GRWG/GDWG Web Meeting 2022-05-05
GSICS Web Meeting on GSICS algorithms and MERSI
- Xin Jin (NOAA Affiliate) – Long-term Monitoring of CrIS and ABI Inter-sensor Radiance Differences via ICVS: An Improved SNO Method and Case Studies
- Hanlie Xu (CMA) – Performance of FY-3D MERSI-II and FY-3E MERSI-LL for the IR bands
Guest Chair: Likun Wang
NOAA: Likun Wang, Fred Wu, Xin Jin, Fangfang Yu, Banghua Yan, Hyelim Yoo, Lin Lin
CMA: Hanlie Xu, Chengli Qi, Hexing Wei
EUMETSAT: Tim Hewison, Vincent Debaecker
ESA: Stefano Casadio
Xin Jin (NOAA Affiliate) – Long-term Monitoring of CrIS and ABI Inter-sensor Radiance Differences via ICVS: An Improved SNO Method and Case Studies
Xin Presented an improve SNO method for inter-calibration between CrIS
and ABI. He first introduced ICVS-LTM system and GSICS portal. Then he talked about QA procedures in current LEO-GEO inter-calibration studies. To reduce inter-calibration uncertainties, he used the method to interpolate the GOE radiances to reduce inter-calibration uncertainties. Finally, some results were presented.
Tim (EUMETSAT): How did you make the time series of BT bias?
A: It is mixed with all the scenes and not separated with different scenes.
Likun Wang: Why do you only focus on the nadir pixels?
A: I used the traditional LEO-LEO SNO methods.
Fred Wu: Slides 4, can you describe the traditional method in details?
A: It is a traditional LEO-LEO SNO method, which is focused on nadir simultaneous overpasses.
Fred Wu: Can you explain more on slide 9? Do you still use STD for QA?
Fangfang: Can you explain time t in Equation of time interpolation?
A: It is GOES pixel time.
Tim: I see the step change for Standard deviation time series in 2021?
A: I suspected that it is caused by CrIS
NEDT trend in slide 10.
Tim (comments) : The temporal uncertainties have been counted in the spatial variation in the GSICS algorithms. It is worthy of further exploring it. It is better to compare with the GSICS traditional method side-by-side.
Fred (comments): It is better to compare with the GSICS traditional method side-by-side. You only compare the results before and after time interpolation.
Fred (comments): Use slide 12’s case as a case study to examine the impacts of temporal interpolation.
Hanlie Xu (CMA) – Performance of FY-3D MERSI-II and FY-3E MERSI-LL for the IR bands
Hanlie presented the performance of FY-3D MERSI-II and FY-3E MERSI-LL for the IR bands. She introduced the instruments, orbit performance (e.g. NEDT), and radiometric calibration validation. Using the SNO methods between IASI and MERSI, she showed the assessment results that have scene dependent features. Long-term stability of FY3E
/MERSI IR channels were presented, which have temporal variation. She thought it was related to instrument temperature change.
Likun Wang：Did you check delta counts of blackbody temperature?
A: Good Suggestion. I will do.
Fred Wu: Is the nonlinearity expected during the WUCD procedures?
A: We don’t derive nonlinearity from the WUCD procedures
Fangfang: If the temporal variation was caused by the instrument blackbody, why did it only impact on some channels instead of all channels?
A: Window channels are stable. It needs an further investigation.
Likun Wang and Tim (comments): Maybe check Blackbody gradient and PRT temperature difference.
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