2 - 5 december, 20082008 hurricane conference tropical prediction center, miami, fl 2009 hurricane...

2 - 5 December, 2008 2008 Hurricane ConferenceTropical Prediction Center, Miami, FL

2009 Hurricane Conference2009 Hurricane Conference

Authors:Paul Chang, NOAA/NESDIS

Jim Carswell, Remote Sensing Solutions

Presentation:SFMR Performance Assessment

Objective

Develop a tool to assess SFMR retrieval performance (post mission and real-time).

• Tool needed to be self contained:– Use on SFMR measurements and those data provided to SFMR in real-time.

• Identify error sources (i.e. individual channels).

• Provide quality assessment of retrieved winds and rain.• Potentially provide real-time corrections to address calibration issues.• Plausible solution for the Air Force systems as well as NOAA.

Note: Even small calibration errors can be significant and will lead to inconsistency between aircraft. Wind speed and rain errors are coupled – must account for both.

1 December, 2009 2009 NOAA Hurricane ConferenceTropical Prediction Center, Miami, FL

Inputs and Assumptions

• Available Information:– Brightness Temperature Measurements.– SFMR Retrievals.– Observed SFMR Model-Measurement Difference

(available through retrieval process).– SFMR Ancillary Data (i.e. altitude, attitude, SST).

• Assumptions:– SFMR Model Function is valid.

1 December, 2009 2009 Hurricane ConferenceTropical Prediction Center, Miami, FL

Difference between modeled and measured Tb is an assessment of retrieval process accuracy & can provide insight on SFMR performance for each channel.

SFMR Retrieval ProcessSFMR Retrieval Steps:1) Determine initial / next guess (U10 & RR).

2) Calculate Tb using SFMR Model Function.

3) Determine difference between measured and modeled Tb.

4) If model and measurements agree within a specified threshold, retrieval complete. If not, determine next guess and repeat.

SFMR Retrieval Products:1) U10 & RR.

2) Error Calculations.


Simplified Retrieval Block Diagram

Histogram of Model-Measurement Tb Difference (Calibration Flight)


ATTRIBUTES:

1)Should be zero mean.

2)Insensitive to modeling error.

3)Each channel shown separately.

4)Evaluates fit to both wind speed (mean calibration) and rain rate (relative calibration).

5)Difference by channel already calculated by retrieval process.

Small Cal Error-non-zero-increase width

Interpretation / Tuning

• Channel Calibration Error– Peak of difference histogram will be non-zero.– Width of histogram will increase with calibration error.– Large errors in one channel will “leak” into the errors of adjacent

channels.

• Auto-calibration Tuning– Apply small bias correction to re-center peaks of error

histograms for each channel to zero offset.– Mean (across channels) bias correction can be set to zero to

prevent introducing a mean bias.


Calibration Bias Correction Applied

• Bias Correction: .1K, -.1K, 0K, 0K

• All channels have zero mean.

• Width of error histograms decreased (error from one channel will “leak” into adjacent channels).

• Peak now near 3000 points (was ~1500).


ProSensing and AOC Retrievals on NOAA Aircraft are Significantly Different

• ProSensing retrievals significantly differ.

• RFI was not present during this flight.

• RSS retrievals are 1 second, and thus have more noise.

• RSS winds seem to follow flight winds much better and show lower wind speeds.

• RSS retrieval process is identical to NOAA except 10 second averaging has not been appied.


ProSensing and AOC Retrievals on NOAA Aircraft are Significantly Different

ProSensing retrievals are used to calculate brightness temperature. Difference between modeled brightness temperature and measured is shown. Significantly negative bias present.


Calibration Drift During the Season

NOAA Calibration: 20080830 Flight


Corrected Calibration: 20080830 Flight


Correction: -.3K,-.5K, 0K, 0K

Other Calibration Issues

NOAA Calibration: 20080911 Flight



Evidence of bi-modal

Large negative biased errors and bi-modal indicates in flight drift or change.

Corrected Calibration: 20080911 Flight



Could not remove bi-modal behavior. Suspect 5.57 GHz channel was having problems.

Retrievals: 20080911 Flight



Air Force20090824



SFMR 010

Green: Land Contamination.

Air Force20090901



SFMR 010

Summary• Calibration assessment tool has been created that could

be deployed as a real-time tool to auto correct calibration and detect instrument drift problems on a channel basis.

• AOC and Air Force SFMRs show significant calibration errors over the season – these errors change.

• Current calibration process tunes to a fixed wind speed and neglects rain. Must use a statistical approach to achieve a more robust calibration.

• ProSensing retrievals differ to the NOAA retrievals. Must be some fundamental differences in the retrieval process. ProSensing retrievals differ from model function.


T H A N K Y O U

Q U E S T I O N S ?

Effects of Calibration Errors


• Calibration Error Introduced- 1 Kelvin error (absolute sum

of individual channel error).- 1000s of different

realizations.• Mean Retrieval Error- Simulated Tb values created

with different cal error realizations.

- Retrieved wind and rain estimated using SFMR retrieval processor.

- Mean error calculated over different realizations for each true wind speed and rain rate combination.

2 - 5 december, 20082008 hurricane conference tropical prediction center, miami, fl 2009 hurricane...

Documents

sfmr measurements

sfmr retrieval products

sfmr retrievals

sfmr model function

sfmr ancillary data

retrieval complete

small calibration errors

calibration issues