Nick Watkins
Nick’s work with the Institute is focused on developing stochastic models for climate fluctuations with applicability to economic impacts. He works in collaboration with David Stainforth and Raphael Calel, and with Sandra Chapman of Warwick University. This team was awarded first prize in the Climate Change category of the 2021 Lloyd’s Science of Risk prize.
Nick’s interests are multidisciplinary, and his other current research includes topics at the intersections of time series analysis, statistical physics, stochastic processes and space physics. He is an Associate Editor of the journal Chaos.
Background
Nick trained as a theoretical physicist at UCL and Sussex, followed by postdoctoral research in space plasma physics. His interests were further broadened into complex systems and environmental science during 16 years with the NERC British Antarctic Survey, and by his long term visiting roles at the Max Planck Institute for the Physics of Complex Systems, The Open University, the University of Warwick, and LSE’s Centre for the Analysis of Time Series.
Research
Research - 2024
This invited chapter was published as part of the Foundational Papers in Complexity Science publication series, Read more
The authors of this article propose an extension of Hasselmann’s stochastic energy balance model. Read more
Global ionospheric total electron content (TEC) maps exhibit TEC intensifications and depletions of various sizes and shapes. Characterizing key features... Read more
Research - 2023
The authors of this paper Read more
Research - 2022
The authors of this paper analyze two geomagnetic index time series, AE and SMR, which track activity in the auroral region and around the Earth's equator, respectively. Read more
Research - 2021
We construct a new solar cycle phase clock which maps each of the last 18 solar cycles onto a single normalized epoch for the approximately 22 yr Hale (magnetic polarity) cycle, using the Hilbert transform of daily sunspot numbers (SSNs) since 1818. Read more
Our complementary approach exploits the correspondence between Hasselmann’s EBM and the original mean-reverting stochastic model in physics, Langevin’s equation of 1908. We propose mapping a model well known in statistical mechanics, the Mori-Kubo Generalised Langevin Equation (GLE) to generalise the Hasselmann EBM. Read more
Multipoint in situ observations of the solar wind are used to identify the magnetic topology and current density of turbulent structures. We find that at least 35% of all structures are both actively evolving and carrying the strongest currents, actively dissipating, and heating the plasma. Read more
Research - 2020
Climate science employs a hierarchy of models, trading the tractability of simplified energy balance models (EBMs) against the detail of... Read more
A number of influential assessments of the economic cost of climate change rely on just a small number of coupled... Read more
Books
Books - 2024
This invited chapter was published as part of the Foundational Papers in Complexity Science publication series, Read more
Books - 2021
Our complementary approach exploits the correspondence between Hasselmann’s EBM and the original mean-reverting stochastic model in physics, Langevin’s equation of 1908. We propose mapping a model well known in statistical mechanics, the Mori-Kubo Generalised Langevin Equation (GLE) to generalise the Hasselmann EBM. Read more