The Environmental Modelling group comprises a diverse group of researchers who are leading efforts to better understand the complexities of atmospheric, hydrological, geomorphological and ecological systems and their responses to, and feedbacks with, environmental change. The complexity and inherent non-linearity of environmental system behaviour means that such questions must necessarily be approached through modelling of various kinds. Innovative model-based science combined with rigorous observation and validation is central to the work of this cluster. We have received significant and sustained external funding from, inter alia, EA, ESA, NASA, EU Framework, DEFRA, DiFID and NERC, and enjoy strong collaborative linkages with the Recent Environmental Change and Past Climates research clusters in UCL Geography. Our work is focused under two major themes: (1) Modelling Climate Change, Its Impacts and Adaptation; and (2) Modelling and observing Terrestrial Ecosystems. There is considerable crossover between these themes, especially through the development, enhancement and implementation of numerical and analytical techniques.
1. Modelling Climate Change, Its Impacts and Adaptation
Our aim under this theme is to elucidate the subtleties of climate change and to contribute new and more robust methodologies with which to understand and predict the response of diverse earth surface systems to environmental variability and change more generally, and the appropriateness of alternative adaptation strategies. Our work in this area is characterised by a wide spectrum of models and methodologies deployed over a cascade of scales, from the global to the local. Key highlights and achievements under this theme include:
- Understanding future climates (Chris Brierley). At a global scale, GCMs have been used by Brierley to provide fundamentally new insights into the warmer climate of the early Pliocene as the closest analogue to the likely effects of contemporary global warming. In a separate strand of work, Brierley has also shown that, whilst the global effect of ocean parameter uncertainties on the rate of transient climate change is small compared to that resulting from uncertainty in atmospheric model parameters, ocean parameter uncertainty may be more significant for probabilistic assessments of regional climate change.
- Regional impacts of climate change (Richard Taylor, Julian Thompson). Downscaling of global model projections provides crucial boundary conditions for analyses of climate change impacts at regional, catchment and smaller scales. Through the combination of process based hydrological models and GCM projections, Taylor and Thompson have investigated the uncertainty associated with hydrological and water resource impacts of climate change. This has been undertaken for a diverse range of catchments with results being compared to global hydrological model projections. Thompson has used downscaled regional climate model projections to assess fine-scale modifications to UK wetland water levels and flood extents and, in turn, the likely impacts of these changes on wetland flora and fauna. This research has contributed to methodologies designed to provide nationwide assessments of the sensitivity of wetlands to climate change.
- Coastal system responses to climate change and human activity (Helene Burningham, Jon French). At a coastal shelf scale, the first detailed analysis of historical seabed dynamics in the southern North Sea and Greater Thames has revealed a remarkable persistence of the major tidal bank systems, with change over a 200-year period being predominantly oscillatory rather than secular in nature. In the most detailed analysis to date of the linkages between the North Atlantic Oscillation winter index and wind data from land stations in northwest Europe, we show that the NAO is a much weaker proxy for storminess than is commonly supposed, but is still implicated in forcing coastal changes through its influence on wind and ocean wave direction. At the estuary scale, our work on sediment flux modelling that has highlighted a previously neglected sensitivity of muddy coastal and estuarine systems to changes in wind climate. Numerical hydrodynamic modelling has also been used to challenge the appropriateness of flood defence realignment as an adaptive response to sea-level rise, and this has highlighted important incompatibilities between flood protection and habitat restoration goals. We are also working on the development of more sophisticated ways of evaluating the performance of coastal process models that take account of a wider range of error sources (including uncertainty in the underlying bathymetric data) and also provide more diagnostic information on the sources of model error.
2. Modelling and Observing Terrestrial Ecosystems
Our aim under this theme is to develop our understanding of radiation interactions with the terrestrial land surface, particularly vegetation, and exploit this understanding in the application of Earth Observation to monitoring and quantifying terrestrial ecosystem dynamics. EO data are fundamental to quantifying ecosystem states and dynamics because of their spatio-temporal coverage across scales, and their information content. Through the work of Philip Lewis and Mat Disney, the cluster is playing a leading role in international efforts to improve the way we exploit observations of the land surface, particularly in moving the field from loose empirical correlations to using physically-based models for retrieving biophysical parameters. Recent highlights and achievements under this theme include:
- New methods for exploiting global-scale satellite observations. New products developed by Lewis and Disney have become firmly established as de-facto standards, disseminated by both NASA and ESA. The MODIS albedo product for example, developed in collaboration with NASA colleagues, is used by hundreds of researchers world-wide across a wide range of disciplines. For example, it has been used to quantify uncertainty in radiative forcing in GCM climate simulations (IPCC AR4). A second theme of our work is developing new frameworks for combining observations with models, through data assimilation. We have published some of the first results using satellite observations of the land surface to constrain terrestrial ecosystem models. We are currently funded by ESA to extend and develop this approach to exploit European satellite products for albedo, as part of the ESA Climate Change Initiative.
- EO data products. We have also been instrumental in developing EO products quantifying disturbance, due to fire in particular, as shown by our work on the development of the MODIS Burned Area product, and through ESA-funded work on monitoring fire impacts. This is of key relevance for C cycle feedbacks to climate, as the impacts of fire are poorly represented in large-scale models at present. As a result of our work in understanding how EO can be used to constrain and test C cycle models we have been funded since the inception of the NERC Centres of Excellence in EO, now through the NERC National Centre for Earth Observation, which was established by the UK Government in part to allow more direct pull-through from EO science to policy. As an example, we have provided evidence to DEFRA on how EO can contribute to monitoring UK commitments on emissions.
- Model – data linkages. The third key area of our work is developing new modelling methods for understanding existing observations and paving the way for new and novel observation techniques. We have a world-leading capability for modelling radiation in vegetation, and have applied this to the understanding of observations such as LIDAR (light detection and ranging). This has led to collaborations both within the UK and abroad (NASA, NSF, CSIRO) and funding for developing/testing new lidar systems, including with the commercial sector. We have been funded by ESA for quantifying the performance of proposed new satellite systems. We are currently funded to develop modelling tools to allow researchers to simulate the observation characteristics of new ESA satellite systems.
Click here for a list of some of our recent research grants.
- Dr Chris Brierley (Climate modelling)
- Dr Helene Burningham (Coastal and estuarine geomorphology; GIS)
- Dr Mat Disney (Remote sensing)
- Professor Jon French (Environmental modelling; coastal, estuarine and limonological processes)
- Professor P Lewis (Remote sensing; vegetation modelling)
- Dr Richard Taylor (Hydrogeology and water management)
- Dr Julian Thompson (Wetland hydrology and management)
- Dr Jose Gomez Dans (Earth observation)
- Emily Lines (Earth Observation)
- (NERC iCOASST Project: coastal systems modelling)
- Professor Ray Harris (Earth Observation and data policy)
- Professor Andrew Warren (Aeolian processes; dryland management)
- (CEH Wallingford; Wetland hydrology)
- Professor Alan Jenkins (CEH Wallingford; Water chemistry and catchment acidification)