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For understanding Arctic climate change, it is critical to quantify and address uncertainties in climate data records on clouds and radiative fluxes derived from long-term passive satellite observations. A unique set of observations collected during the PS106 expedition of the research vessel Polarstern (28 May to 16 July 2017) by the OCEANET facility, is exploited here for this purpose and compared with the CERES SYN1deg ed. 4.1 satellite remote-sensing products. Mean cloud fraction (CF) of 86.7 % for CERES SYN1deg and 76.1 % for OCEANET were found for the entire cruise. The difference of CF between both data sets is due to different spatial resolution and momentary data gaps, which are a result of technical limitations of the set of shipborne instruments. A comparison of radiative fluxes during clear-sky (CS) conditions enables radiative closure (RC) for CERES SYN1deg products by means of independent radiative transfer simulations. Several challenges were encountered to accurately represent clouds in radiative transfer under cloudy conditions, especially for ice-containing clouds and low-level stratus (LLS) clouds. During LLS conditions, the OCEANET retrievals were particularly compromised by the altitude detection limit of 155 m of the cloud radar. Radiative fluxes from CERES SYN1deg show a good agreement with ship observations, having a bias (standard deviation) of −6.0 (14.6) and 23.1 (59.3) W m−2 for the downward longwave (LWD) and shortwave (SWD) fluxes, respectively. Based on CERES SYN1deg products, mean values of the radiation budget and the cloud radiative effect (CRE) were determined for the PS106 cruise track and the central Arctic region (70–90∘ N). For the period of study, the results indicate a strong influence of the SW flux in the radiation budget, which is reduced by clouds leading to a net surface CRE of −8.8 and −9.3 W m−2 along the PS106 cruise and for the entire Arctic, respectively. The similarity of local and regional CRE supports the consideration that the PS106 cloud observations can be representative of Arctic cloudiness during early summer.

Quantifying the role of clouds in the Earth radiation budget is essential for improving our understanding of the drivers and feedbacks of climate change. This holds in particular for the Arctic, the region currently undergoing the most rapid changes. This region, however, also poses significant challenges to remote-sensing retrievals of clouds and radiative fluxes, introducing large uncertainties in current climate data records. In particular, low-level stratiform clouds are common in the Arctic but are, due to their low altitude, challenging to observe and characterize with remote-sensing techniques. The availability of reliable ground-based observations as reference is thus of high importance. In the present study, radiative transfer simulations based on state-of-the-art ground-based remote sensing of clouds are contrasted to surface radiative flux measurements to assess their ability to constrain the cloud radiative effect. Cloud radar, lidar, and microwave radiometer observations from the PS106 cruise in the Arctic marginal sea ice zone in summer 2017 were used to derive cloud micro- and macrophysical properties by means of the instrument synergy approach of Cloudnet. Closure of surface radiative fluxes can only be achieved by a realistic representation of the low-level liquid-containing clouds in the radiative transfer simulations. The original, likely erroneous, representation of these low-level clouds in the radiative transfer simulations let to errors in the cloud radiative effect of 43 W m-2. The present study highlights the importance of jointly improving retrievals for low-level liquid-containing clouds which are frequently encountered in the high Arctic, together with observational capabilities both in terms of cloud remote sensing and radiative flux observations. Concrete suggestions for achieving these goals are provided.

An advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition to continuously monitor aerosol and cloud layers in the central Arctic up to 30 km height. The expedition lasted from September 2019 to October 2020 and measurements were mostly taken between 85 and 88.5∘ N. The lidar was integrated into a complex remote-sensing infrastructure aboard the Polarstern. In this article, novel lidar techniques, innovative concepts to study aerosol–cloud interaction in the Arctic, and unique MOSAiC findings will be presented. The highlight of the lidar measurements was the detection of a 10 km deep wildfire smoke layer over the North Pole region between 7–8 km and 17–18 km height with an aerosol optical thickness (AOT) at 532 nm of around 0.1 (in October–November 2019) and 0.05 from December to March. The dual-wavelength Raman lidar technique allowed us to unambiguously identify smoke as the dominating aerosol type in the aerosol layer in the upper troposphere and lower stratosphere (UTLS). An additional contribution to the 532 nm AOT by volcanic sulfate aerosol (Raikoke eruption) was estimated to always be lower than 15 %. The optical and microphysical properties of the UTLS smoke layer are presented in an accompanying paper (Ohneiser et al., 2021). This smoke event offered the unique opportunity to study the influence of organic aerosol particles (serving as ice-nucleating particles, INPs) on cirrus formation in the upper troposphere. An example of a closure study is presented to explain our concept of investigating aerosol–cloud interaction in this field. The smoke particles were obviously able to control the evolution of the cirrus system and caused low ice crystal number concentration. After the discussion of two typical Arctic haze events, we present a case study of the evolution of a long-lasting mixed-phase cloud layer embedded in Arctic haze in the free troposphere. The recently introduced dual-field-of-view polarization lidar technique was applied, for the first time, to mixed-phase cloud observations in order to determine the microphysical properties of the water droplets. The mixed-phase cloud closure experiment (based on combined lidar and radar observations) indicated that the observed aerosol levels controlled the number concentrations of nucleated droplets and ice crystals.

From 25 May to 21 July 2017, the research vessel Polarstern performed the cruise PS106 to the high Arctic in the region north and northeast of Svalbard. The mobile remote-sensing platform OCEANET was deployed aboard Polarstern. Within a single container, OCEANET houses state-of-the-art remote-sensing equipment, including a multiwavelength Raman polarization lidar PollyXT and a 14-channel microwave radiometer HATPRO (Humidity And Temperature PROfiler). For the cruise PS106, the measurements were supplemented by a motion-stabilized 35 GHz cloud radar Mira-35. This paper describes the treatment of technical challenges which were immanent during the deployment of OCEANET in the high Arctic. This includes the description of the motion stabilization of the cloud radar Mira-35 to ensure vertical-pointing observations aboard the moving Polarstern as well as the applied correction of the vessels heave rate to provide valid Doppler velocities. The correction ensured a leveling accuracy of ±0.5∘ during transits through the ice and an ice floe camp. The applied heave correction reduced the signal induced by the vertical movement of the cloud radar in the PSD of the Doppler velocity by a factor of 15. Low-level clouds, in addition, frequently prevented a continuous analysis of cloud conditions from synergies of lidar and radar within Cloudnet, because the technically determined lowest detection height of Mira-35 was 165 m above sea level. To overcome this obstacle, an approach for identification of the cloud presence solely based on data from the near-field receiver of PollyXT at heights from 50 m and 165 m above sea level is presented. We found low-level stratus clouds, which were below the lowest detection range of most automatic ground-based remote-sensing instruments during 25 % of the observation time. We present case studies of aerosol and cloud studies to introduce the capabilities of the data set. In addition, new approaches for ice crystal effective radius and eddy dissipation rates from cloud radar measurements and the retrieval of aerosol optical and microphysical properties from the observations of PollyXT are introduced.

International audience; With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

In den Atmosphärenwissenschaften spielt die Strahlungsbilanz der Erde eine wichtige Rolle für unser Verständnis des Klimasystems. Hier liefern ausgereifte Satellitenprodukte dekadische Klimazeitreihen mit einer so hohen Genauigkeit, dass z.B. Änderungen im Zusammenhang mit dem Klimawandel detektiert werden können. Dies gilt insbesondere auch für die solaren Strahlungsflüsse an der Erdoberfläche. Beim Vergleich dieser Satellitenprodukte mit instantanen Beobachtungen der Strahlung am Erdboden sind jedoch oft erhebliche Abweichungen feststellbar, die hauptsächlich durch kleinskalige Variabilität in der räumlichen Struktur von Wolken und ihrer Strahlungswirkung verursacht werden. Hier ist auch zu bedenken, dass Bodenbeobachtungen fast einer Punktmessung entsprechen, während Satellitenpixel eine Fläche in der Größenordnung von Quadratkilometern abtasten. Gleichzeitig basieren aktuelle Satellitenprodukte auf der Annahme des 1-dimensionalen Strahlungstransports, während 3D Strahlungseffekte bisher höchstens in Form empirischer Bias-Korrekturen Berücksichtigung finden. So steht eine Abschätzung der Größe systematischer Abweichungen in den Strahlungsflüssen durch 3D-Strahlungseffekte von Wolken auf globaler Skala aus. Solarenergie ist gleichzeitig eine wichtige Säule der Energiewende. Hier wird zum Beispiel Information für die Planung von Solarkraftwerken, die Netzintegration von Stromerzeugung aus Photovoltaik-Anlagen sowie das Lademanagement von Batteriespeichern benötigt, in Form möglichst genaue Vorhersagen der Solarstrahlung auf Zeitskalen von Minuten bis hin zu mehreren Tagen. Gerade für kurze Vorhersagehorizonte liefern dabei in naher Zukunft die Meteosat-Satelliten der 3. Generation deutlich verbesserte Beobachtungen. In dem Beitrag wird dargelegt, dass ein besseres Verständnis der kleinskaligen Variabilität von Solarstrahlung von Wolken für eine optimale Nutzung dieser Beobachtungen essentiell ist. Anhand von Beobachtungen mit einem räumlich engmaschigen Netzwerk von Pyranometern wird gezeigt, dass solche Netzwerke in Kombination mit 3D-Strahlungsmodellen einen wichtigen Beitrag hierzu leisten können. Diese Untersuchungen tragen nicht nur zu einem verbesserten Verständnis der Auswirkungen von kleinskaliger Wolkenvariabilität auf die Strahlungsbilanz bei, sondern auch der Grenzen von Kurzfristvorhersagen der Solarstrahlung.

The large number of unsolved questions concerning the interaction between aerosol particles and clouds and corresponding indirect effects on precipitation and radiative transfer demand new measurement strategies and systems to resolve the atmospheric processes involved. Obtaining synergistic information about cloud and aerosol properties from multi–instrument and hence multi–sensor observations is a key approach to overcome the current lack of knowledge. Motivated by these needs, the mobile multi–instrument platform Leipzig Aerosol and Cloud Remote Observations System LACROS was set-up in 2011 by Leibniz Institute for Tropospheric Research (TROPOS). LACROS nowadays is the central component of a sophisticated framework of synergistic state-of-the-art measurement techniques and methodologies, embedded into an environment of comprehensive data management. The current setup of LACROS comprises a set of state-of-the-art remote-sensing instruments such as a 35-GHz scanning polarimetric cloud radar, multi-wavelength polarization Raman lidars, Doppler lidar, micro rain radar, microwave radiometer, laser disdrometer, as well as sensors for direct and diffuse downwelling solar and terrestrial radiation. All instruments are installed within customized sea-freight containers. This ensures a highest-possible mobility of the whole set of instruments. LACROS is a central mobile exploratory platform of the European Union Aerosol, Clouds, and Trace Gases Research Infrastructure (ACTRIS, http://www.actris.net). A variety of ways for physical, remote, and virtual access to the LACROS capabilities are provided via the European Union project ATMO-ACCESS (https://www.atmo-access.eu). LACROS measurements focus on three main tasks: (1) Investigation of mixed-phase cloud processes by exploiting co‐located remote-sensing observations of microphysical properties and radiative effects of aerosols and clouds and their interactions. (2) Instrument validation and development of algorithms and new measurement techniques for cloud and aerosol microphysics retrievals such as, i.e., dual‐field‐of‐view lidar to derive cloud droplet size information, or retrievals of aerosol microphysical properties from combined lidar and Sun photometer measurements. (3) Field deployments in key regions of atmospheric research, where the processes under investigation are already naturally constrained and observations can ideally be combined with in-situ observations or model simulations. This contribution will present the current setup of LACROS and its recent deployments in Leipzig, the Netherlands, Cyprus and southern Chile, results of aerosol-cloud-interaction studies by means of both, case studies and multi-site long-term statistics, as well as an overview on the current and future involvement of LACROS in cal/val activities of new methods and satellite missions.

In this study Lagrangian large‐eddy simulation of cloudy mixed layers in evolving warm air masses in the Arctic is constrained by in situ observations from the recent PASCAL field campaign. A key novelty is that time dependence is maintained in the large‐scale forcings. An iterative procedure featuring large‐eddy simulation on microgrids is explored to calibrate the case setup, inspired by and making use of the typically long memory of Arctic air masses for upstream conditions. The simulated mixed‐phase clouds are part of a turbulent mixed layer that is weakly coupled to the surface and is occasionally capped by a shallow humidity layer. All eight simulated mixed layers exhibit a strong time evolution across a range of time scales, including diurnal but also synoptic fingerprints. A few cases experience rapid cloud collapse, coinciding with a rapid decrease in mixed‐layer depth. To gain insight, composite budget analyses are performed. In the mixed‐layer interior the heat and moisture budgets are dominated by turbulent transport, radiative cooling, and precipitation. However, near the thermal inversion the large‐scale vertical advection also contributes significantly, showing a distinct difference between subsidence and upsidence conditions. A bulk mass budget analysis reveals that entrainment deepening behaves almost time‐constantly, as long as clouds are present. In contrast, large‐scale subsidence fluctuates much more strongly and can both counteract and boost boundary‐layer deepening resulting from entrainment. Strong and sudden subsidence events following prolonged deepening periods are found to cause the cloud collapses, associated with a substantial reduction in the surface downward longwave radiative flux.

Central Europe has a vital and extensive meteorological research community comprising national weather services, universities, and research organizations and institutes. Nearly all of them are involved in the open scientific questions regarding clouds and precipitation processes. The research activities include observations (from in situ ground-based remote sensing radio soundings to satellite-based observations), model development on all scales (from direct numerical simulations to global climate models), and other activities. With Germany as an example our first objective is to show the large amount and the diversity of observations regarding clouds and precipitation. The goal is to give an overview of existing measurements and datasets to show the benefit of combining the different information from a variety of observations. Up to now the access to and the usage of these datasets from different sources was not straightforward, due to the issue of missing data and archiving standards for observational data. This then motivates our second objective, which is to introduce our solution for this issue—the novel Standardized Atmospheric Measurement Data archive (SAMD). SAMD is one of the outcomes of the German research initiative High Definition Clouds and Precipitation for Advancing Climate Prediction [HD(CP)2]. The goal of SAMD is an easy-to-use approach for both data producers and archive users. Therefore the archive provides observational data in the common Climate Forecast (CF) Conventions format and makes it available to the broader public. SAMD offers highly standardized quality-controlled data and metadata for a wide range of instruments, with open access, which makes this novel archive important for the research community.

A consortium of polar scientists combined observational forces in a field campaign of unprecedented complexity to uncover the secrets of clouds and their role in Arctic amplification. Two research aircraft, an icebreaker research vessel, an ice-floe camp including an instrumented tethered balloon, and a permanent ground-based measurement station were employed in this endeavour. Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the ”Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD)” aircraft campaign, and the ”Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL (PASCAL)” ice breaker expedition. Both observational studies were performed in the framework of the German ”ArctiC Amplification:Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” project. They took place in the vicinity of Svalbard (Norway) in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: Cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent-dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft, the icebreaker research vessel (RV) Polarstern, an ice-floe camp including an instrumented tethered balloon, and the permanent, ground-based measurement station at Ny-Ålesund (Svalbard) were employed to observe Arctic low and mid-level, mixed-phase clouds, and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in-situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above RV Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results, and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.

Community-based participatory research initiatives such as “hackAir”, “luftdaten.info”, “senseBox”, “CAPTOR”, “CurieuzeNeuzen Vlaanderen”, “communityAQ”, and “Healthy Air, Healthier Children” campaign among many others for mitigating short-lived climate pollutants (SLCPs) and improving air quality have reported progressive knowledge transfer results. These research initiatives provide the research community with the practical four-element state-of-the-art method for citizen science. For the preparation-, measurements-, data analysis-, and scientific support-elements that collectively present the novel knowledge transfer method, the Luft-Leipzig project results are presented. This research contributes to science by formulating a novel method for SLCP mitigation projects that employ citizen scientists. The Luft-Leipzig project results are presented to validate the four-element state-of-the-art method. The method is recommended for knowledge transfer purposes beyond the scope of mitigating short-lived climate pollutants (SLCPs) and improving air quality.

Clouds influence the shortwave (SW) and longwave (LW) radiative fluxes, thereby affecting the radiative budget by enhancing or diminishing the heat budget at the surface (SFC), at the top of the atmosphere (TOA), and through the atmosphere. In the Arctic, their complexity enhances due to their intrinsic interactions with several physical processes and feedback mechanisms.With the aim to further investigate the Arctic system, the project (AC)³ (Arctic Amplification: Climate Relevant Atmospheric and SurfaCe Processes and Feedback Mechanisms) established two major field campaigns in summer of 2017. Both performed in situ and remote sensing observations over the ocean with PS106 and in the air with ACLOUD (Macke and Flores, 2018, Wendisch et al., 2019). The observations collected during PS106 are considered to investigate the effects and influence of clouds in the radiation budget for the summer central Arctic.The PS106 expedition took place aboard the German research vessel Polarstern which was equipped with active and passive remote sensing instrumentation (Griesche et al., 2020). The synergistic operation of this instrumentation was used to derive macro and microphysical properties of clouds by applying the Cloudnet algorithm. These retrievals together with vertical profiles of temperature and relative humidity are used as input to the Rapid Radiative Transfer Model for GCM applications (RRTMG). The results of the broadband SW and LW radiative simulations along with hourly satellite products from Clouds and the Earth’s Radiant Energy System (CERES) Synoptic 1-degree Ed.4. are compared to ship-borne observations indicating a better agreement for single-level liquid clouds than for more challenging sky conditions. The results of the comparison bring sufficient information to discuss a radiative closure assessment for selected case studies and for the entire PS106 expedition. Based on these results the cloud radiative effect (CRE) is calculated indicating a net effect of -8.1 W/m².The study is extended by applying this methodology to the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC). Preliminary results will be presented for the first leg which will allow a direct comparison of the contrasting properties of cloud radiative effects during summer and winter season.ReferencesGriesche, H. J., and coauthors. (2020): Application of the shipborne remote sensing supersite OCEANETfor profiling of Arctic aerosols and clouds during Polarstern cruise PS106, Atmos. Meas. Tech., 13,5335–5358, https://doi.org/10.5194/amt-13-5335-2020Macke, A. and Flores, H. (2018): The Expeditions PS106/1 and 2 of the Research Vessel POLARSTERNto the Arctic Ocean in 2017 , Berichte zur Polar- und Meeresforschung = Reports on polar and marineresearch, Bremerhaven, Alfred Wegener Institute for Polar and Marine Research, 719 , 171 p.http://hdl.handle.net/10013/epic.4ff2b0cd-1b2f-4444-a97f-0cd9f1d917abWendisch, M., and coauthors. (2019): The Arctic Cloud Puzzle: Using ACLOUD/PASCAL MultiplatformObservations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification. Bull. Amer.Meteor. Soc., 100, 841–871, https://doi.org/10.1175/BAMS-D-18-0072.1

An advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, lasting from September 2019 to October 2020, to contiuously monitor aerosol and cloud layers in the Central Arctic up to 30 km height at latitudes mostly between 85° N and 88.5° N. The lidar was integrated in a complex remote sensing infrastructure aboard Polarstern. Modern aerosol lidar methods and new lidar techniques and concepts to explore aerosol-cloud interaction were applied for the first time in the Central Arctic. Aim of the introductory article is to provide an overview of the observational spectrum of the lidar products for representative measurement cases. Highlight of the lidar measurements was the detection of a 10 km deep wildfire smoke layer over the North Pole area from, on average, 7 km to 17 km height with an aerosol optical thickness (AOT) at 532 nm around 0.1 (in October–November 2019) and 0.05 from December to mid of March 2020. The wildfire smoke was trapped within the extraordinarily strong polar vortex and remained detectable until the beginning of May 2020. Arctic haze was also monitored and characterized in terms of backscatter, extinction, and extinction-to-backscatter ratio at 355 and 532 nm. High lidar ratios from 60–100 sr in lofted mixed haze and smoke plumes are indicative for the presence of strongly light-absorbing fine-mode particles. The AOT at 532 nm was of the order of 0.025 for the tropospheric haze layers. In addition, so-called cloud closure experiments were applied to Arctic mixed-phase cloud and cirrus observations. The good match between cloud condensation nucleus concentration (CCNC) and cloud droplet number concentration (CDNC) and, on the other hand, between ice-nucleating particle concentration (INPC) and ice crystal number concentration (ICNC) indicated a clear influence of aerosol particles on the evolution of the cloud systems. CDNC was mostly between 20 and 100 cm−3 in the liquid-water dominated cloud top layer. ICNC was of the order of 0.1–1 L−1. The study of the impact of wildfire smoke particles on cirrus formation revealed that heterogeneous ice formation with smoke particles (organic aerosol particles) as INPs may have prevailed. ICNC values of 10–40 L−1 were clearly below ICNC levels that would indicate homogeneous freezing.

Air pollution, which kills an estimated 7 million people every year, is one of the greatest environmental health risks of our times. Finding solutions to this threat poses challenges to practitioners and policymakers alike. Increasing awareness on the benefits of transdisciplinary research in solution-oriented sustainable development projects has led to the establishment of the research project &ldquo, A Transdisciplinary Approach to Mitigate Emissions of Black Carbon&rdquo, (TAME-BC). This paper introduces the TAME-BC research setup that took place with Metro Manila, Philippines, case study. The approach integrates BC measurements with technological, socio-political, and health aspects to improve the scientific state of the art, policymaking, transport sector planning, and clinical studies related to air pollution health effects. The first pillar in the setup presents an (1) air quality assessment through aerosol measurements and instrumentation, complemented by a (2) description and assessment of the current policies, technologies, and practices of the transport sector that is responsible for pollution levels in the Philippines, as well as a (3) BC exposure and associated health impacts assessment. The fourth pillar is intercrossing, fostering (4) knowledge co-creation through stakeholder involvement across scales. We argue that this transdisciplinary approach is useful for research endeavors aiming for emission mitigation in rapidly urbanizing regions beyond Metro Manila.

The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1 km2 compared to the standard 3×3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 µm, 0.8 µm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 µm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 µm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

The authors would like to make the following corrections about the published paper [...]

The HD(CP)2 Observational Prototype Experiment (HOPE) was performed as a major 2-month field experiment in Jülich, Germany, in April and May 2013, followed by a smaller campaign in Melpitz, Germany, in September 2013. HOPE has been designed to provide an observational dataset for a critical evaluation of the new German community atmospheric icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface–atmospheric boundary layer exchange, cloud and precipitation processes, as well as sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. This paper summarizes the instrument set-ups, the intensive observation periods, and example results from both campaigns. HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3 of them provide temperature, 3 of them water vapour, and all of them particle backscatter data), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 sun photometers operated at different sites, some of them in synergy. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in situ observations in the atmospheric column and at the surface. HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds, and precipitation with high spatial and temporal resolution within a cube of approximately 10 × 10 × 10 km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets have been made available through a dedicated data portal. First applications of HOPE data for model evaluation have shown a general agreement between observed and modelled boundary layer height, turbulence characteristics, and cloud coverage, but they also point to significant differences that deserve further investigations from both the observational and the modelling perspective.

The realistic representation of low-level clouds, including their radiative effects, in atmospheric models remains challenging. A sensitivity study is presented to establish a conceptual approach for the evaluation of low-level clouds and their radiative impact in a highly resolved atmospheric model. Considering simulations for six case days, the analysis supports the notion that the properties of clouds more closely match the assumptions of the sub-adiabatic rather than the vertically homogeneous cloud model, suggesting its use as the basis for evaluation. For the considered cases, 95.7 % of the variance in cloud optical thickness is explained by the variance in the liquid water path, while the droplet number concentration and the sub-adiabatic fraction contribute only 3.5 % and 0.2 % to the total variance, respectively. A mean sub-adiabatic fraction of 0.45 is found, which exhibits strong inter-day variability. Applying a principal component analysis and subsequent varimax rotation to the considered set of nine properties, four dominating modes of variability are identified, which explain 97.7 % of the total variance. The first and second components correspond to the cloud base and top height, and to liquid water path, optical thickness, and cloud geometrical extent, respectively, while the cloud droplet number concentration and the sub-adiabatic fraction are the strongest contributors to the third and fourth components. Using idealized offline radiative transfer calculations, it is confirmed that the shortwave and longwave cloud radiative effects exhibit little sensitivity to the vertical structure of clouds. This reconfirms, based on an unprecedented large set of highly resolved vertical cloud profiles, that the cloud optical thickness and the cloud top and bottom heights are the main factors dominating the shortwave and longwave radiative effect of clouds and should be evaluated together with radiative fluxes using observations to attribute model deficiencies in the radiative fluxes to deficiencies in the representation of clouds. Considering the different representations of cloud microphysical processes in atmospheric models, the analysis has been further extended and the deviations between the radiative impact of the single- and double-moment schemes are assessed. Contrasting the shortwave cloud radiative effect obtained from the double-moment scheme to that of a single-moment scheme, differences of about ∼40 W m−2 and significant scatter are observed. The differences are attributable to a higher cloud albedo resulting from the high values of droplet number concentration in particular in the boundary layer predicted by the double-moment scheme, which reach median values of around ∼600 cm−3.

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simu-lations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circula-tion and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change.

The role of clouds in recent Arctic warming is not fully understood, including their effects on the shortwave radiation and the surface energy budget. To investigate relevant small-scale processes in detail, an intensive field campaign was conducted during early summer in the central Arctic during the Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL) drifting ice floe station. During this campaign, the small-scale spatiotemporal variability of global irradiance was observed for the first time on an ice floe with a dense network of autonomous pyranometers. 15 stations were deployed covering an area of 0.83 km × 1.3 km from June 4–16, 2017. This unique, open-access dataset is described here, and an analysis of the spatiotemporal variability deduced from this dataset is presented for different synoptic conditions. Based on additional observations, 5 typical sky conditions were identified and used to determine the values of the mean and variance of atmospheric global transmittance for these conditions. Overcast conditions were observed 39.6 % of the time predominantly during the first week, with an overall mean transmittance of 0.47. The second-most frequent conditions corresponded to multi-layer clouds (32.4 %) which prevailed in particular during the second week, with a mean transmittance of 0.43. Broken clouds had a mean transmittance of 0.61 and a frequency of occurrence of 22.1 %. Finally, the least frequent sky conditions were thin clouds and cloudless conditions, which both had a mean transmittance of 0.76, and occurrence frequencies of 3.5 % and 2.4 %, respectively. For overcast conditions, lower global irradiance was observed for stations closer to the ice edge, likely attributable to the low surface albedo of dark open water, and a resulting reduction of multiple reflections between the surface and cloud base. Using a wavelet-based multi-resolution analysis, power spectra of the time-series of atmospheric transmittance were compared for single-station and spatially averaged observations, and for different sky conditions. It is shown that both the absolute magnitude and the scale-dependence of variability contains characteristic features for the different sky conditions.

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.

The polarization state of electromagnetic radiation scattered by atmospheric particles such as aerosols, cloud droplets, or ice crystals contains much more information about the optical and microphysical properties than the total intensity alone. For this reason an increasing number of polarimetric observations are performed from space, from the ground and from aircraft. Polarized radiative transfer models are required to interpret and analyse these measurements and to develop retrieval algorithms exploiting polarimetric observations. In the last years a large number of new codes have been developed, mostly for specific applications. Benchmark results are available for specific cases, but not for more sophisticated scenarios including polarized surface reflection and multi-layer atmospheres. The International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to fill this gap. This paper presents the results of the first phase A of the IPRT project which includes ten test cases, from simple setups with only one layer and Rayleigh scattering to rather sophisticated setups with a cloud embedded in a standard atmosphere above an ocean surface. All scenarios in the first phase A of the intercomparison project are for a one-dimensional plane–parallel model geometry. The commonly established benchmark results are available at the IPRT website ( http://www.meteo.physik.uni-muenchen.de/iprt ).

International audience; Initially unpolarized solar radiation becomes polarized by scattering in the Earth's atmosphere. In particular molecular scattering (Rayleigh scattering) polarizes electromagnetic radiation, but also scattering of radiation at aerosols, cloud droplets (Mie scattering) and ice crystals polarizes. Each atmospheric constituent produces a characteristic polarization signal, thus spectro-polarimetric measurements are frequently employed for remote sensing of aerosol and cloud properties. Retrieval algorithms require efficient radiative transfer models. Usually, these apply the plane-parallel approximation (PPA), assuming that the atmosphere consists of horizontally homogeneous layers. This allows to solve the vector radiative transfer equation (VRTE) efficiently. For remote sensing applications, the radiance is considered constant over the instantaneous field-of-view of the instrument and each sensor element is treated independently in plane-parallel approximation, neglecting horizontal radiation transport between adjacent pixels (Independent Pixel Approximation, IPA). In order to estimate the errors due to the IPA approximation, three-dimensional (3D) vector radiative transfer models are required. So far, only a few such models exist. Therefore, the International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to provide benchmark results for polarized radiative transfer. The group has already performed an intercomparison for one-dimensional (1D) multi-layer test cases [phase A, 1]. This paper presents the continuation of the intercomparison project (phase B) for 2D and 3D test cases: a step cloud, a cubic cloud, and a more realistic scenario including a 3D cloud field generated by a Large Eddy Simulation (LES) model and typical background aerosols. The commonly established benchmark results for 3D polarized radiative transfer are available at the IPRT website (http://www.meteo.physik.uni-muenchen.de/ iprt).

The two concerted field campaigns Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL) took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL), as well as surface-based stations, a tethered balloon, and satellites. Here, we present the synoptic development during the 35 day period of the campaigns, using classical near-surface and upper-air meteorological observations, as well as operational satellite and model data. Over the campaign period, short-term synoptic variability was substantial, dominating over the long-term background effect of Arctic amplification. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent two weeks were characterized by warm and moist maritime air from the south and east, which included two warm air advections. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final two weeks, adiabatically warmed westerly air dominated, with a strongly varying cloud distribution in between the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

The 19-channel rotating shadowband radiometer GUVis-3511 built by Biospherical Instruments provides automated shipborne measurements of the direct, diffuse and global spectral irradiance components without a requirement for platform stabilization. Several direct sun products, including spectral direct beam transmittance, aerosol optical depth, Ångström exponent and precipitable water, can be derived from these observations. The individual steps of the data analysis are described, and the different sources of uncertainty are discussed. The total uncertainty of the observed direct beam transmittances is estimated to be about 4 % for most channels within a 95 % confidence interval for shipborne operation. The calibration is identified as the dominating contribution to the total uncertainty. A comparison of direct beam transmittance with those obtained from a Cimel sunphotometer at a land site and a manually operated Microtops II sunphotometer on a ship is presented. Measurements deviate by less than 3 and 4 % on land and on ship, respectively, for most channels and in agreement with our previous uncertainty estimate. These numbers demonstrate that the instrument is well suited for shipborne operation, and the applied methods for motion correction work accurately. Based on spectral direct beam transmittance, aerosol optical depth can be retrieved with an uncertainty of 0.02 for all channels within a 95 % confidence interval. The different methods to account for Rayleigh scattering and gas absorption in our scheme and in the Aerosol Robotic Network processing for Cimel sunphotometers lead to minor deviations. Relying on the cross calibration of the 940 nm water vapor channel with the Cimel sunphotometer, the column amount of precipitable water can be estimated with an uncertainty of ±0.034 cm.

This study presents vertical profiles up to a height of 2300 m a.s.l. of aerosol microphysical and optical properties and cloud condensation nuclei (CCN). Corresponding data have been measured during a field campaign as part of the High-Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) Observational Prototype Experiments (HOPE), which took place at Melpitz, Germany from September 9 to 29, 2013. The helicopter-borne payload ACTOS (Airborne Cloud and Turbulence Observation System) was used to determine the aerosol particle number size distribution (PNSD), the number concentrations of aerosol particles (PNC) and cloud condensation nuclei (CCN) (CCN-NC), the ambient relative humidity (RH), and temperature (T). Simultaneous measurements on ground provided a holistic view on aerosol microphysical properties such as the PNSD, the chemical composition and the CCN-NC. Additional measurements of a 3 + 2 wavelength polarization lidar system (PollyXT) provided profiles of the aerosol particle light backscatter coefficient (σbsc) for three wavelengths (355, 532 and 1064 nm). From profiles of σbsc profiles of the aerosol particle light extinction coefficient (σext) were determined using the extinction-to-backscatter ratio. Furthermore, CCN-NC profiles were estimated on basis of the lidar-measurements. Ambient state optical properties of aerosol particles were derived on the basis of airborne in situ measurements of ACTOS (PNSD) and in situ measurements on ground (chemical aerosol characterization) using Mie-theory. On the basis of ground-based and airborne measurements, this work investigates the representativeness of ground-based aerosol microphysical properties for the boundary layer for two case-studies. The PNSD measurements on ground showed a good agreement with the measurements provided with ACTOS for lower altitudes. The ground-based measurements of PNC and CCN-NC are representative for the PBL when the PBL is well mixed. Locally isolated new particle formation events on ground or at the top of the PBL led to vertical variability in the here presented cases and ground-based measurements are not representative for the PBL. Furthermore, the lidar-based estimates of CCN-NC profiles were compared with the airborne in situ measurements of ACTOS. This comparison showed good agreements within the uncertainty range. Finally, this work provides a closure study between the optical aerosol particle properties in ambient state based on the airborne ACTOS measurements and derived with the lidar measurements. The investigation of the optical properties shows for 14 measurement-points that the airborne-based particle light backscatter coefficient is for 1064 nm 50 % smaller than the measurements of the lidar system, 27.6 % smaller for 532 nm and 29.9 % smaller for 355 nm. These results are quite promising, since in-situ measurement based Mie-calculations of the particle light backscattering are scarce and the modelling is quite challenging. In contradiction for the particle light extinction coefficient retrieved from the airborne in situ measurements were found a good agreement. The airborne-based particle light extinction coefficient was just 7.9 % larger for 532 nm and 3.5 % smaller for 355 nm, for an assumed lidar ratio (LR) of 55 sr. The particle light extinction coefficient for 1064 nm was derived with a LR of 30 sr. For this wavelength, the airborne-based particle light extinction coefficient is 5.2 % smaller than the lidar-measurements. Also, the correlation for the particle light extinction coefficient in combination with Mie-based LR's are in agreement for typical LR's of European background aerosol.

The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign period, short-term synoptic variability was substantial, dominating over the seasonal cycle. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent 2 weeks were characterized by warm and moist maritime air from the south and east, which included two events of warm air advection. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final 2 weeks, adiabatically warmed air from the west dominated, with cloud properties strongly varying within the range of the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

A method is presented to analyze the cloud life cycle of frontal systems passing over European supersites. It combines information on the vertical profiles of cloud properties derived from ground-based observations with cloud products obtained from satellite-based observations, including their spatial variability. The Euler and Lagrange perspectives are adopted to consider the history of a cloud system that passes the supersites. The forward model known as RTTOV (Radiative Transfer for the Television and Infrared Observation Satellite Operational Vertical Sounder) and the ground-based “CloudNET” products are used to simulate synthetic satellite observations at the supersites, which are subsequently compared with the actual observations of the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. Different metrics are considered to quantify and interpret the consistency of the synthetic and the observed satellite data: brightness temperatures at the thermal IR channels, the split-window channels, and trispectral combinations, as well as the outgoing longwave radiation. In this way, the uncertainties of the individual datasets are investigated. This knowledge provides the motivation to combine the disjunct cloud products from satellite with those from ground instruments to characterize the development of the passing cloud frontal systems. In addition, back trajectories started at different stages of the cloud system were used to analyze its history prior to the supersite overpass. The trajectories are used to study, for example, the life time of the cloud frontal system, changes of the cloud phase, and the evolution of cloud physics such as optical thickness, effective particle size, and water path. As a test bed, a case study with a cold front passing Lindenberg, Germany, is presented.

Sensible and latent heat fluxes were estimated from turbulence measurements gathered during several Atlantic Ocean transects of the research vessel (R/V) Polarstern. The inertial dissipation method was used to analyze the data. Resulting bulk transfer coefficients were then applied to the data from the ship’s meteorological system to get continuous time series of the heat fluxes. Combined with the measured downward solar and longwave radiation fluxes it allows for an estimate of the total energy budget at the air–sea interface. Comparing these parameterized energy fluxes to those based on the Coupled Ocean–Atmosphere Response Experiment, version 3 (COARE3.0), bulk flux algorithm shows very strong agreement.