A meeting has been proposed to complete the action given to GCC

A.GCC.2018.3b.1: Manik Bali to set up web meeting in September 2108 to discuss requirements for sharing SNO predictions and/or tools. )

An email was sent out on by GCC seeking views from GRWG and GDWG and subgroup chairs on the usefullness of a SNO Prediction tool. Emails were exchanged with the members and a lot of ideas were shared in the emails.

Why SNO prediction tool.

SNO prediciton tools can help in

1. Speed up Reprocessing

2. Validating SNO outputs

3. It was also thought that SNO prediction can help mitigate to an extent the sharing of reference records via the THREDDS server

Eg. as pointed here http://gsics.atmos.umd.edu/pub/Development/20180319/8b_Chen_Requirements_on_GDWG_activities.pptx

There are three approaches to SNO prediction

1. Cangyong Cao maintains a website that shows in real time the SNO prediction among various LEO-LEO and GEO-LEO instruments. ( eg MeTop -X Vs NOAA-X and GOES-15 Vs NOAA-JPSS)


2. An Algorithm to predict SNO by dividing the intercomparing orbit files into Ix1 degree grid boxes and then looping over only overlapping grid boxes.

This idea was proposed by Jon Mittaz and implemented by Manik Bali during re-processing of AVHRR longwave channels. This idea of this algorithm is in the attached presentation. See presentation here. On the 32 Core Linux m/c at NOAA we were able to achive over 100% of speedups. a typical 1x1Km ATSR orbit file Vs IASI collocation takes 3-5 Mins using this approach.

3. Likun Wang has a python-based SGP4 model SNO predication tools to the community.

A very usefull SNO prediction tool
I Attachment Action Size Date Who Comment
sno_prediction.pptxpptx sno_prediction.pptx manage 1 MB 16 Oct 2018 - 02:30 ManikBali SNO Prediction and Unit Testing of SNO
Topic revision: r1 - 16 Oct 2018, ManikBali
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