Planetary Boundary Layer Parameterization Research Articles

Evaluation of the Surface Wind Field over Land in WRF Simulations of Hurricane Wilma (2005). Part II: Surface Winds, Inflow Angles, and Boundary Layer Profiles

AbstractThis is the second of a two-part study that explores the capabilities of a mesoscale atmospheric model to reproduce the near-surface wind fields in hurricanes over land. The Weather Research and Forecasting (WRF) Model is used with two planetary boundary layer parameterizations: the Yonsei University (YSU) and the Mellor–Yamada–Janjić (MYJ) schemes. The first part presented the modeling framework and initial conditions used to produce simulations of Hurricane Wilma (2005) that closely reproduced the track, intensity, and size of its wind field as it passed over South Florida. This part explores how well these simulations can reproduce the winds at fixed points over land by making comparisons with observations from airports and research weather stations. The results show that peak wind speeds are remarkably well reproduced at several locations. Wind directions are evaluated in terms of the inflow angle relative to the storm center, and the simulated inflow angles are generally smaller than observed. Localized peak wind events are associated with vertical vorticity maxima in the boundary layer with horizontal scales of 5–10 km. The boundary layer winds are compared with wind profiles obtained by velocity–azimuth display (VAD) analyses from National Weather Service Doppler radars at Miami and Key West, Florida; results from these comparisons are mixed. Nonetheless the comparisons with surface observations suggest that when short-term hurricane forecasts can sufficiently predict storm track, intensity, and size, they will also be able to provide useful information on extreme winds at locations of interest.

Improving Hurricane Boundary Layer Parameterization Scheme Based on Observations

AbstractFlight‐level data and global positioning system dropwindsonde observations collected from more than 187 flights into 19 tropical cyclones were used to examine why different planetary boundary layer parameterization schemes applied to hurricane models produce diverse forecasts of structure and intensity change. Two popular, yet diverse, physics schemes, namely, the GFS K‐Profile and a 1.5‐order turbulence kinetic energy closure parameterization from NOAA's next‐generation FV3‐based Hurricane Analysis and Forecast System were used. It was found that uncertainty related to some key variables used in the parameterization of the eddy diffusivity, Km, led to diverse solutions. For a given grid resolution, both parameterization schemes converged to a similar forecast state provided those uncertainties could be identified and improved based on observations. This is important for providing a generalized framework for the development and evaluation of parameterization schemes in operational models that resemble reality. This study also indicates that the shape of the Km profile is equally important as its maximum value. The smaller the Km near the surface, the stronger the inflow in the boundary layer.

Sensitivity of an Idealized Tropical Cyclone to the Configuration of the Global Forecast System–Eddy Diffusivity Mass Flux Planetary Boundary Layer Scheme

The intensity and structure of simulated tropical cyclones (TCs) are known to be sensitive to the planetary boundary layer (PBL) parameterization in numerical weather prediction models. In this paper, we use an idealized version of the Hurricane Weather Research and Forecast system (HWRF) with constant sea-surface temperature (SST) to examine how the configuration of the PBL scheme used in the operational HWRF affects TC intensity change (including rapid intensification) and structure. The configuration changes explored in this study include disabling non-local vertical mixing, changing the coefficients in the stability functions for momentum and heat, and directly modifying the Prandtl number (Pr), which controls the ratio of momentum to heat and moisture exchange in the PBL. Relative to the control simulation, disabling non-local mixing produced a ~15% larger storm that intensified more gradually, while changing the coefficient values used in the stability functions had little effect. Varying Pr within the PBL had the greatest impact, with the largest Pr (~1.6 versus ~0.8) associated with more rapid intensification (~38 versus 29 m s−1 per day) but a 5–10 m s−1 weaker intensity after the initial period of strengthening. This seemingly paradoxical result is likely due to a decrease in the radius of maximum wind (~15 versus 20 km), but smaller enthalpy fluxes, in simulated storms with larger Pr. These results underscore the importance of measuring the vertical eddy diffusivities of momentum, heat, and moisture under high-wind, open-ocean conditions to reduce uncertainty in Pr in the TC PBL.

The sensitivity of simulated surface-level pollution concentrations to WRF-ARW-model PBL parameterisation schemes over the Highveld of South Africa

An understanding of the sensitivity of pollutant concentrations to planetary boundary layer (PBL) schemes in numerical weather prediction (NWP) models can provide insight into model results, and possibly advance the accuracy of air pollution modelling. Meteorological output from the Advanced Research Weather Research and Forecasting (WRF-ARW) model, with four frequently used PBL schemes, is used as input for an air quality model. The simulations resulting from the different schemes are compared with each other and evaluated making use of observational air pollution concentration data for a spring and a winter month of 2016 in South Africa. Sensitivity exists in surface-level pollution concentrations as simulated by the considered PBL schemes. No single PBL scheme consistently performed best across the five considered pollutants, five sites and two seasons. During analysis of the air quality simulations, it was found that the two local closure schemes – Mellor-Yamada-Janjić (MYJ) and Mellor-Yamada Nakanishi Niino (MYNN) – often performed well, while the non-local closure schemes – Yonsei University (YSU) and Asymmetric Convection Modelling (ACM) – featured as best-performing schemes the least number of times. Sensitivity also exists on a spatial scale between schemes when simulating sulphur dioxide (SO2) plumes from tall stacks, and the MYNN scheme frequently produced the highest concentrations of SO2. The results from this study should be considered when configuring NWP models for the simulation of air quality in the Highveld region.

Evaluation of PBL parameterization schemes against direct observations during a land depression over Central India

Detailed observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) Phase III integrated observational campaign 2014 are used to validate six different planetary boundary layer (PBL) schemes in Weather Research and Forecasting (WRF) model during a land depression over central India in summer monsoon season. This work is a continuation of our previous study on a dry event associated with a heatwave over the same region (Sathyanadh et al. 2017). Four local and two nonlocal PBL schemes are evaluated with hourly observations of air temperature, eddy covariance fluxes, friction velocity, wind, and radiation components for the model performance of the complete energy budget and weather parameters. The models simulated a slightly warmer and drier surface layer with strong winds and overestimated sensible heat flux and ground heat flux during the wet event. The errors in the surface layer temperature are closely associated with errors in the sensible heat flux and incoming radiation, while the errors associated with moisture are linked to the excessive surface layer mixing. The interrelationships between various surface layer parameters and PBL heights are investigated to identify the key controlling factors of PBL evolution in the context of land depression.

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.

Vertical Eddy Diffusivity Parameterization Based on a Large‐Eddy Simulation and Its Impact on Prediction of Hurricane Landfall

AbstractThe vertical eddy diffusivity (VED) in the planetary boundary layer (PBL) affects tropical cyclones' structure and evolution. Uncertainties of VED in the PBL parametrization scheme of a mesoscale model could be caused by the model's inability to represent large eddies (LEs). Using a large‐eddy simulation (LES) of Hurricane Harvey (2017) as a benchmark, the YSU PBL scheme is improved by adding effects of LEs derived from the LES. It is found that LEs' maximum intensity is linearly significantly related to the square of mean horizontal divergence below 400 m of height at the same air column with a slope coefficient of 1.97. The revised YSU scheme relates the VED of momentum (Km) to the square root of LEs' intensity with a slope coefficient of 0.08 in PBL and 0.20 in a free atmosphere. Compared to the original scheme, the modified YSU scheme leads to improved forecasts of landfalling hurricanes.

Sensitivity evaluation of the different physical parameterizations schemes in regional climate model RegCM4.5 for simulation of air temperature and precipitation over North and West of Iran

In this research the dynamic downscaling method by Regional Climate Model (RegCM4.5) was used to assess the performance and sensitivity of seasonal simulated North and West of Iran (NI&WI) climate factors to different convection schemes, and transforms the large-scale simulated climate variables into land surface states over the North of Iran (NI) and West of Iran (WI). A 30-year (1986–2015) numerical integration simulation of climate over NI&WI was conducted using the regional climate model RegCM4.5 nested in one-way ERA-Interim reanalysis data. The Grell, Kuo and MIT-Emanuel cumulus convection with Holtslag and University of Washington (UW) planetary boundary layer (PBL) parameterization schemes were applied in the running of RegCM4.5 to test their capability in simulating precipitation and temperature in winter-spring (January–April) over NI and WI. The results demonstrated that the RegCM4.5 model has a good potential for simulating the variables and trend of surface temperature over the NI and WI region. Magnitude of the model bias for land surface temperature over different regions of Iran varies by convection parameterization schemes. In most cases, the root mean square error between post-processed simulated seasonal average temperature and observation value was less than 1 °C, but there is a systematic “cold bias”. In general, with respect to land surface temperature simulations, a better performance is obtained when using post-processing model’s data with Holtslag PBL-Grell and Holtslag PBL-Kuo configuration schemes, compared to the other simulations, over the NI&WI region. Also, the UW PBL convection schemes show a relatively excellent spatial correlations and normalized standard deviations closer to 1 for thirty-year seasonal land surface temperature anomalies over the entire NI&WI region. However, the simulation accuracy of model for precipitation is not as optimal as for temperature. The dominant feature in model simulations is a dry bias with the largest average value (∼1.04 mm/day) over NI region, while the lowest mean bias precipitation (∼−0.47 mm/day), mainly located in WI region. In the comparison of six configuration convection schemes, the Emanuel scheme has been proven to be the most accurate for simulating winter-spring seasonal mean precipitation over NI&WI region. The accuracy of the scheme also showed great difference in simulated station interpolation of precipitation, which urges the improvement for the simulation capability of spatial distribution of precipitation. In general, for seasonal variation of precipitation, the Emanuel convection with two (Holtslag, UW) PBL configuration schemes outperforms with a good correlation score between 0.7−0.8 and normalized standard deviations closer to 1.

Reanalysis Profile Downscaling with WRF Model and Sensitivity to PBL Parameterization Schemes Over a Subtropical Station

Atmospheric profiles are essential in weather prediction, atmospheric research, and satellite data calibration. In this study, we assess the use of the Weather Research and Forecasting (WRF) model to downscaling NCEP Climate Forecast System Version 2 (CFSv2) reanalysis atmospheric profiles. Moreover, a sensitivity analysis was conducted to Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ) Planetary Boundary Layer (PBL) parameterization schemes. WRF simulations were carried out using two nested grids with horizontal resolutions of 12 and 3 km. Simulated profiles were evaluated against radiosonde observations in Southern Brazil. Results indicate that WRF can skillfully simulate vertical profiles of water vapor mixing ratio ( q ) and potential temperature ( θ ). The entire profile comparison yielded high correlation coefficients (mostly higher than 0.9), low moist and cold average biases, and overall RMSE (MAE) of 0.84 (0.44) g/Kg and 2.30 (1.61) K for q and θ , respectively. In the lower troposphere (0-3 km), errors are larger for q and lower for θ . Statistically, there is no significant difference in the retrieved profiles on increasing the horizontal resolution. The setting choice is a compromise between spatial detail needs and computational cost. Furthermore, the overall results did not indicate any preferred PBL scheme that outperforms in all case days. The performance depends on the meteorological conditions that prevail in the different cases. The WRF model and even data directly from NCEP CFSv2 reanalysis are useful to represent the vertical structure of the atmosphere when local radiosondes are not available.

High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization

In this study, an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model, with a focus on the effects of planetary boundary layer (PBL) physics using double nesting with large grid ratios (15:1 and 9:1). The sensitivity of the precipitation forecast was examined through three PBL schemes: the Yonsei University Scheme, the Mellor–Yamada–Nakanishi Niino Level 2.5 (MYNN) scheme, and the Mellor–Yamada–Janjic scheme. The PBL effects on boundary layer structures, convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations. The results indicated that in single coarser grids (15 km and 9 km), the extreme rainfall amount was largely underestimated with all three PBL schemes. In the inner 1-km grid, the underestimated intensity was improved; however, using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain–Fritsch cumulus scheme, significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall. MYNN, with the weakest vertical mixing, produced the shallowest and most humid inversion layer with the lowest lifting condensation level, but stronger wind fields and upward motions from the top of the boundary layer to upper levels. These factors all facilitate the development of deep convection and moisture transport for intense precipitation, and result in its most realistic prediction of the primary rainfall peak.

Sensitivity Study of Planetary Boundary Layer Parameterization Schemes for the Simulation of Tropical Cyclone ‘Fani’ Over the Bay of Bengal Using High Resolution Wrf-Arw Model

Comprehensive sensitivity analyses on physical parameterization schemes of WRF-ARW (V3.8.1) model have been carried out for the simulation of Tropical Cyclone (TC) Fani that formed in the Bay of Bengal (BoB) and crossed the Bangladesh and Odisha coast of India on 3rd May 2019. Global Forecasting System (GFS) data 1⁰ and 0.25⁰ from National Centre for Environment Prediction (NCEP) is used as initial and lateral boundary conditions. The six different Planetary Boundary Layer (PBL) schemes used in this research are YSU, BouLac, TEMF, Shin-Hong, GBM and MRF. The meteorological parameters, which have been studied to identify the effect of PBL during the propagation and movement of TC Fani are Estimated Central Pressure (ECP), Maximum Wind Speed (MWS) at 10m height, average relative humidity (%), temperature (⁰C) and potential temperature (0K) at 2m height, Modified Convective Available Potential Energy (MCAP), average PBL height and average high clouds (%). The area considered for these averages are 82-92 ⁰E and 7-22 ⁰N inside the model domain. The simulated ECP by TEMF scheme are 930, 932, 937, 929, 944 and 932 hPa for the Initial Conditions (ICs) at 0000 UTC of 27, 28, 29, 30 April, and 01 May and 02 May, respectively and observed ECP was 932 hPa. The intensity of pressure fall by the TEMF scheme is similar to that observed up to the time of crossing the land of TC Fani. The MWS simulated by the TEMF scheme is almost similar to that of the observed MWS at 10m height and all other schemes have simulated much lower MWS. The temperature at 2m height is positively correlated with the ECP and MWS at 10m height. The TEMF scheme has simulated maximum high clouds for all ICs and for all through the simulation time. The error was systematic for all PBL schemes for the ICs at 0000 UTC of 30 April at 0.25⁰ and 1⁰ GFS data but the track error was much less for 1⁰ GFS data than that of 0.25⁰ GFS data. The TEMF scheme has simulated the most deviated track and MRF scheme has simulated less deviated track for all through the simulation. The study has shown large variations of track and intensity among the different PBL schemes. The PBL schemes have a major impact on the track and intensity of TC Fani. The intensity simulated by the TEMF scheme is better but the track error is higher than that of other schemes.
 Journal of Engineering Science 11(2), 2020, 1-18

Examination of WRF-ARW Experiments Using Different Planetary Boundary Layer Parameterizations to Study the Rapid Intensification and Trajectory of Hurricane Otto (2016)

Hurricane Otto (2016) was characterised by remarkable meteorological features of relevance for the scientific community and society. Scientifically, among the most important attributes of Otto is that it underwent a rapid intensification (RI) process. For society, this cyclone severely impacted Costa Rica and Nicaragua, leaving enormous economic losses and many fatalities. In this study, a set of three numerical simulations are performed to examine the skill of model estimations in reproducing RI and trajectory of Hurricane Otto by comparing the results of a global model to a regional model using three different planetary boundary layer parameterizations (PBL). The objective is to set the basis for future studies that analyse the physical reasons why a particular simulation (associated with a certain model setup) performs better than others in terms of reproducing RI and trajectory. We use the regional model Weather Research and Forecasting—Advanced Research WRF (WRF-ARW) with boundary and initial conditions provided by the Global Forecast System (GFS) analysis (horizontal resolution of 0.5 degrees). The PBL used are the Medium Range Forecast, the Mellor-Yamada-Janjic (MYJ), and the Yonsei University (YSU) parameterizations. The regional model is run in three static domains with horizontal grid spacing of 27, 9 and 3 km, the latter covering the spacial extent of Otto during the simulation period. WRF-ARW results improve the GFS forecast, in almost every aspect evaluated in this study, particularly, the simulated trajectories in WRF-ARW show a better representation of the cyclone path and movement compared to GFS. Even though the MYJ experiment was the only one that exhibited an abrupt 24-h change in the storm’s surface wind, close to the 25-knot threshold, the YSU scheme presented the fastest intensification, closest to reality.

The role of atmospheric forcings and WRF physical set-up on convective initiation over Córdoba, Argentina

The accurate determination of the location and timing of convective initiation (CI) is a crucial aspect of forecasting and high impact weather warning systems associated with deep convection. Central Argentina, particularly the Sierras de Córdoba (SDC), is characterized by the regular occurrence of deep convective cells that reach supercell characteristics producing large hail and occasionally tornadoes.In order to analyze the sensitivity of the CI over SDC, an ensemble of 12 simulations with the WRF model at convection-permitting resolution (3 km.) was carried out to study a marginal supercell initiated on October 17, 2017 at the SDC foothills. The ensemble was built using 3 different microphysics (MP) parameterizations (WSM6, Thompson and Morrison) and 2 planetary boundary layer (PBL) parameterizations (Yonsei University and Mellor Yamada Janjic). Also, the sensitivity of initial and boundary conditions is considered by forcing the model with 2 different global analyses: the European Centre for Medium-Range Weather Forecast (ECMWF) model, and the Global Data Assimilation System (GDAS).The two different forcing data show low-level moisture differences, which later modulate the life-cycle of the simulated cells. A tracking algorithm was used to capture their life-cycle, and CI was detected at both the hills and the plains. Simulations forced with ECMWF analyses tend to show better results with characteristics closer to the ones observed including: initiation over the eastward slope of SDC, stronger cells and slow propagation. Among all simulations analyzed, the best performance was obtained with the combination of Thompson MP and Yonsei University PBL schemes.

Modeling cloud-to-ground lightning probability in Alaskan tundra through the integration of Weather Research and Forecast (WRF) model and machine learning method

Wildland fires exert substantial impacts on tundra ecosystems of the high northern latitudes (HNL), ranging from biogeochemical impact on climate system to habitat suitability for various species. Cloud-to-ground (CG) lightning is the primary ignition source of wildfires. It is critical to understand mechanisms and factors driving lightning strikes in this cold, treeless environment to support operational modeling and forecasting of fire activity. Existing studies on lightning strikes primarily focus on Alaskan and Canadian boreal forests where land-atmospheric interactions are different and, thus, not likely to represent tundra conditions. In this study, we designed an empirical-dynamical method integrating Weather Research and Forecast (WRF) simulation and machine learning algorithm to model the probability of lightning strikes across Alaskan tundra between 2001 and 2017. We recommended using Thompson 2-moment and Mellor–Yamada–Janjic schemes as microphysics and planetary boundary layer parameterizations for WRF simulations in the tundra. Our modeling and forecasting test results have shown a strong capability to predict CG lightning probability in Alaskan tundra, with the values of area under the receiver operator characteristics curves above 0.9. We found that parcel lifted index and vertical profiles of atmospheric variables, including geopotential height, dew point temperature, relative humidity, and velocity speed, important in predicting lightning occurrence, suggesting the key role of convection in lightning formation in the tundra. Our method can be applied to data-scarce regions and support future studies of fire potential in the HNL.

Impacts of global warming on West African monsoon rainfall: Downscaling by pseudo global warming method

A set of numerical experiments was conducted in order to investigate the impacts of global warming on West African monsoon rainfall for selected five years. The experiments varied different cumulus, microphysics and planetary boundary layer parameterization schemes. Rainfall characteristics over three climatic zones, Guinea Coast, Savannah and Sahel, was analyzed. The potential change associated with global warming is assessed by the pseudo global warming (PGW) downscaling method. Multiple PGW runs were conducted using climate perturbation from the 40-member ensemble of the Community Earth System Model version 1 (CESM1) coupled with Community Atmospheric Model version 5.2 (CAM5.2) component large ensemble project. The model output was compared with TRMM and GPCP rainfall and atmospheric parameters from ECMWF reanalysis datasets. Results show that the rainfall amount in the 2070s estimated from the PGW runs substantially increases, especially in the eastern Sahel due to enhanced moisture convergence, compared to the current climate. The percentage change in simulated total rainfall amount can increase or decrease by 50% in the PGW runs and the theoretical rainfall computed based on Clausius-Clapeyron relation. Also, found is an increase (decrease) in heavy (both light and moderate) rainfall amount. These results, however, depend on the GCM used as the boundary conditions of the RCM. This suggests that the 4 o C change in average surface temperature derived from the 40-member ensemble model strongly influenced the increased rainfall simulated by the PGW experiments. Thus, highlighting the advantage of using the PGW technique to estimate the likely difference between present and future climate with reduced large-scale model biases and computational resources.

Characteristics of the turbulence intermittency and its influence on the turbulent transport in the semi-arid region of the Loess Plateau

In this study, observational data from the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) in July 2008 were used to analyze the characteristics of the turbulence intermittency and its influence on the land-atmosphere turbulent transport over the complex terrain of the semi-arid region of the Loess Plateau in summer. Using the Hilbert-Huang transform (HHT), the local intermittent strength of turbulence (LIST) was calculated based on pure dynamics through an automated algorithm to characterize the turbulence intermittency in this region. But LIST misjudged the actual turbulence intermittency under the condition of weak wind and strong radiation. The thermal effects cannot be ignored in this situation and a thermodynamic intermittency correction factor LISTThermal is suggested to modify LIST. Then a new intermittent strength index LISTRevise is proposed, which is assumed to be the weighted average of LIST and LISTThermal according to the stability parameter z/L. LIST (LISTThermal) is closely related to the near-surface wind-speed (sensible heat flux). Most misjudgments of LIST to turbulence intermittency are corrected, and LISTRevise is more consistent with the general diurnal variation of turbulence intermittency. There are overestimations in turbulent standard deviations and fluxes calculated by conventional eddy covariance (EC) method due to sub-mesoscale motions and turbulence intermittency, producing inaccurate quantifications of turbulent mixing and transport in the planetary boundary layer parameterization schemes. After eliminating the influence of it, the relationship between the normalized standard deviations of different meteorological variables and z/L is more consistent with the Monin-Obukhov similarity rule under stable and unstable stratification.

A Review and Evaluation of Planetary Boundary Layer Parameterizations in Hurricane Weather Research and Forecasting Model Using Idealized Simulations and Observations

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL schemes on hurricane structure and intensity. The original Global Forecast System (GFS) PBL scheme in the 2011 version of HWRF produces the weakest storm, while a modified GFS scheme using a wind-speed dependent parameterization of vertical eddy diffusivity (Km) produces the strongest storm. The subsequent version of the hybrid eddy diffusivity and mass flux scheme (EDMF) used in HWRF also produces a strong storm, similar to the version using the wind-speed dependent Km. Both the intensity change rate and maximum intensity of the simulated storms vary with different PBL schemes, mainly due to differences in the parameterization of Km. The smaller the Km in the PBL scheme, the faster a storm tends to intensify. Differences in hurricane PBL height, convergence, inflow angle, warm-core structure, distribution of deep convection, and agradient force in these simulations are also examined. Compared to dropsonde and Doppler radar composites, improvements in the kinematic structure are found in simulations using the wind-speed dependent Km and modified EDMF schemes relative to those with earlier versions of the PBL schemes in HWRF. However, the upper boundary layer in all simulations is much cooler and drier than that in dropsonde observations. This model deficiency needs to be considered and corrected in future model physics upgrades.

Assessment of Planetary Boundary Layer parametrizations and urban heat island comparison: Impacts and implications for tracer transport.

Accurate simulation of planetary boundary layer height (PBLH) is key to greenhouse gas emission estimation, air quality prediction and weather forecasting. This manuscript describes an extensive performance assessment of several Weather Research and Forecasting (WRF) model configurations where novel observations from ceilometers, surface stations and a flux tower were used to study their ability to reproduce planetary boundary layer heights (PBLH) and the impact that the urban heat island (UHI) has on the modeled PBLHs in the greater Washington, D.C. area. In addition, CO2 measurements at two urban towers were compared to tracer transport simulations. The ensemble of models used 4 PBL parameterizations, 2 sources of initial and boundary conditions and 1 configuration including the building energy parameterization (BEP) urban canopy model. Results have shown low biases over the whole domain and period for wind speed, wind direction and temperature with no drastic differences between meteorological drivers. We find that PBLH errors are mostly positively correlated with sensible heat flux errors, and that modeled positive UHI intensities are associated with deeper modeled PBLs over the urban areas. In addition, we find that modeled PBLHs are typically biased low during nighttime for most of the configurations with the exception of those using the MYNN parametrization and that these biases directly translate to tracer biases. Overall, the configurations using MYNN scheme performed the best, reproducing the PBLH and CO2 molar fractions reasonably well during all hours, thus opening the door to future nighttime inverse modeling.

On the Consequences of PBL Scheme Diffusion on UTLS Wave and Turbulence Representation in High-Resolution NWP Models

AbstractMesoscale numerical weather prediction (NWP) models are routinely exercised at kilometer-scale horizontal grid spacings (Δx). Such fine grids will usually allow at least partial resolution of small-scale gravity waves and turbulence in the upper troposphere and lower stratosphere (UTLS). However, planetary boundary layer (PBL) parameterization schemes used with these NWP model simulations typically apply explicit subgrid-scale vertical diffusion throughout the entire vertical extent of the domain, an effect that cannot be ignored. By way of an example case of observed widespread turbulence over the U.S. Great Plains, we demonstrate that the PBL scheme’s mixing in NWP model simulations of Δx = 1 km can have significant effects on the onset and characteristics of the modeled UTLS gravity waves. Qualitatively, PBL scheme diffusion is found to affect not only background conditions responsible for UTLS wave activity, but also to control the local vertical mixing that triggers or hinders the onset and propagation of these waves. Comparisons are made to a reference large-eddy simulation with Δx = 250 m to statistically quantify these effects. A significant and systematic overestimation of resolved vertical velocities, wave-scale fluxes, and kinetic energy is uncovered in the 1-km simulations, both in clear-air and in-cloud conditions. These findings are especially relevant for upper-level gravity wave and turbulence simulations using high-resolution kilometer-scale NWP models.

Análise da influência do uso da parametrização cúmulus na simulação do vento com diferentes parametrizações de camada limite planetária

The present work aimed to evaluate the influence of use the cumulus parameterization on the wind shift with two dynamic planetary boundary layer parameterizations using the Weather Research and Forecast model. Studies on model simulations using PBL parameterizations in tropical regions are generally rare, mainly due to the lack of experimental observations. This work is part of a project developed in partnership betweenTPP Pecém II, TPP Parnaíba I, Parnaíba II and III generation of S.A. Energy and the Federal University of Santa Maria-UFSM. The Parnaíba Thermoelectric Power Plant (UTE) complex is located in Santo Antônio dos Lopes city in Maranhão and is operated by the Brazilian company Eneva. As energy production through the combustion of natural gas produces wastes that are released into the atmosphere, environmental regulatory bodies demand that verification and control measures be taken, such as chemical species monitoring. Therefore, a good description of the atmosphere is fundamental for the good performance of chemical species dispersion models. Four automatic weather stations were used to validate the model simulations. The model had difficulty reproducing the wind magnitude values as observed.