Jun Park National Meteorological Satellite Center Korea Meteorological Administration

Similar documents
6 th ET SAT meeting, April 12 15, Geneva, Switzerland Satellite Programme of KMA

Current status of GK-2A AMV algorithm in NMSC/KMA

Current Status and Future Plan of KMA Satellite Program

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

Satellite P rogram s & Applications of K M A : Current & Future

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

Usage of McIDAS V with GOES R AWG products

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

Overview on GK-2A Data and Products

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

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

Radiative Transfer Model based Bias Correction in INSAT-3D/3DR Thermal Observations to Improve Sea Surface Temperature Retrieval

KOREA GEOSTATIONARY SATELLITE PROGRAM : COMMUNICATION, OCEAN, AND METEOROLOGICAL SATELLITE(COMS)

Planning for next generation geostationary satellites (GK-2A) of Korea Meteorological Administration (KMA)

How to display RGB imagery by SATAID

Status report on the current and future satellite systems by CMA. Presented to CGMS46-CMA-WP-01, Plenary session, agenda item D.1

Icing detection from geostationary satellite data over Korea and Japan using machine learning approaches

Remote sensing with FAAM to evaluate model performance

Status report on the. systems by KMA. Presented to CGMS-43 plenary session, agenda item [E.1]

Joint International Surface Working Group and Satellite Applications Facility on Land Surface Analysis Workshop, IPMA, Lisboa, June 2018

Future GOES (XGOHI, GOES-13/O/P, GOES-R+)

The Status Report of FY-2F

Polar winds from highly elliptical orbiting satellites: a new perspective

Physicochemical and Optical Properties of Aerosols in South Korea

From Space-Based Measurements to Climate Data Records

The current status of FY-3D

Interannual variability of top-ofatmosphere. CERES instruments

GEO New Mission and Synergy Joo-Hyung Ryu

Atmospheric Motion Vectors from Kalpana-1: An ISRO status

Preparation for Himawari 8

CLAVR-x is the Clouds from AVHRR Extended Processing System. Responsible for AVHRR cloud products and other products at various times.

Instrumentation planned for MetOp-SG

Brief introduction to. National Satellite Meteorological Center, CMA. Jinsong Wang Deputy Director-General NSMC/CMA

Introduction to Climate ~ Part I ~

ISRO Report on the Status of Current and future satellites. Presented to CGMS-44 WP-01 Plenary Session

EUMETSAT Activities Related to Climate

School on Modelling Tools and Capacity Building in Climate and Public Health April Remote Sensing

Update on SCOPE-Nowcasting Pilot Project Real Time Ocean Products Suman Goyal Scientist-E

Recent Update on MODIS C6 and VIIRS Deep Blue Aerosol Products

Climate Dynamics (PCC 587): Feedbacks & Clouds

The Cryosphere Radiative Effect in CESM. Justin Perket Mark Flanner CESM Polar Climate Working Group Meeting Wednesday June 19, 2013

Indian National (Weather) SATellites for Agrometeorological Applications

11 days (00, 12 UTC) 132 hours (06, 18 UTC) One unperturbed control forecast and 26 perturbed ensemble members. --

Application of Himawari-8 AHI Data to the GOES-R Rainfall Rate Algorithm

EPS-SG Candidate Observation Missions

A New Era: Three-Dimensional Observation and Service with Fully High Resolutions on FY-4 Platform are Coming Next Year

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

Impact of assimilating the VIIRS-based CrIS cloudcleared radiances on hurricane forecasts

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform

Summary Remote Sensing Seminar

Once a specific data set is selected, NEO will list related data sets in the panel titled Matching Datasets, which is to the right of the image.

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

MSG system over view

Interpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation

FY-2 On-orbit Operational Calibration Approach (CIBLE) and its Benefit to FY-2D/E AMV Products

Seeking a consistent view of energy and water flows through the climate system

Status of Indian Satellite Meteorological Programme

Arctic Weather Every 10 Minutes: Design & Operation of ABI for PCW

How good are our models?

Flux Tower Data Quality Analysis in the North American Monsoon Region

Atmospheric circulation analysis for seasonal forecasting

Direct radiative forcing due to aerosols in Asia during March 2002

IMPACT STUDIES OF HIGHER RESOLUTION COMS AMV IN THE KMA NWP SYSTEM

Introduction of the Hyperspectral Environmental Suite (HES) on GOES-R and beyond

THE EUMETSAT SATELLITE PROGRAMMES. Kenneth Holmlund EUMETSAT. R. Stuhlmann, P. Schlüssel, AN OVERVIEW FROM NOW TO THE FUTURE

TEMPO Aerosols. Need for TEMPO-ABI Synergy

5. General Circulation Models

MSG Indian Ocean Data Coverage (IODC) Jochen Grandell & Sauli Joro

Satellite-based estimate of global aerosol-cloud radiative forcing by marine warm clouds

Current Status of COMS AMV in NMSC/KMA

Status of the GeoKompsat-2A AMI rainfall rate algorithm

Satellite analysis of aerosol indirect effect on stratocumulus clouds over South-East Atlantic

Radiation in climate models.

GOES-R. Getting ready for the next generation earth observing system. Yuguang He AER April 10, 2015

Sand and Dust Monitoring in RA II

Saharan Dust Induced Radiation-Cloud-Precipitation-Dynamics Interactions

EUMETSAT GPRC Report. Jo Schmetz Tim Hewison, Sebastien Wagner, Rob Roebeling, Peter Miu, Simon Elliot, Harald Rothfuss, Bartolomeo Viticchie EUMETSAT

Applications of the SEVIRI window channels in the infrared.

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

Evaluation of Satellite and Reanalysis Products of Downward Surface Solar Radiation over East Asia

Lecture # 04 January 27, 2010, Wednesday Energy & Radiation

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

Lecture 3A: Interception

Infrared continental surface emissivity spectra and skin temperature retrieved from IASI observation

Ash RGB Detection of Volcanic Ash

The Application of Satellite Data i n the Global Surface Data Assimil ation System at KMA

Radiation Quantities in the ECMWF model and MARS

Climate Modeling Dr. Jehangir Ashraf Awan Pakistan Meteorological Department

IASI RADIANCES CLIMATOLOGY. Thierry PHULPIN* and Joaquin GONZALEZ** *Now at TIRSEC **Now at CNES/DLA

Radiation in the atmosphere

WMO OSCAR. Observing Systems Capability Analysis and Review Tool A building block of Rolling Requirements Review

Himawari-8 True Color RGB

Non-meteorological Applications for Next Generation Geostationary Meteorological Satellites

Solar Radiation and Environmental Biophysics Geo 827, MSU Jiquan Chen Oct. 6, 2015

Climate Modeling Research & Applications in Wales. John Houghton. C 3 W conference, Aberystwyth

Snow-atmosphere interactions at Dome C, Antarctica

Estimation of Wavelet Based Spatially Enhanced Evapotranspiration Using Energy Balance Approach

Land Surface Temperature Measurements From the Split Window Channels of the NOAA 7 Advanced Very High Resolution Radiometer John C.

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

Arctic Climate Change. Glen Lesins Department of Physics and Atmospheric Science Dalhousie University Create Summer School, Alliston, July 2013

Transcription:

KMA Implementation Plan for Satellite Climate products Jun Park National Meteorological Satellite Center Korea Meteorological Administration jun.park@kma.go.kr

Outline 1. Introduction : Current & Future KMA GEO Satellite 1.1 Current satellite products 1.2 Product validation & Quality monitoring 1.3 Future GEO-KOMPSAT-2A 2. Implementation plan of KMA 3. Evaluation of effect of GSICS Correction 3.1 GSICS correction results 3.2 SST improvements 4. Summary and Plan 2

Korean Satellite Development Roadmap 3

Current GEO Satellite(COMS) 4

COMS Products NMSC 16 Baseline Products : Development (2003 (2003--2010) and operation (2011~) AMV (Atmospheric Motion Vector) CLD SST LST (Land Surface Temperature) (Cloud Detection) (Sea Surface Temperature) SSI (Snow/Sea Ice) TPW (Total Precipitable Water) Fog CTT/CTH (Cloud Top Temperature/Height) UTH (Upper Tropospheric Humidity) COMS CA (Cloud Analysis) CSR (Clear Sky Radiance) AOD INS (Aerosol Optical Depth) (Insolation) AI (Aerosol Index) OLR (Outgoing Longwave Radiation) RI (Rain Intensity) 5

1.2 Product Validation & Quality Monitoring - Product Observation data Collocation COMS Quality monitoring MODIS Algorithm Improvement Daily Monthly Seasonal Statistical index Algorithm Theoretical Basis Document 6

COMS MI vs. GEO-KOMPSAT-2A (AMI) COMS Geo-KOMPSAT-2A 1 channel (achromatic) 4 channels (color) COMS Geo-KOMPSAT-2A Cloud/Precipitation (5 19) VI Radiation/aerosol (5 16) 2 channels SWIR 1 FD O Atmospheric Motion/Conditions(3 4 FD 4 channels 2 NH 6) 10 channels 10 NH Surface information(3 IR 11)... 4 Korea Every 2 min Korea 5 channels 16 channels 7 16 products 52 products

2. Implementation Plan of KMA Algorithms: In operation Similar algorithms with other GEO satellites Similar input data with other GEO satellites Algorithm: Developed (Albedo) Improvement needed (Precipitation, Cloud fraction, Snow) Different algorithms and inputs with other GEO satellites 8

PESK Implementation Plan, KMA Step 1-1 (3 years) Step 1-2 (3 years) Sea Surface Temperature Outgoing Longwave Radiation Insolation GSICS FCDRs TCDRs continuous generating Evaluation of effect of GSICS correction QC./QA, algorithm improvement Inter-satellite comparison of products EUMETSAT-KMA operating collaboration Preparation for GeoKompsat-2a / Future Korean LEO satellite Obtaining consistency and continuity between COMS and GeoKompsat-2a TCDRs Continuous improvement of TCDRs Continuous collaboration with SCOPE-CM working group SST OLR INS 0.5 0.8 10 W/m 2 70-100 W/m 2 1-5 km 2 15 km 2 15 km 2 2 daily daily daily 9

SESK Implementation Plan, KMA Albedo Precipitation Cloud Fraction Preparation for GeoKompsat-2a / Future Korean LEO satellite Algorithm development GSICS FCDRs continuous generating FCDRs TCDRs generating Evaluation of effect of GSICS correction QC./QA, algorithm improvement Inter-satellite comparison of products Obtaining consistency and continuity between COMS and GeoKompsat-2a TCDRs Continuous collaboration with SCOPE-CM working group Albedo Precipitation Cloud fraction Albedo>0.15 : 10~20% Albedo<0.15 : 0.015~0.15 40-80% (> 10mm/h) 10~20% 15 km 2 8 km 2 4 km 2 daily daily daily 10

3. GSICS Processing Results (IR channels) AIRS, IASI-A : April/2011-Dec/2016 IASI-B : Aug/2013-Dec/2016 CrIS : Jan/2014-Dec/2016 IR1 IR2 IR3 (WV) IR4 (SWIR) IASI-A IASI-B AIRS CrIS Number 184711 156083 698417 349070 Bias 0.1020 0.1231 0.0377 0.0134 RMSE 0.3474 0.3459 0.4276 0.3996 Slope 0.9953 0.9945 1.0134 1.0009 Intercept 1.4723 1.7407-3.9022-0.2376 Number 202627 173165 756648 381557 Bias -0.0126 0.0161 0.0207-0.0125 RMSE 0.3315 0.3337 0.3315 0.2867 Slope 0.9930 0.9917 0.9879 0.9928 Intercept 2.0254 2.4284 3.5324 2.0965 Number 237595 201121 915472 499093 Bias -0.8446-0.8576-1.0822-0.9917 RMSE 0.4230 0.4206 0.4699 0.4384 Slope 0.9826 0.9842 0.9840 0.9856 Intercept 3.4033 3.0112 2.8210 2.5183 Number 58182 49753 136962 52474 Bias 0.1466 0.1409-0.1745-1.4880 RMSE 0.2482 0.2230 0.4704 0.8874 Slope 0.9947 0.9913 0.9859 0.9443 Intercept 1.7125 2.6958 3.9601 15.0280 11

3. GSICS Processing Results (VIS channels) 12

Improvement of SST after GSICS Correction Data: Apr. 2011~Mar. 2015 0.9235 0.8280 COMS IR 10.8, 12.0 μm DN MCSST GSICS correction IR 10.8, 12.0 μm TBB GSICS correction (yearly) IR channel QC Buoy QC Buoy SST 0.8504 0.7477 Match-up DB COMS CLD MCSST_FG CAL/VAL Multi Regress(Day/Night) L2 Product Day Night 13

Level 3 SST 1,5 201104-201503 L3 SST RMSE, bias 1,2 Celsius deg gree ( ) 0,9 0,6 0,3 0 bias(l3) RMSE(L3) bias(l3_fg) RMSE(L3_FG) bias(l3_fg, ltm) RMSE(L3_FG, ltm) -0,3-0,6 201104 201110 201204 201210 201304 201310 201404 201410 MONTH 14

Level 3 SST RMSE ( ) MCSST (L3) 1.21774 MCSST_FG (L3) 1.07426 MCSST(Day mean) 1.0408 MCSST_FG(Day mean) 0.950658 15

SST Level 2, Level 3 validation July 2013, Monthly average anomaly field 16

4. Summary ECVs accuracy was improved after GCIS correction Resulted positive effect of GSICS-based FCDRs toward TCDRs These positive effect of GSICS should be continuously monitored. Try to build CDR processing system for those ECVs 17

Thank you 18

GEO-KOMPSAT-2A payload 16 channels FPM VNIR MWIR LWIR Band name AMI(Geo-KOMPSAT-2A) ABI(GOES-R) AHI(Himawari-8/9) MI (COMS) Center Wavelength (µm) Resolution (km) Center Wavelength (µm) Resolution (km) Center Wavelength (µm) Resolution (km) VIS0.4 0.47 1 0.47 1 0.46 1 VIS0.5 0.51 1 0.51 1 Center Wavelength (µm) VIS0.6 0.64 0.5 0.64 0.5 0.64 0.5 0.675 2 VIS0.8 0.856 1 0.865 1 0.86 1 NIR1.3 1.378 2 1.378 2 NIR1.6 1.61 2 1.61 1 1.6 2 NIR2.2 2.25 2 2.3 2 IR3.8 3.9 2 3.9 2 3.9 2 3.75 4 IR6.3 6.185 2 6.185 2 6.2 2 IR6.9 6.95 2 6.95 2 7.0 2 6.75 4 IR7.3 7.34 2 7.34 2 7.3 2 IR8.7 8.5 2 8.5 2 8.6 2 IR9.6 9.61 2 9.61 2 9.6 2 IR10.5 10.35 2 10.35 2 10.4 2 10.8 4 IR11.2 11.2 2 11.2 2 11.2 2 IR12.3 12.3 2 12.3 2 12.3 2 12.0 4 IR13.3 13.3 2 13.3 2 13.3 2 Resolution (km) 19

No. Products No. Products Development & utilization of GK-2A data Schedule of meteorological data processing system cloud/ rainfall radiation/ aerosol 1 Cloud detection radiation/ Aerosol 27 Visibility 2 Cloud Top Temperature 28 O3 total 3 Cloud Top Pressure 29 Radiances 4 Cloud Top Height 30 Upward Shortwave Radiation(TOA) 5 Cloud type 31 6 Cloud phase 32 7 Cloud Amount 33 8 Cloud Optical Depth 34 9 Cloud Particle Size Distribution 10 Cloud Liquid Water ATM Downward Shortwave Radiation(Surface) Absorbed Shortwave Radiation(Surface) Downward Longwave Radiation(Surface) Upward Longwave Radiation(Surface) 35 Upward Longwave Radiation(TOA) 36 Atmospheric Motion Vector 11 Cloud Ice Water Path 37 Vertical Temp. Profile 12 Cloud Layers/Heights 38 Vertical Moisture Profile 13 Fog 14 In-flight icing motion/ condition 25 Asian dust Optical Depth 51 Ice Cover 20 26 Aerosol Particle Size 52 Current 39 Derived Stability Indices Total Precipitable Water 40 Atmospheric Motion Vector 15 Convection initiation 41 Tropopause folding turbulent flow 16 overshooting top/enhanced thermal couplet detection surface 42 Sea Surface Temperature 17 Rainfall Intensity 43 Land Surface Temperature 18 probability of rainfall 44 Fire/Hot Spot Characteristic 19 rainfall potential 45 Vegetation Index 20 Aerosol detection 46 Vegetation Fraction: Green 21 Asian dust detection 47 Surface Emissivity 22 Volcanic Ash: Detection and Height 48 Surface Albedo 23 SO2 Detection 49 Snow Cover 24 Aerosol Optical Depth 50 Snow Depth