PBL Schemes Research Articles

Modeling of Lightning Events using WRF-derived Microphysical Parameters

Numerical simulation of lightning events in Bangladesh has been carried out by using Weather Research and Forecasting Model with Advanced Research Dynamic solver (WRF-ARW). Three major lightning events have been considered for the case study; Case_1, lightning occurrence in Netrokona district in March 24 2017, Case_2, lightning event in Barishal district in April 23 2017, and case_3, lightning event in Sherpur district in April 29, 2018. The model simulation was run in 9 km and 3 km of horizontal resolution using six hourly NCEP-FNL datasets. Yonsei University (YSU) PBL scheme, Rapid Radiative Transfer Model (RRTM) long-wave scheme for radiation, and Kain-Fritsch cumulus parameterization scheme is used for this study. The obtained results from the simulation could reasonably capture the lightning condition of the atmosphere for all the three cases. The WRF simulation give reasonable agreement with the available observational data with some spatial and temporal variations, for example the Convective Available Potential Energy (CAPE) values observed are 1299 J/Kg, 3150 J/kg, 1221 J/kg and CAPE values simulated are 1618 J/kg, 3275 J/kg and 1023 J/kg for case_1, case_2 and case_3 respectively. The regression analysis of the flash count with the microphysical parameters is also studied. It is found that there is strong correlation between the lightning flash counts with the microphysical parameters. This study will help to understand the lightning better and will help to design a better lightning forecasting system.
 The Dhaka University Journal of Earth and Environmental Sciences, Vol. 8(2), 2019, P 41-50

Segregation of Forecast Errors in the Planetary Boundary Layer Parameterization Over the State of Odisha and Neighboring Regions in India During Summer Monsoon Season

Planetary boundary layer parametrization (PBL) is a key factor influencing weather forecast skills. This article provides a quantitative illustration of the segregation of forecast errors and their growth arising from different PBLs of the Weather Research and Forecasting (WRF) model. The systematic (root mean square) components of forecast errors arising from four different PBLs of the WRF over the state of Odisha (India) and its surrounding regions are elucidated. Error characterizations are carried out for the forecast lead time up to 96 h (day-4) for two contrasting monsoon seasons, i.e., 2013 (normal) and 2014 (deficit). A total of 1112 simulations are carried out for each initial condition, i.e., May 15 to September 29 for both monsoon seasons using four PBL schemes, i.e., Yonsei University (YSU), Mellor–Yamada–Nakanishi-Niino (MYNN), Asymmetric Convective Model version 2 (ACM2), and medium-range forecast (MRF). The overall results suggest the errors in thermodynamical variables (i.e., temperature and relative humidity) are large compared to the dynamical variable (i.e., wind). For the normal monsoon year (i.e., 2013), the MRF and MYNN exhibit the lowest root mean square error (RMSE) of temperature compared to ACM2 and YSU, whereas MRF (MYNN) shows the lowest (highest) error growth at 24–48 h (72–96 h). The deficit year (2014) has a higher temperature error compared to that of the normal monsoon year (2013), which might be due to frequent monsoon break periods. The spatial distribution of wind exhibits the lowest systematic error for MRF with lead time up to 48 h. The subsequent decrease (increase) of convergence (divergence) of error flux over northern Odisha and increase (decrease) of the same over southern Odisha suggests that the error propagation occurs from north to south. In general, both the convergence and divergence of error energy are found to be weak in MRF and MYNN, attributable to the lower error growth rate and hence the smaller systematic errors compared to ACM2 and YSU for both these monsoon seasons. It is also found that the systematic component of the linear (nonlinear) error growth rate is contributed by the physics (dynamics) components of the model. These findings will provide guidance for the model community and operational agencies to make an optimal choice of PBL parameterizations, particularly for the monsoon forecast.

Development of a Single-Column Model in RegCM4 and Its Preliminary Application for Evaluating PBL Schemes in Simulating the Dry Convection Boundary Layer

Development of a Single-Column Model in RegCM4 and Its Preliminary Application for Evaluating PBL Schemes in Simulating the Dry Convection Boundary Layer

Mountain Waves Analysis in the Vicinity of the Madrid-Barajas Airport Using the WRF Model

Turbulence and aircraft icing associated with mountain waves are weather phenomena potentially affecting aviation safety. In this paper, these weather phenomena are analysed in the vicinity of the Adolfo Suárez Madrid-Barajas Airport (Spain). Mountain waves are formed in this area due to the proximity of the Guadarrama mountain range. Twenty different weather research and forecasting (WRF) model configurations are evaluated in an initial analysis. This shows the incompetence of some experiments to capture the phenomenon. The two experiments showing the best results are used to simulate thirteen episodes with observed mountain waves. Simulated pseudosatellite images are validated using satellite observations, and an analysis is performed through several skill scores applied to brightness temperature. Few differences are found among the different skill scores. Nevertheless, the Thompson microphysics scheme combined with the Yonsei university PBL scheme shows the best results. The simulations produced by this scheme are used to evaluate the characteristic variables of the mountain wave episodes at windward and leeward and over the mountain. The results show that north-northwest wind directions, moderate wind velocities, and neutral or slightly stable conditions are the main features for the episodes evaluated. In addition, a case study is analysed to evidence the WRF ability to properly detect turbulence and icing associated with mountain waves, even when there is no visual evidence available.

Evaluation of the WRF model for simulating surface winds and the diurnal cycle of wind speed for the small island state of Fiji

Evaluation of the performance of the WRF model is carried out for simulating the surface winds and the diurnal cycle of wind speed for the small island developing state of Fiji at a 1.33 km by 1.33 km grid resolution using 1deg gridded data from NCEP-FNL. Simulations are performed for an austral summer (January 2017) and an austral winter (July 2017) month using the dynamical downscaling and the two-way nested approach. A set of physics parameterization schemes together with topo_wind = 1, 2 and ysu_topdown_pblmix = 1 physics settings associated with YSU PBL scheme are used to correct the surface winds and the diurnal cycle of wind speed. The results reveal that the WRF model is able to capture the surface winds and the diurnal cycle of wind speed on the windward side. Surface winds on the leeward side and the outer islands, show positive bias especially at nighttime for January and at both the day and night time for July. The statistical evaluation of all stations for January (July) showed a bias of 1.16 m/s (1.89 m/s), RMSE of 2.40 m/s (3.14 m/s), STDE of 1.88 m/s (2.08 m/s) and diurnal cycle correlation of 0.74 (0.68) using topo_wind = 2 and ysu_topdown_pblmix = 1.

Simulation of Flow Fields in Complex Terrain with WRF-LES: Sensitivity Assessment of Different PBL Treatments

AbstractA multiscale modeling study of a real case has been conducted to explore the capability of the large-eddy simulation version of the Weather Research and Forecasting Model (WRF-LES) over Xiaohaituo Mountain (a game zone for the Beijing, China, 2022 Winter Olympic Games). In comparing WRF-LES results with observations collected during the Mountain Terrain Atmospheric Observations and Modeling (MOUNTAOM) field campaign, it is found that at 37-m resolution with LES settings, the model can reasonably capture both large-scale events and microscale atmospheric circulation characteristics. Employing the Shuttle Radar Topography Mission 1 arc s dataset (SRTM1; ~30 m) high-resolution topographic dataset instead of the traditional USGS_30s (~900 m) dataset effectively improves the model capability for reproducing fluctuations and turbulent features of surface winds. Five sensitivity experiments are conducted to investigate the impact of different PBL treatments, including YSU/Shin and Hong (SH) PBL schemes and LES with 1.5-order turbulence kinetic energy closure model (1.5TKE), Smagorinsky (SMAG), and nonlinear backscatter and anisotropy (NBA) subgrid-scale (SGS) stress models. In this case, at gray-zone scales, differences between YSU and SH are negligible. LES outperform two PBL schemes that generate smaller turbulence kinetic energy and increase the model errors for mean wind speed, energy spectra, and probability density functions of velocity. Another key finding is that wind field features in the boundary layer over complex terrain are more sensitive to the choice of SGS models than above the boundary layer. With the increase of model resolution, the effects of the SGS model become more significant, especially for the statistical characteristics of turbulence. Among these three SGS models, NBA has the best performance. Overall, this study demonstrates that WRF-LES is a promising tool for simulating real weather flows over complex terrain.

Meteorological Downscaling with WRF Model, Version 4.0, and Comparative Evaluation of Planetary Boundary Layer Schemes over a Complex Coastal Airshed

AbstractEvaluation of downscaled meteorological information is crucial to identifying model behaviors that may propagate to end applications such as the simulation of local air quality. This study conducted and assessed yearlong simulations of hourly meteorological conditions over the Terrace–Kitimat Valley of northwestern British Columbia, Canada, at 1-km horizontal gridding for six PBL schemes in the Weather and Forecasting (WRF) Model, version 4.0. In terms of key surface meteorological variables that affect air quality, simulations over land demonstrated better skill for specific humidity and wind direction than for air temperature and wind speed. Spatial differences in modeled atmospheric properties and vertical profiles, especially for moisture content, were used to diagnose the relative capacity of each PBL scheme to represent pollutant dispersion and dilution. Stable conditions at night increased suppression of boundary layer mixing by the nonlocal Yonsei University (YSU) scheme when compared with suppression by the local eddy-diffusion component of the Asymmetric Convective Model, version 2 (ACM2), scheme, resulting in decreased wind speed and ambient temperature but moister air with the YSU scheme. The weakening of mixing by the Mellor–Yamada–Nakanishi–Niino (MYNN3) scheme with inland distance suggested that higher-order, nonlocal transport is sensitive to increasing topographic steepness toward the northern part of the valley. Disparities in mixing strengths among PBL schemes were greater in the summer when conditions were generally less stable with moist, warm air blowing inland than in winter when the valley channels cold, stable air from the interior. Increased convection in daytime led to greater entrainment of air from aloft and a thicker PBL with the YSU scheme than with the ACM2 scheme in summer while increasing countergradient transport in the MYNN3 scheme that reduces dilution.

Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile

AbstractAccurate predictions of the wind field are key for better wind power forecasts. Wind speed forecasts from numerical weather models present differences with observations, especially in places with complex topography, such as the north of Chile. The present study has two goals: (a) to find the WRF model boundary layer (PBL) scheme that best reproduces the observations at the Totoral Wind Farm, located in the semiarid Coquimbo region in north‐central Chile, and (b) to use an artificial neural network (ANN) to postprocess wind speed forecasts from different model domains to analyze the sensitivity to horizontal resolution. The WRF model was run with three different PBL schemes (MYNN, MYNN3, and QNSE) for 2013. The WRF simulation with the QNSE scheme showed the best agreement with observations at the wind farm, and its outputs were postprocessed using two ANNs with two algorithms: backpropagation (BP) and particle swarm optimization (PSO). These two ANNs were applied to the innermost WRF domains with 3‐km (d03) and 1‐km (d04) horizontal resolutions. The root‐mean‐square errors (RMSEs) between raw WRF forecasts and observations for d03 and d04 were 2.7 and 2.4 ms−1, respectively. When both ANN models (BP and PSO) were applied to Domains d03 and d04, the RMSE decreased to values lower than 1.7 ms−1, and they showed similar performances, supporting the use of an ANN to postprocess a three‐nested WRF domain configuration to provide more accurate forecasts in advance for the region.

Assessing Systematic Impacts of PBL Schemes on Storm Evolution in the NOAA Warn-on-Forecast System

Abstract The NOAA Warn-on-Forecast System (WoFS) is an experimental rapidly updating convection-allowing ensemble designed to provide probabilistic operational guidance on high-impact thunderstorm hazards. The current WoFS uses physics diversity to help maintain ensemble spread. We assess the systematic impacts of the three WoFS PBL schemes—YSU, MYJ, and MYNN—using novel, object-based methods tailored to thunderstorms. Very short forecast lead times of 0–3 h are examined, which limits phase errors and thereby facilitates comparisons of observed and model storms that occurred in the same area at the same time. This evaluation framework facilitates assessment of systematic PBL scheme impacts on storms and storm environments. Forecasts using all three PBL schemes exhibit overly narrow ranges of surface temperature, dewpoint, and wind speed. The surface biases do not generally decrease at later forecast initialization times, indicating that systematic PBL scheme errors are not well mitigated by data assimilation. The YSU scheme exhibits the least bias of the three in surface temperature and moisture and in many sounding-derived convective variables. Interscheme environmental differences are similar both near and far from storms and qualitatively resemble the differences analyzed in previous studies. The YSU environments exhibit stronger mixing, as expected of nonlocal PBL schemes; are slightly less favorable for storm intensification; and produce correspondingly weaker storms than the MYJ and MYNN environments. On the other hand, systematic interscheme differences in storm morphology and storm location forecast skill are negligible. Overall, the results suggest that calibrating forecasts to correct for systematic differences between PBL schemes may modestly improve WoFS and other convection-allowing ensemble guidance at short lead times.

Evaluation of CMAQ modeling sensitivity to planetary boundary layer parameterizations for gaseous and particulate pollutants over a fjord valley

Abstract Three-dimensional chemical transport models are useful for spatial and temporal analyses of outdoor air quality. However, the suitability of boundary-layer parameterizations for air pollution modeling over deep, coastal valleys has seldom been tested. An evaluation of the Community Multiscale Air Quality (CMAQ) model performance for five planetary boundary-layer schemes (PBL) with the Weather Research and Forecasting (WRF) meteorological driver was conducted at 1-km horizontal resolution for fine particulate matter (PM2.5), sulfur dioxide (SO2) and nitrogen dioxide (NO2) over the Terrace-Kitimat valley of northwestern British Columbia, Canada. The top-ranked schemes were Mellor-Yamada-Nakanishi-Niino Level 3 (MYNN3) for PM2.5 and Mellor-Yamada-Janjic for NO2. Both schemes ranked high for absolute SO2 levels, but the MYJ and Asymmetric Convective Model, version 2 (ACM2) schemes qualitatively emulated peak summertime diurnal concentrations in the near field of elevated point sources. Greater nighttime SO2 concentrations with MYNN3 and Yonsei University PBL schemes, in less agreement with station monitoring 8 km downwind of emissions from tall stacks, suggested sustained pollutant mixing and downward transport within the nocturnal boundary layer. Consequently, for these two schemes with representations of nonlocal mass flux transfers between model layers, inland penetrations of pollutant plumes were farther than those of ACM2, MYJ, and University of Washington schemes. For NO2 and PM2.5 that mainly discharged passively from fugitive, ground-level sources, hence are less accurately quantified than SO2 emissions, the fully local MYJ, and semi-local MYNN3 PBL schemes more reasonably reproduced peak season concentrations than other schemes. It is concluded that for air pollution modeling in rugged, remote areas, the mode of pollutant emissions is important for the choice of a PBL scheme. PM2.5 was consistently underestimated by the various PBL schemes, and aspects for improving CMAQ simulations for a complex environment are discussed.

Sensitivity studies and comprehensive evaluation of RegCM4.6.1 high-resolution climate simulations over the Tibetan Plateau

This study provides the first comprehensive assessment of Regional Climate Model version 4.6.1 (RegCM4) for the Tibetan Plateau (TP) region. A wide range of model configurations were analyzed with different parameterizations employed to represent cumulus convection (Kuo, Grell, Emanuel, Kain, and Tiedtke), land surface processes (BATS and CLM), planetary boundary layer turbulence (Holtslag and UW PBL), and radiation (CCM3 and RRTM). In addition to the above experiments at a 30-km horizontal resolution, another experiment was conducted based upon the use of a double-nested dynamic downscaling method to construct a simulation at a 10-km resolution to study the sensitivity to the model resolution. We evaluated a 20-year simulation for precipitation, cloud cover, surface radiation budget, 2-m air temperature, and the surface atmospheric circulation against ground and satellite-based observations during the period 1989–2008. Among the factors analyzed regarding sensitivity, precipitation was unsurprisingly found to be sensitive to the cumulus parameterization scheme, and the CLM is found to reduce rainfall compared with BATS, which is satisfactory for both the Emanuel and Tiedtke schemes. Compared with the cumulus convection schemes, the cloud cover and surface radiation budget are sensitive to the land surface, PBL, and radiation schemes. Generally, the CLM is characterized by reduced mean cloud cover and enhanced surface longwave and shortwave radiation compared with BATS. Conversely, the UW PBL and RRTM radiation schemes result in increased cloud cover and less surface radiation compared with the default options in RegCM4. All experiments, except those employing the Kuo scheme, represent the mean 2-m air temperature and regional circulation patterns reasonably well. At the basin scale, the seasonal cycle and interannual variations of precipitation are found to be not well depicted by most model configurations, although the temperature field was well reproduced. Considering all the analyzed variables collectively, the Tiedtke scheme combined with the CLM land surface model is demonstrated to provide the best performance over the TP. However, the higher-resolution version of the model improves the precipitation simulation significantly, particularly in the Brahmaputra river basin, which is located in the north of the Himalayas.

The Use of High-Resolution Sounding Data to Evaluate and Optimize Nonlocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer

Abstract Since the 1950s, a countergradient flux term has been added to some K-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (zn), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above zn ~ 0.31–0.33zi, where zi is the CBL depth. These composite profiles are used to evaluate two K-profile PBL schemes, the Yonsei University (YSU) and Shin–Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above zn ~ 0.24zi, while default SH simulates a thick superadiabatic lower CBL with zn ~ 0.45zi. Experiments with the analytic solution of a K-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with fnl specifying the peak value and z*SL specifying the height of this peak value. Increasing fnl to 1.1 lowers zn, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate zn ~ 0.36zi. The calibrated SH scheme performs better than YSU and default SH for real CBLs.

Simulation of mid-latitude winter storms over the North Atlantic Ocean: impact of boundary layer parameterization schemes

This study discusses the performance of various planetary boundary layer parameterization (PBL) schemes—the Quasi-Normal Scale Elimination (QNSE), the University of Washington Moist Turbulence (UWMT), and the Yonsei University (YSU)—for the simulation of rapidly developing North Atlantic (NA) mid-latitude winter storms. Sensitivity experiments with the three PBL schemes, YSU, QNSE, and UWMT, indicate that there are minor differences at the center of the storm while simulating the evolution of the three explosive storms Klaus (21–27 January 2009), Xynthia (25 February–03 March 2010), and Gong (16–20 January 2013). The differences are shown in terms of the central minimum pressure, 10-m wind, specific humidity, CAPE, transitional speed, boundary layer height and frictional velocity of these mid-latitude storms. One of the main result shows the capability of QNSE and UWMT PBL schemes to reproduce accurately both the cyclogenesis and explosive stage for these mid-latitude storms during the winter season, better than YSU scheme. Almost all PBL schemes show dry bias from middle to upper troposphere (600 hPa–250 hPa), while YSU scheme carries this bias at the surface boundary layer, for all simulations. Moreover, QNSE, UWMT and YMSU PBL schemes underestimate the tangential winds for these mid-latitude storms. The 24 h accumulated latent heat flux and precipitation from UWMT scheme show modified results as compared to YSU and QNSE PBL schemes. Overall results show the superiority of QNSE and UWMT PBL schemes for an accurate simulation of the explosive stage of these North Atlantic winter storms.

WITHDRAWN: The influence of local and nonlocal PBL schemes on typhoon intensity

WITHDRAWN: The influence of local and nonlocal PBL schemes on typhoon intensity

Evaluation of Convection-Permitting Precipitation Forecast Products Using WRF, NMMB, and FV3 for the 2016–17 NOAA Hydrometeorology Testbed Flash Flood and Intense Rainfall Experiments

Abstract During the summers of 2016 and 2017, the Center for Analysis and Prediction of Storms (CAPS) ran real-time storm-scale ensemble forecasts (SSEFs) in support of the Hydrometeorology Testbed (HMT) Flash Flood and Intense Rainfall (FFaIR) experiment. These forecasts, using WRF-ARW and Nonhydrostatic Mesoscale Model on the B-grid (NMMB) in 2016, and WRF-ARW and GFDL Finite Volume Cubed-Sphere Dynamical Core (FV3) in 2017, covered the contiguous United States at 3-km horizontal grid spacing, and supported the generation and evaluation of precipitation forecast products, including ensemble probabilistic products. Forecasts of 3-h precipitation accumulation are evaluated. Overall, the SSEF produces skillful 3-h accumulated precipitation forecasts, with ARW members generally outperforming NMMB members and the single FV3 member run in 2017 outperforming ARW members; these differences are significant at some forecast hours. Statistically significant differences exist in the performance, in terms of bias and ETS, among subensembles of members sharing common microphysics and PBL schemes. Year-to-year consistency is higher for PBL subensembles than for microphysical subensembles. Probability-matched (PM) ensemble mean forecasts outperform individual members, while the simple ensemble mean exhibits substantial bias. A newly developed localized probability-matched (LPM) ensemble mean product was produced in 2017; compared to the simple ensemble mean and the conventional PM mean, the LPM mean exhibits improved retention of small-scale structures, evident in both 2D forecast fields and variance spectra. Probabilistic forecasts of precipitation exceeding flash flood guidance (FFG) or thresholds associated with recurrence intervals (RI) ranging from 10 to 100 years show utility in predicting regions of flooding threat, but generally overpredict the occurrence of such events; however, they may still be useful in subjective flash flood risk assessment.

Evaluation of uWRF performance and modeling guidance based on WUDAPT and NUDAPT UCP datasets for Hong Kong

The evaluation of uWRF (WRF BEP/BEM) model over Hong Kong or the Pearl River Delta region has received less attention. One reason is the lack of a complete urban canopy parameters dataset for the building morphology in the PRD region. In recent years, the World Urban Database and Access Portal Tools (WUDAPT) approach has provided an alternative estimation of the building morphology dimensions based on satelliteretrieved local climate zones (LCZs). However, several sources of uncertainty arise when implementing these data in uWRF. In this study, different methods of WUDAPT dataset implementation are carried out to isolate and quantify these sources. This study also revealed that compensation error could occur when all of the uncertainties are summed in the default W2W protocol. Nevertheless, WUDAPT remains a suitable alternative in regions where a NUDAPT type of dataset is not available, provided that building morphology for different LCZs is estimated based on local expertise with a subgrid-averaging approach. Comparison with surface stations over an urban area suggests that uWRF allows a much better simulation of wind speed than the traditional Noah Bulk urban scheme, indicating that the improvement from a multi-layer urban scheme is larger than a non-local PBL scheme over urban area.

Regional Decadal Climate Predictions Using an Ensemble of WRF Parameterizations Driven by the MIROC5 GCM

AbstractRegional climate models (RCMs) are expected to provide better representations of the climate dynamics because of their higher spatial resolutions. Here, we generated an ensemble of decadal (2006–36) RCM predictions for the area of Israel, which spans a considerable climatic gradient and comprises complex terrain. We used the WRF Model forced by the MIROC5 global climate model (GCM). The ensemble was generated by choosing different combinations of radiation, microphysics, surface layer, and planetary boundary layer parameterizations. The simulation results were compared with meteorological station data for the first simulated decade. For the minimum surface temperature, all the RCM configurations performed better than the driving GCM, while for the maximum surface temperature, only three out of eight configurations improved the predictions. The RCM configurations had higher errors in predicting the precipitation, but four configurations had comparable errors to the GCM. For the next two decades, the ensemble average predicts an increase of 0.51° and 0.40°C decade−1 for the average daily minimum and maximum surface temperatures, respectively. No significant change is predicted in the precipitation. We found that all the parameterizations affect the predictions of the surface temperatures and precipitation [e.g., the CAM radiation scheme simulates colder temperatures than the RRTM for GCMs (RRTMG)] but the PBL and surface layer scheme has the largest effect on the errors. Spectral nudging was found to have a considerable effect on the deviations of the precipitation predicted by the WRF configurations from the predictions of the GCM and a much smaller effect on the surface temperature predictions.

Validation and sensitivity analysis of the WRF mesoscale model PBL schemes over Tunisia using dynamical downscaling approach

Regional-scale atmospheric circulations play a critical role in air pollutants transport. The planetary boundary layer height, in conjunction with other components, is a key factor in atmospheric dispersion. In this study, planetary boundary layer parameters over two coastal locations (Skhira and Marsa-Dhouiba) in Tunisia were simulated using the Weather Research and Forecasting (WRF) v.4.0 dynamical core. Regarding the validation process, the model evaluation demonstrated reasonable agreement with measurements in the study sites and periods. In general, the model slightly overestimates the observed values of near-surface temperature as well as the wind speed in Skhira and slightly underestimates the observed values in Marsa-Dhouiba. For wind direction, however, WRF simulations give opposite results. This preliminary study showed that the model is able to predict the considered meteorological fields in an accurate way with both final analysis (FNL) and Era-Interim boundary datasets. Therefore, the required meteorological fields to initialize an atmospheric dispersion model can be captured reasonably well at regional scale after dynamical downscaling. Integrating our results into project studies aiming at tracing air transports could serve the purpose of reducing environmental pollution over Tunisia.

Simulation of extreme heat events over the Valencia coastal region: Sensitivity to initial conditions and boundary layer parameterizations

The Valencia coastal region (Western Mediterranean) is especially sensitive to extreme heat events, where they are really common. However, due to its geophysical characteristics and climatic conditions, the incidence of high and extreme temperatures may still be modulated over this area by means of sea breeze circulations, defining a Sea Breeze Convergence Zone (SBCZ) due to the meet and interaction of these mesoscale conditions and Western synoptic-scale wind regimes. A proper definition of this convergence zone is of significant importance over the study area for the simulation and forecast of intense-heat meteorological events. This study analyses a week period in August 2010 over this area, which alternates the presence of meteorological conditions prone to high and extreme temperatures with sea breeze conditions that temper these extreme temperatures. The simulations have been performed using the mesoscale model Regional Atmospheric Modeling System (RAMS). The analysis focuses on the ability of different initial conditions and technical features and two widely used planetary boundary layer parameterizations to forecast and reproduce the observed high and extreme temperatures, as well as to properly capture the main associated atmospheric patterns. It has been found that an increased horizontal resolution in the initial atmospheric fields produces a better representation of the regional and local wind flows simulated by the mesoscale model, leading to an accurate characterization of the temperature fields when these wind circulations dominate over the area of study. However, no significant differences are obtained within the intense-heat situations, associated with atmospheric synoptic-scale forcings. Regarding PBL parameterizations, the local PBL scheme tends to underestimate the daytime temperatures, while the non-local scheme produces higher temperatures than the local scheme, skilfully reproducing the observations. Additionally, the non-local scheme overestimates temperatures at night-time, but it suitably captures the observed high minimum temperatures produced by the Western synoptic conditions.

Evaluation of Southwest Monsoon Change over Thailand by High-resolution Regional Climate Model under High RCP Emission Scenario

The 5×5 km resolution of Non-Hydrostatic Regional Climate Model (NHRCM) developed by Meteorological Research Institute, Japan was used to evaluate the southwest monsoon season that affects to Thailand during mid-May until mid-October in each years. Bulk-type cloud microphysics, Kain-Fritsch convective scheme, Mellor-Yamada-Nakanishi-Niino level 3 PBL scheme, clear-sky radiation scheme and Hirai-Ohizumi land surface scheme are used as model configuration to simulate climate data under high emission scenario-RCP 8.5. This research was conducted for 2 time periods, i.e., baseline period (1981–2000) and future period (2080–2099), to estimate the southwest monsoon season onset and offset over Thailand by using average wind vector and cumulative precipitation in consecutive 5 days (pentad). Furthermore, the rain-break phase, less precipitation ranges during the southwest monsoon season, had also been analysed.