KNMI held a one day symposium on various aspects of data science for meteorology and climatology. I was invited to present our approach to data-driven quality control of meteorological observations.
The MET Alliance is a group of “national aeronautical meteorological service providers from eight European States that cooperate on further improvement and rationalisation of the meteorological services for aviation”. I was invited to give an overview of our past and current efforts on camera-based visibility estimation to the expert team on AUTO OBS.
The EUMETNET Workshop on AI for Weather and Climate took place at the Royal Meteorological Institute in Brussels - my last opportunity to travel abroad in 2020. I presented our work on data-driven QC and probabilistic plausibility, and briefly mentioned other machine learning activities that are happening in the measurements and data department at MeteoSwiss.
Our paper on “Detecting temperature induced spurious precipitation in a weighing rain gauge” has been published in Meteorologische Zeitschrift, Vol. 28, No. 3.
I have contributed to the QC part of “Homogeneity assessment of phenological records from the Swiss Phenology Network”, which has been published in the International Journal on Biometeorology, Vol. 64, Issue 1.
I’m a member of the newly founded EUMETNET Scientific and Technical Advisory Committee Working Group on Automated Quality Control. At our first meeting in Exeter, the members presented the data processing and quality control methodologies of their respective met services. I gave a talk on some of the aspects of the MeteoSwiss data processing pipeline, with a detailed introduction to probabilistic plausibility.