METEOROLOGICAL AUTHORITY (UNMA)

Non-meteorological Applications for Next Generation Geostationary Meteorological Satellites

The NASA Short-term Prediction Research and Transition (SPoRT) Center:

Lecture 4: Radiation Transfer

EUMETSAT PLANS. Dr. K. Dieter Klaes EUMETSAT Am Kavalleriesand 31 D Darmstadt Germany

Unit: Weather Study Guide

Spectral reflectance: When the solar radiation is incident upon the earth s surface, it is either

Preparation for FY-4A. (Submitted by Xiang Fang, CMA)

Final Review Meteorology

according to and water. High atmospheric pressure - Cold dry air is other air so it remains close to the earth, giving weather.

CLIMATE CHANGE Albedo Forcing ALBEDO FORCING

REVISION OF THE STATEMENT OF GUIDANCE FOR GLOBAL NUMERICAL WEATHER PREDICTION. (Submitted by Dr. J. Eyre)

Lecture 4b: Meteorological Satellites and Instruments. Acknowledgement: Dr. S. Kidder at Colorado State Univ.

Himawari 8: Experiences and Lessons Learned. Daisaku Uesawa Meteorological Satellite Center (MSC) Japan Meteorological Agency (JMA)

From Space-Based Measurements to Climate Data Records

DATA BROWSING AND ANALYSIS TOOL FOR MTSAT/LRIT. Ryoji Kumabe

JMA s ATMOSPHERIC MOTION VECTORS In response to Action 40.22

PRECIPITATION ESTIMATION FROM INFRARED SATELLITE IMAGERY

The Delaware Environmental Monitoring & Analysis Center

Intercomparison of Satellite Precipitation Products for Different Cloud Types

Topics: Visible & Infrared Measurement Principal Radiation and the Planck Function Infrared Radiative Transfer Equation

WMO SPACE PROGRAMME ONLINE RESOURCES (Product Access Guide, Data Access Page, Tools Page) (Submitted by the Secretariat)

The Climatology of Clouds using surface observations. S.G. Warren and C.J. Hahn Encyclopedia of Atmospheric Sciences.

Satellite Meteorology. Protecting Life and Property Around the World

The current status of FY-3D

Interpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation

Transcription:

JMA Day Snow-Fog RGB Detection of low-level clouds and snow/ice covered area Meteorological Satellite Center, JMA

What s Day Snow-Fog RGB? R : B04 (N1 0.86) Range : 0~100 [%] Gamma : 1.7 G : B05 (N2 1.6) Range: 0~70 [%] Gamma : 1.7 2015-02-26 03UTC B : B07(I4 3.9) (Solar component) Range : 0~30 [%] Gamma : 1.7

Components of Day Snow-Fog RGB scheme Channel Himawari-8/ -9 MTSAT-1R/-2 MSG Physical Properties 1 0.46 μm 2 0.51 μm 3 0.64 μm 0.68 μm 0.635 µm vegetation, aerosol B vegetation, aerosol G low cloud, fog R 4 0.86 μm 0.81 µm vegetation, aerosol 5 1.6 μm 1.64 µm cloud phase 6 2.3 μm particle size 7 3.9 μm 3.7 μm 3.92 µm low cloud, fog, forest fire 8 6.2 μm 6.8 μm 6.25 µm mid- and upper level moisture 9 6.9 μm mid- level moisture 10 7.3 μm 7.35 µm mid- and upper level moisture 11 8.6 μm 8.70 µm cloud phase, SO2 12 9.6 μm 9.66 µm ozone content 13 10.4 μm 10.8 μm 10.8 µm 14 11.2 μm 15 12.4 μm 12.0 μm 12.0 µm cloud imagery, information of cloud top cloud imagery, sea surface temperature cloud imagery, sea surface temperature 16 13.3 μm 13.4 µm cloud top height Visible Near Infrared Infrared This scheme is displayed by compositing two near infrared channels (B05(N2 1.6), B04(N1 0.86) ) and infrared channel (B07(I4 3.9) ). Please note that 3.9 micron image is solar component (excepted infrared radiation component). These channels have reflection characteristics of near infrared band for land/ sea surface conditions (such as snow/ ice covered area ) respectively. A set of RGB Day Snow-Fog scheme (RGB: B04/B05/B07r) R : B04 (N1 0.86) Range : 0~100 [%] Gamma : 1.7 G : B05 (N2 1.6) Range : 0~70 [%] Gamma : 1.7 B : B07(I4 3.9) (Solar component) Range : 0~30 [%] Gamma : 1.7

Characteristics and Basis of Three Components B04 as well as B03, has high reflectivity for snow/ice covered area and clouds, sea surface looks dark. On RGB imagery, high level clouds consisting of ice particles, snow/ice and sea ice, which are low reflectivity on green B05 and blue B07, are displayed in red color. Low-level clouds (water clouds) which are high reflectivity on the three colored images, are displayed in white-grey color. R : B04 (N1 0.86) Range : 0~100 [%] Gamma : 1.7 Reflection characteristic of B07 (solar component) depends on the phase and size of cloud particles as well as B05. Smaller particle has higher reflectivity. In the case of ice phase, the reflectivity is relatively low. In the case of water droplets (same size as previous ice particle), the reflectivity is relatively high. High-level clouds consisting of ice crystals, snow/ ice and sea ice appear in relatively dark color. Low clouds consisting of droplets appear in bright color. Reflection characteristic of B05 depends on the phase and size of cloud particles Reflectivity is small for large cloud particles. Ice cloud particles absorb light beams, and reflectivity is small. High-level clouds consisting of ice particles, snow/ice and sea ice are displayed in darker color. Low-level clouds consisting of droplets are displayed in bright color. G : B05 (N2 1.6) Range : 0~70 [%] Gamma : 1.7 B : B07(I4 3.9) (Solar component) Range : 0~30 [%] Gamma : 1.7

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 - Bright, thick - Small ice particles *or thick, high-level lee cloudiness with small ice particles - Large droplets - Small droplets Ocean Vegetation Desert Snow Note: Based on SEVIRI/EUMETSAT interpretation 5

Example of Day Snow-Fog RGB Fog/ low-level clouds after the rainfall in Kanto Plain, Japan Himawari-8 B03 VIS 2015-04-06 00UTC Himawari-8 B13 IR10.4 + Synop 2015-04-06 00UTC Weather Chart ASAS 2015-04-06 00UTC Fog/ low-level clouds (Upper image) Smooth, whitish area correspond to fog or low-clouds in B03(VS 0.64) image. (Upper right image) B13(IR 10.4) image overlapped ground observations. The fog was observed at some stations. The fog or low-clouds are not distinct in B13(IR 10.4) image.

Example of Day Snow-Fog RGB Fog/ low-level clouds after the rainfall in Kanto Plain, Japan Himawari-8 Day Snow-Fog 2015-04-06 00UTC Himawari-8 B03 VIS 2015-04-06 00UTC A B C Fog/ low-level clouds Smooth, whitish area corresponds to fog or low-level clouds extended to Tokyo Bay(A), Bo-so Peninsula(B) and Pacific Ocean(C). - Large droplets - Small droplets Ocean

Example of Day Snow-Fog RGB Fog/Low-level Clouds of Setonai-kai (Inland Sea of Japan) Himawari-8 Day Snow-Fog 2015-03-17 03UTC (Lower right) Fog/ low-level clouds were observed at some stations (around red oval). However, fog/ low-level clouds are not clear in the IR image. Fog or Lowlevel clouds (Upper and lower left) Smooth, whitish areas in Day Snow-Fog RGB correspond to whitish fog/ low-level clouds in B03 visible image. Himawari-8 B03 VIS 2015-03-17 03UTC Himawari-8 B13+Synop 2015-03-17 03UTC

Example of Day Snow-Fog RGB Frontal zone Himawari-8 Day Snow-Fog 2015-04-03 03UTC Low-level cloud with fog around frontal zone Deep precipitating cloud (precip. not necessarily reaching the ground) High-level cloud Deep precipitating cloud Bright, thick, small ice particles - Large droplets - Small droplets Organized thick cloud corresponding to frontal zone Ocean Weather Chart ASAS 2015-04-03 00UTC Himawari-8 B03 VIS + Synop 2015-03-16 03UTC

Example of Day Snow-Fog RGB Sea ice and Snow/Ice covered area Reddish area on the ocean corresponds to sea ice/ drift ice. It's easy to distinguish whitish low-level clouds. Sea ice distribution chart for Hokkaido region 2015-2-27 Himawari-8 Day Snow-Fog 2015-02-26 03UTC - Large droplets - Small droplets Snow Ocean Himawari-8 B03 VIS 2015-02-26 03UTC Sea ice and drift ice are clear on visible image, but the distinction of low-level clouds is slightly difficult without animation.

Low-level cloud Example of Day Snow-Fog RGB Sea ice and Snow/Ice covered area Himawari-8 Day Snow-Fog 2015-02-26 03UTC Sea ice/ Drift ice - Large droplets - Small droplets Snow Ocean Slightly thick low-level, water cloud Reddish area on the ground surface corresponds to snow/ ice covered area. It's easy to distinguish (whitish) snow/ ice covered area from low-level clouds.

Example of Day Snow-Fog RGB Sea ice and Snow/Ice covered area Himawari-8 Day Snow-Fog 2015-02-26 03UTC Interpretation of Colors for Natural Color RGB High-level ice clouds Low-level water clouds Veg. Land Snow Note: Based on SEVIRI/EUMETSAT interpretation Himawari-8 Natural Colors 2015-02-26 03UTC It's easy to distinguish sea ice/ drift ice and snow/ ice covered area on both of two RGBs. Better identification of thickness of low-level clouds on Day Snow-Fog, better identification of vegetation distribution on Natural Colors. It's effective to compare and use the RGB images according to different application!

RGB Day Snow-Fog RGB Detection of low-level clouds and snow/ice covered area This RGB scheme will (summary) make easy to distinguish between low clouds and snow/ice rather than only VIS but in day-time only be so far, unavailable for SATAID, because this includes the solar reflectance component