Planetary Boundary Layer Schemes Research Articles

The Role of Physical Parameterization Schemes in Capturing the Characteristics of Extratropical Cyclones Over the South Pacific Ocean

AbstractThe extratropical cyclone (ETC) of August 2015 in central Chile was investigated using the WRF model to analyze the sensitivity of meteorological variables to different physical parameterization schemes. This study assesses the performance of different physical schemes in the simulation of track, core pressure, mean sea level pressure, wind direction and wind speed associated with ETC over the South Pacific. The analysis uses a total of 36 sensitivity experiments, consisting of: two microphysics schemes; three surface layer and planetary boundary layer; two cumulus schemes; two longwave and shortwave radiation; and Noah for land surface. Sensitivity experiments indicate that the cumulus, planetary boundary layer and surface layer scheme have a fundamental role in the characterization of ETC track and intensity, while the microphysics scheme plays a secondary role in determining these variables. On the other hand, long‐ and shortwave radiation do not have a significant impact. The sensitivity experiments indicate that exp24 provides the best results overall. The results of this work allow the selection time of the different physical schemes to be optimized according to the ETC characteristics that are to be simulated

WRF Model Parameterization Around the Highland Titicaca Lake

AbstractThe computational advances and many times the lack of meteorological measurements in some regions of the world impulse the employment of numerical methods for covering this deficiency of data, and the parameterization is a key factor for use and operation of numerical weather prediction models. The Weather Research & Forecasting (WRF) as one of the most important models has been scarcely parameterized in the Bolivian Altiplano and Titicaca Lake. This work evaluates different physics models and focus the parameterization in the planetary boundary layer (PBL) schemes. This study evaluates the performance of land surface, radiation, convective and microphysics models using WRFv3.8.1. The results showed well‐prediction with NOAH, THOMPSON, and RRTMG for land surface, microphysics and radiation schemes, respectively. For the PBL parameterization QNSE, YSU, MYJ, MYNN, and QNSE‐FDDA were evaluated for wind speed, temperature, and mixing ratio. The minimum root mean square error were 2.025 m s−1(QNSE‐FDDA) for wind speed, 1.721 K (YSU) for temperature, and 0.786 g kg−1(MJY) for mixing ratio. In summary, the results have shown that QNSE scheme well‐predicts wind speed and water mixing ratio. However, using FDDA only wind speed and water mixing ratio were improved, and the temperature prediction becomes worse. These results suggest an underprediction of incoming solar radiation due to temperature and water mixing ratio were underestimated near the Titicaca Lake.

Optimization of physical schemes in WRF model on cyclone simulations over Bay of Bengal using one-way ANOVA and Tukey\u2019s test

Evaluation of appropriate physics parameterization schemes for the Weather Research and Forecasting (WRF) model is vital for accurately forecasting tropical cyclones. Three cyclones Nargis, Titli and Fani have been chosen to investigate the combination of five cloud microphysics (MP), three cumulus convection (CC), and two planetary boundary layer (PBL) schemes of the WRF model (ver. 4.0) with ARW core with respect to track and intensity to determine an optimal combination of these physical schemes. The initial and boundary conditions for sensitivity experiments are drawn from the National Centers for Environmental Prediction (NCEP) global forecasting system (GFS) data. Simulated track and intensity of three cyclonic cases are compared with the India Meteorological Department (IMD) observations. One-way analysis of variance (ANOVA) is applied to check the significance of the data obtained from the model. Further, Tukey’s test is applied for post-hoc analysis in order to identify the cluster of treatments close to IMD observations for all three cyclones. Results are obtained through the statistical analysis; average root means square error (RMSE) of intensity throughout the cyclone period and time error at landfall with the step-by-step elimination method. Through the elimination method, the optimal scheme combination is obtained. The YSU planetary boundary layer with Kain–Fritsch cumulus convection and Ferrier microphysics scheme combination is identified as an optimal combination in this study for the forecasting of tropical cyclones over the Bay of Bengal.

Convection-permitting fully coupled WRF-Hydro ensemble simulations in high mountain environment: impact of boundary layer- and lateral flow parameterizations on land–atmosphere interactions

Numerical climate models have been upgraded by the improved description of terrestrial hydrological processes across different scales. The goal of this study is to explore the role of terrestrial hydrological processes on land–atmosphere interactions within the context of modeling uncertainties related to model physics parameterization. The models applied are the Weather Research and Forecasting (WRF) model and its coupled hydrological modeling system WRF-Hydro, which depicts the lateral terrestrial hydrological processes and further allows their feedback to the atmosphere. We conducted convection-permitting simulations (3 km) over the Heihe River Basin in Northwest China for the period 2008–2010, and particularly focused on its upper reach area of complex high mountains. In order to account for the modeling uncertainties associated with model physics parameterization, an ensemble of simulations is generated by varying the planetary boundary layer (PBL) schemes. We embedded the fully three-dimensional atmospheric water tagging method in both WRF and WRF-Hydro for quantifying the strength of land–atmosphere interactions. The impact of PBL parameterization on land–atmosphere interactions is evaluated through its direct effect on vertical mixing. Results suggest that enabled lateral terrestrial flow in WRF-Hydro distinctly increases soil moisture and evapotranspiration near the surface in the high mountains, thereby modifies the atmospheric condition regardless of the applied PBL scheme. The local precipitation recycling ratio in the study area increases from 1.52 to 1.9% due to the description of lateral terrestrial flow, and such positive feedback processes are irrespective of the modeling variability caused by PBL parameterizations. This study highlights the non-negligible contribution of lateral terrestrial flow to local precipitation recycling, indicating the potential of the fully coupled modeling in land–atmosphere interactions research.

An Investigation of the Impact of Different Turbulence Schemes on the Tropical Cyclone Boundary Layer at Turbulent Gray‐Zone Resolution

AbstractAccurately resolving turbulence in the tropical‐cyclone boundary layer (TCBL) is crucial for realistic simulations of tropical cyclones (TCs), but how well the fine‐scale structure of the simulated TCBL can be reproduced at gray‐zone resolutions by state‐of‐the‐art planetary boundary layer (PBL) parameterization schemes, and why the simulated fine‐scale structure is so sensitive to the PBL scheme, are yet to be evaluated and understood. To address these issues, a series of numerical experiments under idealized conditions were conducted using the advanced research weather research and forecasting (WRF‐ARW) model at 500 and 166 m grid spacing. An 18‐hr WRF‐ARW large‐eddy simulation (LES) with a 55‐m grid spacing based on the nonlinear backscatter and anisotropy subfilter‐scale (NBA‐SFS) stress scheme was used as reference (RLES). Results from experiments using five different PBL schemes, that is, two conventional schemes—the Yonsei University (YSU) and the original MYNN (termed MYNN1)—two scale‐aware schemes—the Shin‐Hong (S‐H) and the revised MYNN (termed MYNN2)—and the coarse‐resolution LES (CLES), were subsequently compared with the RLES. The YSU and S‐H not only produced better simulations of TC intensity and structure than the other three PBL schemes, but also produced a fine‐scale turbulent structure reasonably well compared with the RLES. Discrepancies in the simulated fine‐scale structure among the PBL schemes result primarily from the different strength of vertical mixing, which could be reduced by the scale‐aware option. Results from a series of sensitivity experiments with a 166‐m grid spacing demonstrate that the scale‐aware S‐H can significantly improve the finer resolution simulations than the conventional YSU at relatively finer grid spacing at gray zone.

Prediction of soil moisture and rainfall induced landslides: A comparison of several PBL parameters in the WRF model

Rainfall intensity thresholds only do not take advantage of the awareness of the slope's hydrological processes, so they appear to produce large false and missed alert rates, decreasing the credibility of early warning systems for landslides. This study analyzes this dilemma by modeling the behavior of slopes to precipitation, including the potential effect of soil moisture uncertainty given by numerical modeling. For the simulation of soil moisture during the study period and event rainfall thresholds of an extreme event used to describe the intensity of a rainfall event, the Weather Research and Forecasting (WRF) model is used. The three days simulation conducted during a landslide event in Samigaluh, Kulon Progo on 28 November 2018. The four Planetary Boundary Layer (PBL) parameters in the WRF model are compared to understand each character, i.e., Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), Shin-Hong (SH), and Bougeault-Lacarrère (BL). To evaluate the precipitation as simulated by WRF, we use observation data from rain gauge and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). In general, all parameters have an underestimation of precipitation. Each PBL parameter's response to rainfall is different. Both MYJ and SH schemes are closer to observation than others for day 1 and day 2 of simulation, daily precipitation. For all PBL schemes, increased soil moisture is seen, suggesting that the soil is wetter and more vulnerable to landslide events. As an early warning predictor of landslides in terms of rainfall parameters, the SH method is very useful in this analysis. For early warning of landslides, a short period (<6 hours) of precipitation with a high accumulation of precipitation would be very beneficial.

Simulation of Intensity, Track and Landfall of Tropical Cyclonic Storm Roanu over the Bay of Bengal Using WRF-ARW Model

Almost every year, tropical cyclone forms over the Bay of Bengal in pre-monsoon and post-monsoon which strikes Bangladesh coast and the east coast of India. As the full thermodynamic features of a cyclone is not solved yet, an attempt has been made to simulate the track and landfall of cyclonic disturbances over the Bay of Bengal by using Weather Research and Forecasting (WRF) model. The WRF model (version 3.8) was run in a single domain of 20 km horizontal resolution. The model was run using WRF Single-Moment 3- class microphysics scheme, Kain- Fritsch (new Eta) cumulus physics scheme, Yonsei University planetary boundary layer scheme, revised MM5 surface layer physics scheme, Rapid Radiative Transfer Model (RRTM) for long-wave and Dudhia scheme for short-wave scheme. The model was run for 24-h, 48-h, 72-h and 96-h using the National Centre for Environmental Prediction (NCEP) high-resolution Global Final (FNL) Analysis 6-hourly data using initial and lateral boundary conditions. The model simulated landfall position errors are found 53 km, 129 km, 119km and 23 km and time errors are found 02 E, 06 D, 02 E and 00 for 96-h, 72-h, 48-h and 24-h model run respectively (E indicates Earlier and D indicates Delay). The minimum time and position error is found in 24-hrs simulation. The spatial distribution is captured by the model is almost appropriate but the computational station rainfall is found less than that of observed rainfall. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(1), 2021, P 33-45

A nonlocal three‐dimensional turbulence parameterization (NLT3D) for numerical weather prediction models

AbstractWith increasing resolution of numerical weather prediction (NWP) models, classical subgrid‐scale processes become increasingly resolved on the model grid. In particular, turbulence in the planetary boundary layer (PBL) is vertically already partially resolved in contemporary models. For classical local PBL schemes, resulting up‐gradient heat transports cannot be treated correctly. Thus, nonlocal turbulence schemes have been developed in the past. As the horizontal grid sizes of NWP models become smaller than a few kilometers, the large turbulence eddies in the PBL will also start to become partially resolved in the horizontal direction. A very flexible way to formulate nonlocal turbulent exchange is the transilient matrix method, which is used here to develop a new turbulence parameterization. The resulting NLT scheme applies transilient mixing matrices to subgrid‐scale transports in all three dimensions. We compare results of WRF real‐case simulations including our scheme, a classical local turbulence scheme (MYNN), and an existing nonlocal one‐dimensional scheme (ACM2) with observations from field campaigns over homogeneous terrain (CASES‐99) and complex terrain (CAPTEX). Over homogeneous terrain, all three schemes similarly well capture the observed surface fluxes and radiosonde profiles, whereas over complex terrain more differences become obvious. During a tracer release experiment (CAPTEX) over the Appalachian mountain region, the mixing and vertical extent of the PBL turn out to be decisive to reproduce the observed advection speed of the tracer‐marked air mass. Deeper mixing not only accelerates surface winds but also enables tracer to travel faster at higher altitudes and then mix back to the ground. As results from a version of NLT with only standard horizontal Smagorinsky diffusion (NLT) demonstrate, simulating three‐dimensional turbulence can be beneficial already at horizontal grid sizes of a few kilometers.

Simulation of tropical cyclones over the Bay of Bengal during 1999-2013 : Impact of physical parameterization schemes

Tropical Cyclone (TC) is one of the most devastating and deadly weather phenomena and causes loss of life and property. The Bay of Bengal (BoB) is a potentially energetic region for the development of cyclonic storms, accounting about 6% of the global annual total number of cyclonic storms. Accurate prediction of these storms is essential to avoid loss of lives and damage to properties. In this regard, the reduction of errors associated with the track and intensity forecast of the TCs is an important aspect to disseminate more reliable information to the disaster management. The present study examined the performance of Advanced Research Weather Research and Forecasting (WRF-ARW) model for the simulation of track and intensity of TCs over BoB during 1999-2013. The numerical simulations were carried out for 38-cyclones (during 1999-2013) using different microphysical parameterization (MP), cumulus parameterization (CP) and planetary boundary layer (PBL) schemes of the WRF-ARW model. The total 1133 simulations were performed by using 11 combinations with four MPs [Lin et al. (LIN), Ferrier (new Eta) (FERR), WSM 6-class Scheme graupel scheme (WSM6) and Thompson (THOMP)], four CPs [Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-Devenyi (GD) and New Grell Scheme (NG)] and three PBLs (Yonsei University scheme (YSU), Mellor-Yamada-Janjic (Eta) TKE (MYJ) and Asymmetrical Convective Model version 2 (ACM2)] to identify the best logical combination of these schemes to predict the track and intensity of TCs over BoB. The best combination of CP and PBL schemes were more influenced the simulations of intensity and track of the cyclones compared to the MP schemes. Further, the simulations were conducted for intense storms with different initial conditions and suggested that the combination of KF + LIN + YSU provided better simulations of the storms for 72h over the BoB and also observed the decreased track error from 1999 to 2013 cyclones. This clearly indicated that the improvement in the initial conditions and parameterization schemes of the WRF-ARW model. This study is very useful for the cyclone warning centers, disaster management centers, real-time governance system and researchers to provide better management for coastal community during the cyclone events.

A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea

Abstract. One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating the subgrid-scale physical processes. For more accurate regional weather and climate prediction by improving physics parameterizations, it is important to optimize a combination of physics schemes and unknown parameters in NWP models. We have developed an interface system between a micro-genetic algorithm (µ-GA) and the WRF model for the combinatorial optimization of cumulus (CU), microphysics (MP), and planetary boundary layer (PBL) schemes in terms of quantitative precipitation forecast for heavy rainfall events in Korea. The µ-GA successfully improved simulated precipitation despite the nonlinear relationship among the physics schemes. During the evolution process, MP schemes control grid-resolving-scale precipitation, while CU and PBL schemes determine subgrid-scale precipitation. This study demonstrates that the combinatorial optimization of physics schemes in the WRF model is one possible solution to enhance the forecast skill of precipitation.

The impacts of multi-physics parameterization on forecasting heavy rainfall induced by weak landfalling Typhoon Rumbia (2018)

The weak and sustained tropical cyclone (TC) Rumbia (2018) and its associated heavy precipitation after landfall are simulated by the Weather Research and Forecasting model using three microphysics parameterizations (MP) and two planetary boundary layer (PBL) schemes. Key factors regulating the heavy rainfall distribution of landed TC at three stages (landfall, inland slow-moving and recurving stage) and their sensitivities to multi-physics parameterizations are examined. Results show that heavy rainfall distribution is largely regulated by the intensity of TC itself at landfall, but more affected by environmental factors at the two inland stages, including the environmental vertical wind shear, the associated upper-level wind divergence and low-level moisture convergence. Different MP and PBL schemes mainly affect the simulation of TC thermodynamic structure and key environmental factors, leading to their different forecast skills at three stages. Specifically, the Yonsei University (YSU) PBL scheme systematically outperforms the Mellor-Yamada-Nakanishi-Niino (MYNN) scheme in simulating stronger TC and heavy rainfall intensity. With the advantageous YSU PBL scheme, the Ferrier MP scheme only shows a slight advantage in simulating the intensity of TC and heavy rainfall at landfall. However, the WRF single-moment 6-class (WSM6) and Thompson scheme produce more graupel or snow, and better simulate the key environmental factors, showing their respective advantages in simulating the heavy rainfall structure and location at the two inland stages. This implies that the use of nonlocal YSU PBL scheme and the MP schemes with sophisticated ice processes shows superiority in simulating the postlandfall heavy rainfall induced by weak TCs.

Sensitivity analysis of planetary boundary layer schemes using the WRF model in Northern Colombia during 2016 dry season

This study conducted meteorological simulations in northern Colombia by analyzing different planetary boundary layer (PBL) schemes available in the numerical Weather Research and Forecasting (WRF) model. The study area included three nested domains with horizontal resolutions of 18 km, 6 km, and 2 km, with 38 vertical levels. The evolution and structure of the PBL were analyzed during the driest months (March, April, and May 2016) and in regions with the highest particulate matter concentrations. Sensitivity analysis of the WRF model was performed with two local and two non-local PBL schemes. The results were validated using observations of the surface air temperature, relative humidity, and surface wind speed collected from three meteorological stations in the area. The PBL heights were experimentally determined using radiosonde data provided by a station located in the center of the study area. Variations in PBL heights were estimated using linear regression methods and minimization of statistical errors for the bulk Richardson number, as well as analysis of vertical temperature and wind profiles. The WRF model reliably reproduced the daily values and diurnal cycles of temperature, relative humidity, and wind speed within the PBL and accounted for the influence of topography and sea breezes. Horizontal heat advection dominates the upwelling of air masses when sea breezes are active. The onshore wind direction starts to change from east to northwest, implying a decay in the land breeze regime. All schemes overestimate the mixing height and tend to underestimate surface air temperature values at night. All show wetter conditions and underestimate wind speed. Although the non-local Yonsei University (YSU) scheme shows the best performance, it also shows the largest sources of errors when determining the behavior of the surface layer during stable conditions. Relative humidity and wind speed estimates provided by the local Mellor‐Yamada‐Nakanishi‐Niino (MYNN) scheme were closer to those recorded at the meteorological stations.

Influence on the temperature estimation of the planetary boundary layer scheme with different minimum eddy diffusivity in WRF v3.9.1.1

Abstract. The minimum eddy diffusivity (Kzmin⁡) in the planetary boundary layer (PBL) scheme can influence the model performance when simulating meteorological parameters such as temperature. However, detailed studies on the sensitivities of the simulated temperatures to the settings of Kzmin⁡ are still lacking. Thus, in this study we evaluated the performance of the ACM2 (Asymmetrical Convective Model version 2) scheme in the WRF (Weather Research and Forecasting) model with different Kzmin⁡ settings when simulating the spatiotemporal distribution of the temperature in the region of Beijing, China. Five constant values and a function were implemented in the model to calculate Kzmin⁡, and the simulation results with different Kzmin⁡ settings were compared and analyzed. The results show that the increase in Kzmin⁡ leads to an elevation of the 2 m temperature, especially at nighttime. We figured out that the deviation in the 2 m temperature at night is mainly caused by the different estimations of the turbulent mixing under stable conditions in simulation scenarios with different Kzmin⁡ settings. Moreover, the spatial distribution of the temperature deviation indicates that under various underlying surface categories, the change in Kzmin⁡ exerts a distinct influence on the prediction of the 2 m temperature. This influence was found to be stronger during the nighttime than during the daytime, in plain areas than in mountain areas, and in urban areas than in non-urban areas. During the night in the urban areas, the influence on the simulated 2 m temperature brought about by the change in Kzmin⁡ is the strongest. In addition, the model performance using a functional-type Kzmin⁡ in the ACM2 scheme for capturing the spatiotemporal distribution of the temperature in this region was also compared with that using a constant Kzmin⁡.

A note on surface layer parameterizations in the weather research and forecast model

Two surface layer parameterization schemes along with five planetary boundary layer (PBL) schemes in the Weather Research and Forecasting model (WRF) are analyzed in order to evaluate the performance of the WRF model in simulating the surface variables and turbulent fluxes over an Indian sub-continent region. These surface layer schemes are based on the fifth-generation Pennsylvania State University—National Center for Atmospheric Research Mesoscale Model (MM5) parameterization; (a) Old MM5 scheme having Businger-Dyer similarity functions and (b) revised MM5 scheme utilizing the functions that are valid for full ranges of atmospheric stabilities. The study suggests that each PBL scheme can reproduce the diurnal variation of 2 m temperature, momentum flux and sensible heat flux irrespective of the surface layer scheme used for the simulations. However, a comparison of model-simulated values of surface variables and turbulent fluxes with observed values suggests that each PBL scheme is found to systematically over-estimate the nocturnal 2 m temperature and 10 m wind speed with both the revised and old schemes during stable conditions.

A rapid refresh ensemble based data assimilation and forecast system for the RELAMPAGO field campaign

This paper describes the lessons learned from the implementation of a regional ensemble data assimilation and forecast system during the intensive observing period of the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign (central Argentina, November–December 2018). This system is based on the coupling of the Weather Research and Forecasting (WRF) model and the Local Ensemble Transform Kalman Filter (LETKF). It combines multiple data sources both global and locally available like high-resolution surface networks, AMDAR data from local aircraft flights, soundings, AIRS retrievals, high-resolution GOES-16 wind estimates, and local radar data. Hourly analyses with grid spacing of 10 km are generated along with warm-start 36-h ensemble-forecasts, which are initialized from the rapid refresh analyses every three hours. A preliminary evaluation shows that a forecast error reduction is achieved due to the assimilated observations. However, cold-start forecasts initialized from the Global Forecasting System Analysis slightly outperform the ones initialized from the regional assimilation system discussed in this paper. The system uses a multi-physics approach, focused on the use of different cumulus and planetary boundary layer schemes allowing us to conduct an evaluation of different model configurations over central Argentina. We found that the best combinations for forecasting surface variables differ from the best ones for forecasting precipitation, and that differences among the schemes tend to dominate the forecast ensemble spread for variables like precipitation. Lessons learned from this experimental system are part of the legacy of the RELAMPAGO field campaign for the development of advanced operational data assimilation systems in South America.

Simulated potential wind power sensitivity to the planetary boundary layer parameterizations combined with various topography datasets in the weather research and forecasting model

Wind power simulation was validated to be sensitive to the planetary boundary layer (PBL) parameterization schemes in the Weather Researching and Forecasting (WRF) model. However, the performance of PBL schemes was rarely evaluated under different resolutions of topography. In this study, we present a sensitivity study to figure out how the resolution of the topography database will influence the performance of PBL schemes. It refers not only to the individual impact of the PBL schemes and topography datasets on wind speed prediction but also the combined interactions. Hourly simulated wind speeds are compared with the measurements at different heights, and these differences are statistically analyzed in both stable and unstable surface layers under the flat and complex terrain. The results show that the Yonsei University (YSU) scheme offers consistently good predictions, however, the Mellor-Yamada-Janjic (MYJ) scheme which has poor performance still provides acceptable outcomes under high-resolution topography. The wind speed shows low sensitivity to the PBL schemes and the relevant wind power density is nearly declined by 6% with refined resolution topography datasets over the complex terrain. Accordingly, a precise topography dataset can increase the simulated robustness of potential wind power prediction.

Role of Advection of Parameterized Turbulence Kinetic Energy in Idealized Tropical Cyclone Simulations

AbstractHorizontal homogeneity is typically assumed in the design of planetary boundary layer (PBL) parameterizations in weather prediction models. Consistent with this assumption, PBL schemes with predictive equations for subgrid turbulence kinetic energy (TKE) typically neglect advection of TKE. However, tropical cyclone (TC) boundary layers are inhomogeneous, particularly in the eyewall. To gain further insight, this study examines the effect of advection of TKE using the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme in idealized TC simulations. The analysis focuses on two simulations, one that includes TKE advection (CTL) and one that does not (NoADV). Results show that relatively large TKE in the eyewall above 2 km is predominantly attributable to vertical advection of TKE in CTL. Interestingly, buoyancy production of TKE is negative in this region in both simulations; thus, buoyancy effects cannot explain observed columns of TKE in TC eyewalls. Both horizontal and vertical advection of TKE tends to reduce TKE and vertical viscosity (Km) in the near-surface inflow layer, particularly in the eyewall of TCs. Results also show that the simulated TC in CTL has slightly stronger maximum winds, slightly smaller radius of maximum wind (RMW), and ~5% smaller radius of gale-force wind than in NoADV. These differences are consistent with absolute angular momentum being advected to smaller radii in CTL. Sensitivity simulations further reveal that the differences between CTL and NoADV are more attributable to vertical advection (rather than horizontal advection) of TKE. Recommendations for improvements of PBL schemes that use predictive equations for TKE are also discussed.

Sensitivity Analysis of PBL Physics Schemes of WRF-ARW Model in Simulating the Tropical Cyclone ‘TITLI’ (2018) Over the Bay of Bengal

Tropical Cyclone (TC) is the most destructive weather phenomenon in the Indian sub-continent. To mitigate the destruction due to TC better prediction is needed. So, the study of sensitivity of different physical schemes in WRF-ARW model with intensification and track of TC is important. In this study, sensitivity of Yonsei University (YSU), Asymmetric Convective Model version 2 (ACM2), Bougeault-Lacarrere (Boulac), Medium-Range Forecast (MRF), Mellor-Yamada Nakanishi and Niino Level 2.5 (MYNN2.5) and Level 3 (MYNN3) Planetary Boundary Layer (PBL) schemes are used to simulate the TC ‘Titli’ which made land fall near Palasa in North Andrha Pradesh and South Odhisha coasts at 0000 UTC of 11th October. National center for environmental prediction Global Final Reanalysis (FNL) data have been used as an initial and lateral boundary conditions. Variation of heat flux, latent heat flux and moisture flux with time for these schemes are shown which are responsible to intensify the TC. Model simulated intensity i.e., minimum central pressure, maximum sustained wind speed at the surface (10 m) and track are compared with the India Meteorological Department (IMD) estimated value. It can be specified that the Boulac, MYNN2.5 and MYNN3 schemes simulate the better intensity and track of TC ‘Titli’.

Sensitivity study of PBL schemes and soil initialization using the WRF-BEP-BEM model over a Mediterranean coastal city

Due to increased urbanization and global warming, cities are experiencing more heat wave (HW) events that cause extreme heat stress. To mitigate such effects, a better understanding of the impact of urban morphology on the boundary layer development is needed. This study investigates the sensitivity of mesoscale simulations using the WRF model coupled with the building effect parameterization and the building energy model (BEP-BEM) at a 1-km resolution to 1) soil moisture initializations; 2) the inclusion of site-specific urban morphology parameters; and 3) the planetary boundary layer (PBL) scheme. A HW episode that occurred in the metropolitan area of Barcelona serves as the case study. We find that the use of a high-resolution land data assimilation system (HRLDAS) to initialize soil properties results in larger temperature diurnal range, but it did not improve the performance of simulated temperatures compared to using low-resolution ERA5 data. The inclusion of site-specific urban parameters improved the representation of urban fractions, reducing the night-time overprediction of 2-m temperatures compared to using default urban parameters. Overall, the Bougeault-Lacarrere (BouLac) scheme represents the PBL-height noontime observations better than the Mellor-Yamada-Janjic (MYJ) scheme. This was related to a better representation of daytime near-surface temperatures by the BouLac scheme compared to the MYJ scheme

Sensitivity of near-surface meteorology to PBL schemes in WRF simulations in a port-industrial area with complex terrain

Parameterizations of the Planetary Boundary Layer (PBL) embedded in numerical weather prediction models are crucial in the simulation of local meteorology and require a special investigation. In this study we evaluate simulations at 1 km horizontal resolution using six PBL schemes of the Weather Research and Forecasting model (WRF) by comparison to observations performed in a coastal port-industrial area (Civitavecchia) on the Tyrrhenian coast of Central Italy. During the measurement campaign (April 2016) three types of atmospheric circulation regimes were identified: “breeze”, “jet” and “synoptic”. Some generalizations can be inferred from the results, despite the variety of settings analyzed (two sites, three regimes in both day and night conditions). Our results show that the temperature simulation is much more sensitive to the configuration at night than during the day, especially on breeze days, when the occurrence of stable boundary layer is favored. For wind speed, non-local schemes are very similar to each other, unlike the local closure schemes.The use of the urban Building Environment Parameterization (BEP) significantly improves the simulation of the 2 m temperature during the “jet” evenings and nights, while it entails a further overestimation of the temperature during the “breeze” days leading to a reduction of the bias.