Met Office Academic Partnership Science Framework

To foster the Partnership the Met Office invests in jointly funded chairs (‘MOAP Joint Chair Services’) with partner Universities. Up to 8 Universities will be awarded a place on Lot 1 to deliver Joint Chair Services.

Hazard to Decision Making Research and Innovation Theme Expand and improve our services for stakeholders’ risk-based decision making by working with users, social scientists, behavioural scientists, financial impact experts and engineers to gain an increased understanding of the impacts of hazards and to develop better impact based services.

Research to Production Theme Pull through developments in weather and climate research to improve our forecast systems, tailored to services in the forecasting timescales of primary interest to the Met Office and its customers.

Producing, Refining and Delivering data Theme Develop the Met Office supercomputing estate for operations and research, establish the technology and science needed to move, store and process our data, and design a flexible post-processing framework to turn predictions and observations into customer products.

Seamless Environmental Prediction Theme Further develop our world-leading seamless environmental prediction capability, whereby a single model family is used in conjunction with observations and theory, to quantify weather hazards in the past, in present day climate and into the future across weather and climate timescales.

Next Generation Modelling Systems Theme Revolutionise the Met Office’s complete weather and climate research and operational simulation systems so that the Met Office and its partners are ready to fully exploit future generations of supercomputer.

Fusing Simulation with Data Sciences Theme Use new and evolving data science methods such as artificial intelligence and machine learning and advanced data assimilation in order to remain at the cutting edge of weather and climate prediction and impact-based services.

The Path to High Resolution Theme In order to better predict hazards and extremes, develop the next generation of very high resolution global and regional environmental prediction systems, based on global convection-permitting atmosphere models coupled to eddy-resolving ocean models and eddy-permitting regional atmosphere models coupled to estuary-resolving shelf-seas models.

In order to include forecasts of uncertainty at the heart of our endeavour, develop ensemble based systems and exploit them for prediction across timescales, while developing new and novel uses of ensemble information for improved understanding of weather and climate.

Capturing Environmental Complexity Theme In order to pioneer new and improved impact based forecast services and advice on global climate change mitigation, extend our environmental prediction capability with a focus on cities, air quality, the water cycle, and carbon and nitrogen cycles.

The Met Office is looking to develop a federated cloud data platform for Met Office and partner scientists and experts. This will mean developing appropriate standards for data and cloud service interoperability, enhancing opportunities for collaboration on weather and climate domain protocols, APIs, and architectures; and developing a high level platform service model for weather and climate domain users, such as supercomputing services, data/model cataloguing and discovery, adhoc query engines over massive data sets, cross platform data notification and pipelining from modelling through to data services.

The Met Office is seeking a step change in its observational capability to deliver what is needed in the 2030s through realising the value of third party and opportunistic observations. This will mean enhancing benefits from underpinning reference and baseline observation networks; systemically enabling access to non traditional and third party observational data; identifying opportunities to assess low Technology Readiness Level observational opportunities for viability; and developing methodologies to exploit these data.

Co-Sponsorship Agreements may be available for up to 8 Universities (The same Universities who achieve a Joint Chair Services place on Lot 1). These agreements are approximately 10 in number per annum covering various jointly funded key personnel to support delivery of MOAP research projects.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.

• Reference: 028822-2022-dn600943 - moap science delivery framework-1
• Value: £8,000,000 [share]
• Awarded to group of suppliers.