Parameterization Schemes Research Articles

An Improved Non‐Local Planetary Boundary Layer Parameterization Scheme in Weather Forecasting and Research Model Based on a 1.5‐Order Turbulence Closure Model

AbstractPlanetary boundary layer (PBL) modeling is a primary contributor to uncertainties in a numerical weather prediction (NWP) model due to difficulties in modeling the turbulent transport of surface fluxes. The Weather Research and Forecasting model (WRF) has provided many PBL schemes that may feature a non‐local transport component driven by large eddies or a one‐and‐half order turbulence closure model, but few of them possess the two features at once. In the present study, a turbulent kinetic energy (TKE)‐based eddy diffusivity/viscosity method is integrated into the non‐local Asymmetric Convective Model version 2 (ACM2) PBL scheme and implemented in WRF. The original first‐order eddy‐diffusivity term in ACM2 is discarded and an extra prognostic equation for TKE, which considers the tendency of TKE by buoyancy, wind shear, vertical transport, and dissipative processes, is supplied to calculate the diffusivity/viscosity. Non‐local transport is modeled the same as ACM2 using the transilient matrix method. Idealized tests using prescribed surface heat flux and roughness length are performed. TKE‐ACM2 displays advantages over the PBL scheme developed by Bougeault and Lacarrère (hereinafter referred to as Boulac) and ACM2 in the wind speeds (WS) profile because it better matches large‐eddy simulations results in the surface momentum flux. Real case simulations show that TKE‐ACM2 generally outperforms in the diurnal vertical profiles of WS under stable conditions. TKE‐ACM2 also produces a better alignment under moderately unstable conditions in the early nighttime at the urban LiDAR station. However, the model exhibits discrepancies more apparently under a more unstable condition during the winter daytime.

A family of spectral conjugate gradient methods with strong convergence and its applications in image restoration and machine learning

In this paper, we propose a family of spectral conjugate gradient methods for solving unconstrained optimization problems. Specifically, we provide two classes of bounded spectral parameters to be chosen, design a new truncation scheme of the non-negative conjugate parameter and set a restart procedure in our search direction. Independently of the specific spectral parameter, conjugate parameter and line search criterion, we prove that our proposed family satisfies the sufficient descent condition. We also prove its strong convergence under mild assumptions and the weak Wolfe line search. Numerical comparisons with other methods demonstrate the outstanding performances of our algorithm for solving medium–large-scale unconstrained optimization, image restoration and machine learning problems.

Role of PBL and air-sea flux parameterization schemes in the forecast of super cyclone Amphan and ESCS Phailin in the cloud-resolving scale using WRF-ARW model

Role of PBL and air-sea flux parameterization schemes in the forecast of super cyclone Amphan and ESCS Phailin in the cloud-resolving scale using WRF-ARW model

A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)

A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)

Extended HYDRUS-1D freezing module emphasizes thermal conductivity schemes for simulation of soil hydrothermal dynamics

Soil thermal conductivity (λ) is required to investigate coupled heat and water transport in disciplines such as agriculture, hydrology and engineering. Parameterization schemes or models of λ are also the critical input parameter for various numerical simulation programs like the widely used HYDRUS, one of the most commonly used models for mimicking water, heat, and solute transport. However, λ has not received enough attention in HYDRUS, and it remains unclear how different λ schemes affect the simulated soil water and thermal regimes. Thus, we programmed 24 λ schemes (including two built-in schemes) used in mainstream land surface, hydrological, and soil–vegetation–atmosphere transfer models into HYDRUS-1D (freezing module) to assess the effects of different λ schemes on soil temperature and water content simulations under freezing–thawing. The results showed that the 24 λ schemes performed differently in the simulation of soil temperature within 1 m below ground, with eight λ schemes, i.e., de Vries 1963 scheme/DV1963 (R=0.99), Camillo and Schmugge 1981/CS1981 scheme (R=0.98), Desborough and Pitman 1998/DP1998 scheme (R=0.97), Cass et al. 1984/CS1984 scheme (R=0.96), Shmakin 1998/SA1998 scheme (R=0.95), Dharssi et al. 2009/DI2009 scheme (R=0.95), Becker et al. 1992/BB1992 scheme (R=0.95), Hubrechts 1998/HL1998 scheme (R=0.94), performing superiorly to the built-in λ schemes. This study highlights the importance of choosing appropriate λ schemes in soil water and heat simulations.

Non-excitation closed-loop identification based on hysteresis bias relay feedback

This paper proposes a closed-loop system identification method based on hysteresis loop bias relay feedback without using excitation. The method utilizes hysteresis loop bias relay instead of a controller to ensure the informativity of data without external excitation and with only noisy feedback. Additionally, this paper proposes a parameter scheme for the hysteresis loop bias relay to guide the selection of parameters more rationally, thus improving the accuracy of the identification model. Compared to recently proposed switching controller methods, the advantage of this method lies in the fact that it requires fewer samples and shortens data collection time. The method's effectiveness is verified through simulation comparisons with typical methods.

Parametric optimization scheme of energy dissipation and shock absorption for prefabricated concrete frame

The prefabricated concrete frame structure system has advantages such as short construction period and good seismic performance, but its deformation and energy dissipation capacity are poor under earthquake action, making it prone to damage. By improving the analysis and simulation functions of existing finite element analysis for prefabricated structures, the engineering applicability of the analysis algorithm has been improved. Then, a finite element model has been established for collaborative optimization, and a parameterized optimization scheme that meets the seismic reduction requirements has been obtained. The results show that the optimization method proposed in the study has a better effect in seeking the minimum cost, and meets the design requirements of the specification. The optimization scheme of prefabricated concrete frames designed by the research institute based on finite element analysis can efficiently optimize various parameters, greatly improving the structure energy dissipation and seismic performance.

Niche center identification differential evolution for multimodal optimization problems

Niching techniques are commonly incorporated into evolutionary computation (EC) algorithms to address multimodal optimization problems (MMOPs). Nevertheless, identifying proper individuals as niche centers remains the main challenge in niching techniques. Generally, niche centers should possess promising fitness (fitness aspect) and should be dispersedly distributed in different search regions (distance aspect). In this study, we propose a novel niching technique known as niche center identification (NCI) and integrate it with differential evolution (DE) for tackling MMOPs, termed NCIDE. In NCI, niche centers are first identified from both the fitness and distance aspects. Individuals that are not niche centers are added to their nearest niche centers to form niches. Moreover, we develop a niche-level archival-adaptive parameter scheme (NAAPS) to adaptively adjust the parameters at the niche level and reduce their sensitivity. Meanwhile, with the help of an archive, we can preserve the identified optima and reinitialize stagnant individuals for further exploration. The experimental results on the CEC2013 multimodal benchmark test suite demonstrate that NCIDE significantly outperforms several state-of-the-art multimodal algorithms, including multiple competition winners from CEC2015 and GECCO2017-GECCO2019. Finally, NCIDE is applied to solve multimodal nonlinear equation system (NES) problems to further illustrate its practical applicability.

An Investigation on Potential Dispersal of Airborne Pollen Over China and Their Impact on Climate as Ice Nuclei Using RegCM‐Pollen

AbstractPollen can serve as an effective ice‐nuclei (IN), altering cloud microphysical and radiative properties, thus precipitation and cloud life cycles. Here, a nationwide pollen emission inventory with a horizontal resolution of 5 km was established based on a parameterization scheme of mass balance of pollen grain fluxes surrounding the plant crowns, and using satellite observational data sets (including leaf area index and fractional vegetation cover) as well as pollen emission rates. The potential emission is then implemented in RegCM‐pollen model which treated pollen as aerosol tracers. Besides, pollen‐IN parameterization schemes were incorporated in RegCM‐pollen to simulate the interactions between pollen and ice clouds. Investigations show that the mean annual pollen emission in China is 2.65 × 107 grains m−2 yr−1, mainly distributed in the south and northeast of China. The IN magnitude is mainly determined by a combination of temperature and pollen concentration. Notably, an increasing number concentration of pollen grains produces opposite effects in Southern China (SC) and Northern China (NC). The weakened upward motion and vertical transport of water vapor in NC made ice clouds hardly form, resulting in cloud forcing (CF) of +0.86 W/m2. In contrast, it generates a CF of −0.84 W/m2 in SC mainly owing to expanded cloud cover. The changes in shortwave radiative forcing is more significant compared to longwave radiative forcing in the two regions. At the surface, the net radiative forcing in NC is +0.74 W/m2, while it is a −0.51 W/m2 in SC. Among them, downward shortwave radiative forcing is approximately twice that of upward longwave radiative forcing in SC and 1.4 times in NC. Surface temperature shows rising over NC, ranging from 0.05 to 0.25 K. In SC, it is primarily decreasing by −0.12 to −0.03 K. The pollen‐IN effect also causes a decline of precipitation in NC (−0.17 mm/day) and a rise in SC (0.09 mm/day). Our results suggest that the pollen effect on ice clouds is complex, yet significant in understanding its impact on radiation and climate of the atmosphere.

Sealing performance analysis of pressure controller in pressure core sampling for seafloor drill

In order to improve the working reliability of pressure controller in the pressure core sampling for the seafloor drill, the challenges faced by the pressure controller in the working phase are analyzed. The working parameters of Y-ring on the pressure-retaining performance are analyzed. The optimization scheme of the working parameters for Y-ring is obtained and verified by sea trial. The conclusions are as follows: The gap extrusion degree of Y-ring is proportional to the working pressure. When the working pressure exceeds 20 MPa, the increase rate of the maximum contact stress increases. Under the condition that the friction coefficient is 0.1–0.4, the safety margin of the maximum contact stress is proportional to the friction coefficient. When the friction coefficient increases from 0.4 to 0.5, the safety margin decreases. Under the condition that the interference is 0.66–0.76 mm, the growth rate of the maximum Mises stress is slow. when the interference is 0.7 and 0.76 mm, the safety margin decreases. When the extrusion gap is 0.4–0.6 mm, the increase trend of safety margin is more obvious. When the extrusion gap is 0.6 mm, the growth rate of the maximum Mise stress increases. The success rate of the sealing cap installation is about 80%.

Assimilation of Radar Reflectivity via a Full-Hydrometeor Assimilation Scheme Based on the WSM6 Microphysics Scheme in WRF 4D-Var

Abstract The microphysical parameterization scheme employed in four-dimensional variational data assimilation (4D-Var) plays an important role in the assimilation of humidity and cloud-sensitive observations. In this study, a newly developed full-hydrometeor assimilation scheme, integrating warm-rain and cold-cloud processes, has been implemented in the Weather Research and Forecasting (WRF) 4D-Var system. This scheme is based on the WRF single-moment 6-class microphysics scheme (WSM6). Its primary objective is to directly assimilate radar reflectivity observations, with the goal of evaluating its effects on model initialization and subsequent forecasting performance. Four assimilation experiments were conducted to assess the performance of the full-hydrometeor assimilation scheme against the warm-rain assimilation scheme. These experiments also investigated reflectivity assimilation using both indirect and direct methods. We found that the nonlinearity of the radar operator in the two direct reflectivity assimilation experiments requires more iterations for cost function reduction than in the indirect assimilation method. The hydrometeor fields were reasonably analyzed using the full-hydrometeor assimilation scheme, particularly improving the simulation of ice-phase hydrometeors and reflectivity above the melting layer. The assimilation of radar reflectivity led to improvements in short-term (0–3 h) precipitation forecasting with the full-hydrometeor assimilation scheme. Assimilation experiments across multiple case studies reaffirmed that assimilating radar reflectivity observations with the full-hydrometeor assimilation scheme accelerated model spinup and yielded enhancements in 0–3-h total accumulate precipitation forecasts for a range of precipitation thresholds.

Evaluation of Lightning Flash Rate Parameterizations in a Cloud‐Resolved WRF‐Chem Simulation of the 29–30 May 2012 Oklahoma Severe Supercell System Observed During DC3

AbstractEighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud‐resolved simulation of the 29–30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly‐developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model‐simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model‐simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor‐based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

Strong Skin Cooling and Its Impacts on Lake Thermal Processes in a Large Lake on the Tibetan Plateau

Abstract Skin cooling, wherein the surface temperature of a water body Tskin is lower than the temperature below the surface, is a widespread phenomenon. Previous studies have almost ignored this effect on the Tibetan Plateau (TP), despite the presence of thousands of lakes on the TP and the fact that extraordinary solar heating leads to very strong energy exchanges on the lake surfaces. This study utilizes in situ observations and MODIS-derived Tskin data at Lake Nam Co, one of the largest lakes on the TP, to quantify the skin cooling effect. The observed nighttime skin cooling is approximately 0.52°C on average, with the maximum of about 1°C, during the lake water turnover period (from October to mid-November), which obviously surpasses reported values for oceans (less than 0.4°C). To understand the impact of the skin cooling on the lake thermal processes, a skin cooling parameterization is validated and incorporated into the WRF-lake model. Simulations with the updated model show that accounting for the skin cooling process systematically lowers sensible and latent heat fluxes by a few watts per square meter, which yields an increase in water temperature by 0.45°C at the end of December and may delay the onset of lake freeze. Finally, we show that the inclusion of the skin cooling process in a lake model needs simultaneous adjustment of the parameterization of heat/water vapor transfer. Significance Statement Skin cooling is a widespread phenomenon for a water surface, and its intensity depends on the energy flux exchange of the water surface. The Tibetan Plateau possesses the presence of thousands of lakes, but early studies have ignored the skin cooling effect. We found that the nighttime skin cooling magnitude during the lake water turnover period in this region obviously exceeds reported values for oceans, due to the strong surface energy exchange in the Tibetan Plateau. Neglecting the skin cooling process may lead to systematic overestimation of turbulent heat fluxes and underestimation of water temperature. We highlight that accounting for this skin cooling process is crucial to select appropriate parameterization schemes for heat/water vapor transfer in lake thermal process modeling.

Submesoscale Vertical Heat Transport at the Kuroshio Extension: Characteristics and Mechanisms

AbstractSubmesoscale processes significantly influence the air‐sea interaction, heat budget and the distribution of physical and biogeochemical tracers in the upper‐ocean. We study the spatiotemporal characteristics and generation mechanisms of submesoscale vertical heat transport (SVHT) at the Kuroshio Extension using a submesoscale‐permitting simulation. Compared with the commonly used Boxcar and Hanning filters, the clean‐cut feature of the Butterworth filter in the wavenumber domain makes it a proper filter to diagnose SVHT. SVHT is systematically upward, peaking in winter. Through causality analysis, we find that, among the basic factors (mixed layer depth, strain rate, surface wind stress, and horizontal buoyancy gradient) from the conventional submesoscale generation mechanism scalings, mixed layer depth plays the leading role in modulating the intraseasonal variation of SVHT. Using the budget of submesoscale temperature variance and causality analysis, we find that advection also plays an important role in regulating SVHT. This work suggests that the choice of appropriate spatial filter is important for SVHT diagnosis and including advection may help improve submesoscale parameterization schemes.

An effective parameterization of broadband ocean surface albedo applicable to all skies

The ocean surface albedo (OSA) is an important parameter in ocean and climate models for air-sea heat flux calculations. Current OSA schemes are either too simple, making them only suitable for clear sky conditions, or too complex, because they depend on parameters that are not often measured in conventional ocean observations. Using radiation observations at a fixed offshore platform, we propose a simple but effective parameterization scheme of OSA, in which the broadband OSA is an analytical function of both the solar zenith angle and atmospheric transparency. It depends only on the downward shortwave radiation measured at the ocean surface and applies to all sky conditions. During our 15-month radiation observations, the correlation coefficient between the calculated OSA and the observations reached 0.90 for all skies, and the root mean square deviation was 0.0130. Three other OSA observation datasets are also introduced to verify this scheme.

Advancing state estimation for lithium-ion batteries with hysteresis through systematic extended Kalman filter tuning

Knowledge of remaining battery charge is fundamental to electric vehicle deployment. Accurate measurements of state-of-charge (SOC) cannot be obtained directly and estimation methods must be used instead. This requires both a good model of a battery and a well-designed state estimator. Here, hysteretic reduced-order battery models and adaptive extended Kalman filter estimators are shown to be highly effective, accurate predictors of SOC. A battery model parameterisation framework is proposed, which enhances standardised methods to capture hysteresis effects. The hysteretic model is parameterised for three independent NMC811 lithium-ion cells and is shown to reduce voltage RMS error by 50% across 18 h automotive drive-cycles. Parameterised models are used alongside an extended Kalman filter, which demonstrates the value of adaptive filter parameterisation schemes. When used alongside an extended Kalman filter, adaptive covariance matrices yield highly accurate SOC estimates, reducing SOC estimation error by 85%, compared to the industry standard battery model.

The Design of a Parameterization Scheme for 137Cs Based on the WRF-Chem Model and Its Application in Simulating the Fukushima Nuclear Accident

Based on the Weather Research and Forecasting Model Coupled with Chemistry (WRF-Chem) atmospheric chemistry model, a parameterization scheme for the radioactive isotope caesium (137Cs), considering processes such as advection, turbulent diffusion, dry deposition, and wet deposition, was constructed, enabling the spatial distribution simulation of the concentration and deposition of 137Cs. The experimental simulation studies were carried out during the high emission period of the Fukushima nuclear accident (from 11 to 17 March 2011). Two sets of comparison experiments, with or without deposition, were designed, the effects of wind field and precipitation on the spatial transport and ground deposition of 137Cs were analyzed, and the influence of wind field and precipitation on 137Cs vertical transport was analyzed in detail. The results indicate that the model can accurately simulate the meteorological and 137Cs variables. On 15 March, 137Cs dispersed towards the Kanto Plain in Japan under the influence of northeastern winds. In comparison to the experiment without deposition, the concentration of 137Cs in the Fukushima area decreased by approximately 286 Bq·m−3 in the deposition experiment. Under the influence of updrafts in the non-deposition experiment, a 137Cs cloud spread upward to a maximum height of 6 km, whereas in the deposition experiment, the highest dispersion of the 137Cs cloud only reach a height of 4 km. Affected by the wind field, dry deposition is mainly distributed in Fukushima, the Kanto Plain, and their eastern ocean areas, with a maximum dry deposition of 5004.5 kBq·m−2. Wet deposition is mainly influenced by the wind field and precipitation, distributed in the surrounding areas of Fukushima, with a maximum wet deposition of 725.3 kBq·m−2. The single-station test results from the deposition experiment were better than those for the non-deposition experiment: the percentage deviations of the Tokyo, Chiba, Maebashi, and Naraha stations decreased by 61%, 69%, 46%, and 51%, respectively, and the percentage root mean square error decreased by 46%, 25%, 38%, and 48%, respectively.

An evaluation of the reliability of the Weather Research Forecasting (WRF) model in predicting wind data: a case study of Burundi

BackgroundThe Weather Research and Forecasting (WRF) Model is an exceptional software for mesoscale climate modeling. It is extensively used to simulate key meteorological variables, including temperature, rainfall, and wind.MethodsThis study thoroughly examined the effectiveness of the WRF model in generating precise wind data for assessing the potential of wind power in Burundi. A meticulous evaluation of various combinations of model physics parameterization schemes was conducted to ensure accuracy.By comparing the simulated data with measurements from four meteorological stations and utilizing statistical metrics such as root-mean-square error (RMSE) and bias, the accuracy of the WRF model was determined.Results The findings of the study uncovered that utilizing WRF Single-Moment 3-Class (WSM3) for microphysics, Grell-Devenyi ensemble for cumulus physics, and Yonsei University for planetary boundary layer yields highly accurate wind data results for Burundi.Furthermore, the WRF model was utilized to create detailed seasonal and annual mean wind maps with a high resolution. ConclusionThese maps demonstrated that the western part of Burundi experiences higher wind speeds (ranging from 4 to 9.7 m/s) during the dry seasons revealing the potential for wind energy harvesting in the different areas of Burundi.

Comparative assessment of WRF’s parameterization scheme combinations in assessing land-surface feedback flux and its drivers: a case study of Phailin tropical cyclone

Comparative assessment of WRF’s parameterization scheme combinations in assessing land-surface feedback flux and its drivers: a case study of Phailin tropical cyclone

Moving EMPS model for semipermeable two equal collinear interface cracks in dissimilar magneto-electro-elastic materials

The moving electric-magnetic polarization saturation (EMPS) model is studied for two equal collinear interface cracks in mode-III dissimilar magneto-electro-elastic (MEE) bimaterial under semipermeable crack face conditions. The closed-form solutions of all three possible cases of the proposed EMPS model are derived using the distributed dislocation technique (DDT) and singular integral method. An iterative scheme and explicit expressions of fracture parameters are used to implement the semipermeable crack-face conditions. The study of local energy release rate based on constant electric and magnetic breakdown strength-based saturated conditions concludes that increasing the mismatch of the MEE bimaterial can improve its fracture toughness.