Aquarius L2 Algorithm: Geophysical Model Func;ons

Transcription

1 Aquarius L2 Algorithm: Geophysical Model Func;ons Thomas Meissner and Frank J. Wentz, Remote Sensing Systems Presented at Aquarius Cal/Val Web- Workshop January 29 30, 2013

2 Outline 1. Aquarius Wind Speed Products 2. Surface Roughness Correc;on 3. Galaxy 4. Moon 5. Salinity Retrievals 6. Summary

3 1. Aquarius Wind Speed Products (RSS Testbed)

4 1. HH wind (σ 0HH ) HH and HH- H Wind Speeds 2 χ ( W ) 2 ( W, NCEP ) W W NCEP ( σ 0HH ) Var ( WNCEP ) σ0 HH,meas σ0 HH,mod ϕ = + Var 2 2. HH- H wind (T BH + σ 0HH ) Seasat idea: combines ackve (HH) and passive (H) χ 2 ( W ) 0 HH,meas 0 HH,mod ( WNCEP ) Var ( W, NCEP ) ( σ0hh ) σ σ ϕ B, surf, H,meas B, surf, H,mod Var 2 NCEP Var 2 (, 1,, ϕncep ) T T W SSS SST W W = T B, surf, H + 2 +

5 Aquarius Wind Speed Algorithm φ (NCEP) SSS (1 st guess) HH Model FuncKon ( σ 0HH ) Expected Error Var( σ 0HH ) HH-H Model Func0on ( T B,surf,H ) Expected Error Var( T B,surf,H ) Expected Error Var( W NCEP ) SST (Reynolds) W (NCEP) Background field MLE: 1- dimensional minimiza;on of χ 2 (W) with respect to W No improvement in performance at this stage if adding σ 0VV and/or T BV

6 Model Func;ons: Fourier- Decomposi;on ( ) ( ) cos( rel ) ( ) cos( 2 rel ) σ = B W + B W ϕ + B W ϕ 0, P 0, P 1, P 2, P P = VV, HH, VH, HV ΔE P ( TB, surf TB, sur,0) = = T S ( ) ( ) ( ϕrel ) ( ) ( ϕrel ) A W + A W cos + A W cos 2 P= V, H 0, P 1, P 2, P σ 0HH horn 1 horn 2 horn 3 ΔE H Both σ 0HH and T BH model funckon were developed using Aquarius IM (WindSat, SSMIS F17) colocakons. Different from using NCEP wind speeds for model funckon development. 1 hour Rain- free

7 Model Func;ons: X- wind Insensi;vity σ 0VV up- wind down- wind x- wind σ 0HH T BV T BH σ 0 looses sensikvity: X- wind At high winds No unique minimum for VV TB keeps sensikvity in all cases. Inclusion of NCEP background field in χ 2 helps in x- wind.

8 Expected Errors Do not use Kp values / NEDT. Var(σ 0 ) (Δσ 0 ) 2 Expected error VV HH Full lines: (Δσ 0 ) 2 = ( σ 0meas - σ 0model ) 2 Dashed lines: acer correckng sampling mismatch (Aquarius / IM wind speed and NCEP wind direckon): (Δσ 0 ) 2 = (Δσ 0,corr ) 2 + (Δσ 0,sm ) 2 Δσ 0, sm 0.6 m/s Dot lines: Kp values in Aquarius L2 files (noise) Lookup Tables wind speed dependent At low moderate winds: σ 0,HH dominates. At very high winds only TB surf, H survives. At x- wind: NCEP and TB surf, H dominates. Do the same for radiometer to get error of TB surf, H. This error is higher than NEDT. Compare W NCEP with W IM to get error for W NCEP.

9 1 st guess SSS (1) Necessary input to Aquarius HH- H wind speed retrieval. OpKon 1: Use HYCOM Best wind speed performance. HH- H wind speeds are to be used in SSS retrieval. OpKon 1 would use validakon product (SSS HYCOM) indirectly in SSS retrieval. OpKon 2: World Ocean Atlas (WOA) Climatology Fixed set of 12 monthly SSS maps. Works fine.

10 1 st guess SSS (2) OpKon 3: Make our own climatology from current Aquarius V2.0 SSS Near land, sea ice and in very cold SST use WOA. Fixed set of 12 monthly SSS maps. Works as good as WOA. Currently implemented in RSS testbed. Could be updated periodically. OpKon 4: Use dynamical monthly Aquarius SSS map 2- step process Run OpKon 4. Create SSS map of current month. Run it again for current month using this map. 1- st guess is output of RSS testbed data.

11 Performance Evalua;on of Aquarius Winds (1) Dashed lines = BIAS Full lines = standard deviakon RMS [m/s] Evaluated against IM (WindSat, F17), 1hour, rain- free g land, g ice < NCEP AQ SCAT V2.0 HH HH- H

12 Performance Evalua;on of Aquarius Winds (2) NCEP IM HHH IM HHH g land, g ice < 0.01

13 High Wind Speeds Hurricane KATIA 09/06/2011 AQ overpass 22:30 h UTC NOAA HRD Analysis from 19.:30 h shiced along track and resampled onto AQ resolukon. Possibly sampling mismatch between AQ horn 3 overpass and HRD field.

14 2. Surface Roughness Correc;on

15 Form of the Surface Roughness Correc;on V2.0 Δ E = R W, σʹ 0 + A1 W cos ϕ + A2 W cos 2 ϕ ( ) ( ) ( ) ( ) ( ) W NCEP VV NCEP rel NCEP rel roughness table emissivity wind direckon signal ( ) cos( ) ( ) cos( 2 ) σʹ = σ B W ϕ + B W ϕ 0VV 0VV 1 NCEP rel 2 NCEP rel remove σ 0 wind direckon signal RSS Testbed ( ) (, σʹ ) (, ) (, ϕ ) Δ E = A W + r W + r W SWH + ΔE W W 0 HHH 1 HHH 0VV 2 HHH ϕ HHH rel 0 th order (isotropic model fct.) 1 st order roughness table 2 nd order roughness table wind direckon signal, cos cos 2 HHH rel 1 HHH rel 2 HHH rel Δ E ϕ W ϕ = A W ϕ + A W ϕ emissivity wind direckon signal ( ) cos( ) ( ) cos( 2 ) σʹ = σ B W ϕ + B W ϕ 0VV 0VV 1 HHH rel 2 HHH rel remove σ 0 wind direckon signal

16 Roughness Correc;on Tables Residual ΔE W as funckon of W NCEP and σ' 0VV V 2.0 Color scale: +/- 0.5 K TestBed: The figures show the residual ΔE W acer removing A 0 (W) Residual ΔE W as funckon of W HHH and σ' 0VV

17 SWH in Roughness Correc;on Table Scale: +/- 0.5 K Residual ΔE W as funckon of W NCEP and SWH σ' 0VV and SWH have both similar informakon on surface roughness that is complimentary to W NCEP.

18 σ 0VV and SWH in Roughness Correc;on: RSS Testbed Cascading Approach Start: ΔE W (measured) Step 1: remove wind direckon signal ΔE' W = ΔE W (measured) - ΔE φ (W,φ) Step 2: remove isotropic model funckon ΔE'' W = ΔE' W A 0 (W) Step 3: bin ΔE'' W (measured) as funckon of [W; σ' 0VV ] 1 st order roughness table r 1 Step 4: subtract r 1 from ΔE'' W residuum: ΔE''' W = ΔE'' W r 1 Step 5: bin this residuum ΔE''' W as funckon of [W; SWH] 2 nd order roughness table r 2

19 Performance of Roughness Correc;ons Parameters used 1V 1H 2V 2H 3V 3H NCEP W NCEP W σ 0VV (V2.0) HHH W HHH W σ 0VV HHH W σ 0VV SWH The table shows the standard deviakon of TB surf measured expected [Kelvin] TranslaKon: 1 K error in v- pol TB surf 2 psu error in SSS. Error in h- pol TB surf has dropped below error in v- pol TB surf. Both v- pol and h- pol to be used in SSS retrieval.

20 Zonal and Temporal Biases: V2.0 vs RSS Testbed TF measured TA expected: I/2= (V+H)/2 TF measured TA expected: Q = (V H)

21 3. Galaxy

22 Galac;c Correc;on: Wind Speed Dependence At low winds and high galackc radiakon using NCEP wind speeds leads to over- correckon At high winds using NCEP wind speeds leads to under- correckon Color strakficakon: galackc reflected TA assuming specular surface [I/2 in Kelvin] Lec panel: TA gal reflected as funckon of wind speed (galackc tables) Center panel: TF measured TA expected using NCEP wind speed (V2.0) Right panel: TF measured TA expected using HH wind speed (RSS Testbed)

23 I/2 = (V+H)/2 Galac;c Correc;on: Zonal and Temporal Biases: V2.0 vs RSS Testbed

24 4. Moon

25 Moon Reflected Radia;on

26 TA measured - Expected

27 Case 1 Rev # /- 15 orbits 02/02/2012

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29 Case 2 Rev # /- 15 orbits 12/152/2011

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31 Performance of Lunar Correc;on TA measured expected versus TA moon reflected The lunar correckon works fine if TA moon refl < 0.25 K. For higher values of TA moon refl it overcorrects. Recommend: Flag and do not use data in that case. horn 1 horn 2 horn 3

32 5. Salinity Retrievals

33 Salinity Retrieval Algorithm Basic Principle: Match TB surf,0 measured = TB surf, measured ΔE W T S with model funckon TB surf,0 model for specular surface using Meissner- Wentz dielectric constant. V2.0 Solve: TB surf,0 measured = TB surf,0 model (SSS) for v- pol. RSS Testbed MLE 2 2 T T,,0,,0 ( SSS B surf meas B surf mod ) T T B, surf,0 meas B, surf,0mod ( SSS ) 2 V pol H pol χ ( SSS ) = + Var T Var T B, surf,0 B, surf,0 V pol H pol For variances use errors of roughness correckon. Both V- pol and H- pol are used in SSS retrieval.

34 Salinity Retrieval Algorithm: Basic Flow σ 0HH NCEP W NCEP φ SSS climatology MLE Aquarius Wind Speed SST Reynolds OI T B SUR H-pol NCEP φ Roughness Correction σ 0VV T B SUR V-pol Aquarius Measurement Auxiliary Input Process T B SUR 0 H-pol T B SUR 0 V-pol Intermediate Product MLE Aquarius Salinity Output

35 Salinity Retrieval Algorithm: Detailed Flow T A (V,H,U) σ 0HH NCEP W, φ remove galaxy, sun, moon. APC T B TOI (V,H,U) remove Faraday rotation 1 st pass 2 nd pass HH wind speed MLE MLE SSS climatology T B TOA (V,H) HH-H wind speed remove atmosphere NCEP φ T B SUR V-pol T B SUR H-pol SST surface roughness correction SWH σ 0VV T B SUR 0 (V/H) MLE SSS

36 SSS Performance: Single Cycle (1.44s) SSS AQ HYCOM RMS [psu] T S > 5 o C, W < 20 m/s single cycle (1.44s) V.2.0 (RSS implementakon of dric correckon) 0.55 RSS testbed 0.41 Small bias at low SST SensiKvity ΔSSS : ΔT B = 5:1 dielectric model O 2 absorpkon undetected sea ice?

37 TB Consistency Flag (1) err B, meas B, mod POL= V, H ( S ) 2 TB = T T SS Aq POL Only H- pol in V2.0 V- pol + H- pol in RSS testbed Called rad_tb_consistency in ADPS L2 files To be disknguished from expected TB ( ) TB = T T SSS exp, POL B, meas B, mod ref POL

38 TB Consistency Flag (2) Recommended Q/C Flag: Skip if T B err > 0.3 K Eliminates 7 9% of data horn 1 horn 2 horn 3

39 6. Summary

40 Summary (1) Excellent AQ wind speed retrievals with op;mal channel configura;on σ 0HH + T BH NCEP wind speed as background field NCEP wind direckon matches performance of WindSat + SSMIS in rain- free scenes Instantaneous wind speed measurement significantly improves roughness correc;on in RSS Testbed over V2.0 use of HH- H instead of NCEP wind speed: most important σ 0VV SWH (WW3): minor improvement Instantaneous wind speed measurement significantly improves correc;on for reflected galac;c radia;on in RSS Testbed over V2.0 HH or HH- H wind speed NCEP wind speed insufficient for very low and very high wind speeds

41 Summary (2) Improved roughness correckon allows use of T BV and T BH in salinity retrieval Significant performance improvement in SSS retrieval in RSS Testbed over V2.0 Single cycle RMS of SSS Aquarius HYCOM drops from 0.55 psu to 0.41 psu (RMS improvement of about 0.35 psu) Improvement in zonal and ascending/descending biases Lunar correckon overcorrects if TA moon refl > 0.25 K Recommend Q/C for TB err : 0.3 K