GSICS IR Group Web Meeting 2022-10-06

GSICS Web Meeting on GSICS Corrections, Algorithm, and Products, and GOES ABI

Agenda

1. Johan Strandgren (EUMETSAT): Impact of GSICS Corrections on L1 and L2 products from 3 Meteosats
2. Tim Hewison (EUMETSAT): Developing an Algorithm for GSICS GEO-LEO IR v2 inter-calibration
3. Fangfang Yu (UMD & NOAA Affiliate): Operational calibration performance of GOES ABI IR channels

Attendees

Guest Chair: Likun Wang (UMD & NOAA Affiliate)

ECMWF: Samuel Quesada-Ruiz

EUMETSAT: Johan Strandgren, Tim Hewison, Dorothee Coppens, Mounir Lekouara, Sebastien Wagner, Vincent Debaeker, Ali Mousivand

ISRO: Munn Vinayaka

JMA: Misaki Eiki, Kazuki Kodera, Kazutaka Yamada, Arata Okuyama

KMA: Euidong Hwang, Tae-Hyeong Oh

NOAA: Likun Wang, Manik Bali, Fangfang Yu, Fred Wu, Hyelim Yoo, Boming Sun, Lin Lin

U. Hamburg: Martin Burgdorf

U.Wisc: Dave Tobin

Summary

Johan Strandgren (EUMETSAT): Impact of GSICS Corrections on L1 and L2 products from 3 Meteosats

Johan presented the Impact of GSICS Corrections on L1 and L2 products from 3 Meteosats. He showed the BT time series before and after GSICS corrections. He also analyzed the GSICS corrections on Level 1.5 data between three MSG satellites, including pixel-level difference, mean absolute bias cross full disk, and difference between nominal and GSICS calibration.

Dave Tobin: How similar are the SRFs for MSG3 and MSG4? Should you expect agreement?

• R: On the paper, they look very similar. However, we don’t know exactly in reality.

Fred Wu: the SRFs are very broad. For the biases in the cold temperatures, the SRFs have less impact.

• R: (post meeting): Agreed , but if the SRF is wrong, the radiance to brightness temperature conversion would also be wrong

Samuel: Can you share me with some window channels results? we talk can offline.

Tim Hewison (EUMETSAT): Developing an Algorithm for GSICS GEO-LEO IR v2 inter-calibration

Tim first reviewed current GSICS GEO-LEO IR algorithm. The issues with current GSICS GEO-LEO IR algorithm were then discussed, including 1) formulation is not friendly, 2) performance at the cold end, 3) Hot land bias issues, 4) impact of high view angles, 5) diurnal variation.

He proposed

1. a change from weighted linear to polynomial regression
2. to invert relationship for GEO-LEO radiances with errors on X (GEO radiances)
3. adding alternative method – radiance slicing, Complements regression method to provide check on applicability (e.g. Confirming no outlier BT ranges), Allows definition of filters in algorithm development – e.g. to reject hot land pixels
4. to include daytime collocations

Several ideas for further development are listed in the last slide.

Fangfang: Some of the bias in the Johan’s presentation are caused by the GSICS correction?

• R: Some of the issues with erroneous bias for cold scenes, which the re-formulation tries to correct
• post-meeting note: residual issues with MSG3 could be related to GSICS Correction being derived while operating in Rapid Scan Service
  • could check by repeating analysis restricting collocations north of 15°N

Fangfang: Why do we need to correct hot-land data? It is caused by data issues instead of calibration issues.

• R: Agreed - especially for meteorological sensors. However, we would like to understand root causes.
• Comment: Could add Azimuth Angle filtering to reject bias over hot land pixels = Ray-matching approach.

Fangfang: Brightness temperature references should be channel dependent - and maybe also geographically dependent

• R: Agreed - could be defined based on percentile of observation space (post-meeting note: ideally should be comparable for all GSICS products for a given instrument class)

Likun Wang: There are so many references instruments. Do you consider how to combine them together?

• R: Use the same correction method for different references and find delta (used in Prime GSICS Correction concept). If delta is small, we should not worry. Sometimes, diurnal cycle and instrument calibration differences are mixed.

Dorothée: No significant different between IASIs now. CrIS is also routinely monitored and very close.

Samuel: Would be interested to see statistics from collocations separated for land and ocean.

Munn: Could consider whether GSICS products are defined corrections to radiances, rather than alternative calibration coefficients (as currently done for VIS/NIR channels based on DCC)?

• R: Would depend on whether L1 products are real instruments counts, or scaled radiances - may be different for different instruments. Ideally, all agencies generating GSICS products for each instrument class would have common algorithm and approach for all channels.

Fangfang Yu (UMD & NOAA Affiliate): Operational calibration performance of GOES ABI IR channels

Fangfang presented the results operational calibration performance of GOES ABI IR channels. She first reviewed ABI instruments, Earth Scan patterns and ABI IR calibration method. She also mentioned GOES-17 ABI colling system anomaly. Finally, she presented inter-calibration results using all IASI and CrIS instruments for GOES-16, -17, and -18 instruments, including 1) overall calibration accuracy, 2) the bias over radiance (in BT) dynamic range, 3) bias stability over time (time series jump for calibration change, no apparent seasonal variation, consistent bias pattern over time). The GEO-GEO inter-comparison to diagnose diurnal variation was presented.

Mounir Lekouara: From the Scan patterns, only have one space view look?

R: ABI looks the space view every 30 seconds or less.

Mounir Lekouara: On GOES-16 straight lights case, it is not clear for me.

R: Certain straylight at B07 (3.9um) is allowed at certain time and location. The impact is well within specification.

Tim: can Cooling anomaly change SRFs?

R(Fred): Yes. It changed the SRFs because of high operational temperatures. We can correct them in the radiance domain.

Fred and Mounir discussed the space view look for MSG satellites.

Webmeeting Information:

Topic: GSICS IR Group Meeting
Time: Oct 6, 2022 07:30 AM Eastern Time (US and Canada)

Join Zoom Meeting
https://umd.zoom.us/j/8243989578?pwd=VnV5eWFMbUNJLzVEZGVzdnNWUm1PUT09

Meeting ID: 824 398 9578
Passcode: gsics