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The retrieval of atmospheric composition from space-based measurements, by e.g., Sentinel-5p TROPOMI, is strongly affected by radiative interferences with clouds. Dedicated cloud data products, typically retrieved from measurements by the same sounder, are therefore essential. Cloud information is used to filter data and as input to the modelling of atmospheric radiative transfer and the conversion of slant column densities into vertical column densities. The three main TROPOMI cloud retrieval algorithms are: (i) L2_CLOUD OCRA/ROCINN CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks; Clouds-As-Layers), (ii) L2_CLOUD OCRA/ROCINN CRB (Clouds-as Reflecting Boundaries), and (iii) the S5P support product FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands for Sentinel). The cloud variables provided by these products (radiometric cloud fraction, cloud (top) height, and cloud albedo/cloud optical thickness) are subsequently used in the retrieval of the TROPOMI trace gas products. The quality of cloud products and trace gas products is routinely assessed by the ESA/Copernicus Atmospheric Mission Performance Cluster (ATM-MPC) validation service, with ad hoc support from Sentinel-5p Validation Team (S5PVT) AO projects. Version upgrades have had a significant impact on the characteristics of S5P cloud data. The change of the wavelength window in the FRESCO product since version 1.4 (‘FRESCO-wide’) leads to a clear increase in the height of low clouds with a large impact on the tropospheric NO2 retrieval (van Geffen, 2022), and improving the validation results regarding the tropospheric and total NO2 column. The first upgrades of the ROCINN products (from v1 to v2.1-v2.3) led to an increase in correlation with CLOUDNET cloud height, but to a more negative bias for the low clouds, with ROCINN CRB cloud height even dropping below the CLOUDNET cloud base height on average. However, this effect seems alleviated with the latest upgrade to v2.4. The impact on the HCHO validation results is investigated but is less clear compared to the NO2 case. To resolve the discontinuities due to the processor version jumps, a full mission reprocessing is currently ongoing and largely carried out for the L2_CLOUD and FRESCO-S products. The reprocessed ROCINN data have a lower dispersion and higher correlation with respect to the CLOUDNET cloud heights. The bias of the L2_CLOUD OCRA/ROCINN CAL CTH becomes more negative, but that of L2_CLOUD OCRA/ROCINN CRB CH bias improves. Finally, we also discuss the impact of the FRESCO-S reprocessing on the validation results.

By synthesising remote-sensing measurements made in the central Arctic into a model-gridded Cloudnet cloud product, we evaluate how well the Met Office Unified Model (UM) and the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) capture Arctic clouds and their associated interactions with the surface energy balance and the thermodynamic structure of the lower troposphere. This evaluation was conducted using a 4-week observation period from the Arctic Ocean 2018 expedition, where the transition from sea ice melting to freezing conditions was measured. Three different cloud schemes were tested within a nested limited-area model (LAM) configuration of the UM – two regionally operational single-moment schemes (UM_RA2M and UM_RA2T) and one novel double-moment scheme (UM_CASIM-100) – while one global simulation was conducted with the IFS, utilising its default cloud scheme (ECMWF_IFS). Consistent weaknesses were identified across both models, with both the UM and IFS overestimating cloud occurrence below 3 km. This overestimation was also consistent across the three cloud configurations used within the UM framework, with >90 % mean cloud occurrence simulated between 0.15 and 1 km in all the model simulations. However, the cloud microphysical structure, on average, was modelled reasonably well in each simulation, with the cloud liquid water content (LWC) and ice water content (IWC) comparing well with observations over much of the vertical profile. The key microphysical discrepancy between the models and observations was in the LWC between 1 and 3 km, where most simulations (all except UM_RA2T) overestimated the observed LWC. Despite this reasonable performance in cloud physical structure, both models failed to adequately capture cloud-free episodes: this consistency in cloud cover likely contributes to the ever-present near-surface temperature bias in every simulation. Both models also consistently exhibited temperature and moisture biases below 3 km, with particularly strong cold biases coinciding with the overabundant modelled cloud layers. These biases are likely due to too much cloud-top radiative cooling from these persistent modelled cloud layers and were consistent across the three UM configurations tested, despite differences in their parameterisations of cloud on a sub-grid scale. Alarmingly, our findings suggest that these biases in the regional model were inherited from the global model, driving a cause–effect relationship between the excessive low-altitude cloudiness and the coincident cold bias. Using representative cloud condensation nuclei concentrations in our double-moment UM configuration while improving cloud microphysical structure does little to alleviate these biases; therefore, no matter how comprehensive we make the cloud physics in the nested LAM configuration used here, its cloud and thermodynamic structure will continue to be overwhelmingly biased by the meteorological conditions of its driving model.

Active remote sensors equipped with the capability to detect polarization, a shape relevant parameter, are essential to aerosol particle identification in the vertical domain. Most commonly, the linear particle depolarization ratio has been available at the shorter wavelengths of 355 nm and/or 532 nm. Recently, linear particle depolarization ratios at longer wavelengths (910 nm, 1064 nm and, 1565 nm) have emerged to the lidar aerosol research. In this study, a synergy of three lidars, namely a PollyXT lidar, a Vaisala CL61 ceilometer and a Halo Photonics StreamLine Pro Doppler lidar, and in situ aerosol and pollen observations have been utilized to investigate the spectral dependence of birch and pine pollen particles. We found that regardless of the pollen type, the linear particle depolarization ratio was subject to the amount of pollen and its relative contribution to the aerosol mixture in the air. More specifically, during the birch pollination characteristic linear particle depolarization ratios of 5 ± 2 % (355 nm), 28 ± 6 % (532 nm), 23 ± 6 % (910 nm) and, 33 ± 4 % (1565 nm) were retrieved at the pollen layer. Regarding the pine dominant period, the characteristic linear particle depolarization ratio of 6 ± 2 %, 43 ± 11 %, 22 ± 6 % and, 26 ± 3 %, was determined at 355 nm, 532 nm, 910 nm and, 1565 nm wavelengths, respectively. For birch, the linear particle depolarization ratio at 1565 nm was the highest followed by 532 nm and 910 nm wavelengths, respectively. A sharp decrease at 355 nm was evident for birch pollen. For pine pollen, a maximum at 532 nm wavelength was observed. There was no significant change in the linear particle depolarization ratio at 910 nm for the pollen types considered in this study. Given the low concentration of pollen in the air, the inclusion of the longer wavelengths (910 nm and 1565 nm) for the detection of birch and pine can be beneficial due to their sensitivity to trace large aerosol particles.

A quantitative comparison study for Raman lidar and ceilometer observations, and for model simulations of mass concentration estimates of smoke particles is presented. Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios (PDRs) of this plume were measured to be 0.08±0.02 at 355 nm and 0.05±0.01 at 532 nm, suggesting the presence of partly coated soot particles or particles that have mixed with a small amount of dust or other non-spherical aerosol type. The layer-mean PDR at 355 nm (532 nm) decreased during the day from ∼ 0.11 (0.06) in the morning to ∼ 0.05 (0.04) in the evening; this decrease with time could be linked to the particle aging and related changes in the smoke particle shape properties. Lidar ratios were derived as 47±5 sr at 355 nm and 71±5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 ceilometer is presented from a sensor-provided attenuated backscatter coefficient to particle mass concentration (including the water vapor correction for high latitude for the first time). Aerosol backscatter coefficients (BSCs) were measured at four wavelengths (355, 532, 1064 nm from PollyXT and 910 nm from CL51). Two methods, based on a combined lidar and sun-photometer approach, are applied for mass concentration estimations from both PollyXT and the ceilometer CL51 observations. In the first method, no. 1, we used converted BSCs at 532 nm (from measured BSCs) by corresponding measured backscatter-related Ångström exponents, whereas in the second method, no. 2, we used measured BSCs at each wavelength independently. A difference of ∼ 12 % or ∼ 36 % was found between PollyXT and CL51 estimated mass concentrations using method no. 1 or no. 2, showing the potential of mass concentration estimates from a ceilometer. Ceilometer estimations have an uncertainty of ∼ 50 % in the mass retrieval, but the potential of the data lies in the great spatial coverage of these instruments. The mass retrievals were compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust (as indicated by MERRA-2 data) in the retrieved mass concentration is negligible considering the uncertainties, which also shows that ceilometer observations for mass retrievals can be used even without exact knowledge of the composition of the smoke-dominated aerosol plume in the troposphere.

Accurate wind profile measurements are important for applications ranging from aviation to numerical weather prediction. The spatial pattern of winds can be obtained with ground-based remote sensing instruments, such as weather radars and Doppler lidars. As the return signal in weather radars is mostly due to hydrometeors or insects, and in Doppler lidars due to aerosols, the instruments provide wind measurements in different weather conditions. However, the effect of various weather conditions on the measurement capabilities of these instruments has not been previously extensively quantified. Here we present results from a 7-month measurement campaign that took place in Vantaa, Finland, where a co-located Vaisala WRS400 X-band weather radar and WindCube 400S Doppler lidar were employed continuously to perform wind measurements. Both instruments measured plan position indicator (PPI) scans at 2.0∘ elevation from the horizontal. Direct comparison of radial Doppler velocities from both instruments showed good agreement with R2=0.96. We then examined the effect of horizontal visibility, cloud base height, and precipitation intensity on the measurement availability of each instrument. The Doppler lidar displayed good availability in clear air situations and the X-band radar in precipitation. Both instruments exhibited high availability in clear air conditions in summer when insects were present. The complementary performance in the measurement availability of the two instruments means that their combination substantially increases the spatial coverage of wind observations across a wide range of weather conditions.

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.

After a century of rapid urbanization, the majority of the world’s population is now living within urban areas. Despite this, micro and mesoscale meteorological dynamics and processes within the urban boundary layer are not thoroughly understood. Furthermore, a major fraction of these urban areas are located in coastal regions. These urban boundary layers are characterized by a high degree of surface heterogeneity and complex dynamics associated with interactions between land and marine air masses. The broad range of relevant spatial and temporal scales associated with coastal urban boundary layer phenomena makes them notoriously difficult to model.One example of such phenomenon is the sea-breeze, observed in numerous coastal urban areas around the globe. The general sea-breeze circulation has associated spatial scales ranging from O(10 km) to O(100 km). However, it is directly influenced by surface exchanges, which have spatial scales down to O(1 m) in urban areas. By using novel multi-scale modelling methods capable of explicitly resolving all relevant scales of interactions, our aim is to study the complex balance of boundary layer processes during a realistic springtime sea-breeze case in Helsinki, Finland.The PALM model system, an open source meteorological modelling system for boundary layer flows, has implemented the capability for multi-scale two-way self-nested large-eddy simulation (LES) setups. Such setups of several self-nested LES domains are especially suited for studying problems such as the interaction between the urban surface and the sea-breeze circulation. This approach differs from the more traditional modelling approaches, where interactions at either micro or mesoscale have been parametrized or given as one-way boundary conditions, effectively preventing the possibility of studying the two-way interactions and feedbacks.We study both the mechanical and thermal influence of the urban surface on the development of the mesoscale circulation. Furthermore, we investigate how the urban surface affects the development of the internal boundary layer and subsequent convection in the lower branch of the cell, where the stable marine air mass is advected over land. This is achieved by studying the spatial scales associated with the convective turbulent structures as well as exchanges of heat and momentum in various regions of the circulation.In order to verify the simulation setup and the results obtained, we compare the results with observations from Doppler lidars, a C-band dual-polarization weather radar and an in-situ measurement network being operated in the region. We anticipate that we will gain exciting new insights into the development of a sea-breeze circulation, convective internal boundary layers and turbulent structures in coastal urban boundary layers. Furthermore, we expect to quantify the effect of the urban surface on convective boundary layer development in the region.

Long-range scanning Doppler lidars can provide the vertical profile of the horizontal wind within the boundary layer. We used Doppler lidar wind profiles from six locations around the globe to verify the wind profile forecasts generated by ECMWF from the operational IFS model. The six locations selected cover a variety of surface types (rural, marine, mountainous urban, coastal urban). We first validated the Doppler lidar observations at four locations by comparison with collocated radiosonde profiles to ensure that the Doppler lidar observations were of sufficient quality. The two observation types agree well, with the mean absolute error (MAE) in wind speed almost always less than 1 m s-1. Large deviations in the wind direction were usually seen only for low wind speeds. This is due to the ambiguity in wind direction at low wind speed and that the relative uncertainty in the wind direction measurement increases as the wind speeds decrease. The Doppler lidar observations are at sufficient temporal resolution for us to generate time-height composites of the wind verification with one-hour resolution so that we can investigate the diurnal cycle. Verification of the model winds showed that the IFS model performs best over marine (ocean) locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. For example, in Granada, which is near a high mountain range, the IFS model failed to capture a commonly occurring mountain breeze, a feature which is highly dependent on the orography at sub grid-scale.At one location, we conditionally performed the wind verification based on the presence or absence of a low-level-jet diagnosed from the Doppler lidar observations. The IFS model was able to reproduce the presence of the low-level-jet but the wind speed maximum was about 2 m s-1 lower than observed. This is attributed to the effective vertical resolution of the model being too coarse to create the strong gradients in wind speed observed.

The structure of the urban boundary layer, and particularly the surface layer, displays significant complexity, which can be exacerbated by coastal effects for cities located in coastal regions. Resolving the complexity of the coastal urban boundary layer remains an important question for many applications such as air quality and numerical weather prediction. One of the most promising new techniques for measuring the structure of the surface layer is fibre-optic distributed temperature sensing (DTS), which has the potential to provide new significant insights for boundary layer meteorology by making it possible to study thermal turbulence with high spatial and temporal resolution. We present 14 weeks of profile measurements with a DTS system at an urban site in Helsinki, Finland, during the winter and spring of 2020. We assess the benefits and drawbacks of using DTS measurements to supplement sonic anemometry for longer measurement periods in varying meteorological conditions, including those found difficult for the DTS method in prior studies. Furthermore, we demonstrate the capabilities of the DTS system using two case scenarios: a study of the erosion of a near-ground cold layer during the passage of a warm front, and a comparison of the near-ground thermal structure with and without the presence of a sea-breeze cell during springtime convective boundary layer development. This study demonstrates the utility of DTS measurements in revealing the internal surface layer structure, beyond the predictions of traditional surface layer theories. This knowledge is important for improving surface layer theories and parametrisations, including those used in numerical weather prediction. The study also highlights the drawbacks of DTS measurements, caused by low signal-to-noise ratios in near-neutral atmospheric conditions, especially when such a system would be used to supplement turbulence measurements over longer periods. Overall, this study presents important considerations for planning new studies or ongoing measurements utilising this exciting and relatively new instrumentation.

Marine stratocumulus clouds are intimately coupled to the turbulence in the boundary layer and drizzle is known to be ubiquitous within them. Six years of data collected at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic site are utilized to characterize turbulence in the marine boundary layer and air motions below stratocumulus clouds. Profiles of variance of vertical velocity binned by wind direction (wdir) yielded that the boundary layer measurements are affected by the island when the wdir is between 90° and 310° (measured clockwise from North where air is coming from). Data collected during the marine conditions (wdir310) showed that the variance of vertical velocity was higher during the winter months than during the summer months due to higher cloudiness, wind speeds, and surface fluxes. During marine conditions the variance of vertical velocity and cloud fraction exhibited a distinct diurnal cycle with higher values during the nighttime than during the daytime. Detailed analysis of 32 cases of drizzling marine stratocumulus clouds showed that for a similar amount of radiative cooling at the cloud top, within the sub-cloud layer 1) drizzle increasingly falls within downdrafts with increasing rain rates, 2) the strength of the downdrafts increases with increasing rain rates, and 3) the correlation between vertical air motion and rain rate is highest in the middle of the sub-cloud layer. The results presented herein have implications for climatological and model evaluation studies conducted at the ENA site, along with efforts of accurately representing drizzle-turbulence interactions in a range of atmospheric models.

The atmospheric boundary layer (ABL) is the layer closest to the Earth’s surface within which most human activities take place. The vertical profile of atmospheric thermodynamic parameters in the ABL impact weather, air quality and climate. However, surface sensor networks and satellite observations do not provide sufficient information on the high temporal variability and strong vertical gradients that occur in the ABL. Thus, the ABL represents an important but rather under-sampled part of the atmosphere. This observational gap currently hampers progress in numerical weather prediction, air quality forecasting and climate assessment. Due to recent technological and methodological advances, ground-based remote sensing instruments are now able to provide high-quality profiles of ABL parameters such as temperature, humidity, wind, aerosol and cloud properties. However, even though state-of-the-art ABL profilers are deployed at numerous sites in Europe, efficient science and technology networking and coordination is still required to exploit this rich dataset effectively. The current lack of data and procedure harmonization often diminishes the potential societal benefits of the existing ABL profiling data. This paper introduces PROBE, a new initiative funded by the European Cooperation in Science and Technology (COST), that aims to broaden the bridge between a wide range of user needs and the science and technology expertise residing in industry and academia, while strengthening and harmonizing methods and procedures to yield higher quality ABL observational data. Here, the challenges, objectives and implementation plan for PROBE are described, highlighting some preliminary results that will be further developed into operational applications during the 4-year duration (2019–2023) of this collaborative project.

Aerosol emissions in South Asia are large. The emitted aerosols can travel significant distances and, during the Asian southwest monsoon especially, are prone to modification through cloud processing and wet scavenging while being transported. The scale of emissions and transport means that the global climate impact of these aerosols are sensitive to modification en route, but the process-level understanding is still largely lacking. In this study, we analyse long-term aerosol data measured at an observatory established in Hanimaadhoo, Republic of Maldives, to investigate the long-term properties of aerosols over the Indian Ocean as well as to understand the effect of precipitation on the aerosol particle size distribution during long-range transport. The observatory location is ideal because it is a receptor site with little local influence, and, depending on the season, receives either polluted air masses coming from the Indian subcontinent or clean marine air masses from the Indian Ocean. We analysed the sub-micron particle number size distribution measured during the years 2004–2008, and 2014–2017, and this is the first inter-seasonal long-term study of the sub-micron aerosol features in the region. The aerosol origin and its relative exposure to wet scavenging during long-range transport were analysed using back-trajectory analysis from HYSPLIT. By comparing aerosol measurements to precipitation along its transport, this study shows that there is a substantial change in particle number size distributions and concentrations depending on the amount of rainfall during transport. During the southwest monsoon season, the aerosol size distribution was notably bi-modal and total particle concentrations clearly reduced in comparison with the prevailing aerosol size distribution during the northeast monsoon season. Precipitation during transport usually corresponded with a greater reduction in accumulation mode concentrations than for smaller sizes, and the shape of the median size distribution showed a clear dependence on the trajectory origin and route taken.

The French–German Arctic research base AWIPEV (the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research – AWI – and the French Polar Institute Paul Emile Victor – PEV) at Ny-Ålesund, Svalbard, is a unique station for monitoring cloud-related processes in the Arctic. For the first time, data from a set of ground-based instruments at the AWIPEV observatory are analyzed to characterize the vertical structure of clouds. For this study, a 14-month dataset from Cloudnet combining observations from a ceilometer, a 94 GHz cloud radar, and a microwave radiometer is used. A total cloud occurrence of ∼81 %, with 44.8 % multilayer and 36 % single-layer clouds, was found. Among single-layer clouds the occurrence of liquid, ice, and mixed-phase clouds was 6.4 %, 9 %, and 20.6 %, respectively. It was found that more than 90 % of single-layer liquid and mixed-phase clouds have liquid water path (LWP) values lower than 100 and 200 g m−2, respectively. Mean values of ice water path (IWP) for ice and mixed-phase clouds were found to be 273 and 164 g m−2, respectively. The different types of single-layer clouds are also related to in-cloud temperature and the relative humidity under which they occur. Statistics based on observations are compared to ICOsahedral Non-hydrostatic (ICON) model output. Distinct differences in liquid-phase occurrence in observations and the model at different environmental temperatures lead to higher occurrence of pure ice clouds. A lower occurrence of mixed-phase clouds in the model at temperatures between −20 and −5 ∘C becomes evident. The analyzed dataset is useful for satellite validation and model evaluation.

Observations of profiles of winds, aerosol, clouds, winds, temperature and humidity in the lowest few km of the atmosphere from networks of ceilometers, Doppler wind lidars and microwave radiometers are starting to flow in real time to forecasting centers in Europe.\ud \ud To realise the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few km are hardly accessible by satellite, especially in dynamically-active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real-time to forecast centers. The three classes of instruments are: (i) Automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog and volcanic ash, the last two being especially important for air traffic control; (ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind-gusts and low-level jets; and (iii) Microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. Twenty-two European countries and fifteen European National Weather Services are collaborating in the project, that involves the implementation of common operating procedures, instrument calibrations, data formats and retrieval algorithms. Currently, data from 220 ceilometers in 17 countries are being distributed in near real-time to national weather forecast centers; this should soon rise to many hundreds. The wind lidars should start delivering real time data in late 2018, and the plan is to incorporate the microwave radiometers in 2019. Initial data assimilation tests indicate a positive impact of the new data.

Knowledge of the atmospheric boundary layer state and evolution is important for understanding air pollution and low-level cloud development, among other things. There are a number of instruments and methods that are currently used to estimate boundary layer height (BLH). However, no single instrument is capable of providing BLH measurements in all weather conditions. We proposed a method to derive a daytime convective BLH using clear air echoes in radar observations and investigated the consistency of these retrievals between different radar frequencies. We utilized data from three vertically pointing radars that are available at the SMEAR II station in Finland, i.e. the C band (5 GHz), Ka band (35 GHz) and W band (94 GHz). The Ka- or W-band cloud radars are an integral part of cloud profiling stations of pan-European Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Our method will be utilized at ACTRIS stations to serve as an additional estimate of the BLH during summer months. During this period, insects and Bragg scatter are often responsible for clear air echoes recorded by weather and cloud radars. To retrieve a BLH, we suggested a mechanism to separate passive and independently flying insects that works for all analysed frequency bands. At the lower frequency (the C band) insect scattering has been separated from Bragg scattering using a combination of the radar reflectivity factor and linear depolarization ratio. Retrieved values of the BLH from all radars are in a good agreement when compared to the BLH obtained with the co-located HALO Doppler lidar and ERA5 reanalysis data set. Our method showed some underestimation of the BLH after nighttime heavy precipitation yet demonstrated a potential to serve as a reliable method to obtain a BLH during clear-sky days. Additionally, the entrainment zone was observed by the C-band radar above the CBL in the form of a Bragg scatter layer. Aircraft observations of vertical profiles of potential temperature and water vapour concentration, collected in the vicinity of the radar, demonstrated some agreement with the Bragg scatter layer.

Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios of this plume were measured to be 0.08 ± 0.02 at 355 nm and 0.05 ± 0.01 at 532 nm which were slightly higher than the values given in the literature. Non-spherical shaped aged smoke particles and/or the mixing with a small amount of fine dust particles could cause the observed increase in the particle linear depolarization ratios. Lidar ratios were derived as 47 ± 5 sr at 355 nm and 71 ± 5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 is presented, including the water vapor correction for high latitude for the first time, from sensor provided attenuated backscatter coefficient to particle mass concentration. A combined lidar and sun-photometer approach (based on AERONET products) is applied for mass concentration estimations. Mass concentrations were estimated from both PollyXT and the ceilometer CL51 observations, which were of the order of ~ 30 µg m−3 in the morning and decreased to ~ 20 µg m−3 in the night. A difference of ~ 30% was found between PollyXT and CL51 estimated mass concentrations. The mass retrievals were discussed and compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust in the retrieved mass concentration slightly improved the correspondence between the observations and the MERRA-2 simulations.

Space-born atmospheric composition measurements, like those from Sentinel-5p TROPOMI, are strongly affected by the presence of clouds. Dedicated cloud data products, typically retrieved with the same sensor, are therefore an important tool for the provider of atmospheric trace gas retrievals. Cloud products are used for filtering and modification of the modelled radiative transfer.In this work, we assess the quality of the cloud data derived from Copernicus Sentinel-5 Precursor TROPOMI radiance measurements. Three cloud products are considered: (i) L2_CLOUD OCRA/ROCINN CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks; Clouds-As-Layers), (ii) L2_CLOUD OCRA/ROCINN CRB (same; Clouds-as Reflecting Boundaries), and (iii) the S5p support product FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands for Sentinel). These cloud products are used in the retrieval of several S5p trace gas products (e.g., ozone columns and profile, total and tropospheric nitrogen dioxide, sulfur dioxide, formaldehyde). The quality assessment of these cloud products is carried out within the framework of ESA’s Sentinel-5p Mission Performance Centre (MPC) with support from AO validation projects focusing on the respective atmospheric gases.Cloud height data from the three S5p cloud products is compared to radar/lidar based cloud profile information from the ground-based networks CLOUDNET and ARM. The cloud height from S5p CLOUD CRB and S5p FRESCO are on average 0.6 km below the cloud mid-height of CLOUDNET measurements, and the cloud top height from S5p CLOUD CAL is on average 1 km below CLOUDNET’s cloud top height. However, the comparison is different for low and high clouds, with S5p CLOUD CAL cloud top height being only 0.3 km below CLOUDNET’s for low clouds. The radiometric cloud fraction and cloud (top) height are compared to those of other satellite cloud products like Aura OMI O2-O2. While the latitudinal variation is often similar, offsets are encountered.Recently, major S5p cloud product upgrades were released for S5p OCRA/ROCINN (July 2020) and for S5p FRESCO (December 2020), leading to a decrease of the ROCINN CRB cloud height and an increase of the FRESCO cloud height on average. Moreover, a major change in the ROCINN surface albedo treatment leads to a clear improvement of the comparison with CLOUDNET at the complicated sea/land/ice/snow site Ny-Alesund.

The identification of the severe COVID-19 virus in December 2019 led the World Health Organization to declare a global pandemic by March 2020. Up till recently with the first available vaccines, the only prevention measures include strict social, travel and working restrictions in a so-called lockdown period that lasted for several weeks (mid-March to the end of April 2020 for most of Europe). This abrupt change in social behaviour is expected to impact local but also regional atmospheric composition, and the environmental impact is highly interesting to study.The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) is a pan-European research infrastructure producing high-quality data and information on short-lived atmospheric constituents and on the processes leading to the variability of these constituents in natural and controlled atmospheres. ACTRIS integrates, harmonizes, and distributes datasets, activities, and services provided by the Central Facilities and National Facilities, located in 22 European countries. During the lockdown period in spring 2020 most of the ACTRIS observational were operational. The National Facilities performing the ambient measurements are generally regional background sites, with the aim to detect changes on regional level. Within the context of the current COVID-19 outbreak, ACTRIS has been continuously providing access to data on air quality and atmospheric composition. This is of particular interest and importance as it provides unique information measured from the ground to assess the European air quality and atmospheric composition during the lockdown complementing, in a fundamental way, satellite observations and modelling analysis. ACTRIS released a comprehensive and quality assured set of atmospheric measurement data during the COVID-19 pandemic spring 2020 – January– May 2020. This includes:- 30 sites with aerosol in situ measurements providing mainly absorption and scattering coefficient, size and/or number distribution. A few sites with high time solution aerosol chemical composition;- 12 sites with trace gases in situ data providing VOCs and NOX measurements;24 sites with aerosol remote sensing data providing profiles with backscattering and extinction coefficient;- 11 cloud remote sensing sites providing profile information of 9 various cloud properties.To facilitate studies, ACTRIS has compiled the data and coined a DOI for the data sets measured during the COVID-19 spring lockdown period, including an intensive aerosol remote sensing campaign in May. This presentation will present the data set and the potential applications and benefits using ACTRIS COVID-19 dataset for studying atmospheric composition changes during COVID-19 lockdown periods.

Transboundary-local aerosols interaction requires to be comprehensively understood in urban air quality research. A year-long intensive observation of the atmospheric boundary layer (ABL) at multiple sites in Hong Kong was conducted using a four-Doppler Light Detection and Ranging (LiDAR) network with different scanning modes. Results show that heterogeneity of the ABL in terms of mixing layer height and wind shear was induced by orographic topography. Interaction between local and advected aerosol layers during a transboundary air pollution (TAP) episode was identified by the network. During TAP episode, downward transport of transboundary aerosol relied on small scale eddies with weak wind speed in nighttime, while the transport of surface local aerosol to upper level was the dominated process in daytime, but the heterogeneity of the ABL affected by terrain determined the capacity of the mixing, eventually resulting in the opposite transport direction of aerosols in the transboundary-local aerosols interaction. Published version This study was jointly funded by Dr. Stanley Ho Medicine Development Foundation (Grant no. 8305509), the Vice-Chancellor’s Discretionary Fund of The Chinese University of Hong Kong (Grant no. 4930744), and the project from ENvironmental SUstainability and REsilience (EN-SURE) partnership between CUHK and UoE (http://www.exeter.ac.uk/cuhkpartnership/)

High particulate matter (PM) and ozone (O3) concentration in Hong Kong are frequently observed during the summertime typhoon season. Despite the critical effect of a typhoon on air pollution, contributions of vertical wind profile and cloud movement during transboundary air pollution (TAP) on surface PM and O3 concentration have yet to be fully understood. This work is the first study to apply a network of Doppler light detection and ranging (LiDAR) as well as back trajectory analysis to comprehensively analyze the effect of a weak Typhoon (Danas) occurring during 16–19 July 2019 on different variations in PM and O3 concentration. During the typhoon Danas, three types of surface air pollution with five episodes were identified: (1) low PM and high O3 concentration; (2) co-occurring high PM and O3 concentration and (3) high PM and low O3 concentration. Employing our 3D Real-Time Atmospheric Monitoring System (3DREAMs) along with surface observations, we found the important role of TAP in the increases in surface PM and O3 concentration with significant vertical wind shear that transported air pollutants at upper levels, and strong vertical mixing that brought air pollutants to the ground level. Cloud movement related to typhoon periphery, as well as high solar radiation due to sinking motion and remote transport by continental wind, have an impact on local O3 concentration. For the substantial difference in O3 concentration between two air quality measurement sites, the similar vertical aerosol distributions and wind profiles suggest the comparable TAP contributions at the two sites and thus infer the critical role of local O3 photochemical process in the O3 difference. This work comprehensively reveals the influences of a weak typhoon on variations in PM and O3 during the five episodes, providing important references for air quality monitoring and forecast in regions under the influence of typhoon.

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data derived from Copernicus Sentinel-5 Precursor (S5P) TROPOMI radiance measurements: cloud top height and cloud optical thickness (retrieved with the S5P OCRA/ROCINN_CAL algorithm), cloud height (S5P OCRA/ROCINN_CRB and S5P FRESCO) and radiometric cloud fraction (all three algorithms). The analysis combines: (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS and OMI O2-O2), and (iii) ground-based validation with respect to correlative observations (2018-04-30 to 2020-02-27) from the CLOUDNET network of ceilometers, lidars and radars. Peculiar geographical patterns were identified, and will be mitigated in future releases of the cloud data products. Zonal mean latitudinal variation of S5P cloud properties are similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud top height and cloud optical thickness, and with CLOUDNET cloud top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud top height is below the cloud top height of VIIRS and of CLOUDNET, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the CLOUDNET cloud mean height for the low clouds, but match on an average better with the CLOUDNET cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the CLOUDNET observations.

Eleven years of dual-polarization weather radar data, complemented by satellite and lidar observations, were used to investigate the origin of areas of localized intensification of precipitation spotted in the vicinity of Helsinki-Vantaa airport. It was observed that existing precipitation is enhanced locally on spatial scales from a few kilometers to several tens of kilometers. The precipitation intensity in these localized areas was 6-14 times higher than the background large-scale precipitation rate. Surface observations and dual-polarization radar data indicate that snowflakes within the ice portion of the falling precipitation in the intensification regions are larger and more isotropic than in the surrounding precipitation. There appears to be an increase in the ice particle number concentration within the intensification region. The observed events were linked to arriving or departing air traffic. We advocate that the mechanism responsible for intensification is aircraft-produced ice particles boosting the aggregation growth of snowflakes. Plain Language Summary: By analyzing 11 years of dual-polarization weather radar observations in the Helsinki region, we have discovered that airplanes landing in or departing from the Helsinki-Vantaa airport could locally increase precipitation rate by as much as 14 times. The observed phenomenon is related to the hole-punch clouds, which are also forming with the help of airplanes. The reported observations allow us to have a better understanding of precipitation formation processes that take place in ice and mixed phase clouds. They show that falling ice crystals from upper clouds could seed lower clouds and therefore increase rain or snowfall intensity through the process called snowflake aggregation. During snowflake aggregation bigger faster falling particles are formed by ice particles colliding and sticking together.

State-of-the-art numerical models such as the UK Met Office Unified Model and European Centre for Medium-Range Weather Forecasting Integrated Forecasting System are crucial tools for forecasting future Arctic warming. However, their ability to reproduce clouds and boundary layer meteorology in the high Arctic has not been thoroughly evaluated following significant model developments over the last 10 years. Model evaluation is key to understanding where remaining process weaknesses lie, thus informing further parametrization developments to improve the simulated surface energy budget.Here, we evaluate model performance with comparison to observations made during the Arctic Ocean 2018 expedition, where a suite of remote-sensing instrumentation was active aboard the Swedish icebreaker Oden measuring summertime Arctic cloud and boundary layer properties. We find that both models do not reproduce cloud fractions well at altitude (up to 8 km) and overestimate the occurrence of low (

The Sentinel 5 Precursor products, call for an accurate validation. Europe can be nowadays regarded as a leader in ground-based vertical profiling observations. ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) is an EC funded infrastructure integrating European ground-based stations equipped with advanced atmospheric equipment. Among these, EARLINET (European Aerosol Research Lidar NETwork) and Cloudnet are well-established networks providing vertical profiles of aerosol and clouds with high vertical and temporal resolution. A network of ground-based stations has the ability to provide the spatio-temporal development of aerosol and cloud fields and offers a unique opportunity for the validation of observations from space. In this project, state-of-the-art instrumentations for observing aerosol and clouds will be used for validation purposes: multi-wavelength lidar (EARLINET) and Doppler cloud radar (Cloudnet).Characterization of aerosol and cloud fields over the stations is provided by the use of EARLINET and Cloudnet data. Additional information is provided by AERONET data where available. Differences will be reported as a function of aerosol load, aerosol and cloud height, aerosol type, cloud type and underneath surface.First results of validation efforts performed within ACTRIS in terms of a quantitative evaluation of the accuracy of S5P aerosol and cloud products will be reported. This activity is done under the EC-ACTS: Earlinet and Cloudnet - Aerosol and Clouds Teams for Sentinel-5P Validation unfunded project, which comprises 3 EARLINET/Cloudnet stations [Potenza (IT), Leipzig (DE) and Cabauw (NL)]; 3 EARLINET stations [Granada (ES), Athens (GR) and Bucharest (RO)] and 2 Cloudnet sites [Mace Head (IE) and Sodankylä (FI)].In particular, the first results will be about the S5P Aerosol Layer Height (mandatory product) and Aerosol Optical Depth (optional product) and whenever available the AAI-based columnar Aerosol Type product.

Satellite measurements of tropospheric or total column trace gas species, including those from Sentinel-5p TROPOMI, are affected by the presence of clouds. Therefore, cloud data products retrieved with the same sensor play an essential role, as they allow the data provider to take an estimated cloud impact on the trace gas retrieval into account. Examples are the modification of the radiative transfer and associated quantities such as the air mass factor, and the partial masking of the measurement scene. Evidently, the accuracy of these corrections relies on the accuracy of the retrieved cloud properties, like radiometric cloud fraction (CF), cloud top height (CTH) or cloud height (CH), and cloud optical thickness (COT) or cloud albedo (CA).We consider here three S5p TROPOMI-based cloud products: (i) L2_CLOUD OCRA/ROCINN CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks; Clouds-As-Layers), (ii) L2_CLOUD OCRA/ROCINN CRB (Clouds-as Reflecting Boundaries), and (iii) the S5p support product FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands). These are input to the S5p operational processors for several trace gas products, including ozone columns and profile, total and tropospheric NO2, formaldehyde, sulfur dioxide. The quality assessment of these cloud products is carried out within the framework of ESA’s Sentinel-5p Mission Performance Centre (MPC) with support from AO validation projects focusing on the respective trace gases.In this work, cloud height (from S5p CLOUD CRB and S5p FRESCO algorithms) and cloud top height (from S5p CLOUD CAL) S5p data is validated with radar/lidar-based cloud profile information from the ground-based networks CLOUDNET and ARM at 17 sites. For some sites the comparison is difficult due to e.g., orography or snow/ice cover. S5P and CLOUDNET report similar cloud height variations at several sites, and the correlation between the S5p cloud products and CLOUDNET can be high (Pearson R up to 0.9). However, there is a site-dependent negative bias of the S5p cloud (top) height with respect to the CLOUDNET data: up to -2.5 km for S5p CLOUD CAL cloud top height and -1.5 km for S5p CLOUD CRB and S5p FRESCO cloud height. The dependence on other parameters measured by S5p and CLOUDNET (e.g., radiometric cloud fraction, cloud phase,…) is investigated.

Coal combustion is one of the most significant anthropogenic CO2 and air pollution sources globally. This paper studies the atmospheric emissions of a power plant fuelled with a mixture of industrial pellets (10.5%) and coal (89.5%). Based on the stack measurements, the solid particle number emission, which was dominated by sub-200 nm particles, was 3.4×1011 MJ-1 for the fuel mixture when electrostatic precipitator (ESP) was cleaning the flue gas. The emission factor was 50 mg MJ-1 for particulate mass and 11 740 ng MJ-1 for the black carbon with the ESP. In the normal operation situation of the power plant, i.e., including the flue-gas desulphurisation and fabric filters (FGD and FF), the particle number emission factor was 1.7×108 MJ-1, particulate mass emission factor 2 mg MJ-1 and black carbon emission factor 14 ng MJ-1. Transmission electron microscopy (TEM) analysis supported the particle number size distribution measurement in terms of particle size and the black carbon concentration. The TEM images of the particles showed variability of the particle sizes, morphologies and chemical compositions. The atmospheric measurements, conducted in the flue-gas plume, showed that the flue-gas dilutes closed to background concentrations in 200 sec. However, an increase in particle number concentration was observed when the flue gas aged. This increase in particle number concentration was interpret as formation of new particles in the atmosphere. In general, the study highlights the importance of detailed particle measurements when utilizing new fuels in existing power plants. Implications: CO2 emissions of energy production decrease when substituting coal with biofuels. The effects of fuels changes on particle emission characteristics have not been studied comprehensively. In this study conducted for a real-scale power plant, co-combustion of wood pellets and coal caused elevated black carbon emissions. However, it was beneficial from the total particle number and particulate mass emission point of view. Flue-gas cleaning can significantly decrease the pollutant concentrations but also changes the characteristics of emitted particles. Atmospheric measurements implicated that the new particle formation in the atmospheric flue-gas plume should be taken into account when evaluating all effects of fuel changes.” Are implication statements part of the manuscript?

The atmospheric boundary layer (BL) is the atmospheric layer coupled to the Earth’s surface at relatively short timescales. A key quantity is the BL depth, which is important in many applied areas of weather and climate such as air-quality forecasting. Studying BLs in climates and biomes across the globe is important, particularly in the under-sampled southern hemisphere. The present study is based on a grazed grassland-savannah area in northwestern South Africa during October 2012–August 2014. Ceilometers are probably the cheapest method for measuring continuous aerosol profiles up to several kilometers above ground and are thus an ideal tool for long-term studies of BLs. A ceilometer-estimated BL depth is based on profiles of attenuated backscattering coefficients from atmospheric aerosols; the sharpest drop often occurs at BL top. Based on this, we developed a new method for layer detection that we call the signal-limited layer method. The new algorithm was applied to ceilometer profiles which thus classified BL into classic regime types: daytime convective mixing, and a double layer at night of surface-based stable with a residual layer above it. We employed wavelet fitting to increase successful BL estimation for noisy profiles. The layer-detection algorithm was supported by an eddy-flux station, rain gauges, and manual inspection. Diurnal cycles were often clear, with BL depth detected for 50% of the daytime typically being 1–3 km, and for 80% of the night-time typically being a few hundred meters. Variability was also analyzed with respect to seasons and years. Finally, BL depths were compared with ERA-Interim estimates of BL depth to show reassuring agreement.

Over two years of meteorological observations from Utö, a small island in the Finnish outer archipelago in the Baltic Sea, were used to investigate the occurrence and characteristics of low-level jets (LLJs) and the diurnal and seasonal variations in these properties. An objective LLJ identification algorithm that is suitable for high-temporal-and-vertical-resolution Doppler lidar data was created and applied to wind profiles obtained from a combination of Doppler lidar data and two-dimensional sonic anemometer observations. This algorithm was designed to identify coherent LLJ structures and requires that they persist for at least 1 h. The long-term mean LLJ frequency of occurrence at Utö was 12%, the mean LLJ wind speed was 11.6 m s−1, and the vast majority of identified LLJs occurred below 150 m above ground level. The LLJ frequency of occurrence was much higher during summer (21%) and spring (18%) than in autumn (8%) and winter (3%). During winter and spring, the LLJ frequency of occurrence is evenly distributed throughout the day. In contrast, the LLJ frequency of occurrence peaks at night (1900–0100 UTC) during summer and during the evening hours (1700–1900 UTC) in autumn. The highest and strongest LLJs come from the southwest, which is also the predominant LLJ direction in all seasons. LLJs below 100 m are common in spring and summer, are weaker, and do not show a strong directional dependence.

This study presents analysis of in situ measurements conducted over the period 2005–2014 in the Indian Himalayas to give a thorough overview of the factors and causes that drive aerosol properties. Aerosol extensive properties (namely, particle number concentration, scattering coefficient, equivalent black carbon, PM2.5, and PM10) have 1.5–2 times higher values in the early to late afternoon than during the night, and a strong seasonality. The interannual variability is ±20% for both PM2.5 and total particle number concentration. Analysis of the data shows statistically significant decreasing trends of −2.3 μg m−3 year−1 and −2.7 μg m−3 year−1 for PM2.5 and PM10, respectively, over the study period. The mountainous terrain site (Mukteshwar, MUK) is primarily under the influence of air from the plains. This is due to convective transport processes that are enhanced by local and mesoscale topography, leading to pronounced valley/mountain winds and consequently to atmospheric boundary layer air lifting from the plains below. The transport from plains is evident in seasonal‐diurnal patterns observed at MUK. The timing of the patterns corresponds with changes in turbulence and water vapor (q). According to our analysis, using these as proxies is a viable method for examining boundary layer influence in the absence of direct atmospheric boundary layer height measurements. Comparing the measurements with climate models shows that even regional climate models have problems capturing the orographic influence accurately at MUK, highlighting the importance of long‐term direct measurements at multiple points to understand aerosol behavior in mountainous areas.

Understanding the distribution of aerosol layers is important for determining long range transport and aerosol radiative forcing. In this study we combine airborne in situ measurements of aerosol with data obtained by a ground-based High Spectral Resolution Lidar (HSRL) and radiosonde profiles to investigate the temporal and vertical variability of aerosol properties in the lower troposphere. The HSRL was deployed in Hyytiälä, Southern Finland, from January to September 2014 as a part of the US DoE ARM (Atmospheric Radiation Measurement) mobile facility during the BAECC (Biogenic Aerosols – Effects on Cloud and Climate) Campaign. Two flight campaigns took place in April and August 2014 with instruments measuring the aerosol size distribution from 10 nm to 10 µm at altitudes up to 3800 m. Two case studies from the flight campaigns, when several aerosol layers were identified, were selected for further investigation: one clear sky case, and one partly cloudy case. During the clear sky case, turbulent mixing ensured low temporal and spatial variability in the measured aerosol size distribution in the boundary layer whereas mixing was not as homogeneous in the boundary layer during the partly cloudy case. The elevated layers exhibited greater temporal and spatial variability in aerosol size distribution, indicating a lack of mixing. New particle formation was observed in the boundary layer during the clear sky case, and nucleation mode particles were also seen in the elevated layers that were not mixing with the boundary layer. Interpreting local measurements of elevated layers in terms of long-range transport can be achieved using back trajectories from Lagrangian models, but care should be taken in selecting appropriate arrival heights, since the modelled and observed layer heights did not always coincide. We conclude that higher confidence in attributing elevated aerosol layers with their air mass origin is attained when back trajectories are combined with lidar and radiosonde profiles.

In this study, the crosswind (wind component perpendicular to a path, U⊥) is measured by a scintillometer and estimated with Doppler lidar above the urban environment of Helsinki, Finland, for 15 days. The scintillometer allows acquisition of a path-averaged value of U⊥ (U⊥), while the lidar allows acquisition of path-resolved U⊥ (U⊥ (x), where x is the position along the path). The goal of this study is to evaluate the performance of scintillometer U⊥ estimates for conditions under which U⊥ (x) is variable. Two methods are applied to estimate U⊥ from the scintillometer signal: the cumulative-spectrum method (relies on scintillation spectra) and the look-up-table method (relies on time-lagged correlation functions). The values of U⊥ of both methods compare well with the lidar estimates, with root-mean-square deviations of 0.71 and 0.73 m s−1. This indicates that, given the data treatment applied in this study, both measurement technologies are able to obtain estimates of U⊥ in the complex urban environment. The detailed investigation of four cases indicates that the cumulative-spectrum method is less susceptible to a variable U⊥ (x) than the look-up-table method. However, the look-up-table method can be adjusted to improve its capabilities for estimating U⊥ under conditions under for which U⊥ (x) is variable.

Capsule: A 21-month deployment to Graciosa Island in the northeastern Atlantic Ocean is providing an unprecedented record of the clouds, aerosols and meteorology in a poorly-sampled remote marine environment The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009- December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

We have extensively evaluated the response of cloud base drizzle rate (Rcb; mm d−1) in warm clouds to liquid water path (LWP; g m−2) and to cloud condensation nuclei (CCN) number concentration (NCCN; cm−3), an aerosol proxy. This evaluation is based on a 19 month long data set of Doppler radar, lidar, microwave radiometers, and aerosol observing systems from the Atmospheric Radiation Measurement (ARM) Mobile Facility deployments at the Azores and in Germany. Assuming 0.55% supersaturation to calculate NCCN, we found a power law Rcb=0.0015±0.0009⋅LWP1.68±0.05NCCN−0.66±0.08, indicating that Rcb decreases by a factor of 2–3 as NCCN increases from 200 to 1000 cm−3 for fixed LWP. Additionally, the precipitation susceptibility to NCCN ranges between 0.5 and 0.9, in agreement with values from simulations and aircraft measurements. Surprisingly, the susceptibility of the probability of precipitation from our analysis is much higher than that from CloudSat estimates but agrees well with simulations from a multiscale high-resolution aerosol-climate model. Although scale issues are not completely resolved in the intercomparisons, our results are encouraging, suggesting that it is possible for multiscale models to accurately simulate the response of LWP to aerosol perturbations.

This chapter provides an overview of the present (2016) state of the art in ground-level remote sensing of the wind speed and boundary-layer height by use of lasers. The chapter covers a broad range of aspects of coherent wind-lidar measurements—from the basic measuring principles and calibration, to a discussion on the use of wind-lidar measurements for studies of the wind climate. A number of methods for the determination of atmospheric turbulence and wind gusts from wind-lidar measurements as well as ways to estimate the atmospheric boundary-layer height by use of lidar observations are presented. Finally the so-called wind-scanner system is described.

A new methodology is proposed for scaling Doppler lidar observations of wind gusts to make them comparable to those observed at a meteorological mast. Doppler lidars can then be used to measure wind gusts in regions and heights where traditional meteorological mast measurements are not available. This novel method also provides estimates for wind gusts at arbitrary gust durations, including those shorter than the temporal resolution of the Doppler lidar measurements. The input parameters for the scaling method are the measured wind gust speed as well as the mean and the standard deviation of the horizontal wind speed. The method was tested using WindCube V2 Doppler lidar measurements taken next to a 100-m-high meteorological mast. It is shown that the method can provide realistic Doppler lidar estimates of the gust factor, i.e. the ratio of the wind gust speed to the mean wind speed. The method reduced the bias in the Doppler lidar gust factors from 0.07 to 0.03, and the method can be further improved to reduce the bias by using a realistic estimate of turbulence. Wind gust measurements are often prone to outliers in the time series, because they represent the maximum of a (moving-averaged) horizontal wind speed. To assure the data quality in this study, we applied a filtering technique based on spike detection to remove possible outliers in the Doppler lidar data. We found that the spike detection-removal method clearly improved the wind gust measurements, both with and without the scaling method. Spike detection also outperformed the traditional Doppler lidar quality assurance method based on carrier-to-noise ratio, by removing additional unrealistic outliers present in the time series.

Atmospheric emissions, including particle number and size distribution, from a 726 MWth coal-fired power plant were studied experimentally from a power plant stack and flue-gas plume dispersing in the atmosphere. Experiments were conducted under two different flue-gas cleaning conditions. The results were utilized in a plume dispersion and dilution model taking into account particle formation precursor (H2SO4 resulted from the oxidation of emitted SO2) and assessment related to nucleation rates. The experiments showed that the primary emissions of particles and SO2 were effectively reduced by flue-gas desulfurization and fabric filters, especially the emissions of particles smaller than 200 nm in diameter. Primary pollutant concentrations reached background levels in 200–300 s. However, the atmospheric measurements indicated that new particles larger than 2.5 nm are formed in the flue-gas plume, even in the very early phases of atmospheric ageing. The effective number emission of nucleated particles were several orders of magnitude higher than the primary particle emission. Modelling studies indicate that regardless of continuing dilution of the flue gas, nucleation precursor (H2SO4 from SO2 oxidation) concentrations remain relatively constant. In addition, results indicate that flue-gas nucleation is more efficient than predicted by atmospheric aerosol modelling. In particular, the observation of the new particle formation with rather low flue-gas SO2 concentrations changes the current understanding of the air quality effects of coal combustion. The results can be used to evaluate optimal ways to achieve better air quality, particularly in polluted areas like India and China.

Ceilometer lidars are used for cloud base height detection, to probe aerosol layers in the atmosphere (e.g. detection of elevated layers of Saharan dust or volcanic ash) and to examine boundary layer dynamics. Sensor optics and acquisition algorithms can strongly influence the observed attenuated backscatter profiles; therefore, physical interpretation of the profiles can require corrections to be applied carefully. This study addresses the commonly deployed Vaisala CL31 ceilometers. Attenuated backscatter profiles are studied to evaluate the impact of both the generation of the hardware and version of the firmware. In response to this work and discussion within the CL31/TOPROF user community (TOPROF is a European COST Action aiming to harmonise remote sensing networks across Europe), Vaisala released new firmware (versions 1.72 & 2.03) for the CL31 sensors. These firmware versions are tested against previous versions showing that several artificial features introduced by the data processing have been removed. Hence, it is recommended to use this recent firmware if attenuated backscatter is to be analysed. To allow for consistent processing of historic data, correction procedures are developed that account for the range-dependent electronic background signal and other artefacts detected in data collected with older firmware. Recommendations are made for the processing of attenuated backscatter observed with Vaisala CL31 sensors, including the estimation of noise which is not provided in the standard CL31 output. Taking these aspects into account, attenuated backscatter profiles from Vaisala CL31 ceilometers are considered to provide valuable information for a range of applications including, for example, atmospheric boundary layer studies, detection of elevated aerosol layers, and model verification.