Publications


Predicting El Niño in 2014 and 2015.

Scientific reports 8 (2018) 10733-

S Ineson, MA Balmaseda, MK Davey, D Decremer, NJ Dunstone, M Gordon, H-L Ren, AA Scaife, A Weisheimer

Early in 2014 several forecast systems were suggesting a strong 1997/98-like El Niño event for the following northern hemisphere winter 2014/15. However the eventual outcome was a modest warming. In contrast, winter 2015/16 saw one of the strongest El Niño events on record. Here we assess the ability of two operational seasonal prediction systems to forecast these events, using the forecast ensembles to try to understand the reasons underlying the very different development and outcomes for these two years. We test three hypotheses. First we find that the continuation of neutral ENSO conditions in 2014 is associated with the maintenance of the observed cold southeast Pacific sea surface temperature anomaly; secondly that, in our forecasts at least, warm west equatorial Pacific sea surface temperature anomalies do not appear to hinder El Niño development; and finally that stronger westerly wind burst activity in 2015 compared to 2014 is a key difference between the two years. Interestingly, in these years at least, this interannual variability in wind burst activity is predictable. ECMWF System 4 tends to produce more westerly wind bursts than Met Office GloSea5 and this likely contributes to the larger SST anomalies predicted in this model in both years.


Choosing the Optimal Numerical Precision for Data Assimilation in the Presence of Model Error

Journal of Advances in Modeling Earth Systems (2018)

S Hatfield, P Düben, M Chantry, K Kondo, T Miyoshi, T Palmer

©2018. The Authors. The use of reduced numerical precision within an atmospheric data assimilation system is investigated. An atmospheric model with a spectral dynamical core is used to generate synthetic observations, which are then assimilated back into the same model using an ensemble Kalman filter. The effect on the analysis error of reducing precision from 64 bits to only 22 bits is measured and found to depend strongly on the degree of model uncertainty within the system. When the model used to generate the observations is identical to the model used to assimilate observations, the reduced-precision results suffer substantially. However, when model error is introduced by changing the diffusion scheme in the assimilation model or by using a higher-resolution model to generate observations, the difference in analysis quality between the two levels of precision is almost eliminated. Lower-precision arithmetic has a lower computational cost, so lowering precision could free up computational resources in operational data assimilation and allow an increase in ensemble size or grid resolution.


The benefits of global high-resolution for climate simulation: process-understanding and the enabling of stakeholder decisions at the regional scale.

Bulletin of the American Meteorological Society (2018)

MJ Roberts, PL Vidale, C Senior, HT Hewitt, C Bates, S Berthou, P Chang, HM Christensen, S Danilov, M-E Demory, SM Griffies, R Haarsma, T Jung, G Martin, S Minobe, T Ringler, M Satoh, R Schiemann, E Scoccimarro, G Stephens, MF Wehner


The Signature of Oceanic Processes in Decadal Extratropical SST Anomalies

Geophysical Research Letters 45 (2018) 7719-7730

CH O'Reilly, L Zanna

©2018. The Authors. The relationship between decadal sea surface temperature (SST) and turbulent heat fluxes is assessed and used to identify where oceanic processes play an important role in extratropical decadal SST variability. In observational data sets and coupled climate model simulations from the Coupled Model Intercomparison Project Phase 5 archive, positive correlations between upward turbulent heat flux and SSTs indicate an active role of oceanic processes over regions in the North Atlantic, Northwest Pacific, Southern Pacific, and Southern Atlantic. The contrasting nature of oceanic influence on decadal SST anomalies in the Northwest Pacific and North Atlantic is identified. Over the Northwest Pacific, SST anomalies are consistent with changes in the horizontal wind-driven gyre circulation on timescales of between 3 and 7 years, in both the observations and models. Over the North Atlantic, SST anomalies are also preceded by atmospheric circulation anomalies, though the response is stronger at longer timescales—peaking at around 20 years in the observations and at around 10 years in the models.


Recent multivariate changes in the North Atlantic climate system, with a focus on 2005–2016

International Journal of Climatology (2018)

J Robson, RT Sutton, A Archibald, F Cooper, M Christensen, LJ Gray, NP Holliday, C Macintosh, M McMillan, B Moat, M Russo, R Tilling, K Carslaw, D Desbruyères, O Embury, DL Feltham, DP Grosvenor, S Josey, B King, A Lewis, GD McCarthy, C Merchant, AL New, CH O'Reilly, SM Osprey, K Read, A Scaife, A Shepherd, B Sinha, D Smeed, D Smith, A Ridout, T Woollings, M Yang

© 2018 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Major changes are occurring across the North Atlantic climate system, including in the atmosphere, ocean and cryosphere, and many observed changes are unprecedented in instrumental records. As the changes in the North Atlantic directly affect the climate and air quality of the surrounding continents, it is important to fully understand how and why the changes are taking place, not least to predict how the region will change in the future. To this end, this article characterizes the recent observed changes in the North Atlantic region, especially in the period 2005–2016, across many different aspects of the system including: atmospheric circulation; atmospheric composition; clouds and aerosols; ocean circulation and properties; and the cryosphere. Recent changes include: an increase in the speed of the North Atlantic jet stream in winter; a southward shift in the North Atlantic jet stream in summer, associated with a weakening summer North Atlantic Oscillation; increases in ozone and methane; increases in net absorbed radiation in the mid-latitude western Atlantic, linked to an increase in the abundance of high level clouds and a reduction in low level clouds; cooling of sea surface temperatures in the North Atlantic subpolar gyre, concomitant with increases in the western subtropical gyre, and a decline in the Atlantic Ocean's overturning circulation; a decline in Atlantic sector Arctic sea ice and rapid melting of the Greenland Ice Sheet. There are many interactions between these changes, but these interactions are poorly understood. This article concludes by highlighting some of the key outstanding questions.


A power law for reduced precision at small spatial scales: Experiments with an SQG model

Quarterly Journal of the Royal Meteorological Society (2018)

T Thornes, P Düben, T Palmer

© 2018 Royal Meteorological Society Representing all variables in double-precision in weather and climate models may be a waste of computer resources, especially when simulating the smallest spatial scales, which are more difficult to accurately observe and model than are larger scales. Recent experiments have shown that reducing to single-precision would allow real-world models to run considerably faster without incurring significant errors. Here, the effects of reducing precision to even lower levels are investigated in the Surface Quasi-Geostrophic system, an idealised system that exhibits a similar power-law spectrum to that of energy in the real atmosphere, by emulating reduced precision on conventional hardware. It is found that precision can be reduced much further for the smallest scales than the largest scales without inducing significant macroscopic error, according to a −4/3 power law, motivating the construction of a “scale-selective” reduced-precision model that performs as well as a double-precision control in short- and long-range forecasts but for a much lower estimated computational cost. A similar scale-selective approach in real-world models could save resources that could be re-invested to allow these models to be run at greater resolution, complexity or ensemble size, potentially leading to more efficient, more accurate forecasts.


Improving Weather Forecast Skill through Reduced-Precision Data Assimilation

MONTHLY WEATHER REVIEW 146 (2018) 49-62

S Hatfield, A Subramanian, T Palmer, P Duben


Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

CLIMATE DYNAMICS 50 (2018) 1161-1176

R Manzanas, A Lucero, A Weisheimer, JM Gutierrez


The impact of stochastic parametrisations on the representation of the Asian summer monsoon

CLIMATE DYNAMICS 50 (2018) 2269-2282

K Strommen, HM Christensen, J Berner, TN Palmer


Seasonal predictability of onset and cessation of the east African rains

Weather and Climate Extremes 21 (2018) 27-35

D MacLeod

© 2018 The Author Advanced warning of delayed onset or early cessation of the rainy seasons would be extremely valuable information for farmers in east Africa and is a common request from regional stakeholders. Such warnings are beginning to be provided, however forecast skill for these metrics has not been demonstrated. Here the forecast skill of the ECMWF seasonal hindcasts is evaluated for onset and cessation forecasts over east Africa. Correlation of forecast with observed long rains anomalies only above a 95% statistical significance level for a small part of the domain, whilst short rains are significance a large part of the region. The added value of updating the forecast outlook with the extended range 46 day forecast is assessed and this gives a small improvement. For the short rains detection of early onset is better near the coast, and late onset detection is better over northwestern Kenya. During exceptionally dry years the method to detect onset and cessation fails. Using this as a definition of a failed season, the model shows significant skill at anticipating long rains season failure in the northwest of Kenya, and short rains failure in Somalia and northeast Kenya. In addition the strength of the correlation between long rains cessation and seasonal total is shown to be particularly weak in observations but too strong in the hindcasts. Predictability of onset and cessation for both seasons appears to arise primarily from the link with seasonal total and it is unclear that the model represents variability in onset and cessation beyond this. This has important implications for operational forecasting: any forecast of season timing which is ‘inconsistent’ with seasonal total (e.g. an early onset but low total rainfall) must be treated with caution. Finally links with zonal winds are investigated. Late onset is correlated with easterly (westerly) anomalies during the long (short) rains, though the strength and spatial pattern of the relationship is not well represented in the model. Early cessation is correlated with easterly anomalies in both seasons for most of the region in both observations and hindcasts. However for the long rains the sign of the correlation is reversed along the coast in observations but not in the hindcasts. These dynamical inconsistencies may have a negative impact on forecast skill and have the potential to inform process-based development of climate modelling in the region.


Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty

Quarterly Journal of the Royal Meteorological Society Wiley (2018)

S Juricke, D MACLEOD, A WEISHEIMER, L ZANNA, T PALMER


The Impact of Tropical Precipitation on Summertime Euro-Atlantic Circulation via a Circumglobal Wave Train

JOURNAL OF CLIMATE 31 (2018) 6481-6504

CH O'Reilly, T Woollings, L Zanna, A Weisheimer


The scaling and skewness of optimally transported meshes on the sphere

Journal of Computational Physics Elsevier 375 (2018) 540-564

CJ Budd, ATT McRae, CJ Cotter

In the context of numerical solution of PDEs, dynamic mesh redistribution methods (r-adaptive methods) are an important procedure for increasing the resolution in regions of interest, without modifying the connectivity of the mesh. Key to the success of these methods is that the mesh should be sufficiently refined (locally) and flexible in order to resolve evolving solution features, but at the same time not introduce errors through skewness and lack of regularity. Some state-of-the-art methods are bottom-up in that they attempt to prescribe both the local cell size and the alignment to features of the solution. However, the resulting problem is overdetermined, necessitating a compromise between these conflicting requirements. An alternative approach, described in this paper, is to prescribe only the local cell size and augment this an optimal transport condition to provide global regularity. This leads to a robust and flexible algorithm for generating meshes fitted to an evolving solution, with minimal need for tuning parameters. Of particular interest for geophysical modelling are meshes constructed on the surface of the sphere. The purpose of this paper is to demonstrate that meshes generated on the sphere using this optimal transport approach have good a-priori regularity and that the meshes produced are naturally aligned to various simple features. It is further shown that the sphere's intrinsic curvature leads to more regular meshes than the plane. In addition to these general results, we provide a wide range of examples relevant to practical applications, to showcase the behaviour of optimally transported meshes on the sphere. These range from axisymmetric cases that can be solved analytically to more general examples that are tackled numerically. Evaluation of the singular values and singular vectors of the mesh transformation provides a quantitative measure of the mesh aniso...


Transforming climate model output to forecasts of wind power production: how much resolution is enough?

METEOROLOGICAL APPLICATIONS 25 (2018) 1-10

D MacLeod, V Torralba, M Davis, F Doblas-Reyes


OPTIMAL-TRANSPORT-BASED MESH ADAPTIVITY ON THE PLANE AND SPHERE USING FINITE ELEMENTS

SIAM JOURNAL ON SCIENTIFIC COMPUTING 40 (2018) A1121-A1148

ATT Mcrae, CJ Cotter, CJ Budd


Ensemble sensitivity analysis of Greenland blocking in medium-range forecasts

Quarterly Journal of the Royal Meteorological Society Wiley (2018)

TJ Parker, T WOOLLINGS, A WEISHEIMER

The North Atlantic Oscillation (NAO) is the leading mode of variability in the large scale circulation over the North Atlantic in winter, and strongly influences the weather and climate of Europe. On synoptic timescales, the negative phase of the NAO often corresponds to the occurrence of a blocking episode over Greenland. Hence, the dynamics and predictability of these blocking events is of interest for the prediction of the NAO and its related impacts over a wide region. Ensemble sensitivity analysis utilises the information contained in probabilistic forecast ensembles to calculate a statistical relationship between a forecast metric and some precursor condition. Here the method is applied to 15‐day forecasts of a set of 26 Greenland blocking events using the state‐of‐the‐art European Centre for Medium‐Range Weather Forecasts (ECMWF) forecasting system. The ensemble sensitivity analysis shows that Greenland blocking does not develop in isolation in these forecasts, but instead the blocking is sensitive to remote precursors, such as 500 hPa and 50 hPa geopotential height, particularly in the low‐frequency flow. In general, there are more significant sensitivities to anomalies in the tropics than in the polar regions. Stratospheric sensitivities tend to emerge at later lead times than tropospheric sensitivities. The strongest and most robust sensitivities correspond to a Rossby wave precursor reaching from the Pacific basin across North America.


Forcing Single-Column Models Using High-Resolution Model Simulations

Journal of Advances in Modeling Earth Systems (2018)

HM Christensen, A Dawson, CE Holloway

©2018. The Authors. 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.


Impact of Gulf Stream SST biases on the global atmospheric circulation

Climate Dynamics (2018) 1-19

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

© 2018 The Author(s) The UK Met Office Unified Model in the Global Coupled 2 (GC2) configuration has a warm bias of up to almost (Formula presented.) in the Gulf Stream SSTs in the winter season, which is associated with surface heat flux biases and potentially related to biases in the atmospheric circulation. The role of this SST bias is examined with a focus on the tropospheric response by performing three sensitivity experiments. The SST biases are imposed on the atmosphere-only configuration of the model over a small and medium section of the Gulf Stream, and also the wider North Atlantic. Here we show that the dynamical response to this anomalous Gulf Stream heating (and associated shifting and changing SST gradients) is to enhance vertical motion in the transient eddies over the Gulf Stream, rather than balance the heating with a linear dynamical meridional wind or meridional eddy heat transport. Together with the imposed Gulf Stream heating bias, the response affects the troposphere not only locally but also in remote regions of the Northern Hemisphere via a planetary Rossby wave response. The sensitivity experiments partially reproduce some of the differences in the coupled configuration of the model relative to the atmosphere-only configuration and to the ERA-Interim reanalysis. These biases may have implications for the ability of the model to respond correctly to variability or changes in the Gulf Stream. Better global prediction therefore requires particular focus on reducing any large western boundary current SST biases in these regions of high ocean-atmosphere interaction.


Changes in European wind energy generation potential within a 1.5 degrees C warmer world

ENVIRONMENTAL RESEARCH LETTERS 13 (2018) ARTN 054032

JS Hosking, D MacLeod, T Phillips, CR Holmes, P Watson, EF Shuckburgh, D Mitchell


Flow dependent ensemble spread in seasonal forecasts of the boreal winter extratropics

ATMOSPHERIC SCIENCE LETTERS 19 (2018) UNSP e815

D MacLeod, C O'Reilly, T Palmer, A Weisheimer

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