Publications


Forced summer stationary waves: the opposing effects of direct radiative forcing and sea surface warming

Climate Dynamics (2019)

HS Baker, T Woollings, C Mbengue, MR Allen, CH O’Reilly, H Shiogama, S Sparrow

© 2019, The Author(s). We investigate the opposing effects of direct radiative forcing and sea surface warming on the atmospheric circulation using a hierarchy of models. In large ensembles of three general circulation models, direct CO 2 forcing produces a wavenumber 5 stationary wave over the Northern Hemisphere in summer. Sea surface warming produces a similar wave, but with the opposite sign. The waves are also present in the Coupled Model Intercomparison Project phase 5 ensemble with opposite signs due to direct CO 2 and sea surface warming. Analyses of tropical precipitation changes and equivalent potential temperature changes and the results from a simple barotropic model show that the wave is forced from the tropics. Key forcing locations are the Western Atlantic, Eastern Atlantic and in the Indian Ocean just off the east coast of Africa. The stationary wave has a significant impact on regional temperature anomalies in the Northern Hemisphere summer, explaining some of the direct effect that CO 2 concentration has on temperature extremes. Ultimately, the climate sensitivity and future changes in the land–sea temperature contrast will dictate the balance between the opposing effects on regional changes in mean and extreme temperature and precipitation under climate change.


The El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern Africa

Hydrology and Earth System Sciences Copernicus GmbH 23 (2019) 1751-1762

SR Kolusu, M Shamsudduha, MC Todd, RG Taylor, D Seddon, JJ Kashaigili, GY Ebrahim, MO Cuthbert, JPR Sorensen, KG Villholth, AM MacDonald, DA MacLeod

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The impact of climate variability on groundwater storage has received limited attention despite widespread dependence on groundwater as a resource for drinking water, agriculture and industry. Here, we assess the climate anomalies that occurred over Southern Africa (SA) and East Africa, south of the Equator (EASE), during the major El Niño event of 2015–2016, and their associated impacts on groundwater storage, across scales, through analysis of in situ groundwater piezometry and Gravity Recovery and Climate Experiment (GRACE) satellite data. At the continental scale, the El Niño of 2015–2016 was associated with a pronounced dipole of opposing rainfall anomalies over EASE and Southern Africa, north–south of &lt;span class="inline-formula"&gt;∼12&lt;/span&gt;&lt;span class="inline-formula"&gt;&lt;sup&gt;∘&lt;/sup&gt;&lt;/span&gt;&amp;amp;thinsp;S, a characteristic pattern of the El Niño–Southern Oscillation (ENSO). Over Southern Africa the most intense drought event in the historical record occurred, based on an analysis of the cross-scale areal intensity of surface water balance anomalies (as represented by the standardised precipitation evapotranspiration index – SPEI), with an estimated return period of at least 200 years and a best estimate of 260 years. Climate risks are changing, and we estimate that anthropogenic warming only (ignoring changes to other climate variables, e.g. precipitation) has approximately doubled the risk of such an extreme SPEI drought event. These surface water balance deficits suppressed groundwater recharge, leading to a substantial groundwater storage decline indicated by both GRACE satellite and piezometric data in the Limpopo basin. Conversely, over EASE during the 2015–2016 El Niño event, anomalously wet conditions were observed with an estimated return period of &lt;span class="inline-formula"&gt;∼10&lt;/span&gt; years, likely moderated by the absence of a strongly positive Indian Ocean zonal mode phase. The strong but not extreme rainy season increased groundwater storage, as shown by satellite GRACE data and rising groundwater levels observed at a site in central Tanzania. We note substantial uncertainties in separating groundwater from total water storage in GRACE data and show that consistency between GRACE and piezometric estimates of groundwater storage is apparent when spatial averaging scales are comparable. These results have implications for sustainable and climate-resilient groundwater resource management, including the potential for adaptive strategies, such as managed aquifer recharge during episodic recharge events.&lt;/p&gt; </jats:p>


The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model

Climate Dynamics (2019)

C Yang, HM Christensen, S Corti, J von Hardenberg, P Davini

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. The impact of stochastic physics on El Niño Southern Oscillation (ENSO) is investigated in the EC-Earth coupled climate model. By comparing an ensemble of three members of control historical simulations with three ensemble members that include stochastics physics in the atmosphere, we find that in EC-Earth the implementation of stochastic physics improves the excessively weak representation of ENSO. Specifically, the amplitude of both El Niño and, to a lesser extent, La Niña increases. Stochastic physics also ameliorates the temporal variability of ENSO at interannual time scales, demonstrated by the emergence of peaks in the power spectrum with periods of 5–7 years and 3–4 years. Based on the analogy with the behaviour of an idealized delayed oscillator model (DO) with stochastic noise, we find that when the atmosphere–ocean coupling is small (large) the amplitude of ENSO increases (decreases) following an amplification of the noise amplitude. The underestimated ENSO variability in the EC-Earth control runs and the associated amplification due to stochastic physics could be therefore consistent with an excessively weak atmosphere–ocean coupling. The activation of stochastic physics in the atmosphere increases westerly wind burst (WWB) occurrences (i.e. amplification of noise amplitude) that could trigger more and stronger El Niño events (i.e. increase of ENSO oscillation) in the coupled EC-Earth model. Further analysis of the mean state bias of EC-Earth suggests that a cold sea surface temperature (SST) and dry precipitation bias in the central tropical Pacific together with a warm SST and wet precipitation bias in the western tropical Pacific are responsible for the coupled feedback bias (weak coupling) in the tropical Pacific that is related to the weak ENSO simulation. The same analysis of the ENSO behaviour is carried out in a future scenario experiment (RCP8.5 forcing), highlighting that in a coupled model with an extreme warm SST, characterized by a strong coupling, the effect of stochastic physics on the ENSO representation is opposite. This corroborates the hypothesis that the mean state bias of the tropical Pacific region is the main reason for the ENSO representation deficiency in EC-Earth.


Experimental Non-Violation of the Bell Inequality

ENTROPY 20 (2019) ARTN 356

TN Palmer


Factors Influencing the Seasonal Predictability of Northern Hemisphere Severe Winter Storms

Geophysical Research Letters (2019)

F Hansen, T Kruschke, RJ Greatbatch, A Weisheimer

©2018. The Authors. We investigate the role of the tropics, the stratosphere, and atmosphere-ocean coupling for seasonal forecasts of strong, potentially damaging, Northern Hemisphere extratropical winter wind storm frequencies. This is done by means of relaxation experiments with the European Centre for Medium-Range Weather Forecasts model, which allow us to prescribe perfect forecasts for specific parts of the coupled atmosphere-ocean system. We find that perfect predictions of the Northern Hemisphere stratosphere significantly enhance winter storm predictive skill between eastern Greenland and Northern Europe. Correct seasonal predictions of the occurrence of stratospheric sudden warmings play a decisive role. The importance of correctly predicting the tropics and of two-way atmosphere-ocean coupling, both for forecasting stratospheric sudden warming risk and, correspondingly, severe winter storm frequency, is noted.


The importance of stratospheric initial conditions for winter North Atlantic Oscillation predictability and implications for the signal-to-noise paradox

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 145 (2019) 131-146

CH O'Reilly, A Weisheimer, T Woollings, LJ Gray, D MacLeod


Correction to: The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model (Climate Dynamics, (2019), 10.1007/s00382-019-04660-0)

Climate Dynamics (2019)

C Yang, HM Christensen, S Corti, J von Hardenberg, P Davini

© 2019, The Author(s). The article The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model, written by Chunxue Yang, Hannah M. Christensen, Susanna Corti, Jost von Hardenberg and Paolo Davini, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 07 February 2019 without open access.


How confident are predictability estimates of the winter North Atlantic Oscillation?

Quarterly Journal of the Royal Meteorological Society Wiley (2018) qj.3446

A Weisheimer, D Decremer, D MacLeod, C O’Reilly, TN Stockdale, S Johnson, TN Palmer


From reliable weather forecasts to skilful climate response: A dynamical systems approach

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 145 (2019) 1052-1069

HM Christensen, J Berner


Stochastic Parameterization of Subgrid-Scale Velocity Enhancement of Sea Surface Fluxes

MONTHLY WEATHER REVIEW 147 (2019) 1447-1469

J Bessac, AH Monahan, HM Christensen, N Weitzel


Scale-Selective Precision for Weather and Climate Forecasting

MONTHLY WEATHER REVIEW 147 (2019) 645-655

M Chantry, T Thornes, T Palmer, P Duben


The Sensitivity of Euro-Atlantic Regimes to Model Horizontal Resolution

Geophysical Research Letters American Geophysical Union (2019)

K Strommen, I Mavilia, S Corti, M Matsueda, P Davini, JV Hardenberg, P-L Vidale, R Mizuta

There is growing evidence that the atmospheric dynamics of the Euro-Atlantic sector during winter is driven in part by the presence of quasi-persistent regimes. However, general circulation models typically struggle to simulate these, with e.g. an overly weakly persistent blocking regime. Previous studies have showed that increased horizontal resolution can improve the regime structure of a model, but have so far only considered a single model with only one ensemble member at each resolution, leaving open the possibility that this may be either coincidental or model-dependent. We show that the improvement in regime structure due to increased resolution is robust across multiple models with multiple ensemble members. However, while the high resolution models have notably more tightly clustered data, other aspects of the regimes may not necessarily improve, and are also subject to a large amount of sampling variability that typically requires at least three ensemble members to surmount.


Accelerating high-resolution weather models with deep-learning hardware

Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2019 (2019)

S Hatfield, M Chantry, P Düben, T Palmer

© 2019 Association for Computing Machinery. The next generation of weather and climate models will have an unprecedented level of resolution and model complexity, and running these models efficiently will require taking advantage of future supercomputers and heterogeneous hardware. In this paper, we investigate the use of mixed-precision hardware that supports floating-point operations at double-, single- and half-precision. In particular, we investigate the potential use of the NVIDIA Tensor Core, a mixed-precision matrix-matrix multiplier mainly developed for use in deep learning, to accelerate the calculation of the Legendre transforms in the Integrated Forecasting System (IFS), one of the leading global weather forecast models. In the IFS, the Legendre transform is one of the most expensive model components and dominates the computational cost for simulations at a very high resolution. We investigate the impact of mixed-precision arithmetic in IFS simulations of operational complexity through software emulation. Through a targeted but minimal use of double-precision arithmetic we are able to use either half-precision arithmetic or mixed half/single-precision arithmetic for almost all of the calculations in the Legendre transform without affecting forecast skill.


Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2

GEOSCIENTIFIC MODEL DEVELOPMENT 12 (2019) 3099-3118

K Strommen, HM Christensen, D MacLeod, S Juricke, TN Palmer


Signal and noise in regime systems: A hypothesis on the predictability of the North Atlantic Oscillation

Quarterly Journal of the Royal Meteorological Society (2019)

K Strommen, TN Palmer

© 2018 Royal Meteorological Society Studies conducted by the UK Met Office reported significant skill in predicting the winter North Atlantic Oscillation (NAO) index with their seasonal prediction system. At the same time, a very low signal-to-noise ratio was observed, as measured using the “ratio of predictable components” (RPC) metric. We analyse both the skill and signal-to-noise ratio using a new statistical toy model, which assumes NAO predictability is driven by regime dynamics. It is shown that if the system is approximately bimodal in nature, with the model consistently underestimating the level of regime persistence each season, then both the high skill and high RPC value of the Met Office hindcasts can easily be reproduced. Underestimation of regime persistence could be attributable to any number of sources of model error, including imperfect regime structure or errors in the propagation of teleconnections. In particular, a high RPC value for a seasonal mean prediction may be expected even if the model's internal level of noise is realistic.


The northern hemisphere circumglobal teleconnection in a seasonal forecast model and its relationship to European summer forecast skill

CLIMATE DYNAMICS 52 (2019) 3759-3771

JD Beverley, SJ Woolnough, LH Baker, SJ Johnson, A Weisheimer


Seasonal forecast skill for extratropical cyclones and windstorms

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 145 (2019) 92-104

DJ Befort, S Wild, JR Knight, JF Lockwood, HE Thornton, L Hermanson, PE Bett, A Weisheimer, GC Leckebusch


Forcing Single-Column Models Using High-Resolution Model Simulations.

Journal of advances in modeling earth systems 10 (2018) 1833-1857

HM Christensen, A Dawson, CE Holloway

To use single-column models (SCMs) as a research tool for parameterization development and process studies, the SCM must be supplied with realistic initial profiles, forcing fields, and boundary conditions. We propose a new technique for deriving these required profiles, motivated by the increase in number and scale of high-resolution convection-permitting simulations. We suggest that these high-resolution simulations be coarse grained to the required resolution of an SCM, and thereby be used as a proxy for the true atmosphere. This paper describes the implementation of such a technique. We test the proposed methodology using high-resolution data from the UK Met Office's Unified Model, with a resolution of 4 km, covering a large tropical domain. These data are coarse grained and used to drive the European Centre for Medium-Range Weather Forecast's Integrated Forecasting System (IFS) SCM. The proposed method is evaluated by deriving IFS SCM forcing profiles from a consistent T639 IFS simulation. The SCM simulations track the global model, indicating a consistency between the estimated forcing fields and the true dynamical forcing in the global model. We demonstrate the benefits of selecting SCM forcing profiles from across a large domain, namely, robust statistics, and the ability to test the SCM over a range of boundary conditions. We also compare driving the SCM with the coarse-grained data set to driving it using the European Centre for Medium-Range Weather Forecast operational analysis. We conclude by highlighting the importance of understanding biases in the high-resolution data set and suggest that our approach be used in combination with observationally derived forcing data sets.


A Simple Pedagogical Model linking Initial-Value Reliability with Trustworthiness in the Forced Climate Response.

Bulletin of the American Meteorological Society (2017)

TN Palmer, A Weisheimer


Impact of Gulf Stream SST biases on the global atmospheric circulation

CLIMATE DYNAMICS 51 (2018) 3369-3387

RW Lee, TJ Woollings, BJ Hoskins, KD Williams, CH O'Reilly, G Masato

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