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The purpose of this study was to determine if a web-based educational intervention increased knowledge, attitudes, and intention of perianesthesia nurses regarding opioid discharge education (including safe use, storage, and disposal of opioids). Secondary outcomes were to determine Perceived Behavioral Control, subjective norms, and familiarity with American Society of PeriAnesthesia Nurses (ASPAN) guidance on opioid education.A pre-test, post-test longitudinal design.An email described the study and had a link for those choosing to participate. The intervention was a web-based voiceover module with patient education scenarios focused on information required for patients before discharge home. Responses to the evidence-based pre-survey, post-survey one, and post-survey two were collected. The survey was developed using components of the Theory of Planned Behavior. Data analysis included descriptive summary and evaluation of changes in knowledge and domains of Theory of Planned Behavior using repeated measures mixed modeling.The participants were invited to complete a pre-test survey (n = 672), the immediate post-test (n = 245), and the 4-week post-test (n = 172). The analysis presented is limited to 245 who completed at least the first post-survey. Most were staff nurses (82%), and the majority had a BSN (62%); participants most typically worked in a hospital-based PACU (73%). For all outcomes, there was an immediate increase in the measure following the intervention; this pairwise difference (between pretest and the immediate post-test) was significant in all but one of the models. The immediate and 4-week post-test scores exceeded the corresponding pre-test score, though for Perceived Behavioral Control, attitude, and intention, the degree of increase between baseline and week 4 was not significant.In all cases, both the immediate and 4-week post-test scores exceeded the corresponding pre-test score, though, for three of the TPB constructs, the difference between baseline and week 4 was not significant, while nearly all of the increases between baseline and immediately following the intervention were significant. These findings suggest a more intensive intervention, possibly with the inclusion of booster sessions, may be needed.

The aim of this study was to review the literature regarding the use of an in-home opioid disposal product on unused opioids after surgery.The opioid epidemic in the United States is a major cause of concern for healthcare facilities. The misuse and diversion of retained opioids after a surgical procedure continues to contribute to this problem.A comprehensive search of the Cumulative Index of Nursing and Allied Health Literature, OVID, and PubMed databases with keywords including opioid, analgesics, narcotics, medical waste disposal, medical disposal, refuse disposal, and opioid disposal resulted in 286 articles. Articles were screened based on strict inclusion and exclusion criteria.Eight studies determined that an in-home opioid disposal product provided by a healthcare facility produced rates of opioid disposal between 19% and 71%.The provision of an in-home opioid disposal product by a healthcare facility is likely to increase the disposal of unused opioid medications in the postoperative surgical patient population.

The present opioid epidemic in the United States is a significant cause for concern in healthcare. In 1995, the concept of pain was introduced as the fifth vital sign. Since then, the sales of opioids have increased dramatically, as have the number of opioid deaths. The misuse and diversion of retained opioids following surgical procedures contribute to the problem. The objective of this project was to review the latest scholarly work and evaluate the findings related to patient education and disposal of opioid medications to decrease opioid misuse and increase disposal.A systematic review.The systematic search strategy included PubMed, Ovid Technologies (OVID), and Cumulative Index of Nursing and Allied Health Literature (CINAHL) electronic databases.A total of 4 randomized controlled trials (RCTs), 2 quasi-experimental studies, and 2 quality improvement projects met the criteria for inclusion. The studies found that as many as 92% of patients had leftover unused opioids. The retention rate of opioids among surgical patients was found to be 33 to 95%. When educational material was provided about disposal, the studies found that the disposal rate was as high as 71%.Patient education about opioid misuse, diversion, and disposal are essential topics that need to be addressed with patients and caregivers.

The impact of a physically-based parameterization of atmospheric drag over the marginal-icezone (MIZ) is evaluated through a series of regional and global atmospheric model simulations. The sea-ice drag parameterization has recently been validated and tuned based on a large set of observations of surface momentum flux from the Barents Sea and Fram Strait. The regional simulations are from March 2013 and make use of a collection of cold-air outbreak observations in the vicinity of the MIZ for validation. The global model analysis uses multiple 48-hour forecasts taken from a standard test suite of simulations. Our focus is on the response of the modelled atmosphere to changes in the drag coefficient over the MIZ. We find that the parameterization of drag has a significant impact on the simulated atmospheric boundary layer: for example, changing the surface momentum flux by typically 0.1-0.2 N m-2 (comparable to the mean) and low-level temperatures by 2-3 K in the vicinity of the MIZ. Comparisons against aircraft observations over and downwind of the MIZ show that simulations with the new sea ice drag scheme generally have the lowest bias and lowest rootmean-square errors. The wind speed and temperature biases are reduced by up to 0.5 m s-1 and 2 K respectively, compared to simulations with two settings of the previous drag scheme. In the global simulations the atmospheric response is widespread – impacting most of the Arctic and Antarctic sea-ice areas – with the largest changes in the vicinity of the MIZ and affecting the entire atmospheric boundary layer.

Accurate modelling of air–sea surface exchanges is crucial for reliable extreme surface wind-speed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 m s$$^{-1}$$ - 1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 m s$$^{-1}$$ - 1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 m s$$^{-1}$$ - 1 , due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 m s$$^{-1}$$ - 1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

Prediction of severe natural hazards requires accurate forecasting systems. Recently, there is a tendency to move towards more integrated solutions, where different components of the Earth system are coupled to better reproduce the physical feedbacks between them. Atmosphere–wave coupling should, in principle, improve the momentum flux because there is more detail in the two-way feedback due to the atmosphere receiving a more realistic picture of the surface roughness. However, the coupling between the ocean surface and the wind might become less efficient at transferring momentum during large storms.This study focuses on rapidly developing waves under extratropical storms to understand the sensitivity in atmosphere–wave present generation source terms and coupling strategies. Here, we analyse the effect of momentum transfer to fast growth waves during both long and fetch limited conditions using the Met Office regional atmosphere–ocean–wave coupled research system for the northwestern (NW) European shelf (UKC4).Two different sets of numerical experiments are conducted focusing on the atmosphere–wave components. The first one explores the sensitivity to two different wave source parameterizations, ST4 and ST6, and uses a two-way feedback coupling strategy (A2W) where a sea-state dependent surface roughness modifies the atmospheric momentum budget. In the second set of simulations, the impact of the coupling strategy is assessed. The A2W approach using ST6 physics is compared against a simpler one-way strategy (A1W) where no wave feedback on the atmospheric model exists and the wind stress is directly passed to the wave model (WAVEWATCHIII) ensuring conservation of momentum.Results demonstrate that ST6 physics allows for a faster wave growth than the currently used ST4 parameterization but might degrade low to mid energy wave states for the NW shelf. ST6 versus ST4 difference in wave growth is larger for higher wind speeds and short fetches. The experiment with ST4 and A2W consistently under-predicts the wave growth in those locations across the NW shelf where fetch dependence is an important factor (i.e., seas at the E of Ireland and the UK for storms coming from the NW-WNW). The implementation in the wave model of physics that depend solely in the wind input (ST6) with the A1W coupling strategy appears to improve growth of young wind-seas, reducing bias in those locations where the storms are underestimated. The analysis of the transfer of momentum across the air-sea boundary layer shows that forecasts of large wave events may require a different coupling approach. The slower wave growth seems to be related to an underestimation of the momentum transfer computed by the wave model when coupling the wind speeds (A2W). This suggests that coupling the wind speeds to the wave model and allowing this to calculate the momentum transfer from the atmosphere to waves and ocean underestimates the transfer by a few percent. For very young to young wind seas, this can be overcome when the surface stress is computed by the atmospheric model and directly passed to the ocean (A1W).

Accurate modelling of air-sea surface exchanges is crucial for reliable extreme surface wind forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between atmosphere, ocean and wave model components.Here, we present the results of studying the sensitivity of extreme surface wind speeds to air-sea exchanges at kilometre scale using coupled and uncoupled configurations of the Met Office's UK Regional Coupled Environmental Prediction (UKC4) system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 ms-1 over the UK.Compared to the atmosphere-only results, coupling to ocean decreases the domain-average sea surface temperature by up to 0.5 K. Inclusion of coupling to waves decreases the 98th percentile 10-m wind speed by up to 2 ms-1 as young, growing wind waves decrease wind speed by increasing the sea aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1ms -1, due to enhanced boundary-layer turbulence which partially offsets air-sea momentum transfer.Using a new drag parametrization based on the COARE~4.0 scheme, with a cap on the neutral drag coefficient and decrease for wind speeds exceeding 27 ms-1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

International audience; The atmospheric boundary layer undergoes transitions between stable and convective states. Over land, in undisturbed conditions, these transitions occur daily in the morning and late afternoon or early evening. Though less well studied and presenting more challenges than the fully stable and 2 fully convective states, such transitions have been the subject of growing interest over the last few decades. During transitions, all forcings are weak, and few simplifications are possible. Factors such as terrain, radiation, advection, and subsidence can seldom be safely neglected. In this paper, we review research on transitions over recent decades, with an emphasis on work published in Boundary-Layer Meteorology. The review is brief and inevitably reflects the interests and views of the authors.

In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against, and it is the intention that from this point forward significant changes to the system will be documented in the literature. This reproduces the process used for global configurations of the UM, which was first documented as a science configuration in 2011. While it is our goal to have a single defined configuration of the model that performs effectively in all regions, this has not yet been possible. Currently we define two sub-releases, one for mid-latitudes (RAL1-M) and one for tropical regions (RAL1-T). The differences between RAL1-M and RAL1-T are documented, and where appropriate we define how the model configuration relates to the corresponding configuration of the global forecasting model.

Given the present opioid crisis, the use of opioids in the hospital setting is an increasing concern among hospital administrators and healthcare professionals. A serious problem related to surgical care is persistent postoperative opioid use among previously opioid-naive patients. Certified registered nurse anesthetists (CRNAs) are strategically positioned within the hospital setting to address these concerns. These individuals are actively involved in managing the pain of their patients and can therefore lead change in relation to the opioid crisis. This article profiles a multidisciplinary acute pain service developed in a Magnet redesignated hospital led by CRNAs that has demonstrated positive outcomes in decreasing the use of opioids postprocedure and postdischarge, education for healthcare providers, information for community members related to opioid abuse, and support of new protocols, including Enhanced Recovery After Surgery.

In polar regions, where the boundary layer is often stably stratified, atmospheric models produce large biases depending on the boundary-layer parametrizations and the parametrization of the exchange of energy at the surface. This model intercomparison focuses on the very stable stratification encountered over the Antarctic Plateau in 2009. Here, we analyze results from 10 large-eddy-simulation (LES) codes for different spatial resolutions over 24 consecutive hours, and compare them with observations acquired at the Concordia Research Station during summer. This is a challenging exercise for such simulations since they need to reproduce both the 300-m-deep convective boundary layer and the very thin stable boundary layer characterized by a strong vertical temperature gradient (10 K difference over the lowest 20 m) when the sun is low over the horizon. A large variability in surface fluxes among the different models is highlighted. The LES models correctly reproduce the convective boundary layer in terms of mean profiles and turbulent characteristics but display more spread during stable conditions, which is largely reduced by increasing the horizontal and vertical resolutions in additional simulations focusing only on the stable period. This highlights the fact that very fine resolution is needed to represent such conditions. Complementary sensitivity studies are conducted regarding the roughness length, the subgrid-scale turbulence closure as well as the resolution and domain size. While we find little dependence on the surface-flux parametrization, the results indicate a pronounced sensitivity to both the roughness length and the turbulence closure.

We document the development of the first version of the United Kingdom Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include: a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities, and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall the model performs well, with a stable pre‐industrial state, and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealised simulations show a high climate sensitivity relative to previous generations of models: equilibrium climate sensitivity (ECS) is 5.4 K, transient climate response (TCR) ranges from 2.68 K to 2.85 K, and transient climate response to cumulative emissions (TCRE) is 2.49 K/TtC to 2.66 K/TtC.

Introduction Opioid overdose deaths and opioid use disorders are a crisis in the United States. Perianesthesia nurses have an excellent opportunity to educate patients and families who are discharged to home after surgery. Identification of the problem In a prior study, the authors found that nurses and other providers do not routinely discuss safe use, storage, or disposal of medications; perianesthesia nurses are more likely to discuss side effects of opioids. Purpose of the Study The purpose of this study is to determine if a web-based educational intervention increases knowledge, attitude, and intention of perianesthesia nurses to promote safe use, storage and disposal of opioids. Methodology A one group pre-test, post-test interventional study was conducted using a survey of ASPAN nurses. The intervention was a web-based voiceover module with patient education scenarios focused on information for patients before discharge. Responses to the pre-survey and 2 post surveys were collected. Data analysis included descriptive summary and evaluation of changes in knowledge and domains of Theory of Planned Behavior using repeated measures mixed modeling. Results The participants included pre-test survey (n = 678), the immediate post-test (n = 247), and the 4-week post-test (n = 171). The analysis presented is limited to 247 who completed at least the first post-survey. For all outcomes, there was an immediate increase in the measure following the intervention; this pairwise difference (between pretest and the immediate post-test) was significant in each model. The immediate and 4-week post-test scores exceeded the corresponding pre-test score, though for perceived behavioral control, attitude, and intention, the difference between baseline and week 4 was not significant. Discussion These findings suggest a more intensive intervention with possibly the inclusion of booster sessions, particularly for the outcomes of perceived behavioral control and subjective norms may be needed. Conclusion This educational intervention can be implemented at the national level for optimum impact. Implications for perianesthesia nurses and future research Perianesthesia nurses are well-positioned to teach patients about the risks of diversion, nonmedical use, and proper disposal of opioids. Research to develop safe postdischarge prescription practices and encourage safe opioid practices after surgery is needed.

Atmospheric forcing applied as ocean model boundary conditions can have a critical impact on the quality of ocean forecasts. This paper assesses the sensitivity of an eddy-resolving (1.5 km resolution) regional ocean model of the north-west European Shelf (NWS) to the choice of atmospheric forcing and atmosphere–ocean coupling. The analysis is focused on a month-long simulation experiment for July 2014 and evaluation of simulated sea surface temperature (SST) in a shallow near-coastal region to the south-west of the UK (Celtic Sea and western English Channel). Observations of the ocean and atmosphere are used to evaluate model results, with a particular focus on the L4 ocean buoy from the Western Channel Observatory as a rare example of co-located data above and below the sea surface. The impacts of differences in the atmospheric forcing are illustrated by comparing results from an ocean model run in forcing mode using operational global-scale numerical weather prediction (NWP) data with an ocean model run forced by a convective-scale regional atmosphere model. The value of dynamically representing feedbacks between the atmosphere and ocean state is assessed via the use of these model components within a fully coupled ocean–wave–atmosphere system. Simulated SSTs show considerable sensitivity to atmospheric forcing and to the impact of model coupling in near-coastal areas. A warm ocean bias relative to in situ observations in the simulation forced by global-scale NWP (0.7 K in the model domain) is shown to be reduced (to 0.4 K) via the use of the 1.5 km resolution regional atmospheric forcing. When simulated in coupled mode, this bias is further reduced (by 0.2 K). Results demonstrate much greater variability of both the surface heat budget terms and the near-surface winds in the convective-scale atmosphere model data, as might be expected. Assessment of the surface heat budget and wind forcing over the ocean is challenging due to a scarcity of observations. However, it can be demonstrated that the wind speed over the ocean simulated by the convective-scale atmosphere did not agree as well with the limited number of observations as the global-scale NWP data did. Further partially coupled experiments are discussed to better understand why the degraded wind forcing does not detrimentally impact on SST results.

A limitation of the Met Office operational data assimilation scheme is that surface-sensitive infrared satellite sounding channels cannot be used during daytime periods where numerical weather prediction (NWP) model background land surface temperature (LST) biases are greater than 2 K in magnitude. The Met Office Unified Model (UM) has a significant cold LST bias in semi-arid regions when compared with satellite observations; a range of UM configurations were assessed with different model resolutions, land surface cover datasets and bare soil parameterisations. UM LST biases were evaluated at global resolution and in a limited area model (LAM) at a 2.2 km resolution over the SALSTICE (Semi-Arid Land Surface Temperature and IASI Calibration Experiment) experimental domain in south-eastern Arizona. This validation is in conjunction with eddy-covariance flux tower measurements. LST biases in the Global Atmosphere/Land 3.1 (GA/L3.1) configuration were largest in the mid-morning with respect to Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (-13.6±2.8 K at the Kendall Grassland site). The diurnal cycle of LST in Global Atmosphere/Land 6.1 (GA/L6.1) showed a significant improvement relative to GA/L3.1 with the cold LST biases reduced to -1.4±2.7 K and -3.6±3.0 K for Terra and Aqua overpasses, respectively. The higher-resolution LAM showed added value over the global configurations. The spatial distribution of the LST biases relative to MODIS and the modelled bare soil cover fraction were found to be moderately correlated (0.61±0.08) during the daytime, which suggests that regions of cold LST bias are associated with low bare soil cover fraction. Coefficients of correlation with the shrub surface fractions followed the same trend as the bare soil cover fraction, although with a less significant correlation (0.36±0.09), and indicated that the sparse vegetation canopies in south-eastern Arizona are not well represented in UM ancillary datasets. The x component of the orographic slope was positively correlated with the LST bias (0.41±0.05 for MODIS Aqua) and identified that regions of cold model LST bias are found on easterly slopes, and regions of warm model LST bias are found on westerly slopes. An overestimate in the modelled turbulent heat and moisture fluxes at the eddy-covariance flux sites was found to be coincident with an underestimate in the ground heat flux.

Protein behavior in complex mixtures, such as biological fluids, is often modeled by simplified buffer systems in solution. Here we have used the recently described differential

Atmospheric forcing applied as ocean model boundary conditions can have a critical impact on the quality of ocean forecasts. This paper assesses the sensitivity of an eddy-resolving (1.5 km resolution) regional ocean model of the North-West European shelf (NWS) to atmospheric forcing resolution and air-sea coupling. The analysis is focused on a month-long simulation experiment for July 2014 and evaluation of simulated sea surface temperature (SST) in a shallow near-coastal region to the south-west of the UK (Celtic Sea and western English Channel). Observations above and below the sea surface at the L4 ocean buoy from the Western Channel Observatory are used to evaluate ocean and atmosphere model data. The impacts of differences in the atmospheric forcing are illustrated by comparing results from an ocean model run in forcing mode using operational global-scale numerical weather prediction (NWP) data with a run forced by a convective scale regional atmosphere model. The value of dynamically representing feedbacks between the atmosphere and ocean state is assessed through use of these model components within a fully coupled ocean-wave-atmosphere system. Simulated SST show considerable sensitivity to atmospheric forcing and to the impact of model coupling in near-coastal areas. A warm ocean bias relative to in-situ observations in the simulation forced by global-scale NWP (0.7 K mean difference, warmer relative to all observations in the model domain) is shown to be reduced (to 0.4 K) through use of the 1.5 km resolution atmosphere forcing. When simulated in coupled mode, this bias is further reduced by 0.2 K. Results demonstrate much greater variability of both surface energy balance terms and near-surface winds in the higher resolution atmosphere model data, as might be expected. Assessment of the surface energy balance and wind forcing over the ocean is challenging due to a scarcity of observations. It can however be demonstrated that the wind speed over the ocean simulated by the high resolution atmosphere agreed with the limited number of observations less well than the global-scale NWP data. Further partially-coupled experiments are discussed to better understand why the degraded wind forcing does not detrimentally impact on SST results.

Observations of two typical contrasting weakly stable and very stable boundary layers from the winter at Dome C station, Antarctica, are used as a benchmark for two centimetre-scale-resolution large-eddy simulations. By taking the Antarctic winter, the effects of the diurnal cycle are eliminated, enabling the study of the long-lived steady stable boundary layer. With its homogeneous, flat snow surface, and extreme stabilities, the location is a natural laboratory for studies on the long-lived stable boundary layer. The two simulations differ only in the imposed geostrophic wind speed, which is identified as the main deciding factor for the resulting regime. In general, a good correspondence is found between the observed and simulated profiles of mean wind speed and temperature. Discrepancies in the temperature profiles are likely due to the exclusion of radiative transfer in the current simulations. The extreme stabilities result in a considerable contrast between the stable boundary layer at the Dome C site and that found at typical mid-latitudes. The boundary-layer height is found to range from approximately 50m to just 5m in the most extreme case. Remarkably, heating of the boundary layer by subsidence may result in thermal equilibrium of the boundary layer in which the associated heating is balanced by the turbulent cooling towards the surface. Using centimetre-scale resolutions, accurate large-eddy simulations of the extreme stabilities encountered in Antarctica appear to be possible. However, future simulations should aim to include radiative transfer and sub-surface heat transport to increase the degree of realism of these types of simulations.

A limitation of the Met Office operational data assimilation scheme is that surface-sensitive infrared satellite sounding channels cannot be used during daytime periods where Numerical Weather Prediction (NWP) model background land surface temperature (LST) biases are greater than 2 K. The Met Office Unified Model (UM) has a significant cold LST bias in semi-arid regions when compared with satellite observations. UM LST biases were evaluated at global resolution and in a Limited Area Models (LAM) at 2.2 km resolution over the SALSTICE (Semi-Arid Land Surface Temperature and IASI Calibration Experiment) experimental domain in southeastern Arizona. This validation is in conjunction with eddy-covariance flux tower measurements. LST biases in the Global Atmosphere/Land 3.1 (GA/L3.1) configuration were largest in the mid-morning with respect to Terra (−13.6 ± 2.8 K at the Kendall Grassland site). The diurnal cycle of LST in Global Atmosphere/Land 6.1 (GA/L6.1) showed a significant improvement relative to GA/L3.1. The higher resolution LAM showed added value over the global configurations. The spatial distribution of the LST biases relative to Moderate Resolution Imaging Spectroradiometer (MODIS) and the modelled bare soil cover fraction were found to be moderately correlated (0.61 ± 0.08) during the daytime, which suggests that regions of cold LST bias are associated with low bare soil cover fraction. Coefficients of correlation with the shrub surface fractions followed the same trend as the bare soil cover fraction although with a less significant correlation (0.36 ± 0.09), and indicate that the sparse vegetation canopies in southeastern Arizona are not well represented in UM ancillary datasets. The x-component of the orographic slope was positively correlated with the LST bias (0.35 ± 0.06) and identified that regions of cold model LST bias are found on easterly slopes and regions of warm model LST bias are found on westerly slopes. An overestimate in the modelled turbulent heat and moisture fluxes at the eddy-covariance flux sites was found to be coincident with an underestimate in the ground heat flux.

This paper describes an updated configuration of the regional coupled research system, termed UKC3, developed and evaluated under the UK Environmental Prediction collaboration. This represents a further step towards a vision of simulating the numerous interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land using more integrated regional coupled prediction systems at km-scale resolution. The UKC3 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean surface waves (WAVEWATCH III), coupled together using OASIS3-MCT libraries. The major update introduced since the UKC2 configuration is an explicit representation of wave processes in the ocean and their feedbacks through wave-to-ocean coupling. Ocean model results demonstrate that wave coupling, in particular representing the wave modified surface drag, has a small but positive improvement on the agreement between simulated sea surface temperatures and in situ observations, relative to simulations without wave feedbacks. Other incremental developments to the coupled modelling capability introduced since the UKC2 configuration are also detailed. Coupled regional prediction systems are of interest for applications across a range of timescales, from hours to decades ahead. The first results of simulations run over extended periods, covering four experiments each of order one month in duration are therefore analysed and discussed in the context of further characterising the potential benefits of coupled prediction on forecast skill, and on the stability of such systems over longer time periods. Results across atmosphere, ocean and wave components are shown to be of at least comparable skill to the equivalent uncoupled control simulations, with notable improvements demonstrated in surface temperature and wave state predictions in some near-coastal regions, and in wind speeds over the sea.

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40–60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections., The Southern Ocean is critically important for global climate yet poorly represented by climate models. Here the authors trace sea surface temperature biases in this region to cloud-related errors in atmospheric-model simulated surface heat fluxes and provide a pathway to improve the models.

It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere-land-ocean-wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed. Fil: Lewis, Huw W.. Exeter Met Office; Reino Unido Fil: Manuel Castillo Sanchez, Juan. Exeter Met Office; Reino Unido Fil: Graham, Jennifer. Exeter Met Office; Reino Unido Fil: Saulter, Andrew. Exeter Met Office; Reino Unido Fil: Bornemann, Jorge. Exeter Met Office; Reino Unido Fil: Arnold, Alex. Exeter Met Office; Reino Unido Fil: Fallmann, Joachim. Exeter Met Office; Reino Unido Fil: Harris, Chris. Exeter Met Office; Reino Unido Fil: Pearson, David. Exeter Met Office; Reino Unido Fil: Ramsdale, Steven. Exeter Met Office; Reino Unido Fil: Martínez De La Torre, Alberto. Centre For Ecology & Hydrology; Reino Unido Fil: Bricheno, Lucy. National Oceanography Centre; Reino Unido Fil: Blyth, Eleanor. Centre For Ecology & Hydrology; Reino Unido Fil: Bell, Victoria A.. Centre For Ecology & Hydrology; Reino Unido Fil: Davies, Helen. Centre For Ecology & Hydrology; Reino Unido Fil: Marthews, Toby R.. Centre For Ecology & Hydrology; Reino Unido Fil: O'Neill, Clare. Exeter Met Office; Reino Unido Fil: Rumbold, Heather. Exeter Met Office; Reino Unido Fil: O'Dea, Enda. Exeter Met Office; Reino Unido Fil: Brereton, Ashley. National Oceanography Centre; Reino Unido Fil: Guihou, Karen. National Oceanography Centre; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Hines, Adrian. Exeter Met Office; Reino Unido Fil: Butenschon, Momme. Plymouth Marine Laboratory; Reino Unido Fil: Dadson, Simon J.. University of Oxford; Reino Unido Fil: Palmer, Tamzin. Exeter Met Office; Reino Unido Fil: Holt, Jason. National Oceanography Centre; Reino Unido Fil: Reynard, Nick. Centre For Ecology & Hydrology; Reino Unido Fil: Best, Martin. Exeter Met Office; Reino Unido Fil: Edwards, John. Exeter Met Office; Reino Unido Fil: Siddorn, John. Exeter Met Office; Reino Unido

A Met Office/Natural Environment Research Council Joint Weather and Climate Research Programme workshop brought together 50 key international scientists from the UK and international community to formulate the key requirements for an Urban Meteorological Research strategy. The workshop was jointly organised by University of Reading and the Met Office.

We present the results of a wide-ranging sea ice sensitivity study, performed with a fully-coupled global atmosphere–ice-ocean climate model. We investigate sensitivity to a selection of sea ice parameters, varied within the range of observational uncertainty, and additionally study the effect on the sea ice of increased resolution in the atmosphere and ocean-ice models, as well as dynamics and physics changes in the atmosphere. In the Arctic, we find that the sea ice thickness is most sensitive to the albedo of the overlying snow layer (because of its influence on surface melt) and the thermal conductivities of ice and snow (because of their role in regulating heat flux from the ocean to the atmosphere through the ice). We find the winter Arctic ice extent to be sensitive to the resolution of the ocean-ice model, through increased sea surface temperatures in the Labrador Sea at higher resolution. The Arctic ice extent is reduced under increased atmospheric resolution, because of increased poleward heat transport. In the Antarctic, the sensitivity to sea ice parameters is weaker, and atmosphere and ocean forcing dominate; in particular, increased resolution of the atmosphere and ocean-ice models leads to the enhancement of a warm bias in the Southern Ocean, which has a large impact on sea ice thickness and extent. Inclusion of a selection of these parameters in combination, together with changes to the atmosphere and ocean models, leads to significant improvements in representation of Arctic sea ice extent, thickness and volume in a new global coupled model configuration.

The radiation scheme in the Met Office Unified Model (UM) is extended to allow the calculation of short-wave radiances. Comparisons between short-wave reflectances simulated with the global forecasting configuration of the UM and observations from SEVIRI (Spin Enhanced Visible and Infrared Imager) on board Meteosat 8 are presented. One of the main purposes for such a comparison is model validation, since it allows us to directly compare model and satellite reflectances, without having to make use of retrieval systems. Eliminating the retrieval algorithm has the advantage that we can be certain that any discrepancies between the modelled and the measured radiances are due to inaccuracies in the model, rather than differences in the assumptions made both in the model and the retrieval algorithm. In principle, this should allow us to detect weaknesses in the model parametrizations. In particular, we compare the four short-wave channels of SEVIRI to the corresponding radiance simulations obtained from the UM over oceanic regions. Generally good agreement between the simulated and observed reflectances was obtained in the visible channels, but greater disagreement was found in the NIR 1.6 and IR 3.9 channels, hinting at deficiencies in the model's representation of particle size. Sensitivity studies are carried out to explore these sensitivities.

The high-resolution (4-km grid length) Met Office (UKMO) Unified Model forecasts driven by the coarser-resolution (8-km grid length) High-Resolution Limited-Area Model (HIRLAM), UM4, often produce significantly colder screen-level (2 m) temperatures in winter over Norway than forecast with HIRLAM itself. To diagnose the main error source of this cold bias this study focuses on the forecast initial and lateral boundary conditions, particularly the initialization of soil moisture and temperature. The soil variables may be used differently by land surface schemes of varying complexity, representing a challenge to model interoperability. In a set of five experiments, daily UM4 forecasts are driven by alternating initial and lateral boundary conditions from two different parent models: HIRLAM and Met Office North Atlantic and Europe (NAE). The experiment period is November 2007. Points for scientific examination into the topics of model interoperability and sensitivity to soil initial conditions are identified. The soil moisture is the main error source and is therefore important also in winter, rather than being a challenge only in summer. The day-to-day variability in the forecast error is large with the larger errors on days with strong longwave heat loss at the surface (i.e., the forecast sensitivity to soil moisture content is significant but variable). The much drier soil in HIRLAM compared to NAE reduces the heat capacity of the soil layers and affects the heat flux from the surface soil layer to the surface. Normalizing the respective soil moisture fields reduces these differences. The impact of ground snow is quite limited.

The performance of numerical weather forecasts made with the Met Office Unified Model is evaluated using near-surface measurements made at a comprehensively instrumented site over the course of the annual cycle, with the aim of characterizing the forecasting system's generic behaviour in the surface layer. The study is focused on the seasonal diurnal cycles of the screen-level and surface temperatures and the surface flux budget. High-resolution versions of the model simulate seasonal composite diurnal cycles of the screen temperature to an accuracy of about 1 K, but appear to show a cold bias in the surface skin temperature by day and a warm bias at night, while underestimating the magnitude of the difference in temperature between the screen level and the surface, particularly in conditions of light winds and strong surface cooling. The consistency of the measured surface fluxes is assessed by deriving the full annual cycle of the monthly mean atmospheric surface fluxes. The measured surface flux budget at this site is closed to an accuracy better than 5 W m−2. Comparison of the modelled and measured fluxes shows that in spring and summer the modelled downward shortwave fluxes are too large, while the latent heat fluxes are overestimated. Copyright © 2011 British Crown Copyright. Published by John Wiley & Sons Ltd.

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A poor representation of cloud structure in a general circulation model (GCM) is widely recognised as a potential source of error in the radiation budget. Here, we develop a new way of representing both horizontal and vertical cloud structure in a radiation scheme. This combines the ‘Tripleclouds’ parametrization, which introduces inhomogeneity by using two cloudy regions in each layer as opposed to one, each with different water content values, with ‘exponential-random’ overlap, in which clouds in adjacent layers are not overlapped maximally, but according to a vertical decorrelation scale. This paper, Part I of two, aims to parametrize the two effects such that they can be used in a GCM. To achieve this, we first review a number of studies for a globally applicable value of fractional standard deviation of water content for use in Tripleclouds. We obtain a value of 0.75 ± 0.18 from a variety of different types of observations, with no apparent dependence on cloud type or gridbox size. Then, through a second short review, we create a parametrization of decorrelation scale for use in exponential-random overlap, which varies the scale linearly with latitude from 2.9 km at the Equator to 0.4 km at the poles. When applied to radar data, both components are found to have radiative impacts capable of offsetting biases caused by cloud misrepresentation. Part II of this paper implements Tripleclouds and exponential-random overlap into a radiation code and examines both their individual and combined impacts on the global radiation budget using re-analysis data. Copyright c