Evaluation of the GOES-R Algorithm Working Group Cloud Application
Team’s Daytime Cloud Optical Property Algorithm Applied to the
Spinning Enhanced Visible and Infrared Imager (SEVIRI)
JP2.11
William Straka III*, Andi Walther*, Andrew K. Heidinger+
*Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin —Madison, Madison, Wisconsin
+Center
Introduction
The GOES-R Advanced Baseline Imager (ABI) offers new opportunities for
cloud remote sensing from a geostationary platform. Of paramount
importance to the work described here, the ABI will provide:
for Satellite Applications and Research (STAR), NOAA/NESDIS, Madison, Wisconsin
Case Study Analysis
13 June 2008 contained several overpasses in the ideal location (low viewing zenith angle for both AQUA/MODIS and
MSG/SEVIRI. The area that these instruments viewed corresponded to a region from approximately 0.0N to 15N, and
from 10W to 5E. We also performed an analysis from 1 August 2006 to 5 August 2006 and got similar results, giving us
confidence that the results presented are robust.
Comparison for 13th June 2008
Cloud Optical Depth 13th June 2008 12 UTC
• Full-disk imagery every 5 minutes with a nominal resolution of 2 km.
• 16 spectral bands including observations at 1.6, 2.2 and 3.9 μm.
• On-board reflectance calibration.
To exploit these advances, the GOES-R program has mandated that the ABI
will generate specific cloud products with required accuracies and precisions.
This poster will present our progress within the GOES-R Algorithm Working
Group (AWG) towards developing an algorithm to estimate the cloud optical
thickness and cloud effective particle size.
This poster applies the AWG algorithm to the most advanced currently
operational geostationary imager (SEVIRI instrument on MSG). The main
basis for evaluation will be a direct comparison to the well-documented and
well-characterized products from the MODIS Science Team (MYD06).
Period: 06/13/2008 06:00 -18:00 UTC
Matching criteria: 10 minutes, 2 km, 70S-70N
Sensor: MODIS on AQUA
Total number of matched observations: 420,000
Total number of matched observations: 460,000
Algorithm Description
Algorithm is based on simultaneous measurements in one visible
(conservative scattering) and one near-infrared (absorption) channel.
Cloud optical depth is mainly a function of the visible channel, while
observations in near-infrared are sensitive to particle size.
We developed an algorithm module that is able to work for AVHRR, SEVIRI
and GOES-ABI data with individual include files.
Forward calculations are solved with a doubling-adding radiative transfer
model for a horizontal homogeneous cloud layer.
Inversion problem is solved by optimal estimation technique. One benefit of
this approach is the automatic generation of error estimates for each retrieved
parameter.
To speed up inversion we stored forward calculations for cloud reflectance
MODIS-COP (SEVIRI) comparison of Cloud Optical thickness (left) and
Effective Radius (Right) with statistical parameters.
Phase-specific analysis: Both algorithms must have the same phase
Total number of matched observations: Water: 116,000 ; Ice: 152,000
α W S tθ tθ
0
The LUT fix points was re-designed in order to decrease interpolation error.
Correction of above-cloud water vapor extinction and Rayleigh scattering
with NWP profile and cloud height information
τ MODIS − τ COP
[%]
τ MODIS
•Question: Do different observation geometry
constellations influence the comparison results
of COD?
•The general relative difference Erel lies at 20
percent.
• Solar zenith angle for MODIS and SEVIRI is
identical. Since AQUA is a sun-synchronous
satellite (13:30 Local Solar time overpass) the
solar angle is clustered at some angle regions.
High solar angles are co-located with high
latitudes (and with high satellite angles). The
algorithms differ most in these areas. (up to 40
percent as the mean)
• Satellite zenith angle is different for MODIS
and SEVIRI. Both algorithms show better
agreement for lower viewing angles.
•Relative difference is widely independent on
the azimuth difference angle.
•Conclusion: The algorithms differences are
largest for off-nadir views and low sun angles.
2D histograms of relative difference for Cloud
Optical Depth between MODIS and COP algorithm
as a function of the observation geometry for
hourly data of August 2006. Upper panel shows this
analysis for solar zenith angle, the middle panel for
the satellite (SEVIRI) zenith angle and the lower
panel for the azimuth difference between sun and
satellite. White line indicates the mean value for
each angle bin.
Conclusions and Future work
Our comparisons with the MODIS Science Team (MYD06) reveal good
agreement with the AWG approach and a level of agreement that is
consistent with other non-AWG SEVIRI cloud products. Specifically:
• Overall good correlation is seen between the AWG SEVIRI optical depths and
those from MYD06 for optical depths < 15. For optical depths > 15, MYD06 gives
larger values. The CM-SAF / MYD06 comparison shows a similar behavior.
• For effective radius, MYD06 values are well-correlated with though gives larger
values than the AWG and the CM-SAF approaches. (For water clouds, this is
expected due to the different absorbing channels used in MYD06 (2.1 μm) and
SEVIRI (1.6 μm). ABI will provide both.
MODIS white-sky albedo ( αWS) are used in connection with pre-calculated
LUTs of cloud transmission ( tθ , tθ 0) and spherical albedo (S) to consider
surface influence:
1 − α WS S
Erel = 100 •
Comparison of Cloud Optical Depth from MODIS with EUMETSAT
Climate-SAF product with statistical parameters.
•Cloud Optical Depth comparisons show a good agreement for thin clouds lower than cod=20.
•COP tends to retrieve thicker clouds with lower COD values.
•Other algorithms using SEVIRI show similar behavior.
•Asymptotic nature of thicker clouds (COD > 20) possibly is related to the asymptotic theory described in King (1987) for
the MYD06 algorithm
•Effective Radius has a bias of approx. -3.47.
• Climate-SAF algorithm shows similar biases and correlations to MODIS.A negative bias is expected for water clouds
because of the different channels used by MODIS (2.1 μm) and SEVIRI (1.6 μm).
( Rcl ) in look-up-tables.
R ob s = R cl +
Observation Geometry Analysis
Phase-specific MODIS-COP (SEVIRI) comparison of Cloud Optical thickness (left) and Effective Radius (Right) with statistical parameters for Water
(W) and ice (I) phases..
•Cloud Optical Depth comparisons show a good agreement for thin clouds lower than cod=20 for both phases.
•Asymptotic behavior seems prominent where larger COD’s occur.
- Possibly due to asymptotic theory described in King (1987) algorithm. This is something the COP and Climate-SAF
algorithms do not do. This would have the most impact in thicker clouds (larger CODs)
•Effective Radius
•Liquid phase for MOD06 lookup table has cutoff of 30 microns
•Both phases have good (>.6) correlations
•Bias to smaller effective radii in COP algorithm compared to MODIS for both the ice and water phases
•Further comparisons are being done for the upcoming EUMETSAT cloud
workshop in February 2009. In this workshop, cloud optical properties will be
compared with algorithms from around the world and validated using the A-TRAIN
set of satellites, particularly CALIPSO.
•The initial analysis with the other groups show than the new algorithm is in
agreement with other SEVIRI based algorithms, suggesting that the biases with
MYD06 exhibited by the current study might appear when comparing other nonAWG SEVIRI cloud products.
•This algorithm is also being applied to the 30-years of AVHRR data to develop a
new multi-decadal climatology that benefits from the AWG efforts.
Acknowledgements: The authors would like the thank the GOES-R AWG and others for their help. Thanks to
Rob Roebeling ffor providing the CLIMATE-SAF data . Funding for this project came from NOAA ORA