The FERRUM project: laboratory-measured transition probabilities for Cr II

Aims: We measure transition probabilities for Cr II transitions from the z ^4H_J, z ^2D_J, y ^4F_J, and y ^4G_J levels in the energy range 63000 to 68000 cm^{-1}. Methods: Radiative lifetimes were measured using time-resolved laser-induced fluorescence from a laser-produced plasma. In addition, branching fractions were determined from intensity-calibrated spectra recorded with a UV Fourier transform spectrometer. The branching fractions and radiative lifetimes were combined to yield accurate transition probabilities and oscillator strengths. Results: We present laboratory measured transition probabilities for 145 Cr II lines and radiative lifetimes for 14 Cr II levels. The laboratory-measured transition probabilities are compared to the values from semi-empirical calculations and laboratory measurements in the literature.Comment: 13 pages. Accepted for publication in A&

Estimation and evaluation of high-resolution soil moisture from merged model and Earth observation data in the Great Britain

Soil moisture is an important component of the Earth system and plays a key role in land-atmosphere interactions. Remote sensing of soil moisture is of great scientific interest and the scientific community has made significant progress in soil moisture estimation using Earth observations. Currently, several satellite-based coarse spatial resolution soil moisture datasets have been produced and widely used for various applications in climate science, hydrology, ecosystem research and agriculture. Owing to the strong demand for soil moisture data with high spatial resolution for regional applications, much effort has recently been devoted to the generation of high spatial resolution soil moisture data from either high-resolution satellite observations or by downscaling existing coarse-resolution satellite-based soil moisture datasets. In addition, land surface models provide an alternative way to obtain consistent high-resolution soil moisture information when forced with high-resolution inputs. The aim of this study is to create and evaluate high-resolution soil moisture products derived from multiple sources including satellite observations and land surface model simulations. The JULES-CHESS simulated soil moisture and satellite-based soil moisture datasets including SMAP L3E, SMAP L4, SMOS L4, Sentinel 1, ASCAT, and Sentinel 1/SMAP combined products were first validated against observed soil moisture from COSMOS-UK, a network of in-situ cosmic-ray based sensors. Second, an approach based on triple collocation was applied to compare these satellite products in the absence of a known reference dataset. Third, a combined soil moisture product was generated to integrate the better-performing soil moisture estimates based on triple collocation error estimation and a least-squares merging scheme. From further evaluation, it is found that the merged soil moisture integrates the characteristics of model simulation and satellite observations and particularly improves the limited temporal variability of the JULES-CHESS simulation. Therefore, we conclude that the triple collocation merging scheme is a simple and reliable way to combine satellite-based soil moisture products with outputs from the JULES-CHESS simulation for estimating model-data fused high-resolution soil moisture for the British mainland

A framework for improved predictions of the climate impacts on potential yields of UK winter wheat and its applicability to other UK crops

•Changes in the frequency of extreme weather events related to climate change potentially pose significant challenges to UK agricultural production. There is a need for improved climate change risk assessments to support adaptation strategies and to ensure security of food production in future. •We describe an innovative and practical framework for spatially explicit modelling of climate change impacts on crop yields, based on the UKCP18 climate projections. Our approach allows the integration of relatively simple crop growth models with high spatial and temporal resolution Earth Observation datasets, describing changes in crop growth parameters within year and over the longer term. We focus on modelling winter wheat, a commercially important crop. We evaluate the results of the model against precision yield data collected from 719 fields. We show that the assimilation of leaf area index data from Sentinel-2 satellite observations improves the agreement of the modelled yields with those observed. Our national-scale results indicate that wheat production initially becomes more favourable under climate change across much of the UK with the projected increase in temperature. From 2050 onwards, yields increase northwards, whilst they decline in South East England as the decrease in precipitation offsets the benefits of rising temperature. •Our framework can readily accommodate growth models for other crops and LAI retrievals from other satellite sensors. The ability to explore impacts of crop yields at fine spatial resolutions is an important part of assessing the potential risks of climate change to UK agriculture and of designing more climate resilient agricultural systems

A qualitative examination of inappropriate hospital admissions and lengths of stay

<p>Abstract</p> <p>Background</p> <p>Research has shown that a number of patients, with a variety of diagnoses, are admitted to hospital when it is not essential and can remain in hospital unnecessarily. To date, research in this area has been primarily quantitative. The purpose of this study was to explore the perceived causes of inappropriate or prolonged lengths of stay and focuses on a specific population (i.e., patients with long term neurological conditions). We also wanted to identify interventions which might avoid admission or expedite discharge as periods of hospitalisation pose particular risks for this group.</p> <p>Methods</p> <p>Two focus groups were conducted with a convenience sample of eight primary and secondary care clinicians working in the Derbyshire area. Data were analysed using a thematic content approach.</p> <p>Results</p> <p>The participants identified a number of key causes of inappropriate admissions and lengths of stay, including: the limited capacity of health and social care resources; poor communication between primary and secondary care clinicians and the cautiousness of clinicians who manage patients in community settings. The participants also suggested a number of strategies that may prevent inappropriate admissions or reduce length of stay (LoS), including: the introduction of new sub-acute care facilities; the introduction of auxiliary nurses to support specialist nursing staff and patient held summaries of specialist consultations.</p> <p>Conclusion</p> <p>Clinicians in both the secondary and primary care sectors acknowledged that some admissions were unnecessary and some patients remain in hospital for a prolonged period. These events were attributed to problems with the current capacity or structuring of services. It was noted, for example, that there is a shortage of appropriate therapeutic services and that the distribution of beds between community and sub-acute care should be reviewed.</p

The accuracy of stellar atmospheric parameter determinations: a case study with HD 32115 and HD 37594

We present detailed parameter determinations of two chemically normal late A-type stars, HD 32115 and HD 37594, to uncover the reasons behind large discrepancies between two previous analyses of these stars performed with a semi-automatic procedure and a "classical" analysis. Our study is based on high resolution, high signal-to-noise spectra obtained at the McDonald Observatory. Our method is based on the simultaneous use of all available observables: multicolor photometry, pressure-sensitive magnesium lines, metallic lines and Balmer line profiles. Our final set of fundamental parameters fits, within the error bars, all available observables. It differs from the published results obtained with a semi-automatic procedure. A direct comparison between our new observational material and the spectra previously used by other authors shows that the quality of the data is not the origin of the discrepancies. As the two stars require a substantial macroturbulence velocity to fit the line profiles, we concluded that neglecting this additional broadening in the semi-automatic analysis is one origin of discrepancy. The use of FeI excitation equilibrium and of the Fe ionisation equilibrium, to derive effective temperature and surface gravity, respectively, neglecting all other indicators leads to a systematically erroneously high effective temperature. We deduce that the results obtained using only one parameter indicator might be biased and that those results need to be cautiously taken when performing further detailed analyses, such as modelling of the asteroseismic frequencies or characterising transiting exoplanets.Comment: Accepted for publication by MNRA

Investigating the role of prior and observation error correlations in improving a model forecast of forest carbon balance using Four Dimensional Variational data assimilation

Efforts to implement variational data assimilation routines with functional ecology models and land surface models have been limited, with sequential and Markov chain Monte Carlo data assimilation methods being prevalent. When data assimilation has been used with models of carbon balance, prior or “background” errors (in the initial state and parameter values) and observation errors have largely been treated as independent and uncorrelated. Correlations between background errors have long been known to be a key aspect of data assimilation in numerical weather prediction. More recently, it has been shown that accounting for correlated observation errors in the assimilation algorithm can considerably improve data assimilation results and forecasts. In this paper we implement a Four-Dimensional Variational data assimilation (4D-Var) scheme with a simple model of forest carbon balance, for joint parameter and state estimation and assimilate daily observations of Net Ecosystem CO2 Exchange (NEE) taken at the Alice Holt forest CO2 flux site in Hampshire, UK. We then investigate the effect of specifying correlations between parameter and state variables in background error statistics and the effect of specifying correlations in time between observation errors. The idea of including these correlations in time is new and has not been previously explored in carbon balance model data assimilation. In data assimilation, background and observation error statistics are often described by the background error covariance matrix and the observation error covariance matrix. We outline novel methods for creating correlated versions of these matrices, using a set of previously postulated dynamical constraints to include correlations in the background error statistics and a Gaussian correlation function to include time correlations in the observation error statistics. The methods used in this paper will allow the inclusion of time correlations between many different observation types in the assimilation algorithm, meaning that previously neglected information can be accounted for. In our experiments we assimilate a single year of NEE observations and then run a forecast for the next 14 years. We compare the results using our new correlated background and observation error covariance matrices and those using diagonal covariance matrices. We find that using the new correlated matrices reduces the root mean square error in the 14 year forecast of daily NEE by 44% decreasing from 4.22 gCm−2 day−1 to 2.38 gCm−2 day−

Appropriateness of acute admissions and last in-patient day for patients with long term neurological conditions

<p>Abstract</p> <p>Background</p> <p>To examine the appropriateness of admissions and in-patient stay for patients with long term neurological conditions (LTNCs). To identify variables predictive of appropriateness and explore management alternatives.</p> <p>Methods</p> <p>Adults admitted as acute patients to Derby Hospitals NHS Foundation Trust (England). Data were collected prospectively and examined by a multi-disciplinary expert panel to determine the appropriateness of admission and length of stay (LoS). Management alternatives were discussed.</p> <p>Results</p> <p>A total of 119 participants were recruited. 32 admissions were inappropriate and 83 were for an inappropriate duration. Whether a participant lived in their own home was predictive of an inappropriate admission. The number of LTNCs, number of presenting complaints and whether the participant lived alone in their own home were predictive of an inappropriate LoS. For admissions judged to be inappropriate, the panel suggested management alternatives.</p> <p>Conclusion</p> <p>Patients with LTNCs are being admitted to hospital when other services, e.g. ambulatory care, are available which could meet their needs. Inefficiencies in hospital procedures, such as discharge planning and patient transfers, continue to exist. Recognition of the need to plan for discharge at admission and to ensure in-patient services are provided in a timely manner may contribute towards improved efficiency.</p