assimilation of surface sensitive infrared channels over land at environment canada
DESCRIPTION
Assimilation of surface sensitive infrared channels over land at Environment Canada. L. Garand, S.K. Dutta, and S. Heilliette DAOS Meeting Montreal, Qc August 15-16, 2014. Outline. Context & motivation Approach Assimilation results ________________________ Also: Update on PCW mission. - PowerPoint PPT PresentationTRANSCRIPT
Assimilation of surface sensitive infrared channels over land at Environment Canada
L. Garand, S.K. Dutta, and S. HeillietteDAOS Meeting Montreal, QcAugust 15-16, 2014
DRAFT – Page 2 – April 21, 2023
Outline
• Context & motivation
• Approach
• Assimilation results
________________________
• Also: Update on PCW mission
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Context & motivation
Env. Can. moving to ensemble-variational system with:
•Flow-dependent background errors including surface skin temperature correlations with other variables
•Analysis grid at 50 km, increments interpolated to model 25 km grid (15 km in 2015)
•~140 AIRS and IASI channels assimilated: many sensitive to low level T, q, and Ts. RTM is RTTOV-10.
Favorable context to attempt assimilating surface-sensitive IR channels over land and sea-ice vs earlier work with GOES (Garand et al. JAM, 2004) with analysis grid at 150 km and no hyperspectral IR.
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Ensemble spread of Ts (Feb-Mar 2011)
00 UTC 06 UTC
12 UTC 18 UTC
Maximum ~15h localIn SH (summer)
Maximum at nightTibetan area (winter)
Ts background error over land in 4Dvar isConstant: 3 K.
In EnVar, B is 0.5(BENKF+ BNMC)
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Ensemble T(~964 hpa) spread (Jan-Feb 2011)
00 UTC 06 UTC
12 UTC 18 UTC
Only minor variations withlocal time
Values < 0.5 K in SHseem underestimated
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Key factors to consider
• Reliable cloud mask • Spectral emissivity definition (CERES, U-Wisconsin)• Highly variable topography • Radiance bias correction• Background and observation error definition
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Approach guided by prudence
Assimilate under these restrictive conditions over land and sea ice:
•Estimate of cloud fraction < 0.01•High surface emissivity (> 0.97)•Relatively flat terrain (local height STD < 100 m)•Diff between background Ts and retrieval based on inverting RTE limited to 4K
Radiance bias correction approach:•For channels flagged as being surface sensitive, use only ocean data to update bias coefficients
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Assigned observation error to radiances
15.0m 4.13m 15.3m 4.50m
Assigned = f std(O-P) Desroziers = <(O-P)(O-A)>
f typically in range 1.6-2.0
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Limitation linked to topography
Criterion used: local STD of topography < 50 m (on 3X3 ~50 km areas)
RED: accepted, white std > 100 m, blue 100>std>50 m
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Limitation linked to surface emissivity
Surface emissivityAIRS ch 787
Emissivity based onCERES land types(~15 km) + weighted averagefor water/ice/snowfraction.
Accept only emissivity > 0.97 ; Bare soil, open shrub regions excluded.
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Examples of emissivity from CERES
10.7 micron 3.9 micron
water: 0.990 water: 0.977
A large portion of land masses have surface emissivity > 0.97
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First attempt: negative impact in region 60-90 N/S
00 hr 72hr
Possible cause: cloud contamination ?
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Second attempt: added constraints
• Cut latitudes > 60 deg
• Local gradient of topography < 50 m (was 100 m) Strong impact on (O-B) stats for surface channels
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T std error diff. (CNTL-EXP) NH-Extratropics 6 Feb to 31March 2011
vs ERA Interim vs own analysis
Consistent positive impact vs ERA Interim and own
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T std diff (CNTL-EXP) vs ERA-Interim
Tropics SH Extratropics
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Zonal T STD difference (CNTL-EXP)vs ERA-Interim
72-h 120-h
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Time series of T std diff at 850 hPa
NH extratropics TropicsCNTLEXP
EXP superior to CNTL 54-66 % of cases at days 3-5
(b)(a)
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850 hPa TT anomaly cor.
NH extratropics TropicsCNTLEXP
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120-h N-Extr vs ERA-Interim
CNTLEXP
U HR
GZ T
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Validation vs raobs 120-hFeb-Mar 2011 (59 days)
CNTLEXP
SH-extratropics NH-extratropics
U V U V
GZ T GZ T
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Validation vs raobs 120-hFEB-Mar 2011 (59 days)
North America EuropeCNTLEXP
U V U V
GZ T GZ T
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Added yield: about 15%(for surface sensitive channels)
Number of radiances assimilated for surface channel AIRS 787CNTL: ~1400/6h EXP: ~1600/6h
CNTLEXP
Region: world, EXP excludes surface-sensitive channels at latitudes > 60Radiance thinning is at 150 km
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Std/bias of (O-P) and (O-A), AIRS 787CNTL EXP
O-P
O-A
No major impact on bias. Strong assimilation over land,with std (O-P) of ~1.7 K, std (O-A) of 0.40 K (not shown)
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Conclusion
• Very encouraging results, especially in NH where most of new data are assimilated
Next steps:
• Relax limitations on emissivity, use MODIS-derived atlas• Run a summer cycle• Seek operational implementation
Longer term• Evaluate problems specific to high latitudes
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Update on Polar Communications and Weather (PCW) mission
A possible 2-sat HEO system
Goal:Fill communication and meteorologicalobservation gaps in the Arctic
Most likely configuration:2 satellites in highly elliptical orbits
Status:Seeking approval from Governmentin early 2015. Could startoperating in 2021.
Meteorological instrument:Similar to ABI or FCI
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Weather:High-Level Requirements
Capabilities
• ‘GEO-like’ continuous imaging of Arctic circumpolar region
• ‘GEO-like’ spatial (1-3 km) and temporal (15 min) resolution
• ‘Next-generation’ meteorological imager (ABI, FCI, 16+ channels)
• Near-real time processing to L1c for delivery to Environment Canada
• Compatibility with GEO imagers as part of WMO Global
Observing System.
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Orbit Comparison(2-sat Constellation)
Molniya (12-h)Apogee: 39,800 km
Tundra (24-h)Apogee: 48,300 km
TAP (16-h)Apogee: 43,500 km
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Science Studies: Uniqueness of HEO System vs LEO
23 LEO satellites needed to get 15 minImagery at 60 N, versus 2 HEO
Trichchenko and Garand, Can. J. Remote Sensing, 2012
Also, capability to get image triplets for AMV vastly superior to LEO
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Science Studies:Impact on NWP
OSSE showing significant impact of PCW AMVs filling gap in polar areas
Garand et al., JAMC, 2013
Positive impact (blue) at 120-hIn both polar regions from 4 satellites
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Example of PCW Geometry Matching[16-hr TAP Orbit] for intercalibration
VIIRS/SNPP
GEO
Trishchenko and Garand, GSICS Newsletter, 2012