Application of data assimilation to ocean and climate prediction

Ocean prediction systems are now able to analyse and predict temperature, salinity and velocity structures within the ocean by assimilating measurements of the ocean’s temperature and salinity into physically based ocean models. Data assimilation combines current estimates of state variables, such as temperature and salinity, from a computational model with measurements of the ocean and atmosphere in order to improve forecasts and reduce uncertainty in the forecast accuracy. Data assimilation generally works well with ocean models away from the equator but has been found to induce vigorous and unrealistic overturning circulations near the equator. A pressure correction method was developed at the University of Reading and the Met Office to control these circulations using ideas from control theory and an understanding of equatorial dynamics. The method has been used for the last 10 years in seasonal forecasting and ocean prediction systems at the Met Office and European Center for Medium-range Weather Forecasting (ECMWF). It has been an important element in recent re-analyses of the ocean heat uptake that mitigates climate change.

Steric sea level variability (1993-2010) in an ensemble of ocean reanalyses and objective analyses

Quantifying the effect of the seawater density changes on sea level variability is of crucial importance for climate change studies, as the sea level cumulative rise can be regarded as both an important climate change indicator and a possible danger for human activities in coastal areas. In this work, as part of the Ocean Reanalysis Intercomparison Project, the global and regional steric sea level changes are estimated and compared from an ensemble of 16 ocean reanalyses and 4 objective analyses. These estimates are initially compared with a satellite-derived (altimetry minus gravimetry) dataset for a short period (2003–2010). The ensemble mean exhibits a significant high correlation at both global and regional scale, and the ensemble of ocean reanalyses outperforms that of objective analyses, in particular in the Southern Ocean. The reanalysis ensemble mean thus represents a valuable tool for further analyses, although large uncertainties remain for the inter-annual trends. Within the extended intercomparison period that spans the altimetry era (1993–2010), we find that the ensemble of reanalyses and objective analyses are in good agreement, and both detect a trend of the global steric sea level of 1.0 and 1.1 ± 0.05 mm/year, respectively. However, the spread among the products of the halosteric component trend exceeds the mean trend itself, questioning the reliability of its estimate. This is related to the scarcity of salinity observations before the Argo era. Furthermore, the impact of deep ocean layers is non-negligible on the steric sea level variability (22 and 12 % for the layers below 700 and 1500 m of depth, respectively), although the small deep ocean trends are not significant with respect to the products spread.

Commentary: not just genes - reclaiming a role for environmental influences on aetiology and outcome in autism. A commentary on Mandy and Lai (2016)

Mandy and Lai (2015) do the field a service in 'reclaiming' the role of pre- and postnatal environmental influences on the aetiology and course of autism spectrum conditions (ASC). This follows several decades where now discredited theories about putative psychogenic and biological disease models held sway, not least in the public mind. We discuss issues that arise from their review; including the need to identify how large the environmental influences on ASC are likely to be; the specificity of these environmental influences to ASC as opposed to a broader range of neurodevelopmental conditions and outcomes; how best to study complex interactions between genetic and environmental influences; and the promise of novel insights into their mechanisms of action. The review highlights current research that aims to better our understanding of the role of environmental factors in the aetiology and course of ASC and, in the near future, may offer the potential for personalised medicine approaches to intervention based on these discoveries.

Cambium non est mutuum: exchange and interest rates in medieval Europe

A major gap in our understanding of the medieval economy concerns interest rates, especially relating to commercial credit. Although direct evidence about interest rates is scattered and anecdotal, there is much more surviving information about exchange rates. Since both contemporaries and historians have suggested that exchange and rechange transactions could be used to disguise the charging of interest in order to circumvent the usury prohibition, it should be possible to back out the interest rates from exchange rates. The following analysis is based on a new dataset of medieval exchange rates collected from commercial correspondence in the archive of Francesco di Marco Datini of Prato, c.1383-1411. It demonstrates that the time value of money was consistently incorporated into market exchange rates. Moreover, these implicit interest rates are broadly comparable to those received from other types of commercial loan and investment. Although on average profitable, the return on any individual exchange and rechange transaction did involve a degree of uncertainty that may have justified their non-usurious nature. However, there were also practical reasons why medieval merchants may have used foreign exchange transactions as a means of extending credit.

Production of bioactive diterpenoids in the Euphorbiaceae depends on evolutionarily conserved gene clusters

The Euphorbiaceae produce a diverse range of diterpenoids, many of which have pharmacological activities. These diterpenoids include ingenol mebutate, which is licensed for the treatment of a precancerous skin condition (actinic keratosis), and phorbol derivatives such as resiniferatoxin and prostratin, which are undergoing investigation for the treatment of severe pain and HIV, respectively. Despite the interest in these diterpenoids, their biosynthesis is poorly understood at present, with the only characterized step being the conversion of geranylgeranyl pyrophosphate into casbene. Here, we report a physical cluster of diterpenoid biosynthetic genes from castor (Ricinus communis), including casbene synthases and cytochrome P450s from the CYP726A subfamily. CYP726A14, CYP726A17, and CYP726A18 were able to catalyze 5-oxidation of casbene, a conserved oxidation step in the biosynthesis of this family of medicinally important diterpenoids. CYP726A16 catalyzed 7,8-epoxidation of 5-keto-casbene and CYP726A15 catalyzed 5-oxidation of neocembrene. Evidence of similar gene clustering was also found in two other Euphorbiaceae, including Euphorbia peplus, the source organism of ingenol mebutate. These results demonstrate conservation of gene clusters at the higher taxonomic level of the plant family and that this phenomenon could prove useful in further elucidating diterpenoid biosynthetic pathways.

Reducing defects through organizational learning within a Housing Association environment

Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Detecting defects in the UK new-build housing sector: a learning perspective

Rapid growth in the production of new homes in the UK is putting build quality under pressure as evidenced by an increase in the number of defects. Housing associations (HAs) contribute approximately 20% of the UK’s new housing supply. HAs are currently experiencing central government funding cuts and rental revenue reductions. As part of HAs’ quest to ramp up supply despite tight budget conditions, they are reviewing how they learn from defects. Learning from defects is argued as a means of reducing the persistent defect problem within the UK housebuilding industry, yet how HAs learn from defects is under-researched. The aim of this research is to better understand how HAs, in practice, learn from past defects to reduce the prevalence of defects in future new homes. The theoretical lens for this research is organizational learning. The results drawn from 12 HA case studies indicate that effective organizational learning has the potential to reduce defects within the housing sector. The results further identify that HAs are restricting their learning to focus primarily on reducing defects through product and system adaptations. Focusing on product and system adaptations alone suppresses HAs’ abilities to reduce defects in the future.