Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA40

Reanalysis data obtained from data assimilation are increasingly used for diagnostic studies of the general circulation of the atmosphere, for the validation of modelling experiments and for estimating energy and water fluxes between the Earth surface and the atmosphere. Because fluxes are not specifically observed, but determined by the data assimilation system, they are not only influenced by the utilized observations but also by model physics and dynamics and by the assimilation method. In order to better understand the relative importance of humidity observations for the determination of the hydrological cycle, in this paper we describe an assimilation experiment using the ERA40 reanalysis system where all humidity data have been excluded from the observational data base. The surprising result is that the model, driven by the time evolution of wind, temperature and surface pressure, is able to almost completely reconstitute the large-scale hydrological cycle of the control assimilation without the use of any humidity data. In addition, analysis of the individual weather systems in the extratropics and tropics using an objective feature tracking analysis indicates that the humidity data have very little impact on these systems. We include a discussion of these results and possible consequences for the way moisture information is assimilated, as well as the potential consequences for the design of observing systems for climate monitoring. It is further suggested, with support from a simple assimilation study with another model, that model physics and dynamics play a decisive role for the hydrological cycle, stressing the need to better understand these aspects of model parametrization. .

Life-cycle simulations of shallow frontal waves and the impact of deformation strain

The life-cycle of shallow frontal waves and the impact of deformation strain on their development is investigated using the idealised version of the Met Office non-hydrostatic Unified Model which includes the same physics and dynamics as the operational forecast model. Frontal wave development occurs in two stages; first, a deformation strain is applied to a front and a positive potential vorticity (PV) strip forms, generated by latent heat release in the frontal updraft; second, as the deformation strain is reduced the PV strip breaks up into individual anomalies. The circulations associated with the PV anomalies cause shallow frontal waves to form. The structure of the simulated frontal waves is consistent with the conceptual model of a frontal cyclone. Deeper frontal waves are simulated if the stability of the atmosphere is reduced. Deformation strain rates of different strengths are applied to the PV strip to determine whether a deformation strain threshold exists above which frontal wave development is suppressed. An objective method of frontal wave activity is defined and frontal wave development was found to be suppressed by deformation strain rates $\ge 0.4\times10^{-5}\mbox{s}^{-1}$. This value compares well with observed deformation strain rate thresholds and the analytical solution for the minimum deformation strain rate needed to suppress barotropic frontal wave development. The deformation strain rate threshold is dependent on the strength of the PV strip with strong PV strips able to overcome stronger deformation strain rates (leading to frontal wave development) than weaker PV strips.

Serving GODAE Data and Products to the Ocean Community

The Global Ocean Data Assimilation Experiment (GODAE [http:// www.godae.org]) has spanned a decade of rapid technological development. The ever-increasing volume and diversity of oceanographic data produced by in situ instruments, remote-sensing platforms, and computer simulations have driven the development of a number of innovative technologies that are essential for connecting scientists with the data that they need. This paper gives an overview of the technologies that have been developed and applied in the course of GODAE, which now provide users of oceanographic data with the capability to discover, evaluate, visualize, download, and analyze data from all over the world. The key to this capability is the ability to reduce the inherent complexity of oceanographic data by providing a consistent, harmonized view of the various data products. The challenges of data serving have been addressed over the last 10 years through the cooperative skills and energies of many individuals.

A simple model for predicting soil temperature in snow-covered and seasonally frozen soil: model description and testing

Microbial processes in soil are moisture, nutrient and temperature dependent and, consequently, accurate calculation of soil temperature is important for modelling nitrogen processes. Microbial activity in soil occurs even at sub-zero temperatures so that, in northern latitudes, a method to calculate soil temperature under snow cover and in frozen soils is required. This paper describes a new and simple model to calculate daily values for soil temperature at various depths in both frozen and unfrozen soils. The model requires four parameters average soil thermal conductivity, specific beat capacity of soil, specific heat capacity due to freezing and thawing and an empirical snow parameter. Precipitation, air temperature and snow depth (measured or calculated) are needed as input variables. The proposed model was applied to five sites in different parts of Finland representing different climates and soil types. Observed soil temperatures at depths of 20 and 50 cm (September 1981-August 1990) were used for model calibration. The calibrated model was then tested using observed soil temperatures from September 1990 to August 2001. R-2-values of the calibration period varied between 0.87 and 0.96 at a depth of 20 cm and between 0.78 and 0.97 at 50 cm. R-2 -values of the testing period were between 0.87 and 0.94 at a depth of 20cm. and between 0.80 and 0.98 at 50cm. Thus, despite the simplifications made, the model was able to simulate soil temperature at these study sites. This simple model simulates soil temperature well in the uppermost soil layers where most of the nitrogen processes occur. The small number of parameters required means, that the model is suitable for addition to catchment scale models.

Improved arthritic knee health in a pilot RCT of phytotherapy

Although practitioner-prescribed 'western' herbal medicine (phytotherapy) is a popular complementary therapy in the UK, no clinical studies have been reported on patient-orientated outcomes. The objective of this pilot study was to investigate the effects of phytotherapy on symptoms of osteoarthritis of the knee. A previous study of Chinese herbal medicine for the treatment of irritable bowel syndrome, published in the Journal of the American Medical Association,(1) acted as a model in the development of the protocol of this investigation. Twenty adults, previously diagnosed with osteoarthritis of the knee, were recruited from two Inner London GP practices into this randomized, double-blind, placebo-controlled, pilot study carried out in a primary-care setting. All subjects were seen in consultation three times by a herbal practitioner who was blinded to the randomization coding. Each subject was prescribed treatment and given lifestyle advice according to usual practice: continuation of conventional medication where applicable, healthy-eating advice and nutrient supplementation, Individualized herbal medicine was prescribed for each patient, but only dispensed for those randomized to active treatment - the remainder were supplied with a placebo. At baseline and outcome (after ten weeks of treatment), subjects completed a food frequency questionnaire and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) knee health and Measure Yourself Outcome Profile (MYMOP) wellbeing questionnaires. Subjects completing the study per protocol (n = 14) reported an increased intake of wholegrain foods (p = 0.045) and oily fish (p = 0.039) compared to baseline, but no increase in fruit and vegetables and dairy products intakes. There was no difference in the primary outcome measure of knee health assessed as the difference in the mean response (baseline-week 10) in WOMAC score between the two treatment groups. However, there was, compared with baseline, improvement in the active group (n = 9) for the mean WOMAC stiffness sub-score at week 5 (p = 0.035) and week 10 (p = 0.060) but not in the placebo group (n = 5). Furthermore, for the active, but not the placebo group, the mean WOMAC total and sub-scores all showed clinically significant improvement (>= 20%) in knee symptoms at weeks 5 and 10 compared with baseline. Moreover, the mean MYMOP symptom 2 sub-score, mostly relating to osteoarthritis (OA), showed significant improvement at week 5 (p = 0.02) and week 10 (p = 0.008) compared with baseline for the active, but not for the placebo group. This pilot study showed that herbal medicine prescribed for the individual by a herbal practitioner resulted in improvement of symptoms of OA of the knee.

Interpretation of ambiguity in children: a prospective study of associations with anxiety and parental interpretations

Interpretation of ambiguity is consistently associated with anxiety in children, however, the temporal relationship between interpretation and anxiety remains unclear as do the developmental origins of interpretative biases. This study set out to test a model of the development of interpretative biases in a prospective study of 110 children aged 5–9 years of age. Children and their parents were assessed three times, annually, on measures of anxiety and interpretation of ambiguous scenarios (including, for parents, both their own interpretations and their expectations regarding their child). Three models were constructed to assess associations between parent and child anxiety and threat and distress cognitions and expectancies. The three models were all a reasonable fit of the data, and supported conclusions that: (i) children’s threat and distress cognitions were stable over time and were significantly associated with anxiety, (ii) parents’ threat and distress cognitions and expectancies significantly predicted child threat cognitions at some time points, and (iii) parental anxiety significantly predicted parents cognitions, which predicted parental expectancies at some time points. Parental expectancies were also significantly predicted by child cognitions. The findings varied depending on assessment time point and whether threat or distress cognitions were being considered. The findings support the notion that child and parent cognitive processes, in particular parental expectations, may be a useful target in the treatment or prevention of anxiety disorders in children.

Global climate change and soil carbon stocks: predictions from two contrasting models for the turnover of organic carbon in soil

Enhanced release of CO2 to the atmosphere from soil organic carbon as a result of increased temperatures may lead to a positive feedback between climate change and the carbon cycle, resulting in much higher CO2 levels and accelerated lobal warming. However, the magnitude of this effect is uncertain and critically dependent on how the decomposition of soil organic C (heterotrophic respiration) responds to changes in climate. Previous studies with the Hadley Centre’s coupled climate–carbon cycle general circulation model (GCM) (HadCM3LC) used a simple, single-pool soil carbon model to simulate the response. Here we present results from numerical simulations that use the more sophisticated ‘RothC’ multipool soil carbon model, driven with the same climate data. The results show strong similarities in the behaviour of the two models, although RothC tends to simulate slightly smaller changes in global soil carbon stocks for the same forcing. RothC simulates global soil carbon stocks decreasing by 54 GtC by 2100 in a climate change simulation compared with an 80 GtC decrease in HadCM3LC. The multipool carbon dynamics of RothC cause it to exhibit a slower magnitude of transient response to both increased organic carbon inputs and changes in climate. We conclude that the projection of a positive feedback between climate and carbon cycle is robust, but the magnitude of the feedback is dependent on the structure of the soil carbon model.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: using AMIP runs to understand the heat flux feedback mechanisms

Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (μ) and the heat flux negative feedback (α), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback, μ, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of α in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback, α SW, are the main source of model uncertainty in α. Most models do not successfully represent the negative αSW in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled α SW biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect α SW. We further show that the negative latent heat flux feedback, α LH, exhibits less diversity than α SW and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model αLH differences.

Spatio-temporal dependencies in functional connectivity in rodent cortical cultures

Models of functional connectivity in cortical cultures on multi-electrodes arrays may aid in understanding how cognitive pathways form and improve techniques that aim to interface with neuronal systems. To enable research on such models, this study uses both data- and model-driven approaches to determine what dependencies are present in and between functional connectivity networks derived from bursts of extracellularly recorded activity. Properties of excitation in bursts were analysed using correlative techniques to assess the degree of linear dependence and then two parallel techniques were used to assess functional connectivity. Three models presenting increasing levels of spatio-temporal dependency were used to capture the dynamics of individual functional connections and their consistencies were verified using surrogate data. By comparing network-wide properties between model generated networks and functional networks from data, complex interdependencies were revealed. This indicates the persistent co-activation of neuronal pathways in spontaneous bursts, as can be found in whole brain structures.

The middle-atmosphere Hadley circulation and equatorial inertial adjustment

In the tropical middle atmosphere the climatological radiative equilibrium temperature is inconsistent with gradient-wind balance and the available angular momentum, especially during solstice seasons. Adjustment toward a balanced state results in a type of Hadley circulation that lies outside the “downward control” view of zonally averaged dynamics. This middle-atmosphere Hadley circulation is reexamined here using a zonally symmetric balance model driven through an annual cycle. It is found that the inclusion of a realistic radiation scheme leads to a concentration of the circulation near the stratopause and to its closing off in the mesosphere, with no need for relaxational damping or a rigid lid. The evolving zonal flow is inertially unstable, leading to a rapid process of inertial adjustment, which becomes significant in the mesosphere. This short-circuits the slower process of angular momentum homogenization by the Hadley circulation itself, thereby weakening the latter. The effect of the meridional circulation associated with extratropical wave drag on the Hadley circulation is considered. It is shown that the two circulations are independent for linear (quasigeostrophic) zonal-mean dynamics, and interact primarily through the advection of temperature and angular momentum. There appears to be no significant coupling in the deep Tropics via temperature advection since the wave-driven circulation is unable to alter meridional temperature gradients in this region. However, the wave-driven circulation can affect the Hadley circulation by advecting angular momentum out of the Tropics. The validity of the zonally symmetric balance model with parameterized inertial adjustment is tested by comparison with a three-dimensional primitive equations model. Fields from a middle-atmosphere GCM are also examined for evidence of these processes. While many aspects of the GCM circulation are indicative of the middle-atmosphere Hadley circulation, particularly in the upper stratosphere, it appears that the circulation is obscured in the mesosphere and lower stratosphere by other processes.

GM crops, developing countries and food security

The agronomic and economic performance of genetically modified (GM) crops relative to their conventional counterparts has been largely investigated worldwide. As a result there is considerable information to conduct a meta-analysis to evaluate the agronomic and economic relative performance of GM crops vs. non GM crops by crop, GM trait, and country’s level of development. Such meta-analysis has been recently conducted showing that overall GM crops outperform non GM crops in both agronomic and economic terms (1). This paper focuses on the agronomic and economic performance of GM crops in developing and developed countries as well as the potential implications for global food security of adoption of GM crops by developing countries. The presumption that technology only benefits the developed world is not supported by the meta-analysis conducted. No evidence that GM technology benefits moredeveloped than developing countries was found. Indeed, the agronomic and economic performance of GM crops vs. conventional crops tends to be better for developing than for developed countries. Although it is manifested that the conventional agronomic practices in developing countries are different to those in developed countries, it is also apparent that GM crop adoption in developing countries may help to tackle the growing concerns over the scarcity of food globally.

Parenting difficulties and postnatal depression: implications for primary healthcare assessment and intervention

Postnatal depression (PND) is associated with impairments in the mother–child relationship, and these impairments are themselves associated with adverse child outcomes. Thus, compared to the children of non-depressed mothers, children of mothers with PND are more likely to be insecurely attached, and to have externalising behaviour problems and poor cognitive development. Each of these three child outcomes is predicted by a particular pattern of difficulty in parenting: insecure attachment is related to maternal insensitivity, particularly in relation to infant distress and emotional vulnerability; externalising problems are particularly common in the context of hostile parenting; and poor cognitive development is related to parental difficulties in noticing infant signs of interest and supporting their engagement with the environment. This article sets out procedures for how parenting could be assessed in ways that are sensitive to the domain-specific associations between parenting and child outcome, while remaining sensitive to the child's developmental stage. This set of assessments requires field testing.

ERA-Interim/Land: a global land surface reanalysis data set

ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

Review of monitoring tools for e-learning platforms

The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The Learning Management System (LMS) is the core of the entire e-learning process along with technology, content, and services. This paper investigates the role of model-driven personalisation support modalities in providing enhanced levels of learning and trusted assimilation in an e-learning delivery context. We present an analysis of the impact of an integrated learning path that an e-learning system may employ to track activities and evaluate the performance of learners.

Recent lake-level and outflow variations at Lake Viljandi, Estonia: validation of a coupled lake-catchment modelling scheme for climate change studies

Changes in the depth of Lake Viljandi between 1940 and 1990 were simulated using a lake water and energy-balance model driven by standard monthly weather data. Catchment runoff was simulated using a one-dimensional hydrological model, with a two-layer soil, a single-layer snowpack, a simple representation of vegetation cover and similarly modest input requirements. Outflow was modelled as a function of lake level. The simulated record of lake level and outflow matched observations of lake-level variations (r = 0.78) and streamflow (r = 0.87) well. The ability of the model to capture both intra- and inter-annual variations in the behaviour of a specific lake, despite the relatively simple input requirements, makes it extremely suitable for investigations of the impacts of climate change on lake water balance.