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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.

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.

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.

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.

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.

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.

This study focuses on the occurrence and type of clouds observed in West Africa, a subject that has been neither much documented nor quantified. It takes advantage of data collected above Niamey, Niger, in 2006 with the Atmospheric Radiation Measurement (ARM) Mobile Facility. A survey of cloud characteristics inferred from ground measurements is presented with a focus on their seasonal evolution and diurnal cycle. Four types of clouds are distinguished: high-level clouds, deep convective clouds, shallow convective clouds, and midlevel clouds. A frequent occurrence of the latter clouds located at the top of the Saharan air layer is highlighted. High-level clouds are ubiquitous throughout the period whereas shallow convective clouds are mainly noticeable during the core of the monsoon. The diurnal cycle of each cloud category and its seasonal evolution are investigated. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to demonstrate that these four cloud types (in addition to stratocumulus clouds over the ocean) are not a particularity of the Niamey region and that midlevel clouds are present over the Sahara during most of the monsoon season. Moreover, using complementary datasets, the radiative impact of each type of clouds at the surface level has been quantified in the short- and longwave domains. Midlevel clouds and anvil clouds have the largest impact, respectively, in longwave (about 15 W m−2) and shortwave (about 150 W m−2) radiation. Furthermore, midlevel clouds exert a strong radiative forcing during the spring at a time when the other cloud types are less numerous.

Ground-based remote-sensing observations from Atmospheric Radiation Measurement (ARM) and Cloud-Net sites are used to evaluate the clouds predicted by a weather forecasting and climate model. By evaluating the cloud predictions using separate measures for the errors in frequency of occurrence, amount when present, and timing, we provide a detailed assessment of the model performance, which is relevant to weather and climate time-scales. Importantly, this methodology will be of great use when attempting to develop a cloud parametrization scheme, as it provides a clearer picture of the current deficiencies in the predicted clouds. Using the Met Office Unified Model, it is shown that when cloud fractions produced by a diagnostic and a prognostic cloud scheme are compared, the prognostic cloud scheme shows improvements to the biases in frequency of occurrence of low, medium and high cloud and to the frequency distributions of cloud amount when cloud is present. The mean cloud profiles are generally improved, although it is shown that in some cases the diagnostic scheme produced misleadingly good mean profiles as a result of compensating errors in frequency of occurrence and amount when present. Some biases remain when using the prognostic scheme, notably the underprediction of mean ice cloud fraction due to the amount when present being too low, and the overprediction of mean liquid cloud fraction due to the frequency of occurrence being too high. Copyright © 2011 Royal Meteorological Society and British Crown Copyright, the Met Office

The calibration of the CloudSat spaceborne cloud radar has been thoroughly assessed using very accurate internal link budgets before launch, comparisons with predicted ocean surface backscatter at 94 GHz, direct comparisons with airborne cloud radars, and statistical comparisons with ground-based cloud radars at different locations of the world. It is believed that the calibration of CloudSat is accurate to within 0.5–1 dB. In the present paper it is shown that an approach similar to that used for the statistical comparisons with ground-based radars can now be adopted the other way around to calibrate other ground-based or airborne radars against CloudSat and/or to detect anomalies in long time series of ground-based radar measurements, provided that the calibration of CloudSat is followed up closely (which is the case). The power of using CloudSat as a global radar calibrator is demonstrated using the Atmospheric Radiation Measurement cloud radar data taken at Barrow, Alaska, the cloud radar data from the Cabauw site, Netherlands, and airborne Doppler cloud radar measurements taken along the CloudSat track in the Arctic by the Radar System Airborne (RASTA) cloud radar installed in the French ATR-42 aircraft for the first time. It is found that the Barrow radar data in 2008 are calibrated too high by 9.8 dB, while the Cabauw radar data in 2008 are calibrated too low by 8.0 dB. The calibration of the RASTA airborne cloud radar using direct comparisons with CloudSat agrees well with the expected gains and losses resulting from the change in configuration that required verification of the RASTA calibration.

In 2007, the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was operated for a nine-month period in the Murg Valley, Black Forest, Germany, in support of the Convective and Orographically-induced Precipitation Study (COPS). The synergy of AMF and COPS partner instrumentation was exploited to derive a set of high-quality thermodynamic and cloud property profiles with 30 s resolution. In total, clouds were present 72% of the time, with multi-layer mixed phase (28.4%) and single-layer water clouds (11.3%) occurring most frequently. A comparison with the Cloudnet sites Chilbolton and Lindenberg for the same time period revealed that the Murg Valley exhibits lower liquid water paths (LWPs; median = 37.5 g m −2 ) compared to the two sites located in flat terrain. In order to evaluate the derived thermodynamic and cloud property profiles, a radiative closure study was performed with independent surface radiation measurements. In clear sky, average differences between calculated and observed surface fluxes are less than 2% and 4% for the short wave and long wave part, respectively. In cloudy situations, differences between simulated and observed fluxes, particularly in the short wave part, are much larger, but most of these can be related to broken cloud situations. The daytime cloud radiative effect (CRE), i.e. the difference of cloudy and clear-sky net fluxes, has been analysed for the whole nine-month period. For overcast, single-layer water clouds, sensitivity studies revealed that the CRE uncertainty is likewise determined by uncertainties in liquid water content and effective radius. For low LWP clouds, CRE uncertainty is dominated by LWP uncertainty; therefore refined retrievals, such as using infrared and/or higher microwave frequencies, are needed. Copyright c � 2011 Royal Meteorological Society

A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from a balloon-borne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude. This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of ε can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations.

In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.

Cloud radar and lidar can be used to evaluate the skill of numerical weather prediction models in forecasting the timing and placement of clouds, but care must be taken in choosing the appropriate metric of skill to use due to the non- Gaussian nature of cloud-fraction distributions. We compare the properties of a number of different verification measures and conclude that of existing measures the Log of Odds Ratio is the most suitable for cloud fraction. We also propose a new measure, the Symmetric Extreme Dependency Score, which has very attractive properties, being equitable (for large samples), difficult to hedge and independent of the frequency of occurrence of the quantity being verified. We then use data from five European ground-based sites and seven forecast models, processed using the 'Cloudnet' analysis system, to investigate the dependence of forecast skill on cloud fraction threshold (for binary skill scores), height, horizontal scale and (for the Met Office and German Weather Service models) forecast lead time. The models are found to be least skillful at predicting the timing and placement of boundary-layer clouds and most skilful at predicting mid-level clouds, although in the latter case they tend to underestimate mean cloud fraction when cloud is present. It is found that skill decreases approximately inverse-exponentially with forecast lead time, enabling a forecast 'half-life' to be estimated. When considering the skill of instantaneous model snapshots, we find typical values ranging between 2.5 and 4.5 days. Copyright c � 2009 Royal Meteorological Society

In this paper, observations by a ground-based vertically pointing Doppler lidar and sonic anemometer are used to investigate the diurnal evolution of boundary-layer turbulence in cloudless, cumulus and stratocumulus conditions. When turbulence is driven primarily by surface heating, such as in cloudless and cumulus-topped boundary layers, both the vertical velocity variance and skewness follow similar profiles, on average, to previous observational studies of turbulence in convective conditions, with a peak skewness of around 0.8 in the upper third of the mixed layer. When the turbulence is driven primarily by cloud-top radiative cooling, such as in the presence of nocturnal stratocumulus, it is found that the skewness is inverted in both sign and height: its minimum value of around −0.9 occurs in the lower third of the mixed layer. The profile of variance is consistent with a cloud-top cooling rate of around 30Wm−2. This is also consistent with the evolution of the thermodynamic profile and the rate of growth of the mixed layer into the stable nocturnal boundary layer from above. In conditions where surface heating occurs simultaneously with cloud-top cooling, the skewness is found to be useful for diagnosing the source of the turbulence, suggesting that long-term Doppler lidar observations would be valuable for evaluating boundary-layer parametrization schemes. Copyright c 2009 Royal Meteorological Society

This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Height-dependent RMS accuracies of temperature (humidity) ranging from ∼0.3 to 0.9 K (0.5–0.8 g m−3) in the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined.

Atmospheric emissions, including particle number and size distribution, of a 726 MWth coal-fired power plant were studied experimentally from power plant stack and from flue gas plume dispersing in the atmosphere. Experiments were conducted under two different flue gas cleaning conditions. The results were utilised in a plume dispersion and dilution modelling taking into account nucleation particle precursor (H2SO4 resulted from the oxidation of emitted SO2) formation and assessment related to nucleation rates. The experiments showed that the primary emissions of particles and SO2 were effectively reduced by flue gas desulphurization and fabric filters, especially the emissions of particles smaller than 200 nm in diameter. Primary pollutant concentrations reached background levels in 200–300 seconds. However, the atmospheric measurements indicated that new particles 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, flue gas nucleation is more efficient than natural atmospheric nucleation. Especially, the observation of the new particle formation with rather low flue gas SO2 concentrations changes the current understanding on the air quality effects of coal-combustion. The results can be used to evaluate the optimal ways to achieve better air quality particularly in polluted areas like India and China.

The Cloudnet project aims to provide a systematic evaluation of clouds in forecast and climate models by comparing the model output with continuous ground-based observations of the vertical profiles of cloud properties. In the models, the properties of clouds are simplified and expressed in terms of the fraction of the model grid box, which is filled with cloud, together with the liquid and ice water content of the clouds. These models must get the clouds right if they are to correctly represent both their radiative properties and their key role in the production of precipitation, but there are few observations of the vertical profiles of the cloud properties that show whether or not they are successful. Cloud profiles derived from cloud radars, ceilometers, and dual-frequency microwave radiometers operated at three sites in France, Netherlands, and the United Kingdom for several years have been compared with the clouds in seven European models. The advantage of this continuous appraisal is that the feedback on how new versions of models are performing is provided in quasi-real time, as opposed to the much longer time scale needed for in-depth analysis of complex field studies. Here, two occasions are identified when the introduction of new versions of the ECMWF and Météo-France models leads to an immediate improvement in the representation of the clouds and also provides statistics on the performance of the seven models. The Cloudnet analysis scheme is currently being expanded to include sites outside Europe and further operational forecasting and climate models.

Stratocumulus is one of the most common cloud types globally, with a profound effect on the earth’s radiation budget, and the drizzle process is fundamental in understanding the evolution of these boundary layer clouds. In this paper a combination of 94-GHz Doppler radar and backscatter lidar is used to investigate the microphysical properties of drizzle falling below the base of stratocumulus clouds. The ratio of the radar to lidar backscatter power is proportional to the fourth power of mean size, and so potentially it can provide an accurate size estimate. Information about the shape of the drop size distribution is then inferred from the Doppler spectral width. The algorithm estimates vertical profiles of drizzle parameters such as liquid water content, liquid water flux, and vertical air velocity, assuming that the drizzle size spectrum may be represented by a gamma distribution. The depletion time scale of cloud liquid water through the drizzle process can be estimated when the liquid water path of the cloud is available from microwave radiometers, and observations suggest that this time scale varies from a few days in light drizzle to a few hours in strong drizzle events. Radar and lidar observations from Chilbolton (in southern England) and aircraft size spectra taken during the Atlantic Stratocumulus Transition Experiment have both been used to derive the following power-law relationship between liquid water flux (LWF) (g m−2 s−1) and radar reflectivity (Z) (mm6 m−3): LWF = 0.0093Z0.69. This relation is valid for frequencies up to 94 GHz and therefore would allow a forthcoming spaceborne radar to measure liquid water flux around the globe to within a factor of 2 for values of Z above −20 dBZ.

In this paper a technique for autocalibration of a cloud lidar is demonstrated. It is shown that the lidar extinction-to-backscatter ratio derived from integrated backscatter for stratocumulus is, in the absence of drizzle, constrained to a theoretical value of 18.8 ± 0.8 sr at a wavelength of 905 nm. The lidar can be calibrated by scaling the backscatter signal so that the observed lidar ratio matches the theoretical value when suitable conditions of stratocumulus are available. For a beam divergence of 1–1.5 mrad, multiple scattering introduces an uncertainty of about 10% into the calibration and for a narrow-beam ground-based lidar, with negligible multiple scattering, calibration may be possible to better than 5%. Some examples of the mean lidar ratio of supercooled liquid water layers and ice clouds inferred using this technique are also shown.

In part I it was demonstrated that supercooled liquid-water clouds can occur in the form of thin but radiatively significant layers that are distinctive in lidar imagery due to their high backscatter coefficient. In this paper, 18 months of near-continuous lidar data from two midlatitude locations are analysed to estimate the frequency of occurrence of such clouds as a function of temperature. An algorithm is developed that uses the integrated backscatter to identify liquid-water clouds with a visible optical depth of greater than 0.7 (i.e. those that scatter more than half of the incident radiation), and is found to compare favourably with microwave-radiometer measurements of liquid-water path. From data taken with a lidar pointing at 5° from zenith, the frequency of supercooled liquid-water layers over Chilbolton in southern England is found to fall steadily with temperature; 27% of clouds between −5°C and −10°C are found to contain significant liquid water, falling to only 6% of clouds observed between −25°C and −30°C. The horizontal extent of the layers typically ranges between 20 and 70 km. When the lidar is pointed directly at zenith, specular reflection by horizontally aligned plate crystals is found to bias the statistics between −10°C and −20°C. The importance of supercooled liquid-water clouds in the radiation budget is reduced when thick ice clouds are present above them, so we then use simultaneous cloud radar data to estimate the optical depth of any cloud above. It is found that around 30% of supercooled liquid-water clouds with temperatures between 0°C and −20°C have ice above with a visible optical depth in excess of 0.5, falling to 10% between −20°C and −30°C. Given the substantial optical depth of the supercooled water itself, we conclude that in the majority of cases when supercooled water is present, it will dominate the radiative properties of the cloud profile. Finally, we compare the occurrence of supercooled-liquid clouds with the amounts found in the models of the UK Met Office and the European Centre for Medium-Range Weather Forecasts (ECMWF). Both models are found to produce too much supercooled liquid at warmer temperatures and too little at colder temperatures (with virtually none being simulated below −20°C), although the occurrence of supercooled cloud is far higher in the ECMWF model than the Met Office model. The observations in this paper are limited to one climatic zone but the forthcoming spaceborne lidars will be able to extend these comparisons to the whole globe. Copyright © 2003 Royal Meteorological Society.