Quasi-normal Scale Elimination Research Articles

Sensitivity of the meteorological model WRF-ARW to planetary boundary layer schemes during fog conditions in a coastal arid region

In this study, we intercompare seven different PBL schemes in WRF in the United Arab Emirates (UAE) and we assess their impact on the performance of the simulations. The study covered five fog events reported in 2014 at Abu Dhabi International Airport. The analysis of Synoptic conditions indicated that during all examined events, the UAE was under a high geopotential pressure and light wind that does not exceed 7m/s at 850hPa (~1.5km). Seven PBL schemes, namely, Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), Moller-Yamada Nakanishi and Niino (MYNN) level 2.5, Quasi-Normal Scale Elimination (QNSE-EDMF), Asymmetric Convective Model (ACM2), Grenier-Bretherton-McCaa (GBM) and MYNN level 3 were tested. In situ observations used in the model's assessment included radiosonde data from the Abu Dhabi International Airport and surface measurements of relative humidity (RH), dew point temperature, wind speed, and temperature profiles. Overall, all the tested PBL schemes showed comparable skills with relatively higher performance with the QNSE scheme. The average RH Root Mean Square Error (RMSE) and BIAS for all PBLs were 15.75% and −9.07%, respectively, whereas the obtained RMSE and BIAS when QNSE was used were 14.65% and −6.3% respectively. Comparable skills were obtained for the rest of the variables. Local PBL schemes showed better performance than non-local schemes. Discrepancies between simulated and observed values were higher at the surface level compared to high altitude values. The sensitivity to lead time showed that best simulation performances were obtained when the lead time varies between 12 and 18h. In addition, the results of the simulations show that better performance is obtained when the starting condition is dry.

Evaluation of Nocturnal Temperature Forecasts Provided by the Weather Research and Forecast Model for Different Stability Regimes and Terrain Characteristics

The quality of nocturnal temperature forecasts made by the Weather Research and Forecast (WRF) numerical model is evaluated. The model was run for all July 2012 nights, and temperature fields compared to hourly observations made at 26 weather stations in southern Brazil. Four different planetary boundary-layer (PBL) schemes are considered: Bougeault–Lacarrere (BouLac), Quasi-Normal Scale Elimination (QNSE), Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ). Additional simulations to assess the role of higher horizontal and vertical resolutions were performed using the MYJ scheme. All schemes, except BouLac, underestimated the 2-m temperature, and in all cases the temperature bias is dependent on wind speed. At high wind speeds, all schemes exhibit a cold bias, which is greater for those that yield lower nocturnal surface-layer turbulent intensity. The elevation difference between each station and the model nearest grid point $$H_{\textit{station}} -H_{\textit{gridpoint}} $$ is highly correlated with the temperature simulation error. We found that a consistent cold bias is restricted to conditions with low-level clouds. We concluded that one possible means of improving nocturnal temperature forecast is to use parametrization schemes that allow for higher turbulent intensity in near-neutral conditions. The results indicate that this improvement would partially counteract the misrepresentation of the low-level cloud cover. In most stable cases, a post-processing algorithm based on terrain characteristics may improve the forecasts.

QNSE theory of turbulence anisotropization and onset of the inverse energy cascade by solid body rotation

Under the action of solid body rotation, homogeneous neutrally stratified turbulence undergoes anisotropization and onset of the inverse energy cascade. These processes are investigated using a quasi-normal scale elimination (QNSE) theory in which successive coarsening of a flow domain yields scale-dependent eddy viscosity and diffusivity. The effect of rotation increases with increasing scale and manifests in anisotropization of the eddy viscosities, eddy diffusivities and kinetic energy spectra. Not only the vertical (in the direction of the vector of rotation $\unicode[STIX]{x1D734}$) and horizontal eddy viscosities and eddy diffusivities become different but, reflecting both directional and componental anisotropization, there emerge four different eddy viscosities. Three of them decrease relative to the eddy viscosity in non-rotating flows while one increases; the horizontal ‘isotropic’ viscosity decreases at the fastest rate. This behaviour is indicative of the increasing redirection of the energy flux to larger scales, the phenomenon that can be associated with the energy backscatter or inverse energy cascade. On scales comparable to the Woods’s scale which is the rotational analogue of the Ozmidov length scale in stably stratified flows, the horizontal viscosity rapidly decreases, and in order to keep it positive, a weak rotation limit is invoked. Within that limit, an analytical theory of the transition from the Kolmogorov to a rotation-dominated turbulence regime is developed. It is shown that the dispersion relation of linear inertial waves is unaffected by turbulence while all one-dimensional energy spectra undergo steepening from the Kolmogorov $-5/3$ to the $-3$ slope.

Theoretical study of anisotropic MHD turbulence with low magnetic Reynolds number

Flows of electrically conducting fluids under the action of external magnetic field present an example of strongly anisotropic turbulence. Such flows are not only important for different engineering applications, but also provide an interesting framework for studies of quasi-two-dimensional turbulence with strongly modified transport properties in easily controllable laboratory experiments. We present theoretical results that advance our understanding of magnetohydrodynamic (MHD) flows with low magnetic Reynolds number by treating this phenomenon within the quasi-normal scale elimination (QNSE) theory. Previous applications of the theory to turbulent flows with stable stratification and solid body rotation have demonstrated that QNSE is a powerful tool for studies of anisotropic turbulent flows. We derive expressions for scale-dependent eddy viscosities and eddy diffusivities in the directions parallel and normal to the external magnetic field and investigate progressive anisotropization of turbulent transport of momentum and passive scalar. The theory yields analytical expressions for anisotropic one-dimensional spectra of MHD turbulence. In particular, the theory sheds light upon the modification of the Kolmogorov k−5/3 spectrum by anisotropic Ohmic (Joule) dissipation.

Sensitivity of PBL schemes of the WRF-ARW model in simulating the boundary layer flow parameters for their application to air pollution dispersion modeling over a tropical station

Mesoscale atmospheric circulations play an important role in the transport of air pollution and local air quality issues. The planetary boundary layer (PBL), the thermo-dymamical structure and the flow field play an important role in air pollution dispersion. Hence, the PBL parameters over Nagpur, India are simulated using the ARW v. 3.6.1 mesoscale model. High-resolution simulations are conducted with triple nested domains having a horizontal resolution of 27, 9 and 3km, as well as 27 vertical levels by using the 1×1° NCEP Final Analysis meteorological fields for initial and boundary conditions. Eight fair-weather days in winter and summer (January and April 2009) with no significant synoptic activity were chosen for the study. Sensitivity experiments of the ARW model were conducted with two non-local (Yonsei University [YSU], and Asymmetric Convective Model v. 2 [ACM2]) and three local turbulence kinetic energy (TKE) closure (Mellor-Yamada Nakanishi and Niino Level 2.5 PBL [MYNN2], Mellor-Yamada-Janjic [MYJ], and quasi-normal scale elimination [QNSE]) turbulence diffusion parameterizations, to study the evolution of PBL parameters and the thermodynamical structure during the study period. After validation of the simulated parameters with the available in situ data, it was revealed that the non-local PBL scheme YSU, followed by local scheme MYNN2, could be able to capture the characteristic variations of surface meteorological variables and the thermodynamical structure of the atmosphere. The present results suggest that PBL schemes, namely YSU and MYNN2, performed better in representing the boundary-layer parameters and are useful for air pollution dispersion studies.

The Dependence of QPF on the Choice of Boundary- and Surface-Layer Parameterization for a Lake-Effect Snowstorm

AbstractSix forecasts of a lake-effect-snow event off Lake Erie were conducted using the Weather Research and Forecasting Model to determine how the quantitative precipitation forecast (QPF) was affected when the boundary- and surface-layer parameterization schemes were changed. These forecasts showed strong variability, with differences in liquid-equivalent precipitation maxima in excess of 20 mm over a 6-h period. The quasi-normal scale elimination (QNSE) schemes produced the highest accumulations, and the Mellor–Yamada–Nakanishi–Niino (MYNN) schemes produced the lowest. Differences in precipitation were primarily due to different sensible heat flux FH and moisture flux FQ off the lake, with lower FH and FQ in MYNN leading to comparatively weak low-level instability and, consequently, reduced ascent and production of hydrometeors. The different FH and FQ were found to have two causes. In QNSE, the higher FH and FQ were due to the decision to use a Prandtl number PR of 0.72 (all other schemes use a PR of 1). In MYNN, the lower FH and FQ were due to the manner in which the similarity stability function for heat ψh is functionally dependent on the temperature gradient between the surface and the lowest model layer. It is not known what assumptions are more accurate for environments that are typical for lake-effect snow, but comparisons with available observations and Rapid-Update-Cycle analyses indicated that MYNN had the most accurate results.

Sensitivity of 24-h Forecast Dryline Position and Structure to Boundary Layer Parameterizations in Convection-Allowing WRF Model Simulations

Abstract Recent NOAA Hazardous Weather Testbed Spring Forecasting Experiments have emphasized the sensitivity of forecast sensible weather fields to how boundary layer processes are represented in the Weather Research and Forecasting (WRF) Model. Thus, since 2010, the Center for Analysis and Prediction of Storms has configured at least three members of their WRF-based Storm-Scale Ensemble Forecast (SSEF) system specifically for examination of sensitivities to parameterizations of turbulent mixing, including the Mellor–Yamada–Janjić (MYJ); quasi-normal scale elimination (QNSE); Asymmetrical Convective Model, version 2 (ACM2); Yonsei University (YSU); and Mellor–Yamada–Nakanishi–Niino (MYNN) schemes (hereafter PBL members). In postexperiment analyses, significant differences in forecast boundary layer structure and evolution have been observed, and for preconvective environments MYNN was found to have a superior depiction of temperature and moisture profiles. This study evaluates the 24-h forecast dryline positions in the SSEF system PBL members during the period April–June 2010–12 and documents sensitivities of the vertical distribution of thermodynamic and kinematic variables in near-dryline environments. Main results include the following. Despite having superior temperature and moisture profiles, as indicated by a previous study, MYNN was one of the worst-performing PBL members, exhibiting large eastward errors in forecast dryline position. During April–June 2010–11, a dry bias in the North American Mesoscale Forecast System (NAM) initial conditions largely contributed to eastward dryline errors in all PBL members. An upgrade to the NAM and assimilation system in October 2011 apparently fixed the dry bias, reducing eastward errors. Large sensitivities of CAPE and low-level shear to the PBL schemes were found, which were largest between 1.0° and 3.0° to the east of drylines. Finally, modifications to YSU to decrease vertical mixing and mitigate its warm and dry bias greatly reduced eastward dryline errors.

Numerical simulations of heavy rainfall over central Korea on 21 September 2010 using the WRF model

On 21 September 2010, heavy rainfall with a local maximum of 259 mm d−1 occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting (WRF) model in reproducing this disastrous rainfall event and identified the role of two physical processes: planetary boundary layer (PBL) and microphysics (MPS) processes. The WRF model was forced by 6-hourly National Centers for Environmental Prediction (NCEP) Final analysis (FNL) data for 36 hours form 1200 UTC 20 to 0000 UTC 22 September 2010. Twenty-five experiments were performed, consisting of five different PBL schemes—Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), Quasi Normal Scale Elimination (QNSE), Bougeault and Lacarrere (BouLac), and University of Washington (UW)—and five different MPS schemes—WRF Single-Moment 6-class (WSM6), Goddard, Thompson, Milbrandt 2-moments, and Morrison 2-moments. As expected, there was a specific combination of MPS and PBL schemes that showed good skill in forecasting the precipitation. However, there was no specific PBL or MPS scheme that outperformed the others in all aspects. The experiments with the UW PBL or Thompson MPS scheme showed a relatively small amount of precipitation. Analyses form the sensitivity experiments confirmed that the spatial distribution of the simulated precipitation was dominated by the PBL processes, whereas the MPS processes determined the amount of rainfall. It was also found that the temporal evolution of the precipitation was influenced more by the PBL processes than by the MPS processes.

Mesoscale atmospheric flow-field simulations for air quality modeling over complex terrain region of Ranchi in eastern India using WRF

In the present study mesoscale meteorological flow and planetary boundary layer (PBL) parameters over the complex topographic region of Jharkhand state of tropical India are simulated using high resolution Advanced Research WRF (ARW) mesoscale model to study their role in the air pollution dispersion characteristics using a Lagrangian Particle Dispersion Model (FLEXPART). Eight fair weather days in different seasons (winter, pre-monsoon, monsoon, and post-monsoon) are chosen. Sensitivity experiments are conducted with two non-local [Yonsei University (YSU), Asymmetric Convective Model version 2 (ACM2)] and three local turbulence kinetic energy (TKE) closure [Mellor- Yamada Nakanishi and Niino Level 2.5 PBL (MYNN2), Mellor-Yamada-Janjic (MYJ), and quasi-normal scale elimination (QNSE)] PBL parameterisations to study the evolution of PBL parameters and thermodynamic structure. Simulated parameters are validated with available in situ meteorological observations at three stations in the study region. Results indicate that the low-level flow field is highly influenced by the topography and widely varies in different seasons. Simulated vertical PBL structure varied across seasons with shallow boundary layers (1–1.7 km) during winter, monsoon and post-monsoon seasons, deep mixed layers (2–2.7 km) in pre-monsoon season. Simulations in various seasons revealed that ACM2 followed by MYNN2 and YSU reproduced various PBL features such as topographic flows, surface layer fluxes, meteorological variables and the thermo-dynamical structure reasonably well indicating the suitability of the above PBL schemes for air quality simulations over the region. This is corroborated with the error statistics as well. Simulations with FLEXPART using ARW derived meteorology revealed higher dilution potential of the atmosphere in monsoon and pre-monsoon compared to post monsoon and winter seasons over the region. Results also indicate the ACM2, MYNN2 and YSU produce relatively larger dispersion than the QNSE and MYJ.

Methodical assessment of the differences between the QNSE and MYJ PBL schemes for stable conditions

The increasing number of physics parametrization schemes adopted in numerical weather forecasting models has resulted in a proliferation of intercomparison studies in recent years. Many of these studies concentrated on determining which parametrization yields results closest to observations rather than analyzing the reasons underlying the differences. In this work, we study the performance of two 1.5‐order boundary layer parameterizations, the quasi‐normal scale elimination (QNSE) and Mellor–Yamada–Janjić (MYJ) schemes, in the weather research and forecasting model. Our objectives are to isolate the effect of stability functions on the near‐surface values and vertical profiles of virtual temperature, mixing ratio and wind speed. The results demonstrate that the QNSE stability functions yield better error statistics for 2 m virtual temperature but higher up the errors related to QNSE are slightly larger for virtual temperature and mixing ratio. A surprising finding is the sensitivity of the model results to the choice of the turbulent Prandtl number for neutral stratification (Prt0): in the Monin–Obukhov similarity function for heat, the choice of Prt0 is sometimes more important than the functional form of the similarity function itself. There is a stability‐related dependence to this sensitivity: with increasing near‐surface stability, the relative importance of the functional form increases. In near‐neutral conditions, QNSE exhibits too strong vertical mixing attributed to the applied turbulent kinetic energy subroutine and the stability functions, including the effect of Prt0.

An Evaluation of the Mellor-Yamada-Janjić Formulation Parameters for the QNSE Scheme in the WRF Model over the Lower Yangtze River Valley

Accurate description of boundary layer processes is important for numerical simulations, and some model parameters in the boundary layer schemes play an important role in the model simulations. The Quasi-Normal Scale Elimination (QNSE) scheme in the Weather Research and Forecasting (WRF) model version 3.1.1 reverts into the Mellor-Yamada-Janjic (MYJ) model under unstable and neutral conditions. The parameters (A_1, A_2, B_1, B_2, C_1) that affect the turbulent mixing in the MYJ formulation are the proportional coefficients of turbulence length scales and the master turbulence length scale. This study examines the model simulations sensitivity to different MYJ parameters. The simulation results show that MYJ parameters play a significant role in rainfall simulations. The analysis results imply that the parameters may affect the rainfall mainly by changing turbulent mixing and coupling with other physical process, such as cumulus convection processes, and then changing heat, momentum, and moisture transfer. The previous parameters used in the original MYJ formulation are not always the best and none of the parameters are always the best. It may be more appropriate that the parameters should be adopted in their plausible physical bounds depending on the planetary boundary layer (PBL) structures characteristics under specific meteorological and geographical circumstances.

The importance of surface layer parameterization in modeling of stable atmospheric boundary layers

AbstractThe accuracy of prediction of stable atmospheric boundary layers depends on the parameterization of the surface layer which is usually derived from the Monin–Obukhov similarity theory. In this article, several surface‐layer models in the format of velocity and potential temperature Deacon numbers are compared with observations from CASES99, Cardington, and Halley datasets. The comparisons were hindered by a large amount of scatter within and among datasets. Tests utilizing R2 demonstrated that the quasi‐normal scale elimination (QNSE) theory exhibits the best overall performance. Further proof of this was provided by 1D simulations with the Weather Research and Forecasting (WRF) model.

Objectively Determined Fair-Weather NBL Features in ARW-WRF and Their Comparison to CASES-97 Observations

AbstractHeights of nocturnal boundary layer (NBL) features are determined using vertical profiles from the Advanced Research Weather Research and Forecasting Model (ARW-WRF), and then compared to data for three moderately windy fair-weather nights during the April–May 1997 Kansas-based Cooperative Atmosphere–Surface Exchange Study (CASES-97) to evaluate the success of four PBL schemes in replicating observations. The schemes are Bougeault–LaCarrere (BouLac), Mellor–Yamada–Janjić (MYJ), quasi-normal scale elimination (QNSE), and Yonsei University (YSU) versions 3.2 and 3.4.1. This study’s chosen objectively determined model NBL height h estimate uses a turbulence kinetic energy (TKE) threshold equal to 5% , where TKE′ is relative to its background (free atmosphere) value. The YSU- and MYJ-determined h could not be improved upon. Observed heights of the virtual temperature maximum hTvmax and wind speed maximum hSmax, and the heights h1wsonde and h2wsonde, between which the radiosonde slows from ~5 to ~3 m s−1 as it rises from turbulent to nonturbulent air, and thus brackets h, were used for comparison to model results. The observations revealed a general pattern: hTvmax increased through the night, and hTvmax and hSmax converged with time, and the two mostly lay between h1wsonde and h2wsonde after several hours. Clear failure to adhere to this pattern and large excursions from observations or other PBL schemes revealed excess mixing for BouLac and YSU version 3.2 (but not version 3.4.1) and excess thermal mixing for QNSE under windy conditions. Observed friction velocity was much smaller than model values, with differences consistent with the observations reflecting local skin drag and the model reflecting regional form drag + skin drag.

A Compact Model for the Stability Dependency of TKE Production–Destruction–Conversion Terms Valid for the Whole Range of Richardson Numbers

Abstract Recently, observational and numerical evidence has accumulated against the concept of a critical Richardson number Ricr beyond which too-stable stratification would extinguish turbulence. It also appeared that the characteristics of the “weak turbulent regime” where the Prandtl number σt increases proportionally to the Richardson number Ri can be explained via the conservation of total turbulent energy in a strongly anisotropic flow. Having a “No Ri(cr)” situation together with due consideration of the anisotropy thus leads to the correct asymptotic behavior at high stabilities in several recent proposals [revisit of the Mellor–Yamada basic system, non-Reynolds-type quasi-normal scale elimination (QNSE) theory, and energy and flux budget (EFB) theory leading to a fully self-consistent hierarchy of increasingly prognostic schemes]. The present work derives a simple unique analytical framework for these various alternatives, simplifying, in two complementary but surprisingly converging ways, the revisited Mellor–Yamada formulation and emulating with high accuracy the relevant solutions within QNSE and EFB. The simplification or emulation steps differ from one case to the next, but the obtained common framework is very compact, valid for Ri going from −∞ to +∞, depending only on four free parameters and on three “functional dependencies.” Each functional dependency corresponds either to a constant value or to a regular function of the flux Richardson number Rif depending on the complexity of the considered hypotheses. Four realizations of this codification are representative of all related possibilities, the analytical scheme thus possessing high transversal validity. Extension toward higher-order solutions and/or moist turbulence can be envisaged in such a unified framework.

Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in Houston/Texas

With over 6 million inhabitants the Houston metropolitan area is the fourth-largest in the United States. Ozone concentration in this southeast Texas region frequently exceeds the National Ambient Air Quality Standard (NAAQS). For this reason our study employed the Weather Research and Forecasting model with Chemistry (WRF/Chem) to quantify meteorological prediction differences produced by four widely used PBL schemes and analyzed its impact on ozone predictions. The model results were compared to observational data in order to identify one superior PBL scheme better suited for the area. The four PBL schemes include two first-order closure schemes, the Yonsei University (YSU) and the Asymmetric Convective Model version 2 (ACM2); as well as two turbulent kinetic energy closure schemes, the Mellor–Yamada–Janjic (MYJ) and Quasi-Normal Scale Elimination (QNSE). Four 24 h forecasts were performed, one for each PBL scheme. Simulated vertical profiles for temperature, potential temperature, relative humidity, water vapor mixing ratio, and the u–v components of the wind were compared to measurements collected during the Second Texas Air Quality Study (TexAQS-II) Radical and Aerosol Measurements Project (TRAMP) experiment in summer 2006. Simulated ozone was compared against TRAMP data, and air quality stations from Continuous Monitoring Station (CAMS). Also, the evolutions of the PBL height and vertical mixing properties within the PBL for the four simulations were explored. Although the results yielded high correlation coefficients and small biases in almost all meteorological variables, the overall results did not indicate any preferred PBL scheme for the Houston case. However, for ozone prediction the YSU scheme showed greatest agreements with observed values.

Numerical simulation and intercomparison of boundary layer structure with different PBL schemes in WRF using experimental observations at a tropical site

In this study the performance of seven PBL parameterizations in the Weather Research and Forecast (WRF-ARW) mesoscale model was tested at the tropical site Kalpakkam. Meteorological observations collected during an intense observation campaign for wind field modeling called Round Robin Exercise (RRE) were used for comparison. High resolution simulations were conducted for a warm summer condition on 22–24 September 2010. The observations included GPS Sonde vertical profiles, surface level data from meteorological towers and turbulent fluxes from sonic anemometers. Sensitivity experiments with seven PBL schemes [Mellor-Yamada-Janjic (MYJ), Mellor-Yamada-Nakanishi-Niino (MYNN), Quasi Normal Scale Elimination (QNSE), Yonsei University (YSU), Asymmetric Convective Model (ACM2), Bougeault-Lacarrére (BL), Bretherton-Park (UW)] indicated that while all the schemes similarly produced the stable boundary layer characteristics there were large differences in the convective daytime PBL. It has been found that while ACM2 and QNSE produced highly unstable and deep convective layers, the UW produced relatively shallow mixed layer and all other schemes (YSU, MYNN, MYJ, BL) produced intermediately deep convective layers. All the schemes well produced the vertical wind directional shear within the PBL. A wide variation in the eddy diffusivities was simulated by different PBL schemes in convective daytime condition. ACM2 and UW produced excessive diffusivities which led to relatively weaker winds, warmer and dryer mixed layers with these schemes. Overall the schemes MYNN and YSU simulated the various PBL quantities in better agreement with observations. The differences in the simulated PBL structures could be partly due to various surface layer formulations that produced variation in friction velocity and heat fluxes in each case.

A down-valley low-level jet event during T-REX 2006

A prolonged down-valley flow and low-level jet were observed throughout the Enhanced Observing Period 4 (April 28–29) of the 2006 Terrain-induced Rotor Experiment, held in the Owens Valley of California near the town of Independence. The low-level jet was strongest during the nocturnal hours, and special field observations captured important details of the event lifecycle. High-resolution simulations using the Weather Research and Forecasting numerical weather prediction model were generated, with underlying assumptions being that model resolution, boundary layer physics, and nesting configuration would be dominant controlling factors in reproducing the jet. The large-scale conditions were dry throughout the event, so moist physics were not a significant forcing consideration. For the control simulation, a two-nest (4.5 and 1.5 km grid spacing) configuration with 90 vertical levels was applied. Additionally, the Quasi-Normal Scale Elimination planetary boundary and surface layer option were selected due to its published performance under conditions of stable stratification. Three other sensitivity simulations were run for comparison, differing from the control just in the choice of vertical resolution (60 versus 90 levels with Quasi-Normal Scale Elimination) and planetary boundary/surface layer physics (90 levels/Mellor-Yamada-Jancic; 90 levels/Yonsei State University). Although the gross evolution (location, height, and timing) of the low-level jet is captured by all model runs (with the 1.5 km inner nest providing the more accurate details), there were at times large underestimations of the nocturnal jet speed max in each simulation (approaching 100 % error, or up to almost 10 m s−1). Overall, the variations of vertical resolution and planetary boundary/surface physics against the control seemed to (1) yield little overall improvement to statistical or subjective evaluations; (2) do little to improve deficiencies in reproducing the magnitude strength of the nocturnal down-valley low-level jet. Since the cold-start simulations spanned 36 h (including a 12-h spin-up period), it was suspected that the lateral boundary conditions imposed on the outermost 4.5 km nest might negatively impact the interior model solutions in the Owens Valley. To investigate this possibility, an additional simulation was executed by adding two extra nests to the control configuration: an outer 13.5 km and an inner 500 m. This simulation produced a better evolution of the nocturnal low-level jet and especially the speed max. The addition of the larger 13.5 km nest appears more critical to this improvement than that of the extra spatial resolution provided by the inner 500 m nest, which supports the idea that accurate capturing of the large-scale synoptic condition was critical in reproducing important details of this down-valley low-level jet event. The extra 500-m resolution did seem to improve the morning valley cold pool forecast.

Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations

Abstract This study evaluates forecasts of thermodynamic variables from five convection-allowing configurations of the Weather Research and Forecasting Model (WRF) with the Advanced Research core (WRF-ARW). The forecasts vary only in their planetary boundary layer (PBL) scheme, including three “local” schemes [Mellor–Yamada–Janjić (MYJ), quasi-normal scale elimination (QNSE), and Mellor–Yamada–Nakanishi–Niino (MYNN)] and two schemes that include “nonlocal” mixing [the asymmetric cloud model version 2 (ACM2) and the Yonei University (YSU) scheme]. The forecasts are compared to springtime radiosonde observations upstream from deep convection to gain a better understanding of the thermodynamic characteristics of these PBL schemes in this regime. The morning PBLs are all too cool and dry despite having little bias in PBL depth (except for YSU). In the evening, the local schemes produce shallower PBLs that are often too shallow and too moist compared to nonlocal schemes. However, MYNN is nearly unbiased in PBL depth, moisture, and potential temperature, which is comparable to the background North American Mesoscale model (NAM) forecasts. This result gives confidence in the use of the MYNN scheme in convection-allowing configurations of WRF-ARW to alleviate the typical cool, moist bias of the MYJ scheme in convective boundary layers upstream from convection. The morning cool and dry biases lead to an underprediction of mixed-layer CAPE (MLCAPE) and an overprediction of mixed-layer convective inhibition (MLCIN) at that time in all schemes. MLCAPE and MLCIN forecasts improve in the evening, with MYJ, QNSE, and MYNN having small mean errors, but ACM2 and YSU having a somewhat low bias. Strong observed capping inversions tend to be associated with an underprediction of MLCIN in the evening, as the model profiles are too smooth. MLCAPE tends to be overpredicted (underpredicted) by MYJ and QNSE (MYNN, ACM2, and YSU) when the observed MLCAPE is relatively small (large).

An analytical theory of the buoyancy–Kolmogorov subrange transition in turbulent flows with stable stratification

The buoyancy subrange of stably stratified turbulence is defined as an intermediate range of scales larger than those in the inertial subrange. This subrange encompasses the crossover from internal gravity waves (IGWs) to small-scale turbulence. The energy exchange between the waves and small-scale turbulence is communicated across this subrange. At the same time, it features progressive anisotropization of flow characteristics on increasing spatial scales. Despite many observational and computational studies of the buoyancy subrange, its theoretical understanding has been lagging. This article presents an investigation of the buoyancy subrange using the quasi-normal scale elimination (QNSE) theory of turbulence. This spectral theory uses a recursive procedure of small-scale modes elimination based upon a quasi-normal mapping of the velocity and temperature fields using the Langevin equations. In the limit of weak stable stratification, the theory becomes completely analytical and yields simple expressions for horizontal and vertical eddy viscosities and eddy diffusivities. In addition, the theory provides expressions for various one-dimensional spectra that quantify turbulence anisotropization. The theory reveals how the dispersion relation for IGWs is modified by turbulence, thus alleviating many unique waves' features. Predictions of the QNSE theory for the buoyancy subrange are shown to agree well with various data.

Objectively Determined Fair-Weather CBL Depths in the ARW-WRF Model and Their Comparison to CASES-97 Observations

Abstract High-resolution 24-h runs of the Advanced Research version of the Weather Research and Forecasting Model are used to test eight objective methods for estimating convective boundary layer (CBL) depth h, using four planetary boundary layer schemes: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), Bougeault–LaCarrere (BouLac), and quasi-normal scale elimination (QNSE). The methods use thresholds of virtual potential temperature Θυ, turbulence kinetic energy (TKE), Θυ,z, or Richardson number. Those that identify h consistent with values found subjectively from modeled Θυ profiles are used for comparisons to fair-weather observations from the 1997 Cooperative Atmosphere–Surface Exchange Study (CASES-97). The best method defines h as the lowest level at which Θυ,z = 2 K km−1, working for all four schemes, with little sensitivity to horizontal grid spacing. For BouLac, MYJ, and QNSE, TKE thresholds did poorly for runs with 1- and 3-km grid spacing, producing irregular h growth not consistent with Θυ-profile evolution. This resulted from the vertical velocity W associated with resolved CBL eddies: for W > 0, TKE profiles were deeper and Θυ profiles more unstable than for W < 0. For the 1-km runs, 25-point spatial averaging was needed for reliable TKE-based h estimates, but thresholds greater than free-atmosphere values were sensitive to horizontal grid spacing. Matching Θυ(h) to Θυ(0.05h) or Θυ at the first model level were often successful, but the absence of eddies for 9-km grids led to more unstable Θυ profiles and often deeper h. Values of h for BouLac, MYJ, and QNSE, are mostly smaller than observed, with YSU values close to slightly high, consistent with earlier results.