Cite this as (APA format)
Fussen, D. (2024). Software and Datafiles subtending the application of the Ozone Neural Network Inversion (ONNI) method for limb scattering geometries (Version 1) [Dataset]. Royal Belgian Institute for Space Aeronomy. https://doi.org/10.18758/71021092
Technical info
| Resource format | mat |
|---|---|
| Resource size | 1.5 kB |
Additional info
| Data last updated | April 25, 2024 |
|---|---|
| Metadata last updated | August 19, 2024 |
| Created | April 25, 2024 |
buildBigXY21
This routine builds the input X state vector that generated any LTS case and the output Y measurement vector.
For the logical array "loks" of considered cases, X contains 35 elements
X=[A(loks,1:npcOz) CAE(loks,:) Aair(loks,:) REF(loks) SIG(loks) SZA(loks) SAA(loks) ALB(loks)];
= 20 ozone cooeff + 5 aerosol number log-density coeff + 5 air number log-density coeff
+ effective radius + sigma (dist. width) + sza + saa+ albedo