Combined Active / Passive Retrievals of Ocean VectorWind and Sea Surface Salinity with SMAPAlex Fore, Simon Yueh, Wenqing Tang, Bryan Stiles, and Akiko HayashiJet Propulsion Laboratory, California Institute of Technologyalexander.fore@jpl.nasa.gov

AbstractWe outline the algorithms for a radar-only salinity product, a radar-only vector wind product, and a combined active /

passive vector wind and salinity product. We show SMAP can provide ocean vector winds with accuracy approaching thatfrom traditional scatterometers using both the active and passive instruments. We demonstrate the novel ability of SMAP tomake higher-resolution salinity estimates as compared to Aquarius while having accuracy approaching it. Next we show somepromising results using only the radiometer channels to retrieve extreme winds.

IntroductionThe Soil Moisture Active / Passive (SMAP) mission is a combined active / passive L-band microwave instru-ment designed to measure the soil moisture over land at 9 km resolution with a revisit time of 8 days. To meetthese requirements, SMAP has included an L-band radar (1.22 − 1.3 GHz) and radiometer (1.41 GHz) whichshare a 6 meter rotating deployable mesh reflector. The full footprint 1-way resolution is 40 km while the radaralso operates in a range-sliced and Synthetic Aperture Radar (SAR) mode giving resolutions of 30x6 km and1-3 km, respectively. Due to data downlink constraints the SAR mode is generally only available over land andwithin 1000 km of the coastline.

While the mission goals of SMAP are solely over land, the similarities of SMAP to the Aquarius missionenable combined Ocean Vector Wind (OVW) and Sea Surface Salinity (SSS) measurements. Aquarius haspaved the way of L-band combined active/passive estimations of ocean wind speed and salinity [2, 3] and theconically-scanning nature of SMAP, similar to RapidScat and QuikSCAT, enables wind direction retrieval aswell due to the addition azimuthal looks afforded by the measurement geometry.

Algorithm OverviewThe first stage of the combined active passive (CAP) processing is the radiometer-only portion which entailsa residual TB bias estimation as a function of time and polarization. Next the data are binned into a typicalscatterometer L2A swath grid and we perform two retrievals using the radiometer-only data. First a combinedwind speed and salinity retrieval where we use the following objective function:

FTB =∑i

[TB,i − TmB,iNEDTi

]2+

[spd− spd anc

δspd

]2.

Here TB,i is one of the four flavors of TB (H-fore, H-aft, V-fore, V-aft), TmB,i is the model value of TB which is afunction of wind speed, relative wind azimuth, sea surface temperature, significant wave height, and incidenceangle. The second term serves to impose a prior on the wind speed keeping it near the NCEP wind speed other-wise the problem has a continuous family of solutions in the wind speed and salinity space. We use δspd = 1.5m/s. For extreme winds we remove the prior term from the objective function and fix the salinity at the valuefrom the ancillary data product. Then we retrieve wind speed and direction using algorithms developed forNSCAT, QuikSCAT, and RapidScat (i.e. DIRTH [1]). After performing the radiometer-only processing weperform the radar-only processing, which is a direct application of algorithms developed for QuikSCAT andRapidScat to the SMAP data with the only significant change being in the model function used. Finally, theCAP processing stage then combines the radar-only and radiometer-only retrievals to obtain the salinity andwind vector solution using the objective function:

Fcap =∑i

[TB,i − TmB,iNEDTi

]2+∑i

σ0,i − σm0,i√var

(σ0,i)2

,

where σm0,i is the model σ0, which is a function of wind speed, relative azimuth, and incidence angle. TheCAP processing is an extension of the DIRTH processing to include salinity retrieval as well as wind speed anddirection.

Results

Salinity

5°S

5°N

15°N

25°N

35°N

5°S

5°N

15°N

25°N

35°N

120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W 40°W

APDRC ARGO Salinity May 2015 [PSU]

31 32 33 34 35 36 37 38 39

5°S

5°N

15°N

25°N

35°N

5°S

5°N

15°N

25°N

35°N

120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W 40°W

HYCOM Salinity May 2015 [PSU]

31 32 33 34 35 36 37 38 39

5°S

5°N

15°N

25°N

35°N

5°S

5°N

15°N

25°N

35°N

120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W 40°W

Aquarius Salinity May 2015 [PSU]

31 32 33 34 35 36 37 38 39

5°S

5°N

15°N

25°N

35°N

5°S

5°N

15°N

25°N

35°N

120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W 40°W

SMAP Salinity May 2015 [PSU]

31 32 33 34 35 36 37 38 39

Monthly SSS maps for ARGO (upper-left), HYCOM (upper-right), Aquarius (lower-left), and SMAP (lower-right). This map illus-trates the new level of detail that an instrument like SMAP is able to provide, even as compared to Aquarius which was designed forSSS. The Amazon river outflow is much more striking in the SMAP map than in the HYCOM or ARGO map, both of which vastlyunderestimate the magnitude and size of the localized freshening that is occurring during the rainy season. We also see noticeabledifferences in the major river outflows in the gulf of Mexico, which are not detectable in the Aquarius map due to its larger antennafootprint size. In addition we can see higher-resolution features than in Aquarius, such as in the East Pacific, and swirling diffusionpatterns in the Amazon freshwater plume. The SMAP TB-only product can enable novel science even as compared to Aquarius dueto the higher spatial resolution and resulting closer to land SSS estimation validity.

−60 −45 −30 −15 0 15 30 45 60

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Latitude [deg]

SS

S B

ias

[psu

]

Bias SMAP/AQ − APDRC Stats for May 2015

AQ: 0.06AQ/CAP: 0.09SMAP/TB: −0.03SMAP/TBADJ: −0.01SMAP/CAP: 0.02

−60 −45 −30 −15 0 15 30 45 600

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

Latitude [deg]

SS

S S

TD

[psu

]

STD SMAP/AQ − APDRC Stats for May 2015

AQ: 0.20AQ/CAP: 0.19SMAP/TB: 0.29SMAP/TBADJ: 0.24SMAP/CAP: 0.24

Various Aquarius and SMAP biases (left) and STD (right) of monthly Level 3 (L3) SSS products as compared to APDRC ARGOdata for May 2015. For Aquarius we show the project products as well as the CAP (JPL produced) salinity products. For SMAP weshow two types of TB-only processing, one with an empirical TB bias removal procedure applied and the combined radar / radiometerproduct. The legend of each shows the overall STD of SSS between ±50◦ latitude. The SMAP CAP product is not significantlybetter than the TB-only product due to the averaging criteria used to create the L3 data. The accuracy of the SMAP products is good,however, it is currently significantly worse than that from Aquarius and continues to have a bias issue at high/low latitudes.

Ocean Vector Winds

0 2.5 5 7.5 10 12.5 15 17.5 20 22.5−1

−0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

WindSat Wind Speed [m/s]

Spe

ed D

iffer

ence

[m/s

]

SMAP/RapidScat Speed Difference to WindSAT

RapidScat Bias: 0.06CAP Bias: 0.01Radar−Only Bias: 0.00RapidScat RMS: 0.91CAP RMS: 0.94Radar−Only RMS: 1.34

0 2.5 5 7.5 10 12.5 15 17.5 20 22.50

5

10

15

20

25

30

35

40

45

50

55

60

WindSat Wind Speed [m/s]

Dire

ctio

n D

iffer

ence

[deg

]

SMAP/RapidScat Direction Difference to ECMWF

RapidScat RMS: 17.05CAP RMS: 19.08Radar−Only RMS: 19.23

Joint collocation analysis of SMAP, RapidScat, and WindSat. (left) Speed mean difference (diamonds) and RMS difference (squares)of the RapidScat (blue), SMAP CAP (black), and SMAP radar-only (red) OVW data products versus WindSat / SSMI/S wind speed,conditioned on the WindSat / SSMI/S wind speed, (right) wind direction RMS difference (squares) as compared to ECMWF winddirection, conditioned on the WindSat / SSMI/S wind speed. Comparing the SMAP radar-only and SMAP CAP products, we find thatthe CAP product has a wind speed that is significantly better than the radar-only, about 0.4 m/s better in an RMS sense while the winddirections are only marginally improved by using the radiometer. Next comparing SMAP and RapidScat, we note that the SMAPCAP wind speed is worse than RapidScat for speeds between 6.5-12.5 m/s and direction is worse for speeds between 5.5 and 10.5m/s, however, above 11.5-12.5 m/s it seems that the SMAP CAP wind speed and direction may be superior to that from RapidScat.

Extreme Winds

19°N

21.5°N

24°N

135°E 137.5°E 140°E

SMAP Radiometer-Only Winds

19°N

21.5°N

24°N

135°E 137.5°E 140°E

SMAP Radar-Only Winds

19°N

21.5°N

24°N

135°E 137.5°E 140°E

SMAP Active/Passive Winds

0 4 8 12 16 20 24 28 32 36 40SMAP Wind Speed [m/s]

DOLPHIN as observed by SMAP

Various SMAP ocean vector wind retrievals in tropical cyclone Dolphin, where the best track speed indicated 41 m/s. (left) SMAPTB-only wind vectors, (middle) SMAP radar-only wind vectors, and (right) SMAP CAP wind vectors. The TB-only wind vectors arequite good in extreme winds and continue to be available after the failure of the SMAP radar.

10 15 20 25 30 35 40 45 50 55 60 65 70 75 8010

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80

NHC/JTWC Best Track Speed [m/s]

Rap

idS

cat W

ind

Spe

ed [m

/s]

RapidScat Wind Speed versus Best TrackAll storms that reached >= cat 1 intensity

NHC: Corr: 0.77JTWC: Corr: 0.62

10 15 20 25 30 35 40 45 50 55 60 65 70 75 8010

15

20

25

30

35

40

45

50

55

60

65

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75

80

NHC/JTWC Best Track Speed [m/s]

SM

AP

TB

Spe

ed [m

/s]

SMAP Radiometer Wind Speed versus Best TrackAll storms that reached >= cat 1 intensity

NHC: Corr: 0.84JTWC: Corr: 0.80

(left) Scatter plot of peak RapidScat wind compared to best track wind speed for all hits on storms that reach category 1 intensity forRapidScat low SNR data, (right) same for the SMAP TB-only extreme winds data product. The SMAP radiometer extreme windsproduct seems to maintain sensitivity to winds far past traditional scatterometers such as RapidScat, perhaps even as high as 70 m/s.

Summary• SMAP active / passive ocean vector wind estimates approach the accuracy from traditional scatterometers

and may out-perform for winds above 12-15 m/s.

• SMAP radiometer-only data has sensitivity to ocean surface winds far past that from traditional scatterome-ters, perhaps as high as 70 m/s.

• SMAP can continue the time series of ocean surface salinity data from Aquarius.

• Higher resolution of SMAP allows for new science as compared to Aquarius.

References[1] B. Stiles, B. Pollard, and R. Dunbar. Direction interval retrieval with thresholded nudging: a method for improving the accuracy

of QuikSCAT winds. IEEE Transactions on Geoscience and Remote Sensing, 40(1):79–89, January 2002.

[2] S. Yueh and J. Chaubell. Sea surface salinity and wind retrieval using combined passive and active L-band microwave observa-tions. Geoscience and Remote Sensing, IEEE Transactions on, 50(4):1022 –1032, April 2012.

[3] S. Yueh, W. Tang, A. Fore, G. Neumann, A. Hayashi, A. Freedman, J. Chaubell, and G. Lagerloef. L-band passive and activemicrowave geophysical model functions of ocean surface winds and applications to Aquarius retrieval. Geoscience and RemoteSensing, IEEE Transactions on, 51(9):4619–4632, September 2013.

AcknowledgementsThis research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the NationalAeronautics and Space Administration. Copyright 2016 California Institute of Technology. Government sponsorship acknowledged.