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

CLIMATE DYNAMICS 53 (2019) 4291-4309

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

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>

Compatible Finite Element Methods for Geophysical Flows Automation and Implementation Using Firedrake

Springer, 2019

TH Gibson, ATT McRae, CJ Cotter, L Mitchell, DA Ham

This book introduces recently developed mixed finite element methods for large-scale geophysical flows that preserve essential numerical properties for accurate simulations.

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

CLIMATE DYNAMICS 53 (2019) 2843-2859

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

Experimental Non-Violation of the Bell Inequality

ENTROPY 20 (2019) ARTN 356

TN Palmer

Assessing External and Internal Sources of Atlantic Multidecadal Variability Using Models, Proxy Data, and Early Instrumental Indices

JOURNAL OF CLIMATE 32 (2019) 7727-7745

CH O'Reilly, L Zanna, T Woollings

Climate Services and Communication for Development: The Role of Early Career Researchers in Advancing the Debate


FK Donkor, C Howarth, E Ebhuoma, M Daly, C Vaughan, L Pretorius, J Mambo, D MacLeod, A Kythreotis, L Jones, S Grainger, N Golding, JA Anderson

Seasonal forecasts of the East African long rains: insight from atmospheric relaxation experiments

Climate Dynamics (2019)

D MacLeod

© 2019, The Author(s). The impacts of recent droughts and floods over East Africa may have been avoided with accurate and timely early warnings. However skillful predictions for the long rains season from dynamical seasonal forecasts have long proved elusive and understanding of the drivers of interannual variability of this season is incomplete. Although recent work has highlighted several candidates for key drivers of variability during March–April, the representation of East African precipitation and links to remote processes in seasonal climate models is relatively unknown. This is investigated here through use of the atmospheric relaxation technique in coupled seasonal climate hindcast experiments, which also provide an estimate of the upper bound of seasonal predictability from remote sources. Results highlight the key role of the lower troposphere in the northwest Indian Ocean in controlling interannual variability, particularly in March and April. This is in support of recent work suggesting ascent-induced boundary-layer heating this region as a key driver of interannual variability. Results from single-variable relaxation experiments also reveal the importance of correct simulation of humidity for the proper representation of this link. Processes in the southwest Indian Ocean provide a control on May precipitation over southwest Kenya and northern Tanzania, highlighting the role of Somali jet variability in long rains cessation. Relaxation in more remote regions over the Pacific is unable to improve the representation of interannual variability over East Africa in general, although variability in the east Pacific appears to provide a weak control on March rainfall, consistent with previous hypotheses linking decaying ENSO events to early season rainfall. Finally, modelled precipitation anomalies are found to be insufficiently constrained to the coast of Africa. Relaxation (particularly in the northwest Indian Ocean) can improve these spatial biases, however the variance explained by these modes is systematically underestimated in the model and appears insensitive to remote processes. Inadequate representation of local processes over East Africa is proposed as the cause of this underestimation and several candidates are outlined.

Stochastic weather and climate models

Nature Reviews Physics Springer Science and Business Media LLC 1 (2019) 463-471

TN Palmer

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


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

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.

Seasonal Predictability of the Winter North Atlantic Oscillation From a Jet Stream Perspective


T Parker, T Woollings, A Weisheimer, C O'Reilly, L Baker, L Shaffrey

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


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

The scientific challenge of understanding and estimating climate change.

Proceedings of the National Academy of Sciences of the United States of America 116 (2019) 24390-24395

T Palmer, B Stevens

Given the slow unfolding of what may become catastrophic changes to Earth's climate, many are understandably distraught by failures of public policy to rise to the magnitude of the challenge. Few in the science community would think to question the scientific response to the unfolding changes. However, is the science community continuing to do its part to the best of its ability? In the domains where we can have the greatest influence, is the scientific community articulating a vision commensurate with the challenges posed by climate change? We think not.

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