Vertical Temperature Profiles Research Articles

Raindrop size distribution characteristics of pre-monsoon precipitation observed over eastern India

The knowledge of raindrop size distribution (DSD) is crucial for understanding the microphysical processes involved with the precipitation. Different empirical relationships established with DSD parameters, like radar reflectivity– rainfall rate (Z–R) relationships and shape–slope (μ–Ʌ) relationships, can progress the rainfall estimation algorithms and cloud modeling simulations. In the present study, long-term (2018–2021) measurements of a Laser Precipitation Monitor (LPM) disdrometer installed at the National Institute of Technology, Rourkela, India is used to investigate the DSD characteristics of pre-monsoon (March–May) rainfall. Along with the disdrometer data, auxiliary parameters like convective available potential energy (CAPE), total column water vapor (TCWV), vertical profiles of temperature and relative humidity from reanalysis data sets of ECMWF (European Centre for Medium-Range Weather Forecasts) fifth-generation reanalysis (ERA5) are also used in this study. Based on standardized rainfall anomaly, the pre-monsoon precipitation days are classified into strong, moderate, and weak rainy days, and they contributed to 58.69%, 32.7%, and 8.61% of total rainfall, respectively. The average DSD indicated noteworthy variations among strong, moderate, and weak rainy days with maximum (minimum) concentration of raindrops in strong (weak) rainy days. The mean value of rain rate (R), normalized intercept parameter (Nw), and mass-weighted mean diameter (Dm) is maximum during days of strong rainfall. Strong rainy days showed high-value CAPE, TCWV and vertical profile of relative humidity. The majority of R is contributed by moderate-sized raindrops with a significant difference in the Z–R and μ–Λ relationships among three types of rainy days.

Full-field temperature prediction in tunnel fires using limited monitored ceiling flow temperature data with transformer-based deep learning models

In practical tunnel scenarios, full-field coverage of sensors is impractical and costly. During a tunnel fire, the available information is constrained and localized, making the prediction of full-field smoke temperature distribution becoming a noteworthy challenge. This study proposes a transformer-based deep learning model to predict full-field smoke temperature distributions during fire incidents in real-time using limited temporal data from the sensors installed in localized regions below the ceiling, considering heat release rate of the fire source is unknown. The results indicate that proposed approach can predict the longitudinal temperature distribution throughout the tunnel with a length of 750 m by leveraging temperature data from limited sensors within a monitoring length of 210 m. It can further predict the vertical temperature profiles, and eventually estimate the full-field temperature distribution within the tunnel. The transformer model achieved R2 of 0.95 and 0.87 for longitudinal and vertical temperature distribution predictions, respectively. Under the influence of the self-attention mechanism, the transformer model has an advantage over the long short-term memory model in capturing global information, enhancing the accuracy of longitudinal temperature distribution predictions by 18.8 %. This study significantly contributes to effective emergency response and rescue strategies during tunnel fire incidents.

Limnological Characteristics and Relationships with Primary Productivity in Two High Andean Hydroelectric Reservoirs in Ecuador

Studies on limnology are essential to reservoir management; nevertheless, few are known about the limnological features of the Andean reservoirs in Ecuador. To overcome this limitation in the information, from December 2018 to December 2019, the limnological characteristics of El Labrado and Chanlud reservoirs in the Machángara river basin (Ecuador south) were examined. Using the light/dark bottles technique, the primary productivity (PP) of phytoplankton was studied in conjunction with (1) vertical profiles of oxygen concentrations, water temperature, nitrogen, phosphorus, alkalinity, and heterotrophic bacteria; (2) Secchi disk transparency; and (3) meteorological factors such as wind force, precipitation, and water level. Data indicate that both reservoirs are polymictic, with alkaline waters, low nutrients, and low PP rates. Despite this, a principal component analysis revealed that Chanlud exhibits higher nitrogen, alkalinity, heterotrophic bacteria, and PP values. In two approaches through multiple linear regression analysis, each per reservoir, the PP was explained mainly by water temperature, depth, light, heterotrophic bacteria, and meteorological parameters. The low concentrations of nutrients and the low residency time explain the low PP values. Likewise, the altitudinal factor (i.e., both reservoirs are 3400 m above sea level) and the low human perturbations in surrounding reservoir zones play a crucial role in explaining their poor PP. Notwithstanding the low metabolic rates, clear seasonal trends were observed in both reservoirs; the lowest PP rates occurred during the cold season. To our knowledge, this is the first limnological study of high Andean reservoirs in Ecuador. These findings should be part of Andean reservoir management protocols, contributing significantly to local conservation efforts. Additionally, they could be extrapolated as a frame of reference to similar eco-hydrological systems.

Algorithm-based segmentation of temperature-depth profiles: Examples from a mine

Temperature can be a valuable indicator for the identification and quantification of water fluxes in surface and subsurface water bodies. Therefore, the measurement and analysis of vertical temperature profiles is an important part of the characterization of a water body. Besides its easy application and widespread use, the analysis of temperature profiles can be complex due to its nature as a non-stationary measurement in a dynamic system. This work presents a data-based algorithm to process and segment vertical water temperature profiles avoiding subjectivity in the quantitative analysis of these profiles. Special emphasis is given to studying the reproducibility and precision of the method from data acquisition to data processing and analysis. The presented method provides a blueprint for adjacent applications and showcases the explanatory power of vertical profiles of water temperature to study water fluxes.

KHz Rate Fs/Ps-CARS Thermometry For Supersonic H_2/Air Combustion Studies

Accurate flow field measurements are essential to probe the phenomena involved in aeronautical engines undergoing high temperature and high turbulences. Indeed, reliable experimental datasets are needed to compare and validate numerical models. Among other laser diagnostics, Coherent Anti-stokes Raman Scattering (CARS) is a well-established non-linear spectroscopic technique used to probe harsh environments, since it provides non-intrusive local point measurements of chemical composition and temperature. We report here hybrid fs/ps Coherent Anti-Stokes Raman Scattering (fs/ps-CARS) thermometry campaign performed on N 2 in a supersonic H2 /air combustion. We used a mobile and compact laser architecture that shapes, synchronize and generates the laser beams necessary for CARS spectroscopy. The instrument was moved to a large-scale facility representative of a scramjet combustor (ONERA LAERTE/LAPCAT-II bench). H2 /air was injected during several burst at 0,12 and 0,15 equivalent ratios. Using kHz single-shot measurements combined with motorized translation stages, spatial and temporal resolution were obtained to probe the flow and the combustion at various positions upstream and downstream the hydrogen injectors. At these positions, horizontal and vertical temperature profiles were retrieved and compared with a numerical unsteady fluid dynamic simulation using delayed detached eddy simulations (DDES) developed at ONERA (CEDRE). The position of the combustion inside the combustion chamber could be identified through several horizontal and vertical profile temperature measurements. The signal-to-noise ratio of the detection was optimized by empirically adjusting the number of averaged laser shots based on the level of flow turbulence. For instance, far downstream the H2 injection, averaging over 10 to 100 pulses was possible as the heated air flow was steady. This was confirmed by the good agreement with numerical simulations although some distortion could still be observed and will be used to adjust the numerical simulation algorithm. However, averaging was no longer possible close to the injectors, where a highly turbulent H2 /air combustion was observed. Nevertheless, taking advantages of the high rate single-shot capacity of the spectroscopic technique, temperature could still be retrieved inside this area. These measurements provided a valuable experimental database for comparing and refining computational fluid dynamics modeling.

Acoustic Propagation in the Near‐Surface Martian Atmosphere

AbstractThis work introduces a comprehensive model of sound propagation on Mars, in light of the recent operation of several microphones on the Martian surface. The main outcome of this work is an operational acoustic model capable of simulating the sound field created by any source, at any location on the Martian surface, at any time. Expanding on the result of previous work (Gillier et al., 2024, https://doi.org/10.1029/2023je008257), we use the parabolic equation method for sound propagation in order to obtain the overall sound field produced by a source, in a given atmospheric composition and state, and accounting for ground properties. The resulting model enables the study of acoustics on Mars, and has the potential also to be used to probe the properties of the Martian environment using acoustic measurements with known sources. We investigate the effects of the Martian ground and the vertical profile of temperature and wind, on sound propagation. We find that the ground has a minor effect on sound propagation, and the wind profile strongly influences sound propagation as on Earth. However, the midday near surface temperature profiles on Mars are shown to cause refraction, which generates non‐negligible acoustic losses that are an order of magnitude stronger than typical refraction‐related acoustic losses on Earth. We show that the effect of the Martian atmospheric turbulence is to slightly reduce the acoustic losses due to refraction. Finally, we apply our model to show that refraction and atmospheric turbulence have a negligible effect on the propagation of sound from Ingenuity to the Perseverance rover.

Evaluation of heat transfer conditions during polydisperse gas–solid flow in an industrial fluidised bed reactor

Knowledge of heat transfer conditions in large-scale circulating fluidised bed reactors plays an essential role in their proper design and optimization of theirs. This work presents an evaluation of the heat transfer conditions taking into account the coordinate height of the furnace chamber and the fluidised bed flow regime in the reactor. Experimental tests used method and measurement technique that provides reliable temperature data. The vertical and horizontal temperature profiles were obtained at different 966MWth fluidised bed reactor operating conditions. Four characteristic areas can be distinguished in the furnace chamber: the bottom region with a high-temperature gradient from 10.6 °C/m to 22.7 °C/m; the dense region with a medium temperature gradient from 4.7 °C/m to 7.3 °C/m; the dilute area with the lowest temperature gradient from 0.7 °C/m to 3.1 °C/m and the exit region with a temperature gradient (4.3 °C ≤ grad T ≤ 9.6 °C) similar to dense region. The horizontal temperature profiles confirmed a core-annular flow structure inside the furnace chamber. At the pressure drop below 5 kPa, the low variation of average temperature (from ±0.7 °C to ±4.2 °C) inside the furnace chamber of the CFB reactor was observed. As a result of fly ash recirculation of 3.86 kg/s, the lowest temperature gradient 0.2 °C/m was achieved in the bottom region of the furnace chamber. In the range of bed material circulation rates of 32 to 68 were registered temperature fluctuations 115 °C. The experimental results also showed the variation of the bed temperature was small and kept at a very low level of ±13 °C whereas the fluidised bed reactor was operated with a fluidisation velocity range of 1.8 to 2.4. Obtained findings provide unique data on heat transfer conditions in industrial facilities and thus fill the gap in literature data for CFB reactors. Based on main tests carried out in a large-scale CFB reactor, it can be concluded that detailed experimental data on thermal conditions provide important information to validate guidelines and for verifying empirical relationships, which are used in the design, optimization, and scaling of heat transfer surfaces in commercial fluidised bed reactors.

Thermal response tests on boreholes in multi-layered ground with geothermal gradient

The design of ground source heat pump systems requires knowledge of the properties of the ground and boreholes, which are often measured through thermal response tests (TRTs). Conventional TRT analysis methods apply for uniform ground properties and undisturbed ground temperature. These assumptions become less valid for deeper boreholes, which penetrate more ground layers while the geothermal gradient becomes more important. In multi-layered ground without a geothermal gradient, conventional methods estimate the effective ground thermal conductivity kgr near the thickness-weighted average, but a geothermal gradient adds complications. In the present study simulated TRTs with quasi-steady-state and fully transient models demonstrate that the required test duration for conventional methods may become impractically large as the borehole depth increases. In general, this occurs when the dimensionless parameter |qratio| approaches 1 or less. This parameter represents the ratio of the externally imposed heat injection/extraction rate to the natural heat rate associated with the geothermal gradient. In these cases, the conventional methods do not estimate the thickness-weighted average value of kgr. On the other hand, a fully transient multi-layered ground model can determine the thickness-weighted average value of kgr. This model requires measured fluid vertical temperature profiles to estimate individual layer values of kgr within reasonable uncertainties.

Enhancing resilience in urban utility tunnels power transmission systems: Analysing temperature distribution in near-wall cable fires for risk mitigation

Urban utility tunnels are integral to the underground power transmission systems of cities. Enhancing the understanding of cable fire hazards within these tunnels is pivotal for fostering risk-resilient underground environments. This study delves into the temperature distribution characteristics of near-wall cable fires in urban utility tunnels. Employing a reduced-scale utility tunnel model, a series of fire experiments were conducted, focusing on the safety monitoring of horizontally arranged cables. Cone calorimeter tests were initially performed to ascertain the heat release rate of cable fires. The study meticulously considered cable spatial position parameters, such as cable height and near-wall distance, as dependent variables, and monitored real-time temperature changes within the utility tunnel under various fire scenarios.The findings reveal that the cable’s proximity to the wall significantly influences the fire temperature field. For instance, when a fire near the sidewall (at 1 cm) is compared to one in the middle of the tunnel (at 20 cm), the ceiling maximum temperature is reduced by 38.9 %. The sidewall’s limiting effect diminishes fire energy release, moderates vertical temperature decay, and enhances longitudinal temperature attenuation. The study introduces dimensionless mathematical models that account for the sidewall effect, quantifying the characteristics of fire-induced smoke temperature distribution in utility tunnels, such as ceiling maximum temperature rise, vertical smoke temperature profile, and longitudinal smoke temperature decay. The models’ predicted values closely align with the experimental results.These insights are pivotal for integrating cable numbers and spatial positioning in scenario-based fire prevention and mitigation strategies. The study’s implications extend to the design and operation of urban utility tunnels, emphasizing the need for strategic cable placement and the potential for mathematical models to inform risk mitigation measures. The research contributes to the advancement of sustainable urban development by providing a framework for enhancing the safety and resilience of critical infrastructure against fire hazards.

Influence of Radiation Stress on Upper-Layer Ocean Temperature under Geostrophic Condition

Wave-induced radiation stress (RS), as a primary driver of ocean currents influenced by waves, plays an important role in the response of upper ocean temperatures under typhoons. Previous studies have mainly focused on wave-generated currents and coastal currents in nearshore areas. This paper incorporates the geostrophic effect into the wave-induced radiation stress of wave-current interaction, and the effect of waves on the changes in upper ocean temperature (including sea surface temperature (SST) and mixed layer temperature) under typhoon Nanmadol (2022) is studied. The FVCOM-SWAVE model is used to conduct a preliminary numerical study in the western Pacific Ocean. The RS with the geostrophic effect increased the horizontal and vertical components, leading to an enhancement in turbulent mixing and a decrease in SST by up to 1.0 °C to 1.4 °C, which is closer to the SST obtained by OISST remote sensing fusion observation data. In the strong divergence domain, the direction of the vortex flow exhibits a more pronounced turn to the right, accompanied by an increase in water velocity. The vertical temperature profile of the ocean shows that the water below is perturbed by the RS component of the geostrophic effect, and the depth of the mixed layer increases by about 2 m, which is closer to the depth of the mixed layer observed by the Argo floats, indirectly enhancing the vertical mass transport of the ocean. In general, this shows that RS, which takes into account geostrophic effects, enhances the effect of waves on the water below, indirectly leading to lower temperatures in the upper ocean, and the simulated results align more closely with the observed data, offering valuable insights for enhancing marine numerical forecasting accuracy.

Global Stratospheric Properties of Gravity Waves From 1 Year of Radio Occultations

AbstractGravity waves (GW) transport momentum flux (MF) and energy across the lower, middle and upper atmosphere. Global Navigation Satellite System (GNSS) radio occultation (RO) is one of the measuring techniques used onboard satellites to provide vertical temperature profiles with global and permanent coverage. These retrievals may be applied in the study of GW. Most of the analysis methods provide absolute GWMF but are missing its net direction. This happens because the procedures can deduce the orientation but not the propagation sign of GW and hence the full direction of MF. We apply here a method that allows the net calculation with four close in space and time RO soundings (quartets). We use about 10,000 daily retrievals from 1 March 2022 to 28 February 2023 to study the seasonal and latitudinal characteristics of net GWMF in the height interval from 20 to 35 km. About 600 quartets were found. The calculated zonal MF and drag exhibited negative minima at middle and high latitudes during winter in the Southern Hemisphere. This well‐known characteristic is usually mainly assigned to orographic sources. A similar intensity in zonal MF and drag is found during the same season at low latitudes. Meridional components are generally less significant. Besides finding the correct sign of the GWMF and the corresponding forcing on the mean flow, the quartets method also allows the determination of the horizontal and vertical wavelengths, the amplitude and sign of the vertical wave phase velocity and the intrinsic frequencies. The global statistics of these parameters are shown and each one exhibits a similar distribution shape across latitude bands. Large differences in the frequency of cases in vertical phase velocity sign appear only at low and high positive latitudes. The most even distribution of GW intrinsic frequency is found at low latitudes. We estimate that absolute MF calculations by methods assuming only upward GW propagation may produce a bias not larger than 40%. The increase of satellite measuring devices achieved in the last years due to the release of new missions led to a high spatial and temporal density of profiles that may allow the attainment of net GWMF climatologies over a seasonal time scale and about 4,000 km latitude bands but this performance may be even improved if the amount of retrievals continues to rise.

Evaluation of a 4DVAR Assimilation System in the California Current at the SWOT Calibration/Validation Site

Abstract This study evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean (ECCO) data assimilation (DA) framework to a submesoscale-resolving model [Massachusetts Institute of Technology General Circulation Model (MITgcm), at 1-km grid resolution]. This is in preparation for future studies to understand and assimilate the novel swath measurements of sea surface height from the Surface Water and Ocean Topography (SWOT) satellite mission. The model domain is centered at the SWOT calibration/validation (CalVal) site, located 300 km offshore of Monterey Bay, California. We assimilate vertical profiles of temperature and salinity from a linear array of three SWOT prelaunch CalVal moorings, between September and December 2019. Two model solutions are analyzed: 1) a nonassimilating forward simulation termed “first-guess” and 2) an optimized solution that assimilates the in situ observations. Both runs are nested within the global 1/12° Hybrid Coordinate Ocean Model that uses Navy Coupled Ocean Data Assimilation (HYCOM/NCODA) analysis. We evaluate the performance by comparing the two model solutions against assimilated and withheld in situ observations. We show that by assimilating hydrographic data, the model performance over the first-guess solution is improved with an error-to-observation reduction of 30%–45% for temperature, 14%–41% for salinity, and 44%–56% for steric height. Over the study period, the average steric height error at the three assimilated moorings was 1.27 cm for the optimized solution versus 2.6 cm for the first-guess solution. A comparison to withheld glider observations shows that the optimized solution outperforms the first-guess solution with an error-to-observation reduction of approximately 38% in steric height (1.5 versus 2.4 cm). This study indicates, for the first time, that the MITgcm–ECCO framework can be successfully applied to the reconstruction of submesoscale ocean variability, via the nesting of a high-resolution regional domain into a global outer domain.

Lab on a Secchi disk: A prototype open‐source profiling package for low‐cost monitoring in aquatic environments

AbstractOwing to the high cost of commercial optical sensors, there is a need to develop low‐cost optical sensing packages to expand monitoring of aquatic environments, particularly in under‐resourced regions. Visual methods to monitor the optical properties of water, like the Secchi disk and Forel‐Ule color scale, remain in use in the modern era owing to their simplicity, low‐cost and long history of use. Yet, recent years have seen advances in low‐cost, electronic‐based optical sensing. Here, the designs of a miniaturized hand‐held device (mini‐Secchi disk) that measures the Secchi depth and Forel‐Ule color are updated. We then extend the device by integrating a small electronic sensing package (Arduino‐based) into the Secchi disk, for vertical profiling, combining historic and modern methods for monitoring the optical properties of water into a single, low‐cost sensing device, that measures positioning (GPS), light spectra, temperature, and pressure. It is charged and transfers data wirelessly, is encased in epoxy resin, and can be used to derive vertical profiles of spectral light attenuation and temperature, in addition to Secchi depth and Forel‐Ule color. We present data from a series of deployments of the package, compare its performance with commercially available instruments, and demonstrate its use for validation of satellite remotely sensed data. Our designs are made openly available to promote community‐based development and have potential in communicating and teaching science, participatory science, and low‐cost monitoring of aquatic environments.

A radiative–convective model computing precipitation with the maximum entropy production hypothesis

Abstract. All climate models use parameterizations and tuning in order to be accurate. The different parameterizations and tuning processes are the primary source of difference between models. Because models are tuned with present observations of Earth, they may not accurately simulate climates of other planets or palaeoclimate. A model with no adjustable parameter that happens to fit today's observations is probably more universal and should be more appropriate to model palaeoclimate. However, to our knowledge, such a model does not exist or is yet to be developed. This paper aims to improve a parameter-free radiative–convective model that computes a realistic temperature vertical profile to compute the water cycle, giving a value on average tropical precipitation. Although it is known that the radiative transfer constrains the order of magnitude of precipitation, no parameter-free model has yet been able to compute precipitation. Our model finds a precipitation value closer to observations than similar radiative–convective models or some general circulation models (GCMs).

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.

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. Significance Statement Thunderstorms typically produce “pools” of cold air beneath them owing in part to the evaporation of rain and melting of ice produced by the storm. Past work has found that in computer simulations of thunderstorms, the cold pools that form beneath thunderstorms are sensitive to how rain and ice are modeled in the simulation. In this study, we show that in the strongest thunderstorms that are capable of producing tornadoes, this sensitivity is reduced when the humidity in the lowest few kilometers above the surface is increased. Exploring why the sensitivity is reduced when the humidity increases provides a deeper understanding of the relationship between humidity and cold pool strength, which is important for severe storm forecasting.

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.

ПРИМЕНЕНИЕ ГЛУБИННЫХ НЕЙРОННЫХ СЕТЕЙ ДЛЯ ОБНАРУЖЕНИЯ ВЕРОЯТНЫХ ЗОН АТМОСФЕРНЫХ ОСАДКОВ И ГРОЗ

A method for the probabilistic identification of the precipitation and thunderstorm zones using artificial neural networks (ANNs), in particular, deep neural networks is described. The vertical profiles of temperature and humidity retrieved from satellite data are used as initial data. The ANN calculations have been validated using the ground-based observations in the Siberian region.

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.