Planetary Boundary Layer Schemes Research Articles

Turbulent characteristics in complex coastal areas assessed using BSWO observations and WRF-LES simulation results

Studies exploring the turbulent structure of the planetary boundary layer (PBL) over complex topographies are very limited, especially at night, because of the lack of available observations and difficulty of highly resolved simulation. In this study, micro-meteorological and turbulent characteristics over complex coastal areas were investigated based on high spatial-temporal resolution by using the Weather Research and Forecasting–Large Eddy Simulation (WRF-LES) model. Then, the simulations were compared to comprehensive observations obtained at the Boseong Standard Weather Observatory (BSWO), which is equipped with various observation facilities, such as a meteorological observation tower with a height of 307 m, and aiding ground-based remote sensing measurements used for PBL research. The comparison between the WRF-LES model results and the measurements by the wind lidar system at the BSWO showed that the LES approach in this study reproduced the spatial/vertical wind field structure and land-sea wind circulation distinctly better than the conventional PBL schemes. High turbulent kinetic energy (TKE) was observed near the surface level at night due to the increased nocturnal shear production following the evolution of land and mountain breezes. The calculated TKE from WRF-LES model was applied to identify the mixing intensity based on the mixing length and eddy diffusion coefficient within the boundary layer, and then those were evaluated with the observed extinction coefficient from the aerosol Micro-Pulse Lidar system (MPL). In addition, the planetary boundary layer height (PBLH) at night was explored by using the TKE threshold method combined with the bulk Richardson number threshold method for the daytime PBLH. Compared with the observed value from a ceilometer at the BSWO, we found that the TKE threshold method proposed in this study could yield highly accurate PBLH values, especially at night. It is also expected that the enhanced application of WRF-LES like to this study can lead to understanding and prediction with the high confidence for much detail and accurate spatiotemporal turbulent structure over complex coastal areas, which will contribute to more comprehensive air quality modeling studies.

Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain.

The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM2.5 by a chemical transport model.

Snowfall events in the Cantabrian Mountains of northwestern Spain: WRF multiphysics ensemble assessment based on ground and multi-satellite observations

Snowfall in elevated areas of the mid-latitudes has a strong impact on infrastructure, freshwater availability, and the climate system. The Cantabrian Mountains of the northwestern Iberian Peninsula are very vulnerable to climate change because of their moderate altitudes, which limits their snowfall. Monitoring snow events is essential for the evaluation of weather and climate prediction models. However, measurement networks are scarce in mountainous areas and have great uncertainties because of blizzards. In this study, a multiphysics ensemble of the Weather Research and Forecasting (WRF) model was designed using three microphysics and two planetary boundary layer (PBL) schemes to simulate nine snowfall events in the Cantabrian Mountains during autumn and winter 2021–2022. The WRF was validated using several snow characteristics, such as liquid water equivalent, snow cover, and snow depth. Liquid water equivalent was evaluated using snow-gauge networks and satellite products in an assessment of snow cover. In addition, a monitoring network of webcams and snow poles was implemented, improving the low density of snow observations in the mountains. The results showed good model performance for detection of snow cover and slight overestimation of liquid water equivalent and snow thickness, which may have been caused by under-catchment that is generally an effect of wind on the measurement systems and by snow compaction, respectively. Morrison microphysics and Mellor-Yamada-Nakanishi-Niino (MYNN PBL) yielded better results for liquid water equivalent at higher altitudes and output greater snow cover. The results help determine the best configurations for snow modelling in the study area to develop future studies of the spatiotemporal patterns of snow distribution.

Simulating Meteorological and Water Wave Characteristics of Cyclone Shaheen

The Bay of Bengal and Arabian Sea are annually exposed to severe tropical cyclones, which impose massive infrastructure damages and cause the loss of life in coastal regions. Cyclone Shaheen originally generated in the Bay of Bengal in 2021 and translated a rare east-to-west path toward the Arabian Sea. Although the cyclone’s wind field can be obtained from reanalysis datasets such as ERA5 (fifth generation European Centre for Medium-Range Weather Forecasts), the wind speed cannot be reproduced with realistic details in the regions close to the center of cyclone due to spatial resolution. In this study, to address this problem, the high-resolution advanced Weather Research and Forecasting (WRF) model is used for simulation of Shaheen’s wind field. As a critical part of the study, the sensitivity of the results to the planetary boundary layer (PBL) parameterization in terms of the track, intensity, strength and structure of the cyclone Shaheen is investigated. Five experiments are considered with five PBL schemes: Yonsei University (YSU); Mellor–Yamada–Janjić (MYJ); Mellor–Yamada–Nakanishi–Niino level 2.5 (MYNN); Asymmetric Convective Model version 2 (ACM2); Quasi-Normal Scale Elimination (QNSE). The track, intensity, and strength of the experiments are compared with the wind fields obtained from the Joint Typhoon Warning Centre (JTWC) dataset. The results imply the high dependency of the track, intensity, and strength of the cyclone to the PBL parameterization. Simulated tracks with non-local PBL schemes (YSU and ACM2) outperformed those of the local PBL schemes (MYJ, MYNN, and QNSE), especially during the rapid intensification phase of Shaheen before landfall. The YSU produced highly intensified storm, while the ACM2 results are in better agreement with the JTWC data. The most accurate track was obtained from the ERA5 data; however, this dataset overestimated the spatial size and underestimated the wind speed. The WRF model using either YSU or ACM2 overestimated the wind speed compared to that of the altimeter data. The YSU and ACM2 schemes were able to reproduce the observed increase in wind speed and pressure drop at in situ stations. The wind data from EAR5 and cyclone parametric model were applied to the SWAN model to simulate the wave regime in the Arabian Sea during the time that Shaheen was translating across the region. Janssen formulation for wind input and whitecapping dissipation source terms in combination with both ERA5 and hybrid wind were used and the minimum combined error in the prediction of significant wave height (Hs) and zero up-crossing wave period (Tz) was examined. The maximum significant wave height for hybrid wind is higher than that of ERA5, while the cyclone development was successfully inferred from the wave field of the hybrid data.

Performance of an Improved TKE-Based Eddy-Diffusivity Mass-Flux (EDMF) PBL Scheme in 2021 Hurricane Forecasts from the Hurricane Analysis and Forecast System

Abstract Continuous development and evaluation of planetary boundary layer (PBL) parameterizations in hurricane conditions are crucial for improving tropical cyclone (TC) forecasts. A turbulence kinetic energy (TKE)-based eddy-diffusivity mass-flux (EDMF-TKE) PBL scheme, implemented in NOAA’s Hurricane Analysis and Forecast System (HAFS), was recently improved in hurricane conditions using large-eddy simulations. This study evaluates the performance of HAFS TC forecasts with the original (experiment HAFA) and modified EDMF-TKE (experiment HAFY) based on a large sample of cases during the 2021 North Atlantic hurricane season. Results indicate that intensity and structure forecast skill was better overall in HAFY than in HAFA, including during rapid intensification. Composite analyses demonstrate that HAFY produces shallower and stronger boundary layer inflow, especially within 1–3 times the radius of maximum wind (RMW). Stronger inflow and more moisture in the boundary layer contribute to stronger moisture convergence near the RMW. These boundary layer characteristics are consistent with stronger, deeper, and more compact TC vortices in HAFY than in HAFA. Nevertheless, track skill in HAFY is slightly reduced, which is in part attributable to the cross-track error from a few early cycles of Hurricane Henri that exhibited ∼400 n mi (1 n mi = 1.852 km) track error at longer lead times. Sensitivity experiments based on HAFY demonstrate that turning off cumulus schemes notably reduces the track errors of Henri while turning off the deep cumulus scheme reduces the intensity errors. This finding hints at the necessity of unifying the mass fluxes in PBL and cumulus schemes in future model physics development.

Sensitivity of boundary layer parameterization schemes in a marine boundary layer jet and associated precipitation during a coastal warm-sector heavy rainfall event

The sensitivity of planetary boundary layer (PBL) parameterization schemes in a marine boundary layer jet and associated precipitation is investigated in this study. Six PBL parameterization schemes in the Weather Research and Forecasting Model, including YSU, MYJ, MYNN, ACM2, BouLac, and UW schemes, are examined in simulating a marine boundary layer jet (BLJ) over South China Sea and associated coastal precipitation during a warm-sector heavy rainfall event (19–20 May 2015) near the coast of South China. The results show that YSU, MYJ, MYNN, and BouLac schemes can generally reproduce the coastal warm-sector heavy rainfall with 6-h accumulated precipitation exceeding 50 mm, but not for the ACMs and UW schemes. No convection initiation occurs in the ACM2 run, while rainfall is located to further north with weaker intensity in the UW run. Meanwhile, weakest and strongest BLJs are simulated in the ACM2 and UW runs, respectively. In the ACM2 run, the weaker BLJ with the maximum wind speed less than 17 m s−1 induces weaker convergence and lifting in the upwind side of the coastal terrain as well as less water vapor transport to the coastal area, which thus inhibit convection initiation. On the contrary, the too strong BLJ in the UW run with large area of wind speed greater than 18 m s−1 causes the northward movement of convection along with cold pools, and rainfall moves further north accordingly. The differences in BLJs’ strength among PBL schemes are attributed to varying simulated low-level vortex on the northern side of the BLJ through veering ageostrophic winds. The intensity of the simulated low-level vortex is affected by variations in boundary layer mixing over land and associated vertical temperature stratification under different PBL schemes.

Evaluation of planetary boundary layer schemes on the urban heat islands in the urban agglomeration over the greater bay area in South China

Urbanization of large cities exerts significant changes in surface air temperature, which subsequently lead to inadvertent local weather and climate changes. The exchanges of momentum, moisture and heat within the planetary boundary layer (PBL) impact the urban atmosphere representation. The applicability of PBL schemes in regional modeling varies with different climate regimes and underlying surface. As the first step to gaining a better forecast of urban climates, the performances of multiple PBL schemes (YSU, MRF, ACM2, BL, MYNN, UW and GBM) on reproducing the low-level urban atmosphere are evaluated over the Greater Bay Area, South China, during April–June 2018. With the aid of observations from in situ weather stations and radiosondes, the urban environmental characteristics, including surface air temperature and humidity, temperature profile, urban heat island (UHI), and PBL height, are assessed. The results show a cool/moist bias near the surface during nighttime and a warm/dry bias during daytime for all PBL schemes. The daytime bias is significant on weak-UHI days while the nocturnal bias appears to be significant on strong-UHI days. The so-called best scheme depends on the exact meteorological variables, diurnal cycles, and thermodynamic conditions that are of interest. Specifically, the MYNN and MRF schemes perform the best for the daytime and nighttime air temperature, respectively. The MRF scheme also presents the best performance in simulating the observed UHI, with a good agreement with the observed diurnal variation. The numerical exercises in this study may serve as a reference for an efficient operational way that is readily accessible to forecast air temperature in the urban agglomeration over South China.

Assessment of WRF planetary boundary layer schemes in the simulation of fog events over Hungary

Accurate depiction of meteorological conditions, especially within the planetary boundary layer (PBL), is essential for fog forecasting. This study examines the sensitivity of the performance of the Weather Research and Forecast (WRF) model to the use of four different PBL schemes [Yonsei University (YSU), asymmetric convective model version 2 (ACM2), quasinormal scale elimination (QNSE), and Mellor-Yamada-Nakanishi-Niino version 3.0 (MYNN3)]. For this case study we have taken the fog event occurred in November 23-24, 2020. Surface observed temperature and relative humidity, furthermore, sounding data are compared with the output of the 36 hours, high-resolution weather forecast. The horizontal extension of the simulated fog is compared with satellite observations. The visibility is calculated from the prognostic variables of drop number concentration and mixing ratio. The simulated visibility and fog duration are validated by the visibility and fog duration evaluated by ceilometer observations. Validation of thermodynamical values such as 2-m temperature and relative humidity reveals, that during most of the simulation time, the bias is significant between the simulated and observed data. Results show that the PBL parameterization scheme significantly impacts fog microphysics also. The QNSE scheme results in unrealistic early formation of the fog, and too large liquid water content. YSU and ACM2 simulated the duration of fog to be rather short comparing with the other two PBL schemes. The best fitting with observed data is found in the case of MYNN3 PBL schemes.

Analysis of planetary boundary layer feedbacks on the multiple equilibria of the continental water cycle

A simple soil-atmosphere interaction model is developed to study the bimodal distribution of soil moisture in regions where there is feedback between precipitation and soil moisture. Our study includes planetary boundary layer (PBL) feedback in the coupled analytical soil-atmosphere interaction model with a varying PBL height and entrainment from the free atmosphere. This study aims to reveal the dominant PBL feedbacks that impact the occurrence of soil moisture bimodality by comparing the evolution of prognostic variables for a detailed PBL scheme (with varying PBL height and entrainment of heat and moisture from the free atmosphere) with the simple PBL scheme (with fixed PBL height and no entrainment). This study has shown the existence of multiple equilibria in the continental water balance for both detailed PBL and simple PBL schemes when the model is integrated for different initial soil moisture up to equilibria. Although both with and without PBL feedback, the results are in qualitative agreement; the soil moisture initialization to realize multiple equilibria of a detailed PBL scheme is larger than the simple PBL scheme. Although the direct quantitative comparison with observation is clearly limited in the simple model, it also demonstrates how the non-linear dynamics of the coupled soil-atmosphere system may be expected to occur in observations.

Diagnosing Near-Surface Model Errors with Candidate Physics Parameterization Schemes for the Multiphysics Rapid Refresh Forecast System (RRFS) Ensemble during Winter over the Northeastern United States and Southern Great Plains

Abstract During the winter of 2020/21 an ensemble of FV3-LAM forecasts was produced over the contiguous United States for the Winter Weather Experiment using five physics suites. These forecasts are evaluated with the goal of optimizing physics parameterizations within the future operational Rapid Refresh Forecast System (RRFS) in the Unified Forecast System (UFS) realm and for selecting suitable physics suites for a multiphysics RRFS ensemble. The five physics suites have different combinations of land surface models (LSMs), planetary boundary layer (PBL) parameterizations, and surface layer schemes, chosen from those used in current and possible future operational systems and likely to be supported in the operational UFS. Full-season evaluation reveals a persistent near-surface cold bias in the U.S. Northeast from one suite and a nighttime warm bias in the southern Great Plains in another suite, while other suites have smaller biases. A representative case is chosen to diagnose the cause for each of these biases using sensitivity simulations with different physics combinations or modified parameters and verified with additional mesonet observations. The cold bias in the Northeast is attributed to aspects of the Noah-MP LSM over snow cover, where Noah-MP simulates lower soil water content, and thus lower thermal conductivity than other LSMs, leading to less upward ground heat flux during nighttime and consequently lower surface temperature. The nighttime warm bias found in the southern Great Plains is attributed to overestimation of vertical mixing in the K-profile-based eddy-diffusivity mass-flux (K-EDMF) PBL scheme and insufficient land–atmospheric coupling from the GFS surface layer scheme over short vegetation. A few key parameters driving these systematic biases are identified.

Influence of Two Types of Planetary Boundary Layer Schemes on the Intensity of Typhoon Rammasun (2014)

Influence of Two Types of Planetary Boundary Layer Schemes on the Intensity of Typhoon Rammasun (2014)

Improving the Wind Power Density Forecast in the Middle- and High-Latitude Regions of China by Selecting the Relatively Optimal Planetary Boundary Layer Schemes

As the power generation mode with the lowest carbon emissions, wind power generation plays an indispensable role in achieving the goal of carbon neutralization. To optimize the wind power density (WPD), forecasting is crucial to improve wind power utilization and power system stability. However, because near-surface wind is characterized by notable randomness, diversity, intermittence, and uncontrollability, accurately forecasting the WPD on wind farms remains a challenging task. In this study, we attempted to improve the WPD forecast in the middle- and high-latitude regions of China (wind energy resources are abundant there) by selecting the relatively optimal planetary boundary layer (PBL) scheme, as the PBL processes exert notable effects on the near-surface wind field directly. Based on a whole month in the summer (July 2021), seven PBL schemes were compared quantitatively by using the Weather Research and Forecasting (WRF) model for a total of 70 runs (for each run, the forecast period was 3 days). The results show that no PBL schemes could always show the best performance in forecasting all variables, and the forecast accuracy showed a notable dependence on the evolution of the weather systems. Among the seven PBL schemes, the Medium-Range Forecast (MRF) scheme showed the overall best performance in forecasting the 100 m wind speed, sea level pressure, and 2 m temperature, which ensured that it had the highest forecast skill for the WPD in the middle- and high-latitude regions of China. Further analyses indicate that the background conditions were also well forecasted by the MRF scheme (ranked first or second). This was a crucial reason why the WPD forecast was the best for the MRF scheme.

Variations of Subgrid-Scale Turbulent Fluxes in the Dry Convective Boundary Layer at Gray Zone Resolutions

Abstract In the numerical gray zone of the convective boundary layer (CBL), the horizontal resolution is comparable to the size of organized convective circulation. As turbulence becomes partially resolved, gridscale variations of the subgrid-scale (SGS) turbulent fluxes become significant compared to the mean. Previously, such variations have often been ignored in scale-adaptive planetary boundary layer (PBL) schemes developed for the gray zone. This study investigates these variations with respect to height and resolution based on large-eddy simulations. It is found that SGS fluxes exhibit maximum variability at the center of the gray zone, where the resolved and the SGS mean fluxes are approximately equal. A simple analytical model is used to associate such characteristic variations to the nonlinear interactions of the dominant energy-containing mode of CBL turbulence. Examination of the horizontal distribution of the SGS fluxes reveals their preferential location over the updraft edges surrounding the core. A priori analysis further suggests the ability of a scale-similarity closure to reproduce the unique spatial patterns of the SGS fluxes at gray zone resolutions. Four scale-adaptive PBL schemes are evaluated focusing on their representations of the modeled SGS flux variability. Their shared shortcomings as a result of their gradient diffusion–based formulation are exposed. This study suggests that a mixed model consisting of a scale-adaptive PBL scheme to represent the mean, and a scale-similarity component to account for gridscale variability to be advantageous for the gray zone. Significance Statement As Gresho and Lee’s famous quote on numerical schemes goes, “Don’t suppress the wiggles. They’re telling you something!” In the numerical gray zone, where the grid spacing is comparable to the characteristic length scale of the flow, turbulence is partially resolved. The “wiggles” (or gridscale variability) reflecting the resolved heterogeneity of turbulent fluxes is an outstanding feature of the gray zone. However, they are often overlooked as error bars to the mean. This study uncovers the significance of these error bars, and characterizes and explains their variations with height and grid spacing. A suitable model that captures such variations is investigated to help build better planetary boundary layer schemes.

Evaluation of Model Summertime Boundary Layer Cloud Development over Complex Terrain in New York State

Abstract Weather forecasting over complex terrain with diverse land cover is challenging. Utilizing the high-resolution observations from New York State Mesonet (NYSM), we are able to evaluate the surface processes of the Weather Research Forecast (WRF) Model in a detailed, scale-dependent manner. In the study, possible impacts of land–atmosphere interaction on surface meteorology and boundary layer cloud development are investigated with different model resolutions, land surface models (LSMs), and planetary boundary layer (PBL) physical parameterizations. The High-Resolution Rapid Refresh, version 3 (HRRR), forecasting model is used as a reference for the sensitivity evaluation. Results show that over complex terrain, the high-resolution simulations (1 km × 60 vertical levels) generally perform better compared to low-resolution (3 km × 50 levels) in both surface meteorology and cloud fields. LSMs play a more important role in surface meteorology compared to PBL schemes. The NoahMP land surface model exhibits daytime warmer and drier biases compared to the Rapid Update Cycle (RUC) due to better prediction of the Bowen ratio in RUC. The PBL schemes would affect the convective strength in the boundary layer. The Shin–Hong (SH) scale-aware scheme tends to produce the strongest convective strength in the PBL, while the ACM2 PBL scheme rarely resolved convection even at 1-km resolution. By considering the radiation effect of subgrid-scale (SGS) clouds, the Mellor–Yamada–Nakanishi–Niino eddy diffusivity mass flux (MYNN-EDMF) predicted the highest cloud coverage and lowest surface solar radiation bias. The configuration of SGS clouds in MYNN-EDMF would not only significantly reduce shortwave radiation bias, but also affect the convection behaviors through land surface–cloud–radiation interaction.

Investigations on offshore wind turbine inflow modelling using numerical weather prediction coupled with local-scale computational fluid dynamics

The computational power available nowadays to industry and research paves the way to increasingly more accurate systems for the wind resource prediction. A promising approach is to support the mesoscale numerical weather prediction (NWP) with high fidelity computational fluid dynamics (CFD). This approach aims at increasing the spatial resolution of the wind prediction by not only accounting for the complex and multiphysics aspects of the atmosphere over a large geographical region, but also including the effects of the fine scale turbulence and the interaction of the wind flow with the sea surface. In this work, we test a set of model setups for both the mesoscale (NWP) and local scale (CFD) simulations employed in a multi-scale modelling framework. The method comprises a one-way coupling interface to define boundary conditions for the local scale simulation (based on the Reynolds Averaged Navier–Stokes equations) using the mesoscale wind given by the NWP system. The wind prediction in an offshore site is compared with LiDAR measurements, testing a set of mesoscale planetary boundary layer schemes, and different model choices for the local scale simulation, which include steady and unsteady approaches for simulation and boundary conditions, different turbulence closure constants, and the effect of the wave motion of the sea surface. The resulting wind is then used for the simulation of a large wind turbine, showing how a realistic wind profile and an ideal exponential law profile lead to different predictions of wind turbine rotor performance and loads.

The influence of different parameterizations on diurnal cycle of land precipitation in CAS-ESM

The impacts of physical parameterizations on the diurnal cycle of precipitation (DCP) over land are investigated by comparing long-term simulations of the Chinese Academy of Sciences Earth System Model (CAS-ESM). Significant improvements in the DCP occur when the model replaces the Community Atmosphere Model version 4 (CAM4) physics package with the CAM5 package at both global and regional scales. Globally, the reduced amplitudes and delayed phases of DCP with the CAM5 package can be explained by the diurnal variations in convective available potential energy (CAPE). Regionally, the improvements in the DCP are caused by the decreased daytime convergence at 850 hPa, smaller vertically integrated water vapor transport, weakened vertical velocity, and smaller stratus cloud liquid water amount simulated by the CAM5 package. Besides, CAS-ESM with the CAM5 package produces the decreased amplitudes and delayed phases of the diurnal variation of the convective cloud, which is closely related to the planetary boundary layer (PBL) processes. CAS-ESM with the CAM5 package exhibits a significantly lower PBL height than with the CAM4 package for both direct model outputs and estimates with the bulk Richardson number method. The peaks of lifting condensation level (LCL) deficit (difference between PBL height and LCL height) occur later (∼1–3 h) and are lower with the CAM5 package than with the CAM4 package. Consequently, CAS-ESM with the CAM5 package decreases the probability of cloud formation and produces more realistic DCP. This study underscores the importance of PBL schemes to the simulated convective clouds and DCP.

Simulating the Impacts of Wind Farm Wake under the Changes in MYNN Planetary Boundary Layer Scheme in High Resolution Weather Research and Forecasting Model

This study focuses on simulating the impacts of wind farm wake due to changes in the Mellor-Yamanda-Nakanishi-Niino (MYNN) planetary boundary layer (PBL) scheme in a high-resolution mesoscale Weather Research and Forecasting (WRF) model for a non-flat region in Turkey. This is the first study with a comprehensive evaluation of simulated wind farm wake impact responses to changes in the MYNN PBL scheme in the WRF model. Our results show that the WRF-WFP solutions for the wind farm wake impact significantly change with a change in the MYNN PBL scheme. In addition, the incorrect TKE advection and the correction factor of 0.25 for the TKE coefficient in wind farm parametrization (WFP) cause incorrect wind farm wake impacts especially on TKE and air temperature. Our study also shows that modifications in the mixing length create greater changes in simulated wind farm wake impacts than activation of the mass-flux scheme. In this study, the relative contributions of WFP’s components are also evaluated.

Mesoscale Simulation of Open Cellular Convection: Roles of Model Resolutions and Physics Parameterizations

The Open Cellular Convection (OCC) associated with cold air outbreaks is a common phenomenon over the North Sea where a large number of wind parks are presented. Thus, reliable numerical simulations of OCC events have great importance for offshore wind energy. We investigate the ability to simulate the OCC events using the Weather Research and Forecast (WRF) model with the ERA5 reanalysis data as initial and lateral boundary conditions and the OSITA data as the sea surface temperature. The domains were nested from 9 km as the outermost domain to 1 km as the innermost domain surrounding the Teesside wind farm located in the North Sea off the northeast coast of England. We simulated an OCC event in 2015 with three series of sensitivity numerical experiments of planetary boundary layer, microphysics, and radiation parameterizations. The model outputs were validated against the wind observation at the Teesside’s meteorological mast. The results suggest that the planetary boundary layer schemes are the most sensitive during the events compared to other parameterization schemes. Futher more, a convective-resolved resolution is necessary for simulating the OCC variation properly. The paper also discuss the verification methods for such short time-scale events like the OCC.

Optimizing simulation of summer precipitation by weather research and forecasting model over the mountainous southern Tibetan Plateau

The mountainous regions of southern Tibetan Plateau and surroundings (hereafter mountainous southern TP), mainly including Himalayas, Gangdise, Nyainqentanglha and Hengduan Mountains, are characterized by high mountains and a complex terrain, and play a crucial role in the redistribution of monsoon water vapor and consequently determine the spatial distribution of precipitation over the TP. However, numerical simulations generally have large precipitation deviation in this focus area. Therefore, optimizing simulation of summer precipitation by Weather Research and Forecasting (WRF) model with two-way nested domains was carried out. A matrix of 11 model experiments, including four cumulus convection (CU) schemes, four microphysics (MP) schemes and four planetary boundary layer (PBL) schemes, were designed. In situ observations from 44 stations, TRMM 3B42 v7 precipitation product, and statistical and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods were utilized for the model evaluation. The results showed that physical parameterization schemes, Kain-Fritsch-Cumulus Potential scheme (CU), Thompson scheme (MP), Mellor-Yamada-Janjic scheme (PBL), Unified Noah land surface model, and Eta similarity surface layer scheme, greatly reduced the summer precipitation simulation error of newly High Asia Refined analysis (HAR v2) over the mountainous southern TP, with the better reproduction of the spatiotemporal distribution and vertical variability of precipitation. Compared to NCEP-FNL reanalysis data, the performance of this model setup forced by ERA5 was notably improved, especially with perspective to the vertical variability of precipitation. Our findings suggested that summer precipitation simulation was more sensitive to the CU scheme, and the choice of Kain-Fritsch-Cumulus Potential scheme (ERA5 as initial conditions) significantly improved the precipitation simulation, especially with the lowest MAE (2.00 mm/d), RMSE (2.89 mm/d) and highest Rs (0.74). Further analysis implied that accurate description of shallow convection and proper suppression of deep convection should be considered in precipitation simulations over the TP, especially in mountainous regions. This study could provide a firm foundation for the production of more realistic dynamic downscaling precipitation dataset over the TP.

The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

Abstract. Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds often significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, as of the Weather Research and Forecasting model v4.3.3, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. We simulate a wind plant in pseudo-steady states under idealized stable, neutral, and unstable conditions with matching hub-height wind speeds using two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, average hub-height wind speed losses within the plant differ between PBL schemes by between −0.20 and 0.22 m s−1, and correspondingly, capacity factors range between 39.5 %–53.8 %. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.