Planetary Boundary Layer Wind Research Articles

Study of boundary layer parameterization simulation uncertainties of sand-dust storm windfield using high-resolution three-dimensional Doppler wind lidar data

The processes of dust emission, the development, and dissipation of sand and dust storms all exhibit dynamic and rapidly changing characteristics, posing significant challenges for us to accurately represent their complex behaviors in numerical simulations. In the numerical weather prediction model, the selection and optimization of planetary boundary layer (PBL) parameterization schemes have a direct impact on the simulation results of PBL wind fields, primarily due to the significant uncertainty in the fine-grained simulation of PBL wind field structure. To gain a deeper understanding of the sources of uncertainty in simulating sand-dust storms through vertical wind field structure simulations of the PBL, this study utilizes high-resolution 3D Doppler wind lidar (DWL) data. Focusing on sand-dust storm wind fields with distinctive regional characteristics in Inner Mongolia, China, it examines the turbulent momentum equation and assumptions of the PBL. A comprehensive and systematic evaluation was conducted on the characteristics of horizontal and vertical wind fields, wind shear, as well as the dynamic and thermodynamic differences that arise when simulating typical sand-dust storm wind fields using the Weather Research and Forecasting (WRF) Model with various PBL schemes. This evaluation focused on simulating the typical wind field of sand-dust storms during various stages, including dust generation, occurrence, development, and dissipation. The findings indicate that non-adiabatic heating plays a significant role in the sustainability and evolution of sand-dust storms. The wind shear index holds particular importance as it embodies the dynamic factor in the model. The PBL schemes such as Mellor-Yamada Nakanishi and Niino Level 2.5 (MYNN2), A new version of asymmetric convective model (ACM2), and Grenier-Bretherton-McCaa (GBM), which factor in buoyancy effects, demonstrate more accurate wind shear simulations in sand-dust storms. Furthermore, the ACM2 scheme effectively replicates the fundamental variation characteristics of meteorological elements throughout the sand-dust storm lifecycle.

The vortex structure and near‐surface winds of Typhoon Faxai (2019) during landfall. Part II: Evaluation of WRF simulations

AbstractThis two‐part study presents a comprehensive analysis of (1) the vortex structure, (2) the inner core planetary boundary layer (PBL) wind profile, and (3) the overland surface winds of Typhoon Faxai(2019) during landfall observationally (Part I) and in high‐resolution Weather Research and Forecasting Model (WRF) simulations (Part II). Part II presents a framework for evaluating the wind field in the WRF simulations of Typhoon Faxai (2019) by comparing them with the observations presented in Part I. First, WRF simulations with two different surface roughness tables are presented. The simulation with the default table in WRF is shown to largely overestimate the surface wind speed. The overestimation is largely mitigated by using larger based on the climatology for urban and forest areas in Japan. Next, using the modified table, WRF simulations with three different PBL parametrizations, namely, Mellor–Yamada–Janjić, Yonsei University, and Mellor–Yamada–Nakanishi–Niino schemes are presented, and their impacts on the simulated vortex structure, inner core PBL wind profile, and overland surface winds are evaluated. In particular, the simulated surface winds are in good agreement with the observations outside the inner core of Typhoon Faxai. However, during the passage of the eyewall, the maximum surface winds are underestimated in the simulations. We show that the underestimation of the inertial stability, associated with the excessively large inner core of Typhoon Faxai in the simulations, led to the overestimation of the eyewall PBL jet height. This, in turn, caused the underestimation of the peak surface winds, as based on the empirical model of the wind reduction factor proposed in Part I.

Impacts of Sea Surface Temperature Gradient on Monsoon Intraseasonal Oscillation

Abstract The northward-propagating monsoon intraseasonal oscillation (MISO) is the most pronounced variability over the tropical Indian Ocean during the Indian summer monsoon (June–September). MISO is accompanied by significant air–sea interactions; however, the mechanism of the oceanic feedback to MISO is still a great scientific challenge. In this study, the role of the intraseasonal sea surface temperature (SST) gradient in MISO is diagnosed using reanalysis products and model sensitivity experiments. It is found that the positive meridional gradient of intraseasonal SST induces positive wind convergence in the planetary boundary layer (PBL) and leads convection by about 1–2 days. This accounts for approximately half of the total wind convergence in the PBL to the north of convection during MISO. The warm SST anomalies before convection accelerate the intraseasonal northerly wind in the PBL due to the enhanced downward transport of momentum from aloft. By contrast, the cold SST anomalies behind deep convection weaken the downward vertical momentum transport, thereby inducing a deceleration in the intraseasonal northerly. Consequently, changes in the speed of intraseasonal northerly along the meridional direction strengthen the PBL wind convergence ahead of deep convection. It finally results in the intensification of intraseasonal rainfall associated with MISO over the summer monsoon region. In addition, a strong (weak) SST meridional gradient at an intraseasonal time scale amplifies (lessens) the MISO intensity in the model simulation. Thus, this study highlights the role of SST meridional gradient in the feedback to MISO, which differs from the weak contribution of the warm SST itself to the wind convergence mentioned in previous studies. Collectively, these findings indicate that consideration of oceanic feedback is necessary to improve the understanding and simulation of MISO.

Profiling the Planetary Boundary Layer Wind with a StreamLine XR Doppler LiDAR: Comparison to In-Situ Observations and WRF Model Simulations

Halo-Photonics StreamLine XR Doppler LiDAR measurements are performed using several scan configurations (Velocity Azimuth Display-VAD and Doppler Beam Swing-DBS) and elevation angles of 60° and 80°. The measurements are compared to wind observations conducted by various in situ instruments (tethered balloon, meteorological mast, and radiosondes). Good agreement is obtained, with R2 over 0.90 for wind speed and a standard error ≤ 18.6° for wind direction. The best performance was attained for lower elevation scans (60°), which is consistent with the higher spatial horizontal homogeneity exhibited by lower angle scans. VAD and DBS scans performed almost equally well with slight advantage for VAD in higher altitudes and for DBS for lower altitudes. The boundary layer structure along a diurnal cycle is analyzed by utilizing retrieved backscatter data and wind measurements in conjunction with Weather Research and Forecast (WRF) simulations. The presence of multiple inversions which allow the coexistence of different layers within the studied profile is also verified using data acquired by several radiosondes. Synergic use of LiDAR data with WRF simulations for low SNR regions is demonstrated.

Impact of lidar data assimilation on planetary boundary layer wind and PM2.5 prediction in Taiwan

Accurate simulations of planetary boundary layer (PBL) processes in numerical weather models are vital for air quality predictions. Advanced remote sensing techniques, such as lidar detection and ranging (lidar), can provide aerosol information with high temporal and vertical resolutions in the PBL. In this study, a lidar data assimilation system was developed based on the Weather Research and Forecasting-Local Ensemble Transform Kalman Filter (WRF-LETKF) framework coupled with the Community Multiscale Air Quality (CMAQ) model. The objective was to investigate the impact of lidar data assimilation on PBL prediction and the subsequent influence on PM2.5 prediction for a high-air-pollution event.The fine particulate matter (PM2.5) profiles retrieved from two micropulse lidar observations in northern and central Taiwan were assimilated in the WRF-LETKF system. Three numerical experiments, BASE (with a nudging strategy), CTRL (with an ensemble framework), and LDA (with assimilation of lidar-retrieved PM2.5 profiles), were conducted for a high-air-pollution episode. The BASE simulation overestimates the wind speed, which also leads to PM2.5 underestimation. The CTRL and LDA simulations are able to improve the wind fields and enhance the PM2.5 accumulation. With a strong error correlation between the lidar-retrieved PM2.5 concentration and the wind fields, the LDA simulation effectively corrects the wind flow from the surface to the PBL top, which further adjusts the PM2.5 transport processes and leads to results that agree well with observations.

Impact of data assimilation and aerosol radiation interaction on Lagrangian particle dispersion modelling

Lagrangian particle dispersion models (LPDMs) have been widely used in air pollution studies. However, substantial uncertainties still exist in LPDM simulations due to biased meteorological data, especially under stagnant and highly-polluted conditions. In this work, to better investigate the source contribution and formation of winter haze pollution in eastern China, we conduct a sensitivity study of WRF-FLEXPART by using different reanalysis data, applying observational meteorological nudging, and considering aerosols' radiative feedback on meteorology. We find that simulations driven by reanalysis datasets generally underestimate pollutant concentration, especially during periods with heavy haze pollution. The underestimation is directly caused by overestimated planetary boundary layer (PBL) height and lower PBL horizontal wind speeds. By assimilating meteorological data from surface and radiosonde observation, the WRF model can well represent the PBL dynamics and wind fields, especially those near the ground surface, which then substantially improves particle tracing in the LPDM. In addition, by including aerosols' radiative feedback in the WRF-Chem model, which significantly influences PBL evolution, the biases between LPDM modelling and observations are notably narrowed, particularly when the haze pollution is severe. Quantitatively, the accuracy increase of the simulations with aerosols’ radiative effect accounted for 48% of the improvement produced by assimilating meteorological data. Overall, meteorological input is of great importance in LPDM modelling. In regions with intensive pollution like China and India, applying observational data assimilation or considering the feedbacks of aerosols to meteorology serve as an effective way to reduce the biases of LPDMs and better understand the source contributions as well as the formation and accumulation of pollution.

Aircraft observed diurnal variations of the planetary boundary layer under heat waves

Abstract This study investigates the diurnal variations of the planetary boundary layer (PBL) properties during heat waves (HWs) based on a decade-long data record of hourly profiles from the Aircraft Meteorological Data Reports (AMDAR) at 54 major airports over the Continental United States. The results are also corroborated by surface observations from weather stations. HWs are defined as periods of at least two consecutive days with daily mean temperature higher than the 95th percentile of the warm season (May to September) climatology. Temperature differences between HW and non-HW periods show strong vertical variations throughout the PBL. Under HWs, the daytime convective PBL is deeper while the nocturnal residual layer is excessively hotter. The difference between HWs and non-HWs in the PBL wind and humidity are not uniform, with clear diurnal and vertical variations at some sites. HW-related changes in PBL wind components are strongly associated with changes in atmospheric circulation patterns, especially in the northeastern region. The specific humidity in the PBL shows increases in humid regions but decreases in arid regions under HWs. Moisture transport and surface evaporation are found to play an important role in modulating the changes in PBL humidity. This study highlights that HW-related changes in the PBL structure are not uniform and are affected by both synoptic and local factors.

Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model

Abstract. Atmospheric inversions have been used to assess biosphere–atmosphere CO2 surface exchanges at various scales, but variability among inverse flux estimates remains significant, especially at continental scales. Atmospheric transport errors are one of the main contributors to this variability. To characterize transport errors and their spatiotemporal structures, we present an objective method to generate a calibrated ensemble adjusted with meteorological measurements collected across a region, here the upper US Midwest in midsummer. Using multiple model configurations of the Weather Research and Forecasting (WRF) model, we show that a reduced number of simulations (less than 10 members) reproduces the transport error characteristics of a 45-member ensemble while minimizing the size of the ensemble. The large ensemble of 45 members was constructed using different physics parameterization (i.e., land surface models (LSMs), planetary boundary layer (PBL) schemes, cumulus parameterizations and microphysics parameterizations) and meteorological initial/boundary conditions. All the different models were coupled to CO2 fluxes and lateral boundary conditions from CarbonTracker to simulate CO2 mole fractions. Observed meteorological variables critical to inverse flux estimates, PBL wind speed, PBL wind direction and PBL height are used to calibrate our ensemble over the region. Two optimization techniques (i.e., simulated annealing and a genetic algorithm) are used for the selection of the optimal ensemble using the flatness of the rank histograms as the main criterion. We also choose model configurations that minimize the systematic errors (i.e., monthly biases) in the ensemble. We evaluate the impact of transport errors on atmospheric CO2 mole fraction to represent up to 40 % of the model–data mismatch (fraction of the total variance). We conclude that a carefully chosen subset of the physics ensemble can represent the uncertainties in the full ensemble, and that transport ensembles calibrated with relevant meteorological variables provide a promising path forward for improving the treatment of transport uncertainties in atmospheric inverse flux estimates.

Influence of Boundary Layer Structure and Low-Level Jet on PM2.5 Pollution in Beijing: A Case Study

Beijing experiences frequent PM2.5 pollution, which is influenced by the planetary boundary layer (PBL) structure/process. Partly due to a lack of appropriate observations, the impacts of PBL on PM2.5 pollution are not yet fully understood. Combining wind-profiler data, radiosonde measurements, near-surface meteorological observations, aerosol measurements, and three-dimensional simulations, this study investigated the influence of PBL structure and the low-level jet (LLJ) on the pollution in Beijing from 19 to 20 September 2015. The evolution of the LLJ was generally well simulated by the model, although the wind speed within the PBL was overestimated. Being influenced by the large-scale southerly prevailing winds, the aerosols emitted from the southern polluted regions could be easily transported to Beijing, contributing to ~68% of the PM2.5 measured in Beijing on 20 September. The relative contribution of external transport of PM2.5 to Beijing was high in the afternoon (≥80%), which was related to the strong southerly PBL winds and the presence of thermally-induced upslope winds. On 20 September, the LLJ in Beijing demonstrated a prominent diurnal variation, which was predominant in the morning and after sunset. The occurrence of the LLJ could enhance the dilution capacity in Beijing to some extent, which favors the dilution of pollutants at a local scale. This study has important implications for better understanding the complexity of PBL structure/process associated with PM2.5 pollution in Beijing.

Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO<sub>2</sub> mole fractions in the US Midwest

Abstract. Atmospheric transport model errors are one of the main contributors to the uncertainty affecting CO2 inverse flux estimates. In this study, we determine the leading causes of transport errors over the US upper Midwest with a large set of simulations generated with the Weather Research and Forecasting (WRF) mesoscale model. The various WRF simulations are performed using different meteorological driver datasets and physical parameterizations including planetary boundary layer (PBL) schemes, land surface models (LSMs), cumulus parameterizations and microphysics parameterizations. All the different model configurations were coupled to CO2 fluxes and lateral boundary conditions from the CarbonTracker inversion system to simulate atmospheric CO2 mole fractions. PBL height, wind speed, wind direction, and atmospheric CO2 mole fractions are compared to observations during a month in the summer of 2008, and statistical analyses were performed to evaluate the impact of both physics parameterizations and meteorological datasets on these variables. All of the physical parameterizations and the meteorological initial and boundary conditions contribute 3 to 4 ppm to the model-to-model variability in daytime PBL CO2 except for the microphysics parameterization which has a smaller contribution. PBL height varies across ensemble members by 300 to 400 m, and this variability is controlled by the same physics parameterizations. Daily PBL CO2 mole fraction errors are correlated with errors in the PBL height. We show that specific model configurations systematically overestimate or underestimate the PBL height averaged across the region with biases closely correlated with the choice of LSM, PBL scheme, and cumulus parameterization (CP). Domain average PBL wind speed is overestimated in nearly every model configuration. Both planetary boundary layer height (PBLH) and PBL wind speed biases show coherent spatial variations across the Midwest, with PBLH overestimated averaged across configurations by 300–400 m in the west, and PBL winds overestimated by about 1 m s−1 on average in the east. We find model configurations with lower biases averaged across the domain, but no single configuration is optimal across the entire region and for all meteorological variables. We conclude that model ensembles that include multiple physics parameterizations and meteorological initial conditions are likely to be necessary to encompass the atmospheric conditions most important to the transport of CO2 in the PBL, but that construction of such an ensemble will be challenging due to ensemble biases that vary across the region.

Linkages between aerosol pollution and planetary boundary layer structure in China

China suffers from high levels of PM2.5 pollution, which is often exacerbated by unfavorable planetary boundary layer (PBL) structures. Partly due to a lack of appropriate observations, the PBL-aerosol linkages in China are not clearly understood. Thus, we investigated these linkages from a national perspective using sounding data collected from 2014 to 2017. Correlation analyses revealed a significant anti-correlation between monthly boundary layer height (BLH) and aerosol pollution that was ubiquitous across China, indicating the important role of the PBL in regulating the seasonal variations of pollution in China. Besides, the day-to-day variations in pollution were modulated by the daily variabilities in the PBL structure. During winter, highly polluted days in most of the Chinese cities studied were associated with a low BLH, strong thermal stability, and weak PBL winds. In the North China Plain and Northeast China, the wintertime heavy pollution was often related to southerly winds and moister PBL. This study has important implications for understanding the crucial role that the PBL plays in modulating aerosol pollution in China.

Measurement of Planetary Boundary Layer Winds with Scanning Doppler Lidar

The accurate measurement of wind profiles in the planetary boundary layer (PBL) is important not only for numerical weather prediction, but also for air quality modeling. Two wind retrieval methods using scanning Doppler light detection and ranging (lidar) measurements were compared and validated with simultaneous radiosonde soundings. A comparison with 17 radiosonde sounding profiles showed that the sine-fitting method was able to retrieve a larger number of data points, but the singular value decomposition method showed significantly smaller bias (0.57 m s−1) and root-mean-square error (1.75 m s−1) with radiosonde soundings. Increasing the averaging time interval of radial velocity for obtaining velocity azimuth display scans to 15 min resulted in better agreement with radiosonde soundings due to the signal averaging effect on noise. Simultaneous measurements from collocated wind Doppler lidar and aerosol Mie-scattering lidar revealed the temporal evolution of PBL winds and the vertical distribution of aerosols within the PBL.

Turbulent Helicity in the Atmospheric Boundary Layer

We consider the assumption postulated by Deusebio and Lindborg (J Fluid Mech 755:654–671, 2014) that the helicity injected into the Ekman boundary layer undergoes a cascade, with preservation of its sign (right- or alternatively left-handedness), which is a signature of the system rotation, from large to small scales, down to the Kolmogorov microscale of turbulence. At the same time, recent direct field measurements of turbulent helicity in the steppe region of southern Russia near Tsimlyansk Reservoir show the opposite sign of helicity from that expected. A possible explanation for this phenomenon may be the joint action of different scales of atmospheric flows within the boundary layer, including the sea-breeze circulation over the test site. In this regard, we consider a superposition of the classic Ekman spiral solution and Prandtl’s jet-like slope-wind profile to describe the planetary boundary-layer wind structure. The latter solution mimics a hydrostatic shallow breeze circulation over a non-uniformly heated surface. A 180°-wide sector on the hodograph plane exists, within which the relative orientation of the Ekman and Prandtl velocity profiles favours the left rotation with height of the resulting wind velocity vector in the lowermost part of the boundary layer. This explains the negative (left-handed) helicity cascade toward small-scale turbulent motions, which agrees with the direct field measurements of turbulent helicity in Tsimlyansk. A simple turbulent relaxation model is proposed that explains the measured positive values of the relatively minor contribution to turbulent helicity from the vertical components of velocity and vorticity.

Impact of Highly Reflective Materials on Meteorology, PM10 and Ozone in Urban Areas: A Modeling Study with WRF-CHIMERE at High Resolution over Milan (Italy)

The Urban Heat Island (UHI) is a well-known phenomenon concerning an increasing percentage of the world’s population due to the growth rates of metropolitan areas. Given the health and economic implications of UHIs, several mitigation techniques are being evaluated and tested. In this study, we consider the use of highly reflective materials for urban surfaces, and we carried out numerical experiments using the Weather Research and Forecasting model coupled with the CHIMERE model in order to investigate the effects of these materials on the meteorology and air quality in the urban area of Milan (Italy). Results show that an increase in albedo from 0.2 to 0.7 for urban roofs, walls and streets leads to a decrease in UHI intensity by up to 2–3 °C and of the planetary boundary layer (PBL) height of about 500 m. However, the difference of PM10 and ozone between urban and surrounding areas increases by a factor of about 2, attributable to the reduction of PBL height and wind speed and to the increased reflected solar radiation that may enhance photochemical production during the daytime. Therefore, if anthropogenic emissions are held at the same levels, the potential benefit to the UHI in terms of thermal discomfort may have negative repercussions on air quality.

Weather Condition Dominates Regional PM2.5 Pollutions in the Eastern Coastal Provinces of China during Winter

China has suffered from severe particulate matter (PM) pollution in recent years. Both pollution areas and levels are increasing gradually. The PM pollution episodes not only occur in the traditional developed areas like the Yangtze River Delta (YRD) and the Beijing-Tianjin-Hebei (BTH) region, but also frequently happen in the eastern coastal provinces (ECPs) of China. Based on hourly fine-PM (PM2.5) concentrations during December 2013 to February 2014 of 55 cities located in the ECPs, we investigated the spatial and temporal variabilities of PM2.5 concentration and the corresponding meteorological conditions during winter. The results generally showed that the winter mean concentrations over all ECPs exceeded China’s national standard of 75 µg m–3, and the most polluted areas with mean concentrations exceeding 150 µg m–3 were in the southwest of Hebei and the west of Shandong Province. The PM2.5 concentrations in February were lower than December in most areas, especially in the YRD, but they were higher over the north of Hebei Province. The spatial distributions and monthly variations were strongly related to weather conditions. Overall, severe PM pollution corresponded with stable weather conditions: small Sea Level Pressure gradient, lower Planetary Boundary Layer (PBL) height and weaker winds. Statistics showed that the changes of the mean PM2.5 concentration over the ECP region lagged behind the variations in the PBL height and wind speeds by about 12–18 h, and the variations in weather conditions could explain about 71% (R2) of the overall changes in PM2.5 concentrations, indicating that regional PM2.5 pollution was dominated by weather conditions in the ECPs. This study gives insight into the PM2.5 pollution in the ECPs of China during winter, which would be helpful to predict and control the PM2.5 pollution for this area in the future.

Assessing the Impact of Surface and Wind Profiler Data on Fog Forecasting Using WRF 3DVAR: An OSSE Study on a Dense Fog Event over North China

AbstractBecause fog is a high-impact weather phenomenon, there has been increased demand for its accurate prediction. Both surface data and wind profiler data possess great potential for improved fog prediction. This study aimed to quantitatively assess the impact of surface and wind profiler data on fog prediction in terms of their spatial resolutions and distributions and also to assess the relative effect of these two types of observations. A dense fog event in northern China that occurred on 20 February 2007 was studied using the Weather Research and Forecasting (WRF) Model’s three-dimensional variational data assimilation (3DVAR) system with observing system simulation experiments (OSSE). The results indicated that the incorporation of surface data has an obvious positive impact on fog forecasts, especially with respect to effective assimilation of automated weather station data. Dense planetary boundary layer (PBL) wind profilers are more beneficial for fog forecasting than troposphere wind profilers, and an even spatial distribution over a large region is superior to a localized distribution. Surface data show greater benefit for fog forecasting than wind profiler data, with a 6.6% increase of skill score as a result of the improvement of near-surface thermal stratification. Moreover, combining both types of data greatly enhances fog predictive skill, with a 13.6% increase in skill score relative to the experiment assimilating only surface data, as a result of better dynamically balanced fields of thermodynamic and kinematic variables within the PBL with the assimilation of PBL wind profiler data.

Classification of summertime synoptic patterns in Beijing and their associations with boundary layer structure affecting aerosol pollution

Abstract. Meteorological conditions within the planetary boundary layer (PBL) are closely governed by large-scale synoptic patterns and play important roles in air quality by directly and indirectly affecting the emission, transport, formation, and deposition of air pollutants. Partly due to the lack of long-term fine-resolution observations of the PBL, the relationships between synoptic patterns, PBL structure, and aerosol pollution in Beijing have not been well understood. This study applied the obliquely rotated principal component analysis in T-mode to classify the summertime synoptic conditions over Beijing using the National Centers for Environmental Prediction reanalysis from 2011 to 2014, and investigated their relationships with PBL structure and aerosol pollution by combining numerical simulations, measurements of surface meteorological variables, fine-resolution soundings, the concentration of particles with diameters less than or equal to 2.5 µm, total cloud cover (CLD), and reanalysis data. Among the seven identified synoptic patterns, three types accounted for 67 % of the total number of cases studied and were associated with heavy aerosol pollution events. These particular synoptic patterns were characterized by high-pressure systems located to the east or southeast of Beijing at the 925 hPa level, which blocked the air flow seaward, and southerly PBL winds that brought in polluted air from the southern industrial zone. The horizontal transport of pollutants induced by the synoptic forcings may be the most important factor affecting the air quality of Beijing in summer. In the vertical dimension, these three synoptic patterns featured a relatively low boundary layer height (BLH) in the afternoon, accompanied by high CLD and southerly cold advection from the seas within the PBL. The high CLD reduced the solar radiation reaching the surface, and suppressed the thermal turbulence, leading to lower BLH. Besides, the numerical sensitive experiments show that cold advection induced by the large-scale synoptic forcing may have cooled the PBL, leading to an increase in near-surface stability and a decrease in the BLH in the afternoon. Moreover, when warm advection appeared simultaneously above the top level of the PBL, the thermal inversion layer capping the PBL may have been strengthened, resulting in the further suppression of PBL and thus the deterioration of aerosol pollution levels. This study has important implications for understanding the crucial roles that meteorological factors (at both synoptic and local scales) play in modulating and forecasting aerosol pollution in Beijing and its surrounding area.

Toward reduced transport errors in a high resolution urban CO2 inversion system

We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO2 emission product Hestia to simulate the atmospheric mole fractions of CO2. For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO2 inverse fluxes estimated using observed CO2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s–1, while the bias remains small in all configurations (< 6 degrees and 0.2 m s–1). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ~10%, with little bias reduction. The inverse results indicate that the spatial distribution of CO2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.

Role of synoptic- and meso-scales on the evolution of the boundary-layer wind profile over a coastal region: the near-coast diurnal acceleration

The contributions of synoptic- and meso-scales to the boundary layer wind profile evolution in a coastal environment are examined. The analysis is based on observations of the wind profile within the first 200 m of the atmosphere continuously recorded during a 10 year period (2001–2010) at the 213-m meteorological tower at the Cabauw Experimental Site for Atmospheric Research (CESAR, The Netherlands). The analysis is supported by a numerical experiment based on the Weather Research and Forecasting (WRF) model performed at high horizontal resolution of 2 km and spanning the complete observational period (10 years). Results indicate that WRF is able to reproduce the inter-annual wind variability but with a tendency to be too geostrophic. At seasonal scales, we find a differentiated behavior between Winter and Summer seasons with the Spring and Autumn transition periods more similar to the Summer and Winter modes, respectively. The winter momentum budget shows a weak intradiurnal variability. The synoptic scale controls the shape of the near surface wind profile that is characterized by weaker and more ageostrophic winds near the surface than at higher altitudes within the planetary boundary layer (PBL) as a result of the frictional turning. In turn, during summer, mesoscale circulations associated with the differential heating of land and sea become important. As a result, the PBL winds show a stronger intradiurnal component that is characterized by an oscillation of the near surface winds around the geostrophic direction with the maximum departure in the afternoon. Although also driven by thermal land-sea differences, this mesoscale component is not associated with the classical concept of a sea-breeze front. It originates from the thermal expansion of the boundary layer over land and primarily differs from the sea-breeze in its propagation speed resulting in a wind rotation far ahead of any coastal front. We refer to it as the near-coast diurnal acceleration (NCDA). The contribution of the NCDA depends on the specific orientation of the coast (NE-SW at CESAR). Our findings stress the importance of evaluating and understanding the performance of mesoscale models with multi-year observational/simulated data sets in order to provide a statistically robust characterization of the limitations of surface layer and boundary-layer parameterizations and thus compensate for the scarceness of upper level wind observations.

Mesoscale modelling study of the interactions between aerosols and PBL meteorology during a haze episode in China Jing–Jin–Ji and its near surrounding region – Part 2: Aerosols' radiative feedback effects

Abstract. Two model experiments, namely a control (CTL) experiment without aerosol–radiation feedbacks and a experiment with online aerosol–radiation (RAD) interactions, were designed to study the radiative feedback on regional radiation budgets, planetary boundary layer (PBL) meteorology and haze formation due to aerosols during haze episodes over Jing–Jin–Ji, China, and its near surroundings (3JNS region of China: Beijing, Tianjin, Hebei, East Shanxi, West Shandong and North Henan) with a two-way atmospheric chemical transport model. The impact of aerosols on solar radiation reaching Earth's surface, outgoing long-wave emission at the top of the atmosphere, air temperature, PBL turbulence diffusion, PBL height, wind speeds, air pressure pattern and PM2.5 has been studied focusing on a haze episode during the period from 7 to 11 July 2008. The results show that the mean solar radiation flux that reaches the ground decreases by about 15% in 3JNS and 20 to 25%in the region with the highest aerosol optical depth during the haze episode. The fact that aerosol cools the PBL atmosphere but warms the atmosphere above it leads to a more stable atmospheric stratification over the region, which causes a decrease in turbulence diffusion of about 52% and a decrease in the PBL height of about 33%. This consequently forms a positive feedback on the particle concentration within the PBL and the surface as well as the haze formation. Additionally, aerosol direct radiative forcing (DRF) increases PBL wind speed by about 9% and weakens the subtropical high by about 14 hPa, which aids the collapse of haze pollution and results in a negative feedback to the haze episode. The synthetic impacts from the two opposite feedbacks result in about a 14% increase in surface PM2.5. However, the persistence time of both high PM2.5 and haze pollution is not affected by the aerosol DRF. On the contrary over offshore China, aerosols heat the PBL atmosphere and cause unstable atmospheric stratification, but the impact and its feedback on the planetary boundary layer height, turbulence diffusion and wind is weak, with the exception of the evident impacts on the subtropical high.