Analysis of the Thermodynamic Phase Transition of Tracked Convective Clouds Based on Geostationary Satellite Observations

Clouds are liquid at temperature greater than 0°C and ice at temperature below −38°C. Between these two thresholds, the temperature of the cloud thermodynamic phase transition from liquid to ice is difficult to predict and the theory and numerical models do not agree: Microphysical, dynamical, and meteorological parameters influence the glaciation temperature. We temporally track optical and microphysical properties of 796 clouds over Europe from 2004 to 2015 with the space‐based instrument Spinning Enhanced Visible and Infrared Imager on board the geostationary METEOSAT second generation satellites. We define the glaciation temperature as the mean between the cloud top temperature of those consecutive images for which a thermodynamic phase change in at least one pixel is observed for a given cloud object. We find that, on average, isolated convective clouds over Europe freeze at −21.6°C. Furthermore, we analyze the temporal evolution of a set of cloud properties and we retrieve glaciation temperatures binned by meteorological and microphysical regimes: For example, the glaciation temperature increases up to 11°C when cloud droplets are large, in line with previous studies. Moreover, the correlations between the parameters characterizing the glaciation temperature are compared and analyzed and a statistical study based on principal component analysis shows that after the cloud top height, the cloud droplet size is the most important parameter to determine the glaciation temperature

Tobac 1.2: Towards a flexible framework for tracking and analysis of clouds in diverse datasets

We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two-or three-dimensional timevarying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the threedimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data. © 2019 Author(s)

Optical doping of nitrides by ion implantation

A series of rare earth elements (RE) were implanted in GaN epilayers to study the lattice site location and optical activity. Rutherford backscattering spectrometry in the channeling mode(RBS/C) was used to follow the damage behavior in the Ga sublattice and the site location of the RE. For all the implanted elements (Ce, Pr, Dy, Er, and Lu) the results indicate the complete substitutionality on Ga sites after rapid thermal annealing at 1000°C for 2 min. The only exception occurs for Eu, which occupies a Ga displaced site. Annealing at 1200°C in nitrogen atmosphere at a pressure of IGPa is necessary to achieve the complete recovery of the damage in the samples. After annealing the recombination processes of the implanted samples were studied by above and below band gap excitation. For Er implanted samples besides the 1.54 μm emission green and red emissions are also observed. Red emissions from 5D0→7F2 and 3P0→3F2 transitions were found in Eu and Pr implanted samples even at room temperature

A simple non-contact optical method to quantify in-vivo sweat gland activity and pulsation

Objective: Most methods for monitoring sweat gland activity use simple gravimetric methods, which merely measure the average sweat rate of multiple sweat glands over a region of skin. It would be extremely useful to have a method which could quantify individual gland activity in order to improve the treatment of conditions which use sweat tests as a diagnostic tool, such as hyperhidrosis, cystic fibrosis, and peripheral nerve degeneration. Methods: An optical method using an infrared camera to monitor the skin surface temperature was developed. A thermodynamics computer model was then implemented to utilize these skin temperature values along with other environmental parameters, such as ambient temperature and relative humidity, to calculate the sweat rates of individual glands using chemically stimulated and unstimulated sweating. The optical method was also used to monitor sweat pulsation patterns of individual sweat glands. Results: In this preliminary study, the feasibility of the optical approach was demonstrated by measuring sweat rates of individual glands at various bodily locations. Calculated values from this method agree with expected sweat rates given values found in literature. In addition, a lack of pulsatile sweat expulsion was observed during chemically stimulated sweating, and a potential explanation for this phenomenon was proposed. Conclusion: A simple, non-contact optical method to quantify sweat gland activity in-vivo was presented. Significance: This method allows researchers and clinicians to investigate several sweat glands simultaneously, which has the potential to provide more accurate diagnoses and treatment as well as increase the potential utility for wearable sweat sensors

Aerosol effects on deep convection: the propagation of aerosol perturbations through convective cloud microphysics

The impact of aerosols on ice- and mixed-phase processes in deep convective clouds remains highly uncertain, and the wide range of interacting microphysical processes is still poorly understood. To understand these processes, we analyse diagnostic output of all individual microphysical process rates for two bulk microphysics schemes in the Weather and Research Forecasting model (WRF). We investigate the response of individual processes to changes in aerosol conditions and the propagation of perturbations through the microphysics all the way to the macrophysical development of the convective clouds. We perform simulations for two different cases of idealised supercells using two double-moment bulk microphysics schemes and a bin microphysics scheme. The simulations cover a comprehensive range of values for cloud droplet number concentration (CDNC) and cloud condensation nuclei (CCN) concentration as a proxy for aerosol effects on convective clouds. We have developed a new cloud tracking algorithm to analyse the morphology and time evolution of individually tracked convective cells in the simulations and their response to the aerosol perturbations. This analysis confirms an expected decrease in warm rain formation processes due to autoconversion and accretion for more polluted conditions. There is no evidence of a significant increase in the total amount of latent heat, as changes to the individual components of the integrated latent heating in the cloud compensate each other. The latent heating from freezing and riming processes is shifted to a higher altitude in the cloud, but there is no significant change to the integrated latent heat from freezing. Different choices in the treatment of deposition and sublimation processes between the microphysics schemes lead to strong differences including feedbacks onto condensation and evaporation. These changes in the microphysical processes explain some of the response in cloud mass and the altitude of the cloud centre of gravity. However, there remain some contrasts in the development of the bulk cloud parameters between the microphysics schemes and the two simulated cases.</p

Voltage-programmable liquid optical interface

Recently, there has been intense interest in photonic devices based on microfluidics, including displays and refractive tunable microlenses and optical beamsteerers, that work using the principle of electrowetting. Here, we report a novel approach to optical devices in which static wrinkles are produced at the surface of a thin film of oil as a result of dielectrophoretic forces. We have demonstrated this voltage-programmable surface wrinkling effect in periodic devices with pitch lengths of between 20 and 240 µm and with response times of less than 40 µs. By a careful choice of oils, it is possible to optimize either for high-amplitude sinusoidal wrinkles at micrometre-scale pitches or more complex non-sinusoidal profiles with higher Fourier components at longer pitches. This opens up the possibility of developing rapidly responsive voltage-programmable, polarization-insensitive transmission and reflection diffraction devices and arbitrary surface profile optical devices

An improved representation of physical permafrost dynamics in the JULES land-surface model

PublishedJournal Article© Author(s) 2015. It is important to correctly simulate permafrost in global climate models, since the stored carbon represents the source of a potentially important climate feedback. This carbon feedback depends on the physical state of the permafrost. We have therefore included improved physical permafrost processes in JULES (Joint UK Land Environment Simulator), which is the land-surface scheme used in the Hadley Centre climate models. The thermal and hydraulic properties of the soil were modified to account for the presence of organic matter, and the insulating effects of a surface layer of moss were added, allowing for fractional moss cover. These processes are particularly relevant in permafrost zones. We also simulate a higher-resolution soil column and deeper soil, and include an additional thermal column at the base of the soil to represent bedrock. In addition, the snow scheme was improved to allow it to run with arbitrarily thin layers. Point-site simulations at Samoylov Island, Siberia, show that the model is now able to simulate soil temperatures and thaw depth much closer to the observations. The root mean square error for the near-surface soil temperatures reduces by approximately 30%, and the active layer thickness is reduced from being over 1 m too deep to within 0.1 m of the observed active layer thickness. All of the model improvements contribute to improving the simulations, with organic matter having the single greatest impact. A new method is used to estimate active layer depth more accurately using the fraction of unfrozen water. Soil hydrology and snow are investigated further by holding the soil moisture fixed and adjusting the parameters to make the soil moisture and snow density match better with observations. The root mean square error in near-surface soil temperatures is reduced by a further 20% as a result

Impact of model developments on present and future simulations of permafrost in a global land-surface model

There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon–climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth system models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land-surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock and a modification to the snow scheme; the sensitivity of permafrost to these new developments is investigated in this study. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. A comparison with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated; by contrast, with a poorly resolved soil at least 50 % of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14 and 19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost loss per degree of warming reduced from 1.5 million km2 °C−1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C−1 in the new model version. However, the near-surface permafrost area is still projected to approximately half by the end of the 21st century under the RCP8.5 scenario

An optoelectronic framework enabled by low-dimensional phase-change films.

Accepted author version. The definitive version was published in: Nature 511, 206–211 (10 July 2014) doi:10.1038/nature13487The development of materials whose refractive index can be optically transformed as desired, such as chalcogenide-based phase-change materials, has revolutionized the media and data storage industries by providing inexpensive, high-speed, portable and reliable platforms able to store vast quantities of data. Phase-change materials switch between two solid states--amorphous and crystalline--in response to a stimulus, such as heat, with an associated change in the physical properties of the material, including optical absorption, electrical conductance and Young's modulus. The initial applications of these materials (particularly the germanium antimony tellurium alloy Ge2Sb2Te5) exploited the reversible change in their optical properties in rewritable optical data storage technologies. More recently, the change in their electrical conductivity has also been extensively studied in the development of non-volatile phase-change memories. Here we show that by combining the optical and electronic property modulation of such materials, display and data visualization applications that go beyond data storage can be created. Using extremely thin phase-change materials and transparent conductors, we demonstrate electrically induced stable colour changes in both reflective and semi-transparent modes. Further, we show how a pixelated approach can be used in displays on both rigid and flexible films. This optoelectronic framework using low-dimensional phase-change materials has many likely applications, such as ultrafast, entirely solid-state displays with nanometre-scale pixels, semi-transparent 'smart' glasses, 'smart' contact lenses and artificial retina devices.Engineering and Physical Sciences Research Council (EPSRC)OUP John Fell Fun

Investigation of Cortisol Dynamics in Human Sweat Using a Graphene-Based Wireless mHealth System

Prompt and accurate detection of stress is essential to the monitoring and management of mental health and human performance. Considering that current methods such as questionnaires are very subjective, we propose a highly sensitive, selective, miniaturized mHealth device based on laser-enabled flexible graphene sensor to non-invasively monitor the level of stress hormones (e.g., cortisol). We report a strong correlation between sweat and circulating cortisol and demonstrate the prompt determination of sweat cortisol variation in response to acute stress stimuli. Moreover, we demonstrate, for the first time, the diurnal cycle and stress-response profile of sweat cortisol, revealing the potential of dynamic stress monitoring enabled by this mHealth sensing system. We believe that this platform could contribute to fast, reliable, and decentralized healthcare vigilance at the metabolic level, thus providing an accurate snapshot of our physical, mental, and behavioral changes