Objective detection of sting jets in low-resolution datasets

Sting jets are transient coherent mesoscale strong wind features that can cause damaging surface wind gusts in extratropical cyclones. Currently, we have only limited knowledge of their climatological characteristics. Numerical weather prediction models require enough resolution to represent slantwise motions with horizontal scales of tens of kilometres and vertical scales of just a few hundred metres to represent sting jets. Hence, the climatological characteristics of sting jets and the associated extratropical cyclones can not be determined by searching for sting jets in low-resolution datasets such as reanalyses. A diagnostic is presented and evaluated for the detection in low-resolution datasets of atmospheric regions from which sting jets may originate. Previous studies have shown that conditional symmetric instability (CSI) is present in all storms studied with sting jets, while other, rapidly developing storms of a similar character but no CSI do not develop sting jets. Therefore, we assume that the release of CSI is needed for sting jets to develop. While this instability will not be released in a physically realistic way in low-resolution models (and hence sting jets are unlikely to occur), it is hypothesized that the signature of this instability (combined with other criteria that restrict analysis to moist mid-tropospheric regions in the neighbourhood of a secondary cold front) can be used to identify cyclones in which sting jets occurred in reality. The diagnostic is evaluated, and appropriate parameter thresholds defined, by applying it to three case studies simulated using two resolutions (with CSI-release resolved in only the higher-resolution simulation).

Provider diversity in the NHS: impact on quality and innovation

The overall objective of the research project has been to assess the impact of provider diversity on quality and innovation in the NHS. The specific research aims were to identify the differences in performance between non-profit Third Sector organisations, for-profit private enterprises, and incumbent public sector institutions within the NHS as providers of health care services, as well as the factors that affect the entry and growth of new private and Third Sector providers. The study used both qualitative and quantitative methods based on case studies of four Local Health Economies (LHEs). Qualitative methods included documentary analysis and interviews with key informants and managers of both commissioning and provider organisations. To provide a focus to the study, two tracer conditions were followed: orthopaedic surgery and home health care for frail older people. In the case of hospital inpatient care, data on patient characteristics were also collected from the HES database. The analysis of this data provided preliminary estimates of the effects of provider type on quality, controlling for client characteristics and case mix. In addition, a survey of patient experience in diverse provider organisations was analysed to compare the different dimensions of quality of provision of acute services between incumbent NHS organisations and new independent sector treatment centres. The research has shown that, in respect of inpatient hospital services, diverse providers supply health services of at least as good quality as traditional NHS providers, and that there is ample opportunity to expand their scale and scope as providers of services commissioned by the NHS. The research used patient experience survey data to investigate whether hospital ownership affects the quality of services reported by NHS patients in areas other than clinical quality. The raw survey data appear to show that private hospitals provide higher quality services than the public hospitals. However, further empirical analysis leads to a more nuanced understanding of the performance differences. Firstly, the analysis shows that each sector offers greater quality in certain specialties. Secondly, the analysis shows that differences in the quality of patients’ reported experience are mainly attributable to patient characteristics, the selection of patients into each type of hospital, and the characteristics of individual hospitals, rather than to hospital ownership as such. Controlling for such differences, NHS patients are on average likely to experience a similar quality of care in a public or privately-run hospital. Nevertheless, for specific groups of patients and for specific types of treatments, especially the more straightforward ones, the private sector provides an improved patient experience compared to the public sector. Elsewhere, the NHS continues to provide a high quality service and outperforms the private sector in a range of services and for a range of clients.

Citation and peer review of data: moving towards formal data publication

This paper discusses many of the issues associated with formally publishing data in academia, focusing primarily on the structures that need to be put in place for peer review and formal citation of datasets. Data publication is becoming increasingly important to the scientific community, as it will provide a mechanism for those who create data to receive academic credit for their work and will allow the conclusions arising from an analysis to be more readily verifiable, thus promoting transparency in the scientific process. Peer review of data will also provide a mechanism for ensuring the quality of datasets, and we provide suggestions on the types of activities one expects to see in the peer review of data. A simple taxonomy of data publication methodologies is presented and evaluated, and the paper concludes with a discussion of dataset granularity, transience and semantics, along with a recommended human-readable citation syntax.

Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

The Along-Track Scanning Radiometers (ATSRs) provide a long time-series of measurements suitable for the retrieval of cloud properties. This work evaluates the freely-available Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) dataset (version 3) created from the ATSR-2 (1995�2003) and Advanced ATSR (AATSR; 2002 onwards) records. Users are recommended to consider only retrievals flagged as high-quality, where there is a good consistency between the measurements and the retrieved state (corresponding to about 60% of converged retrievals over sea, and more than 80% over land). Cloud properties are found to be generally free of any significant spurious trends relating to satellite zenith angle. Estimates of the random error on retrieved cloud properties are suggested to be generally appropriate for optically-thick clouds, and up to a factor of two too small for optically-thin cases. The correspondence between ATSR-2 and AATSR cloud properties is high, but a relative calibration difference between the sensors of order 5�10% at 660 nm and 870 nm limits the potential of the current version of the dataset for trend analysis. As ATSR-2 is thought to have the better absolute calibration, the discussion focusses on this portion of the record. Cloud-top heights from GRAPE compare well to ground-based data at four sites, particularly for shallow clouds. Clouds forming in boundary-layer inversions are typically around 1 km too high in GRAPE due to poorly-resolved inversions in the modelled temperature profiles used. Global cloud fields are compared to satellite products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements, and a climatology of liquid water content derived from satellite microwave radiometers. In all cases the main reasons for differences are linked to differing sensitivity to, and treatment of, multi-layer cloud systems. The correlation coefficient between GRAPE and the two MODIS products considered is generally high (greater than 0.7 for most cloud properties), except for liquid and ice cloud effective radius, which also show biases between the datasets. For liquid clouds, part of the difference is linked to choice of wavelengths used in the retrieval. Total cloud cover is slightly lower in GRAPE (0.64) than the CALIOP dataset (0.66). GRAPE underestimates liquid cloud water path relative to microwave radiometers by up to 100 g m�2 near the Equator and overestimates by around 50 g m�2 in the storm tracks. Finally, potential future improvements to the algorithm are outlined.

Do designers show categorical perception of typefaces?

Readers need to easily discriminate between different letters, so typefaces are designed to make these differences distinctive. But there is also a uniformity of style within a typeface. These styles are recognised by typographic designers and may be categorised to enable more efficient discrimination among typefaces. The manner in which designers perceive typefaces is explored using the paradigm of Categorical Perception (CP). A continuum of fonts is created by interpolating between two typefaces and two tasks (identification and discrimination) are used to test for CP. As the application of CP to typefaces is a new approach, various methodological issues are pursued. The experiments reveal that the conditions required to demonstrate CP are quite specific and CP was only evident in Times and Helvetica and not Garamond and Bodoni. Possible reasons for this difference are the characteristics of the two typefaces and their context of use. Speculation as to the purpose of CP in non-designers raises the under-researched question of how we identify letters in different typefaces when reading.

The precipitation climate of Central Asia: intercomparison of observational and numerical data sources in a remote semiarid region

In this study, we systematically compare a wide range of observational and numerical precipitation datasets for Central Asia. Data considered include two re-analyses, three datasets based on direct observations, and the output of a regional climate model simulation driven by a global re-analysis. These are validated and intercompared with respect to their ability to represent the Central Asian precipitation climate. In each of the datasets, we consider the mean spatial distribution and the seasonal cycle of precipitation, the amplitude of interannual variability, the representation of individual yearly anomalies, the precipitation sensitivity (i.e. the response to wet and dry conditions), and the temporal homogeneity of precipitation. Additionally, we carried out part of these analyses for datasets available in real time. The mutual agreement between the observations is used as an indication of how far these data can be used for validating precipitation data from other sources. In particular, we show that the observations usually agree qualitatively on anomalies in individual years while it is not always possible to use them for the quantitative validation of the amplitude of interannual variability. The regional climate model is capable of improving the spatial distribution of precipitation. At the same time, it strongly underestimates summer precipitation and its variability, while interannual variations are well represented during the other seasons, in particular in the Central Asian mountains during winter and spring

Early warning with calibrated and sharper probabilistic forecasts

Given a nonlinear model, a probabilistic forecast may be obtained by Monte Carlo simulations. At a given forecast horizon, Monte Carlo simulations yield sets of discrete forecasts, which can be converted to density forecasts. The resulting density forecasts will inevitably be downgraded by model mis-specification. In order to enhance the quality of the density forecasts, one can mix them with the unconditional density. This paper examines the value of combining conditional density forecasts with the unconditional density. The findings have positive implications for issuing early warnings in different disciplines including economics and meteorology, but UK inflation forecasts are considered as an example.

Diaspora return of transnational migrants to Trinidad and Tobago: the additional contributions of social remittances

Current enthusiasm among development stakeholders for the enticement and recruitment ‘back home’ of skilled Diaspora migrants has predominantly revolved around how human capital gains and transfers of capital, knowledge, technical skills and workplace entrepreneurialism and innovation can be facilitated. In this article, we widen the conceptual basis of this dimension of the migration–development nexus, by bringing the additional contributions of the social remittances that return migrants offer, and practice, into the mix. As evidence, the article examines how and why a sample of ‘middling’1 Trinidadian transnational professionals engage in social development activities and why experiences vary widely on their return. Their views are appraised through the verbal optic of their narratives, which they shared with us during in-depth interviews. Several among these Diaspora returnees appear to be agents for the diffusion and infusion of social capital and non-monetary, social remittances in the homeland to which they have returned in mid-life and mid-career. Others are disappointed, or frustrated, and have their hopes dashed, leading to thoughts of re-migration, or re-return. Despite such difficulties, we find that family belonging and national pride strengthens many of these return migrants’ development potential through their deeply felt commitments to local ‘capacity-building’.

The causes and effects of depreciation in office buildings: a ten year update

This paper publishes the results of the 1996 study, which repeats a cross-section analysis of around 125 City of London office buildings, and examines the longitudinal data contributed by a sample of 56 unrefurbished properties common to the 1986 and 1996 City of London datasets. An estimate of the average rate of rental and capital value depreciation is made; the effect of age is shown not to be straight-line; and the causes if depreciation are measured. The results are compared with the 1986 City of London findings.

Assessing and understanding the impact of stratospheric dynamics and variability on the earth system

Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.

Carbon and nitrogen stable isotope ratio analysis of freshwater, brackish and marine fish from Belgian archaeological sites (1st and 2nd millennium AD)

Carbon and nitrogen stable isotope ratios were measured in 157 fish bone collagen samples from 15 different archaeological sites in Belgium which ranged in ages from the 3rd to the 18th c. AD. Due to diagenetic contamination of the burial environment, only 63 specimens produced results with suitable C:N ratios (2.9–3.6). The selected bones encompass a wide spectrum of freshwater, brackish, and marine taxa (N = 18), and this is reflected in the δ13C results (−28.2‰ to −12.9%). The freshwater fish have δ13C values that range from −28.2‰ to −20.2‰, while the marine fish cluster between −15.4‰ and −13.0‰. Eel, a catadromous species (mostly living in freshwater but migrating into the sea to spawn), plots between −24.1‰ and −17.7‰, and the anadromous fish (living in marine environments but migrating into freshwater to spawn) show a mix of freshwater and marine isotopic signatures. The δ15N results also have a large range (7.2‰ to 16.7‰) indicating that these fish were feeding at many different trophic levels in these diverse aquatic environments. The aim of this research is the isotopic characterization of archaeological fish species (ecology, trophic level, migration patterns) and to determine intra-species variation within and between fish populations differing in time and location. Due to the previous lack of archaeological fish isotope data from Northern Europe and Belgium in particular, these results serve as an important ecological backdrop for the future isotopic reconstruction of the diet of human populations dating from the historical period (1st and 2nd millennium AD), where there is zooarchaeological and historical evidence for an increased consumption of marine fish.

Co-variation of temperature and precipitation in CMIP5 models and satellite observations

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled(CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates. There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5 simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 %/K for simulations and 3-4 %/K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Niño Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (75% precipitation percentile), the precipitation response is ~13-15%/K for GPCP and ~5%/K for models while trends in P are 2.4%/decade for GPCP, 0.6% /decade for CMIP5 and 0.9%/decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

Root phenomics of crops: opportunities and challenges

Reliable techniques for screening large numbers of plants for root traits are still being developed, but include aeroponic, hydroponic and agar plate systems. Coupled with digital cameras and image analysis software, these systems permit the rapid measurement of root numbers, length and diameter in moderate ( typically <1000) numbers of plants. Usually such systems are employed with relatively small seedlings, and information is recorded in 2D. Recent developments in X-ray microtomography have facilitated 3D non-invasive measurement of small root systems grown in solid media, allowing angular distributions to be obtained in addition to numbers and length. However, because of the time taken to scan samples, only a small number can be screened (typically<10 per day, not including analysis time of the large spatial datasets generated) and, depending on sample size, limited resolution may mean that fine roots remain unresolved. Although agar plates allow differences between lines and genotypes to be discerned in young seedlings, the rank order may not be the same when the same materials are grown in solid media. For example, root length of dwarfing wheat ( Triticum aestivum L.) lines grown on agar plates was increased by similar to 40% relative to wild-type and semi-dwarfing lines, but in a sandy loam soil under well watered conditions it was decreased by 24-33%. Such differences in ranking suggest that significant soil environment-genotype interactions are occurring. Developments in instruments and software mean that a combination of high-throughput simple screens and more in-depth examination of root-soil interactions is becoming viable.

On reliability analysis of multi-categorical forecasts

Reliability analysis of probabilistic forecasts, in particular through the rank histogram or Talagrand diagram, is revisited. Two shortcomings are pointed out: Firstly, a uniform rank histogram is but a necessary condition for reliability. Secondly, if the forecast is assumed to be reliable, an indication is needed how far a histogram is expected to deviate from uniformity merely due to randomness. Concerning the first shortcoming, it is suggested that forecasts be grouped or stratified along suitable criteria, and that reliability is analyzed individually for each forecast stratum. A reliable forecast should have uniform histograms for all individual forecast strata, not only for all forecasts as a whole. As to the second shortcoming, instead of the observed frequencies, the probability of the observed frequency is plotted, providing and indication of the likelihood of the result under the hypothesis that the forecast is reliable. Furthermore, a Goodness-Of-Fit statistic is discussed which is essentially the reliability term of the Ignorance score. The discussed tools are applied to medium range forecasts for 2 m-temperature anomalies at several locations and lead times. The forecasts are stratified along the expected ranked probability score. Those forecasts which feature a high expected score turn out to be particularly unreliable.

Crossbred cow adoption and milk market participation in a multivariate count data framework

Cross-bred cow adoption is an important and potent policy variable precipitating subsistence household entry into emerging milk markets. This paper focuses on the problem of designing policies that encourage and sustain milkmarket expansion among a sample of subsistence households in the Ethiopian highlands. In this context it is desirable to measure households’ ‘proximity’ to market in terms of the level of deficiency of essential inputs. This problem is compounded by four factors. One is the existence of cross-bred cow numbers (count data) as an important, endogenous decision by the household; second is the lack of a multivariate generalization of the Poisson regression model; third is the censored nature of the milk sales data (sales from non-participating households are, essentially, censored at zero); and fourth is an important simultaneity that exists between the decision to adopt a cross-bred cow, the decision about how much milk to produce, the decision about how much milk to consume and the decision to market that milk which is produced but not consumed internally by the household. Routine application of Gibbs sampling and data augmentation overcome these problems in a relatively straightforward manner. We model the count data from two sites close to Addis Ababa in a latent, categorical-variable setting with known bin boundaries. The single-equation model is then extended to a multivariate system that accommodates the covariance between crossbred-cow adoption, milk-output, and milk-sales equations. The latent-variable procedure proves tractable in extension to the multivariate setting and provides important information for policy formation in emerging-market settings