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Cold pools formed by precipitating convective clouds are an important source of mesoscale temperature variability. However, their sub‐mesoscale (100 m–10 km) structure has not been quantified, impeding validation of numerical models and understanding of their atmospheric and societal impacts. We assess temperature variability in observed and simulated cold pools using variograms calculated from dense network observations collected during a field experiment and in high‐resolution case‐study and idealized simulations. The temperature variance in cold pools is enhanced for spatial scales between ∼5 and 15 km compared to pre‐cold pool conditions, but the magnitude varies strongly with cold pool evolution and environment. Simulations capture the overall cold pool variogram shape well but underestimate the magnitude of the variability, irrespective of model resolution. Temperature variograms outside of cold pool periods are represented by the range of simulations evaluated here, suggesting that models misrepresent cold pool formation and/or dissipation processes. Plain Language Summary: Cold pools are cool gusty winds beneath thunderstorms that are formed by cooling from rainfall. They have many important impacts in the atmosphere and on society but are difficult to properly simulate in numerical weather models. The variability in cold pool temperature is an understudied feature of cold pools but which is important to represent in numerical models. In this study, we examine cold pool temperature variability from a dense network of surface weather station observations collected during a field campaign, and we compare those observations to numerical simulations of cold pools in a range of environments. We find that cold pools enhance temperature variability for distances greater than ∼5 km but suppress variability on smaller distances, and that the magnitude of cold pool temperature variability is strongly dependent on the environment and cold pool lifetime. We also show that numerical models, even at very high resolutions, are not able to properly simulate the magnitude of cold pool temperature variability. We highlight areas for improvement in numerical models that may help to improve simulations of cold pool variability, including land‐atmosphere interactions, turbulence, and conversion processes between water vapor and condensed water in storms. Key Points: Cold pool impacts on sub‐mesoscale temperature variability are quantified using variograms derived from observations and simulationsCold pools enhance temperature variability on scales between 5 and 15 km, but the magnitude varies strongly with lifetime and environmentHigh‐resolution case‐study and idealized simulations underestimate the magnitude of cold pool variability, irrespective of resolution [ABSTRACT FROM AUTHOR]

Abstract Cold pools formed by precipitating convective clouds are an important source of mesoscale temperature variability. However, their sub‐mesoscale (100 m–10 km) structure has not been quantified, impeding validation of numerical models and understanding of their atmospheric and societal impacts. We assess temperature variability in observed and simulated cold pools using variograms calculated from dense network observations collected during a field experiment and in high‐resolution case‐study and idealized simulations. The temperature variance in cold pools is enhanced for spatial scales between ∼5 and 15 km compared to pre‐cold pool conditions, but the magnitude varies strongly with cold pool evolution and environment. Simulations capture the overall cold pool variogram shape well but underestimate the magnitude of the variability, irrespective of model resolution. Temperature variograms outside of cold pool periods are represented by the range of simulations evaluated here, suggesting that models misrepresent cold pool formation and/or dissipation processes.

Seven years of data collected at the Atmospheric Radiation Measurement's Eastern North Atlantic (ENA) site are analyzed to understand the controls of Cloud Condensation Nuclei (CCN) concentrations in the region. Day‐night differences in the aerosol data as segregated by wind direction demonstrate the aerosol observations to be impacted by local emissions when the wind direction (wdir) is between 90° and 310° (measured clockwise from the North where air is coming from). Data collected during marine conditions (wdir <90° or wdir >310°) show the CCN concentrations to be higher in the summer months as compared to the winter months. CCN budget analysis revealed advection and precipitation scavenging being primarily responsible for modulating the CCN concentrations at the site on monthly timescales, with rain rates driving the precipitation scavenging term. High (greater than 75th percentile) and low (lower than 25th percentile) CCN events were identified for each month to characterize the sub‐monthly variability of CCN concentrations. Low CCN events had thicker clouds, stronger rain rates, and lower reanalysis reported free‐tropospheric aerosol pseudo number concentration at the ENA site as compared to the high CCN events. Analysis of satellite data of air‐parcels 48 hr prior to their arrival at the ENA site demonstrated the air parcels during low CCN events to encounter higher cloudiness, stronger rain rates, and higher cloud top heights as compared to the high CCN events. The results presented herein provide key constraints for model evaluation studies and climatological studies conducted at the ENA site. Plain Language Summary: Aerosols on which water vapor condenses to form cloud droplets are commonly referred to as cloud condensation nuclei (CCN). The mechanisms responsible for changes in CCN concentrations over the open oceans are not fully known. The variability in the CCN concentrations over the Eastern North Atlantic region is examined. Analysis of day‐night differences in aerosol properties with wind direction show the aerosol measurements to be affected by human activity during certain wind conditions. Seven years of data collected when conditions were not impacted by human activity show higher CCN concentrations during summer months as compared to the winter month, and substantial variability within each month. CCN can be locally produced through wave‐breaking, transported to the location, and subsequently removed from the atmosphere as they transition into cloud or rain drops. Causes of seasonal and sub‐monthly changes in these CCN concentrations are examined. The analysis show transport of CCN to the site along with removal due to cloud processing to be the primary mechanisms for causing seasonal changes. In addition, air associated with low CCN concentration conditions at the site encountered higher cloudiness and rain prior to its arrival at the site as compared to that with high CCN concentrations. Key Points: Data suggest aerosol measurements at the Atmospheric Radiation Measurement Eastern North Atlantic site are affected by local emissions when the wind direction is between 90° and 310°Lower ambient wintertime Cloud Condensation Nuclei (CCN) concentrations compared to summer are primarily driven by advection and precipitationCCN variability at sub‐monthly timescales is driven by clouds and precipitation upstream of the site [ABSTRACT FROM AUTHOR]

Global reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of O(10) $\mathcal{O}(10)$ km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the "Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics," or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions. Plain Language Summary: Modern global weather models are accurate in predicting atmospheric processes at scales of around 10 km or larger, but are less good at predicting smaller scale processes, like for example, the interaction between solar radiation, individual clouds, and the resulting clouds shadows that are cast onto the land surface. High spatio‐temporal resolution research models are able to capture these smaller scale processes, but require a coupling to a weather model to account for the day‐to‐day variability in our weather. In this paper, we present a framework to couple large to small scale models, and demonstrate both the benefits and challenges of using this coupled model setup. The coupled setup excels in capturing the aforementioned high frequency interactions between small clouds and surface solar radiation. However, the chaotic nature of broken to overcast clouds is proven difficult to represent. The coupled model setup is published as open‐source code, and is therefore freely available to the research community. Key Points: We developed an open‐source Python package named (LS)2D, designed to downscale the ERA5 reanalysis with turbulence and cloud‐resolving large‐eddy simulation (LESs)One month long experiments with (LS)2D and MicroHH over the Netherlands demonstrate both the skill and limitations of the coupled setupCapturing high‐frequency interactions between clouds and surface solar irradiance requires high resolution (O $\mathcal{O}$(10) m) LES [ABSTRACT FROM AUTHOR]

Abstract Global reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of O(10) km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the “Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics,” or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions.

Predicting the evolution of burned area, smoke emissions, and energy release from wildfires is crucial to air quality forecasting and emergency response planning yet has long posed a significant scientific challenge. Here we compare predictions of burned area and fire radiative power from the coupled weather/fire‐spread model WRF‐Fire (Weather and Research Forecasting Tool with fire code), against simpler methods typically used in air quality forecasts. We choose the 2019 Williams Flats Fire as our test case due to a wealth of observations and ignite the fire on different days and under different configurations. Using a novel re‐gridding scheme, we compare WRF‐Fire's heat output to geostationary satellite data at 1‐hr temporal resolution. We also evaluate WRF‐Fire's time‐resolved burned area against high‐resolution imaging from the National Infrared Operations aircraft data. Results indicate that for this study, accounting for containment efforts in WRF‐Fire simulations makes the biggest difference in achieving accurate results for daily burned area predictions. When incorporating novel containment line inputs, fuel density increases, and fuel moisture observations into the model, the error in average daily burned area is 30% lower than persistence forecasting over a 5‐day forecast. Prescribed diurnal cycles and those resolved by WRF‐Fire simulations show a phase offset of at least an hour ahead of observations, likely indicating the need for dynamic fuel moisture schemes. This work shows that with proper configuration and input data, coupled weather/fire‐spread modeling has the potential to improve smoke emission forecasts. Plain Language Summary: Predicting wildfire growth and smoke behavior is an important and historically difficult task. Here we compare a coupled fire‐weather model to current practices used in air quality forecasting in their ability to predict daily wildfire spread and fire intensity for the 2019 Williams Flats Fire. We also evaluate the fire‐weather model against high‐resolution satellite and aircraft measurements in ways previously unexplored. We find that including fire‐fighting efforts in our model makes the biggest improvements toward accurate wildfire forecasting. When we account for fire‐fighting efforts, fuel moisture maps, and increased fuel loads, our coupled fire‐weather model significantly outperforms simpler methods with reasonable computational time. Despite this, modeled fire intensity tends to lead observations by at least an hour. Optimal configuration options and avenues for forecasting improvements are discussed. Key Points: Adding containment lines into our wildfire model made the biggest difference in improving accuracy of daily burned area predictionsAccounting for containment, fuel moisture content maps, and increased fuel density consistently increased prediction skill above persistenceModeled fire radiative power leads observations by at least an hour, but with similar accuracy to prescribed diurnal cycles [ABSTRACT FROM AUTHOR]

The diurnal cycle of environmental conditions for shallow and deep convection regimes within the Indian monsoon environment is investigated using comprehensive observations from the surface, boundary layer, and cloud layers. For shallow convection (SC) and deep convection (DC) in the afternoon hours, thermodynamics, moisture convergence, and several other environmental variables provide information on the factors that control the vertical extent of convection in both regimes. The SC regime is characterized by high sensible heat flux, leading to stronger boundary layer turbulence, a higher mixed layer, and increased dry air entrainment from the free troposphere. Evaluation of several pre-conditioning parameters with T-test statistics suggests that stronger mid-level meridional wind shear and lack of mid-level moistening are detrimental to the growth of clouds in the SC regime. Conversely, the DC regime is driven by low surface fluxes and low surface-level buoyancy, with higher boundary layer and mid-layer moisture and more mid-layer instability, supporting larger Convective Available Potential Energy (CAPE). Morning precursor conditions for the preference of SC versus DC regime in the afternoon reveal that total column water vapor, relative humidity and CAPE are significantly higher on DC days. Large-scale moisture transport in the early morning within and above the boundary layer, driven by stronger westerly winds, is a key factor for the development of DC later in the day. This investigation enhances our understanding of boundary layer controls on shallow and deep convection within the Indian Monsoon environment.

We used the observations from the east coast of the USA and model simulations to elicit marine atmospheric surface layer (MASL) processes that controlled the spatial variability of electromagnetic ducting conditions in the near‐shore (60 km) marine environment during CASPER‐East field campaign. The estimated evaporation duct height (EDH) showed an average decrease of ∼2.5 m over every 10 km distance from the shore. The surface layer stability conditions chiefly determined the duct heights. While the mean duct height remained ∼10 m under unstable conditions, deeper (>20 m) evaporation ducts were frequently evident (∼40% of the time) during stable MASL conditions, which were responsible for the observed near‐shore EDH variability. Episodes of warm offshore flow and advection of hot and humid air from the Gulfstream region created ideal environmental conditions for stable MASL development and thus deeper ducts over the coastal ocean. A detailed case study of warm and humid Gulfstream air advection over the cooler coastal ocean is presented to elucidate the temporal evolution of the surface layer stability and associated changes in the spatial distribution of the evaporation duct height. Key Points: Stable conditions in the nearshore CASPER‐East region can be caused by both offshore flow and flow from the Gulf StreamThe near‐shore region of Duck, North Carolina, showed a gradual decrease of evaporation duct height from the shore ∼2.5 m for every 10 kmHigh‐evaporation ducts are associated with stable stratifications in the coastal marine atmospheric surface layer [ABSTRACT FROM AUTHOR]

Abstract This study investigates the role of interactive sea surface temperature (SST) in the early development of aggregated convection using a vector vorticity equation cloud‐resolving model coupled to a slab ocean. The simulations are initialized by a mock Walker circulation driven by initial SST gradient in the elongated x axis, with an average of 300 K and sinusoidal variation of amplitude ranging from 1.5 to 3 K. According to large‐scale perturbation strength, which is caused by SST variation, the results can be divided into two groups. Under weak perturbation, convection‐SST feedback efficiently eliminates SST gradient and moisture anomaly. The large‐scale environment is homogenized within 2 days. Even though SST in the group with stronger perturbation undergoes a similar process, significant moist static energy (MSE) advection in the boundary produces enough moisture difference to introduce virtual temperature effect and aggregation is triggered. Once dry zone starts to expand, radiative and convective effects regenerate SST gradient, which intensifies circulation and accelerates the process. We further show that the evolution of aggregation or not is captured by the trend of MSE‐EIS (estimated inversion strength) variance. The results highlight the boundary layer processes on the formation of aggregated convection in the tropics.

The spread in global mean precipitation among climate models is explored in two ensembles using the complementary perspectives of surface evaporation and energy budgets. Models with higher global mean precipitation have stronger oceanic evaporation, driven by drier near‐surface air. The drier surface conditions occur alongside increases in near‐surface temperature and moisture at 925 hPa, which point to stronger boundary layer mixing. Correlations suggest that the degree of lower tropospheric mixing explains 18%–49% of the intermodel precipitation variance. To test this hypothesis, the degree of mixing is indirectly varied in a single‐model experiment by adjusting the relative humidity threshold that controls low‐cloud fraction. Indeed, increasing lower tropospheric mixing results in more global mean precipitation. Energetically, increased precipitation rates are associated with more downwelling longwave radiation to the surface and weaker sensible heat fluxes. These results highlight how lower‐tropospheric processes must be better constrained to reduce the precipitation discrepancy among climate models. Plain Language Summary: Climate models exhibit a spread in their simulation of the present‐day global mean precipitation rate; a fundamental climate statistic whose spread is surprisingly understudied. This 13% spread compares with the expected change in the global mean precipitation rate in a warmer climate scenario. Complex precipitation physics can make understanding what processes control the global mean precipitation rate across climate models inherently difficult. We find that the degree of mixing within the lower 1‐km of the atmosphere (lower‐tropospheric mixing) controls a large fraction of the spread in global mean precipitation across models. We also show linkages between the lower tropospheric mixing and the energy budget framework that is typically used to understand the global mean precipitation rate. Our results highlight a local scale process (mixing) that controls and impacts a global scale climate statistic (global mean precipitation). They also suggest that future attempts to bridge satellite observations and climate model output can potentially help reduce the existing spread and bias among climate models. Key Points: Fifth Coupled Model Intercomparison Project Atmospheric Model Intercomparison Project simulations disagree on the magnitude of the present‐day global mean precipitation rate by 13%Lower tropospheric mixing explains as much as 49% of the intermodel varianceMost (up to 75%) of the spread in column atmospheric energy happens at the surface [ABSTRACT FROM AUTHOR]

Quantifying the influence of sea spray on air‐sea fluxes under high‐wind conditions is challenging due to a variety of factors. Among existing models, the so‐called bulk air‐sea flux model is commonly used in meteorological applications due to its simplicity, which often involves strong but untested assumptions on spray‐mediated heat fluxes and feedback effects. For example, a common assumption is to treat each droplet size as an independent contribution; that is, it does not interact with other sizes. Thus, the interactions between different size classes of spray are often neglected. In this study, we focus on the polydispersity of the spray size distribution and investigate the appropriateness of assuming an independent contribution from different spray size classes. We implement direct numerical simulations (DNS) with Lagrangian tracking of spray droplets. Based on DNS results, the bulk spray model fails to capture the interactions between different sizes that are observed directly from the droplet and feedback statistics in DNS. Thus, assuming independent contributions from spray droplets results in significant overestimates on the total heat fluxes. We further test different representative sizes of a spray size distribution. We find that the volume‐weighted representative size is capable of predicting the droplet‐modified temperature and humidity fields and generally captures the vertical profiles of spray‐mediated and interfacial heat fluxes. The results indicate that the computation of spray‐mediated fluxes can be simplified in large‐scale parameterizations. Key Points: Directly adding all contributions from spray droplets in bulk models may introduce overestimates on spray‐mediated heat fluxesWe improved the overestimation issue in bulk model for the total heat flux by considering the effects of spray time scalesUsing the volume‐weighted mean size as a representative size could simplify the quantifying of air‐sea fluxes in an Eulerian framework [ABSTRACT FROM AUTHOR]

In this work the very severe cyclonic storm Thane which formed over the Bay of Bengal during 25–31 December 2011 and struck the East coast of India was simulated using the Weather Research and Forecasting (WRF)-Advanced Research WRF (WRF-ARW) mesoscale model. Normally, very severe cyclones rarely form in this late season. The moisture transport, intensity, track and structure of the cyclone is analyzed through vertically integrated moisture flux convergence and planetary boundary layer physics of the Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ) and Asymmetrical Convective Model version 2 (ACM2) schemes. Cyclonic circulation and moisture convergence are seen 6 days ahead of the development of the cyclone and strengthened by the transport of moisture advected from the South China Sea. From the three planetary boundary layer (PBL) schemes, the YSU scheme gives better results both qualitatively and quantitatively for the moisture flux convergence. The MYJ scheme produced the least errors for cyclone intensity from genesis to the landfall stage, while the ACM2 scheme gave better results after landfall. The track of the cyclone with the YSU scheme produced the least errors throughout the life cycle which gives the least landfall error. The structure of the cyclone in terms of tangential winds, the spatial distribution of cloud bands, vertical cross section of temperature anomaly, relative humidity and vertical winds was well simulated by the ACM2 scheme. [ABSTRACT FROM AUTHOR]

Aeolian transport of sand and dust is driven by turbulent winds that fluctuate over a broad range of temporal and spatial scales. However, commonly used aeolian transport models do not explicitly account for such fluctuations, likely contributing to substantial discrepancies between models and measurements. Underlying this problem is the absence of accurate sand flux measurements at the short time scales at which wind speed fluctuates. Here, we draw on extensive field measurements of aeolian saltation to develop a methodology for generating high-frequency (up to 25 Hz) time series of total (vertically-integrated) saltation flux, namely by calibrating high-frequency (HF) particle counts to low-frequency (LF) flux measurements. The methodology follows four steps: (1) fit exponential curves to vertical profiles of saltation flux from LF saltation traps, (2) determine empirical calibration factors through comparison of LF exponential fits to HF number counts over concurrent time intervals, (3) apply these calibration factors to subsamples of the saltation count time series to obtain HF height-specific saltation fluxes, and (4) aggregate the calibrated HF height-specific saltation fluxes into estimates of total saltation fluxes. When coupled to high-frequency measurements of wind velocity, this methodology offers new opportunities for understanding how aeolian saltation dynamics respond to variability in driving winds over time scales from tens of milliseconds to days. [ABSTRACT FROM AUTHOR]

An observing network has been established along the United States west coast that provides up to 20 years of observations to support early warning, preparedness and studies of atmospheric rivers (ARs). The Hydrometeorology Testbed−West Legacy Observing Network, a suite of upper air and surface observing instruments, is now an official National Oceanic and Atmospheric Administration (NOAA) observing system with real-time data access provided via publicly available websites. This regional network of wind profiling radars and co-located instruments also provides observations of boundary layer processes such as complex-terrain flows that are not well depicted in the current operational rawindsonde and radar networks, satellites, or in high-resolution models. Furthermore, wind profiling radars have been deployed ephemerally for projects or campaigns in other areas, some with long records of observations. Current research uses of the observing system data are described as well as experimental products and services being transitioned from research to operations and applications. We then explore other ways in which this network and data library provide valuable resources for the community beyond ARs, including evaluation of high-resolution numerical weather prediction models and diagnosis of systematic model errors. Other applications include studies of gap flows and other terrain-influenced processes, snow level, air quality, winds for renewable energy and the predictability of cloudiness for solar energy industry.

ABSTRACT Forecasting tropical cyclone ( TC) intensity changes over land is complicated by interactions of various surface and atmospheric features. Due to generally unfavorable conditions, many TCs weaken and decay soon after landfall. In some cases, TCs may also transition to extratropical cyclones (ETs). Despite the absence of oceanic forcing, a number of TCs have been observed to maintain or increase strength inland, termed 'tropical cyclone maintenance or intensification' (TCMIs). This study identifies the environments and characteristic features of TCMIs and explores physical processes that may help to produce an atmosphere conducive for tropical systems. The objectives are to compile an inland TC dataset over a 30-year period, quantify TC traits that may relate to maximum strength over land, and analyse surface and atmospheric conditions leading up to intensification. Of 227 inland TCs globally, 45 maintained or increased strength inland: 17 cold-core ( ET), 16 warm-core ( TCMI), and 12 hybrid cases. Analysis of synoptic conditions indicates that TCs persist when low-level temperature gradients are weak. Soil moisture gradients were in the vicinity of the cyclones at the time of intensification and may be forcing the TCMIs via increased surface latent heat flux ( LHF). The area-averaged LHF threshold is found to be around 70 W m−2 for TCMI occurrence. In the 2 weeks leading up to each TCMI, the LHF tends to be higher than average over the intensification regions and provides further evidence of land surface forcing. [ABSTRACT FROM AUTHOR]

While tropical cyclones (TCs) usually decay after landfall, Tropical Storm Fay (2008) initially developed a storm central eye over South Florida by anomalous intensification overland. Unique to the Florida peninsula are Lake Okeechobee and the Everglades, which may have provided a surface feedback as the TC tracked near these features around the time of peak intensity. Analysis is done with the use of an ensemble model-based approach with the Developmental Testbed Center (DTC) version of the Hurricane WRF (HWRF) model using an outer domain and a storm-centered moving nest with 27- and 9-km grid spacing, respectively. Choice of land surface parameterization and small-scale surface features may influence TC structure, dictate the rate of TC decay, and even the anomalous intensification after landfall in model experiments. Results indicate that the HWRF model track and intensity forecasts are sensitive to three features in the model framework: land surface parameterization, initial boundary conditions, and the choice of planetary boundary layer (PBL) scheme. Land surface parameterizations such as the Geophysical Fluid Dynamics Laboratory (GFDL) Slab and Noah land surface models (LSMs) dominate the changes in storm track, while initial conditions and PBL schemes cause the largest changes in the TC intensity overland. Land surface heterogeneity in Florida from removing surface features in model simulations shows a small role in the forecast intensity change with no substantial alterations to TC track. [ABSTRACT FROM AUTHOR]

Abstract: Observations for the 2005–2008 time period from three Southeastern Aerosol Research and Characterization (SEARCH) air quality monitoring sites are examined for diurnal and seasonal variation in concentrations of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particle bound mercury (HgP < 2.5 μm). The sites are located at 1) a suburban-coastal location near Pensacola, Florida (OLF), 2) an urban location in Birmingham, Alabama (BHM), and 3) a rural location west-northwest of Atlanta, Georgia (YRK). Average concentrations of GEM at both OLF and YRK are 1.35 ng m−3, whereas at BHM it is 2.12 ng m−3. All sites show increase in GEM concentration during the morning hours (0.023 and 0.011 ng m−3hr−1 at OLF and YRK between 6 and 10 AM, 0.038 ng m−3hr−1 at BHM between 5 and 10 AM) due to downward mixing of higher concentrations from the residual layer, after which OLF and YRK show negligible variation compared to decrease in concentration at BHM (2.3–1.9 ng m−3 from 10 AM to 6 PM). All sites show seasonal variation of GEM with enhanced concentrations found in winter and spring. Average GOM concentrations are 4.26, 8.55, and 78.2 pg m−3 at OLF, YRK, and BHM, respectively. Seasonally, GOM values are enhanced during fall and spring. All sites undergo a sinusoidal daytime variation of GOM that peaks in the afternoon, while BHM additionally exhibits an early morning enhancement likely caused by vertical mixing. The average HgP concentrations at OLF, YRK, and BHM are 2.49, 4.43, and 39.5 pg m−3, respectively. At OLF, vertical mixing causes an early morning increase in HgP concentration followed by an afternoon decline during all seasons. A daytime increase in HgP is found at YRK for all seasons, while at BHM, nocturnal accumulation followed by a daytime decline is also found for most seasons except winter. In winter, concentrations increase due to vertical mixing in the morning and then decline as the boundary layer grows. Boundary layer processes appear to play an important role in the seasonal and diurnal variation of Hg species and further investigation utilizing a boundary layer process model is warranted. [Copyright &y& Elsevier]

Abstract: In this investigation, the impact of soil moisture on the precipitation amount and distribution in model simulations for West Africa was assessed. This included the examination of the dependence of precipitation on soil moisture, boundary layer parameters or convective conditions. For this purpose, different soil moisture fields from the rainy season of the year 2006 in West Africa were collected. These included three analysis fields, satellite measurements, and model output from the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project. The different soil moisture fields were analyzed and compared first; large differences in the mean values, the north–south gradients, and the heterogeneity were revealed. The distributions were taken to initialize five convection-permitting model runs performed with the limited-area model COSMO (Consortium for Small-scale Modeling), forced by reanalyses from the European Centre for Medium-Range Weather Forecasts. A case study of a period with intense convective activity in the Sudanian and Sahelian zone was selected for the simulations. The simulated precipitation was compared with data from two satellite-based precipitation analyses and with forecasts from two global models of lower resolution. The model spread encompassed the precipitation analyses in the southern subdomain, while the latter lay far above the model results in the northern subdomain. The different soil moisture fields also influenced the turbulent fluxes at the surface, the boundary layer state and height as well as convective instability. Standard deviation of the simulations was highest for convective available potential energy, while the impact on convective inhibition was less pronounced. Only a weak negative relation of precipitation to soil moisture or conditional instability could be discerned. In this case, dry soil favored a higher boundary layer with better developed convective cells contributing to larger precipitation sums. The spread between the five precipitation forecasts suggests that a high-resolution limited-area ensemble, built by applying atmospheric variations as well as variations of the initial land surface conditions, will be a proper method to improve the prediction of mesoscale convective systems and convective precipitation for West Africa. [Copyright &y& Elsevier]

The S-L (She and Leveque) scaling law, also named the hierarchical similarity theory, has been extensively tested for the turbulence made in the laboratory, but seldom been tested for the turbulence in the atmospheric boundary layer (ABL). In this paper, the S-L scaling law is applied to the turbulence in the ABL observed under unstably stratified conditions and over different types of underlying surfaces. The results of analyses show that over this type of homogeneous and flat underlying surface, such as the underlying surface in HUBEX (Huaihe River Basin Energy and Water Cycle Experiment), vertical speed and temperature fields well satisfy the S-L scaling law. For the turbulence over the homogeneous but rather rough underlying surface of forest and under unstably stratified conditions in PFRD (Park Falls Ranger District of the Chequamegon National Forest, Wisconsin, USA), the analyses show that the vertical speed and temperature fields sometimes conform sometimes do not conform to the S-L scaling law. However, at a time, either both of the vertical speed and temperature fields conform to the S-L scaling law, or both of them do not. Horizontal speed fields in both of the field experiments do not satisfy the S-L scaling law. The new explanation of the above-mentioned phenomena is given. [ABSTRACT FROM AUTHOR]

An observing network has been established along the United States west coast that provides up to 20 years of observations to support early warning, preparedness and studies of atmospheric rivers (ARs). The Hydrometeorology Testbed–West Legacy Observing Network, a suite of upper air and surface observing instruments, is now an official National Oceanic and Atmospheric Administration (NOAA) observing system with real-time data access provided via publicly available websites. This regional network of wind profiling radars and co-located instruments also provides observations of boundary layer processes such as complex-terrain flows that are not well depicted in the current operational rawindsonde and radar networks, satellites, or in high-resolution models. Furthermore, wind profiling radars have been deployed ephemerally for projects or campaigns in other areas, some with long records of observations. Current research uses of the observing system data are described as well as experimental products and services being transitioned from research to operations and applications. We then explore other ways in which this network and data library provide valuable resources for the community beyond ARs, including evaluation of high-resolution numerical weather prediction models and diagnosis of systematic model errors. Other applications include studies of gap flows and other terrain-influenced processes, snow level, air quality, winds for renewable energy and the predictability of cloudiness for solar energy industry. [ABSTRACT FROM AUTHOR]

Bulk and size‐resolved particle concentrations were measured at 2.1 and 6.5 m above the soil surface during an intense dust deposition event that occurred in June 2006 in Niger. Bulk concentration measurements were performed using two tapered element oscillating microbalance instruments, and the size‐resolved particle concentrations (from 0.3 to 20 μm) using two optical particle counters. The deposition fluxes derived from the bulk concentrations and those derived from the size‐resolved ones are in very good agreement. The largest deposition fluxes are recorded when the dust concentrations are maximal. The temporal evolution of the dust deposition flux follows that of the dust concentration. This is not the case of the dry deposition velocities that are most of the time controlled by the wind friction velocity. The results also show that large particles are strongly sensible to rebound when the wind friction velocity is the highest. Size‐resolved dry deposition velocities are compared with the rare measurements of dust deposition velocities over bare sandy soils and are confronted to existing parameterizations of the dry deposition velocity. The parameterization of Zhang and Shao (2014, https://doi.org/10.5194/acp‐14‐12429‐2014) appears to be the only one able to reproduce satisfyingly the measured dry deposition velocities on sandy soils in the 1‐ to 10‐μm particle size range. Indeed, unlike others, this scheme considers the desert sandy surfaces as rough surfaces, allowing the interception of dust particles by the sand grains and/or by the small roughness elements present on the surface. Key Points: A dust deposition event allows the determination of dust deposition fluxes and dry deposition velocities using the flux gradient methodThe time evolution of dry deposition velocities is mainly controlled by the wind friction velocity and, for large particles, by reboundMeasured dry deposition velocities are in better agreement with parameterizations that consider bare sandy surfaces as rough surfaces [ABSTRACT FROM AUTHOR]

Based on the ARPS (Advanced Regional Prediction System) at 2 km grid spacing, the convective initiation (CI) of cells that evolved into a squall line on the southern flank of a Meiyu front in East China is investigated. The initiations of four convective cells, denoted CI-A through CI-D, are reasonably captured in the simulation. For CI-A and CI-B, locally enhanced convergence bands associated with boundary layer horizontal convective rolls (HCRs) play a crucial role in determining the exact locations of CIs, whereas a cold outflow boundary from earlier frontal precipitation contributes to additional convergence forcing. For CI-C, initiation occurs directly over the gust front, with the frontal convergence providing the main forcing. CI-D occurs south of and sufficiently far from the gust front, and is mainly forced by the HCR circulations. With surface heat flux turned off in the model, CI is much delayed. Therefore, surface heating increases the convective instability of air south of the front and causes the development of HCRs; it also enhances the gust front convergence by mixing higher southwesterly momentum toward the surface. When the condensation process is turned off, HCRs and/or gust frontal forcing are still able to lift the low-level air to super-saturation where CI is expected. [ABSTRACT FROM AUTHOR]