Radiative Model Research Articles

Adaptive Robust Optimal Scheduling of Combined Heat and Power Microgrids Based on Photovoltaic Mechanism/Data Fusion-Driven Power Prediction

In order to effectively deal with the adverse effects of the randomness of photovoltaic output on the operation of combined heat and power (CHP) microgrids, this paper proposes an adaptive robust optimal scheduling strategy for CHP microgrids based on photovoltaic mechanism/data fusion-driven power prediction. Firstly, the mechanism of the clear sky radiation model is used to calculate the photovoltaic clear sky limit output and random output, and the latter is reorganized in different periods by using the idea of similar days. Then, the data-driven random prediction results are superimposed with the clear sky limit output, the photovoltaic mechanism/data fusion-driven power prediction model is established, and the fusion-driven power prediction framework is provided. Secondly, the boundary information of uncertain factors is deeply explored, and an adaptive robust uncertainty set considering the confidence interval of predictive error statistical information is constructed. On this basis, a robust optimization model of CHP microgrids with the lowest operating cost is proposed, and the optimization model is solved by column and constraint generation algorithm. Finally, the rationality and effectiveness of the proposed model are verified through simulation examples and analytical calculations.

A Statistical Split Window Method Without Atmospheric Profile Input for Temperature and Emissivity Retrieval from Airborne Long-Wavelenght Infrared Hyperspectral Imagery

The retrieval of Land Surface Temperature (LST) and Emissivity (LSE) from long-wavelength thermal infrared (LWIR) hyperspectral data can be challenging due to uncertainties in atmospheric compensation (AC). While AC is typically performed using atmospheric radiance models, errors in the input atmospheric profiles can lead to significant inaccuracies. In this study, we propose an end-to-end method for retrieving LST and LSE without the need for local atmospheric profile inputs. The method consists of two main steps: first, a statistical split-window (SSW) method is used to estimate the ground leaving radiance, with optimal band configurations and coefficients determined through a trial-and-error approach and statistical regression based on simulation datasets. Second, by integrating the ASTER Temperature And Emissivity Separation (ASTER-TES) method with an atmospheric downwelling lookup table (LUT), the optimal LST and LSE are derived based on the principle of emissivity smoothness. The proposed method is applied to airborne HypercamLW LWIR hyperspectral data. When compared to the MODTRAN-based AC with ASTER-TES (MODTRAN-TES) and the built-in method of FLAASH-IR, the proposed SSW-TES method yields better accuracy, with a LST root mean square error (RMSE) of 1.24 K and an LSE RMSE of 0.016.

Cordycepin ameliorates spaceflight-induced osteoporosis by preventing BMSCs oxidative stress and senescence via interacting with PI3K p110α and regulating PI3K/Akt/FOXO3 signalling.

Spaceflight-induced osteoporosis (SFOP) is a detrimental healthcare consequence during spaceflight. Weightlessness and ionizing radiation were main environmental factors that contribute to SFOP, especially in the manned deep space voyages. However, currently there is scarce effective method to treat SFOP. This study aims at discovering the role and mechanism of cordycepin (COR) in treating SFOP. A combined ionizing radiation and tail suspension (IR/IS) model is constructed in mice to simulate SFOP. COR injection exhibits certain dose-dependent therapeutic effects including better imageological bone index and improved histological bone regeneration in treating SFOP, which is most prominent at a dose of 20mg/kg. A combined radiation and microgravity (R/M) model is established to treat BMSCs in vitro. 10μM COR alleviates oxidative stress and cellular senescence of BMSCs. Through high-throughput sequencing, molecular docking and microscale thermophoresis (MST), we reveal a novel mechanism that COR interacts with p110α subunit in PI3K isoform α (PI3Kα) and inhibits PI3K kinase activity, which then regulates the PI3K/Akt/FOXO3 signalling. To elevate the bioavailability of COR in the SFOP treatment, a BMSCs-targeted delivery system that uses exosomes (Exos) modified with BMSC-affinity peptide E7 (E7-Exos) is constructed and loaded with COR. E7-Exos loaded COR reduces the dosage of COR to 5mg/kg while enhancing the therapeutic effect than using 20mg/kg COR alone in treating SFOP. In conclusion, COR shows promise as a potential agent in SFOP therapy.

Improved Snow Albedo Evolution in Noah-MP Land Surface Model Coupled with a Physical Snowpack Radiative Transfer Scheme

Abstract The widely used community Noah-MP land surface model currently adopts snow albedo parameterizations that are semiphysical in nature and have systematic biases which impact the accuracy of weather and climate modeling systems that use Noah-MP as the land component. We hypothesized that integrating the snowpack radiative transfer scheme from the latest version of the Snow, Ice, and Aerosol Radiative (SNICAR) model can improve the physical representation of snow albedo processes and reduce corresponding land model uncertainties. Therefore, we evaluate Noah-MP simulations employing the SNICAR scheme and compare model accuracy to a Noah-MP simulation using the default semiphysical Biosphere-Atmosphere Transfer Scheme (BATS) scheme using in situ spectral snow albedo observations at three Rocky Mountain field stations. The agreement between simulated and in situ observed ground snow albedo is significantly enhanced in NoahMP–SNICAR simulations relative to NoahMP–BATS simulations (root-mean-square error reductions from 0.116 to 0.103). Especially, NoahMP–SNICAR improves modeled snow albedo variability for fresh snow and aged snowpack (correlation increase from 0.42 to 0.67). The underestimated variability of snow albedo in NoahMP–BATS is a result of inadequate representation of physical linkages between snow albedo evolution and environmental/snowpack conditions (temperature, snow density, snow water equivalent, and light-absorbing particles), which is substantially improved by the NoahMP–SNICAR scheme. This new development of NoahMP–SNICAR physics provides a means to improve snow albedo accuracy and reduce corresponding uncertainties while providing new modeling capabilities such as hyperspectral snow albedo and effects of snow grain size, snow grain shape, and light-absorbing particles in future studies. Significance Statement The widely used community Noah-MP land surface model utilizes simplified snow albedo parameterizations that are semiphysical and have large uncertainties that affect the accuracy of weather and climate modeling systems. We aim to reduce uncertainties by incorporating a radiative transfer snow albedo model (i.e., SNICAR) into Noah-MP. The newly coupled NoahMP–SNICAR model shows a significant enhancement in simulating snow albedo at three Rocky Mountain stations when compared to the Noah-MP configuration with the default snow albedo scheme (i.e., BATS). It also introduces new modeling capabilities for future studies, such as hyperspectral snow albedo and the effects of snow grain size, snow grain shape, and light-absorbing particles.

Heat transfer modeling and system performance assessment of an innovative thermosyphon radiator integrated with air source heat pumps for sustainable heating applications

Heat transfer modeling and system performance assessment of an innovative thermosyphon radiator integrated with air source heat pumps for sustainable heating applications

Corrigendum to “Combined stochastic and transfer model for atmospheric radiation” [Journal of Quantitative Spectroscopy and Radiative Transfer 73 (2002) 249–259

Corrigendum to “Combined stochastic and transfer model for atmospheric radiation” [Journal of Quantitative Spectroscopy and Radiative Transfer 73 (2002) 249–259

Revealing the contribution of flame spread to vertical thermal runaway propagation for energy storage systems

The rapidly growing energy storage systems necessitate more high-capacity lithium iron phosphate batteries but pose significant safety concerns. In multi-layer battery clusters, if thermal runaway propagation occurs between modules, particularly in the vertical direction, the ensuing fire spread can further result in the accelerated propagation of battery and even an irrevocable catastrophe. Clarifying the contribution of flame spread to vertical thermal runaway propagation is the goal of this investigation. The unexpected propagation characteristics between the upper and lower modules are explored. Further, the critical heat and the percentage of heat that leads to thermal runaway in the upper battery are determined using the equivalent replacement battery. The flame heat transfer is finally decoupled using the thermal radiation model. And the mechanism of vertical thermal runaway propagation induced flame between modules is analyzed. The findings reveal that the higher module's thermal runaway and venting sequence differs from the lower module's, suggesting that flame spread dominated the thermal runaway propagation paths. The critical triggering energy of the upper battery is 1193.6 kJ, comprising 279 kJ of conductive heat, 750 kJ of flame heat, and 164.6 kJ of self-generation heat, with the flame heat accounting for approximately 1.18 % of the total heat released from the battery fire. In contrast to horizontal thermal runaway propagation, where thermal conduction is predominant, the convection heat from battery fire serves as the main heat source for vertical propagation. The findings serve as a foundation for both emergency response to fire incidents and the safe design of battery modules in existing energy storage systems.

Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security

The inherently stochastic nature of radiation emissions makes modeling background radiation structure a particularly challenging research area. In source identification scenarios, which are critical to nuclear security, the complexity of background radiation modeling is intensified by dynamically changing factors that influence radiation measurements. Consequently, accurately modeling and estimating background radiation can significantly improve our nuclear security capabilities by enhancing the detection of anomalies within radiation data. This study introduces a new data-driven approach to modeling background radiation from spectral measurements. By leveraging the novel data mining technique, Matrix Profile (MP), this approach identifies structural patterns within radiation measurements. The method was tested on real-world background 1-second spectral data collected across various locations, with results demonstrating MP’s effectiveness in modeling background structures for measurements taken in the same location. Additionally, MP modeling outperformed the traditional method of using raw measurement averages, particularly in generating distinct models for low-count backgrounds from different locations.

Regional modeling of surface solar radiation, aerosol, and cloud cover spatial variability and projections over northern France and Benelux

Abstract. Investigating the current and future evolution of surface solar radiation (SSR) is essential in the context of climate change and associated environmental issues. We focus on the influence of atmospheric aerosols, along with cloud cover and water vapor content, on northern France and Benelux in spring and summer. Our analysis relies on the National Centre for Meteorological Research–Limited Area Adaptation Dynamic International Development v6.4 (CNRM-ALADIN64) regional climate model at 12.5 km resolution, which includes an interactive aerosol scheme. A regional evaluation of 2010–2020 ALADIN hindcast simulations of clear-sky and all-sky SSR, clear-sky frequency, and aerosols, through comparison to coincident multi-site ground-based measurements, shows reasonable agreement. In addition, these hindcast simulations emphasize how elevated aerosol loads over Benelux and high cloud cover over southwestern England reduce the SSR. Additional ALADIN climate simulations for 2050 and 2100 under Coupled Model Intercomparison Project phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP) 1-1.9 predict a significant reduction in aerosol loads compared to 2005–2014, especially over Benelux, associated with future increases in clear-sky SSR but geographically limited all-sky SSR evolution. In contrast, under SSP3-7.0, clear-sky and all-sky SSR is projected to decline significantly over the domain. This decline is greatest in spring over Benelux due to combined increases in cloud cover and nitrate aerosols projected from 2050 onwards. In summer, projected decreases in cloud cover largely attenuate the reduction in SSR due to aerosols in 2050, while by 2100 rising water vapor contents counteract this attenuation. Thus, our results highlight seasonally and spatially variable impacts of future anthropogenic aerosol emissions on SSR evolution due to cloud cover and water vapor modifications that will likely largely contribute to the modulation of forthcoming aerosol influences.

Phase-resolved Hubble Space Telescope WFC3 Spectroscopy of the Weakly Irradiated Brown Dwarf GD 1400 and Energy Redistribution–Irradiation Trends in Six White Dwarf–Brown Dwarf Binaries

Abstract Irradiated brown dwarfs offer a unique opportunity to bridge the gap between stellar and planetary atmospheres. We present high-quality Hubble Space Telescope/Wide Field Camera 3/G141 phase-resolved spectra of the white dwarf–brown dwarf binary GD 1400, covering more than one full rotation of the brown dwarf. Accounting for brightness variations caused by ZZ Ceti pulsations, we revealed weak (∼1%) phase-curve amplitude modulations originating from the brown dwarf. Subband light-curve exploration in various bands showed no significant wavelength dependence on amplitude or phase shift. Extracted day- and nightside spectra indicated chemically similar hemispheres, with slightly higher dayside temperatures, suggesting efficient heat redistribution or the dominance of radiative escape over atmospheric circulation. A simple radiative and energy redistribution model reproduced the observed temperatures well. Cloud-inclusive models fit the day and night spectra better than cloudless models, indicating global cloud coverage. We also begin qualitatively exploring atmospheric trends across six irradiated brown dwarfs, from the now complete “Dancing with the Dwarfs” white dwarf–brown dwarf sample. The trend we find in the dayside/nightside temperature and irradiation levels is consistent with efficient heat redistribution for irradiation levels less than ∼109 erg s−1 cm−2 and decreasing efficiency above that level.

Alpha/beta values in pediatric medulloblastoma: implications for tailored approaches in radiation oncology

BackgroundMedulloblastoma is the most common malignant pediatric brain tumor, typically treated with normofractionated craniospinal irradiation (CSI) with an additional boost over about 6 weeks in children older than 3 years. This study investigates the sensitivity of pediatric medulloblastoma cell lines to different radiation fractionation schedules. While extensively studied in adult tumors, these ratios remain unknown in pediatric cases due to the rarity of the disease.Materials and methodsFive distinct medulloblastoma cell lines (ONS76, UW228-3, DAOY, D283, D425) were exposed to varying radiation doses and fractionation schemes. In addition, ONS76 and UW228-3 stably overexpressing MYC were analyzed. Alpha/beta values, representing fractionation sensitivity, were quantified using the linear-quadratic model of radiation survival.ResultsThe study unveiled elevated alpha/beta ratios across diverse medulloblastoma cell lines, with a weighted mean alpha/beta value of 11.01 Gy (CI: 5.23–16.79 Gy). Neither TP53 status nor the levels of MYC expression influenced fractionated radiosensitivity. Furthermore, differences in alpha/beta values cannot be correlated with molecular subgroups (p = 0.07) or radiosensitivity (SF2).ConclusionThese in vitro findings strongly recommend normofractionated or hyperfractionated radiotherapy for paediatric medulloblastoma cases due to consistently high alpha/beta values across subgroups. Conversely, hypofractionated radiotherapy is not advisable within a curative approach. This study presents significant potential by enabling the estimation of radiobiological fractionations and dose effects in young, vulnerable patients, highlighting its importance for advancing patient-specific therapeutic strategies.

Time-integrated polarizations in the prompt phase of gamma-ray bursts via the multi-window interpretation

We used multi-window observations, including the light curve and evolutions of the spectral peak energy (E_p), the polarization degree (PD), and the polarization angle (PA), to infer the model parameters for predicting the time-integrated PD in the prompt phase of gamma-ray bursts (GRBs). We selected 23 GRBs that were codetected by Fermi/GBM and polarization detectors (i.e., GAP, POLAR, and AstroSat). In our multi-window fitting, the light curve, E_p curve, PD curve, and PA curve were interpreted simultaneously under the synchrotron radiation model in ordered magnetic fields (i.e., the aligned-field case and the toroidal-field case). For bursts with strong (∼90^∘) PA rotations, the predicted time-integrated PD of the aligned-field case roughly matches the corresponding observed best-fit value, while it is higher for the toroidal-field case. For bursts without strong (∼90^∘) PA rotation(s), the predicted PDs of the aligned-field case and the toroidal-field case are comparable and can interpret the observational data equally well. The observed time-resolved and time-integrated PDs for GRB 170206A are comparable and are both lower than our predicted upper limits in ordered magnetic fields. This means that mixed magnetic fields, that is, magnetic fields with both ordered and random components, probably reside in the radiation regions of this burst. Except for one out of the total 23 bursts, the predicted time-integrated PDs, which are ∼44% for the aligned-field case and around $49%$ for the toroidal-field case, are consistent with the corresponding observed values. Consistent with previous study, the models with synchrotron radiation in ordered magnetic fields can therefore interpret most of the current polarization data within an error bar of $1σ$.

Multi-block Directed Radiation Routing Algorithm for Optimized Wireless Sensor Network

In recent years, the axial radiation model has emerged as a pivotal framework for Wireless Sensor Networks (WSN), particularly in enhancing intelligent sensing platforms. This study delves into the WSN structured around the axial radiation model, encompassing critical aspects like model reconstruction, node deployment, and routing optimization. Our focus is on evaluating the performance metrics that influence the responsiveness of these intelligent platforms. We introduce the Multi-block Directed Radiation (MBDR) routing algorithm, designed to extend system operational time and boost data transmission efficiency. Comprehensive experimental analyses demonstrate the significant advancements of MBDR in survivability, data transmission rates, and regional balance within central axis radiation model environments.

Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation

Abstract. The urban canopy model Town Energy Balance (TEB) is coupled with the radiation model SPARTACUS-Urban to improve the urban geometry simplification and the radiative transfer calculation. SPARTACUS-Urban assumes that the probability density function of wall-to-wall and ground-to-wall distances follows a decreasing exponential. This better matches the distributions in real cities than in the infinitely long street canyon employed by the classical TEB. SPARTACUS-Urban solves the radiative transfer equation using the discrete ordinate method. This allows us to take into account physical processes such as the interaction of radiation with the air in the urban canopy layer and the spectral dependence of urban material reflectivities or specular reflections. Such processes would be more difficult to account for with the radiosity method used by the classical TEB. With SPARTACUS-Urban, the mean radiant temperature, a crucial parameter for outdoor human thermal comfort, can be calculated from the radiative fluxes in the vertical and horizontal directions incident on the human body in an urban environment. TEB–SPARTACUS is validated by comparing the solar and terrestrial urban radiation budget observables with those simulated by the Monte-Carlo-based HTRDR-Urban reference model for procedurally generated urban districts that mimic the local climate zones. Improvement is found for almost all radiative observables and urban morphologies for direct solar, diffuse solar, and terrestrial infrared radiation. The TEB mean radiant temperature diagnostic for a person in the urban environment is also improved with TEB–SPARTACUS compared with the classical TEB. Based on these results, TEB–SPARTACUS could lead to more realistic results for building energy consumption, outdoor human thermal comfort, or the urban heat island effect.

Investigation of the thermal structure in the atmospheric boundary layer during evening transition and the impact of aerosols on radiative cooling

AbstractThe evening transition is crucial in various phenomena, including boundary‐layer stability, temperature inversion, radiation fog, vertical mixing, and pollution dispersion. We have explored this transition using data from 80 days of observations across two fog seasons at the Kempegowda International Airport, Bengaluru (KIAB). Through field experiments and simulations integrating aerosol interaction in a radiation–conduction model, we elucidate the impact of aerosols on longwave cooling of the atmospheric boundary layer (ABL). Field observations indicate that, under calm and clear‐sky conditions, the evening transition typically results in a distinct vertical thermal structure called the lifted temperature minimum (LTM). We observe that the prevailing profile near the surface, post‐sunset is the LTM profile. Additionally, the occurrence of LTM is observed to increase with decreases in downward and upward longwave flux, soil sensible heat flux, wind speed, and turbulent kinetic energy measured at 2 m above ground level (AGL). In such scenarios, the intensity of LTM profiles is governed primarily by the aerosol‐induced longwave heating rate (LHR) within the surface layer. Furthermore, the presence of dense clouds leads to increased downward flux, causing the disappearance of LTM, whereas shallow fog can enhance LTM intensity, as observed in both field observations and simulations. Usually, prevailing radiation models underestimate aerosol‐induced LHR by an order of magnitude compared with actual field observations. We attribute this difference to aerosol‐induced radiation divergence. We show that the impact of aerosol‐induced LHR extends hundreds of meters into the inversion layer, affecting temperature profiles and potentially influencing processes such as fog formation. As the fog layer develops, LHR strengthens at its upper boundary. However, we highlight the difficulty in detecting this cooling using remote instruments such as microwave radiometers.

Impact of Turbulence, Combustion, and Radiation Models on RANS-Based Simulation of Methane–Hydrogen Diffusion Flames

Impact of Turbulence, Combustion, and Radiation Models on RANS-Based Simulation of Methane–Hydrogen Diffusion Flames

Large Eddy Simulations of a Medium-Scale Ethanol Pool Fire Using Conditional Source-Term Estimation Including Coupled Soot Radiation Effects

ABSTRACT The objective of this paper is to assess the combined capabilities of Conditional Source-Term Estimation with radiation and soot modeling in large eddy simulations of a medium-scale ethanol pool fire. Tabulated detailed chemistry is implemented including radiative losses. The radiative transfer equation is solved with the weighted sum of gray gas models to determine the gaseous absorption. Two subgrid soot models are considered using the laminar smoke point concept. The first approach calculates the soot formation and oxidation rates corrected to account for turbulent effects. The second determines the soot reaction rates in conditional space using analytical functions and the filtered reaction rates are determined by convolution with the filtered mixture fraction density function. Predictions of the time-averaged and root mean square temperature, species mole fractions and soot mass fraction are compared with experimental measurements. Numerical temperatures agree well with experiments except in the fire plume where some overpredictions are observed. Species concentrations match the measurements with some discrepancies observed in the products farther downstream, partly explained by the experimental uncertainty. The peak soot predicted with the first model is in reasonable agreement with the experiments but is much lower using the second approach. These differences are explained by the differences in the turbulence soot chemistry treatment and calibration of empirical constants. However, here, soot has a limited impact on the temperature, flow and mixing fields due to low soot concentrations produced by ethanol. The radiative heat fluxes are reasonably well predicted. Further validation is needed with additional experimental soot data.

Ecophysiological responses to heat waves in the marine intertidal zone.

One notable consequence of climate change is an increase in the frequency, scale and severity of heat waves. Heat waves in terrestrial habitats (atmospheric heat waves, AHW) and marine habitats (marine heat waves, MHW) have received considerable attention as environmental forces that impact organisms, populations and whole ecosystems. Only one ecosystem, the intertidal zone, experiences both MHWs and AHWs. In this Review, we outline the range of responses that intertidal zone organisms exhibit in response to heat waves. We begin by examining the drivers of thermal maxima in intertidal zone ecosystems. We develop a simple model of intertidal zone daily maximum temperatures based on publicly available tide and solar radiation models, and compare it with logged, under-rock temperature data at an intertidal site. We then summarize experimental and ecological studies of how intertidal zone ecosystems and organisms respond to heat waves across dimensions of biotic response. Additional attention is paid to the impacts of extreme heat on cellular physiology, including oxidative stress responses to thermally induced mitochondrial overdrive and dysfunction. We examine the energetic consequences of these mechanisms and how they shift organismal traits, including growth, reproduction and immune function. We conclude by considering important future directions for improving studies of the impacts of heat waves on intertidal zone organisms.

New geographic information system based sustainability metric for isolated photovoltaic systems

The integration of photovoltaic (PV) technologies is vital for achieving sustainable energy solutions in isolated systems. However, A critical challenge that remains is maintaining the sustainability of these systems under the fluctuating conditions of solar irradiance, which is key for isolated energy systems. This study hypothesizes that the sustainability of PV systems can be accurately assessed through a new metric that incorporates performance consistency, variability, and resilience, using real-time energy production data alongside GIS-based solar radiation models. By analyzing fixed PV, concentrated PV (CPV), and dual axis tracking PV (DATPV) systems over a three-year period (2017–2019), The analysis indicates that DATPV systems achieved the highest energy output, with energy ratios exceeding 300% in 2019, though this was accompanied by substantial variability in performance. Fixed PV systems demonstrated the most stable performance, with a consistency term reaching 0.93 and a sustainability score of 0.87 in 2019. CPV systems performed moderately, with a sustainability score of 0.66 in 2017. These results highlight the trade-off between energy capture and operational stability, which is critical for sustainable energy management in isolated systems.

Updated Weighted-Sum-of-Gray-Gases Model Parameters for a Wide Range of Water and Carbon Dioxide Concentrations and Temperatures up to 5000 K.

The weighted-sum-of-gray-gases model (WSGGM) is a commonly used radiative properties model for combustion engineering applications. This work presents updated WSGGM parameters from our previously published WSGGM to cover a temperature range up to 5000 K for pure H2O and CO2 species as well as mixtures of the two. The gases are considered ideal at all temperatures and new conditions are covered in comparison to existing WSGGM parameters; examples of engineering applications are hydrogen combustion, oxygen-enriched, and oxy-fuel combustion as well as thermal and hybrid plasma systems applying either H2O- or CO2-based plasma conditions. Thus, the parameters are considered relevant in high-temperature processes where gas dissociation effects are unknown. The updated sets of WSGGM parameters are compared to existing WSGGMs by predicting the total emissivity for different gaseous domains; the computational accuracy is assessed using the statistical narrow band model (SNBM) as a reference. Additional comparisons applying the WSGGMs for predicting the radiative source term under nonisothermal and nonhomogeneous conditions in a gaseous domain consisting of two infinite black plates are also included. The results show the suitability of the updated model parameters for such conditions and the increasing deviation error from the SNBM for existing WSGGMs when used outside of their temperature limits. The updated parameters achieve a mean deviation error from the SNBM of below 20% for most cases, which is at a range similar to previous works.