Towards retrieving 3-D cloud fractions using Infrared Radiances from multiple sensors Dongmei Xu...
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Transcript of Towards retrieving 3-D cloud fractions using Infrared Radiances from multiple sensors Dongmei Xu...
Towards retrieving 3-D cloud fractions using Infrared Radiances from multiple sensors
Dongmei Xu
JCSDA summer colloquium, July 27 2015- August 7 2015
• 2015.1— Postdoc Researcher in MMM Laboratory in NCAR
• 2010.9—2014.12 PhD Candidate of Meteorology, Nanjing University of Information Science & Technology (NUIST)
• 2007.9—2010.6 Master of Meteorology, NUIST
• 2003.9—2007.6 Bachelor of Information and Computation Science (Department of Maths), NUIST
PhD thesis:
Data assimilation and synthetically retrieving clouds with satellite infrared radiance observations
Data assimilation Retrieving clouds
cloud detection
clear-sky radiance
Data assimilation
Verification using multi-
sensor IR radiance
Multivariate and Minimum Residual
(MMR) method
Multi-sensor Advection-
Diffusion nowCast
system
Implemented channel dependent cloud detection scheme and the Metop-2 IASI radiance DA facility inWRFDAEvaluated the impact of data assimilate Metop-2 IASIIn WRFDA on the forecasts on typhoon and hurricane casesIn both hybrid and 3dvar frameworks.
Why?• Cloud parameters, such as cloud top pressure
and effective cloud fraction, are useful for cloud initialization in numerical weather prediction
(NWP), to understand their impact to the earth’s climate change, to estimate incoming and outgoing thermal radiation
budget …
• It is crucial to develop a fast and efficient algorithm to estimate real-time global cloud information in NWP studies to achieve fresh cloud analysis products.
MMRMMRCRTM(clear)CRTM(clear)
T, Q
Ts, εs
Cloud fractions
obs
Clear Simulated Tb
k_top : the cloud top level
k_topc 0.01
How? MMR (Multivariate and Minimum Residual Method)
WRFWRFDA
ν_clearR
ν_cloud 0 1 2 n ν_clear1
( , , , ..., ) 0 _ k
n
kk
R c c c c c R c R
ν_cloud obs
clear
1( , )
2
2
_0
_
R RJ c
Rc
ν _ obsR
ν _ kR :the radiance calculated for overcast black cloud at level k.
ν_cloudR
1 2 nc c , c , ..., c
0c : the fraction of clear sky
:the array of vertical effective cloud fractions for K model levels
:the observed radiance
:the modeled cloudy radiance
:the radiance calculated in clear sky at the wavenumber v
(1)
(2)
The formulations:
0
1
0 1, 0
1,
[ , ]
k
nk
k
c k k
c c
with
DATA
the nadir
AIRS IASI
IASI
before after
AIRS
afterbefore
Main results
Inter-comparisons among cloud retrievals from different sensors
Cloud mask
Cloud top pressure
Cloud profile Cloud retrievals from Multi-sensor Advection-
Diffusion nowCast system
Cloud mask
AIRS
GOES-Sounder
IASI
MODISGOES-Imager
GOESproductsas reference
(NASA-Langley cloud and radiation
products)
1900 UTC 03 June 2012
IASI MODIS
AIRS GOES-Sounder
GOES-Imager
Cloud mask
0800UTC
0900UTC
1100UTC
AIRS MODIS
Cloud top
Cloud profile
CloudSat AIRS MODIS
0800UTC
0900UTC
1100UTC
Cloud profile
Date/height AIRS (ets/corr)
MODIS (ets/corr)
0800 UTC/9 km0800 UTC/5.5 km0800 UTC/3 km0800 UTC/2.5 km
0.32/0.600.36/0.610.45/0.640.34/0.56
0.28/0.510.25/0.550.44/0.630.41/0.60
0900 UTC/9 km0900 UTC/5.5 km0900 UTC/3 km0900 UTC/2.5 km
0.27/0.490.43/0.600.62/0.780.56/0.70
0.31/0.500.40/0.540.47/0.650.39/0.55
1100 UTC/9 km1100 UTC/5.5 km1100 UTC/3 km1100 UTC/2.5 km
0.10/0.150.40/0.620.30/0.460.26/0.39
0.11/0.190.41/0.590.38/0.610.41/0.63
Cloud profile
Multi-sensor Advection-Diffusion nowCast system
AIRS IASI
MODISGOES-Sounder
GOES-Imager
( age_index )
2012060300-2012060323
AIRS IASI
MODIS GOES-Sounder
GOES-Imager
• Investigating a new retrieval prototype based on the Particle Filter (PF) algorithm in the framework of GSI (Gridpoint Statistical Interpolation system)
• Conducting comparisons between the MMR and PF methods.
Ongoing work
…..
…..
100%
90%
10%
.
.
.
…….
PF
APF
CloudSat MMR AIRS
PF APF
Weights for different particles
Conclusions• The MMR method is proved to be robust in
retrieving the quantitative cloud mask, using radiances from multiple satellites.
• MMR produced realistic cloud top pressures, with an accuracy varying with the sensors’ spectral resolutions.
• The accuracy of the MMR scheme in detecting mid-level clouds was found to be higher than for higher and lower clouds.
• The development of a new prototype of cloud retrieval scheme base on particle filter is underway.
Thanks for your time !
Channels’ weight functionpeak
clrv
kv
R
Rindexability _
Channels’ abilities to identify clouds
Smaller values: sensitive to clouds
close to 1: hard to identify clouds