Review: The Quiet Revolution of Numerical Weather Prediction

By WMO Secretariat1

Peter Bauer, Alan Thorpe and Gilbert Brunet have published a fascinating tale that will give readers a special flavour of how science can be both intriguing and valuable for humanity. The Quiet Revolution of Numerical Weather Prediction2 was published in “Nature” this September (Nature, vol. 525, 3 September 2015).

Global weather prediction is one of the largest scientific and technological challenges in the twenty-first century. As particle physics, astronomy and life science, it requires a broad array of experiments and large facilities in order to address fundamental questions – and to produce valuable, every day information to run our lives.

Based on the first attempts to predict the weather, making use of the first electronic computers at Princeton and in Stockholm after World War II, the modern physics of forecasting is now developing along three main lines:

  • The inclusion of more and more atmospheric processes, because of the finer granularity in numerical weather prediction models, incorporating interactions with hydrology, oceanography and chemistry.
  • The recognition that errors in the initial conditions will grow because of the nonlinear complexity of the system brought to an ensemble approach. The authors note that “Weather forecasts today involve an ensemble of numerical weather predictions, providing an inherently probabilistic assessment” – a major achievement in physical science.
  • How to make a perfect use of imperfect observations into imperfect models. A variety of new mathematical methods, under the name of data assimilation, have been developed to address this issue. An intrinsic link between observational strategies and modelling advancements has been establishe

Where we are? And where we are going? These are the two key questions the article answers. Over the past 40 years, forecast skill has been increasing by about one day per decade – a unique accomplishment that is moving science from research into practical solutions. WMO, through key programmes such as the Global Atmospheric Research Programme (GARP), The Observing system Research and Predictability Experiment (THORPEX) and the World Weather Research Programme (WWRP), is strongly engaged in contributing to this global effort.

The article highlights how the inter-linked evolution of weather science and of high-performance computing is crucial for continued progress in numerical weather prediction and for providing more valuable services. However, the authors did not highlight the promise that cheaper computing holds for reducing the technological gap between developed and developing countries in the area of numerical weather prediction.

The authors feature key elements and priorities towards a seamless world where weather and climate prediction skill are closely linked, “because accurate climate prediction needs a good representation of weather phenomena and their statistics, as the underlying physical laws apply to all prediction time ranges”. I would recommend this article to the scientific community to whom it will offer motivation and to the broader public who will be inspired by this story of science in service of humanity. 




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