Prof Jim Haywood
Current Projects (Dec 2021):
ADVANCE: 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 Dr Dan Partridge as a co-I collaborators from the Universities of Leeds and Cambridge. The University of Exeter affiliated post-doctoral research associate is Ying Chen.
SASSO is a NERC funded standard grant (NE/S00212X/1) led by Prof James Allan of the University of Manchester. Prof Jim Haywood is the University of Exeter PI with Prof Claire Belcher as a co-I. The University of Exeter affiliated post-graduate research associated is Lilly Damany-Pearce.
Atmospheric soot is a pollutant that contains black carbon (BC) and potentially also brown carbon (BrC) and is produced from combustion sources such as diesel engines, wildfires, agricultural waste burning and the burning of solid fuels such as wood and coal. Because BC and BrC absorb sunlight, they can have a warming effect on climate, in particular on local scales; there is evidence to suggest that the increase in absorbing aerosols associated with pollution has been responsible for the weakening of the South Asian Monsoon. However, while BC and BrC are very important for climate, they are currently very poorly represented in the models used to study and predict these effects. Comparison exercises between the various models in use around the world tend to highlight strong disagreements and comparisons against observations of absorbing aerosols are consistently very poor. This indicates a strong need to improve the treatment of soot and its processes within models, however this has so far been limited by deficiencies in the instrumentation and laboratory techniques available. SASSO will capitalise on the timely development of new methodologies, facilities and instruments at the Universities of Manchester and Exeter to use a novel and unique combination of tools to study soot on a level of detail previously not possible. This data will be used to develop and test new models of soot optical properties and this will be implemented in the UK's main climate model (hadGEM3), to test what effects this new, improved understanding has on predictions of climate responses to changes in soot emissions. One aspect thyat has been examined in details is the unprecedented fires in SE Australia where the smoke plume was detected in the stratosphere.
IMPRESS: IMpacts of PRecipitation from Extreme StormS - Malaysia
IMPRESS is a NERC funded directed international grant (NE/S002707/1) led by Jim Haywood with co-Is Dr Matt Hawcroft and Dr Jenn Catto and University of Reading co-I Dr Kevin Hodges. Thepost-doctoral research associate is Dr Ju Liang. The work is closely coordinated with the hydrological catchment work of Dr Mou Leong Tan of Universite Sains Malaysia.
In a warmer climate, the amount of precipitation is expected to increase, as warmer air can hold more water. At the regional level - where impacts are felt - patterns of change are less well understood due to uncertainty in the circulation response to warming. In addition to these changes in mean precipitation, increases in precipitation extremes may be considerable, and are expected to increase at around 7% per degree Celsius of warming. Extreme events frequently cause the greatest damage, making understanding the nature of changes in both the frequency and magnitude of such extremes a critical issue given their impact on society. In Peninsular Malaysia, the majority of the annual total precipitation is produced by a relatively small number of intense events. These extreme precipitation events have been increasing in recent decades. They can lead to considerable damage through flooding, which can be enhanced by changes in land use. Annual, average annual flood losses are currently around RM 915 million in Malaysia. In a warmer climate, a shift to a more intense wet season (which is expected), with increased frequency of the most extreme events, may have significant implications for the hydrology of Peninsular Malaysia and associated impacts on society. In this project, we will investigate the dynamical features (e.g. tropical storms) that lead to extreme precipitation in Malaysia. We will study both their present-day behaviour and likely changes in the future. In doing so, we will achieve a dynamically constrained understanding of future extreme precipitation events. This represents a considerable advance on our current understanding of future changes in extreme precipitation in Malaysia. We will then use this information to run a hydrological model to estimate future changes in streamflow, flood magnitudes and flood return periods. This model will include estimates of land use change which will also be developed as part of the project.
The realization by the scientific community of the difficulty of limiting global mean temperatures to within these 1.5 or 2.0C targets has led to increased calls for climate intervention via so called "solar radiation management (SRM)" techniques which aim to increase planetary albedo and induce a cooling that acts to partially offset global warming. Haywood has authored many cautionary studies including detrimental teleconnection impacts on Amazonian rainfall, termination effect, impacts on Sahelian drought and hurricane frequency of hemispherically asymmetric SRM, and stressed that any practical SRM deployment should only be used to temporally ameliorate the worst impacts of climate change whilst transitioning to a net carbon zero economy. Recent assessments of SRM support a cautionary and objective analysis using models that can represent the detailed mechanisms of SRM. For SAI, they must represent the dynamics and chemistry of the stratosphere such as the Brewer-Dobson circulation, the Quasi-biennial oscillation (QBO), homogeneous and heterogeneous chemistry relevant to the ozone layer, and the detailed sulphate microphysical evolution such as gas phase oxidation, nucleation, condensation, coagulation, evaporation and gravitational settling. Only a handful of GCMs within the most advanced GeoMIP G6sulph experiment adequately; the two best models are arguably the UK Met Office Hadley Centre UKESM1 and the USA's National Center for Atmospheric Research (NCAR) CESM2-WACCM. This proposal uses the UK's climate model (UKESM1) to EXTEND the large-ensemble approach pioneered by NCAR with CESM2-WACCM. Direct collaboration between the University of Exeter and NCAR promises a dual-model assessment of the various pros, cons, perils and pitfalls of SAI climate intervention utilising two of the most advanced GCMs currently available. The collaboration will not only position the UK scientific community at the forefront of SAI climate intervention, but provide a balanced assessment of the potential of SAI as a climate intervention strategy to policy-makers worldwide.
DRIVE: Developing Resilience to Icelandic Volcanic Eruptions
The overarching aim of the program is “to increase economic and social resilience to high-impact events …. by improving forecasting and the uptake of scientific advice”. Program objectives include “to build economically and socially viable resilience into the assessment of, planning for, and management of natural hazards, with a specific focus on high consequence, regional scale events in volcanic and earthquake-prone areas”. The economic cost of the Eyjafjallajökull eruption in Iceland in 2010 due to the closure of UK and European airspace has been estimated at around £200m/day for the airline industry with total subsequent impacts on the global economy of US$5bn. This volcanic event is economically the most high-impact, high-consequence regional scale volcanic event in recent history, and resilience to such events needs to be significantly increased. Assessing the economic risk of reoccurrence of such an event is one goal of Developing the Resilience to Icelandic Volcanic Eruptions within the UK (DRIVE-UK). Economic resilience can be built by minimising the impact of such eruptions on UK and European airspace closure, which can be achieved through developing a more robust network of near-real-time observations