Atmospheric Boundary Layer Research Articles

Exchange between the atmospheric boundary layer and free troposphere over the Indian monsoon region

Exchange between the atmospheric boundary layer and free troposphere over the Indian monsoon region

Characterizing Near-surface Moisture Increase During the Clear-sky Afternoon-to-Evening Transition Using a Single Column Model

Abstract The afternoon-to-evening transition is the period when the atmospheric boundary layer transitions from convective to stable conditions. One noticeable feature during this transition period is the rapid increase in water vapor concentration near the surface. However, the mechanism behind the increase in water vapor remains poorly understood. This study investigated the processes contributing to the water vapor increase and the impacts of the land cover and horizontal advection on the water vapor increase using a single-column model for the clear-sky condition. Numerical experiments were conducted on three cases at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. Evapotranspiration was found to be the main moisture source to the water vapor increase and that change of the near-surface vertical temperature gradient from negative to positive is the trigger for this increase during the afternoon-to-evening transition. This is because the near-surface turbulence divergence term decreases due to the change in the buoyancy profile caused by vertical temperature gradient change. The impact of horizontal advection on water vapor varies, and it can either lead to an increase or decrease in water vapor, depending on the spatial horizontal water vapor gradient. This study also found that land cover can influence the timing of the water vapor increase since different land covers may have different Bowen ratios. Water vapor increases earlier under conditions with smaller Bowen ratios compared to those with larger values.

Preface: 4th International Conference on Media, Art, Management and Educational Engineering (MAMEE 2025)

We are so delighted to announce that 2025 4th International Conference on Media, Art, Management and Educational Engineering (MAMEE 2025) was successfully held in Vienna, Austria during March 29-30, 2025. The conference aimed to provide a platform for interdisciplinary cooperation and communication for young scholars to lighten academic atmosphere, encourage innovation, create cooperation opportunities, and boost young scholars' growth. About 40 participants from academic, high-education institutes and other organizations took part in MAMEE 2025. The conference model was divided into two sessions, including oral presentations and keynote speeches. In the first part, some scholars, whose submissions were selected as the excellent papers, were given 10-15 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-40 minutes to hold their speeches. It is expected that MAMEE 2025 can provide a free academic atmosphere to encourage our distinguished guests to share their views, ignite new ways of thinking and harvest new ideas. This international academic conference aims to further promote exchanges and cooperation, to play an active role in improving academic standing and international influence in the areas of mass media, new media, art design, public art, management system, human resource management, distance education, and educational engineering as well as shortening the gap with the top subject in the world. MAMEE Organizing Committee Vienna, Austria

Modeling the Atmospheric CO2 Concentration in the Beijing Region and Assessing the Impacts of Fossil Fuel Emissions

Reducing anthropogenic fossil fuel CO2 (FFCO2) emissions in urban areas is key to mitigating climate change. To better understand the spatial characteristics and temporal variations in urban CO2 levels in the Beijing (BJ) region, we conducted a long-term CO2 simulation study by using the Weather Research and Forecasting WRF-Chem model and CO2 observation data. To assess the model performance, three representative sites with high-precision CO2 observation data were chosen in this study: the rural regional background Shangdianzi (SDZ) site, the suburban Xianghe (XH) site, and the urban BJ site. The simulation results generally captured the observed variations at these three sites, but the model performed much better at the SDZ and XH sites, with mean biases of −0.7 ppm and −2.3 ppm, respectively, and RMSE of 12.3 ppm and 21.4 ppm, respectively. The diurnal variations in the model results agreed well with those in the observed CO2 concentrations at the SDZ and XH sites during all seasons. In the meanwhile, the diurnal variations in the modeled FFCO2 were similar to those in the CO2 observation with a positive bias at the BJ site, which may have been caused by higher emissions especially in winter. Moreover, both the modeled FFCO2 and biospheric CO2 (BIOCO2) have positive correlations with the observed CO2 concentration, whereas the planetary boundary layer height (PBLH) and observed CO2 concentration exhibited negative correlations at all sites. In addition, the contributions of FFCO2 and BIOCO2 to CO2 varies depending on the seasons and the location of sites.

Direct numerical simulations on transport and deposition of charged inertial particles in turbulent channel flow

From particle lifting in atmospheric boundary layers to dust ingestion in jet engines, the transport and deposition of inertial particles in wall-bounded turbulent flows are prevalent in both nature and industry. Due to triboelectrification during collisions, solid particles often acquire significant charges. However, the impacts of the resulting electrostatic interaction on the particle dynamics remain less understood. In this study, we present four-way coupled simulations to investigate the deposition of charged particles onto a grounded metal substrate through a fully developed turbulent boundary layer. Our numerical method tracks the dynamics of individual particles under the influence of turbulence, electrostatic forces and collisions. We first report a more pronounced near-wall accumulation and an increased wall-normal particle velocity due to particle charging. In addition, contrary to predictions from the classic Eulerian model, the wall-normal transport rate of inertial particles is significantly enhanced by electrostatic forces. A statistical approach is then applied to quantify the contributions from turbophoresis, biased sampling and electrostatic forces. For charged particles, a sharper gradient in wall-normal particle fluctuation velocity is observed, which substantially enhances turbophoresis and serves as the primary driving force of near-wall particle accumulation. Furthermore, charged particles are found to sample upward-moving fluids less frequently than neutral particles, thereby weakening the biased-sampling effect that typically pushes particles away from the wall. Finally, the wall-normal electric field is shown to depend on the competition between particle–wall and particle–particle electrostatic interactions, which helps to identify the dominant electrostatic force across a wide range of scenarios.

Characteristics of Eddy Dissipation Rates in Atmosphere Boundary Layer Using Doppler Lidar

The eddy dissipation rate (EDR, or turbulence dissipation rate) is a crucial parameter in the study of the atmospheric boundary layer (ABL). However, the existing Doppler lidar-based estimates of EDR seldom offer long-term comparisons that span the entire ABL. Building upon prior research utilizing Doppler lidar wind-field data, we optimized the EDR retrieval algorithm using a genetic adaptive approach. The newly developed algorithm demonstrates enhanced accuracy in EDR estimation. The daily evolution of EDR reveals a distinct diurnal pattern in its variation. A detailed four consecutive days study of turbulence generated via low-level jets (LLJs) indicated that EDR driven by heat flux (~10−2 m2/s3) is significantly stronger than that produced through wind shear (~10−3 m2/s3). Subsequently, we examined seasonal variations in EDR at different mixing layer heights (MLH, Zi): elevated EDR values in summer (~7 × 10−3 m2/s3 at 0.1Zi) contrasted with reduced levels in winter (~6 × 10−4 m2/s3 at 0.1Zi). In the early morning, EDR decreases with height for 1 magnitude, while in later stages, it remains relatively stable within 0.1 order of magnitude across 0.1Zi to 0.9Zi. Notably, the EDR during DJF exceeds that of MAM and SON in the afternoon. This suggests that ML turbulence is not solely dependent on surface fluxes (SHF + LHF) but may also be influenced by MLH. A lower MLH (smaller volume), even with reduced surface fluxes, could potentially result in a stronger EDR. Finally, we compared the evolution of the EDR and MLH in the boundary layer using Doppler lidar data from ARM sites and the PBL (Planetary Boundary Layer) Moving Active Profiling System (PBLMAPS) Airborne Doppler Lidar (ADL). The results show that the vertical wind data exhibit strong consistency (R = 0.96) when the ADL is positioned near ARM Southern Great Plains (SGP) sites C1 or E37. The ADL’s mobility and flexibility provide significant advantages for future field experiments, particularly in challenging environments such as mountainous or complex terrains. This study not only highlights the potential of utilizing Doppler lidar alone for EDR calculations but also extensively explores the development patterns of EDR within the ABL.

The Relative Role of Different Mechanisms of Northward‐Propagating Intraseasonal Oscillation Over the Indian Ocean, the South China Sea, and the Western North Pacific

ABSTRACTPrevious studies have proposed several well‐recognised mechanisms for the northward‐propagating boreal summer intraseasonal oscillations (BSISOs), while their relative roles tend to be qualitatively analysed. In the present study, based on the planetary boundary layer (PBL) moisture mode theory and the associated moisture budget equation, we quantitatively calculated the contribution of each mechanism, including PBL moisture advection, vertical easterly wind shear, vorticity advection, and external sea surface temperature (SST) forcing, to the northward propagation of BSISO by using the Japanese 55‐year reanalysis (JRA‐55). The results show that the dominant mechanisms are the vertical easterly wind shear effect (51.75%–56.1% of the positive contribution) and the SST forcing (18.89%–23.6%) over the Indian Ocean, the vertical easterly wind shear effect (40.72%–51.87%) and the vorticity advection effect (24.65%–31.4%) over the South China Sea, and the vorticity advection effect (56.37%–65.67%) and the air‐sea interaction (19.92%–22.2%) over the western North Pacific, which favour the PBL moisture asymmetry, and then the northward‐propagating BSISOs. Moisture advection is a supplementary mechanism, while the contributions of vertical moisture advection and nonlinear effects can be ignored in all three regions. These results help us to further understand the northward propagation mechanism of ISO in the Asia‐Pacific monsoon region, provide a clear reference for diagnosing persistent extreme weather associated with ISO, and provide quantitative criteria for evaluating tropical ISO propagation in numerical models.

Spatiotemporal Analysis of Air Pollution and Climate Change Effects on Urban Green Spaces in Bucharest Metropolis

Being an essential issue in global climate warming, the response of urban green spaces to air pollution and climate variability because of rapid urbanization has become an increasing concern at both the local and global levels. This study explored the response of urban vegetation to air pollution and climate variability in the Bucharest metropolis in Romania from a spatiotemporal perspective during 2000–2024, with a focus on the 2020–2024 period. Through the synergy of time series in situ air pollution and climate data, and derived vegetation biophysical variables from MODIS Terra/Aqua satellite data, this study applied statistical regression, correlation, and linear trend analysis to assess linear relationships between variables and their pairwise associations. Green spaces were measured with the MODIS normalized difference vegetation index (NDVI), leaf area index (LAI), photosynthetically active radiation (FPAR), evapotranspiration (ET), and net primary production (NPP), which capture the complex characteristics of urban vegetation systems (gardens, street trees, parks, and forests), periurban forests, and agricultural areas. For both the Bucharest center (6.5 km × 6.5 km) and metropolitan (40.5 km × 40.5 km) test areas, during the five-year investigated period, this study found negative correlations of the NDVI with ground-level concentrations of particulate matter in two size fractions, PM2.5 (city center r = −0.29; p < 0.01, and metropolitan r = −0.39; p < 0.01) and PM10 (city center r = −0.58; p < 0.01, and metropolitan r = −0.56; p < 0.01), as well as between the NDVI and gaseous air pollutants (nitrogen dioxide—NO2, sulfur dioxide—SO2, and carbon monoxide—CO. Also, negative correlations between NDVI and climate parameters, air relative humidity (RH), and land surface albedo (LSA) were observed. These results show the potential of urban green to improve air quality through air pollutant deposition, retention, and alteration of vegetation health, particularly during dry seasons and hot summers. For the same period of analysis, positive correlations between the NDVI and solar surface irradiance (SI) and planetary boundary layer height (PBL) were recorded. Because of the summer season’s (June–August) increase in ground-level ozone, significant negative correlations with the NDVI (r = −0.51, p < 0.01) were found for Bucharest city center and (r = −76; p < 0.01) for the metropolitan area, which may explain the degraded or devitalized vegetation under high ozone levels. Also, during hot summer seasons in the 2020–2024 period, this research reported negative correlations between air temperature at 2 m height (TA) and the NDVI for both the Bucharest city center (r = −0.84; p < 0.01) and metropolitan scale (r = −0.90; p < 0.01), as well as negative correlations between the land surface temperature (LST) and the NDVI for Bucharest (city center r = −0.29; p< 0.01) and the metropolitan area (r = −0.68, p < 0.01). During summer seasons, positive correlations between ET and climate parameters TA (r = 0.91; p < 0.01), SI (r = 0.91; p < 0.01), relative humidity RH (r = 0.65; p < 0.01), and NDVI (r = 0.83; p < 0.01) are associated with the cooling effects of urban vegetation, showing that a higher vegetation density is associated with lower air and land surface temperatures. The negative correlation between ET and LST (r = −0.92; p < 0.01) explains the imprint of evapotranspiration in the diurnal variations of LST in contrast with TA. The decreasing trend of NPP over 24 years highlighted the feedback response of vegetation to air pollution and climate warming. For future green cities, the results of this study contribute to the development of advanced strategies for urban vegetation protection and better mitigation of air quality under an increased frequency of extreme climate events.

Toward a Global Planetary Boundary Layer Observing System: A Summary

Abstract A global Planetary Boundary Layer (PBL) observing system is urgently needed to address fundamental PBL science questions and societal applications related to climate, weather and air quality. Such a PBL observing system should optimally combine emerging yet technically viable space-based observations of the PBL thermodynamic structure with complementary surface-based and suborbital assets, while taking advantage of, and helping improve, climate and weather models as well as data assimilation systems. The Earth science community has expressed great interest in improving the characterization of the atmospheric PBL in the recent National Academies of Sciences, Engineering and Medicine (NASEM) 2017-2027 decadal survey for Earth Science and Applications from Space (ESAS). Specifically, higher spatial and temporal resolution observations of PBL temperature and water vapor profiles, and of PBL height, were selected as priorities by the decadal survey, which recommended a PBL mission in its incubation class. In response, NASA established the decadal survey incubation program and a PBL study team focused on prioritizing PBL science and technology that would require advancement and development prior to implementation. In this paper we summarize the key findings of the NASA PBL study team report.

Short-Term Energy and Meteorological Impacts on Thanksgiving CO2 in Salt Lake City

Abstract Long-term, high-frequency atmospheric CO2 measurements at multiple sites in the Salt Lake City (SLC), Utah, reveal that annual and monthly CO2 variability aligns with a priori estimates of emissions from anthropogenic and biological sources. In this study, we investigate whether short-term fluctuations in anthropogenic emissions, as captured in the Vulcan3 dataset for the United States, can be detected in atmospheric CO2 observations. Specifically, we focus on Thanksgiving holidays, when traffic and energy usage patterns differ from the rest of November. Onroad CO2 emissions exhibit a double peak during weekday morning and evening rush hours but remain relatively low on weekends and Thanksgiving. Interestingly, CO2 mole fractions during Thanksgiving were higher than the rest of November at all SLC monitoring sites, particularly from 2008 to 2013. This increase is partially attributed to elevated energy-related emissions — especially residential sources — and meteorological factors such as weak wind speeds, cold temperature, and a low planetary boundary layer height (PBLH).

 While CO₂ emissions and mole fraction patterns align over time, notable spatial differences exist. For instance, the near-highway site in Murray shows the highest CO₂ mole fractions despite low local emissions, suggesting pollution transport via highways and wind advection. Random Forest model-based SHapley Additive exPlanations (SHAP) analysis reveals that onroad emissions dominate CO2 contributions on weekdays and weekends, while energy-related emissions play a larger role during Thanksgiving, alongside meteorological drivers such as wind speed and PBLH. Across six urban cities, CO2 emissions display a consistent pattern: residential and commercial (onroad) emissions peak during Thanksgiving (weekday) with substantial (minimal) year-to-year variability. These findings highlight that urban CO₂ variability is driven by the combined influence of emissions and meteorology, underscoring the need for integrated mitigation strategies. Additionally, multi-site measurements are essential for accurate source attribution and the development of effective policy interventions. 

A numerical study of the agricultural irrigation effects on summer soil moisture and near-surface meteorology in California’s Central Valley

Abstract California's Central Valley (CV) is one of the most productive agricultural regions in the world, relying significantly on irrigation. This study explores the impacts of agricultural irrigation on soil moisture and near-surface meteorology in the CV. Employing the Weather Research and Forecasting (WRF) model with a modified irrigation module, the WRF-irrigation simulation (WIR3D) reproduces observed humid surface soil moisture in the CV, as identified by satellite data. Without irrigation effects (WoIR), the model presents a dry surface soil moisture bias, with an average value below 0.05 m3/m3 over the CV. A comparison with surface-station observations reveals that the mean bias of the simulated 2-m dew point temperature is −1.62 °C in WoIR but only 0.05 °C in WIR3D. The 2-m temperature change by irrigation could be cooling or warming. The complexity of the temperature change arises from the combination of evapotranspirative cooling, soil heat flux, and radiative feedback, with differences between daytime evapotranspirative cooling and nighttime greenhouse gas effects. Compared with derived planetary boundary layer height (PBLH) from ceilometer observations, irrigation reduces simulated maximum positive PBLH bias by approximately 580 m (53%), resulting in a daily wind speed decrease of 0.5 m s−1. In addition, this study examines the irrigation spatial heterogeneity effect, and the results show variations of approximately 30% and 40% differences in PBLH and other near-surface variables between incorporating a county-level versus uniform irrigation rate over the CV. These findings underscore the importance of better integrating irrigation practices to improve weather forecasting in the CV.

On the drivers of ice nucleating particle diurnal variability in Eastern Mediterranean clouds

We report the drivers of spatiotemporal variability of ice nucleating particles (INPs) for mixed-phase orographic clouds (~−25 °C) in the Eastern Mediterranean. In the planetary boundary layer, pronounced INP diurnal periodicity is observed, which is mainly driven by biological (and to a lesser extent, dust) particles but not aerosols from biomass burning. The comparison of size-resolved and fluorescence-discriminated aerosol particle properties with INPs reveals the primary role of fluorescent bioaerosol. The presence of Saharan dust increases INPs during nighttime more than daytime, because of lower boundary layer height during nighttime which decreases the contribution of aerosols (including bioaerosols) from the boundary layer. INP diurnal periodicity is absent in the free troposphere, although levels are driven by the availability of bioaerosol and dust particles. Given the effective ice nucleation ability of bioaerosols and subsequent effects from ice multiplication at warm temperatures, the lack of such cycles in models points to important and overlooked drivers of cloud formation and precipitation in mountainous regions.

Quantifying the thermodynamic impacts on the atmospheric boundary layer due to the sea breeze in the coastal Houston region

Abstract The atmospheric boundary layer (ABL) is unique in coastal regions because of kinematic and thermodynamic influences from continental and marine environments. Sea breeze (SB) circulations act to equilibrate the land-sea temperature gradient through advecting marine air onshore. The strength of the SB varies in terms of stability, temperature and moisture advection, and influences air quality and weather forecasts. The TRacking Aerosol Convection interactions ExpeRiment (TRACER) collected a wealth of data on coastal boundary layer evolution, including observations from uncrewed aerial systems (UAS). Vertical profiles of temperature, humidity, and winds were collected by the OU CopterSonde UAS from June to September in the coastal region of Houston. These profiles offer 5 m vertical resolution, on average, every 30 min through diurnal transitions, SB events, and nearby deep convection. During the campaign, CopterSonde observations were gathered through 17 SB events, 6 of which led to convection initiation. The UAS data can resolve the thermodynamic evolution and interactions between the SB and the pre-existing convective boundary layer. Results show large variability across observed SBs and their impacts on temperature and moisture. The intensity of thermodynamic changes depends on the time of sea breeze passage and influence from the Galveston Bay Breeze, a secondary marine circulation commonly observed in this region. In quantifying the spectrum of SB impacts, equivalent potential temperature (θe) is used to contextualize its role in convection initiation and evolution. While all SBs tend to increase θe from moisture advection, the rate and timing of the θe rise can distinguish convective from non-convective cases.

Sea Breeze-Driven Variations in Planetary Boundary Layer Height over Barrow: Insights from Meteorological and Lidar Observations

The planetary boundary layer height (PBLH) in coastal Arctic regions is influenced by sea breeze circulation. However, the specific mechanisms through which sea breeze affects PBLH evolution remain insufficiently explored. This study uses meteorological data, micro-pulse lidar (MPL) data, and sounding profiles from 2014 to 2021 to investigate the annual and polar day PBLH evolution driven by sea breezes in the Barrow region of Alaska, as well as the specific mechanisms. The results show that sea breeze events significantly suppress PBLH, especially during the polar day, when prolonged solar radiation intensifies the thermal contrast between land and ocean. The cold, moist sea breeze stabilizes the atmospheric conditions, reducing net radiation and sensible heat flux. All these factors inhibit turbulent mixing and PBLH development. Lidar and sounding analyses further reveal that PBLH is lower during sea breeze events compared to non-sea-breeze conditions, with the peak of its probability density distribution occurring at a lower PBLH range. The variable importance in projection (VIP) analysis identifies relative humidity (VIP = 1.95) and temperature (VIP = 1.1) as the primary factors controlling PBLH, highlighting the influence of atmospheric stability in regulating PBLH. These findings emphasize the crucial role of sea breeze in modulating PBL dynamics in the Arctic, with significant implications for improving climate models and studies on pollutant dispersion in polar regions.

Characteristics of aerosols and planetary boundary layer dynamics during biomass burning season

Abstract The northeastern region of Pakistan (NEP) has experienced increased haze episodes over the past decade, primarily due to enhanced biomass burning activities during the post-monsoon season. Economic growth, urbanization and industrial development also controbuted to high pollutants levels that leads to decline in air quality and visibility. These elevated pollution levels over NEP (69–75.5°E, 27.4–34°N) are influenced by both meteorological conditions and anthropogenic activities. This study investigates aerosol concentrations before, during, and after the haze episode during November 2021 using model simulations and remote sensing data. The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), along with satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), are used for validation and analysis of this haze episode. The results illustrate the key contributors to this haze event and showed the there is significant increases in aerosol components such as sulfate, black carbon, organic carbon, dust and aerosol optical depth (AOD). The planetary boundary layer (PBL) height, measured with Ceilometer LIDAR, showed decreasing trend in height from October to December that support aerosol accumulation near the surface during the the month of November. This month is also biomass burning, crop residue burning, season in the region. These haze episodes also impacts the atmospheric visibility that dropped below 2 km in November. These findings provide key insights into the complex interactions between meteorology, emissions, and haze formation in NEP region, and will provide policy makers to design effective mittigation strategies.

Power production and area usage of offshore wind and the relationship with available energy in the atmosphere.

This paper presents an analysis of the area dependency of power and capacity density of wind farms, based on derivations of the available energy in the atmosphere and data on the power production of existing wind farms in the North Sea. The amount of available energy is determined by the mechanical energy budget of the atmospheric boundary layer and is found to be a function of C/A, where C is the circumference and A is the area of the wind farm. The actual power production of 31 wind farms is analyzed, and the power production in 23 of the largest wind farms follows the same functional form as the available energy, indicating that the power production in these wind farms is limited by the available energy. The power density in the North Sea, as a function of the area usage, is found by fitting the actual power density of existing wind farms to the expression for available energy in the atmospheric boundary layer. Wind farms below 10 km2 can produce more than 6 Wm-2, but the power density rapidly decreases with area. Wind farms with an area of about 1000 km2 will produce [Formula: see text] 1 Wm-2, and power densities will asymptotically approach a value of 0.78 [Formula: see text] 0.58 Wm-2 for increasing wind farm area. Since atmospheric energy input is the limiting factor for power production, an atmospheric energy budget is vital for a reliable estimate of offshore wind power potential.

Improving Planetary Boundary Layer Height Estimation From Airborne Lidar Instruments

AbstractThe height of the planetary boundary layer (PBLH) influences processes such as pollutant distributions, convection, and cloud formation within the troposphere. Aerosol observables play a critical role in deriving the mixed layer height (MLH) using retrieval techniques like the Haar wavelet covariance transform (WCT), which employs gradients in aerosol backscatter to estimate MLH. Currently, backscatter‐only approaches struggle with identifying very shallow stable boundary layers, distinguishing PBL from lofted residual or other aerosol layers, and profiles with very low aerosol loading. Here, we reflect on the WCT method's performance and evaluate different approaches to improve PBLH estimations. We aggregate lidar observables from recent NASA airborne field campaigns and compute MLHs based on the WCT method. Machine learning (ML) approaches are explored to produce PBLH estimates by training lidar information on thermodynamically derived PBLHs over marine and land settings. A linear model is found suitable for producing PBLH estimates in marine settings (improving mean bias by 71 m), while an ensemble tree method proves more suitable for PBLH types over land, as indicated by improved biases (13 m mean bias), errors (179 m mean error and 391 m RMSE), and correlations (+0.3) for the models explored. The algorithms are additionally tested on “unseen” data to gauge differences between MLH and PBLH estimates produced from each of the models. The PBLH estimates, composed of information from lidar and thermodynamic profiles, further support the use of ML for an automated method of PBLH prediction. Overall, these improved predictions will help evaluate models and deepen our understanding of PBL‐aerosol interactions.

Impacts of Vertical Resolution and Diurnally Varying Background Error Covariance on FY-4A/AGRI Data Assimilation over Land

Abstract This study aims at improving the assimilation of Fengyun-4A (FY-4A)/Advanced Geostationary Radiation Imager (AGRI) clear-sky surface-sensitive brightness temperature over land using the Weather Research and Forecasting and the Gridpoint Statistical Interpolation three-dimensional variational data assimilation for summer convective cases over eastern China. We investigated the influences of the planetary boundary layer on the assimilation of FY-4A/AGRI surface-sensitive channels, focusing on model low-level vertical resolution and diurnal variation of background error covariance. The vertical levels are increased from 48 to 91 by adding more near-surface levels. First, stronger low-level vertical background error correlations of humidity and temperature are found during daytime than during nighttime. A total of five numerical experiments are then conducted to examine the impacts of FY-4A/AGRI assimilation with two vertical resolutions. The experiments WV48 and WV91 assimilate only the water vapor channels, and ALL48, ALL91, and ALL91M assimilate the water vapor and surface-sensitive channels. The diurnally varying background error covariance, which is estimated at 3-h intervals, is incorporated into ALL91M. The 6-h cycling data assimilation at 1-h interval prior to convection initiation is conducted for each of the seven cases. Overall, a comparison between WV48/WV91 and ALL48/ALL91M revealed a consistent positive impact of AGRI brightness temperature assimilation over land on convective precipitation forecasts. The added values of assimilating AGRI surface-sensitive channels are more pronounced by using the finer vertical resolution due to low-level humidity enhancements that are related to the rise of the planetary boundary layer. With the diurnally varying background error covariance, ALL91M outperformed ALL91 because of improved low-level analyzed structures that are associated with proper low-level vertical error correlations of humidity and thermal variables.

Surface Flux Homogenization and its Impacts on Convection Across CONUS

Abstract In large scale Earth System Models (ESMs) used to study climate processes, surface heterogeneity that is sub-grid to the larger atmospheric grid is often represented by a number of land tiles, effectively providing a higher resolution land surface to a coarser resolution overlying atmosphere. ESMs, however, average the surface fluxes and other surface characteristics before they are communicated to the atmosphere, ignoring the affect that this variability can have on the atmosphere. In this study, we examine the impact of this flux averaging through 257 2-day summer WRF simulations over the Continental United States (CONUS) at 3km resolution, including runs where the surface fluxes and temperature are homogenized at 60 km prior to communication to the overlying atmosphere. Results show large increases (200mm and higher) in precipitation in moisture limited regions of CONUS, a persistent increase in precipitation bias when compared to observations, and a near universal increase in evaporative fraction. Changes are most significant where moist areas (i.e. water bodies) are averaged with dry areas as the feedback between atmospheric moisture concentrations and the land are weakened when that moisture flux is more spatially distributed through homogenization. Results also show a significant decline in mesoscale flow activity within the atmospheric boundary layer, which in energy limited regions may cause the simulated decreases in precipitation due to less frequent convective initiation. Overall, results indicate that flux averaging applied in large scale models can have unintended consequences by neglecting the heterogeneous imprint of the surface on the atmosphere.

Evaluating Stochastic Parameter Perturbations in Convection-Permitting Ensemble Forecasts of Lake-Effect Snow

Abstract Lake-effect snowstorms can produce large snowfall accumulations that are challenging to simulate and forecast. One source of forecast uncertainty for these events is the uncertain parameterization of sub-grid processes, such as planetary boundary layer and surface layer turbulence (PBL/SL) and cloud and precipitation microphysics (MP), in numerical weather prediction models. One way to quantify this uncertainty is to design ensembles that use stochastic parameter perturbations (SPP) to vary individual uncertain parameters within physics schemes. This research aims to evaluate and improve the utility of SPP for convection-permitting ensemble forecasts of lake-effect snow, with a focus on PBL/SL and MP parameterizations. We focus on a snowfall event observed during the Ontario Winter Lake-effect Systems (OWLeS) field campaign, which is simulated with 1-km horizontal grid spacing using the Weather Research and Forecasting model. A suite of 20-member ensemble simulations are run, including ensembles where SPP is applied only to PBL/SL or MP, where SPP applied to multiple schemes concurrently, where perturbations to initial and boundary conditions (ICs/BCs) are applied instead of SPP, and where SPP and IC/BC perturbations are applied together. SPP perturbations produce substantial spread in simulated precipitation, despite having only modest impacts on the synoptic-scale flow. They accomplish this by modulating lake-atmosphere fluxes, boundary layer characteristics, precipitation growth processes, and hydrometeor terminal fall speeds. The spread and skill of simulated precipitation from an ensemble using SPP alone is comparable to that from ensemble that uses IC/BC perturbations alone. The physical pathways whereby SPP perturbations generate spread are examined and discussed.