Development of Instability Index of GEO-KOMPSAT-2A
Sung-Rae Chung1, Myoung-Hwan Ahn2, Su-Jeong Lee2
1 KMA/NMSC, 2 Ewha Womans University
2014 Convection Working Group Workshop, 7-11 April 2014, Zagreb, Croatia
2
Geo-KOMPSAT-2 Program
GK-2A for the next generation Meteorological Imager and Space Weather
monitoring
GK-2B for the Ocean Color and Atmospheric Trace Gas monitoring
Meteorological Sensor
Space weather Sensor
Ground Segment
Data Processing System
KMA
Ocean /Environmental
Sensor
Geo-KOMPSAT-2B
2012 ~ 2017 (6 years)
Geo-KOMPSAT-2A
3
AMI (Geo-KOMPSAT-2A)
[Source: Konig, 2002]
<Basic Spectral Bands>
BandsBand Name
Center Wavelength Band Width
(Max, um)
Resolution (km)
SNRNEdT(K)
(240/300K)Radiometric
AccuracyMin(um) Max(um)
VNIR
1 VIS0.4 0.431 0.479 0.075 1 250 5%
2 VIS0.5 0.5025 0.5175 0.0625 1 250 5%
3 VIS0.6 0.625 0.66 0.125 0.5 120 5%
4 VIS0.8 0.8495 0.8705 0.0875 1 210 5%
5 NIR1.3 1.373 1.383 0.03 2 300 5%
6 NIR1.6 1.601 1.619 0.075 2 300 5%
MWIR
7 IR3.8 3.74 3.96 0.5 2 3/0.2 1K8 IR6.3 6.061 6.425 1.038 2 0.4/0.1 1K9 IR6.9 6.89 7.01 0.5 2 0.37/0.1 1K
10 IR7.3 7.258 7.433 0.688 2 0.35/0.12 1K11 IR8.7 8.44 8.76 0.5 2 0.27/0.1 1K
LWIR
12 IR9.6 9.543 9.717 0.475 2 0.35/0.15 1K13 IR10.5 10.25 10.61 0.875 2 0.4/0.2 1K14 IR11.2 11.08 11.32 1.0 2 0.19/0.1 1K
15 IR12.3 12.15 12.45 1.25 2 0.35/0.2 1.1K16 IR13.3 13.21 13.39 0.75 2 0.48/0.3 1.1K
AMI (Advanced Meteorological Imager)• 16 spectral bands
4
Satellite observed radi-ances
Stability Indices (e.g. CAPE)
• Good at estimating non-linear relations
• Once the statistical relations are established, the retrieval can be made computationally very fast (Konig, 2002), often with surprising accuracy (Gardner & Dorling, 1998)
• Training dataset should be complete (large enough to cover a variety of atmospheric phenomena, seasons, and locations) (Blackwell & Chen, 2009)
Artificial Neural Network (ANN)
setup rela-tion
[Source: Konig, 2002]
Statistical Retrieval of Instability Index
T, q profiles (radiosonde, satellite,..)
Work Process Flow
5
CAPE
Final set ofObjective
selectionprofiles
CAPE
Simulated Radiance (I)
MODTRAN run
band-averaged Radiance ()
SRF (SEVIRI for AMI)
Theoretical TB
Inverse of Planck eq.
(establish relations)
Best ANN Parameters
determine
Measured ra-diance (TB)
Real Application: CAPE
direct estima-tionfrom GK2A AMI
ANN training
CAPE Range TOTALselecte
d 0 <= CAPE <1000
133,194
1,375
1000 <= CAPE <2000
6,360 1,375
2000 <= CAPE 1,375 1,375
TOTAL140,9
294,125
IASI (SEVIRI coverage)
6
cir_day
CAPE
INPUTTotal
weights ( WIHxWHO )
circular day 0.09circular
time0.22
Latitude 0.02
Longitude 0.32
Sat. zenith -0.18
Tb6.2 -0.71
Tb7.3 1.56
Tb8.7 6.79
Tb9.6 4.63
Tb10.8 -0.38
Tb12.0 -7.04
Tb13.4 -4.17strongest weight
cir_time
latitude
longitude
sat_zenith
TB6.2
TB7.3
TB8.7
TB9.6
TB10.8
TB12.0
TB13.4
n 1
n 2
n 3
n 4
n 5
n 6
n 7
n 8
n 9
n 10
n 11
n 12
Input layer Hidden layer
Output layer
2nd strongest weight* thickness of the arrows: relative magni-
tude of connection weights
Combination of weights for the best ANN per-formance
Algorithm Validation
7
Radiosonde
IASI(SEVIRI cover-
age)
CAPEANN
training
CAPE re-trieved
CAPE measured
ANN withbest parame-
ter
Radiances from SEVIRI 2.5min (super) rapid
scan
direct es-timation
Validation
compareFuture work
CAPE derived using ANN algorithm(20 June 2013)
8
09:02:14 11:02:13 13:02:12
15:02:15 17:02:14 20:02:13
Significant features- During the afternoon hours (at around 13:02 UTC) several convective clouds begin
to pop up over the regions where the CAPE values are relatively high (marked with arrows and circles at 09:02 UTC image) and developed to the severe convective clouds (at 15:02 UTC)
- High CAPE values around the leading edges of clouds induce a further develop-ment, while weaker CAPE values around the trailing edges result in weakened convective activities. Significance will be assessed with more case studies and quantitative validation.
- No significant convection occurs over high CAPE areas in the morning images (at around 11:02 UTC marked with dashed blue arrows) which requires further inves-tigation.
1,000 2,000 4,000 (J / kg)
0 3,000
CAPE derived using ANN algorithm(20 June 2013 09~21 UTC)
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1,000 2,000 4,000 (J / kg)
0 3,000
Thank you!
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