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Science and Technology Facilities Council (STFC) Delivery costs of International Science Partnerships Fund (ISPF) ODA activities
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Operational costs occurred at Science and Technology Facilities Council (STFC) associated with hosting and/or managing ODA International Science Partnerships Fund (ISPF) programmes
ISPF-034, Supporting a neutron and muon user community in Indonesia and Malaysia 2025/2026
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
The initial cost of building and running large research facilities is often prohibitive to developing countries. This programme aims to build research capacity in ODA relevant research areas by allowing access to UK research infrastructures, specifically the ISIS Neutron & Muon Source, for Indonesian and Malaysian researchers. It will also develop a relationship with ASEAN funders to further spread the use of neutron and muon techniques.
Royal Society -International Collaboration Awards -International Science Partnerships Fund
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
The International Collaboration Awards (ICAs) provide crucial funding to support outstanding emerging research leaders in the UK and either Brazil or South Africa in developing research collaborations that primarily address development challenges faced by developing countries, with strong encouragement to include a Least Developed Country (LDC) in the partnership. This ODA-funded program is designed to foster sustainable collaborative research partnerships, aimed at generating innovative approaches to tackle significant and complex problems prevalent in developing nations. The grants, open to newly independent researchers who are ready to lead international research initiatives, will strengthen research capacity through the collaboration, sharing of knowledge and skills, and exchange of staff between UK institutions and their partners in developing countries. By attracting top international scientists to work with UK’s leading universities, this program enhances the research quality and impact on global development challenges, aligning with the primary objective of ODA to promote the economic development and welfare of developing countries. The Royal Society will offer grants up to £225k over three years, with an additional £25k per year for capacity strengthening in African Least Developed Country (LDC), ensuring the funding is used flexibly on activities directly relevant to the proposed research collaboration.
Royal Society - ODA Delivery Costs -International Science Partnerships Fund
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Delivery costs for ODA International Science Partnerships Fund (ISPF) programmes at the Royal Society.
Royal Society: Core and Resilient Futures - UK ODA Fellowships
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Fellowships for non-UK scientists who are at an early stage of their research career and wish to conduct research in the UK. (From the Resilient Futures Collective Fund).
Engineering and Physical Sciences Research Council (EPSRC) Delivery costs of International Science Partnerships Fund (ISPF) ODA activities
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Operational costs occurred at Natural Environment Research Council (NERC) associated with hosting and/or managing ODA International Science Partnerships Fund (ISPF) programmes
Amazon +10 Initiative
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
This call will support UK-Brazil research expeditions to improve our knowledge of the biodiversity and socio-cultural diversity in the Brazilian Amazon. Projects will address geographic and taxonomic biases in our understanding and encourage co-creation of research with traditional knowledge holders from local and indigenous communities. This will support sustainable development of the Amazon by enabling better use of the region’s natural resource and associated traditional knowledge. This opportunity is led by Brazil (CONFAP and CNPq) and forms part of the wider Amazon+10 initiative. It will strengthen UK-Brazil (both UKRI and the British Council will participate in this opportunity) research and position the UK as a key global player in biodiversity conservation and sustainable development.
Weather and Climate Science for Service Partnership S E Asia (WCSSP) - Calls - tender - UNIVERSITY OF LEEDS
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Strengthened partnership between meteorological services in UK, Philippines, Malaysia Vietnam, and Indonesia - research on understanding and evaluating convective processes over SE Asia.
Climate Science for Service Partnership (CSSP) Brazil - Calls- tender-UNIVERSITY OF LEEDS
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Collaborative climate science research programme between Brazilian and UK to improve understanding of recent climate changes and Brazil’s role in mitigation activities to inform international negotiations; to enhance projections of future weather and climate extremes and impacts to inform decision making and contribute to disaster risk reduction in Brazil. Research on Moisture Transport and Deforestation.
Climate Science for Service Partnership (CSSP) Brazil - Calls- tender-UNIVERSITY OF LEEDS
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Collaborative climate science research programme between Brazil and UK to improve understanding of recent climate changes and Brazil’s role in mitigation activities to inform international negotiations; to enhance projections of future weather and climate extremes and impacts to inform decision making and contribute to disaster risk reduction in Brazil. Research hydrological cycle responses to land-use change and climate change over Brazil
Climate Science for Service Partnership (WCSSP) South Africa - Calls- tender-UNIVERSITY OF SOUTHAMPTON
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Collaborative project between meteorological services in South Africa and UK focusing on capacity building for improved weather and climate services, enabling mitigation of risk from extreme weather events. Research into improving representation of Climate Variability and change over Africa by using Machine Learning as a tool for Data Rescue.
Weather and Climate Science for Service Partnership (WCSSP) India - Calls- tender-SCIENCE AND TECHNOLOGY FACILITIES COUNCIL (STFC)
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
To undertake research on natural hazards in South Asian Monsoon system (both summer and winter); Improve capability of global coupled, regional convective scale (km) coupled and sub-km city-scale (300m) modelling frameworks to predict priority natural hazards over India. This is for 100TBAs storage on the JASMIN system to support scientists storing and sharing their outputs in order to carry out research for the weather and climate science to service partnership (WCSSP).
Weather and Climate Science for Service Partnership S E Asia (WCSSP) - Calls - tender - SCIENCE AND TECHNOLOGY FACILITIES COUNCIL (STFC)
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Strengthened partnership between meteorological services in UK, Philippines, Malaysia Vietnam, and Indonesia. This is for 100TBAs storage on the JASMIN system to support scientists storing and sharing their outputs in order to carry out research for the weather and climate science to service partnership (WCSSP).
Climate Science for Service Partnership (CSSP) Brazil - Calls- tender-UNIVERSITY OF READING
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Collaborative climate science research programme between Brazil and UK to improve understanding of recent climate changes and Brazil’s role in mitigation activities to inform international negotiations; to enhance projections of future weather and climate extremes and impacts to inform decision making and contribute to disaster risk reduction in Brazil. Research into Sub-seasonal and seasonal predictions for advancing climate services in Brazil. Specifically this grant will support the development of communication materials to support partner uptake of programme outputs.
AI for Climate - calls - tender - UNIVERSITY OF LEEDS
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Kilometre-Scale Simulations for Al Training - High-impact weather (HIW) events, such as heavy rain and consequent flooding and landslides, or drought, can be devastating to the livelihoods of local people and the economy of many countries in the tropics. The societal and economic impacts of HIW include loss of human life, damage to property, destruction of crops, loss of livestock, poor health, displacement of populations, loss of infrastructure, severe disruption to transportation from heavy rainfall, and the suspension of many economic activities (UNDRR, 2019, 2020a, 2020b, 2020c). Almost all HIW is expected to increase across the tropics and sub-tropics with ongoing climate change, affecting the poorest and most vulnerable. Improved projections of climate change in HIW aid adaptation, and motivate mitigation. However, in many tropical regions it is unclear whether regions will become wetter or drier (IPCC), limiting adaptation. UPSCALE will focus on the tropics, where moist convection dominates rainfall and is a primary source of heating to the tropical atmosphere, and where we can use the full model hierarchy including the cyclic-tropical-channel. The UPSCALE project will conduct research into (1) the evaluation of the newly developed Met Office Convection-Permitting Models (CPM) hierarchy of simulations, and (2) the development and application of novel process-based diagnostics and propose sensitivity experiments to understand the mechanisms of up and down scale interactions in the CPMs vs. current simulations with parametrised convection, focusing on the value of large pan-tropical domains. These activities will benefit weather forecasting and climate prediction, especially for the tropics/sub-tropics, including the development of machine learning-based predictions. The K-Scale simulations work package would exploit UK and international research in K-scale modelling with both developed (Australia, U.S.) and developing countries (India, S. Africa) to derive additional value from these high-resolution simulations as training data for AI data driven prediction systems that could then be exploited by partners. The resource would accelerate development and evaluation of the K-scale predictions and work with dataset curators/developers to ensure efficient workflows for ML applications. Initially the work will be on using research we are currently collaborating with partners on and deployment with in-country partners in subsequent years.
Climate Science for Service Partnership (CSSP) Brazil - Calls- tender-UNIVERSITY OF LEEDS WP3
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Constraining future projections of wildfire and air quality in Brazil This project will bring together and analyse data on fire, climate, air pollution and human health to improve our understanding of the climate and human drivers of wildfire and poor air quality across Brazil. We will use new understanding gained from analysis of historical fires to help constrain future model projections of wildfire and air quality in Brazil. We will provide new evidence of how fire and land management alongside other mitigations could reduce exposure to poor air quality. We will work to develop UK-Brazil collaborations on wildfire and air quality and ensure outputs from the research inform policy and decision making in Brazil.
Weather and Climate Science for Service Partnership (WCSSP) South Africa - Calls- tender-HR WALLINGFORD
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Informing context-specific needs for impact-based early warning systems South Africa experiences a wide range of weather and climate-related extremes, including droughts, storms, floods and heat waves which are projected to get worse with climate change. Recent examples of extreme weather events include the 2018 drought in the Western Cape, when Cape Town came dangerously close to what was described as "Day Zero", the moment when approximately four million inhabitants would have been left without water (Pascale et al., 2020) and the April 2022 floods in KwaZulu-Natal which left over 460 people dead and caused US$1.6 billion of damage (Keen et al., 2022). In February 2025, South Africa was hit by extreme weather which resulted in thunderstorms, tornados and flash floods over large areas of the country leading to widespread disruptions to the education system in some provinces and two school children tragically dying in flash floods (Daily Maverick, 2025). Climate change will have an impact on South Africa via, for example, increases in droughts which will affect the agricultural sector and maximum wet bulb temperatures which will adversely affect mortality rates, especially for those living in informal settlements, where houses are often constructed of sheets of corrugated iron (Chersich et al., 2018). Under a high greenhouse gas emissions pathway, climate change is also projected to have potentially devastating impacts on South Africa’s coastal settlements and infrastructure, owing to rising sea levels, coastal erosion, and changing storm patterns, which will combine to worsen coastal flood events (Cartwright, 2011; Dube et al., 2021). One way to ameliorate the effects of extreme weather-related events is via Impact-based Forecasts and Warnings (IbFWs). IbFWs provide stakeholders with the information they need to act before disasters occur, helping them to reduce the socio-economic costs of weatherrelated hazards. In 2020, the South African Weather Service (SAWS) introduced a new severe weather warning system which provides impact-based warnings. SAWS adopted a qualitative approach, as opposed to a quantitative model-based approach, to identify impacts, whereby hazard forecasts are translated into qualitative and selected impacts by emergency managers on the ground. This approach means that emergency managers make the choices on which impacts deserve to be communicated, and which ones are left out.
Weather and Climate Science for Service Partnership (WCSSP) South Africa - Calls- tender-UKCEH
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
WARD SA: Water Availability duRing Drought in South Africa South Africa is a semi-arid to arid country, with low rainfall (~500 mm annual average) (Abiodun, Naik , Mogebisa, & Makhanya, 2022) and high evaporation rates. Rainfall over South Africa is highly variable, both spatially and temporally, and the country often experiences meteorological drought. The intensity of meteorological drought is projected to increase under climate change (Engelbrecht F. A., Steinkopf, Padavatan, & Midgley, 2024), and is a significant risk to sustainable development into the future. Because of South Africa’s high levels of terrestrial, freshwater and marine biodiversity and endemism, South Africa’s progress towards environmental sustainability is critically dependent on being able to predict and manage hydro-climate risks into the future (Mutanga, et al., 2024). While South Africa has a long tradition of research-based approaches to the management of its water resources (Morant & Quinn, 1999) and there has been significant research on future climate over Southern Africa (Engelbrecht F. A., Steinkopf, Padavatan , & Midgley , 2024; Engelbrecht & Monteiro, 2021), there have been relatively few studies on the impacts of climate change on hydrology and water resources (Kusangaya, Warburton, van Garderen, & Jewitt, 2014). This information is key to future planning of water resource management, to assist decision making and to inform potential adaptation and mitigation strategies. Until relatively recently, land surface models, such as the Joint UK Land Environment Simulator (JULES), have tended to ignore water resource management activities, instead representing a more nearly natural system. More recently land surface models have started to recognise the importance of better representing human management of the natural world, often using approaches pioneered in earlier global hydrology models such as H08, WaterGAP and GWAVA (Hanasaki N. , et al., 2008; Döll, Kaspar, & Lehner, 2003; Meigh, McKenzie, & Sene, 1999). However, to date JULES includes very little description of water resource management – just a simple scheme to acquire water for irrigation from soil and then rivers. Land surface models are used across a range of resolutions (i.e. the model gridbox size) from of the order of 50 km for global earth system applications, to of order 1 km in so-called “K-scale” applications. An area of active research is the extent to which model formulation and parameterisations need to be adapted for K-scale, and water resource management is no exception here. In WARD SA we will address these knowledge gaps by building on existing Water Resource Management (WRM) functionality in JULES to create a modelling tool which can be applied at coarse and fine spatial scales to assess the impacts of climate change on available water resources in Southern Africa. Driving data from the Inter-Sectoral Impacts Model Inter-comparison Project (ISIMIP) at 0.5⁰ spatial resolution, and km-scale data from convection-permitting models, will be used to produce simulations that can inform effective climate adaptation and mitigation action. Working closely with South African partners, different land and water resource management options will be investigated through a set of exploratory runs, demonstrating the potential for this tool to inform critical policy decisions. Alongside the development of JULES, WARD SA will explore the potential of Machine Learning (ML) methods to aid water resource forecasting in reservoirs. Machine Learning methods are being increasingly applied to hydrological modelling, particularly Long Short-Term Memory (LSTM) models (Kratzert, Gauch, Klotz, & Nearing, 2024). There are far fewer studies applying ML methods to reservoir storage or outflow (Dai, et al., 2022; García-Feal, González-Cao, Fernández-Nóvoa, Dopazo, & Gómez-Gesteira, 2022), perhaps because this data is far less available than streamflow data, but the restricted nature of reservoir data is what makes it a good candidate for ML methods. Operating rules for managed reservoirs are rarely openly available, so process-based models rely on generic equations with calibrated or approximated parametrisations, but ML methods can “learn” the operating rules provided there is sufficient training data. These ML models can then be run independently with appropriate driving data, or used as part of a hybrid modelling approach, to improve reservoir storage predictions and downstream flow simulations.
Weather and Climate Science for Service Partnership S E Asia (WCSSP) - Calls - tender - UNIVERSITY OF READING
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
Understanding and Prediction of Compound Ocean-Atmosphere Storms in the Tropics (SEA-COAST) The South-East Asia region (SEA) is prone to extreme precipitation and winds from weather systems operating at different scales, e.g. squall lines, tropical cyclones or cold surges. Ocean processes like ocean tides, sea-waves and ocean surge driven by these weather systems can aggravate their impacts, the so-called compound events. For example, increasing the risk of flooding in extreme precipitation events, or the risk of damaging infrastructure in extreme wind cases. The provision of effective weather warnings for coastal hazards over the SEA region requires sophisticated modelling tools, with enough detail to represent the multiscale behaviour of local hazards, the interactions between different components of the environment and the region’s complex coastlines and orography. Forecasting tools to support decision-making include an atmosphere model at convective scale resolutions to capture the convection processes and its feedback to larger scales, a full 3-D or a 2-D barotropic ocean model to capture tides and storm surge, and a wave model to capture the total sea level. These models run as an ensemble with schemes representing the uncertainty of the initial condition and modelled processes to capture the uncertainty of the events. Relevant areas of improvement include the prediction of the impacts and uncertainty of costal hazards linked to (a) tropical cyclone landfall for cases where rapid intensification occurred, (b) smaller-scale convective processes with an associated storm surge and enhanced seawaves. This work is focused on developing scientific understanding on the predictability of coastal hazards over SEA and the development of prototypes for forecasting coastal hazards and collaboration with in-country partners.
Weather and Climate Science for Service Partnership (WCSSP) India - Calls- tender-PML
DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY
River outflow to the ocean in the NEMO model of the Regional Coupled System is currently prescribed as pure fresh water input, either at the surface or on a few ocean levels. However, in reality, fresh water gets mixed with marine water in estuaries, and the inflow into the ocean has a very different salinity and temperature profile with depth than what is currently done in the NEMO model at river outflow points. Current Met Office simulations do have stability issues at river outflow points, because of the current crude estimation of river flows. Estuary box models are considered as the way forward for ocean models which can't explicitly resolve estuaries (Matte et al. 2025). This will enable better numerical stability to run month-long or multi-decadal simulations and better oceanic circulation, due to improved temperature and salinity profiles near coastlines. This work will allow a better understanding of the interactions between river outflow and the ocean to enable partners to better assess potential impacts and thus mitigate against climate change. Primary beneficiaries would be the South Asian region, particularly those countries with an Indian Ocean coastline.
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