A continuum model of a fishing net

A working report for the Department of Agriculture and Fisheries, Scotland, Marine Laboratory Aberdeen

Breakdown of hydrostatic balance at convective scales in the forecast errors in the Met Office Unified Model

For data assimilation in numerical weather prediction, the initial forecast-error covariance matrix Pf is required. For variational assimilation it is particularly important to prescribe an accurate initial matrix Pf, since Pf is either static (in the 3D-Var case) or constant at the beginning of each assimilation window (in the 4D-Var case). At large scales the atmospheric flow is well approximated by hydrostatic balance and this balance is strongly enforced in the initial matrix Pf used in operational variational assimilation systems such as that of the Met Office. However, at convective scales this balance does not necessarily hold any more. Here we examine the extent to which hydrostatic balance is valid in the vertical forecast-error covariances for high-resolution models in order to determine whether there is a need to relax this balance constraint in convective-scale data assimilation. We use the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and a 1.5 km resolution version of the Unified Model for a case study characterized by the presence of convective activity. An ensemble of high-resolution forecasts valid up to three hours after the onset of convection is produced. We show that at 1.5 km resolution hydrostatic balance does not hold for forecast errors in regions of convection. This indicates that in the presence of convection hydrostatic balance should not be enforced in the covariance matrix used for variational data assimilation at this scale. The results show the need to investigate covariance models that may be better suited for convective-scale data assimilation. Finally, we give a measure of the balance present in the forecast perturbations as a function of the horizontal scale (from 3–90 km) using a set of diagnostics. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office

Integration of a 3D Variational data assimilation scheme with a coastal area morphodynamic model of Morecambe Bay

This paper describes the implementation of a 3D variational (3D-Var) data assimilation scheme for a morphodynamic model applied to Morecambe Bay, UK. A simple decoupled hydrodynamic and sediment transport model is combined with a data assimilation scheme to investigate the ability of such methods to improve the accuracy of the predicted bathymetry. The inverse forecast error covariance matrix is modelled using a Laplacian approximation which is calibrated for the length scale parameter required. Calibration is also performed for the Soulsby-van Rijn sediment transport equations. The data used for assimilation purposes comprises waterlines derived from SAR imagery covering the entire period of the model run, and swath bathymetry data collected by a ship-borne survey for one date towards the end of the model run. A LiDAR survey of the entire bay carried out in November 2005 is used for validation purposes. The comparison of the predictive ability of the model alone with the model-forecast-assimilation system demonstrates that using data assimilation significantly improves the forecast skill. An investigation of the assimilation of the swath bathymetry as well as the waterlines demonstrates that the overall improvement is initially large, but decreases over time as the bathymetry evolves away from that observed by the survey. The result of combining the calibration runs into a pseudo-ensemble provides a higher skill score than for a single optimized model run. A brief comparison of the Optimal Interpolation assimilation method with the 3D-Var method shows that the two schemes give similar results.

Adeno-associated virus-8-Mediated intravenous transfer of myostatin propeptide leads to systemic functional improvements of slow but not fast muscle

Myostatin is a member of the transformating growth factor-_ (TGF-_) superfamily of proteins and is produced almost exclusively in skeletal muscle tissue, where it is secreted and circulates as a serum protein. Myostatin acts as a negative regulator of muscle mass through the canonical SMAD2/3/4 signaling pathway. Naturally occurring myostatin mutants exhibit a ‘double muscling’ phenotype in which muscle mass is dramatically increased as a result of both hypertrophy and hyperplasia. Myostatin is naturally inhibited by its own propeptide; therefore, we assessed the impact of adeno associated virus-8 (AAV8) myostatin propeptide vectors when systemically introduced in MF-1 mice. We noted a significant systemic increase in muscle mass in both slow and fast muscle phenotypes, with no evidence of hyperplasia; however, the nuclei-to- cytoplasm ratio in all myofiber types was significantly reduced. An increase in muscle mass in slow (soleus) muscle led to an increase in force output; however, an increase in fast (extensor digitorum longus [EDL]) muscle mass did not increase force output. These results suggest that the use of gene therapeutic regimens of myostatin inhibition for age-related or disease-related muscle loss may have muscle-specific effects.