The Climate dynamics group focuses on the modelling, analysis and understanding of the Earth system and its response to human perturbations.
We are working on many components of the Earth System such as: ocean-atmosphere dynamics and variability; aerosols, clouds and water cycle interactions; carbon cycle feedbacks; land surface biogeochemistry; sea ice dynamic; atmospheric chemistry; detection and attribution of climate change; etc.
To find out more about our academics and their research, please click on the accordions below under their name to find out more:
Members of our group are investigating initialised predictions of climate and are particularly interested in the recently uncovered 'Signal to Noise Paradox' which occurs especially in predictions around the Atlantic sector. This paradox arises from the fact that despite containing only small predictable signals and therefore being unable to predict themselves, ensemble climate predictions are able to skilfully predict real world variations in climate such as the North Atlantic Oscillation.
Figure 1: Predictability of the North Atlantic Oscillation in the real world (black) is higher than the predictability in the model (blue).
The effects of ensemble size on seasonal hindcasts of the winter North Atlantic Oscillation are plotted. The black line shows the average correlation score when different size ensemble averages are correlated with the observed NAO (rmo). The blue line shows the same quantity when ensemble means are correlated with a single forecast member (rmm). The black dotted line is a theoretical fit to the solid black line23. The skill grows with ensemble size due to the suppression of unpredictable noise, but in principle the curves should be the same. In practice the model is better able to predict the real world than itself. Data are from the GloSea5 forecast system, after Scaife et al (2014b).
Publication: A Signal to Noise Paradox in Climate Science.
General circulation models (GCMs) are the only tools at our disposal for predicting future climate, however, the current representation of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Despite decades of research, reducing these uncertainties has proved extremely challenging.
Accordingly, the goal of my research is to improve the representation of aerosol-cloud interactions in GCMs and subsequently reduce the uncertainties in the aerosol-cloud forcing of climate.
My current and future research plans focus on the development and application of novel computational strategies that robustly link observations with models for improved understanding and representation of atmospheric processes relevant for aerosol-cloud interactions in GCMs. In these efforts we collaborate strongly with the UK Met Office Hadley Centre, a world-renowned climate modelling centre.
The Cloud-Aerosol-Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) is a NERC funded large grant (NE/L013584/1) investigating the impacts that smoke aerosols from biomass burning have on climate. Led by Prof Jim Haywood of the University of Exeter, CLARIFY-2017 was a major consortium programme consisting of the universities of Exeter, Leeds, Manchester, Oxford, and Reading, with project partners from the UK Met Office. The campaign was coordinated with the major USA NASA-led ORACLES, and DoE-led LASIC programmes and the French led AEROCLO-sA project. CLARIFY-2017 involved locating the UK’s FAAM aircraft on Ascension Island (Figure 1) in the tropical south Atlantic and making detailed observations of the plume of smoke that is transported from fires from deforestation and agricultural waste clearance on mainland Africa. The aims of CLARIFY-2017 were four-fold; 1) to improve the representation and reduce uncertainty in model estimates of the direct, semi-direct and indirect radiative effect of absorbing biomass burning aerosols; 2) improve our knowledge and representation of the processes determining stratocumulus cloud microphysical and radiative properties and their transition to cumulus regimes; 3) challenge, validate and improve satellite retrievals of cloud and aerosol properties and their radiative impacts; 4) improve the impacts of aerosols in weather and climate numerical models.
Prof Jim Haywood provided expertise in all aspects of the planning and execution of the measurement campaign (e.g. Zuidema et al., 2016; 2018; Redemann et al., 2020; Haywood et al, 2020) and his researchers were involved in all aspects from design, manufacture, and analysis of the performance of state-of the-art aerosol measurement equipment (Davies et al., 2019, 2020; Cotterell et al., 2019; 2020) through modelling aerosol physical and optical properties (Wu et al., 2020; Taylor et al, 2020, Abel et al., 2020), and development of novel new satellite detection algorithms for detecting aerosols above cloud (de Graaf et al., 2019; Peers et al, 2019, Peers et al, 2020; Deconu et al., 2020). This project provided vital information on aerosol-radiation interactions and aerosol-cloud interactions that are so important for our understanding of climate. A Special Issue in Atmospheric Chemistry and Physics is currently being compiled with several publications from researchers at the University of Exeter.
Figure 1: 2003-2011 mean Aug-Oct AODs (coloured contours) retrieved from the MODIS satellite, MODIS cloud fraction (black and white colour scale), and Global Fire Emissions Dataset (GFED) aresol emission eseimates (colours over land). The yellow star shows the position of Ascension Island with a dashed circule representing the approximate operating range of the FAAM aircraft. The position of São Tomé where ORACLES operations were performed, and Walvis Bay where AEROCLO-sA operations were performed are marked by red and green stars respectively.
Prof Jim Haywood and his team have been at the heart of the UK’s research into modelling the impacts of so-called solar radiation management climate geoengineering schemes that propose combatting the increase in global mean temperatures by reflecting a proportion of sunlight back to space. He has been involved with the Geoengineering Model Intercomparison Project (GEOMIP) under which consistent emission scenarios are applied across models. Importantly, he and his group try to provide a balanced assessment of both the pros and cons of solar radiation management aspects. Jim has recently been appointed to the United Nations Environmental Panel of the Montreal Protocol Assessment on Ozone and will lead the chapter on stratospheric aerosol injection which is due for publication in 2022.
A schematic diagram of a solar radiation management (SRM) “peak shaving” strategy to reduce the most harmful impacts of global warming is shown in the following figure, where conventional mitigation and aggressive net zero carbon measures fail to reduce global mean temperature 1.5K above pre-inductrial levels.
He has given many recent talks on geoengineering including briefings to BEIS and the Bank of England, and seminars at The University of Cambridge, the National Centre for Atmospheric Research, Boulder, Colorado, USA and the Institute of Mechanical Engineers. He appeared as a panellist on BBC2’s Politics Live in November 2019.
The Aerosol-cloud-climate interactions derived from Degassing VolcANiC Eruptions (ADVANCE) is a NERC funded standard grant (NE/T006897/1) led by Prof Jim Haywood of the University of Exeter with collaborators from the Universities of Leeds and Cambridge.
Anthropogenic emissions that affect climate are not just confined to greenhouse gases. Sulfur dioxide (SO2) and other pollutants form atmospheric aerosols that scatter and absorb sunlight, and influence the properties of clouds, modulating the Earth-atmosphere energy balance. Anthropogenic emissions of aerosols exert a significant, but poorly quantified, cooling of climate that acts to counterbalance the global warming from anthropogenic emissions of greenhouse gases. Uncertainties in aerosol-climate impacts are dominated by uncertainties in aerosol-cloud interactions (ACI) which operates through aerosols acting as cloud-condensation nuclei (CCN) which increases the cloud droplet number concentration (CDNC) while reducing the size of cloud droplets and subsequently impact rain formation which may change the overall physical properties of clouds. This consequently impacts the uncertainty in climate sensitivity (the climate response per unit climate forcing) because climate models with a strong/weak aerosol cooling effect and a high/low climate sensitivity respectively are both able to represent the historic record of global mean temperatures.
ADVANCE seeks to use the huge fissure eruption at Holuhraun in 2014-2015 in Iceland, which was the largest effusive degassing event from Iceland since the eruption of Laki in 1783-17849. The eruption at Holuhraun emitted sulphur dioxide at a peak rate of up to 1/3 of global emissions, creating a massive plume of sulphur dioxide and sulphate aerosols across the entire North Atlantic. In effect, Iceland became a significant global/regional pollution source in an otherwise unpolluted environment where clouds should be most susceptible to aerosol emissions. Thus, the eruption at Holuhraun created an excellent analogy for studying the impacts of anthropogenic emissions of sulphur dioxide and the resulting sulphate aerosol on ACI.
Our research will comprehensively evaluate impacts of the Holuhraun aerosol plume on clouds, precipitation, the energy balance, and key weather and climate variables. Observational analysis will be extended beyond that of our pilot study to include high quality surface sites. Two different climate models will be used; HadGEM3, which is the most up to date version of the Met Office Unified model and ECHAM6-HAM, developed by MPI Hamburg. These models are chosen because they produce radically different responses in terms of ACI; ECHAM6-HAM produces far stronger ACI impacts overall than HadGEM3. Additionally, the UK Met Office Unified Model framework means that the underlying physics is essentially identical in low-resolution climate models and high-resolution numerical weather predication models, a feature that is unique in weather/climate research. In the high resolution numerical weather prediction version, parameterisations of convection can be turned off and sub-gridscale processes can be explicitly represented. Thus the impacts of choices of parameterisation schemes and discrete values of variables within the schemes may be evaluated.
The research promises new insights into ACI and climate sensitivity promising us great strides improving weather and climate models and simulations of the future.
Find out further information about the ArctiCONNECT project within James' staff profile under 'projects'.
Professor Mat Collins
My research is on physical aspects of climate variability and change, principally using the output from complex climate models. I have specific interests in quantifying uncertainty in climate projections, the dynamics of the El Nino Southern Oscillation climate phenomenon, the dynamics of monsoons and general aspects of decadal and longer time scale variability and change associated with, for example, the hydrological cycle.
I am currently leading a NERC-funded highlight topic, ‘Emergence of Climate Hazards’ and previously led a NERC large-grant on ‘Robust Spatial Projections of Real-World Climate Change’. I am a Joint Met Office Chair in Climate Change and am the Field Chief Editor of Frontiers in Climate [could add link from signature below].
We study interactions between atmospheric chemistry and the climate system. Our goal is to understand the impacts of the short-lived climate forcers on air quality and climate in past, present and future worlds. The main tools are Earth system modelling and multiple observational datasets, especially from satellites and flux towers. Current research areas include: plant volatile organic carbon emissions, wildfire emissions, and human land use change and land-based climate mitigation impacts on air quality and climate. Our policy-relevant research projects provide results that support effective environmental management and decision-making.
Pierre is interested in the role of biogeochemical cycles in the climate system over time scales ranging from glacial interglacial to future IPCC-like projections. For future climate projections, he identified to positive feedback between climate change and carbon cycle and developed a mathematical framework for climate-carbon feedbacks analysis. He is also involved in development and evaluation of land surface models (JULES) and inclusion in Earth System Models.
Pierre is currently coordinating the EU H2020 4C project 'Climate carbon Cycle Interavtions in the Current Century'.