jet propulsion laboratory california institute of technology quikscat retrieving ocean surface wind...

Jet Propulsion Laboratory California Institute of Technology

QuikScat

Retrieving Ocean Surface Wind Speeds from the Nonspinning QuikSCAT Scatterometer

Bryan W. Stiles, R. Scott Dunbar, and Alexandra H. ChauSimon Yueh (presenting for the authors)

Jet Propulsion Laboratory, California Institute of Technology


QuikScat

QuikSCAT Nonspinning Winds 2

Overview

• Current Status of QuikSCAT– QuikSCAT stopped spinning in November 2009.– Current data is all single azimuth data

• Large number of looks; reduced noise• No directional discrimination• Narrow swath, global coverage once per month.

• Single look wind retrieval method– Determine wind speed from backscatter by assuming ECMWF wind direction is

correct.• Spectral and Noise characteristics of single look winds

– Comparison of spinning and non-spinning QuikSCAT wind spectra• Investigation of residual differences from ECMWF winds

– Map of Differences from ECMWF– Rain effects – Overall westward bias in scatterometer winds– Ocean current effects

• Conclusions

2011/07/28 IGARSS 2011


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Current Status of QuikSCAT

• QuikSCAT stopped spinning on November 23, 2009• Since then we have obtained single azimuth data from a variety

of incidence angles and polarizations.• Data will be used to

– Develop geophysical model functions for OceanSAT-2– Calibrate cryosphere products for OceanSAT-2– Retrieve accurate wind speed profiles on a narrow (30 km) swath with

global coverage once per month.Start Date End Date Polarization Incidence Angle

(deg)16 March 2010 14 April 2010 Vertical co-pol 5415 July 2010 1 Sept 2010 Vertical co-pol 591 Sept 2010 4 March 2011 Horizontal co-pol 504 March 2010 9 June 2011 Vertical co-pol 599 June 2011 12 July 2011 Vertical co-pol 5412 July 2011 present Horizontal co-pol 46

This is what we are discussing today.

2011/07/28 IGARSS 2011


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Current Status of QuikSCAT

• The two primary purposes of this talk are to– Compare the spectra of the nonspinning wind data with that of

the spinning wind data to quantify the resolution and noise characteristics of each data set.

– Compare the relatively noise-free non-spinning winds to ECWMF winds, SSM/I rain rate, and OSCAR current information in order to better quantify the differences between scatterometer and NWP winds and to demonstrate the utility of the data set.

• We have concentrated on the June-July 2011 data, because it has the same incidence angle and polarization as the nominal QuikSCAT outer beam and thus we can use the same GMF to retrieve winds and more readily compare the spinning and nonspinning data sets.

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Single Look Wind Retrieval Method

• Step 1: Average 50 consecutive footprint (egg) measurements to produce a ~ 30 km by 30 km backscatter measurement.– Slice processing is not done because it would require extensive

recalibration and accurate attitude knowledge.– Footprints move 3.8 km on ground during averaging.

• Step 2: Determine co-located ECMWF direction and thus relative azimuth.

• Step 3: Assuming ECMWF direction is correct, invert geophysical model function (GMF) to obtain retrieved speed.– Use Remote Sensing Systems Ku2011 GMF, (Ricciardulli and Wentz)

• Step 4: Co-locate SSM/I rain rate measurements for use in rain flagging.– 26% of wind vector observations within 30 minutes of a SSM/I co-

location.– 58% with 90 minutes

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Comparison of Spinning and Non-Spinning Wind Profiles

Here we compare a 1000-km long non-spinning wind speed profile (bottom) with a similar profile (top) obtained when QuikSCAT was spinning.

Both profiles are compared with co-located ECWMF and SSM/I wind speeds.Rainy data is omitted.

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Spectra Comparison

• Non-spinning QuikSCAT data is compared with– ECMWF (much lower energy at meso-scales)– Spinning QuiKSCAT data obtained from slices binned in 12.5 km by 12.5 km

cells.• Factor of two better resolution than non-spinning data which uses whole footprints

rather than slices.• 2 orders of magnitude more instrument noise than non-spinning data.

• An analytical spectrum is produced assuming a k-2 slope with added white noise and a low pass filter representing the typical resolution of the backscatter measurements used in the retrievals.– The analytical spectra for the spinning and nonspinning QuikSCAT wind

speeds are consistent with the observed spectra.• Nonspinning Spectra were computed using data from the month of June

2011.• Spinning QuikSCAT spectra were computed using a full year (2008) of wind

data.• Wind speed spectra are computed for four different spatial regions.

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Equations for Analytical Spectra

Half power contour

FWHM

Gaussian filter models antenna spatial response

A = constant scale factor used to match the observed magnitude of the spectra

Analytical Spectrum S(k)

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Spectra by region

Freilich and Chelton, Journal of Physical Oceanography, 19862011/07/28 IGARSS 2011


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QuikSCAT Nonspinning Winds 102011/07/28 IGARSS 2011


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Spectra of regions 3 and 4

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Results from Spectra Study

• Noise floor for non-spinning data is ~ 2 orders of magnitude lower than for spinning data.

• The non-spinning wind speed spectrum (red ) is consistent with a spectrum (black solid curve) with 30-km measurement resolution and k-2 slope.

• The noise in the new 12.5 km JPL reprocessing (cyan) of the nominal (spinning) QuikSCAT data is less than that of the current (blue) JPL data set.

• The spinning wind speed spectrum (cyan ) is consistent with a spectrum (black dashed curve) with 15-km measurement resolution and k-2 slope.

• The spectra of the non-spinning wind speeds (red) are similar to the spectra of the backscatter (green).

• Interesting Observation: There is excess energy in all the observed spectra at 80-km scale for regions 2 and 3 as compared to regions 1 and 4.

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Map of Difference of Non-Spinning Wind Speeds from ECWMF

Speed Bias (Non-spinning QuikSCAT – ECMWF m/s)

Standard Deviation of Difference (m/s)

The speed bias (top) of the non-spinning QuikSCAT speeds w.r.t. ECMWF winds shows prominent discontinuities around + or – 40 deg latitude and features of rain.

The standard deviation (bottom) of the difference also shows the effect of rain.

All data was included in these plots. No rain flagging was applied.

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Rain Effects on Retrieved Winds

0.0 1.5 3.0 mm/hr

The top panel shows the average SSM/I rain rate from http://www.ssmi.com for the month of June 2010.

The standard deviation of the difference between QuikSCAT non-spinning wind speeds and ECMWF wind speeds is highly correlated with rain.

Standard Deviation of Wind Speed Difference form ECMWF, June 2011

SSM/I Rain Rate, June 2010

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http://www.ssmi.com/


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Overall Westward BiasThe prominent latitudinal discontinuity in the wind speed bias (top) is due to a 0.3 m/s westward bias in the zonal component of the scatterometer winds w.r.t the ECMWF winds that has been observed for multiple scatterometers (Hristova and Rodriguez).

The middle panel shows the residual bias when 0.3 m/s is added to the zonal component of the QuikSCAT winds.

The bottom panel is the average zonal winds. Note the sign change between the tropics and the high latitudes. This sign change is why a constant offset in zonal winds yields a speed reduction in high latitudes and a speed increase in the tropics.

Speed Bias (QuikSCAT –ECMWF m/s)

Zonal Component of QuikSCAT non-spinning winds (m/s)

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Residual Speed Bias with 0.3 m/s Westward Bias Removed


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Overall Westward Bias

Speed Bias (QuikSCAT –ECMWF m/s) with 0.3 m/s Eastward Bias removed

0.0 1.5 3.0 mm/hr

SSM/I Rain Rate, June 2010

After the 0.3 m/s westward bias is removed from the QuikSCAT winds, the remaining bias is highly correlated with the distribution of rain.

Arguably, the “westward scatterometer bias” is actually an eastward ECMWF bias (Hristova and Rodriguez).

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Ocean Current EffectsOSCAR monthly average current June 2011 (m/s) After omitting wind

vectors that are co-located with nonzero SSM/I rain rates (within 30 minutes), we compared the residual differences from ECMWF with OSCAR ocean currents.

The residual differences when binned by OSCAR ocean current speed are consistent with the root sum square of a nominal ECMWF error (1 m/s) and the OSCAR current.

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Conclusions

• Because QuikSCAT stopped spinning, nominal operation ceased in November 2009.

• The current non-spinning state of QuikSCAT– limits global coverage to once a month; – disallows wind direction determination due to single azimuth looks;– makes rain detection difficult due to single polarization availability.

• Nonetheless, the currently acquired data has a unique feature.– Due to the large number of looks, non-spinning QuikSCAT winds have

negligibly small errors due to instrument noise.• Nonspinning QuikSCAT winds can be useful for

– analyzing the differences between scatterometer winds and numerical wind products.

– detecting small effects on sigma-0 that are harder to observe under higher noise conditions.

– monitoring long term trends in 6:00 AM / 6:00 PM local time wind speeds.

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References

• Ricciardulli and Wentz, (Ku2011 Ku-band Geophysical Model Function) manuscript in preparation, technical report on http://www.ssmi.com

• Hristova-Veleva, S. M., and E. Rodriguez, 2010: “SST-Induced Surface Wind Response: Comparison of QuikSCAT and ASCAT depiction of the phenomenon”, OVWST meeting, Barcelona, Spain, May 2010

2011/07/28 IGARSS 2011

jet propulsion laboratory california institute of technology quikscat retrieving ocean surface wind...

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