University of Reading and US Scientists Team Up to Boost Weather Forecast Accuracy

University of Reading Researchers Team Up with U.S. Scientists to Enhance Weather Forecast Accuracy

The University of Reading, in a collaboration orsed by the Biden-Harris administration and backed financially by the National Oceanic and Atmospheric Administration NOAA, has launched the Consortium for Advanced Data Assimilation Research and Education CADRE. This initiative ms at refining numerical weather prediction techniques through the use of advanced tools to boost forecast accuracy.

Leadership and Partnerships

Directed by the University of Oklahoma, CADRE brings together experts from across the U.S., along with mathematicians from the University of Reading’s School of Mathematical, Physical and Computational Sciences. A key component is the Data Assimilation Research Centre DARC, part of DARC at the University of Reading. of data assimilation involves merging weather observations with numericalto furnish the initial conditions for forecasts.

Professor Sarah Dance, co-director of DARC at the University of Reading, emphasized the significance of this project: We are thrilled that NOAA has funded a consortium that facilitates collaborations with our esteemed colleagues from the U.S., and we look forward to initiating new partnerships. The enhancement in numerical weather prediction through innovative techniques promises to refine computer' capacity for predicting weather changes. This is essential for foreseeing hazardous events like storms, high winds, floods, droughts, and heatwaves more accurately, particularly as these occurrences are anticipated to become more common due to climate change.

Professor Amos Lawless, co-director of DARC at the University of Reading's School of Mathematical, Physical and Computational Sciences further elucidated: Our country invests over ￡50 million annually in satellites for weather forecasting purposes. Research on data assimilation is pivotal for making optimal use of satellite and other instrumentation data to improve our forecasts. By integrating weather observations with, we are creating improved starting points for predictions while solving complex mathematical equations that forecast how weather evolves over time. However, there exist considerable challenges due to the intricacy of theseand the vast amounts of data involved.

Cross-Pollination Efforts

Under this project, Ph.D. students and postdoctoral researchers from the U.S. will partner with their colleagues at the University of Reading on developing cutting-edge data assimilation techniques. The University of Reading is also collaborating with other UK universities, the National Centre for Earth Observation, and the Met Office to design a cohesive Transatlantic Data Science Academy. This program focuses on enhancing workforce diversity in weather and climate science by offering skills development and career opportunities.

Overcoming Data Assimilation Challenges

Next-generation data assimilation confronts significant hurdles due to substantial gaps within the global data assimilation workforce and a lack of sustned innovative research efforts in this field. Through close collaborations with NOAA, the UK Met Office, and its academic partners including the University of Reading, CADRE is tackling these challenges along with the new Transatlantic Data Science Academy.

This initiative cultivate an inclusive community by enhancing data assimilation skills among professionals while addressing the current shortages within the workforce.
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