A nutrient increment method for reducing bias in global biogeochemical models

Assimilation of physical variables into coupled physical/biogeochemical models poses considerable difficulties. One problem is that data assimilation can break relationships between physical and biological variables. As a consequence, biological tracers, especially nutrients, are incorrectly displaced in the vertical, resulting in unrealistic biogeochemical fields. To prevent this, we present the idea of applying an increment to the nutrient field within a data assimilating model to ensure that nutrient-potential density relationships are maintained within a water column during assimilation. After correcting the nutrients, it is assumed that other biological variables rapidly adjust to the corrected nutrient fields. We applied this method to a 17 year run of the 2° NEMO ocean-ice model coupled to the PlankTOM5 ecosystem model. Results were compared with a control with no assimilation, and with a model with physical assimilation but no nutrient increment. In the nutrient incrementing experiment, phosphate distributions were improved both at high latitudes and at the equator. At midlatitudes, assimilation generated unrealistic advective upwelling of nutrients within the boundary currents, which spread into the subtropical gyres resulting in more biased nutrient fields. This result was largely unaffected by the nutrient increment and is probably due to boundary currents being poorly resolved in a 2° model. Changes to nutrient distributions fed through into other biological parameters altering primary production, air-sea CO2 flux, and chlorophyll distributions. These secondary changes were most pronounced in the subtropical gyres and at the equator, which are more nutrient limited than high latitudes.

Modeling entangled dynamics: comparison between stochastic single-chain and multichain models

To test the effectiveness of stochastic single-chain models in describing the dynamics of entangled polymers, we systematically compare one such model; the slip-spring model; to a multichain model solved using stochastic molecular dynamics(MD) simulations (the Kremer-Grest model). The comparison involves investigating if the single-chain model can adequately describe both a microscopic dynamical and a macroscopic rheological quantity for a range of chain lengths. Choosing a particular chain length in the slip-spring model, the parameter values that best reproduce the mean-square displacement of a group of monomers is determined by fitting toMDdata. Using the same set of parameters we then test if the predictions of the mean-square displacements for other chain lengths agree with the MD calculations. We followed this by a comparison of the time dependent stress relaxation moduli obtained from the two models for a range of chain lengths. After identifying a limitation of the original slip-spring model in describing the static structure of the polymer chain as seen in MD, we remedy this by introducing a pairwise repulsive potential between the monomers in the chains. Poor agreement of the mean-square monomer displacements at short times can be rectified by the use of generalized Langevin equations for the dynamics and resulted in significantly improved agreement.

Effects of utterance length on lip kinematics in aphasia

Most existing models of language production and speech motor control do not explicitly address how language requirements affect speech motor functions, as these domains are usually treated as separate and independent from one another. This investigation compared lip movements during bilabial closure between five individuals with mild aphasia and five age and gender-matched control speakers when the linguistic characteristics of the stimuli were varied by increasing the number of syllables. Upper and lower lip movement data were collected for mono-, bi- and tri-syllabic nonword sequences using an AG 100 EMMA system. Each task was performed under both normal and fast rate conditions. Single articulator kinematic parameters (peak velocity, amplitude, duration,and cyclic spatio-temporal index) were measured to characterize lip movements. Results revealed that compared to control speakers, individuals with aphasia showed significantly longer movement duration and lower movement stability for longer items (bi- and tri-syllables). Moreover, utterance length affected the lip kinematics, in that the monosyllables had smaller peak velocities, smaller amplitudes and shorter durations compared to bi- and trisyllables, and movement stability was lowest for the trisyllables. In addition, the rate-induced changes (smaller amplitude and shorter duration with increased rate) were most prominent for the short items (i.e., monosyllables). These findings provide further support for the notion that linguistic changes have an impact on the characteristics of speech movements, and that individuals with aphasia are more affected by such changes than control speakers.

Large-scale length and time scales for use with stochastic convective parameterization

Many numerical models for weather prediction and climate studies are run at resolutions that are too coarse to resolve convection explicitly, but too fine to justify the local equilibrium assumed by conventional convective parameterizations. The Plant-Craig (PC) stochastic convective parameterization scheme, developed in this paper, solves this problem by removing the assumption that a given grid-scale situation must always produce the same sub-grid-scale convective response. Instead, for each timestep and gridpoint, one of the many possible convective responses consistent with the large-scale situation is randomly selected. The scheme requires as input the large-scale state as opposed to the instantaneous grid-scale state, but must nonetheless be able to account for genuine variations in the largescale situation. Here we investigate the behaviour of the PC scheme in three-dimensional simulations of radiative-convective equilibrium, demonstrating in particular that the necessary space-time averaging required to produce a good representation of the input large-scale state is not in conflict with the requirement to capture large-scale variations. The resulting equilibrium profiles agree well with those obtained from established deterministic schemes, and with corresponding cloud-resolving model simulations. Unlike the conventional schemes the statistics for mass flux and rainfall variability from the PC scheme also agree well with relevant theory and vary appropriately with spatial scale. The scheme is further shown to adapt automatically to changes in grid length and in forcing strength.

Root growth models: towards a new generation of continuous approaches

Models of root system growth emerged in the early 1970s, and were based on mathematical representations of root length distribution in soil. The last decade has seen the development of more complex architectural models and the use of computer-intensive approaches to study developmental and environmental processes in greater detail. There is a pressing need for predictive technologies that can integrate root system knowledge, scaling from molecular to ensembles of plants. This paper makes the case for more widespread use of simpler models of root systems based on continuous descriptions of their structure. A new theoretical framework is presented that describes the dynamics of root density distributions as a function of individual root developmental parameters such as rates of lateral root initiation, elongation, mortality, and gravitropsm. The simulations resulting from such equations can be performed most efficiently in discretized domains that deform as a result of growth, and that can be used to model the growth of many interacting root systems. The modelling principles described help to bridge the gap between continuum and architectural approaches, and enhance our understanding of the spatial development of root systems. Our simulations suggest that root systems develop in travelling wave patterns of meristems, revealing order in otherwise spatially complex and heterogeneous systems. Such knowledge should assist physiologists and geneticists to appreciate how meristem dynamics contribute to the pattern of growth and functioning of root systems in the field.

Assessment of surface winds over the Atlantic, Indian and Pacific Ocean sectors of the Southern Ocean in CMIP5 models: historical bias, forcing response, and state dependence

An assessment of the fifth Coupled Models Intercomparison Project (CMIP5) models’ simulation of the near-surface westerly wind jet position and strength over the Atlantic, Indian and Pacific sectors of the Southern Ocean is presented. Compared with reanalysis climatologies there is an equatorward bias of 3.7° (inter-model standard deviation of ± 2.2°) in the ensemble mean position of the zonal mean jet. The ensemble mean strength is biased slightly too weak, with the largest biases over the Pacific sector (-1.6±1.1 m/s, 27 -22%). An analysis of atmosphere-only (AMIP) experiments indicates that 41% of the zonal mean position bias comes from coupling of the ocean/ice models to the atmosphere. The response to future emissions scenarios (RCP4.5 and RCP8.5) is characterized by two phases: (i) the period of most rapid ozone recovery (2000-2049) during which there is insignificant change in summer; and (ii) the period 2050-2098 during which RCP4.5 simulations show no significant change but RCP8.5 simulations show poleward shifts (0.30, 0.19 and 0.28°/decade over the Atlantic, Indian and Pacific sectors respectively), and increases in strength (0.06, 0.08 and 0.15 m/s/decade respectively). The models with larger equatorward position biases generally show larger poleward shifts (i.e. state dependence). This inter-model relationship is strongest over the Pacific sector (r=-0.89) and insignificant over the Atlantic sector (r=-0.50). However, an assessment of jet structure shows that over the Atlantic sector jet shift is significantly correlated with jet width whereas over the Pacific sector the distance between the sub-polar and sub-tropical westerly jets appears to be more important.

Some numerical experiments on the effect of the variation of static stability in two-layer quasi-geostrophic models

A method to solve a quasi-geostrophic two-layer model including the variation of static stability is presented. The divergent part of the wind is incorporated by means of an iterative procedure. The procedure is rather fast and the time of computation is only 60–70% longer than for the usual two-layer model. The method of solution is justified by the conservation of the difference between the gross static stability and the kinetic energy. To eliminate the side-boundary conditions the experiments have been performed on a zonal channel model. The investigation falls mainly into three parts: The first part (section 5) contains a discussion of the significance of some physically inconsistent approximations. It is shown that physical inconsistencies are rather serious and for these inconsistent models which were studied the total kinetic energy increased faster than the gross static stability. In the next part (section 6) we are studying the effect of a Jacobian difference operator which conserves the total kinetic energy. The use of this operator in two-layer models will give a slight improvement but probably does not have any practical use in short periodic forecasts. It is also shown that the energy-conservative operator will change the wave-speed in an erroneous way if the wave-number or the grid-length is large in the meridional direction. In the final part (section 7) we investigate the behaviour of baroclinic waves for some different initial states and for two energy-consistent models, one with constant and one with variable static stability. According to the linear theory the waves adjust rather rapidly in such a way that the temperature wave will lag behind the pressure wave independent of the initial configuration. Thus, both models give rise to a baroclinic development even if the initial state is quasi-barotropic. The effect of the variation of static stability is very small, qualitative differences in the development are only observed during the first 12 hours. For an amplifying wave we will get a stabilization over the troughs and an instabilization over the ridges.

Southern annular mode dynamics in observations and models, Part I: The influence of climatological zonal wind biases in a comprehensive GCM

A common bias among global climate models (GCMs) is that they exhibit tropospheric southern annular mode (SAM) variability that is much too persistent in the Southern Hemisphere (SH) summertime. This is of concern for the ability to accurately predict future SH circulation changes, so it is important that it be understood and alleviated. In this two-part study, specifically targeted experiments with the Canadian Middle Atmosphere Model (CMAM) are used to improve understanding of the enhanced summertime SAM persistence. Given the ubiquity of this bias among comprehensive GCMs, it is likely that the results will be relevant for other climate models. Here, in Part I, the influence of climatological circulation biases on SAM variability is assessed, with a particular focus on two common biases that could enhance summertime SAM persistence: the too-late breakdown of the Antarctic stratospheric vortex and the equatorward bias in the SH tropospheric midlatitude jet. Four simulations are used to investigate the role of each of these biases in CMAM. Nudging and bias correcting procedures are used to systematically remove zonal-mean stratospheric variability and/or remove climatological zonal wind biases. The SAM time-scale bias is not alleviated by improving either the timing of the stratospheric vortex breakdown or the climatological jet structure. Even in the absence of stratospheric variability and with an improved climatological circulation, the model time scales are biased long. This points toward a bias in internal tropospheric dynamics that is not caused by the tropospheric jet structure bias. The underlying cause of this is examined in more detail in Part II of this study.

Fireball models for flares in AE Aquarii

We examine the flaring behaviour of the cataclysmic variable AE Aqr in the context of the `magnetic propeller' model for this system. The flares are thought to arise from collisions between high-density regions in the material expelled from the system after interaction with the rapidly rotating magnetosphere of the white dwarf. We calculate the first quantitative models for the flaring and calculate the time-dependent emergent optical spectra from the resulting hot, expanding ball of gas. We compare the results under different assumptions to observations and derive values for the mass, length-scale and temperature of the material involved in the flare. We see that the fits suggest that the secondary star in this system has Population II composition.

Influence of mass diffusion in sea ice dynamical models

The mixing of floes of different thickness caused by repeated deformation of the ice cover is modeled as diffusion, and the mass balance equation for sea ice accounting for mass diffusion is developed. The effect of deformational diffusion on the ice thickness balance is shown to reach 1% of the divergence effect, which describes ridging and lead formation. This means that with the same accuracy the mass balance equation can be written in terms of mean velocity rather than mean mass-weighted velocity, which one should correctly use for a multicomponent fluid such as sea ice with components identified by floe thickness. Mixing (diffusion) of sea ice also occurs because of turbulent variations in wind and ocean drags that are unresolved in models. Estimates of the importance of turbulent mass diffusion on the dynamic redistribution of ice thickness are determined using empirical data for the turbulent diffusivity. For long-time-scale prediction (≫5 days), where unresolved atmospheric motion may have a length scale on the order of the Arctic basin and the time scale is larger than the synoptic time scale of atmospheric events, turbulent mass diffusion can exceed 10% of the divergence effect. However, for short-time-scale prediction, for example, 5 days, the unresolved scales are on the order of 100 km, and turbulent diffusion is about 0.1% of the divergence effect. Because inertial effects are small in the dynamics of the sea ice pack, diffusive momentum transfer can be disregarded.

Forecasting models of retail rents

The authors model retail rents in the United Kingdom with use of vector-autoregressive and time-series models. Two retail rent series are used, compiled by LaSalle Investment Management and CB Hillier Parker, and the emphasis is on forecasting. The results suggest that the use of the vector-autoregression and time-series models in this paper can pick up important features of the data that are useful for forecasting purposes. The relative forecasting performance of the models appears to be subject to the length of the forecast time-horizon. The results also show that the variables which were appropriate for inclusion in the vector-autoregression systems differ between the two rent series, suggesting that the structure of optimal models for predicting retail rents could be specific to the rent index used. Ex ante forecasts from our time-series suggest that both LaSalle Investment Management and CB Hillier Parker real retail rents will exhibit an annual growth rate above their long-term mean.

Disparity-driven vs blur-driven models of accommodation and convergence in binocular vision and intermittent strabismus

Background. Current models of concomitant, intermittent strabismus, heterophoria, convergence and accommodation anomalies are either theoretically complex or incomplete. We propose an alternative and more practical way to conceptualize clinical patterns. Methods. In each of three hypothetical scenarios (normal; high AC/A and low CA/C ratios; low AC/A and high CA/C ratios) there can be a disparity-biased or blur-biased “style”, despite identical ratios. We calculated a disparity bias index (DBI) to reflect these biases. We suggest how clinical patterns fit these scenarios and provide early objective data from small illustrative clinical groups. Results. Normal adults and children showed disparity bias (adult DBI 0.43 (95%CI 0.50-0.36), child DBI 0.20 (95%CI 0.31-0.07) (p=0.001). Accommodative esotropes showed less disparity-bias (DBI 0.03). In the high AC/A and low CA/C scenario, early presbyopes had mean DBI of 0.17 (95%CI 0.28-0.06), compared to DBI of -0.31 in convergence excess esotropes. In the low AC/A and high CA/C scenario near exotropes had mean DBI of 0.27, while we predict that non-strabismic, non-amblyopic hyperopes with good vision without spectacles will show lower DBIs. Disparity bias ranged between 1.25 and -1.67. Conclusions. Establishing disparity or blur bias, together with knowing whether convergence to target demand exceeds accommodation or vice versa explains clinical patterns more effectively than AC/A and CA/C ratios alone. Excessive bias or inflexibility in near-cue use increases risk of clinical problems. We suggest clinicians look carefully at details of accommodation and convergence changes induced by lenses, dissociation and prisms and use these to plan treatment in relation to the model.

Tropical cyclones in the UPSCALE ensemble of high resolution global climate models

The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project, using PRACE (Partnership for Advanced Computing in Europe) resources, constructed and ran an ensemble of atmosphere-only global climate model simulations, using the Met Office Unified Model GA3 configuration. Each simulation is 27 years in length for both the present climate and an end-of-century future climate, at resolutions of N96 (130 km), N216 (60 km) and N512 (25 km), in order to study the impact of model resolution on high impact climate features such as tropical cyclones. Increased model resolution is found to improve the simulated frequency of explicitly tracked tropical cyclones, and correlations of interannual variability in the North Atlantic and North West Pacific lie between 0.6 and 0.75. Improvements in the deficit of genesis in the eastern North Atlantic as resolution increases appear to be related to the representation of African Easterly Waves and the African Easterly Jet. However, the intensity of the modelled tropical cyclones as measured by 10 m wind speed remain weak, and there is no indication of convergence over this range of resolutions. In the future climate ensemble, there is a reduction of 50% in the frequency of Southern Hemisphere tropical cyclones, while in the Northern Hemisphere there is a reduction in the North Atlantic, and a shift in the Pacific with peak intensities becoming more common in the Central Pacific. There is also a change in tropical cyclone intensities, with the future climate having fewer weak storms and proportionally more stronger storms

Intercomparison and evaluation of global aerosol microphysical properties among AeroCom models of a range of complexity

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

The DYMECS project: a statistical approach for the evaluation of convective storms in high-resolution NWP models

A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective storms and rainfall distributions. The DYMECS project (Dynamical and Microphysical Evolution of Convective Storms) is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, we have gathered a large database of 3D storm structures on 40 convective days using the Chilbolton radar in southern England. We have related these structures to storm life-cycles derived by tracking features in the rainfall from the UK radar network, and compared them statistically to storm structures in the Met Office model, which we ran at horizontal grid length between 1.5 km and 100 m, including simulations with different subgrid mixing length. We also evaluated the scale and intensity of convective updrafts using a new radar technique. We find that the horizontal size of simulated convective storms and the updrafts within them is much too large at 1.5-km resolution, such that the convective mass flux of individual updrafts can be too large by an order of magnitude. The scale of precipitation cores and updrafts decreases steadily with decreasing grid lengths, as does the typical storm lifetime. The 200-m grid-length simulation with standard mixing length performs best over all diagnostics, although a greater mixing length improves the representation of deep convective storms.