Lagrangian ocean analysis: Fundamentals and practices

OCEAN MODELLING 121 (2018) 49-75

E van Sebille, SM Griffies, R Abernathey, TP Adams, P Berloff, A Biastoch, B Blanke, EP Chassignet, Y Cheng, CJ Cotter, E Deleersnijder, K Doos, HF Drake, S Drijfhout, SF Gary, AW Heemink, J Kjellsson, IM Koszalka, M Lange, C Lique, GA MacGilchrist, R Marsh, CGM Adame, R McAdam, F Nencioli, CB Paris, MD Piggott, JA Polton, S Ruehs, SHAM Shah, MD Thomas, J Wang, PJ Wolfram, L Zanna, JD Zika

First Successful Hindcasts of the 2016 Disruption of the Stratospheric Quasi-biennial Oscillation


S Watanabe, K Hamilton, S Osprey, Y Kawatani, E Nishimoto

Report on the Joint SPARC Dynamics and Observations Work- shop: SATIO-TCS, FISAPS and QBOi, Kyoto, Japan

(2018) 50

J Anstey, S Yoden, M Geller, SM Osprey, K Hamilton, N Butchart

Changing response of the North Atlantic/European winter climate to the 11 year solar cycle


H Ma, H Chen, L Gray, L Zhou, X Li, R Wang, S Zhu

Quantifying the effects of horizontal grid length and parameterized convection on the degree of convective organization using a metric of the potential for convective interaction

Journal of the Atmospheric Sciences 75 (2018) 425-450

BA White, AM Buchanan, CE Birch, P Stier, KJ Pearson

© 2018 American Meteorological Society. The organization of deep convection and its misrepresentation in many global models is the focus of much current interest. A new method is presented for quantifying convective organization based on the identification of convective objects and subsequent derivation of object numbers, areas, and separation distances to describe the degree of convective organization. These parameters are combined into a "convection organization potential" based on the physical principle of an interaction potential between pairs of convective objects. This technique is applied to simulated and observed fields of outgoing longwave radiation (OLR) over the West African monsoon region using data from Met Office Unified Model simulations and satellite observations made by the Geostationary Earth Radiation Budget (GERB) instrument. The method is evaluated by using it to quantify differences between models with different horizontal grid lengths and representations of convection. Distributions of OLR, precipitation and organization parameters, the diurnal cycle of convection, and relationships between the meteorology in different states of organization are compared. Switching from a configuration with parameterized convection to one that allows the model to resolve convective processes at the model grid scale is the leading-order factor improving some aspects of model performance, while increased model resolution is the dominant factor for others. However, no single model configuration performs best compared to observations, indicating underlying deficiencies in both model scaling and process understanding.

Improving weather forecast skill through reduced-precision data assimilation

Monthly Weather Review 146 (2018) 49-62

S Hatfield, A Subramanian, T Palmer, P Düben

© 2018 American Meteorological Society. A new approach for improving the accuracy of data assimilation, by trading numerical precision for ensemble size, is introduced. Data assimilation is inherently uncertain because of the use of noisy observations and imperfect models. Thus, the larger rounding errors incurred from reducing precision may be within the tolerance of the system. Lower-precision arithmetic is cheaper, and so by reducing precision in ensemble data assimilation, computational resources can be redistributed toward, for example, a larger ensemble size. Because larger ensembles provide a better estimate of the underlying distribution and are less reliant on covariance inflation and localization, lowering precision could actually permit an improvement in the accuracy of weather forecasts. Here, this idea is tested on an ensemble data assimilation system comprising the Lorenz '96 toy atmospheric model and the ensemble square root filter. The system is run at double-, single-, and half-precision (the latter using an emulation tool), and the performance of each precision is measured through mean error statistics and rank histograms. The sensitivity of these results to the observation error and the length of the observation window are addressed. Then, by reinvesting the saved computational resources from reducing precision into the ensemble size, assimilation error can be reduced for (hypothetically) no extra cost. This results in increased forecasting skill, with respect to double-pre cision assimilation.

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)

Geoscientific Model Development Copernicus Publications 11 (2018) 1009-1032

N Butchart, J Anstey, K Hamilton, SM Osprey, C McLandress, A Bushell, Y Kawatani, Y-H Kim, F Lott, J Scinocca, T Stockdale, M Andrews, O Bellprat, P Braesicke, C Cagnazzo, C-C Chen, H-Y Chun, M Dobrynin, R Garcia, J Garcia-Serrano, L Gray, L Holt, T Kerzenmacher, H Naoe, H Pohlmann, J Richter, A Scaife, V Schenzinger, F Serva, S Versick, S Watanabe, K Yoshida, S Yukimoto

The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison.

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

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


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

Southern Ocean carbon-wind stress feedback

Climate Dynamics (2018) 1-15

B Bronselaer, L Zanna, DR Munday, J Lowe

© 2017 The Author(s) The Southern Ocean is the largest sink of anthropogenic carbon in the present-day climate. Here, Southern Ocean (Formula presented.) and its dependence on wind forcing are investigated using an equilibrium mixed layer carbon budget. This budget is used to derive an expression for Southern Ocean (Formula presented.) sensitivity to wind stress. Southern Ocean (Formula presented.) is found to vary as the square root of area-mean wind stress, arising from the dominance of vertical mixing over other processes such as lateral Ekman transport. The expression for p\hbox {CO}_{2} is validated using idealised coarse-resolution ocean numerical experiments. Additionally, we show that increased (decreased) stratification through surface warming reduces (increases) the sensitivity of the Southern Ocean (Formula presented.) to wind stress. The scaling is then used to estimate the wind-stress induced changes of atmospheric (Formula presented.) in CMIP5 models using only a handful of parameters. The scaling is further used to model the anthropogenic carbon sink, showing a long-term reversal of the Southern Ocean sink for large wind stress strength.

Frazil-ice growth rate and dynamics in mixed layers and sub-ice-shelf plumes

CRYOSPHERE 12 (2018) 25-38

DWR Jones, AJ Wells

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.

Climate Impacts From a Removal of Anthropogenic Aerosol Emissions


BH Samset, M Sand, CJ Smith, SE Bauer, PM Forster, JS Fuglestvedt, S Osprey, C-F Schleussner

Challenges and opportunities for improved understanding of regional climate dynamics

NATURE CLIMATE CHANGE 8 (2018) 101-108

M Collins, S Minobe, M Barreiro, S Bordoni, Y Kaspi, A Kuwano-Yoshida, N Keenlyside, E Manzini, CH O'Reilly, R Sutton, S-P Xie, O Zolina

Processes Maintaining Tropopause Sharpness in Numerical Models

Journal of Geophysical Research: Atmospheres 122 (2017) 9611-9627

L Saffin, SL Gray, J Methven, KD Williams

©2017. The Authors. Recent work has shown that the sharpness of the extratropical tropopause declines with lead time in numerical weather prediction models, indicating an imbalance between processes acting to sharpen and smooth the tropopause. In this study the systematic effects of processes contributing to the tropopause sharpness are investigated using daily initialized forecasts run with the Met Office Unified Model over a three-month winter period. Artificial tracers, each forced by the potential vorticity tendency due to a different model process, are used to separate the effects of such processes. The advection scheme is shown to result in an exponential decay of tropopause sharpness toward a finite value at short lead times with a time scale of 20–24 h. The systematic effect of nonconservative processes is to sharpen the tropopause, consistent with previous case studies. The decay of tropopause sharpness due to the advection scheme is stronger than the sharpening effect of nonconservative processes leading to a systematic decline in tropopause sharpness with forecast lead time. The systematic forecast errors in tropopause level potential vorticity are comparable to the integrated tendencies of the parametrized physical processes suggesting that the systematic error in tropopause sharpness could be significantly reduced through realistic adjustments to the model parametrization schemes.

Characterizing the chaotic nature of ocean ventilation


GA MacGilchrist, DP Marshall, HL Johnson, C Lique, M Thomas

Submesoscale Instabilities in Mesoscale Eddies


L Brannigan, DP Marshall, ACN Garabato, AJG Nurser, J Kaiser

Uncertainty information in climate data records from Earth observation

Earth System Science Data 9 (2017) 511-527

CJ Merchant, F Paul, T Popp, M Ablain, S Bontemps, P Defourny, R Hollmann, T Lavergne, A Laeng, G de Leeuw, J Mittaz, C Poulsen, AC Povey, M Reuter, S Sathyendranath, S Sandven, VF Sofieva, W Wagner

A note on ‘Toward a stochastic parameterization of ocean mesoscale eddies’

Ocean Modelling 113 (2017) 30-33

I Grooms, L Zanna

© 2017 Porta Mana and Zanna (2014) recently proposed a subgrid-scale parameterization for eddy-permitting quasigeostrophic models. In this model the large-scale fluid is represented as a non-Newtonian viscoelastic medium, with a subgrid-stress closure that involves the Lagrangian derivative of large-scale quantities. This note derives this parameterization, including the nondimensional proportionality coefficient, using only two statistical assumptions: that the subgrid-scale term is locally homogeneous and decorrelates rapidly in space. The parameterization is then verified by comparing against eddy-resolving quasigeostrophic simulations, independently reproducing the results of Porta Mana and Zanna in a simpler model.

A study of reduced numerical precision to make superparameterization more competitive using a hardware emulator in the OpenIFS model


PD Duben, A Subramanian, A Dawson, TN Palmer