Offline Assessment of NESDIS OSCAT data

Li Bi1

Sid Boukabara2

1RTI/STAR/JCSDA2STAR/JCSDA

American Meteorological Society 94th Annual Meeting02/06/2014

Outline

• Motivation• Introduction of statistics used in this study• Preliminary results– Raw data– Filtered data

• Conclusion • Future work

Motivation

• Optimize the usage of OSCAT data by performing offline assessment before the assimilation.

• Based on the offline assessment statistics of wind speed, direction, u/v component bias and STDV comparing with GDAS analysis, suggest optimal QC methods.

• Data usage:– NESDIS OSCAT 50km data June 2012

HDF5/BUFR data.• Selected wind vector cell quality flags:

– Land-sea boundary flag– Land flag– Ice flag– Rain impact flag– Wind retrieval flag

Fig.1. Selected wind vector cell quality flags

Statistics for raw data

• Calculated O-B bias and STDV w.r.t. GDAS analysis– Wind speed, direction, U/V components

• Geographic stats• By observation bins• By SST range• By cell index

– Ascending, descending separated.– Histogram of counts in each bins– Latitude band profile

20120601-20120630 speed bias raw data 20120601-20120630 speed bias filtered data

20120601-20120630 speed STDV raw data 20120601-20120630 speed STDV filtered data

20120601-20120630 direction bias raw data 20120601-20120630 direction bias filtered data

20120601-20120630 direction STDV raw data 20120601-20120630 direction STDV filtered data

Raw data ascending Raw data descending Raw data all

Filtered data ascending Filtered data descending Filtered data all

Raw data ascending Raw data descending Raw data all

Filtered data ascending Filtered data descending Filtered data all

Summary finding after applying basic retrieval filtering

• The basic retrieval filtering effectively remove land/sea boundary flag, ice flag, etc.

• Slightly reduce latitude band wind speed STDV. Direction latitude profile remains similar except for high latitudes.

• Latitude band cut off (60oS-60oN) is suggested.• Further assessment for optimal filtering is very

necessary.

Raw data ascending (speed, dir, u/v)

Raw data descending (speed, dir, u/v)

Raw data all (speed, dir, u/v)

Filtered data ascending (speed, dir, u/v)

Filtered data ascending (speed, dir, u/v)

Filtered data all (speed, dir, u/v)

Layout of OSCAT vs. GDAS stats bias and STDV

Wind Speed - Raw data

Wind Speed Filtered data

Speed Relative Bias - Raw data

Speed Relative Bias - Filtered data

5m/s cut off for wind speed is suggested

Wind Direction - Raw data

Wind Direction - Filtered data

Count Histogram - Raw data

Count Histogram - Filtered data

Basic filter + 5m/s cut off for wind speed + high wind speed cut off for U/V components

Raw data

Filtered data

15m/s cut off for U-Comp is suggested

Raw data

Filtered data

15m/s cut off for V-Comp is suggested

Raw data ascending Raw data descending Raw data all

Filtered data ascending Filtered data descending Filtered data all

Wind Speed - Raw data

Wind Speed - Filtered data

Wind Direction - Raw data

Wind Direction - Filtered data

Raw data all

Filtered data all

Wind Speed - Raw data

Wind Speed - Filtered data

Wind Direction - Raw data

Wind Direction - Filtered data

Count Histogram - Raw data

Count Histogram - Filtered data

Conclusion

• The optimal filtering effectively reduced large STDV for wind speed, as well as wind direction in the observation bins.

• Suggested new filtering includes:– Old filtering provided during the retrieval to remove ice/rain flag

etc. – 5m/s cut off for wind speed– Latitude band cut off (60oS-60oN only)– 15m/s cut off for high u and v components of the winds

• Wind speed biases generated in the observation bins.• Largely reduce wind direction STDV in scan position which is

mainly due to low winds.

Future Work

• Test the optimal observation error • Possible bias correction based on the preliminary results• Revisit thinning methods• Test with high resolution OSCAT data (25km)• Exploring assessing and assimilating the scatterometer

data in rainy conditions (pending maturity of the products)

• Perform the data assimilation experiment with the optimal filtering, bias correction and observation error.