Vertical Temperature Profiles Research Articles

Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands

Abstract. Meteorological fields calculated by numerical weather prediction (NWP) models drive offline chemical transport models (CTMs) to solve the transport, chemical reactions, and atmospheric interaction over the geographical domain of interest. HARMONIE (HIRLAM ALADIN Research on Mesoscale Operational NWP in Euromed) is a state-of-the-art non-hydrostatic NWP community model used at several European weather agencies to forecast weather at the local and/or regional scale. In this work, the HARMONIE WINS50 (cycle 43 cy43) reanalysis dataset at a resolution of 0.025° × 0.025° covering an area surrounding the North Sea for the years 2019–2021 was coupled offline to the LOTOS-EUROS (LOng-Term Ozone Simulation-EURopean Operational Smog model, v2.2.002) CTM. The impact of using either meteorological fields from HARMONIE or from ECMWF on LOTOS-EUROS simulations of NO2 has been evaluated against ground-level observations and TROPOMI tropospheric NO2 vertical columns. Furthermore, the difference between crucial meteorological input parameters such as the boundary layer height and the vertical diffusion coefficient between the hydrostatic ECMWF and non-hydrostatic HARMONIE data has been studied, and the vertical profiles of temperature, humidity, and wind are evaluated against meteorological observations at Cabauw in The Netherlands. The results of these first evaluations of the LOTOS-EUROS model performance in both configurations are used to investigate current uncertainties in air quality forecasting in relation to driving meteorological parameters and to assess the potential for improvements in forecasting pollution episodes at high resolutions based on the HARMONIE NWP model.

Using Icepack to reproduce ice mass balance buoy observations in landfast ice: improvements from the mushy-layer thermodynamics

Abstract. Icepack (v1.1.0) – the column thermodynamics model of the Community Ice CodE (CICE) version 6 – is used to assess how changing the thermodynamics from the Bitz and Lipscomb (1999) physics (hereafter BL99) to the mushy-layer physics impacts the model performance in reproducing in situ landfast ice observations from two ice mass balance (IMB) buoys co-deployed in the landfast ice close to Nain (Labrador) in February 2017. To this end, a new automated surface retrieval algorithm is used to determine the in situ ice thickness, snow depth, basal ice congelation and snow-ice formation from the measured vertical temperature profiles. Icepack simulations are run to reproduce these observations using each thermodynamics scheme, with a particular interest in how the different physics influence the representation of snow-ice formation and ice congelation. Results show that the BL99 parameterization represents well the ice congelation but underrepresents the snow-ice contribution to the ice mass balance. In particular, defining snow-ice formation based on the hydrostatic balance alone does not reproduce the negative freeboards observed for several days in the IMB observations, resulting in an earlier snow-flooding onset, a positive ice thickness bias and reduced snow depth variations. We find that the mushy-layer thermodynamics with default parameters significantly degrades the model performance, overestimating both the congelation growth and snow-ice formation. The simulated thermodynamics response to flooding, however, better represents the observations, and the best results are obtained when allowing for negative freeboards in the mushy-layer physics. We find that the mushy-layer thermodynamics produces a larger variability in congelation rates at the ice bottom interface, alternating between periods of exceedingly fast growth and periods of unrealistic basal melt. This pattern is related to persistent brine dilution in the lowest ice layer by the congelation and brine drainage parameterizations. We also show that the mushy-layer congelation parameterization produces significant frazil formation, which is not expected in a landfast ice context. This behavior is attributed to the congelation parameterization not fully accounting for the conductive heat flux imbalance at the ice–ocean boundary. We propose a modification of the mushy-layer congelation scheme that largely reduces the frazil formation and allows for better tuning of the congelation rates to match the observations. Our results demonstrate that the mushy-layer physics and its parameters can be tuned to closely match the in situ observations, although more observations are needed to better constrain them.

Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system

Abstract. Ocean models must be regularly updated through the assimilation of observations (data assimilation) in order to correctly represent the timing and locations of eddies. Since initial conditions play an important role in the quality of short-term ocean forecasts, an effective data assimilation scheme to produce accurate state estimates is key to improving prediction. Western boundary current regions, such as the East Australia Current system, are highly variable regions, making them particularly challenging to model and predict. This study assesses the performance of two ocean data assimilation systems in the East Australian Current system over a 2-year period. We compare the time-dependent 4-dimensional variational (4D-Var) data assimilation system with the more computationally efficient, time-independent ensemble optimal interpolation (EnOI) system, across a common modelling and observational framework. Both systems assimilate the same observations: satellite-derived sea surface height, sea surface temperature, vertical profiles of temperature and salinity (from Argo floats), and temperature profiles from expendable bathythermographs. We analyse both systems' performance against independent data that are withheld, allowing a thorough analysis of system performance. The 4D-Var system is 25 times more expensive but outperforms the EnOI system against both assimilated and independent observations at the surface and subsurface. For forecast horizons of 5 d, root-mean-squared forecast errors are 20 %–60 % higher for the EnOI system compared to the 4D-Var system. The 4D-Var system, which assimilates observations over 5 d windows, provides a smoother transition from the end of the forecast to the subsequent analysis field. The EnOI system displays elevated low-frequency (>1 d) surface-intensified variability in temperature and elevated kinetic energy at length scales less than 100 km at the beginning of the forecast windows. The 4D-Var system displays elevated energy in the near-inertial range throughout the water column, with the wavenumber kinetic energy spectra remaining unchanged upon assimilation. Overall, this comparison shows quantitatively that the 4D-Var system results in improved predictability as the analysis provides a smoother and more dynamically balanced fit between the observations and the model's time-evolving flow. This advocates the use of advanced, time-dependent data assimilation methods, particularly for highly variable oceanic regions, and motivates future work into further improving data assimilation schemes.

Monitoring Thermal Exchange of Hot Water Mass via Underwater Acoustic Tomography with Inversion and Optimization Method

Thermal exchange of underwater water mass caused by marine heat wave is a hot point of research recently. In particular, because the water temperature observation along hot water mass transportation is hard work. Acoustic tomography is an advanced method to measure water temperature variations via sound signal transmission with multi-station network sensing. The 5 kHz frequency acoustic tomography used for observing water temperature variations caused by ocean heat waves is interesting work. In this paper, the numerical simulation of hot water mass is completed first, then floatation and diffusion of hot water mass in a simulation are monitored by acoustic tomography. A new inversion optimization method is proposed to obtain hot water mass transportation variations at two-dimensional temperature vertical profile. The proposed inversion method adds a regularized mode matrix and the optimization method adds the model correlation matrix to improve the results quality. The accuracy of inversion optimization results is compared and discussed, where the mean temperature error is less than 0.4 °C. Sensing water temperature variation of marine heat waves is verified via acoustic signal transmission and improved inversion optimization method. The water dynamical process observation is an application of acoustic tomography, which can be further used observe underwater environmental characteristics.

Vertical profiles of temperature, wind, and turbulent fluxes across a deciduous forest over a slope observed with a UAV

To contribute to a better understanding of the dynamics of the atmosphere inside and above a forest, vertical profiles are flown with a remotely-controlled multicopter in the Steinkrug forest. This area is located over a slope in the Solling natural area in Lower Saxony (Germany), composed mostly of deciduous trees about 30 m tall. Fifteen vertical flights made near sunset between summer 2019 and spring 2020 were inspected from the surface to 100 m above ground level. These measurements provide information on the vertical structures of wind and temperature within and above the canopy, including the effects of shallow slope flows near the ground. Contrasting measurements downhill outside the forest were also made. The gathered data allow estimated profiles of the turbulent fluxes of sensible heat and momentum to be obtained by computing averages and fluctuations for layers of 5 m depth. A leaf area density profile in both leafy and leafless conditions could also be produced. The presence of a slope flow is inspected at both sites, and the applicability of existing theories is explored.

Aerodynamic properties of boundary layers along the roof of a large banana screenhouse under near-neutral atmospheric stability

Cultivation under screens and in screenhouses protects the crops from insects and extreme climate conditions and allows water saving. Previous studies considered the aerodynamic properties of boundary layers along two types of screens: a small shading thermal screen covering a hedgerow citrus orchard and a large 50-mesh, insect-proof screen covering a pepper plantation. To extend the previous results, a third type of screen was analysed in this study, a large flat-roof 17-mesh white woven shading screen covering a banana plantation. Vertical profiles of wind speed, air temperature, relative humidity, and friction velocity were measured by a lifting tower, and wind profiles were analysed under near-neutral atmospheric stability. Results show that normalised friction velocity, normalised roughness length, normalised zero plane displacement height and aerodynamic resistance are closer to the previous results of the large insect-proof screenhouse than those of the small shade net.

Temperature Inversion and Particulate Matter Concentration in the Low Troposphere of Cergy-Pontoise (Parisian Region)

This study aims to elucidate the influence of meteorological conditions on particle levels in Cergy-Pontoise. It explores the temporal variability of PM10 pollution days by associating them with the vertical temperature profile derived from conventional radiosondes from 2013 to 2022 (regional station). The results indicate that nearly 80% of exceedance days were associated with thermal inversions, primarily observed in winter and typically lasting 1 to 3 days. Analysis of winter thermal inversion characteristics suggests that those linked to pollution primarily occur near the ground, with higher intensity in December (12.1 °C) and lower in February (10.3 °C). Persistent inversions (extended nocturnal by diurnal inversion) account for 91.4% of the total inversions associated with high concentrations. Captive balloon soundings and temperature measurements at different altitudes were conducted during the winter of 2022/2023 to clarify thermal inversion in the Oise Valley at the center of Cergy-Pontoise. The results highlight three nocturnal wind circulation mechanisms in the valley, including downslope flow, circulation influenced by an urban heat island, and mechanical air evacuation under an inversion layer towards the less steep East side of the valley. Analysis of PM with the temperature gradient in the Oise Valley shows a significant correlation, suggesting an increase in concentrations during locally detected inversions and a decrease during atmospheric disturbance.

Dimensionless correlations of indoor thermal stratification in a non-enclosed large-space building under heating and cooling conditions

Indoor thermal stratification is a prevailing phenomenon in large-space buildings, which poses great pressure on their energy consumption and indoor built environment. This paper revealed the mechanism of indoor thermal stratification in a non-enclosed large-space building under heating and cooling conditions. It can be abstracted as a joint effect of the cold and hot air inflow (i.e., HVAC system and outdoor air infiltration), which are respectively depicted by two newly-defined Archimedes numbers (i.e., Arc and Arh). Then, we developed dimensionless correlations between the indoor thermal stratification (quantified by the dimensionless factor of the vertical temperature profile, CT) and the two streams of air inflow (quantified by Arc and Arh). For application, the dimensionless correlations can be coupled with our previously proposed theoretical model to accurately predict the air infiltration rate in a large-space building. Moreover, the dimensionless analysis reveals a principle of indoor vertical temperature profile control to minimize the buoyancy driving force of air infiltration in large-space buildings: Achieving a vertically uniform indoor thermal environment under heating condition and an effectively stratified indoor thermal environment under cooling condition. These findings help to provide practical guidelines to minimize buoyancy-driven air infiltration in large-space buildings.

The Sensitivity of Supercell Cold Pools to the Lifting Condensation Level and the Predicted Particle Properties Microphysics Scheme

Abstract Previous work found that cold pools in ordinary convection are more sensitive to the microphysics scheme when the lifting condensation level (LCL) is higher owing to a greater evaporation potential, which magnifies microphysical uncertainties. In the current study, we explore whether the same reasoning can be applied to supercellular cold pools. To do this, four perturbed-microphysics ensembles are run, with each using an environment with a different LCL. Similar to ordinary convection, the sensitivity of supercellular cold pools to the microphysics increases with higher LCLs, though the physical reasoning for this increase in sensitivity differs from a previous study. Using buoyancy budgets along parcel trajectories that terminate in the cold pool, we find that negative buoyancy generated by microphysical cooling is partially countered by a decrease in environmental potential temperatures as the parcel descends. This partial erosion of negative buoyancy as parcels descend is most pronounced in the low-LCL storms, which have steeper vertical profiles of environmental potential temperature in the lower atmosphere. When this erosion is accounted for, the strength of the strongest cold pools in the low-LCL ensemble is reduced, resulting in a narrower distribution of cold pool strengths. This narrower distribution is indicative of reduced sensitivity to the microphysics. These results suggest that supercell behavior and supercell hazards (e.g., tornadoes) may be more predictable in low-LCL environments.

Use of distributed temperature sensing (DTS) coupled to ground source heat exchangers for geological thermo-stratigraphic correlation

The thermal characterisation of a geosonde field, consisting of four boreholes at the ENEA-Casaccia Research Centre (Rome, Italy), was carried out by processing the temperature values measured by DTS (Distributed Temperature Sensing) fibre optics positioned vertically in each well. By correlating the vertical temperature profiles, it was possible to estimate the thermal conductivity of each stratigraphic level and the contribution of the groundwater on the heat exchange between ground and geothermal probes. The theoretical model has been confirmed by the experimental data obtained through direct measurement of thermal conductivity on soil/rock samples collected at different depths.In the first 10 m of depth, temperature variations are influenced by seasonal climatic fluctuations, the amplitude of which decreases with depth, to regularise and assume a linear trend, compatible with the movement of groundwater.The work carried out has shown that the area investigated is affected by the upwelling of hydrothermal fluids from the deep aquifer, which infiltrate the fractured lavas reaching the most superficial layers of the subsurface. The results of this research could be useful for estimating the geothermal potential of the areas within the ‘Cesano geothermal field’, whose lithotypes belong to the Sabatini volcanic province.

Improvement of Stable Atmospheric Boundary Simulation with High-Spatiotemporal-Resolution Nudging over the North China Plain

The WRF model often struggles to accurately replicate specific characteristics of the atmospheric boundary layer, particularly under highly stable conditions. In this study, we reconstructed an OBS-nudging module using meteorological data with high spatiotemporal resolution, then coupled it in the WRF model (WRF-OBS) to improve stable boundary layer (SBL) simulation over the North China Plain (NCP). The results showed that WRF-OBS improved the simulation of SBL characteristics and reduced the deviation from observations significantly. The correlations (R2) between WRF-OBS simulations and observations of 2 m temperature, relative humidity, and 10 m wind speed at 460 stations across the NCP were 0.72, 0.56, and 0.75, respectively, which were much higher than the values for results from the unassimilated WRF model (WRF-BS). The simulated vertical profiles of temperature, relative humidity, and wind were generally consistent with observations at Pingyuan station. The meteorological factors which caused heavy air pollution was also investigated based on WRF-OBS simulation. The SBL characteristics obtained from WRF-OBS showed that light wind persisted over the NCP region during the period of heavy pollution, and Pingyuan was affected by warm and humid air. Vertically, the persistent temperature inversion at Pingyuan station was one of the main drivers of the heavy pollution. The WRF-OBS simulation captured the characteristics of the two temperature inversion layers very well. The two inversion layers covered the NCP, with a horizontal scale of approximately 200 km, and created very stable conditions, preventing the vertical diffusion of pollutants and maintaining high PM2.5 concentrations.

How Can We Improve the Seamless Representation of Climatological Statistics and Weather Toward Reliable Global K‐Scale Climate Simulations?

AbstractToward the achievement of reliable global kilometer‐scale (k‐scale) climate simulations, we improve the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) by focusing on moist physical processes. A goal of the model improvement is to establish a configuration that can simulate realistic fields seamlessly from the daily‐scale variability to the climatological statistics. Referring to the two representative configurations of the present NICAM, each of which has been used for climate‐scale and sub‐seasonal‐scale experiments, we try to find the appropriate partitioning of fast/local and slow/global‐scale circulations. In a series of sensitivity experiments at 14‐km horizontal resolution, we test (a) the tuning of terminal velocities of rain, snow, and cloud ice, (b) the implementation of turbulent diffusion by the Leonard term, and (c) enhanced vertical resolution. These tests yield reasonable convection triggering and convection‐induced tropospheric moistening, and result in better performance than in previous NICAM climate simulations. In the mean state, double Intertropical Convergence Zone bias disappears, and the zonal contrast of equatorial precipitation, top‐of‐atmosphere radiation balance, vertical temperature profile, and position/strength of subtropical jet are reproduced dramatically better. Variability such as equatorial waves and the Madden–Julian oscillation (MJO) is spontaneously realized with appropriate spectral power balance, and the Asian summer monsoon, boreal‐summer MJO, and tropical cyclone (TC) activities are more realistically simulated especially around the western Pacific. Meanwhile, biases still exist in the representation of low‐cloud fraction, TC intensity, and precipitation diurnal cycle, suggesting that both higher spatial resolutions and further model development are warranted.

Analysis of Radon Near-Surface Measurements, Using Co-Located Ozone Data, Radio-Sounding Vertical Profiles, Sensible Heat Flux and Back-Trajectory Calculation

Simultaneous and co-located observations of near-surface Radon-222, ozone and meteorological parameters in a central Italy observation site operated by the University of L’Aquila (Italy), are used to study the physical drivers of the radon abundance during night-time hours. The knowledge of the potential temperature vertical gradient in the surface layer of nocturnal thermal inversion is made possible using co-located radio-sounding vertical profiles of pressure and temperature, thus making possible to indirectly infer the local surface flux of atmospheric radon (16 ± 6 mBq m−2 s−1). The dynamical removal due to turbulent convective motions is found to be the dominant controlling process, determining large differences in the near-surface radon abundance between stable and unstable conditions of the nocturnal Planetary Boundary Layer (PBL). Usual unstable PBL conditions during daytime hours induce an effective dynamical vertical dilution of surface radon, which rapidly reaches a quasi-steady-state abundance during mid-day and afternoon hours, with very low concentration values (5.1 ± 2.0 Bq m−3). Using back-trajectory reanalyses, estimates of local radon fluxes and vertical mixing efficiencies inside the PBL along the air mass latitudinal-longitudinal path and finally the irreversible radon loss due to radioactive decay, we have explored the fraction of daytime radon attributable to long-range advection in the continental near-mountain measurement site of L’Aquila (44 ± 18%).

A pressure-free long-time stable reduced-order model for two-dimensional Rayleigh-Bénard convection.

The present work presents a stable proper orthogonal decomposition (POD)-Galerkin based reduced-order model (ROM) for two-dimensional Rayleigh-Bénard convection in a square geometry for three Rayleigh numbers: 104 (steady state), 3×105 (periodic), and 6×106 (chaotic). Stability is obtained through a particular (staggered-grid) full-order model (FOM) discretization that leads to a ROM that is pressure-free and has skew-symmetric (energy-conserving) convective terms. This yields long-time stable solutions without requiring stabilizing mechanisms, even outside the training data range. The ROM's stability is validated for the different test cases by investigating the Nusselt and Reynolds number time series and the mean and variance of the vertical temperature profile. In general, these quantities converge to the FOM when increasing the number of modes, and turn out to be a good measure of accuracy. However, for the chaotic case, convergence with increasing numbers of modes is relatively difficult and a high number of modes is required to resolve the low-energy structures that are important for the global dynamics.

Planetary Boundary Layer Flow over Complex Terrain during a Cold Surge Event: A Case Study

Planetary boundary layer (PBL) flow over complex terrain during a cold surge event was investigated using 3-hourly radiosonde measurements in upwind, near ridge, and downwind locations of mountains in the northeastern part of Republic of Korea and using a high-resolution (333-m) numerical simulation. A cold surge occurred on 23 January 2018 and lasted for 4 days. We analyzed onset day of the cold surge when air temperature dropped rapidly. Analysis of the radiosonde data shows that the PBL was characterized by an adiabatic layer with strong capping inversion in early morning and evening as well as during daytime in the upwind and near-ridge sites. The PBL flow at the near-ridge site was strongest among three sites except at 0600 local standard time (LST) when the PBL flow in the lee was strongest. We performed high-resolution (333-m) numerical simulations using the Weather Research and Forecasting (WRF) model. The adiabatic PBL in the upwind site at 0600 LST was simulated, although its depth was underestimated. The model reproduced the strong low-level wind at 0600 LST and large wind shear during the daytime in the lee, but it did not capture the exact timing of the large wind shear. The model showed overall good performance in simulating the vertical profile of the virtual potential temperature and wind below 2 km above ground level at the three sites, with a high index of agreement (IOA) except for the wind at 1200 and 1500 LST in the lee. To examine the cause for the different behavior of PBL flow in the lee of mountains between 0600 LST and the daytime, we calculated the Froude number for PBL flow using radiosonde measurements based on reduced gravity shallow water (RGSW) theory. At 0600 LST, the upwind Froude number F0 was close to 1, while during the daytime, it was much lower than 1. The observed lee flow behavior was consistent with the flow regime change of a single layer over an obstacle with changing F0; the flow with a propagating lee jump changes into that with a stationary lee jump with decreasing F0. Numerical simulation shows that the steepening of streamlines of lee-wave field leads to a jump-like structure in the lee of mountains during the daytime.

Inverse Problem Protocol to Estimate Horizontal Groundwater Velocity from Temperature–Depth Profiles in a 2D Aquifer

A general and precise protocol that follows the standards of an inverse problem in engineering is proposed to estimate groundwater velocity from experimental lectures of temperature vertical profiles in a 2D aquifer. Several values of error in the temperature measurements are assumed. Since a large quantity of parameters and initial conditions influence the solution of this process, the protocol is very complex and needs to be tested to ensure its reliability. The studied scenario takes into account the input temperature of the water as well as the isothermal conditions at the surface and bottom of the aquifer. The existence of an input region, in which profiles develop to become linear, allows us to eliminate experimental measurements beyond such a region. Once the protocol is developed and tested, it is successfully applied to estimate the regional (lateral) groundwater velocity of the real aquifer and the result compared with estimations coming from the piezometric map.

Deduction of the Dimensionless Groups and Type Curves of Temperature Profiles in Two-Layer Soils with Water Flow at Depth

In the common hydrogeologic scenarios of horizontal groundwater flow and a water table below the surface, the steady-state 2D thermal field resulting from the coupling between water flow and heat flow and transport gives rise to a vertical temperature profile that develops progressively over a finite extent of the domain. Beyond this region, the temperature profiles are linear and independent of horizontal position. Such profiles are related to the groundwater velocity so they can be usefully used to estimate this velocity in the form of an inverse problem. By non-dimensionalization of the governing equations and boundary conditions, this manuscript formally derives the precise dimensionless groups governing the main unknowns of the problem, namely, (i) extent of the profile development region, (ii) time required for the steady-state temperature profile solution to be reached and (iii) the temperature–depth profiles themselves at each horizontal position of the development region. After verifying the mathematical dependencies of these unknowns on the deduced dimensionless groups, and by means of a large number of accurate numerical simulations, the type curves related to the horizontal extension of the development of the steady-state profiles, the characteristic time to develop such profiles and the dimensionless vertical temperature profiles inside the characteristic region are derived. These universal graphs can be used for the estimation of groundwater horizontal velocities from temperature–depth measurements.

Exploring the Use of Machine Learning to Improve Vertical Profiles of Temperature and Moisture

Abstract Vertical profiles of temperature and dewpoint are useful in predicting deep convection that leads to severe weather, which threatens property and lives. Currently, forecasters rely on observations from radiosonde launches and numerical weather prediction (NWP) models. Radiosonde observations are, however, temporally and spatially sparse, and NWP models contain inherent errors that influence short-term predictions of high impact events. This work explores using machine learning (ML) to postprocess NWP model forecasts, combining them with satellite data to improve vertical profiles of temperature and dewpoint. We focus on different ML architectures, loss functions, and input features to optimize predictions. Because we are predicting vertical profiles at 256 levels in the atmosphere, this work provides a unique perspective at using ML for 1D tasks. Compared to baseline profiles from the Rapid Refresh (RAP), ML predictions offer the largest improvement for dewpoint, particularly in the middle and upper atmosphere. Temperature improvements are modest, but CAPE values are improved by up to 40%. Feature importance analyses indicate that the ML models are primarily improving incoming RAP biases. While additional model and satellite data offer some improvement to the predictions, architecture choice is more important than feature selection in fine-tuning the results. Our proposed deep residual U-Net performs the best by leveraging spatial context from the input RAP profiles; however, the results are remarkably robust across model architecture. Further, uncertainty estimates for every level are well calibrated and can provide useful information to forecasters.

Modulation of tropical cyclone rapid intensification by mesoscale asymmetries

AbstractComputer model simulations are one of the most important tools in current use for understanding tropical cyclone (TC) formation and rapid intensification (RI). These include “idealized” simulations in which a TC‐like vortex is placed in a hypothetical environment with predefined sea surface temperature and vertical profiles of temperature, humidity, and wind that are either constant or slowly varying across a large domain. The vast majority of such simulations begin with a perfectly circular vortex as the precursor to a TC. However, most real TCs form or intensify while interacting with asymmetric wind fields either within or external to the vortex circulation. This study introduces a method to initialize idealized TC simulations with asymmetries, and investigates the extent to which such asymmetries might delay RI in favorable environments. It is shown that mesoscale asymmetries can delay RI and reduce the fastest rates of intensification, and that these effects are statistically significantly increased when relatively low values of vertical shear of the horizontal wind are present. In some cases the asymmetries tilt the vortex directly through advection. In other cases, the wind asymmetries increase the disorganization of the convection or increase the size of the inner‐core wind field, and thus make the weaker TC more susceptible to environmental wind shear. The results suggest that mesoscale asymmetries of the wind field could be useful predictors for delay of RI in otherwise favorable environments.

An NEA/OECD benchmark-experiment for the validation of CFD for mixing and thermal fatigue in T-junction dead leg flows

The current screening criteria for thermal fatigue used in isolated branch lines at nuclear power plants are based on simplified approaches, which, on one hand, tend to be overly conservative, and on the other hand, appear to miss important physics. This is demonstrated by the fact that a number of affected pipes were missed by the current screening methods.The purpose of the present work is to produce novel and accurate experimental data, which can be used for a benchmark of Computational Fluid Dynamics (CFD) in order to advance the prediction capabilities of thermal mixing and fatigue in dead leg T-junctions and improve the accuracy of the screening criteria. The ultimate value creation is increased safety and availability at nuclear power plants. This is of great interest and utmost importance to the nuclear reactor safety community.A new pressurized experimental setup of a T-junction has been designed and constructed for the purpose. The experimental setup, with a temperature difference of 120 °C, more closely resembles plant conditions than in earlier experiments. The boundary conditions in terms of the flowrates and temperatures are controlled and stable within their measurement uncertainty – a prerequisite for CFD-grade experiments.The novelty of the present work is measurements of the temperature fluctuations both in the near wall fluid mixing region and throughout the solid pipe wall material.It has been shown that the interaction between the swirl penetration of hot water and the stratified layer in the cold dead leg has an intermittent character and that random clusters of bursts of hot water penetrate into the stratification and the stagnant cold water below. The average time scale of this process is of the order of hundreds of seconds.The stratification between the hot and the cold water in the dead leg has also shown to have a low frequency oscillation of the order of 0.1 Hz, which wiggles in the circumferential direction. After hot water has penetrated downward and excited the instability, the temperature falls back to the initial one in a manner similar to a damped oscillation.The vertical temperature profiles have shown to be self-similar, for moderate temperatures, when scaled with the temperature difference between the hot and the cold water and with the penetration length.The penetration length increases with the velocity in the hot leg confirming earlier reported correlations.A small (less than 0.1 % of the hot main flow) cold leakage flow into the T-junction is sufficient to suppress the swirl penetration and substantially reduces the penetration length. However, the temperature fluctuations have a larger amplitude and range across the whole mixing zone. The fluid temperature fluctuations are shifted towards a more high frequency content, however, the low frequency nature of the swirl penetration is still present.The obtained novel dataset will be provided for a blind CFD benchmark exercise as part of an OECD/NEA project in 2023 and 2024.