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Although the quality of weather forecasts in the polar regions is improving, forecast skill there still lags behind lower latitudes. So far there have been relatively few efforts to evaluate processes in numerical weather prediction systems using in situ and remote sensing datasets from meteorological observatories in the terrestrial Arctic and Antarctic compared to the mid-latitudes. Progress has been limited both by the heterogeneous nature of observatory and forecast data and by limited availability of the parameters needed to perform process-oriented evaluation in multi-model forecast archives. The Year of Polar Prediction (YOPP) site Model Inter-comparison Project (YOPPsiteMIP) is addressing this gap by producing merged observatory data files (MODFs) and merged model data files (MMDFs), bringing together observations and forecast data at polar meteorological observatories in a format designed to facilitate process-oriented evaluation. An evaluation of forecast performance was performed at seven Arctic sites, focussing on the first YOPP Special Observing Period in the Northern Hemisphere (NH-SOP1) in February and March 2018. It demonstrated that although the characteristics of forecast skill vary between the different sites and systems, an underestimation in boundary layer temperature variability across models, which goes hand in hand with an inability to capture cold extremes, is a common issue at several sites. It is found that many models tend to underestimate the sensitivity of the 2 m air temperature (T2m) and the surface skin temperature to variations in radiative forcing, and the reasons for this are discussed.

A large and ever-growing body of geophysical information is measured in campaigns and at specialized observatories as a part of scientific expeditions and experiments. These collections of observed data include many essential climate variables (as defined by the Global Climate Observing System) but are often distinguished by a wide range of additional non-routine measurements that are designed to not only document the state of the environment but also the drivers that contribute to that state. These field data are used not only to further understand environmental processes through observation-based studies but also to provide baseline data to test model performance and to codify understanding to improve predictive capabilities. To address the considerable barriers and difficulty in utilizing these diverse and complex data for observation–model research, the Merged Observatory Data File (MODF) concept has been developed. A MODF combines measurements from multiple instruments into a single file that complies with well-established data format and metadata practices and has been designed to parallel the development of corresponding Merged Model Data Files (MMDFs). Using the MODF and MMDF protocols will facilitate the evolution of model intercomparison projects into model intercomparison and improvement projects by putting observation and model data “on the same page” in a timely manner. The MODF concept was developed especially for weather forecast model studies in the Arctic. The surprisingly complex process of implementing MODFs in that context refined the concept itself. Thus, this article explains the concept of MODFs by providing details on the issues that were revealed and resolved during that first specific implementation. Detailed instructions are provided on how to make MODFs, and this article can be considered a MODF creation manual.

The rapid changes occurring in the polar regions require an improved understanding of the processes that are driving these changes. At the same time, increased human activities such as marine navigation, resource exploitation, aviation, commercial fishing, and tourism require reliable and relevant weather information. One of the primary goals of the World Meteorological Organization's Year of Polar Prediction (YOPP) project is to improve the accuracy of numerical weather prediction (NWP) at high latitudes. During YOPP, two Canadian “supersites” were commissioned and equipped with new ground-based instruments for enhanced meteorological and system process observations. Additional pre-existing supersites in Canada, the United States, Norway, Finland, and Russia also provided data from ongoing long-term observing programs. These supersites collected a wealth of observations that are well suited to address YOPP objectives. In order to increase data useability and station interoperability, novel Merged Observatory Data Files (MODFs) were created for the seven supersites over two Special Observing Periods (February to March 2018 and July to September 2018). All observations collected at the supersites were compiled into this standardized NetCDF MODF format, simplifying the process of conducting pan-Arctic NWP verification and process evaluation studies. This paper describes the seven Arctic YOPP supersites, their instrumentation, data collection and processing methods, the novel MODF format, and examples of the observations contained therein. MODFs comprise the observational contribution to the model intercomparison effort, termed YOPP site Model Intercomparison Project (YOPPsiteMIP). All YOPPsiteMIP MODFs are publicly accessible via the YOPP Data Portal (Whitehorse: https://doi.org/10.21343/a33e-j150, Huang et al., 2023a; Iqaluit: https://doi.org/10.21343/yrnf-ck57, Huang et al., 2023b; Sodankylä: https://doi.org/10.21343/m16p-pq17, O'Connor, 2023; Utqiaġvik: https://doi.org/10.21343/a2dx-nq55, Akish and Morris, 2023c; Tiksi: https://doi.org/10.21343/5bwn-w881, Akish and Morris, 2023b; Ny-Ålesund: https://doi.org/10.21343/y89m-6393, Holt, 2023; and Eureka: https://doi.org/10.21343/r85j-tc61, Akish and Morris, 2023a), which is hosted by MET Norway, with corresponding output from NWP models.

Active remote sensors equipped with the capability to detect polarization, a shape-relevant parameter, are essential to aerosol particle identification in the vertical domain. Most commonly, the linear particle depolarization ratio has been available at the shorter wavelengths of 355 and/or 532 nm. Recently, linear particle depolarization ratios at longer wavelengths (910, 1064, and 1565 nm) have emerged in lidar aerosol research. In this study, a synergy of three lidars, namely a PollyXT lidar, a Vaisala CL61 ceilometer, and a HALO Photonics StreamLine Pro Doppler lidar, as well as in situ aerosol and pollen observations have been utilized to investigate the spectral dependence of birch and pine pollen particles. We found that, regardless of the pollen type, the linear particle depolarization ratio was subject to the amount of pollen and its relative contribution to the aerosol mixture in the air. More specifically, during birch pollination, characteristic linear particle depolarization ratios of 5 ± 2 % (355 nm), 28 ± 6 % (532 nm), 23 ± 6 % (910 nm), and 33 ± 4 % (1565 nm) were retrieved at the pollen layer. Regarding the pine-dominant period, characteristic linear particle depolarization ratios of 6 ± 2 %, 43 ± 11 %, 22 ± 6 %, and 26 ± 3 % were determined at wavelengths of 355, 532, 910, and 1565 nm, respectively. For birch, the linear particle depolarization ratio at 1565 nm was the highest, followed by the 532 and 910 nm wavelengths, respectively. A sharp decrease at 355 nm was evident for birch pollen. For pine pollen, a maximum at the 532 nm wavelength was observed. There was no significant change in the linear particle depolarization ratio at 910 nm for the pollen types considered in this study. Given the low concentration of pollen in the air, the inclusion of the longer wavelengths (910 and 1565 nm) for the detection of birch and pine can be beneficial due to their sensitivity to trace large aerosol particles.

By synthesising remote-sensing measurements made in the central Arctic into a model-gridded Cloudnet cloud product, we evaluate how well the Met Office Unified Model (UM) and the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) capture Arctic clouds and their associated interactions with the surface energy balance and the thermodynamic structure of the lower troposphere. This evaluation was conducted using a 4-week observation period from the Arctic Ocean 2018 expedition, where the transition from sea ice melting to freezing conditions was measured. Three different cloud schemes were tested within a nested limited-area model (LAM) configuration of the UM – two regionally operational single-moment schemes (UM_RA2M and UM_RA2T) and one novel double-moment scheme (UM_CASIM-100) – while one global simulation was conducted with the IFS, utilising its default cloud scheme (ECMWF_IFS). Consistent weaknesses were identified across both models, with both the UM and IFS overestimating cloud occurrence below 3 km. This overestimation was also consistent across the three cloud configurations used within the UM framework, with >90 % mean cloud occurrence simulated between 0.15 and 1 km in all the model simulations. However, the cloud microphysical structure, on average, was modelled reasonably well in each simulation, with the cloud liquid water content (LWC) and ice water content (IWC) comparing well with observations over much of the vertical profile. The key microphysical discrepancy between the models and observations was in the LWC between 1 and 3 km, where most simulations (all except UM_RA2T) overestimated the observed LWC. Despite this reasonable performance in cloud physical structure, both models failed to adequately capture cloud-free episodes: this consistency in cloud cover likely contributes to the ever-present near-surface temperature bias in every simulation. Both models also consistently exhibited temperature and moisture biases below 3 km, with particularly strong cold biases coinciding with the overabundant modelled cloud layers. These biases are likely due to too much cloud-top radiative cooling from these persistent modelled cloud layers and were consistent across the three UM configurations tested, despite differences in their parameterisations of cloud on a sub-grid scale. Alarmingly, our findings suggest that these biases in the regional model were inherited from the global model, driving a cause–effect relationship between the excessive low-altitude cloudiness and the coincident cold bias. Using representative cloud condensation nuclei concentrations in our double-moment UM configuration while improving cloud microphysical structure does little to alleviate these biases; therefore, no matter how comprehensive we make the cloud physics in the nested LAM configuration used here, its cloud and thermodynamic structure will continue to be overwhelmingly biased by the meteorological conditions of its driving model.

Accurate wind profile measurements are important for applications ranging from aviation to numerical weather prediction. The spatial pattern of winds can be obtained with ground-based remote sensing instruments, such as weather radars and Doppler lidars. As the return signal in weather radars is mostly due to hydrometeors or insects, and in Doppler lidars due to aerosols, the instruments provide wind measurements in different weather conditions. However, the effect of various weather conditions on the measurement capabilities of these instruments has not been previously extensively quantified. Here we present results from a 7-month measurement campaign that took place in Vantaa, Finland, where a co-located Vaisala WRS400 X-band weather radar and WindCube 400S Doppler lidar were employed continuously to perform wind measurements. Both instruments measured plan position indicator (PPI) scans at 2.0∘ elevation from the horizontal. Direct comparison of radial Doppler velocities from both instruments showed good agreement with R2=0.96. We then examined the effect of horizontal visibility, cloud base height, and precipitation intensity on the measurement availability of each instrument. The Doppler lidar displayed good availability in clear air situations and the X-band radar in precipitation. Both instruments exhibited high availability in clear air conditions in summer when insects were present. The complementary performance in the measurement availability of the two instruments means that their combination substantially increases the spatial coverage of wind observations across a wide range of weather conditions.

The structure of the urban boundary layer, and particularly the surface layer, displays significant complexity, which can be exacerbated by coastal effects for cities located in such regions. Resolving the complexity of the coastal urban boundary layer remains an important question for many applications such as air quality and numerical weather prediction. One of the most promising new techniques for measuring the structure of the surface layer is fibre-optic distributed temperature sensing (DTS), which has the potential to provide new significant insights for boundary layer meteorology by making it possible to study thermal turbulence with high spatial and temporal resolution. We present 14 weeks of profile measurements with a DTS system at an urban site in Helsinki, Finland, during the winter and spring of 2020. We assess the benefits and drawbacks of using DTS measurements to supplement sonic anemometry for longer measurement periods in varying meteorological conditions, including those found difficult for the DTS method in prior studies. Furthermore, we demonstrate the capabilities of the DTS system using two case scenarios: a study of the erosion of a near-ground cold layer during the passage of a warm front, and a comparison of the near-ground thermal structure with and without the presence of a sea-breeze cell during springtime convective boundary layer development. This study demonstrates the utility of DTS measurements in revealing the internal surface layer structure, beyond the predictions of traditional surface layer theories. This knowledge is important for improving surface layer theories and parametrisations, including those used in numerical weather prediction. The study also highlights the drawbacks of DTS measurements, caused by low signal-to-noise ratios in near-neutral atmospheric conditions, especially when such a system would be used to supplement turbulence measurements over longer periods. Overall, this study presents important considerations for planning new studies or ongoing measurements utilising this exciting and relatively new instrumentation.

Knowledge of the atmospheric boundary layer state and evolution is important for understanding air pollution and low-level cloud development, among other things. There are a number of instruments and methods that are currently used to estimate boundary layer height (BLH). However, no single instrument is capable of providing BLH measurements in all weather conditions. We proposed a method to derive a daytime convective BLH using clear air echoes in radar observations and investigated the consistency of these retrievals between different radar frequencies. We utilized data from three vertically pointing radars that are available at the SMEAR II station in Finland, i.e. the C band (5 GHz), Ka band (35 GHz) and W band (94 GHz). The Ka- or W-band cloud radars are an integral part of cloud profiling stations of pan-European Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Our method will be utilized at ACTRIS stations to serve as an additional estimate of the BLH during summer months. During this period, insects and Bragg scatter are often responsible for clear air echoes recorded by weather and cloud radars. To retrieve a BLH, we suggested a mechanism to separate passive and independently flying insects that works for all analysed frequency bands. At the lower frequency (the C band) insect scattering has been separated from Bragg scattering using a combination of the radar reflectivity factor and linear depolarization ratio. Retrieved values of the BLH from all radars are in a good agreement when compared to the BLH obtained with the co-located HALO Doppler lidar and ERA5 reanalysis data set. Our method showed some underestimation of the BLH after nighttime heavy precipitation yet demonstrated a potential to serve as a reliable method to obtain a BLH during clear-sky days. Additionally, the entrainment zone was observed by the C-band radar above the CBL in the form of a Bragg scatter layer. Aircraft observations of vertical profiles of potential temperature and water vapour concentration, collected in the vicinity of the radar, demonstrated some agreement with the Bragg scatter layer.

Abstract Wolfram syndrome (WS) is an ultra-rare progressive neurodegenerative disorder defined by early-onset diabetes mellitus and optic atrophy. The majority of patients harbour recessive mutations in the WFS1 gene, which encodes for Wolframin, a transmembrane endoplasmic reticulum protein. There is limited availability of human ocular and brain tissues, and there are few animal models for WS that replicate the neuropathology and clinical phenotype seen in this disorder. We, therefore, characterised two wfs1 zebrafish knockout models harbouring nonsense wfs1a and wfs1b mutations. Both homozygous mutant wfs1a −/− and wfs1b −/− embryos showed significant morphological abnormalities in early development. The wfs1b −/− zebrafish exhibited a more pronounced neurodegenerative phenotype with delayed neuronal development, progressive loss of retinal ganglion cells and clear evidence of visual dysfunction on functional testing. At 12 months of age, wfs1b −/− zebrafish had a significantly lower RGC density per 100 μm2 (mean ± standard deviation; 19 ± 1.7) compared with wild-type (WT) zebrafish (25 ± 2.3, p

A quantitative comparison study for Raman lidar and ceilometer observations, and for model simulations of mass concentration estimates of smoke particles is presented. Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios (PDRs) of this plume were measured to be 0.08±0.02 at 355 nm and 0.05±0.01 at 532 nm, suggesting the presence of partly coated soot particles or particles that have mixed with a small amount of dust or other non-spherical aerosol type. The layer-mean PDR at 355 nm (532 nm) decreased during the day from ∼ 0.11 (0.06) in the morning to ∼ 0.05 (0.04) in the evening; this decrease with time could be linked to the particle aging and related changes in the smoke particle shape properties. Lidar ratios were derived as 47±5 sr at 355 nm and 71±5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 ceilometer is presented from a sensor-provided attenuated backscatter coefficient to particle mass concentration (including the water vapor correction for high latitude for the first time). Aerosol backscatter coefficients (BSCs) were measured at four wavelengths (355, 532, 1064 nm from PollyXT and 910 nm from CL51). Two methods, based on a combined lidar and sun-photometer approach, are applied for mass concentration estimations from both PollyXT and the ceilometer CL51 observations. In the first method, no. 1, we used converted BSCs at 532 nm (from measured BSCs) by corresponding measured backscatter-related Ångström exponents, whereas in the second method, no. 2, we used measured BSCs at each wavelength independently. A difference of ∼ 12 % or ∼ 36 % was found between PollyXT and CL51 estimated mass concentrations using method no. 1 or no. 2, showing the potential of mass concentration estimates from a ceilometer. Ceilometer estimations have an uncertainty of ∼ 50 % in the mass retrieval, but the potential of the data lies in the great spatial coverage of these instruments. The mass retrievals were compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust (as indicated by MERRA-2 data) in the retrieved mass concentration is negligible considering the uncertainties, which also shows that ceilometer observations for mass retrievals can be used even without exact knowledge of the composition of the smoke-dominated aerosol plume in the troposphere.

This study identified risk, promotive, and protective factors for handgun carriage among 265 primarily African American adolescents (M[subscript age] = 14.3) living in low-income urban areas. Community-based violent victimization and witnessing violence and in-person and cyber forms of peer victimization increased the probability of handgun carriage. Community collective efficacy, including caregiver-reported social connectedness and informal social control, and community developmental strengths/supports, including youth-reported community recognition for prosocial involvement and community developmental assets, moderated relations between both violent victimization and witnessing violence and handgun carriage. School developmental strengths/supports, including school developmental assets and family prosocial involvement in school, moderated relations between in-person and cyber victimization and handgun carriage. Family developmental strengths/supports, including family developmental assets and family recognition and opportunities for prosocial involvement, were associated with lower odds of handgun carriage. Study findings revealed distinct protective factors related to community violence exposure or peer victimization that can inform youth violence prevention efforts.

The suitability of a fibre-optic distributed temperature sensing (DTS) technique for observing atmospheric mixing profiles within and above a forest was quantified, and these profiles were analysed. The spatially continuous observations were made at a 125 m tall mast in a boreal pine forest. Airflows near forest canopies diverge from typical boundary layer flows due to the influence of roughness elements (i.e. trees) on the flow. Ideally, these complex flows should be studied with spatially continuous measurements, yet such measurements are not feasible with conventional micrometeorological measurements with, for example, sonic anemometers. Hence, the suitability of DTS measurements for studying canopy flows was assessed. The DTS measurements were able to discern continuous profiles of turbulent fluctuations and mean values of air temperature along the mast, providing information about mixing processes (e.g. canopy eddies and evolution of inversion layers at night) and up to third-order turbulence statistics across the forest–atmosphere interface. Turbulence measurements with 3D sonic anemometers and Doppler lidar at the site were also utilised in this analysis. The continuous profiles for turbulence statistics were in line with prior studies made at wind tunnels and large eddy simulations for canopy flows. The DTS measurements contained a significant noise component which was, however, quantified, and its effect on turbulence statistics was accounted for. Underestimation of air temperature fluctuations at high frequencies caused 20 %–30 % underestimation of temperature variance at typical flow conditions. Despite these limitations, the DTS measurements should prove useful also in other studies concentrating on flows near roughness elements and/or non-stationary periods, since the measurements revealed spatio-temporal patterns of the flow which were not possible to be discerned from single point measurements fixed in space.

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.

Abstract Objective To describe the technical aspects and outcomes of robotic‐assisted radical prostatectomy (RARP) following abandoned open radical prostatectomy (ORP). Patients and Methods A retrospective review was performed of patients who underwent RARP following abandonment of ORP between 2016 and 2020. RARP was undertaken by two highly experienced robotic surgeons. Analysis of patient and operative characteristics, outcomes, and reasons for abandonment of ORP were described. Results Six patients were included for analysis with a median age of 63.5 years [50.3‐67.5]. The median body mass index (BMI) was 34.7 [27.8‐36.2]. All patients had intermediate‐risk prostate cancer. Small prostate and deep pelvis were given as reasons for abandoning ORP in five cases (83.3%), with four of these also attributing increased BMI as a factor. Extensive mesh from previous bilateral inguinal hernia repair was cited as the reason for abandonment in the remaining patient. One patient had commenced androgen deprivation therapy following abandoned ORP. Extensive retropubic adhesions were noted at the time of RARP in five of six patients, with intraoperative complication of small bladder lacerations encountered in the patient with prior mesh hernia repair. The median time from abandoned ORP to RARP was 128 days [40‐216]. Median operating time was 160 minutes [139‐190] and estimated blood loss was 225 mL [138‐375]. Negative margins were obtained in four of six cases, with further salvage treatment being required in one case at a median follow‐up duration of 10.5 months [6.5‐25.3]. Conclusion Abandonment of ORP is an uncommonly reported event, however, in this small case series, we demonstrate that, in the hands of experienced surgeons, RARP is a safe and technically feasible alternative in such cases. Increased BMI, small prostate size and pelvic anatomical constraints appear to be common catalysts for abandonment of open surgery in this cohort. Identifying these high‐risk patients early and considering referral to robotic centers may be preferred.

One year of ground-based night-time Raman lidar observations has been analysed under the Optimization of Aerosol Seeding In rain enhancement Strategies (OASIS) project, in order to characterize the aerosol particle properties over a rural site in the United Arab Emirates. In total, 1130 aerosol particle layers were detected during the 1-year measurement campaign which took place between March 2018 and February 2019. Several subsequent aerosol layers could be observed simultaneously in the atmosphere up to 11 km. The observations indicate that the measurement site is a receptor of frequent dust events, but predominantly the dust is mixed with aerosols of anthropogenic and/or marine origin. The mean aerosol optical depth over the measurement site ranged at 0.37 ± 0.12 and 0.21 ± 0.11 for 355 and 532 nm, respectively. Moreover, mean lidar ratios of 43 ± 11 sr at a wavelength of 355 nm and 39 ± 10 sr at 532 nm were found. The average linear particle depolarization ratio measured over the course of the campaign was 15 ± 6 % and 19 ± 7 % at the 355 and 532 nm wavelengths, respectively. Since the region is both a source and a receptor of mineral dust, we have also explored the properties of Arabian mineral dust of the greater area of the United Arab of Emirates and the Arabian Peninsula. The observed Arabian dust particle properties were 45 ± 5 (42 ± 5) sr at 355 (532) nm for the lidar ratio, 25 ± 2 % (31 ± 2 %) for the linear particle depolarization ratio at 355 (532) nm, and 0.3 ± 0.2 (0.2 ± 0.2) for the extinction-related Ångström exponent (backscatter-related Ångström exponent) between 355 and 532 nm. This study is the first to report comprehensive optical properties of the Arabian dust particles based on 1-year long observations, using to their fullest the capabilities of a multi-wavelength Raman lidar instrument. The results suggest that the mineral dust properties over the Middle East and western Asia, including the observation site, are comparable to those of African mineral dust with regard to the particle depolarization ratios, but not for lidar ratios. The smaller lidar ratio values in this study compared to the reference studies are attributed to the difference in the geochemical characteristics of the soil originating in the study region compared to northern Africa.

Abstract Background Technological advances have driven huge change in educational practices though concerns exist about a lack of evidence informing this change, in particular with social media-based medical education activities. The purpose of this study was to conduct a scoping review of WhatsApp use in medical education, narratively describing how it has been used and evaluated, and the theoretical considerations in relevant articles. Methods A modified 5-stage scoping review model was used. We performed 2 searches from February 2009 to February 2019 in EBSCO, SCOPUS, Web of Science, EMBASE, Medline PubMed and Google Scholar) using the term “WhatsApp” in all search fields. A 3-stage process for study selection was performed. Only original articles in English presenting original data about WhatsApp in medical education were included. The Kirkpatrick model of training evaluation was used to describe learning outcomes in included studies. Results Twenty-three articles were selected for review. Three strategies for WhatsApp use were apparent; primarily educational use with a pre-defined curriculum (n = 5), primarily educational use without a curriculum (n = 11), and primarily non-educational use (n = 7). Most of the educational studies used an online moderator and were in a local hospital or university department. Studies not primarily educational were national or international and seldom included an online moderator. All 5 studies with a pre-defined curriculum reported Kirkpatrick level 2 learner knowledge outcomes. A majority of the remaining studies only reported Kirkpatrick level 1 learner attitudes. Seven studies with 647 participants reported an improvement in learners’ knowledge following WhatsApp learning, though methodological weaknesses were apparent. Evidence for underlying learning theory considerations were scant throughout the studies. Conclusions WhatsApp is popular and convenient in medical education. Current published literature suggests it may also be effective as a medical learning tool. By combining the 3 strategies for WhatsApp use and the exploration-enactment-assessment integrated learning design framework, we propose an instant messenger design model for medical education. This may address the need for theory-driven instructional design in social media learning. Further research would clarify the role of WhatsApp and our design model in this area.

The French–German Arctic research base AWIPEV (the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research – AWI – and the French Polar Institute Paul Emile Victor – PEV) at Ny-Ålesund, Svalbard, is a unique station for monitoring cloud-related processes in the Arctic. For the first time, data from a set of ground-based instruments at the AWIPEV observatory are analyzed to characterize the vertical structure of clouds. For this study, a 14-month dataset from Cloudnet combining observations from a ceilometer, a 94 GHz cloud radar, and a microwave radiometer is used. A total cloud occurrence of ∼81 %, with 44.8 % multilayer and 36 % single-layer clouds, was found. Among single-layer clouds the occurrence of liquid, ice, and mixed-phase clouds was 6.4 %, 9 %, and 20.6 %, respectively. It was found that more than 90 % of single-layer liquid and mixed-phase clouds have liquid water path (LWP) values lower than 100 and 200 g m−2, respectively. Mean values of ice water path (IWP) for ice and mixed-phase clouds were found to be 273 and 164 g m−2, respectively. The different types of single-layer clouds are also related to in-cloud temperature and the relative humidity under which they occur. Statistics based on observations are compared to ICOsahedral Non-hydrostatic (ICON) model output. Distinct differences in liquid-phase occurrence in observations and the model at different environmental temperatures lead to higher occurrence of pure ice clouds. A lower occurrence of mixed-phase clouds in the model at temperatures between −20 and −5 ∘C becomes evident. The analyzed dataset is useful for satellite validation and model evaluation.

Understanding the distribution of aerosol layers is important for determining long-range transport and aerosol radiative forcing. In this study we combine airborne in situ measurements of aerosol with data obtained by a ground-based high spectral resolution lidar (HSRL) and radiosonde profiles to investigate the temporal and vertical variability of aerosol properties in the lower troposphere. The HSRL was deployed in Hyytiälä, southern Finland, from January to September 2014 as a part of the U.S. DOE ARM (Atmospheric Radiation Measurement) mobile facility during the BAECC (Biogenic Aerosols – Effects on Cloud and Climate) Campaign. Two flight campaigns took place in April and August 2014 with instruments measuring the aerosol size distribution from 10 nm to 5 µm at altitudes up to 3800 m. Two case studies with several aerosol layers present were selected from the flight campaigns for further investigation: one clear-sky and one partly cloudy case. During the clear-sky case, turbulent mixing ensured small temporal and spatial variability in the measured aerosol size distribution in the boundary layer, whereas mixing was not as homogeneous in the boundary layer during the partly cloudy case. The elevated layers exhibited larger temporal and spatial variability in aerosol size distribution, indicating a lack of mixing. New particle formation was observed in the boundary layer during the clear-sky case, and nucleation mode particles were also seen in the elevated layers that were not mixing with the boundary layer. Interpreting local measurements of elevated layers in terms of long-range transport can be achieved using back trajectories from Lagrangian models, but care should be taken in selecting appropriate arrival heights, since the modelled and observed layer heights did not always coincide. We conclude that higher confidence in attributing elevated aerosol layers to their air mass origin is attained when back trajectories are combined with lidar and radiosonde profiles.

Abstract In the last 100 years or so, much information has been accumulated on avian karyology, genetics, physiology, biochemistry and evolution. The chicken genome project generated genomic resources used in comparative studies, elucidating fundamental evolutionary processes, much of it funded by the economic importance of domestic fowl (which are also excellent model species in many areas). Studying karyotypes and whole genome sequences revealed population processes, evolutionary biology, and genome function, uncovering the role of repetitive sequences, transposable elements and gene family expansion. Knowledge of the function of many genes and non-expressed or identified regulatory components is however still lacking. Birds (Aves) are diverse and have striking adaptations for flight, migration and survival; they inhabit all continents and most islands. They also have a unique karyotype with ~ 10 macrochromosomes and ~ 30 microchromosomes that are smaller than other reptiles. Classified into Palaeognathae and Neognathae they are evolutionarily close, and a subset of reptiles. Here we overview avian molecular cytogenetics with reptilian comparisons, shedding light on their karyotypes and genome structure features. We consider avian evolution, then avian (followed by reptilian) karyotypes and genomic features. We consider synteny disruptions, centromere repositioning, and repetitive elements before turning to comparative avian and reptilian genomics. In this context, we review comparative cytogenetics and genome mapping in birds as well as Z- and W-chromosomes and sex determination. Finally, we give examples of pivotal research areas in avian and reptilian cytogenomics, particularly physical mapping and map integration of sex chromosomal genes, comparative genomics of chicken, turkey and zebra finch, California condor cytogenomics as well as some peculiar cytogenetic and evolutionary examples. We conclude that comparative molecular studies and improving resources continually contribute to new approaches in population biology, developmental biology, physiology, disease ecology, systematics, evolution and phylogenetic systematics orientation. This also produces genetic mapping information for chromosomes active in rearrangements during the course of evolution. Further insights into mutation, selection and adaptation of vertebrate genomes will benefit from these studies including physical and online resources for the further elaboration of comparative genomics approaches for many fundamental biological questions.

Ceilometer lidars are used for cloud base height detection, to probe aerosol layers in the atmosphere (e.g. detection of elevated layers of Saharan dust or volcanic ash), and to examine boundary layer dynamics. Sensor optics and acquisition algorithms can strongly influence the observed attenuated backscatter profiles; therefore, physical interpretation of the profiles requires careful application of corrections. This study addresses the widely deployed Vaisala CL31 ceilometer. Attenuated backscatter profiles are studied to evaluate the impact of both the hardware generation and firmware version. In response to this work and discussion within the CL31/TOPROF user community (TOPROF, European COST Action aiming to harmonise ground-based remote sensing networks across Europe), Vaisala released new firmware (versions 1.72 and 2.03) for the CL31 sensors. These firmware versions are tested against previous versions, showing that several artificial features introduced by the data processing have been removed. Hence, it is recommended to use this recent firmware for analysing attenuated backscatter profiles. To allow for consistent processing of historic data, correction procedures have been developed that account for artefacts detected in data collected with older firmware. Furthermore, a procedure is proposed to determine and account for the instrument-related background signal from electronic and optical components. This is necessary for using attenuated backscatter observations from any CL31 ceilometer. Recommendations are made for the processing of attenuated backscatter observed with Vaisala CL31 sensors, including the estimation of noise which is not provided in the standard CL31 output. After taking these aspects into account, attenuated backscatter profiles from Vaisala CL31 ceilometers are considered capable of providing valuable information for a range of applications including atmospheric boundary layer studies, detection of elevated aerosol layers, and model verification.

Atmospheric emissions, including particle number and size distribution, from a 726 MWth coal-fired power plant were studied experimentally from a power plant stack and flue-gas plume dispersing in the atmosphere. Experiments were conducted under two different flue-gas cleaning conditions. The results were utilized in a plume dispersion and dilution model taking into account particle formation precursor (H2SO4 resulted from the oxidation of emitted SO2) and assessment related to nucleation rates. The experiments showed that the primary emissions of particles and SO2 were effectively reduced by flue-gas desulfurization and fabric filters, especially the emissions of particles smaller than 200 nm in diameter. Primary pollutant concentrations reached background levels in 200–300 s. However, the atmospheric measurements indicated that new particles larger than 2.5 nm are formed in the flue-gas plume, even in the very early phases of atmospheric ageing. The effective number emission of nucleated particles were several orders of magnitude higher than the primary particle emission. Modelling studies indicate that regardless of continuing dilution of the flue gas, nucleation precursor (H2SO4 from SO2 oxidation) concentrations remain relatively constant. In addition, results indicate that flue-gas nucleation is more efficient than predicted by atmospheric aerosol modelling. In particular, the observation of the new particle formation with rather low flue-gas SO2 concentrations changes the current understanding of the air quality effects of coal combustion. The results can be used to evaluate optimal ways to achieve better air quality, particularly in polluted areas like India and China.

Rising tuition rates across colleges and universities contribute to the mounting financial strain on students. In response to rising costs, literature details that students seek to bolster their financial security by working additional hours per week, consequently leading to less available time. Previous studies have focused on the negative associations with GPA but not with in-class points. We observed this relationship within a 77-student 200-level genetics course and associated lab. Students working 20+ hours per week (59.7% of students) fared significantly worse on exams. These students scored significantly fewer total class points (p = 0.0089), exam points (p = 0.0255, p = 0.0028, p = 0.0311), and were more likely to incur a failed assignment sooner during the class than their counterparts (p = 0.0025). We observed these trends again in a 34-student 400-level immunology validation cohort (p = 0.0032). These findings represent the first quantitative analysis of employment vs. numerical biology exam and course scores. They are an important step toward identifying and treating the underlying factors associated with reduced STEM performance, retention, and well-being, and represent a forewarning of an approaching higher education crisis as institutions seek to retain and support underrepresented students.

Socioeconomically Marginalized Youth of Color (SMYoC) across global contexts tend to receive lower academic grades and standardized test scores due to systemic racism and classism. Research suggests that preschool enrollment is associated with short-term positive academic effects, yet little is known about how absenteeism relates to later academic outcomes particularly among SMYoC. This is a crucial area of study as preschool can help to close opportunity gaps and promote educational equity, yet absenteeism may buffer its benefits. The present study investigated long-term associations between preschool absenteeism and academic outcomes and whether later absenteeism mediates this association among SMYoC in New York City. Analyses revealed significant negative associations between preschool absenteeism and both math and English language arts achievement in third through sixth grades. Additionally, we found mediation effects of assessment grade absenteeism (i.e., absenteeism rate during the year of the assessment) in third and sixth grade math. Results highlight the importance of identifying strategies to increase preschool attendance rates to support academic outcomes.

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Urban boundary layers (UBLs) can be highly complex due to the heterogeneous roughness and heating of the surface, particularly at night. Due to a general lack of observations, it is not clear whether canonical models of boundary layer mixing are appropriate in modelling air quality in urban areas. This paper reports Doppler lidar observations of turbulence profiles in the centre of London, UK, as part of the second REPARTEE campaign in autumn 2007. Lidar-measured standard deviation of vertical velocity averaged over 30 min intervals generally compared well with in situ sonic anemometer measurements at 190 m on the BT telecommunications Tower. During calm, nocturnal periods, the lidar underestimated turbulent mixing due mainly to limited sampling rate. Mixing height derived from the turbulence, and aerosol layer height from the backscatter profiles, showed similar diurnal cycles ranging from c. 300 to 800 m, increasing to c. 200 to 850 m under clear skies. The aerosol layer height was sometimes significantly different to the mixing height, particularly at night under clear skies. For convective and neutral cases, the scaled turbulence profiles resembled canonical results; this was less clear for the stable case. Lidar observations clearly showed enhanced mixing beneath stratocumulus clouds reaching down on occasion to approximately half daytime boundary layer depth. On one occasion the nocturnal turbulent structure was consistent with a nocturnal jet, suggesting a stable layer. Given the general agreement between observations and canonical turbulence profiles, mixing timescales were calculated for passive scalars released at street level to reach the BT Tower using existing models of turbulent mixing. It was estimated to take c. 10 min to diffuse up to 190 m, rising to between 20 and 50 min at night, depending on stability. Determination of mixing timescales is important when comparing to physico-chemical processes acting on pollutant species measured simultaneously at both the ground and at the BT Tower during the campaign. From the 3 week autumnal data-set there is evidence for occasional stable layers in central London, effectively decoupling surface emissions from air aloft.