A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances

Variational data assimilation for parameter estimation: application to a simple morphodynamic model

Data assimilation is a sophisticated mathematical technique for combining observational data with model predictions to produce state and parameter estimates that most accurately approximate the current and future states of the true system. The technique is commonly used in atmospheric and oceanic modelling, combining empirical observations with model predictions to produce more accurate and well-calibrated forecasts. Here, we consider a novel application within a coastal environment and describe how the method can also be used to deliver improved estimates of uncertain morphodynamic model parameters. This is achieved using a technique known as state augmentation. Earlier applications of state augmentation have typically employed the 4D-Var, Kalman filter or ensemble Kalman filter assimilation schemes. Our new method is based on a computationally inexpensive 3D-Var scheme, where the specification of the error covariance matrices is crucial for success. A simple 1D model of bed-form propagation is used to demonstrate the method. The scheme is capable of recovering near-perfect parameter values and, therefore, improves the capability of our model to predict future bathymetry. Such positive results suggest the potential for application to more complex morphodynamic models.

The geography of tyranny and despair: development indicators and the hypothesis of genetic inevitability of national inequality

Development geography has long sought to understand why inequalities exist and the best ways to address them. Dependency theory sets out an historical rationale for under development based on colonialism and a legacy of developed core and under-developed periphery. Race is relevant in this theory only insofar that Europeans are white and the places they colonised were occupied by people with darker skin colour. There are no innate biological reasons why it happened in that order. However, a new theory for national inequalities proposed by Lynn and Vanhanen in a series of publications makes the case that poorer countries have that status because of a poorer genetic stock rather than an accident of history. They argue that IQ has a genetic basis and IQ is linked to ability. Thus races with a poorer IQ have less ability, and thus national IQ can be positively correlated with performance as measured by an indicator like GDP/capita. Their thesis is one of despair, as little can be done to improve genetic stock significantly other than a programme of eugenics. This paper summarises and critiques the Lynn and Vanhanen hypothesis and the assumptions upon which it is based, and uses this analysis to show how a human desire to simplify in order to manage can be dangerous in development geography. While the attention may naturally be focused on the 'national IQ' variables as a proxy measure of 'innate ability', the assumption of GDP per capita as an indicator of 'success' and 'achievement' is far more readily accepted without criticism. The paper makes the case that the current vogue for indicators, indices and cause-effect can be tyrannical.

A Functional Magnetic Resonance Imaging Predictor of Treatment Response to Venlafaxine in Generalized Anxiety Disorder

Background: Functional magnetic resonance imaging (fMRI) holds promise as a noninvasive means of identifying neural responses that can be used to predict treatment response before beginning a drug trial. Imaging paradigms employing facial expressions as presented stimuli have been shown to activate the amygdala and anterior cingulate cortex (ACC). Here, we sought to determine whether pretreatment amygdala and rostral ACC (rACC) reactivity to facial expressions could predict treatment outcomes in patients with generalized anxiety disorder (GAD).Methods: Fifteen subjects (12 female subjects) with GAD participated in an open-label venlafaxine treatment trial. Functional magnetic resonance imaging responses to facial expressions of emotion collected before subjects began treatment were compared with changes in anxiety following 8 weeks of venlafaxine administration. In addition, the magnitude of fMRI responses of subjects with GAD were compared with that of 15 control subjects (12 female subjects) who did not have GAD and did not receive venlafaxine treatment.Results The magnitude of treatment response was predicted by greater pretreatment reactivity to fearful faces in rACC and lesser reactivity in the amygdala. These individual differences in pretreatment rACC and amygdala reactivity within the GAD group were observed despite the fact that 1) the overall magnitude of pretreatment rACC and amygdala reactivity did not differ between subjects with GAD and control subjects and 2) there was no main effect of treatment on rACC-amygdala reactivity in the GAD group.Conclusions: These findings show that this pattern of rACC-amygdala responsivity could prove useful as a predictor of venlafaxine treatment response in patients with GAD.