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D CV-17-01: L1 top-of-atmosphere interoperability
L1 top-of-atmosphere interoperability
Creation Year:
Completion Date:
2021 Q4 (28 days remaining)

Develop an initial recommendation of a community reference in collaboration with GSICS.

Link to GEO Work Programme:
External Reference:
Responsible Users:
Nigel Fox
Responsible CEOS Entities:
Contributing Agencies:
Progress Reports:
2019-09-07 03:10:24 UTC

A concerted effort is planned for Q1 and Q2 2019 to gather existing material from across multiple GSICS and WGCV activities to place the specified recommendation on the CEOS website by Q4 2019.Confusion on the intent of the work plan caused delays in completing this item during 2018.  Clarifications at WGCV-44 led to an updated completion date of Q4 2019

Nigel Fox | 2019-09-30 13:01:10 UTC

A joint WGCV GSICS workshop 'An SI-Traceable Space-based Climate Observing System'  hosted by UKSA at NPL in the UK was held in September.  The workshop attracted nearly 100 participants and considered the needs, state of the art and prospects of how to achieve L1 traceabiliy and satellite to satellite interoperabiliy to meet the most demanding needs of climate. However, it was recognised that steps required for climate would result in the necessary benefits for science and operational sensors. Although the 3 day workshop concerned primarily optical sensors (UV to TIR) it also addressed the needs of passive microwave as well. The conclusion of the workshop was that whilst every effort should be made to incorporate all comparison knowledge from vicarious earth surface and Lunar measuremnts, comparison to a well-calibrated reference sensor over a range of geogrpahical locations was a solution to be strived for.  These reference sensors should be SI-traceable and have been given the generice name of SITSATS (SI Traceables Satellites) with current examples being CLARREO Pathfinder, TRUTHS and a proposed Chinese mission called CRABS. 

The output of the workshop will be a community white paper (Dec 2019) and a peer review porceedings early in 2020. It is believed that this white paper will provide a top-level strategy for this task and with it establish a framework for sub-tasks that will need to be continued and developed further to facilitate bias analysis for both main stream sensors and new space constellations . Notalbly, Lunar model improvement, methods to carry out sensor to sensor comparison and vicarous test sites including the operational RadCalNet and methods to mathematically combine the results in an effective and robust manner..  

2020-09-04 21:09:32 UTC
Cindy Ong | 2019-10-07 07:05:42 UTC

Seeing the workshop proceedings are not due until early 2020 does this deliverable need extension to Q12020?

| 2020-09-04 21:09:32 UTC
The final workshop took place at ESA/ESRIN in December 2019. All results show high accuracies (> 80%) for all processors. ├┐Cloud screening algorithms are generally good but can be improved. CMIX had shown that there is no clear superiority of any methodology (Spectral tests vs. AI;mono vs. multitemporal) . Thin semi-transparent clouds and cloud boundaries are an issue for mostly all algorithms ( How to define a transparent cloud? boundary of a cloud?). A buffer and its size have a strong influence on the validation results (Bigger buffer = better results). It was also noted that the current validation datasets and validation methodology is insufficient. All 5 validation datasets (VD) have different strengths and weaknesses; the results vary depending on the validation dataset. The combination of 5 VDs allow a more detailed analysis of strengths and weaknesses ├┐but detecting/photo-interpreting clouds;especially thin clouds remains very subjective. The current VD and method does not allow for detecting systematic errors and it was recommended to collect a dedicated validation data set.
2019-09-07 03:10:24 UTC
Last Updated:
2021-02-23 11:50:00 UTC