The weather information value chain is a framework that describes how information is produced, communicated, and used in an end-to-end warning system for weather and hazard monitoring. A project under the WMO aims to explore value chain approaches to describe and evaluate high-impact weather events. The project developed a template for high-impact weather event case study collection, which allows scientists and practitioners to assess the effectiveness of warning value chains.

This paper reviews new observations for the verification of high-impact weather and provides advice for their usage in objective verification. New observations include remote sensing datasets, products developed for nowcasting, datasets derived from telecommunication systems, data collected from citizens, reports of impacts and reports from insurance companies. This work has been performed in the framework of the Joint Working Group on Forecast Verification Research (JWGFVR) of the WMO.

We present the first representation of grass pollen in a 3-D dispersion model in Australia, tested using observations from eight counting sites in Victoria. The technology was developed in response to the severe thunderstorm asthma event which took place in Melbourne in November 2016. A total of 10 pollen emission methodologies were developed and evaluated. The best results were obtained using statistical methods that included elements of the satellite derived enhanced vegetation index.