The provision of weather forecasts for the London Olympic and Paralympic Games in 2012 offered the opportunity for the Met Office to accelerate the transition to operations of several advanced numerical modeling capabilities and to demonstrate their performance to external scientists. It was also an event that captured public interest, providing an opportunity to educate and build trust in the weather forecasting enterprise in the United Kingdom and beyond. The baseline NWP guidance for the duration of the Olympic Games came from three main configurations of the Met Office Unified Model: global 25-km deterministic, North Atlantic/Europe 18-km ensemble, and U.K. 1.5-km deterministic. The advanced capabilities demonstrated during the Olympic Games consisted of a rapid-update hourly cycle of a 1.5-km grid length configuration for the southern United Kingdom using four-dimensional variational data assimilation (4D-Var) and enhanced observations; a 2.2-km grid length U.K. ensemble; a 333-m grid length configuration of the Unified Model and 250-m configuration of the Simulating Waves Nearshore (SWAN) ocean wave model for Weymouth Bay; and a 12-km grid length configuration of Air Quality in the Unified Model with prognostic aerosols and chemistry. Despite their different levels of maturity, each of the new capabilities provided useful additional guidance to Met Office weather advisors, contributing to an outstanding service to the Olympic Games organizers and the public. The website provided layered access to information about the science and to selected real-time products, substantially raising the profile of Met Office weather forecasting research among the United Kingdom and overseas public.
Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.