IOMASA DTU Status October 2003
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1 IOMASA DTU Status October 2003 Leif Toudal Pedersen Dorthe Hofman-Bang Roberto Saldo LTP - 04/11/2003-1
2 DTU IOMASA Web site LTP - 04/11/2003-2
3 OI-SAF products in browser LTP - 04/11/2003-3
4 OI-SAF products in browser LTP - 04/11/2003-4
5 OI-SAF products in browser LTP - 04/11/2003-5
6 AMSR-E data processing at DTU Ice products 89 GHz polarization difference Bootstrap algorithm ice conc. Combined alg. ~5 Km resolution. Advanced statistical retrieval SST, WS, WV, CLW, C, F,T ice LTP - 04/11/2003-6
7 NASAs AMSR-E on AQUA Precision Quantifying Bit Number 12-bit 10-bit Center Frequency (GHz) Bandwidth (MHz) Sensitivity (K) Mean Spatial Resolution (km) IFOV (km) 1K x x x x x 8 6 x 4 Sampling Interval (km) 10 x 10 5 x 5 Integration Time (msec) Main Beam Efficiency (%) Beamwidth (degrees) LTP - 04/11/2003-7
8 Operational microwave radiometer systems x LTP - 04/11/2003-8
9 AMSR-E ice concentrations LTP - 04/11/2003-9
10 AMSR-E ice concentrations (resolution enhanced) LTP - 04/11/
11 AMSR 89 GHz 3 Km Polarization Difference LTP - 04/11/
12 Estimation theory - 1 T A ( f, θ, p ) = F ( S S T, W S, W V ( z ), C L W ( z ), T a i r ( z ), T i c e, C, e t ( f )... ) ( 7. 1 ) T A = F ( p ) ( 7. 2 ) p = ( S S T, W S, W V, C L W, T, C, F ) ( 7. 3 ) T A = M p ( 7. 4 ) M i j = δ T a p i δ p j ( 7. 5 ) LTP - 04/11/
13 Partial derivatives Atmosphere Ocean surface LTP - 04/11/
14 Estimation theory - 2 p ˆ = ( M t M ) 1 M t T a p ( 7. 6 ) T A = M p + e ( 7. 7 ) p ˆ = ( M t S - e 1 M ) - 1 M t S - e 1 T A ( 7. 8 ) S ˆ = ( M t S - 1 e M ) - 1 ( 7. 9 ) LTP - 04/11/
15 Estimation theory - 3 S ˆ = ( S - p 1 + S - D 1 ) - 1 ( ) S ˆ = ( S - p 1 + M t S - e 1 M ) - 1 ( ) p ˆ = ( S - p 1 + S - D 1 ) - 1 ( S - p 1 p 0 + S - D 1 p 1 ) ( ) p ˆ = S ˆ ( S - 1 p p 0 + M t S - 1 e T A ) ( ) LTP - 04/11/
16 September 26, 2003, ~04:30 UTC Water vapour Clouds (CLW) Wind Sea surface temperature (Ice surface temperature) (Ice (C,F)) LTP - 04/11/
17 September 26, 2003, ~04:30 UTC Water vapour Cloud liquid Wind SST LTP - 04/11/
18 Comparison of AMSR and IOSAF SST AMSR SST IO-SAF SST LTP - 04/11/
19 SST comparison DTU vs. Wentz :28 LTP - 04/11/
20 Wind estimate 03:28, AMSR wind estimate and NCEP wind forecast 06:00 St. Dev. Wind Wind Estimate LTP - 04/11/
21 AMSR-E wind retrieval DTU vs F. Wentz DTU vs Wentz AMSR wind estimate 03:28 and NCEP wind forecast for 06:00 LTP - 04/11/
22 AMSR Water Vapour retrieval DTU WV St.Dev. WV DTU vs Wentz Watervapourcomparison LTP - 04/11/
23 Cloud Liquid Water retrieval Avhrr ch4 02:12 Amsr clw 03:28 Amsr Std clw 03:28 LTP - 04/11/
24 Ice concentration retrieval Statistical retrieval Bootstrap alg. LTP - 04/11/
25 Ice concentration retrieval Ice conc. St. Dev. LTP - 04/11/
26 Multi-year ice fraction MY-ice FY F St. Dev. LTP - 04/11/
27 Algorithm performance LTP - 04/11/
28 Sensitivity analysis Parameter default min max σ SST ( C) WS (m/s) Integrated water vapour (cm) Surface air temperature ( C) Integrated liquid water (cm) Rain/snow mm/hr Ice temperature ( C) Ice concentration 0 to 1 MY ice fraction 0 to 1 LTP - 04/11/
29 Sensitivity analysis water case No Algorithm SST WS WV T CLW Total 1 Simple 6.6 GHz H Simple 18 H+V Simple 21 H+V Simple 37 H+V Cavalieri et al Comiso Polarization 13 Comiso Frequency LTP - 04/11/
30 Sensitivity analysis FY case No Algorithm SST WS WV T CLW Total 1 Simple 6.6 GHz H Simple 18 H+V Simple 21 H+V Simple 37 H+V Cavalieri et al Comiso Polarization 13 Comiso Frequency LTP - 04/11/
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