Physical Scheme Research Articles

A 240 Gb/s dynamic one-time-pad THz-coherent PON seamless integrated physical layer encryption scheme based on double chaotic models assistance

A 240 Gb/s dynamic one-time-pad THz-coherent PON seamless integrated physical layer encryption scheme based on double chaotic models assistance

Investigating the complementarity of thermal and physical soil organic carbon fractions

Abstract. Partitioning soil organic carbon (SOC) in fractions with different biogeochemical stability is useful to better understand and predict SOC dynamics and provide information related to soil health. Multiple SOC partition schemes exist, but few of them can be implemented on large sample sets and therefore be considered relevant options for soil monitoring. The well-established particulate organic carbon (POC) vs. mineral-associated organic carbon (MAOC) physical fractionation scheme is one of them. Introduced more recently, Rock-Eval® thermal analysis coupled with the PARTYSOC machine learning model can also fractionate SOC into active (Ca) and stable SOC (Cs). A debate is emerging as to which of these methods should be recommended for soil monitoring. To investigate the complementarity or redundancy of these two fractionation schemes, we compared the quantity and environmental drivers of SOC fractions obtained on an unprecedented dataset from mainland France. About 2000 topsoil samples were recovered all over the country, presenting contrasting land cover and pedoclimatic characteristics, and analysed. We found that the environmental drivers of the fractions were clearly different, the more stable MAOC and Cs fractions being mainly driven by soil characteristics, whereas land cover and climate had a greater influence on more labile POC and Ca fractions. The stable and labile SOC fractions provided by the two methods strongly differed in quantity (MAOC/Cs=1.88 ± 0.46 and POC/Ca=0.36 ± 0.17; n=843) and drivers, suggesting that they correspond to fractions with different biogeochemical stability. We argue that, at this stage, both methods can be seen as complementary and potentially relevant for soil monitoring. As future developments, we recommend comparing how they relate to indicators of soil health such as nutrient availability or soil structural stability and how their measurements can improve the accuracy of SOC dynamics models.

A physical classification of Killing magnetic fields in Thurston geometries

In recent years, numerous studies have appeared that considered Killing vectors of three‐dimensional Riemannian manifolds as magnetic fields, since these vector fields are divergenceless by definition. The existence of adivergenceless vector field modeled as a magnetic field does not imply that it is physically realizable. In this study, we propose a physical classification scheme based on the divergences of the integral that defines the energy of a Killing magnetic field. We consider all the Killing magnetic fields of Thurston geometries studied in the literature and classify them as either physical or nonphysical.

Investigating the Impact of Multiphysics on Modeled Planetary Boundary Layer Height Estimates during the PECAN Field Campaign

Abstract Accurate representation of the planetary boundary layer (PBL) in numerical weather prediction is crucial to air quality, weather forecasting, and climate change research and operations. Here, we evaluate the estimates of PBL height (PBLH) from a set of convective-permitting simulations conducted using the Weather Research and Forecasting (WRF) Model during the Plains Elevated Convection at Night (PECAN) campaign (from June to mid-July 2015). Our analysis aims to quantify the variability in PBLH, along with its associated surface variables and atmospheric profiles, to gauge the influence of model physics on the accuracy of simulated PBL properties. Specifically, we conducted twenty-four 45-day retrospective simulations encompassing different combinations of three PBL and two microphysics schemes, two initial and boundary condition (ICBC) datasets, and two model vertical grid spacings. We compare these simulations with measurements from surface sites and radiosonde launches across four sites in the southern Great Plains during PECAN. Our findings indicate that deriving PBLH from modeled atmospheric profiles yields a narrower spread (200–300 m) compared to PBLH calculated from the model’s PBL scheme (400–500 m) relative to radiosonde-derived PBLH under fair weather conditions. The choice of PBL scheme and ICBCs exerts the most significant impact (by up to 400 m) on the spread of modeled PBLH and associated atmospheric profiles, primarily influencing the representation of surface heating, transport, and mixing processes in the model. The model has difficulty reproducing the correct thermodynamic profile under cloud-intense conditions. These results underscore the benefit of using the physically consistent approach in retrieving, evaluating, and assimilating PBLH estimates, as well as the utility of multiphysics to better address model uncertainties. Significance Statement Studies on weather forecast models typically involve running the model multiple times and adjusting model inputs slightly each time to produce a range of predicted variables. This range is crucial for evaluating forecast probabilities and integrating observations into the model. We found that using different model physics schemes can result in an equal or greater spread for predicted variables (here, we focus on boundary layer height and related variables), compared to input tweaks alone. Additionally, a particular scheme can introduce biases. These findings underscore the importance of employing multiple physics schemes in the model, as they widen the coverage (potentially doubling) of outputs, and thus better address forecast uncertainties.

Physical layer security enhancement scheme for PDM-16QAM system based on seven-dimensional CNN hyperchaotic encryption

The paper presents a secure communication scheme for the optical physical layer based on a seven-dimensional (7-D) Cellular Neural Network (CNN) hyperchaotic encryption. The encryption scheme utilizes a 7-D CNN hyperchaotic system to generate a hyperchaotic sequence as the key source. A portion of this key is selected to encrypt the plaintext image. The proposed scheme has been successfully implemented in a PDM-16QAM system with a data rate of 224 Gbps over a 200 km single-mode fiber (SMF). Experimental results show that authorized users can successfully decrypt the received signal, while eavesdroppers are unable to obtain useful information with a bit error rate (BER) of approximately 0.5. The key space of the scheme is 101792. Through key sensitivity analysis and key space analysis, it is known that the proposed encryption system can effectively resist various attacks by cryptanalysts.

Demonstration of a physical inversion scheme for all-sky, day-night IASI observations and application to the analysis of the onset of the Antarctica ozone hole: Assessment of retrievals and consistency of forward modeling

Based on a recently developed all-sky forward model (σ-IASI/F2N) for the computation of spectral radiances in the range 100 to 2760 cm-1, the paper addresses the spring onset of the Antarctica ozone hole with infrared observations from the IASI (Infrared Atmospheric Sounder Interferometer) satellite sounder. The Antarctica ozone hole is a cyclic event that grows in normal conditions in late August and collapses in late November/early December. Because of climate change (cooling of the stratosphere), the O3 hole is expected to become deeper. Indeed, 2021 and 2023 have been characterized by very spatially extensive and deep ozone hole. To demonstrate that we can gain further insights into these phenomena with the help of infrared nadir viewing observations, we have developed an all-sky retrieval tool, which inverts the whole IASI infrared spectrum to simultaneously estimate thermodynamic and geophysical parameters, including ozone and nitric acid, which are key parameters in analyzing the Antarctic ozone hole. Infrared sounders acquire data day and night, unlike visible and ultraviolet sounders, which are only operational during daytime. This enables us to acquire data also during the polar night, which is a critical time for O3 hole formation. Ice polar stratospheric clouds have been identified and fitted with our scheme. Maps of atmospheric ozone, complemented with those of nitric acid, temperature, and lower stratosphere height, have been retrieved for July, September, and October 2021 and 2023. Results are compared to those derived from TROPOMI (TROPOspheric Monitoring Instrument) and OMI (Ozone Monitoring Instrument), showing a very good agreement. The comparison of simultaneously retrieved O3 and HNO3 shows that the onset of the ozone hole is associated with relevant denitrification in the Antarctica Stratosphere. For 2023, our findings also show that O3 depletion episodes began as early as July. Although demonstrative, our analysis evidences the importance of Numerical Weather Prediction centers to assimilating all-sky infrared radiances (day, night, clear, or with ice or water clouds) to get insights into providing a more comprehensive picture of the Southern Spring ozone depletion over Antarctica.

Enhancing Surface Wind Speed and Temperature Prediction Using Surface-Layer Emulator and Transfer Learning

Abstract Accurate prediction of surface wind speed and temperature is crucial for many sectors. Physical schemes in numerical weather prediction (NWP) and data-driven correction approaches have limitations due to uncertainties in parameterization and lack of robustness, respectively. This study introduces a physics-informed data model, PhyCorNet, which combines a deep learning–based physics emulator (PhyNet) and a subsequent correction network (CorNet). PhyNet imitates the revised surface-layer parameterization scheme [default option of the Weather Research and Forecasting (WRF) Model]. CorNet refines predictions by mitigating the difference between PhyNet and observations. PhyCorNet enables gridded forecasts despite the training data being point based. Therefore, PhyCorNet can be regarded as a rediagnostic scheme for surface wind speed at 10 m (WS10) and temperature at 2 m (T2). Compared to WRF, it reduced diagnostic root-mean-square errors in the 24-h forecasts for WS10 and T2 by 40% and 36%, respectively, across China, with unbiased forecasts at almost all sites. PhyCorNet addresses the oversmoothing prediction issue of other deep learning models by providing the ability to represent fine-scale features and perform well in statistically extreme samples. In grid cells without observations for training, PhyCorNet performed much better than WRF, demonstrating the zero-shot learning capability. This study implies that the emulator plus bias correction provided by PhyCorNet could be used as a simple but effective approach to improve the performance of other diagnostic quantities in NWP. Significance Statement We developed a new model called PhyCorNet to improve the surface wind speed and temperature forecasts. Existing weather forecast models have limitations in accurately predicting these variables. PhyCorNet first uses a neural network (PhyNet) to mimic an existing physics-based wind and temperature calculation method. Another neural network [correction network (CorNet)] improves the PhyNet forecasts by comparing them with observations. Across China, PhyCorNet reduced 24-h forecast errors for wind speed by 40% and temperature by 36% compared to a conventional model. It performed well under diverse conditions and overcame the oversmoothing issues faced by other machine learning models. Importantly, PhyCorNet outperformed traditional models in areas without historical observations. We suggest that this new framework can also be used to enhance the forecasts of other atmospheric variables.

S-слівна арифметика та високоточні обчислення

The intricacies of using S-word arithmetic, the influence of the value of the parameter S on the estimation of the rounding error are analyzed; what are high-precision calculations and where they are used. The problems of two-key cryptography, computer steganography and the problem of transcomputational complexity are considered as areas of application of S-word arithmetic. For the development of S-word arithmetic algorithms, sequential, parallel, quantum computing models are used, and systems of residual classes are used. The architectural features of the computer system for the implementation of an effective algorithm in various models of calculations are considered. For the parallel computing model, the importance of reducing the connected steps is indicated, which can increase the amount of processed data, but allows to involve a larger number of parallel processors. This approach is in conflict with a method that reduces the amount of processed data, and there is a need to maintain a balance between these two methods in a parallel computing model. For the quantum computing model, the connection of qubits is a key factor in determining the quantum volume. The physical scheme determines which pairs of qubits can be entangled in a quantum computer. Peculiarities of transferring algorithms to another computing model are considered. An analysis of the complexity of implementing S-word arithmetic operations in sequential, parallel, and quantum computing models is carried out. For the parallel computing model, the importance of reducing the connected steps is indicated, which can increase the amount of processed data, but allows to involve a larger number of parallel processors. This approach is in conflict with a method that reduces the amount of processed data, and there is a need to maintain a balance between these two methods in a parallel computing model. For the quantum computing model, the connection of qubits is a key factor in determining the quantum volume. The physical scheme determines which pairs of qubits can be entangled in a quantum computer. Information is provided about the ongoing scientific forum «Calculation optimization issues», the subject of which is closely related to the topic (1969-2023)

Effects of Surface Layer Physics Schemes on the Simulated Intensity and Structure of Typhoon Rai (2021)

The influences of surface layer (SL) physics schemes on the simulated intensity and structure of Typhoon Rai (2021) are investigated using the WRF model. Numerical experiments using different SL physics schemes—revised MM5 scheme (MM5), Eta similarity scheme (CTL), and Mellor–Yamada–Nakanishi–Niino scheme (MYNN)—are conducted. The results show that the intensity forecast of Typhoon Rai is largely influenced by SL physics schemes, while its track forecast is not significantly affected. All three experiments can successfully capture the movement of Rai, while CTL provides better intensity simulation compared to the other two experiments. The higher ratio of enthalpy exchange coefficient to drag coefficient (CK/CD) in CTL than MM5 and MYNN leads to significantly increased surface enthalpy fluxes, which are crucial for the typhoon intensification of the former. To explore the influence of SL physics on the structural evolution of the typhoon, the azimuthal-mean angular momentum (AM) budget is utilized. The results indicate that asymmetric eddy terms may also largely contribute to the AM tendencies, which are relatively more comparable in the weaker TC for MM5, compared to the stronger TC with the dominant symmetric mean terms for CTL. Furthermore, the extended Sawyer–Eliassen (SE) equation is solved to quantify the transverse circulations of the typhoon induced by different forcing sources for CTL and MM5. The SE solution indicates that the transverse circulation above and within the boundary layer is predominantly induced by diabatic heating and turbulent friction, respectively, for both CTL and MM5, while all other physical forcing terms are relatively insignificant for the induced transverse circulation for CTL, except for the large contribution from the eddy forcing in the upper-tropospheric outflow for MM5. With the stronger connective heating in the eyewall and boundary-layer radial inflow, the linear SE analysis agrees much better with the nonlinear simulation for CTL than MM5.

The Ensemble Tangent Linear Model Applied to a Cloud Physics Parameterization

Abstract An Ensemble Tangent Linear Model (ETLM) is applied to a cloud physics scheme used in the Navy Global Environmental Model (NAVGEM). The ensemble is created using 3-hour forecasts from the Ensemble Transform method used in the NAVGEM data assimilation system. The model states are saved before and after applying the cloud physics parameterization (which includes condensation/evaporation of cloud ice and cloud liquid water and stratiform precipitation), and these states are used to construct linearized model tendencies for temperature, specific humidity, cloud liquid water, and cloud ice water. We examine separately the application of the ETLM to cloud physics components that are explicitly local versus non-local. For the local components, an ETLM is built using a single grid point. ETLMs from 50 to 1000 members are tested, and skillful forecasts can be obtained for both local and non-local physics even with a moderate sized ensemble (e.g., 100 members). At 1000 members, the globally-averaged forecast error reductions (relative to persistence errors) are ∼40% for temperature, water vapor, and cloud liquid water and ∼30% for cloud ice. When initial perturbations are reduced by a factor of 0.1, the error reductions increase to ∼65% for all variables. For physics with non-local components (stratiform precipitation) the covariances that comprise the ETLM are localized with a Schur product matrix using a Gaussian localization shape with tunable length. The optimal lengths increased with ensemble size from ∼2-3 km for 50 members to ∼10 km for 1000 members. ETLMs for “all cloud physics” are also constructed and evaluated.

Optimizing Numerical Weather Prediction Utility of the Maryland Mesonet with Observing System Simulation Experiments

Abstract The Maryland Mesonet Project will construct a network of 75 surface observing stations with aims that include mitigating the statewide impact of severe convective storms and improving analyses of record. The spatial configuration of mesonet stations is expected to affect the utility newly provided observations will have via data assimilation, making it desirable to study the effects of mesonet configuration. Furthermore, the impact associated with any observing system configuration is constrained by errors inherent to the prediction systems used to generate forecasts, which may change with future advances in data assimilation methodology, physical parameterization schemes, and resource availability. To address such possibilities, we perform sets of observing system simulation experiments using a high-resolution regional modeling system to assess the expected impact of four candidate mesonet configurations. Experiments cover seven 18-hour case-study events featuring moist convective regimes associated with severe weather over the state of Maryland and are performed using two versions of our experimental modeling system: a ’standard-uncertainty’ configuration tuned to be representative of existing convective-allowing prediction systems, and a ’constrained-uncertainty’ configuration with reduced boundary condition and model error that reflects a possible trajectory for future prediction systems. We find that the assimilation of mesonet data produces definitive improvements to analysis fields below 1000 m that are mediated by modeling system uncertainty. Conversely, mesonet impact on forecast verification is inconclusive and strongly variable across verification metrics. The impact of mesonet configuration appears limited by a saturation effect that caps local analysis improvements past a minimal density of observing stations.

Numerical Investigation of Track and Intensity Evolution of Typhoon Doksuri (2023)

This study utilized the WRF model to investigate the track evolution and rapid intensification (RI) of Typhoon Doksuri (2023) as it moved across the Luzon Strait and through the South China Sea (SCS). The simulation results indicate that Doksuri has a smaller track sensitivity to the use of different physics schemes, while having a greater intensity sensitivity. Sensitivity numerical experiments with different physics schemes can well capture its northwestward movement in the first two days, but they predict less westward track deflection as the typhoon moves across the Luzon Strait and through the SCS. Moreover, all the experiments successfully simulated Doksuri’s RI, albeit with quite different rates and a time lag of 12 h. Among different combinations of physics schemes, there exists an optimal set of cumulus parameterization and cloud microphysics schemes for track and intensity predictions. Doksuri’s track changes as the typhoon moved across the Luzon Strait and through the SCS were influenced by the topographic effects of the terrain of the Philippines and Taiwan, to different extents. The track changes of Doksuri are explained by the wavenumber-one potential vorticity (PV) tendency budget from different physical processes, highlighting that the horizontal PV advection dominates the PV tendency throughout most of the simulation time due to the offset of vertical PV advection and differential diabatic heating. In addition, this study applies the extended Sawyer–Eliassen (SE) equation to compare the transverse circulations of the typhoon induced by various forcing sources. The SE solution indicates that radial inflow was largely driven in the lower-tropospheric vortex by strong diabatic heating, while being significantly enhanced in the lower boundary layer due to turbulent friction. All other physical forcing terms were relatively insignificant for the induced transverse circulation. The coordinated radial inflow at low levels may have led to the eyewall development in unbalanced dynamics. Intense diabatic heating thus was vital to the severe RI of Doksuri under a weak vertical wind shear.

Sensitivity of Cumulus Physics in ARW Model on Track of Tropical Cyclones ‘Amphan’ and ‘Bulbul’ over the Bay of Bengal

The Advanced Research Weather Research and Forecasting (ARW) model performance can be improved by analyzing the sensitivity of the physical parameterization schemes. In order to revalidate the performance of the ARW model in relation to the selection of Cumulus Physics (CP) schemes, the sensitivity of CP schemes for Tropical Cyclones (TCs) over the Bay of Bengal (BoB) region has been examined. National Centre for Environment Prediction (NCEP)’s Final Reanalysis (FNL) data (1010) have been used as lateral and initial conditions in the ARW model. The model has been configured in a single domain and runs for four different initial conditions in simulating TC ‘Amphan’ and for three different initial conditions in simulating TC ‘Bulbul’. In this study, average track errors have been found between 40-50 km for Kain-Fritsch Cumulus Potential (KFCP) and Multi-Scale Kain-Fritsch (MSKF) schemes for TC Amphan and below 60 km for the Kain Fritsch (KF) scheme for TC Bulbul. Lower landfall position error has been found below 60 km for the KF scheme for TC Amphan, and 40 km for KFCP and MSKF schemes for TC Bulbul. Journal of Engineering Science 15(1), 2024, 119-129

Influence of weather research and forecasting model microphysics and cumulus schemes for forecasting monsoon rainfall over the Kelani River basin, Sri Lanka

ABSTRACT Creating precise quantitative precipitation forecasts is essential for reducing losses and damages. This study aimed to identify the best microphysics and cumulus schemes for forecasting monsoon rainfall over the Kelani River basin, Sri Lanka, using the WRF-ARW model. Four extreme rainfall events from the 2020 and 2021 monsoon seasons were simulated with various microphysics and cumulus parameterizations to find the optimal combinations. These combinations were then tested for their ability to forecast two monsoon events with a 24-h lead time. Simulated and forecasted rainfalls were compared with observations from 15 gauging stations. Results indicate that WSM3 and WSM6 microphysics schemes with the Betts–Miller–Janjic (BMJ) cumulus scheme are optimal for simulating rainfall, with WSM3_BMJ being the most suitable for forecasting. The findings of this study provide valuable initial data for research in regions with similar environmental conditions, offering insights into the suitability of various physics schemes for simulating and forecasting monsoon rainfall, particularly under extreme conditions. Furthermore, given the prevalence of monsoons in many tropical and subtropical climates, these results will be instrumental in enhancing the use of numerical weather prediction models for forecasting monsoon rainfall on a global scale.

S14 Physical activity promotion in healthcare settings: Designing and implementing physical activity referral schemes

Abstract Purpose This symposium will share findings, expertise and experiences from different countries on the design and implementation of physical activity referral schemes (PARS). Description Physical activity promotion by healthcare professionals is a key strategy to increase population physical activity levels. This strategy has been outlined in the World Health Organisation’s (WHO) ‘Global Action Plan on Physical Activity’ (GAPPA) and the ‘Physical activity strategy for the WHO European Region 2016-2025‘. PARS are a promising intervention that allow healthcare professionals to advocate for physical activity and integrate its promotion into routine clinical care. PARS are a heterogeneous group of interventions. Simpler PARS, for example, may consist only of a written description, while more complex PARS might include different healthcare professionals working together systematically, applying several behaviour change techniques in combination with physical activity practice, to connect patients to community resources. There is currently no consensus on the optimal PARS approach and implementation strategies. Implementers need specific knowledge, skills and methods; however, implementation is also influenced by structural and context-related factors in the healthcare system. Accordingly, a successful implementation of PARS needs co-productive capacity building within healthcare systems and proper support for healthcare professionals. The symposium includes four contributions (3 research-oriented and 1 practise-oriented) related to the design and implementation of PARS in different countries. 1) EUPAP Feasibility Study. Practice transfer of a HEPA prescription model to other nine EU countries. From theory to practice. Sebastià Mas-Alòs 2) The association of physical activity referral scheme’ components with physical activity level, scheme uptake and adherence rates: a systematic review, meta-analysis with meta-regression. Wolfgang Geidl 3) The adoption and implementation of a physical activity referral pathway integrated into a major U.S. health system. Mark Stoutenberg 4) Designing a physical activity pathway in healthcare model for Irish Health Services. Sarah O’Brien This symposium will provide guidance on the development of PARS and future successful implementation in other healthcare settings.

145 Co-producing a physical activity referral scheme for the German healthcare system: A qualitative analysis of stakeholder experiences

Abstract Purpose Physical activity referral schemes (PARS) are a promising strategy to promote physical activity within healthcare settings. Despite the perceived potential of PARS, no national scheme has yet been implemented in Germany. This study investigated stakeholders’ experiences with the development of a PARS in the German healthcare system using a co-production approach. The focus was on examining facilitators and challenges, along with gathering insights on potential modifications to the joint development process, all from the viewpoint of stakeholders. Methods Based on 25 stakeholders participating in the co-production process, seven stakeholders were purposefully selected for one-to-one semi-structured interviews. Following the maximum variation principle, interview partners represented a variety of participating stakeholders regarding the health sector they belong to, the stakeholders’ position within their organization and their attendance during the development phase. We analyzed the interview transcripts using summarizing qualitative content analysis (software MAXQDA 2022). Results The following factors were identified as facilitators of the development process: co-production approach, process of co-production, multi-sector stakeholder group, possibility of active participation, coordinating role of researchers, communication, atmosphere and interaction. In contrast, differences in roles and hierarchy, merging of different perspectives, clarification of intervention costs, and competition and conflicting interests were pointed out as challenges. Interviewees made a few suggestions for improving group composition and cooperation among stakeholders. Conclusions Overall, stakeholder experiences with the development process were overwhelmingly positive, indicating that co-production is a beneficial approach for the development of PARS intended for integration into healthcare systems. To further improve co-production of PARS models and other interdisciplinary health services, scientists should report on and evaluate the collaborative development processes more frequently and systematically. Support/Funding Source The study is funded by the Federal Ministry of Health based on a resolution of the German ‘Bundestag’ by the federal government.

A physical layer security enhancement scheme for CO-OFDM systems based on 3D Brownian motion and TZBN Joint Scramble

In this paper, we propose a scheme for enhancing the physical layer security and transmission performance of coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. The scheme for OFDM data first after 3-dimensional (3D) Brownian motion rotational permutation, and then according to the time zone and band number (TZBN) scrambling to achieve the effect of further data perturbation, which through the SHA-256 algorithm and 6-dimensional (6D) hyperchaotic processing to obtain the chaotic keys to enhance the security. After simulation experiment of 16QAM CO-OFDM security system transmitting over 80 km standard single-mode fiber (SSMF) at the symbol rate of 30 Gbaud, it is shown that the encryption scheme can guarantee that the authorized user receives valid data and the eavesdropper obtains the information with the BER of about 0.5. The key space of the scheme is about 2.88×10194, which can effectively resist attacks such as violent attacks and chosen plaintext attacks. And the peak-to-average power ratio (PAPR) can be reduced by about 1.09 dB while the encryption process.

The Role of Forcing and Parameterization in Improving Snow Simulation in the Upper Colorado River Basin Using the National Water Model

AbstractThis study assesses snow water equivalent (SWE) simulation uncertainty in the National Water Model (NWM) due to forcing and model parameterization, using data from 46 Snow Telemetry (SNOTEL) sites in the Upper Colorado River Basin (UCRB). We evaluated the newly developed Analysis of Record for Calibration (AORC) forcing data for SWE simulation and examined the impact of bias correction applied to AORC precipitation and temperature. Additionally, we investigated the sensitivity of SWE simulations to choices of physical parameterization schemes through 72 ensemble experiments. Results showed that NWM driven by AORC forcings captured the overall temporal variation of SWE but underestimated its amount. Adjusting AORC precipitation with SNOTEL observations reduced SWE root‐mean‐square error (RMSE) by 66%, adjusting temperature trimmed it by 10%, and adjusting both decreased it by 69%. Among the physical processes, the snow/soil temperature time scheme (STC) demonstrated the highest sensitivity, followed by the surface exchange coefficient for heat (SFC), snow surface albedo (ALB), and rainfall and snowfall partitioning (SNF), while the lower boundary of soil temperature (TBOT) proved to be insensitive. Further optimization of the parameterization combination resulted in a 12% SWE RMSE reduction. When combined with the bias‐corrected AORC precipitation and temperature, this optimization led to a remarkable 78% SWE RMSE reduction. Despite these enhancements, a persistent slow and late spring ablation suggests model deficiencies in snow ablation physics. The study emphasizes the critical need to enhance the accuracy of forcing data in mountainous regions and address model parameterization uncertainty through optimization efforts.

Improving Hurricane Intensity and Streamflow Forecasts in Coupled Hydrometeorological Simulations by Analyzing Precipitation and Boundary Layer Schemes

Abstract Hurricanes have been the most destructive and expensive hydrometeorological event in U.S. history, causing catastrophic winds and floods. Hurricane dynamics can significantly impact the amount and spatial extent of storm precipitation. However, the complex interactions of hurricane intensity and precipitation and the impacts of improving hurricane dynamics on streamflow forecasts are not well established yet. This paper addresses these gaps by comprehensively characterizing the role of vertical diffusion in improving hurricane intensity and streamflow forecasts under different planetary boundary layer, microphysics, and cumulus parameterizations. To this end, the Weather Research and Forecasting (WRF) atmospheric model is coupled with the WRF hydrological (WRF-Hydro) model to simulate four major hurricanes landfalling in three hurricane-prone regions in the United States. First, a stepwise calibration is carried out in WRF-Hydro, which remarkably reduces streamflow forecast errors compared to the U.S. Geological Survey (USGS) gauges. Then, 60 coupled hydrometeorological simulations were conducted to evaluate the performance of current weather parameterizations. All schemes were shown to underestimate the observed intensity of the considered major hurricanes since their diffusion is overdissipative for hurricane flow simulations. By reducing the vertical diffusion, hurricane intensity forecasts were improved by ∼39.5% on average compared to the default models. These intensified hurricanes generated more intense and localized precipitation forcing. This enhancement in intensity led to ∼16% and ∼34% improvements in hurricane streamflow bias and correlation forecasts, respectively. The research underscores the role of improved hurricane dynamics in enhancing flood predictions and provides new insights into the impacts of vertical diffusion on hurricane intensity and streamflow forecasts. Significance Statement Despite significant recent improvements, numerical weather prediction models struggle to accurately forecast hurricane intensity and track due to many reasons such as inaccurate physical parameterization for hurricane flows. Furthermore, the performance of existing physics schemes is not well studied for hurricane flood forecasting. This study bridges these knowledge gaps by extensively evaluating different physical parameterizations for hurricane track, intensity, and flood forecasts using an atmospheric model coupled with a hydrological model. Then, a reduced diffusion boundary layer scheme is developed, making remarkable improvements in hurricane intensity forecasts due to the overdissipative nature of the considered schemes for major hurricane simulations. This reduced diffusion model is shown to significantly enhance hurricane flood forecasts, indicating the significance of hurricane dynamics on its induced precipitation.

Performance ranking of multiple CORDEX-SEA sensitivity experiments: towards an optimum choice of physical schemes for RegCM over Southeast Asia

Performance ranking of multiple CORDEX-SEA sensitivity experiments: towards an optimum choice of physical schemes for RegCM over Southeast Asia