James Murphy

Areas of expertise

Joining the Met Office in 1981, James has spent his career pioneering the development of core capabilities that underpin climate predictions from a month to a century ahead.

These include:

• Developing ensemble methods in dynamical monthly forecasting, including the first real-time predictions based on a global climate model.
• The first Met Office Hadley Centre (MOHC) coupled ocean-atmosphere simulation of transient climate change.
• Establishing nested high-resolution climate modelling as a key tool in the provision of national climate scenarios at regional scales.  
• Developing methods to quantify uncertainties in climate projections, culminating in provision of probabilistic projections of 21^st century climate in the UKCP09 and UKCP18 national scenarios.
• Steering development of the world’s first system for initialised decadal predictions using a global coupled model.

Current activities

The UKCP18 land projections provide Probabilistic, Global, Regional and Local projections that are rich in content and support a wide range of user applications.

However, the products are based on different climate modelling datasets, so do not provide fully consistent information, especially with respect to uncertainties.

James is contributing to a future design that ties together the use of updated modelling components across these products, so that future provision of UKCI can potentially include a set of common components that supports a simpler user experience and a more consistent analysis of UK impacts.

His team is working on updating the probabilistic projections, and on improved methods for characterising changing risks of extreme events.

Where possible, we will seek to combine these capabilities to extend their functionality, in order (for example) to provide probabilistic projections of rare events.

UKCI will also add new types of capability, including information from initialised predictions.

James’s team will assess potential to create harmonised information by merging initialised predictions with (uninitialised) long-term projections.

This work will aim to create a combined dataset that improves on the separate products by accounting for their relative performance in predicting both best-estimate outcomes and uncertainties.

External recognition

• L F Richardson Prize of the Royal Meteorological Society (1989), for work on ensemble monthly prediction.
• L G Groves Memorial Prize for Meteorology (1993), for papers describing the MOHC  coupled ocean-atmosphere model projections of global climate change.
• A Lead Author in the fourth IPCC Working Group I assessment of the science of climate change.
• Awarded the Symons Gold Medal by the Royal Meteorological Society (2024), for contributions to the science of climate projections.