GRWG/GDWG IR Group Web Meeting 2022-03-16

GSICS Web Meeting in lieu of annual meeting


  1. Likun Wang (NOAA Affliate) – Introduction, Agenda, and Plan (10 mins)
  2. Laura LeBarbier (CNES) - IASI-A end-of-life tests (20 mins)
  3. Bertrand Theodore (EUMETSAT) - IASI SNO tests during Metop-A End Of Life and nonlinarity correction (20 mins)
  4. Su Jeong Lee (Ewha Woman's University, Korea) - Inter-comparisons of Geostationary Infrared Observations using Simulated Radiances from two NWP models (20 mins)
  5. Kozo Okamoto (JMA) - Examination of all-sky infrared radiance simulation of Hiwamari-8 for global data assimilation (20 mins)
  6. Lu Lee (CMA)- Performance Status of FY-3E/HIRAS and FY-4B/GIIRS (20 mins)
  7. Denis Tremblay & Simon Hook (NOAA/GST & NASA/JPL) - Lake Titicaca as potential validation site (20 mins)
  8. Constanze Seibert, Martin Burgdorf, Stefan Bühler (University of Hamburg) - The moon as a tool for the calibration of infrared sensors (20 mins)


Guest Chair: Likun Wang

CNES: Yannick Kangah, Arthur Dick, Sebastien Marcq, Arthur Dick

CMA: Chengli Qi, Yong Zhang, Ling Sun, Yuan Li, Scott (Xiuqing) Hu, Xingwei He, Song Guo, Lee Lu

ESA: Fabrizio Niro, Silvia Scifoni, Stefano Casadio

EUMETSAT: Tim Hewison, Dorothée Coppens, Bertrand Theordore, Sebastien Wagner, Viju John

ISRO: Pradeep Thapliyal, Munn Vinayak

JMA: Kozo Okamoto, Miaki Eiki, Kazuki Kodera, Kazutaka Yamada

KMA: Hyelim Yoo, Jiyoung Kim, Eunkyu Kim, Yooncheol Kim, Dohyeong Kim

NOAA: Banghua Yan, Cheng-Zhi Zou, Denis Tremblay, Fangfang Yu, Fred Wu, Hyelim Yoo, Jason Choi, Lawrence Flynn, Lin Lin, Mark Liu, Bomin Sun, Hui Xu, Haifeng Qian, Peter Beierle, Xin Jin, Likun Wang

U. of Wisconsin: Dave Tobin

NASA: Amit Angal, Conor Haney

Univ. of Hamburg: Contanze Seibert, Martin Burgdorf

Ewha Woman's University: Su Jeong Lee


Agenda Item: 3a Introduction, Agenda, and Plan
Presenter Likun Wang
Overview Likun introduced the agenda and proposed some further web meetings.
Discussion point, conclusions, Actions, Recommendations, Decisions
Tim Hewison proposed a Web Meeting to discuss revisions to the GEO-LEO IR algorithm to give better performance for cold scenes, following his analysis of the impact of GSICS Corrections on SEVIRI L2 products. It was agreed that this should take place some

Agenda Item: 3b IASI-A end-of-life tests
Presenter Yannick Kangah for Laura LeBarbier (CNES)

7 technical tests. Most relevant:

NEdT improvement by switching off 3 out of 4 pixels
- also reduced due to temperature decrease

Inter-calibration with IASI-B and –C.

Limb acquisition during backflip maneuver – although problems limited use of data after first 10 minutes

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: How to use overlap in spatial density-enhanced acquisitions?
A: Could investigate applications requiring reduced noise
Q: Idea to use increased overlap test to check geolocation accuracy.

A: Expected same performance in terms of geolocation accuracy during test.
Q: Was the temperature increase during the maneuver expected?

A: Not expected

Q: Did the limb acquisition start before the maneuver?

A: Yes

Q: Data availability?

A: Yes – through NOAA CLASS and EUMETSAT Data Centre from Campaign #3 (End of Life tests), but not Campaign #4 (deorbitting tests)

Agenda Item: 3c IASI SNO tests during Metop-A End Of Life
Presenter Bertrand Theodore (EUMETSAT)

Limb acquisitions : Bertrand compared model and observations

SNOs between IASI-A, -B (5 SNOs) and –C (3 SNOs):

  • first time possible, as normal orbits out-of-phase

  • Average all pixels in orbit cross-over area

  • No cloud fraction available on scan edges (does this matter?)

  • Broke down by temperature class

Availability of data from EUMETSAT – on request to

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: Have you compared with results of previous QSNO off-nadir comparisons?

A: Not yet – but in the plan

Agenda Item: 3d IASI nonlinearity correction
Presenter Bertrand Theodore (EUMETSAT)

IASI non-linearity correction performed on-board in raw interferograms.

Could it be removed a posteriori?

Derived correction, based on earth view and black body interferogram baselines

Initial validation confirms it works perfectly

  • Now being tested over whole IASI lifetime

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: Congratulations! Even though they said it couldn’t be done. How much processing work?

A: about 1 month – before end 2022

Propose to present at IR Web Meeting to consider whether GSICS proposes new dataset for IASI-A as anchor reference for FCDR generation.

Agenda Item: 3e O-B comparison for GEO imager
Presenter Su Jeong Lee (Ewha Woman's University, Korea)

From Lee and Ahn 2021, TGARS paper


Clear sky over ocean for 1 month

WV channels systematic bias due to NWP models being too moist


  • Able to capture stripes in CO2 channels (except SEVIRI)

  • Gives robust results with only 5 days data (as good as 1 month)

  • Multiple NWP models can reveal model biases

  • Can reveal RTM errors (e.g. O-A v SZA) - e.g. IR8 channel – due to Sea Surface emissivity – also used CRTM – to compare with RTTOV

Importance of having consistent cloud screen method for all satellites

  • Stricter cloud screening gave better agreement with GSICS results

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: Any feedback on striping in CO2 channels from instrument scientists?

Fred Wu: strong VZA dependence evident in O-A maps – warrants further investigation

  • Related to striping

  • Could also check stripes correspond to instrument swaths

  • Mark Liu: VZA dependence coming from RTM

Q: RTM error at 8µm - due to RTM or model inputs?

  • Mark Liu offered to work together to resolve VZA dependence

Q: For high VZA, do you use a ray-trace through atmosphere to include multiple grid points?

A: no – could be a large effect for high VZA – could introduce systematic bias at high latitudes

Q: gaps in Indian Ocean?

A: Overlapped O-A from multiple instruments – could also use Meteosat-8/SEVIRI from 41.5°E in 2019

Agenda Item: 3f O-B all- sky comparison for Hiwamari-8 GEO Imager
Presenter Kozo Okamoto (JMA)

First step to assimilation – investigate O-B characteristics


RTM: RTTOV + Joint-Simulator

Obs: Himawari-8/AHI

1 month period (Aug 2018), with consistent cloud fraction

Broke-down statistics between clear and all sky

  • Found model dry bias and skin T bias, with strong diurnal var over land

  • Investigated contribution to biased pixels

  • Compared to distribution of AHI-IASI collocations’ BT

  • – not enough to explain O-B biases

  • - some bias contributions found to be due to cloud model

Developed QC – remove scenes that cannot be well modelled (low BT, thick ice cloud, large O-B, large CA, …

Developed Bias Correction – based on Cloud Affect parameter (see Okamoto 2014 QJRMS)

Compared O-B for AHI, ABI, SEVIRI (MSG4 outlier over S.Atlantic)

Expectation for GSICS Activity:

  • Higher calibration accuracy – esp in low TB

  • Quantitative and detailed info on calibration error (scene dependence, scan dependence + diurnal changes)

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: More info on DARDAR cloud model?

A: Cloudsat+CALIPSO combined product, which reduced O-B bias

Q: Any sign of striping in O-B images?

A: Not found in ASR – but could be found in clear sky data, on close investigation

Q: Is model input uniform within each swath?

A: Use common profile – no 3D effects along slant-path – tricky in cloudy situations

Comment from Su-Jeong: striping issue observed only in CO2 channels – and due to detector differences.

Comment from Su-Jeong: striping issue observed only in CO2 channels – and due to detector differences.

Q: Why striping/banding only found in CO2 channels?

Web Meeting to follow-up on NWP method within GSICS

Discussion for Friday plenary session: Cooperation with RTM developers to document

Agenda Item: 3g Performance Status of FY-3E/HIRAS and FY-4B/GIIRS
Presenter Lu Lee (CMA)

Lu introduced HIRAS-II and GIIRS, including the important new FY-3E early-morning orbit.

  • HIRAS-II now 3x3 detectors, with 3 contiguous bands 650-2550cm-1 at 0.625cm-1 res.

  • LWIR and MWIR good noise performance - SWIR less so (esp FOV1)

  • Polar SNOs with IASI-B - BT diff <1K in MWIR & LWIR

  • Comparison with RTTOV similar

  • FY-4B/GIIRS - now suitable for NWP

  • Spectral calibration within ±7ppm - also checked with SNO with IASI-C

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: FY-4A also carries GIIRS - has this been used for any operational applications?

A: Chengli confirmed some papers have been published by CMA NWP on case studies (e.g. wind forecasting and hurricane monitoring)

A: Why change GIIRS focal plane detector layout?

A: long story - originally planned as an imager-sounder - new layout reduces off-axis effect

Q: What improvements in HIRAS-II design compared to HIRAS-I in instrument design?

A: Detector layout now more similar to CrIS + better noise performance + contiguous spectra + processing at full spectral resolution

Action: A.GIR.20220316.1: Chengli Qi (CMA) to share references of the papers you mentioned on the impact of GIIRS on NWP (winds, regional,... ) - done:

Agenda Item: 3h Lake Titicaca as potential validation site
Presenter Denis Tremblay, Simon Hook

Lake at 3812m (649hPa) at 11-17°C

Covers few CrIS FOV

In-situ measurements of air temperature, pressure, RH, winds, skin temperature, radiosonde profiles + uplooking lidar and IR FTS + 4 buoys

  • Provide inputs into RTM to perform Obs-Calc

Reviewed results for other lakes with MODIS+VIIRS

  • Works well for VZA<50°

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: What are the uncertainties in all the inputs? And how do you propagate them through the RTM? (see slide ~11)

A: conducted experiment with tropospheric emission spectrometer over Lake Tahoe - comparing with modelled radiances within 0.3K - will share poster

Comment: These are valuable dataset, but difficult working environment to collect

Q: Ground-up estimate of uncertainty in modelled top of atmospheric radiances?

A: Studies suggest 0.23-0.25K uncertainty from atmosphere + RTM - can share!

Agenda Item: 3i The Moon as a tool for the calibration of infrared sensors
Presenter Constanze Seibert, Martin Burgdorf, Stefan Bühler (University of Hamburg)

Case of the moon in the HIRS FOV.

Better seen in the LW channels, as in the SW the moon is moving inside the FOV.

Methodology is explained to find the moon intrusion looking at the counts.

The moon represents 0.5 degrees, in a 1.4 degree FOV.

Preliminary results show the moon BT in dependance of the phase angle for SW. The moon BT is around 340 K.

Good agreement was shown between different HIRS channels and validation with models as well.

Discussion point, conclusions, Actions, Recommendations, Decisions

Q: With the movement of the moon and satellite and so on, how can you be sure the lowest count gives the good position of the moon in the FOV?

A: For the LW it is constant and easy to use, SW is more difficult we can’t be sure that we capture the moon

Q: About SEVIRI, there is saturation in the IR. We are not sure it is then possible.

A: Saturation is seen at specific phase angles. We need phase angle close to no moon (phase > 90) is possible, but not close to full moon where there will be saturation.


Action: ??

Meeting Information:
Wednesday, Mar 16, 2022 8:00 am | 3 hours | (UTC-05:00) Eastern Time (US & Canada)
Meeting number: 2624 181 6333
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Topic revision: r5 - 27 Apr 2022, LikunWang
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