Transparent and Conducting Tin Oxide Thin Films Deposited by Spray Pyrolysis

The chemical spray pyrolysis technique has been one of the major techniques to deposit a wide variety of materials in thin film form, for different applications. The most important control parameters for obtaining good quality thin film are the nature and temperature of the substrate, the composition of the precursor solution, the gas and solution flow rates and the deposition time. The paper presents the morphology, the electrical and optical properties of tin oxide (SnO2) thin films deposited by spray pyrolysis technique onto glass substrates at 400 oC using SnCl2 as precursor and methanol as solvent. The change in the grain shapes and orientation is presented based on SEM data. The minimum sheet resistance of 21.4 Ω/sqr was obtained, being the lowest value reported in the literature for these materials. Optical transmittance in the range of 58-85 % has been obtained for the prepared films

Selective Growth of 1D Nanostructures Oxide Materials Using PDMS Stamp

The approach for selective growth of 1D nanostructured oxide materials using poly (dimethylsiloxane) (PDMS) stamp consists of using microcontact printing, as such the soft lithography technique, for transferring the pattern of ZnO film on a substrate, followed by the hydrothermal growth of 1D nanowires on patterned areas. The nanowires have been grown in aqueous solutions of zinc nitrate at temperature at 95 °C. The wettability of the glass and of the Si/SiO2 substrates was investigated by contact angle measurements. The morphology of the nanostructures obtained was characterized by optical microscopy and scanning electron micoscopy

Inter-model comparison of sub-seasonal tropical variability in aquaplanet experimets: effect of a warm pool

This study compares the simulation of sub-seasonal tropical variability by a set of six state-of-the-art AGCMs in two experiments in aqua-planet configuration: a zonally-symmetric experiment, and an experiment with a warm pool centered on the equator. In all six models, the presence of the warm pool generates zonal asymmetries in the simulated mean states in the form of a “Gill-type” response, made more complex by feedbacks between moisture, convective heating and circulation. Noticeable differences appear from one model to another. Only half the models simulate mean low-level equatorial westerlies over the warm pool area. The presence of the warm pool can also favor the development of large-scale variability consistent with observed Madden-Julian Oscillation (MJO) characteristics, but this happens only in half the models. Our results do not support the idea that the presence of the warm pool and/or of mean low-level equatorial westerlies are sufficient conditions for MJO-like variability to arise in the models. Comparing spectral characteristics of the simulated Convectively Coupled Equatorial Waves (CCEWs) in the aquaplanet experiments and the corresponding coupled atmosphere-ocean (i.e. CMIP) and atmosphere-only (i.e. AMIP) simulations, we also show that there is more consistency for a given model across its configurations, than for a given configuration across the six models. Overall, our results confirm that the simulation of sub-seasonal variability by given model is significantly influenced by the parameterization of sub-grid physical processes (most-likely cloud processes), both directly and through modulation of the mean state

Significant benefits of AIP testing and clinical screening in familial isolated and young-onset pituitary tumors

Context Germline mutations in the aryl hydrocarbon receptor-interacting protein (AIP) gene are responsible for a subset of familial isolated pituitary adenoma (FIPA) cases and sporadic pituitary neuroendocrine tumors (PitNETs). Objective To compare prospectively diagnosed AIP mutation-positive (AIPmut) PitNET patients with clinically presenting patients and to compare the clinical characteristics of AIPmut and AIPneg PitNET patients. Design 12-year prospective, observational study. Participants & Setting We studied probands and family members of FIPA kindreds and sporadic patients with disease onset ≤18 years or macroadenomas with onset ≤30 years (n = 1477). This was a collaborative study conducted at referral centers for pituitary diseases. Interventions & Outcome AIP testing and clinical screening for pituitary disease. Comparison of characteristics of prospectively diagnosed (n = 22) vs clinically presenting AIPmut PitNET patients (n = 145), and AIPmut (n = 167) vs AIPneg PitNET patients (n = 1310). Results Prospectively diagnosed AIPmut PitNET patients had smaller lesions with less suprasellar extension or cavernous sinus invasion and required fewer treatments with fewer operations and no radiotherapy compared with clinically presenting cases; there were fewer cases with active disease and hypopituitarism at last follow-up. When comparing AIPmut and AIPneg cases, AIPmut patients were more often males, younger, more often had GH excess, pituitary apoplexy, suprasellar extension, and more patients required multimodal therapy, including radiotherapy. AIPmut patients (n = 136) with GH excess were taller than AIPneg counterparts (n = 650). Conclusions Prospectively diagnosed AIPmut patients show better outcomes than clinically presenting cases, demonstrating the benefits of genetic and clinical screening. AIP-related pituitary disease has a wide spectrum ranging from aggressively growing lesions to stable or indolent disease course

New Cloud System Metrics to Assess Bulk Ice Cloud Schemes in a GCM

International audienceBulk microphysical properties of ice clouds, such as fall speed and ice crystal size distribution, strongly impact the life time and the radiative effects of these clouds. Three coherent bulk ice schemes, with fall speed and effective ice crystal diameter depending on both ice water content and temperature, have been constructed from published parameterizations. We present a novel upper tropospheric cloud system concept to study the impact of these schemes on the LMDZ climate simulations. For this evaluation, cloud data from hyperspectral infrared sounders Atmospheric InfraRed Sounder and IR Atmospheric Sounding Interferometer are used, because they include cirrus with visible optical depths as low as 0.2. The analogous satellite observation simulator, developed for this purpose, is also presented. The cloud system concept, applied to the data and to the simulator outputs, allows a process‐oriented evaluation. In general, the new bulk ice schemes lead to a better agreement with the cloud data, in particular concerning the cloud system property distributions and the relation between cloud system properties and proxies mimicking the life stage and the convective depth. Sensitivity studies have demonstrated that both the introduction of the new schemes as well as the necessary adjustment of the relative width of the upper tropospheric subgrid water distribution lead to these improvements. Our studies also suggest to revise the formulation of the latter

Convective Boundary Layer Control of the Sea Surface Temperature in the Tropics

International audienceUsing successive versions of a global climate model, we show how convective transport to the free troposphere of the humidity evaporated at the surface or, reciprocally, entrainment of dry air from the free troposphere into the mixed layer, controls surface evaporative cooling and then sea surface temperature. This control is as important as the radiative effect of boundary layer clouds on radiation. Those aspects are shown to be improved when activating a mass flux representation of the organized structures of the convective boundary layer coupled to eddy diffusion, the so-called "thermal plume model," leading to an increased near-surface drying compared to the use of turbulent diffusion alone. Controlling detrainment by air properties from just above the boundary layer allows the thermal plume model to be valid for both cumulus and stratocumulus regimes, improving the contrast in near-surface humidity between the trade winds region and East Tropical oceans. Using pairs of stand-alone atmospheric simulations forced by sea surface temperature and of coupled atmosphere-ocean simulations, we show how the improvement of the surface fluxes that arise from this improved physics projects into an improvement of the representation of sea surface temperature patterns in the coupled model, and in particular into a reduction of the East Tropical Ocean warm bias. The work presented here led to the bias reduction in sea surface temperature in the Institute Pierre Simon Laplace coupled model, IPSL-CM6A, developed recently for the 6th phase of the Coupled Model Intercomparison Project, CMIP6. Plain Language Summary Global numerical models used to anticipate the future of our climate under global warming still suffer from significant errors, some of which are shared among all models. Among those shared errors is the tendency to predict too warm sea surface temperature over the east part of the tropical ocean in the tropics. We show how a better representation of the vertical convective transport in the first km above sea surface improves the representation of transport of dry air from the free troposphere. The drying of the near surface increases evaporation at the surface, that in turn contributes to significantly cool the sea surface in those regions

Cloud transition across the daily cycle illuminates model responses of trade cumuli to warming

International audienceThe response of trade-wind clouds to warming has long been a major source of uncertainty for climate change projections. By analyzing a set of climate models, we identify two contrasting types of model behaviors, which are evident both at the daily timescale and under global warming. These opposing behaviors depend on whether models can simulate cloud transitions—between very shallow and deeper cumuli—in response to changes in the convective mass flux. We show that the daily cycle can be used as a laboratory for assessing the physical credibility of trade cumulus responses to warming as simulated by climate models relative to observed cloud variations and processes. Our findings can also help guide future model development using observational benchmarking

Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections

International audienceDocumenting the uncertainty of climate change projections is a fundamental objective of the inter-comparison exercises organized to feed into the Intergovernmental Panel on Climate Change (IPCC) reports. Usually, each modeling center contributes to these exercises with one or two configurations of its climate model, corresponding to a particular choice of “free parameter” values, resulting from a long and often tedious “model tuning” phase. How much uncertainty is omitted by this selection and how might readers of IPCC reports and users of climate projections be misled by its omission? We show here how recent machine learning approaches can transform the way climate model tuning is approached, opening the way to a simultaneous acceleration of model improvement and parametric uncertainty quantification. We show how an automatic selection of model configurations defined by different values of free parameters can produce different “warming worlds,” all consistent with present-day observations of the climate system