Parameterization Schemes Research Articles

Impact of boundary layer parameterizations on simulated seasonal meteorology over North-East India

This study evaluated the accuracy of six planetary boundary layer (PBL) parameterization schemes in simulating two different seasons of pre-monsoon and monsoon in India's North-East region through the Weather Research and Forecasting (WRF) model. Twelve one-month simulations were conducted with the PBL schemes, six each for April (pre-monsoon) and July (monsoon), and the model outputs were compared against observations. Three non-local schemes, Asymmetric Convective Model (ACM2), Yonsei University (YSU), Shin-Hong (HONG), and three local schemes, Quasi Normal Scale Elimination (QNSE), Mellor Yamada Janjic (MYJ) and Mellor Yamada Nakanishi Nino (MYNN3), were tested. The meteorological variables of temperature, relative humidity (RH), wind speed, wind direction, and rainfall were evaluated, and the performance of each scheme for each meteorological variable is reported. The 2m temperature (T2) variable was well simulated by ACM2, MYJ in April, and YSU in July, while MYNN3 best simulated the 2m RH (RH2) during both seasons. 10m wind speed (WS10) and directions (WD10) were better simulated by MYNN3, HONG and YSU. HONG also best-simulated rainfall in April and MYJ in July. April and July being rainfall periods, an analysis of the schemes’ simulated rainfall frequency was also carried out. Moreover, the PBL schemes were also ranked, considering their combined performance with all the above meteorological parameters. While considering both the seasons and all meteorological variables, the scale-aware scheme, HONG, was the best scheme and can be used to simulate both seasons. Additionally, an in-depth analysis of surface and atmospheric parameters was also carried out to reason the simulated meteorology. QNSE expends the highest amount of its surface energy through surface evaporation, leading to the lowest surface skin temperature and T2 predictions. In contrast, MYNN3 produced the lowest mixing, which caused the moistest boundary layer, highest RH, cloud cover, and highly overestimated rainfall. Besides evaluation, which will help to choose a suitable PBL scheme for weather predictions in this region, this study also identifies the characteristics and deficiencies of PBL and surface layer schemes for improvement.

Comprehensive Geometric Parameterization and Computationally Efficient 3D Shape Matching Optimization of Realistic Stents

Abstract Flexible and compact shape representation schemes are essential for design optimization problems. Current shape representation schemes for coronary stent designs concern predominantly idealized or independent ring (IR) designs, which are outdated and only consider a small number of core design variables (such as strut width, height, and thickness) and ignore clinically critical design characteristics such as the number of connectors. No reports exist on the geometry parameterization of the latest helical stents (HS) that have more complex geometric designs than IR stents. Here, we present two new shape parameterization schemes to fully capture the 3D designs of contemporary IR and double-helix HS stents. We developed a 3D stent geometry builder based on 17 (IR) and 18 (HS) design variables, including strut width, thickness, height, number of connectors and rings, stent length, and strut centerline shape. The shape of the strut centerline was derived via a combination of NURBS, PARSEC, quarter circle, and straight line segments. Shape matching for complex 3D geometries, such as the contemporary stents within limited function evaluations, is not trivial and requires efficient parameterization and optimization algorithms. We used shape matching optimization with a limited function evaluation budget to test the proposed parameterization and two surrogate-assisted optimization algorithms relying on predictor believer and an expected improvement maximization formulation. The performance of these algorithms is objectively compared with a gradient-based optimization method to highlight their strengths. Our work paves the way for more realistic, full-fledged stent design optimization with structural and hemodynamic objectives in the future.

Microstructure Evolution and Cryogenic Impact Toughness Changes in Ce‐Containing Novel Cryogenic High‐Mn Austenitic Steel Weld Metals under Different Heat Inputs

The Ce‐containing novel cryogenic high‐Mn austenitic steel weld metals under different heat inputs are prepared by submerged‐arc welding to provide a satisfactory welding parameter scheme and further optimize its cryogenic impact toughness. The effect of heat input on microstructure, inclusion, and cryogenic impact toughness of weld metals are investigated via optical, scanning electron microscopy, electron backscatter diffraction, electronic probe microanalyzer, and cryogenic impact test. The results show that the dendrite arm spacing, segregation ratio of Mn, Si, and C elements and average effective grain size of the weld metals gradually increase, and the proportion of high‐angle grain boundaries decrease with the heat input increase from 11.91 to 20.24 kJ cm−1. The type of inclusions of weld metal with different heat inputs are all Ce2O3 and Ce2O2S. The number density of inclusions decreases monotonically from 5976 to 4912 mm−2, while the average size increases from 0.32 to 0.45 μm with the heat input increased. The increase in heat inputs consistently decreases the mean cryogenic impact toughness of weld metals from 123 to 102 J. The higher proportion of high‐angle grain boundaries and finer inclusions at lower heat input play the critical role in improving the cryogenic impact toughness.

Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses

Abstract While tropical cyclones (TCs) are axisymmetric vortices to the first order, they often exhibit noteworthy structural asymmetries. These often result from environmental vertical wind shear, which tilts the vortex and induces a wavenumber 1 pattern in the circulation and precipitation fields. Reanalyses and climate models have improved in representing the TC structure and climatology, but their relatively coarse resolution and dependence on parameterized physics cast doubt on their ability to capture the asymmetric TC structure. We perform the most comprehensive process-oriented assessment of TC asymmetry to date in reanalyses. Specifically, we analyze the composite shear-relative TC structure in ERA5 and Climate Forecast System Reanalysis (CFSR), which vary in their resolutions, physical parameterization suites, and data assimilation techniques. These structures are compared with aircraft reconnaissance radar observations. In agreement with the observations, the strongest tangential winds are usually found left-of-shear, while inner core rainfall, ascent, vortex tilt, and low-level inflow are favored directly downshear or in the downshear-left quadrant. Outer rainband convection generally peaks in the downshear-right quadrant. Thermodynamic asymmetries are also apparent, with anomalous low-level moisture right-of-shear, midlevel warmth in the upshear-right quadrant (uptilt), and cloud properties suggestive of a realistic precipitation life cycle from growth to fallout. We also decompose rainfall contributions from the convective parameterization and large-scale cloud schemes and highlight the roles of vorticity advection, buoyancy advection, and diabatic processes in driving asymmetric vertical motions in the inner core and outer rainband regions. Our results suggest that process-level studies of TC asymmetry and TC–wind shear interaction under future warming are viable using climate models. Significance Statement Asymmetries are common in tropical cyclones (TCs), influencing their intensity, track, and hazards. Vertical wind shear often plays a leading-order role in causing these asymmetries. It is uncertain how well asymmetric structures and processes are captured in reanalyses and global climate models (GCMs) with grid spacings of 0.25° and coarser. In this study, we first evaluate TC asymmetry in reanalyses, which have the benefit of being forced by observations. This helps to assess whether the resolutions associated with GCMs sufficiently capture asymmetric structures and processes and motivates upcoming work with free-running GCMs to study how TC asymmetry may change in a warming climate.

Laboratory studies on cloud electrification during ice crystal-graupel collisions: New parametrization scheme

Laboratory studies on cloud electrification during ice crystal-graupel collisions: New parametrization scheme

Positive Feedback between Partitioning of Carbonyl Compounds and Particulate Sulfur Formation during Haze Episodes.

Carbonyl compounds are important precursors of aqueous aerosols in the atmosphere, while their gas-particle partitioning behaviors and roles in particulate sulfur formation are poorly understood. In this study, we investigate the partitioning of five carbonyl compounds (formaldehyde, acetaldehyde, acetone, glyoxal, and methylglyoxal) during haze episodes in Beijing, China. On haze days, the values of field-derived effective Henry's law coefficients (KHf) on aerosols for these carbonyl compounds are 106-108 M atm-1, which are significantly higher (102-104 times) than those in pure water. Sulfate is observed to have a pronounced "salting-in" effect on these carbonyl compounds, resulting in at least 1-order-of-magnitude increase in their particle-phase concentrations. Parameterization schemes for their partitioning in the ambient aerosols were provided and applied to the multiphase chemical box model (RACM2-CAPRAM). When incorporated into the field-derived parametrization, the model significantly increased hydroxymethanesulfonate (HMS) production by 50-fold compared to using the parameters obtained in pure water, increasing from 2.6 × 10-2 to 1.23 μg m-3 h-1. The formed HMS can facilitate sulfate formation in turn through further oxidation by OH radicals and enhance aerosol hygroscopicity. These findings indicate a positive feedback loop between the partitioning of carbonyl compounds and particulate sulfur formation during haze episodes, providing new insights for controlling particulate pollution and reducing SO2 levels in urban areas.

The Brewer–Dobson circulation in the JRA‐3Q reanalysis and the impact of changes in model physical processes

AbstractThis study evaluates the climatology and trends of the Brewer–Dobson circulation (BDC) in the Japanese Reanalysis for Three Quarters of a Century (JRA‐3Q) reanalysis compared with those in the Japanese 55‐year reanalysis (JRA‐55) and ERA5 reanalyses. The spatial structure of the BDC shows good agreement among the reanalyses. However, zonal mean tropical upwelling near the lower stratosphere in JRA‐3Q is approximately 80% of that in JRA‐55 throughout the reanalysis period. The long‐term trend of BDC intensity for the period 1948–2022 showed a slight increase in JRA‐3Q and in JRA‐55, whereas that in ERA5 decreased. To investigate the cause of the difference in tropical upwelling between JRA‐3Q and JRA‐55, data assimilation sensitivity experiments were conducted by modifying the forecast model used in the data assimilation system. These results indicate that the difference in BDC intensity between JRA‐3Q and JRA‐55 can be primarily attributed to diabatic heating in the tropical troposphere produced in the forecast model. However, the difference between JRA‐3Q and ERA5 cannot be accounted for by diabatic heating in the forecast model. It is also found that the implementation of the non‐orographic gravity wave drag parameterisation scheme in the JRA forecast model is not the reason for the weaker BDC in JRA‐3Q.

Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm

Permanent magnet synchronous motor (PMSM) drive systems are receiving increasing attention due to their superior control quality and efficiency. Optimizing the control parameters are key to achieve the high-performance operation of PMSMs. Although heuristic algorithms demonstrate excellent optimization outcomes in simulations, there are still challenges in deploying optimization schemes in practical drives. In this study, a real-time online deployable control parameter optimization scheme is proposed. The optimization effect is evaluated through the system step response performance, and a framework for deploying optimization algorithms within the driver is developed. A fault suppression mechanism is also designed to mitigate overshoot and vibration issues caused by suboptimal solutions. The proposed scheme is validated on a rapid prototyping control platform. Experimental results confirm that the scheme exhibits good optimization performances across various operating conditions. The honey badger algorithm employed in this paper shows faster convergence and more stable optimization effects than other optimization algorithms. The optimization effect is improved by 2.2% and its performance in terms of consistency across multiple optimization results has increased by 40%.

Updates to NOAA’s Unified Forecast System’s Cumulus Convection Parameterization Scheme between GFSv16 and GFSv17

Abstract This study outlines the updates made to cumulus convection parameterizations between Global Forecast System, version 16 (GFSv16), and the forthcoming GFSv17 which will be the first global forecast application to become operational under the Unified Forecast System infrastructure. The updates, addressing known systematic errors and biases, incorporate innovations such as stochasticity, three-dimensional subgrid organizational effects, and a prognostic closure evolution. The changes are shown to improve tropical temperature/humidity biases, convective available potential energy (CAPE) forecasts, CONUS precipitation, and tropical variability. By examining individual updates’ impact on temperature, humidity profiles, and precipitation power spectra, we find that the new prognostic closure and stricter precipitation evaporation criteria alleviate a dry and cold bias in the tropical boundary layer and enhance precipitation variability in the tropics. Stricter triggering criteria also allow for more CAPE buildup, particularly over the tropics. The cumulus convection updates have a modest impact on precipitation skill scores over CONUS, but overall, there is an improvement when comparing GFSv16 and the latest GFSv17 prototype configurations, in particularly for larger thresholds. The study also highlights the challenges in developing convection parameterizations suitable for both coupled and uncoupled model configurations. Evaluation of the MJO shows varying responses to cumulus convection changes depending on whether the model is coupled with a dynamic ocean model.

Sensitivity of localized heavy rainfall in Northern Japan to WRF physics parameterization schemes

Sensitivity of localized heavy rainfall in Northern Japan to WRF physics parameterization schemes

Quantitation of Rainfall Retention Capacity for Small Reservoirs Considering Spatial Soil Moisture

To realize the estimation of rainfall retention capacity for small reservoirs considering spatial soil moisture, a rainfall retention capacity model and its parameter schemes have been developed in this study. An iterative trial solution method considering potential rainfall and soil moisture for the model constructed was proposed for efficient computation. The rainfall retention capacity of 32 pilot small reservoirs located in ungauged basins of Hunan province was calculated starting from 21 August 2023. In addition, a continuous calculation was carried out from 1 August to 30 September 2023 using the proposed method for Heping reservoir. The results show that the Pearson’s correlation coefficients between rainfall retention capacity and available reservoir capacity and soil moisture, are 0.36 and −0.64, respectively. Using Heping reservoir as an example, this study effectively characterized the dynamic change in its rainfall retention capacity, which ranged from 123.6 mm to 68 mm in August 2023. The analysis indicates the rainfall retention capacity of the pilot small reservoirs calculated is reasonably related to the soil moisture, supporting risk visualization for small reservoirs within rain-affected regions. Furthermore, the impact of the antecedent precipitation on rainfall retention capacity can also be dynamically quantified in real time, which provides reference for the continuous management of small reservoirs.

Impact of the stiffness of equation of state on saturation properties of asymmetric nuclear matter and Urca cooling in neutron stars

Abstract We consider nuclear equation of state (EoS) based on the semi-realistic M3Y-Paris and M3Y-Reid effective nucleon-nucleon (NN) interactions to assess the influence of the stiffness of the isospin-asymmetric nuclear matter (ANM) on its isoscalar and isovector saturation properties, and on the β-stable proton fraction in neutron star (NS) matter. Two parameterizations schemes of the CDM3Y isovector density dependence of the NN interaction are adopted, one is scaled to the isoscalar density dependence and the other (IVF1) is developed independently of it. We found that the stiffer EoS yields larger binding saturation density that decreases with the isospin asymmetry (I), and slightly decreases the maximum asymmetry ( I max ) reached for bound ANM. The density-slope (L) of the symmetry energy is found to correlate directly with the stiffness of ANM, meanwhile the symmetry-energy curvature (K sym ) and the quadratic isovector incompressibility coefficient (K τ ) are found to correlate with it inversely. We found also that the stiffer EoS indicates larger neutron-rich npe μ NS matter under β-equilibrium. Only the CDM3Y-Paris EoSs of isoscalar incompressibility K 0 up to 270 MeV and that of CDM3Y-Reid with K 0 = 200 MeV indicate allowed direct Urca (DU) cooling process in β-stable NS matter, at densities greater than 3.5 ρ 0, based on the IVF1 density dependence. The stiffer EoS proposes a narrower density range for DU process in NS. According to the considered Paris (Reid) forces, muons can emerge in cold β-stable npe matter at ρ ≥ 0.85 ρ 0(0.79 ρ 0), which slightly decreases both the neutron richness at NS core and the DU threshold density.

Does a Fractional-Order Recurrent Neural Network Improve the Identification of Chaotic Dynamics?

This paper presents a quantitative study of the effects of using arbitrary-order operators in Neural Networks. It is based on a Recurrent Wavelet First-Order Neural Network (RWFONN), which can accurately identify several chaotic systems (measured by the mean square error and the coefficient of determination, also known as R-Squared, r2) under a fixed parameter scheme in the neural algorithm. Using fractional operators, we analyze whether the identification capabilities of the RWFONN are improved, and whether it can identify signals from fractional-order chaotic systems. The results presented in this paper show that using a fractional-order Neural Network does not bring significant advantages in the identification process, compared to an integer-order RWFONN. Nevertheless, the neural algorithm (modeled with an integer-order derivative) proved capable of identifying fractional-order dynamical systems, whose behavior ranges from periodic and multi-stable to chaotic oscillations. That is, the performances of the Neural Network model with an integer-order derivative and the fractional-order network are practically identical, making the use of fractional-order RWFONN-type networks meaningless. The results deepen the work previously published by the authors, and contribute to developing structures based on robust and generic neural algorithms to identify more than one chaotic oscillator without retraining the Neural Network.

Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection

Abstract Composite materials find increasing applications in modern industry and transport. However, they may lose desirable mechanical properties due to external mechanical excitations, ultraviolet radiation, moisture penetration, or other factors. Therefore, an effective way to assess the condition of materials is necessary. In this article, a nondestructive evaluation of glass fiber-reinforced composite subjected to five-stage static bending is presented. For this reason, pulsed excitation terahertz imaging was utilized, and a data processing/exploration scheme was proposed. The proposed, novel approach consists of an efficient data registration algorithm based on surface approximation (for surface roughness and unevenness elimination) and a parametrization scheme applied for the signals gained from the time response of the glass fiber-reinforced polymer layer. Obtained parameters enable the global description of the evaluated material state and prediction of failure effectively, even in the early stages of destruction.

Optical turbulence simulations over the Tibetan Plateau based on a single-column model with high-order closure

Optical turbulence limits the maximum resolution of ground-based telescopes and leads to image degradation. The use of atmospheric numerical techniques to forecast optical turbulence is crucial for observation scheduling and optimization of adaptive optic systems. Current research methods for forecasting optical turbulence are primarily based on mesoscale models with turbulence closure techniques to parameterize the key terms required for C n 2 calculations under the assumption of atmospheric quasi-steady-state balance, and then the integrated astroclimatic parameters related to C n 2 profile can be obtained. In this study, we propose what we believe to be a novel approach to forecast C n 2 using a boundary layer parameterization based on higher-order turbulence closure in the single-column framework of the CLUBB model. Compared to mesoscale models, the CLUBB model serves as a single-column model, which simplifies modifications and reduces compilation time, and is more conducive to testing the performance of C n 2 parameterization scheme. In the design of C n 2 parameterization scheme, we consider a more complete physical process rather than omitting certain terms to obtain a steady-state solution. The performance of the model is evaluated using measurements obtained during a field campaign conducted at Da Qaidam site above the Tibetan Plateau. The results show that the model is able to capture typical features of the C n 2 profile evolution under convective conditions. Comparison of the model with contemporaneous sounding measurements and quantification of the model’s performance using statistical operators demonstrate the statistical agreement between simulations and measurements. In terms of atmospheric seeing, we can observe a bias of 0.01 and a root-mean-square error (RMSE) of 0.31 without any model calibration, which outperforms the results of previous mesoscale modeling studies. In addition, the new parameterization scheme is also compared with two representative C n 2 algorithms previously used in the mesoscale models, with some improvements observed. The potential demonstrated by this approach is expected to bring greater value and advancement to the research of three-dimensional forecasting of optical turbulence in the future by coupling with the mesoscale model.

Gas dynamic optimization of the work process of a single-stage cooled axial turbine with an inside baffle

The article presents the results of optimization of the work process of a single-stage axial turbine in order to increase its efficiency. During optimization, it was necessary to preserve the construction of the original turbine as much as possible. To solve this problem, a parameterization scheme for turbine blades and path contours was developed, taking into account the design and technological limitations. The turbine nozzle blade had an inside baffle. To control the possibility of placing the baffle, a special program was developed that automatically monitors the spatial position of the sections of the blade of the nozzle set. A post-processing program was developed to control the flow parameters at the turbine outlet in height. The efficiency and the vertical deviation of the angle of the outflow from the turbine from the original one were used as optimization criteria. The limitations were the mass flow rate of the working fluid and the total pressure ratio of the turbine. The problem was solved in several stages with different changing variables. As a result of solving the problem, it was possible to increase the turbine efficiency by 0.9%

Experimental performance investigation on a desiccant-assisted two-stage evaporative cooling system in hot and humid areas

The escalating demand for energy-efficient and eco-friendly air conditioning systems in buildings has spurred the development of comfortable, efficient, and cost-effective air handling system configurations. Desiccant cooling has shown a higher coefficient of performance (COP) compared to traditional vapor compression refrigeration (MVCR) systems. However, current desiccant cooling facilities struggle to decouple and efficiently handle indoor heat and moisture loads. The complexity of these facilities has kept intricate cooling systems remaining theoretical, requiring simplification and experimental investigation. This paper presents an experimental study on a compact, two-stage evaporative cooling system assisted by a liquid desiccant. A key innovation of this system is the inclusion of a two-stage heat exchanger that adeptly manages the decoupling of indoor heat and moisture loads under challenging high-temperature and high-humidity conditions. Performance analysis was conducted experimentally under three hot and humid climatic conditions using an optimized operating parameter scheme. Starting from an initial condition of 36.22 °C and a humidity ratio of 0.028 kg/kg, the proposed system achieves COP values ranging from 11.3 to 18.4 without compromising indoor comfort or facility compactness. Under high heat and high humidity conditions, the optimized system extracts 20 % of the product air as the secondary air source. It can reach a minimum supply air temperature of 18.44 °C, achieved under optimized conditions of low wind speed (1.0 m/s), high desiccant concentration (35 %), and substantial desiccant flow (0.09 kg/s). Experimental studies of this new system provide the possibility of achieving high efficiency in air handling over a wide range of temperatures and humidity.

Dynamic Behaviors of Composite-Laminated Concentrically Stiffened Rectangular Plates by Substructure Modal Synthesis

Existing numerical analysis methods often incur high computational costs when directly solving multi-degree-of-freedom systems due to computer capacity limitations. To address this issue, this paper took the composite laminated concentrically stiffened rectangular plate as the research object. The modal synthesis method was employed to reduce the degrees of freedom of the model, enabling the solution of complex dynamic characteristics. In the research process, the domain decomposition theory was used to divide the research object into plate and rib substructures. Based on the spectral Chebyshev method, the substructure dynamic model of the composite laminated rectangular plate was constructed. Subsequently, the function expressions of the complex load excitation on each substructure were derived, and the fixed modal synthesis method was introduced to construct the spectral Chebyshev reduced model of the substructures. According to the artificial spring theory equivalent, the interface force, and the whole reduction model of the composite laminated concentrically stiffened rectangular plate were obtained by assembling the substructure models. The time–domain and frequency–domain dynamic behaviors of composite laminated concentrically stiffened rectangular plates are yielded by solving the whole reduced model. The novelty of this work lies in combining the spectral Chebyshev method with the modal synthesis method. The established reduced model no longer depended on mesh quality and required fewer matrix dimensions and computation time compared to the whole model, while still achieving sufficiently accurate results. Additionally, based on the reduced model, an effective parametric study scheme was proposed to analyze the impact of dimensions and material properties of rib substructures on the dynamic behaviors of the composite laminated concentrically stiffened rectangular plate. These findings can be used to guide the optimal design of laminated concentrically stiffened rectangular plates in engineering practice.

Turbulent Heat Fluxes over Arctic Sea Ice: Measurements and Evaluation of Recent Parameterizations

We present direct eddy covariance measurements of the surface heat flux in sea ice over a wide range of conditions across the Arctic Ocean made during two research cruises. Photographic imagery of the surface around the ship provides a local, in situ estimate of the ice fraction. Aerodynamically rough conditions prevail for the majority of the time in the consolidated pack ice. The results are analyzed in the framework of a recently-developed parameterization scheme in which the exchange coefficients over ice are functions of a roughness Reynolds number, R*, hence account for aerodynamic roughness variability. This parameterization accurately represents the measured fluxes under all conditions, while under aerodynamically rough conditions the existing parameterizations from both the Met Office Unified Model, and ECMWF Integrated Forecast System overestimate the fluxes. The results corroborate those of a previous airborne study over the marginal ice zone, and encompass a wider range of atmospheric stability conditions.

Enhancing model temperature estimations in shallow, turbid, coastal regions: Mobile Bay, Alabama

Accurate estimation of water column temperature is vital for modeling physical and biogeochemical processes. A key process in the thermal dynamics of the upper ocean is the attenuation of solar radiation. In shallow-turbid coastal systems, spatially and temporally varying optical characteristics present challenges for commonly used attenuation parameterization schemes. This study investigates the dependency of temperature with a ROMS model of Mobile Bay, a shallow, turbid estuary, using six different attenuation approaches including three base cases: Conventional approach PS77 based on water type-9; Novel approach SAL relating in situ PAR attenuation to salinity; and Surface trapped irradiance method ST. In addition, these base cases are also tested with surface atmospheric heat flux correction (QC). Simulations were validated against observations from various sources to identify the optimal approach at annual and synoptic scales. While all simulations showed effective temperature performance over an annual cycle, monthly analysis revealed some seasonality, with winter months typically performing better than summer months. The influence of QC notably enhanced temperature performance in both annual and synoptic scales, given that surface heat flux primarily drove temperature changes in this shallow system. The best overall performance was determined to be the ST approach incorporating QC. Conversely, PS77 without QC demonstrated the poorest performance. The SAL model with QC, notably improved performance over PS77 with QC, yet demonstrated comparable yet weaker performance compared to the ST model with QC. The study also implies that neglecting subseasonal validation in long-term regional climate modeling could introduce uncertainty into analyzing events tied to subseasonal temperatures.