SPC Mesoscale Analysis Compared to Field-Project Soundings: Implications for Supercell Environment Studies

Two-hundred-fifty-seven supercell proximity soundings obtained for field programs over the central U.S. are compared to profiles extracted from the SPC mesoscale analysis system (the SFCOA) to understand how errors in the SFCOA and in its baseline model analysis system – the RUC/RAP – might impact climatological assessments of supercell environments. A primary result is that the SFCOA underestimates the low-level storm-relative winds and wind shear, a clear consequence of the lack of vertical resolution near the ground. The near-ground (≤ 500 m) wind shear is underestimated similarly in near-field, far-field, tornadic, and nontornadic supercell environments. The near-ground storm-relative winds, however, are underestimated the most in the near field and in tornadic supercell environments. Under-prediction of storm-relative winds is therefore a likely contributor to the lack of differences in storm-relative winds between nontornadic and tornadic supercell environments in past studies that use RUC/RAP-based analyses. Furthermore, these storm-relative wind errors could lead to an under emphasis of deep-layer SRH variables relative to shallower SRH in discriminating nontornadic from tornadic supercells. The mean critical angles are 5–15° larger and farther from 90° in the observed soundings than in the SFCOA, particularly in the near field, likely indicating that the ratio of streamwise to crosswise horizontal vorticity is often smaller than that suggested by the SFCOA profiles. Errors in thermodynamic variables are less prevalent, but show low-level CAPE to be too low closer to the storms, a dry bias above the boundary layer, and the absence of shallow near-ground stable layers that are much more prevalent in tornadic supercell environments.

Thermodynamic effects of Bardeen black hole surrounded by perfect fluid dark matter under general uncertainty principle

In this paper, the thermodynamics of Bardeen black hole surrounded by perfect fluid dark matter is investigated. We calculate the analytical expresses of corresponding thermodynamic variables, e.g. the Hawking temperature, entropy of the black hole. In addition, we derive the heat capacity to analyze the thermal stability of the black hole. We also compute the rate of emission in terms of photons through tunneling. By numerical method, an obvious phase transition behavior is found. Furthermore, according to the general uncertainty principle, we study the quantum corrections to these thermodynamic quantities and obtain the quantum-corrected entropy containing the logarithmic term. At last, we investigate the effects of the magnetic charge g, the dark matter parameter k and the generalized uncertainty principle parameter α on the thermodynamics of Bardeen black hole surrounded by perfect fluid dark matter under general uncertainty principle.

Towards the use of conservative thermodynamic variables in data assimilation: preliminary results using ground-based microwave radiometer measurements

This study aims at introducing two conservative thermodynamic variables (moist-air entropy potential temperature and total water content) into a one-dimensional variational data assimilation system (1D-Var) to demonstrate the benefit for future operational assimilation schemes. This system is assessed using microwave brightness temperatures from a ground-based radiometer installed during the field campaign SOFGO3D dedicated to fog forecast improvement. An underlying objective is to ease the specification of background error covariance matrices that are currently highly dependent on weather conditions making difficult the optimal retrievals of cloud and thermodynamic properties during fog conditions. Background error covariance matrices for these new conservative variables have thus been computed by an ensemble approach based on the French convective scale model AROME, for both all-weather and fog conditions. A first result shows that the use of these matrices for the new variables reduces some dependencies to the meteorological conditions (diurnal cycle, presence or not of clouds) compared to usual variables (temperature, specific humidity). Then, two 1D-Var experiments (classical vs. conservative variables) are evaluated over a full diurnal cycle characterized by a stratus-evolving radiative fog situation, using hourly brightness temperatures. Results show, as expected, that analysed brightness temperatures by the 1D-Var are much closer to the observed ones than background values for both variable choices. This is especially the case for channels sensitive to water vapour and liquid water. On the other hand, analysis increments in model space (water vapour, liquid water) show significant differences between the two sets of variables.

Fluctuations in heat engines

At the dawn of thermodynamics, Carnot's constraint on efficiency of heat engines stimulated the formulation of one of the most universal physical principles, the second law of thermodynamics. In recent years, the field of heat engines acquired a new twist due to enormous efforts to develop and describe microscopic machines based on systems as small as single atoms. At microscales, fluctuations are an inherent part of dynamics and thermodynamic variables such as work and heat fluctuate. Novel probabilistic formulations of the second law imply general symmetries and limitations for the fluctuating output power and efficiency of the small heat engines.} Will their complete understanding ignite a similar revolution as the discovery of the second law? Here, we review the known general results concerning fluctuations in the performance of small heat engines. To make the discussion more transparent, we illustrate the main abstract findings on exactly solvable models and provide a thorough theoretical introduction for newcomers to the field.

Slowdown in the Decay of Western North Pacific Tropical Cyclones Making Landfall on the Asian Continent

This study finds an increasing trend in the decay timescale (τ) of western North Pacific (WNP) tropical cyclone (TCs) making landfall on the Asian continent from 1966–2018. Statistical analysis of individual landfalling TCs shows that τ is significantly positively linked to soil wetness, 850-hPa relative vorticity and 200-hPa divergence, whereas it is weakly correlated with 700–500-hPa relative humidity and 850–200-hPa vertical wind shear. For TCs hitting southeastern China, the observed increasing τ is likely caused by enhanced 850-hPa vorticity and 200-hPa divergence. For TCs hitting southern China, increasing τ is likely driven by increased 850-hPa vorticity. By comparison, there are no significant trends in environmental variables over the eastern Indo-China Peninsula, and τ has not significantly changed in this region. Our results imply that the increasing τ of WNP landfalling TCs on the Asian continent are more likely caused by changes in dynamic variables than changes in thermodynamic variables.

Inter-comparison of ABL height estimates from different profiling sensors and models in the framework of HyMeX-SOP1

This paper reports results from an inter-comparison effort involving different sensors/techniques used to measure the Atmospheric Boundary Layer (ABL) height. The effort took place in the framework of the first Special Observing Period of the Hydrological cycle of the Mediterranean Experiment (HyMeX-SOP1). Elastic backscatter and rotational Raman signals collected by the Raman lidar system BASIL were used to determine the ABL height and characterize its internal structure. These techniques were compared with co-located measurements from a wind profiler and radiosondes and with ECMWF-ERA5 data. In the effort we consider radiosondes launched in the proximity of the lidar site, as well as radiosondes launched from the closest radiosonde station included in the Integrated Global Radiosonde archive (IGRA). The inter-comparison effort considers data from October 2012. Results reveal a good agreement between the different approaches, with values of the correlation coefficient R2 in the range 0.52 to 0.94. Results clearly reveals that the combined application of different techniques to distinct sensors’ and model datasets allow getting accurate and cross-validated estimates of the ABL height over a variety of weather conditions. Furthermore, correlations between the ABL height and other atmospheric dynamic and thermodynamic variables as CAPE, friction velocity and relative humidity are also assessed to infer possible mutual dependences.

Non-commutative space engine: A boost to thermodynamic processes

We introduce quantum heat engines that perform quantum Otto cycle and the quantum Stirling cycle by using a coupled pair of harmonic oscillator as its working substance. In the quantum regime, different working medium is considered for the analysis of the engine models to boost the efficiency of the cycles. In this work, we present Otto and Stirling cycle in the quantum realm where the phase space is non-commutative in nature. By using the notion of quantum thermodynamics, we develop the thermodynamic variables in non-commutative phase space. We encounter a catalytic effect (boost) on the efficiency of the engine in non-commutative space (i.e. we encounter that the Stirling cycle reaches near to the efficiency of the ideal cycle) when compared with the commutative space. Moreover, we obtained a notion that the working medium is much more effective for the analysis of the Stirling cycle than that of the Otto cycle.

Nested sampling for materials

We review the materials science applications of the nested sampling (NS) method, which was originally conceived for calculating the evidence in Bayesian inference. We describe how NS can be adapted to sample the potential energy surface (PES) of atomistic systems, providing a straightforward approximation for the partition function and allowing the evaluation of thermodynamic variables at arbitrary temperatures. After an overview of the basic method, we describe a number of extensions, including using variable cells for constant pressure sampling, the semi-grand-canonical approach for multicomponent systems, parallelizing the algorithm, and visualizing the results. We cover the range of materials applications of NS from the past decade, from exploring the PES of Lennard–Jones clusters to that of multicomponent condensed phase systems. We highlight examples how the information gained via NS promotes the understanding of materials properties through a novel way of visualizing the PES, identifying thermodynamically relevant basins, and calculating the entire pressure–temperature(–composition) phase diagram. Graphic abstract