KMA

KMA

Satellite Asian Dust Monitoring of KMA

Jae-Dong Jang NMSC

SCOPE-Nowcasting EP-1

KMA

DUST 10.8㎛ 12㎛ CLOUD 10.8㎛ 12㎛

BT10.8- BT12 : negative absorption 10.8㎛>12㎛

BT10.8- BT12 : positive absorption 10.8㎛<12㎛

Absorption coefficient of radiance depending on atmospheric particle

BTD(Brightness Temperature Difference) = 10.8㎛ -12㎛

Dust detection of COMS

Factors influencing BTD Aerosol types Satellite zenith angle Surface emissivity Surface temperature Surface reflectance Dust altitude

use BTV

Specific period COMS L1B data

Cloud Screening (BTD > 0.5K)

Extract Maximum BT11㎛ (extract maximum 11㎛ BTV

at same time, same pixel )

11㎛ – 12㎛ =BTV When 11㎛ has maximum value

BTV

Usage of BTV(Background Threshold Value) - BTD expected to be clear sky - To Minimize effects generated by surface characteristics

when using BTD

BTD(11㎛-12㎛) BTV BTD-BTV

2015.02.22. 00:00UTC

KMA

Area: East Asia Spatial res.: 4km Temporal res.: 15 min. NMSC is currently operated using Static BTV made of a month data

(specific period:2011.04).

<BTV>

COMS AI Algorithm

<COMS AI Algorithm>

KMA

False detection in land Weakened signal in ocean

Increase of radiance emitted from surface by heating of surface

Decrease of 12㎛ radiance by water vapor effect in ocean

Problems on Dust detection of COMS

2012.03.31 06:00UTC

2012.03.31 06:16UTC

GOCI DUST WEATHER CHART

2015.02.22 03:00UTC

KMA Use of Dynamic BTV

Static BTV applied uniformly cause error because BTV pixels change depending on time and space.

Change of Static BTV as time passes

DAY

NIGHT

→ Use of Dynamic BTV considering spatial-temporal change

KMA New COMS AI algorithm

Usage of dynamic BTV(10 days from the day before observation) Application of BTV condition depending on BTV threshold [consideration of influences on Surface characteristic(surface emissivity, temperature)]

⁃ Land : BTV<0: BTD-BTV, BTV>0: BTD ⁃ Ocean : BTD-BTV

Adjustment of threshold in ocean: AI≤-0.5 →AI≤-0.2

KMA

Previous algorithm new algorithm MODIS RGB IMAGE Dust weather chart

Application of new COMS AI algorithm

2015.02.22. 03:00 UTC False detection over land

Previous algorithm new algorithm HIMAWARI dust RGB LIDAR

This image cannot currently be displayed.

Discontinuity between land and ocean 2016.04.13. 16:00 UTC

KMA COMS AI Algorithm applied to Himawari-8(1/3)

Channel

AHI(Himawari-8) MI(COMS)

Center wave length(㎛)

Spatial resolution(km)

Center wave length(㎛)

Spatial resolution(km)

1(VIS) 0.46 1

2(VIS) 0.51 1

3(VIS) 0.64 0.5 0.67 1

4(NIR) 0.86 1

5(NIR) 1.6 2

6(NIR) 2.3 2

7(IR) 3.9 2 3.7 4

8(WV) 6.2 2

9(WV) 7.0 2 6.7 4

10(WV) 7.3 2

11(IR) 8.6 2

12(IR) 9.6 2

13(IR) 10.4 2 10.8 4

14(IR) 11.2 2

15(IR) 12.3 2 12.0 4

16(IR) 13.3 2

<COMS AI Algorithm applied to Himawari-8 data>

CH

AHI MI

C.W. (㎛)

Spatial res. (km)

Application C.W. (㎛)

Spatial res. (km)

13 10.4 2 Surface, cloud, dust 10.8 4

14 11.2 2 SST, cloud, precipitation

15 12.3 2 SST, Dust, Ash, TPW 12.0 4

<Spectral Response Function>

Response function vary with wave length of satellite channels.

#13-#15(10.4㎛-12.3㎛) exhibits the greatest similarity to that of MTSAT-2(IR1-IR2(10.8㎛-12.0㎛))

-Hidehiko et al., 2015

Ch13(10.4㎛) and Ch15(12.3㎛) were used considering similarity to center wave length between COMS and MTSAT2.

KMA

Application of equation to through channel analysis between COMS and Himawari-8

EQ_CH13 = 0.9198*CH13 +22.7638 EQ_CH15 = 0.9430*CH15 +16.8116

AI ≤-0.5K(COMS AI algorithm) → AI ≤-0.85K, AI ≤-1.0K

Adjust AI threshold 30days dynamic BTV

regression coefficient to correct difference of Satellite channel

COMS AI Algorithm applied to Himawari-8(2/3)

2016.05.05. 0300UTC

COMS AI No Equation Equation

CLOUD THRE. BTD1315 > 0.5

BTV

AI Dust Signal

White: cloud area

Weaken dust signal

KMA

COMS AI≤-0.5 AI≤-0.85 AI≤-1.0

2016.03.06. 04:00UTC

2016.04.21. 10:00UTC

2016.05.05. 03:00UTC

2017.01.26. 04:00UTC

Most similar to COMS AI

COMS AI Algorithm applied to Himawari-8(3/3)

KMA Test operation of COMS AI applied to Himawari-8

Test operation of COMS AI algorithm based on Himawari-8 using equation (2017.2.20. 0210UTC)

• 30days Dynamic BTV • Application of Equation • Cloud threshold(BTD, BTV) BTD1315 > 0.5 • AI threshold AI ≤ -0.5 AI ≤ -0.85 AI ≤ -1.0

KMA

Example Products Resolution

D*-parameter • Dust detection Using 3 bands(8.6㎛,11㎛,12㎛) of Aqua/Terra

MODIS (Moderate Resolution Imaging Spectradiometer) • D*-parameter > 1 : Dust

1X 1 (km)

Polarized Optical Depth Index • AQUA data use only • polarized method(Fresnel Equation) use to improve detection

problem based on IR(discontinuous dust signal between land and sea)

• Large Nr(dust index) is dust.

Nighttime AOD • Production using retrieved weight from AOD and Artificial

Neural Network(ANN) model to improve detection problem based on IR (discontinuous dust signal between day and night)

• Dust area in D*-parameter use only

AOD/ Dust Height • Production for vertical dust information using AIRS

(Atmospheric Infrared Sounder) of AQUA • AOD and dust Height are produced using 111 BTs and

retrieved weight from BTD thresholds and ANN model

2.3X2.3 (km)

Dust Detection from Low orbit satellite

Productions : D*-parameter,

Polarized Optical Depth Index, Nighttime AOD (MODIS)/AOD, dust height(AIRS)

Period : 2016. 11. 27. ~

Example of test operation

KMA D*-parameter Algorithm

(D*>1: dust , C= -0.5, E= 15) D*= 𝑒𝑒𝑒𝑒𝑒𝑒(𝐵𝐵𝐵𝐵𝐵𝐵 11−12 −𝐶𝐶

𝐵𝐵𝐵𝐵𝐵𝐵 8−11 −𝐸𝐸)

C(BTD11-12 thermal offset) : related to dust area offset C can vary as BTD11-12 is sensitive to dust composition, surface type, and column water vapor E(BTD8-11 thermal offset) : related to dust strength Cirrus cloud(ice) particle absorption: 11㎛>8.6㎛ (BTD8-11: positive) Silicate mineral(dust) absorption : 8.6㎛>11㎛ (BTD8-11: negative) These offsets are adjustable based on analyses of dust-laden MODIS scenes and simulations to enhance the dust signal against a cloud-filled background.

(Hansell et al., 2007)

KMA D*-parameter applied to Himawari-8(1/2)

channel

center wave length

AHI (Himawari-8)

MODIS (Aqua/Terra)

11(IR) 8.6 8.529(B29)

12(IR) 9.6 9.734(B30)

13(IR) 10.4 B30+B31

14(IR) 11.2 11.019(B31)

15(IR) 12.3 12.032(B32)

Use L1B MOD02(1km), MYD02(1km)

MOD02,MYD02 product: 16 bands of Level1B-Calibrated collocated Radiances

1 B20 9 B29(8.40-8.70㎛)

2 B21 10 B30(9.580-9.880㎛)

3 B22 11 B31(10.780-11.280㎛)

4 B23 12 B32(11.770-12.270㎛)

5 B24 13 B33

6 B25 14 B34

7 B27 15 B35

8 B28 16 B36

MODIS(y) AHI(x) Equation

B29(8.529) CH11(8.6) f(x) = 1.0252060391x – 5.6846872174

B31(11.019) CH13(10.4) f(x) =1.0401442194x – 11.530109417

B31(11.019) CH14(11.2) f(x) =1.0286364624x – 8.363347252

B32(12.032) CH15(12.0) f(x) = 1.1336973173x – 36.3084260175

regression coefficient to correct difference of Satellite channel

KMA D*-parameter applied to Himawari-8(2/2)

2017. 05. 05. 0600UTC

MODIS D*_parameter Himawari dust RGB COMS AI HIMAWARI AI (AI≤-1.0)

No Equation BTD13-15(C=-0.85)

Equation BTD13-15(C=-0.85)

No Equation BTD14-15(C=-0.85)

Equation BTD14-15(C=-0.85)

Application of equation to through channel analysis between COMS and Himawari-8 Adjust C threshold(C = -0.85)

Most similar to COMS AI

Detect dust signal

KMA Validation of Himawari-8 D*-parameter with CALIPSO AOD

- AREA Lat: 30.0N - 50.0N, Lon: 80.0E - 135.0E

- DATA CALIPSO: L2 Profile : Column_Optical_Depth_Tropospheric_Aerosols_532 Himawari-8: D*_parameter Index(No equation, C=-0.85) Nearest Himawari-8 pixel within 2km at CALIPSO Lat/Lon

2016.5.1. 06:18UTC

CALIPSO orbit

Dust weather chart

Himawari-8 D*-parameter

result

KMA Summary

Current status of COMS AI - Using BTD and BTV with dynamic threshold, adjust AI to improve the

detection

Apply COMS algorithm to Himawari-8 - Using spectral matching equation and use different BTV

Algorithms for LEO

- D*-parameter, PODI, Nighttime AOD, AOD/Dust Height from LEO

KMA

THANK YOU!