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Ben Snaith

345725803-The-state-of-weather-data-infrastructure-white-paper.pdf - 1 views

ODI-Outputs Weather Data-Infrastructure Data Data-Institution

shared by Ben Snaith on 19 May 20 - No Cached
  • From its early beginnings over 150 years ago, weather forecasting at the Met Office has been driven by data. Simple observations recorded and used to hand-plot synoptic charts have been exchanged for the billions of observations received and handled every day, mainly from satellites but also from weather stations, radar , ocean buoys, planes, shipping and the public.
  • The key stages of the weather data value chain are as follows: Ÿ Monitoring and observation of the weather and environment, e.g. by NMSs. Ÿ Numerical weather prediction (NWP) and climate modelling carried out by NMSs to create global, regional and limited area weather forecasts. Private companies are growing their presence in the market and challenging the traditional role of NMSs to provide forecasts to the public, by statistically blending data from NMS models to create their own forecast models, for example. Other companies providing data via online channels and/or apps include The Weather Company, Accuweather or the Climate Corporation. Ÿ Communication and dissemination of forecasts by news, NMS and media organisations like the BBC, Yahoo and Google, or within consumer-targeted mobile and web applications. Ÿ Decision making by individuals and businesses across a variety of sectors, which draws on weather data and reporting.
  • The core data asset of our global weather data infrastructure is observation data that captures a continuous record of weather and climate data around the world. This includes temperature, rainfall, wind speed and details of a host of other atmospheric, surface and marine conditions.
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  • The collection of observation data is a global effort. The Global Observing System consists of around 11,000 ground-based monitoring stations supplemented with thousands of sensors installed on weather balloons, aircraft and ships. 3 Observations are also collected from a network of radar installations and satellite-based sensors. As we see later, the ‘official’ observation system is increasingly being supplemented with new sources of observation data from the Internet of Things (IoT).
  • Ensemble model forecasts aim to give an indication of the range of possible future states of the atmosphere and oceans (which are a significant driver of the weather in the atmosphere). This overcomes errors introduced by using imperfect measurement of initial starting conditions that are then amplified by the chaotic nature of the atmosphere. Increasing the number of forecast members over a global scale and at higher resolutions result in data volumes increasing exponentially .
  • Created in 1950, The World Meteorological Organisation (WMO) is made up of 191 member states and territories around the world. The WMO was founded on the principle that global coordination was necessary to reap the benefits of weather and climate data. This includes a commitment to weather data and products being freely exchanged around the world (Obasi, 1995).
  • While the WMO has a global outlook, its work is supplemented by regional meteorological organisations like the European Centre for Medium Range Weather Forecasts (ECMWF) and NMSs, such as the Met Office in the UK
  • There are increasing new sources of weather observation data. In recent years, services like Weather Underground and the Met Office’s Weather Observation Website have demonstrated the potential for people around the world to contribute weather observations about their local areas – using low-cost home weather stations and sensors, for example. But there is now potential for sensors in cities, homes, cars, cell towers and even mobile phones to contribute observational data that could also be fed into forecast models.
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