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UNIV OF ILLINOIS AT URBANA-CHAMPAIGN

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38 Projects, page 1 of 8
  • Funder: NIH Project Code: 1H13DP525001-01
    Partners: UNIV OF ILLINOIS AT URBANA-CHAMPAIGN
  • Funder: UKRI Project Code: NE/X01004X/1
    Funder Contribution: 79,204 GBP
    Partners: University of Birmingham, UNIV OF ILLINOIS AT URBANA-CHAMPAIGN

    Severe synoptic-scale windstorm events in the Northwest Atlantic are affecting the UK and western Central Europe in winter (DJF). Damages in the magnitude of ca. EUR 3,610 million were recorded for the last season in 2021/22. Those damaging, rare events are linked to the development of strong storm cyclones in the climate system of the North-Atlantic. This project will explore the opportunity to provide skilful and useful predictions of the winter storm season ahead of the season in November. Thus, it will explore and understand our ability to predict whether it will be e.g., an active season (number of severe events) or not, whether we can have confidence in the forecast at the time of it being issued and what the reasons for this confidence would be. Usability of predictions of the upcoming winter storm season depends a) on our understanding of the factors leading to the variability of storms, and b) on our understanding how a forecast for the next season will depend on these factors. This project will explore one potential critical factor and its role for the forecast skill of severe events leading to loss and damage. One crucial factor of steering the climatic conditions in the North-Atlantic and Europe is the forcing of the atmospheric conditions (and here especially its baroclinicity) from anomalous sea-surface temperature patterns. So called re-emerging (in autumn/winter) temperature anomalies (from summer) would provide a potential mechanism for memory transport (via slow-varying components of the climate system) from late summer/early autumn to winter and finally resulting in extreme storm activity. Recent developments in seasonal forecast suites to forecast those oceanic re-emerging events are existing and this project will explore their role in steering variability of the storm season in reality as well as to quantify their potential role in gaining forecast skill in the model domain. EX-Storms will apply a novel approach (UNSEEN, i.a. pioneered by the applicant) to use non-realised but physically consistent events from century long seasonal and decadal hindcast (multi-member ensembles) to explore this physical pathway influencing the winter storm activity level. For the first time, EX-Storms will explore how far our current abilities allow for a pre-season view on the upcoming risk of severe storms.

  • Funder: UKRI Project Code: BB/M006468/1
    Funder Contribution: 396,748 GBP
    Partners: University of Edinburgh, UNIV OF ILLINOIS AT URBANA-CHAMPAIGN

    In most plants, growth rate is limited by the rate at which carbon dioxide from the atmosphere is taken up and converted to sugars in the process of photosynthesis. The enzyme responsible for the first step in this process, Rubisco, does not work at its potential maximum efficiency at the current levels of carbon dioxide present in the atmosphere. If levels were much higher, photosynthesis would be increased and plant productivity would be higher. There is an immediate requirement for increased crop productivity to provide food for the rising population of the planet. Our project addresses this problem. We are studying a mechanism present in unicellular green algae that results in high concentrations of carbon dioxide inside their photosynthesising cells (called a Carbon Concentrating Mechanism, or CCM), enabling Rubisco to work at maximum efficiency. During the initial CAPP1 programme, we discovered important new information about this mechanism, and using new and rapid methods we have identified novel algal genes and additional regulatory components which allow the CCM to operate in association with a specific micro-compartment called a pyrenoid. We have also successfully introduced some of these components into a model higher plant, Arabidopsis, and also successfully introduced a modified form of Rubisco which may facilitate aggregation into the pyrenoid. The ambitious goals of the CAPP2 extension will be to combine the expression of the CCM and pyrenoid in the Advanced Plant. Firstly, we will continue to identify genes required by the algae to achieve high concentrations of carbon dioxide inside the cells, and develop new markers and sensors to reveal the location and activity of these genes when expressed in the higher plant. Secondly, we will identify additional regulatory elements needed to form a pyrenoid, as well as exploring the impact on Rubisco enzyme efficiency and light utilisation. Thirdly, we will continue to introduce successive components into our model Advanced Plant so as to "stack" up the activities of CCM components and examine the extent of pyrenoid formation and enhanced productivity associated with the CCM. This work will provide new insights into how plants and algae acquire and use carbon dioxide from the atmosphere, of great importance in predicting and coping with the current rapid changes in the atmosphere and hence in climate. The work will also contribute to strategies to increase global food security, because it will indicate new ways in which crop productivity can be increased.

  • Funder: UKRI Project Code: BB/J01981X/1
    Funder Contribution: 49,598 GBP
    Partners: UNIV OF ILLINOIS AT URBANA-CHAMPAIGN, University of Bristol

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

  • Funder: UKRI Project Code: BB/L026562/1
    Funder Contribution: 30,204 GBP
    Partners: Pirbright Institute, UNIV OF ILLINOIS AT URBANA-CHAMPAIGN

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.