PySciDON: A python scientific framework for development of ocean network applications

Remote sensing reflectance is measured by ocean colour satellites, and is used as a proxy for estimation of ocean productivity. However, satellite reflectance data needs to be validated so accurate productivity data is retrieved. To accomplish this, large amounts of in situ above-water reflectance data are collected by the SAS Solar Tracker developed by Satlantic, and installed in moving ships. This provides a large amount of data that needs to be calibrated, flagged for erroneous measurements, and further processed for proper validation of satellite measure reflectance. In this paper we compare our own system, PySciDON, with state-of-the-art commercial software. PySciDON filters data based on longitude, meteorological, and erroneous viewing angle flags, and further calculates reflectance based on input wind speeds, and simulation of different ocean colour satellite bands. As a case study, we tested PySciDON output with data acquired in 2016 on the west coast of Canada with FOCOS (Ferry Ocean Colour Observation Systems) and compared with Prosoft, a proprietary software by Satlantic. The analysis shows that in the early processing stages, PySciDON produces similar data as Prosoft. However, later processing stages show small differences, which could be associated with the interpolation model or some issues we have uncovered with Prosoft.