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WP2: Profiling of aerosols and clouds

WP2 Objectives

The overall objective of this activity is to consolidate and optimize the European observing capabilities for investigating aerosols, clouds, and their interactions, with high vertical and temporal resolution throughout the troposphere by means of an advanced network of coordinated lidar and cloud-radar stations in such a way that the data they provide can be efficiently integrated with other observations and effectively shared with a wide user community. The specific objectives are:

•    To optimize the ACTRIS aerosol profiling component established in the framework of EARLINET by improving instrumentation, standardization, data processing and quality assessment, implementing additional observation capabilities and new data products and providing them to end users together with tools to fully exploit the products.
•    To optimize the ACTRIS cloud profiling component established in the framework of Cloudnet by improving observation strategies, enhancing the processing chain, implementing new data products, providing them to users, and developing suitable radar calibration methodologies to improve data accuracy.  
•    To integrate the observing capabilities of aerosol and cloud remote-sensing networks and to make best use of synergy by supporting the co-location of EARLINET, Cloudnet and AERONET sites, implementing new instruments capable of contributing to aerosol and cloud research, defining common standards and developing common products and data processing algorithms.
To enhance the shared scientific and technological knowledge on remote sensing of aerosols and clouds among the participants and to provide an interface to the internal and external scientific community through exchange of expertise with focus on the strengthening of the ACTRIS observing capabilities.

Description of work

ACTRIS comprises two advanced remote-sensing networks for the observation of the vertical aerosol and cloud distribution over Europe: EARLINET, with currently 27 stations (most of them co-located with AERONET stations), and Cloudnet, with 9 stations. Both networks have been operated for more than a decade and have already provided the world’s largest database on aerosol and cloud four-dimensional (space-time) distributions at continental scale. At the same time, they have pioneered the task of establishing standards for aerosol and cloud data products and processing algorithms. In particular, EARLINET has developed a suite of quality-assurance methods at both the hardware and software level to ensure the quality of lidar products, which now is considered to be mature enough to set up a Lidar Calibration Centre in ACTRIS-2 (WP6).

The goal of this networking activity is to consolidate, further optimize, harmonize and integrate EARLINET and Cloudnet instrumentation, observing strategies, processing chains and data products. Regarding hardware, focus is on the implementation of new observing capabilities by either improving existing instrumentation and data acquisition or adding recently implemented equipment and by establishing the respective standards. On the software side, the existing processing chains will be improved and new data products will be included. A challenging and innovative task is the exploitation of synergies between EARLINET and Cloudnet and the envisaged development of common observing strategies and algorithms, with the ambition to provide both cloud and aerosol products in near-real time for fast analysis of hazardous events, instantaneous evaluation of numerical-weather-prediction and atmospheric-transport models as well as for data assimilation purposes.

A large part of the work planned in NA2 will consolidate developments started in ACTRIS and will strongly benefit from innovations of the previous JRAs on “Lidar and sun photometer” and “A framework for cloud-aerosol interaction studies”. Developments initiated by ITaRS (ITN on Initial Training for atmospheric Remote Sensing) will be considered as well. The implementation of new data products will lead to significantly enhanced EARLINET and Cloudnet databases, accessible through Virtual Access, and will thus require cooperation with WP10. Development of quality-assurance standards for new aerosol products and consolidation of existing methodologies within EARLINET will be performed in close collaboration with the Lidar Calibration Centre (WP6). A specific subtask is proposed in this NA to work on radar calibration strategies, which are not yet well established.  Activities on calibration techniques and new hardware quality standards will be carried out in collaboration with European SMEs supplying commercial cloud radars and aerosol lidars. Furthermore, interaction of this NA with JRA1 by providing lidar products related to aerosol absorption, with JRA2 by contributing expertise for remote flux measurements, and with JRA3 by supporting the use of aerosol and cloud profiles for modelling tasks is planned. The JRAs will also facilitate a close link between remote-sensing and in-situ endeavours (NA3). Close interaction with NA4 for innovation activities and with NA5 for education, collaboration and outreach is envisaged.

Task 2.1: Optimization of aerosol profiling
(CNR, CNRS, TROPOS, NOA, FMI, INOE, LMU, JRC, UGR, KNMI, CyI, DWD, IPNASB, CNISM, INRNE, IGF PAS)

This task is dedicated to the innovative and sustainable advancement of aerosol lidar observations within EARLINET. The current observing strategy and product design of EARLINET had been first established within the Fifth Framework Programme (2000-2003). Usually, observations are performed during limited, fixed time periods (two hours, three times a week) in order to establish the unbiased aerosol climatology. Additional measurements are carried out for special cases on an alert basis. The shortened temporal coverage was mainly due to limited automation of the instruments and high expenses of hardware, software and person power. The strong demand from the scientific community for long-lasting or even continuous observations and the technological progress over the past decade have motivated respective renewals and require accompanying efforts for hardware and software developments, also in collaboration with commercial suppliers (SMEs). Next to instrument improvements, the major goal of this task is to set up a rigorous, level-based, user-friendly product chain, reaching from near-real-time (NRT) visualization of measurements to statistical and climatological products based on long-term observations.

Task 2.1.1: Improvement of instrumentation, standardization and quality assessment
(TROPOS, CNR, CNRS, NOA, FMI, INOE, LMU, JRC, UGR, KNMI, CyI, DWD, IPNASB, CNISM, INRNE, IGF PAS)

The following three goals were identified regarding the required optimization of instruments. -    Implementation of new measurement capabilities: The upgrading of existing lidar instruments has been a continuously progressing effort since the start of EARLINET. Nowadays, most stations operate multi-wavelength Raman-polarization lidars. Further upgrades that will be facilitated in ACTRIS-2 will consider Raman daytime capabilities following recommendations from the previous ACTRIS JRA1 and polarization observing capabilities at two or more wavelengths in order to better identify different aerosol types. -    Optimization of instruments for long-lasting or continuous (unattended) operation: In principle, modern lidar instruments are capable of operating continuously, and several EARLINET stations already provide continuous data (24 hours/7 days a week). The expertise in the network will be used to facilitate developments for automated operation and remote control of lidar instruments at EARLINET stations.
-    Protocols and quality check procedures will be further optimized, in particular for new products. As in the past, all EARLINET lidar stations have to apply regular quality tests and take action in case of observed instrumental non-compliance.

Task 2.1.2: Implementation of new data products and optimization of the processing chain
(CNR, CNRS, TROPOS, NOA, INOE, UGR, DWD, IPNASB, UNIVLEEDS)

The EARLINET processing chain or Single Calculus Chain (SCC) will be enhanced and coupled with other processing chains in order to serve data providers and end users with a sophisticated level-based product chain, starting with raw lidar data uploaded by the individual EARLINET stations and leading to advanced geometrical, optical, and microphysical aerosol products. The chain will include tools for NRT data provision on alert, campaign, or continuous basis. The following data processing steps are to be realized:
-    The existing SCC Preprocessor, which converts individual Level 0 raw signals into standardized, quality-assured Level 1 lidar data, will be used to develop a homogeneous network-wide, open and freely accessible quicklook database (high-resolution images of time-height cross sections). Tools for cloud/aerosol masking and layer identification as partly already developed in ACTRIS will be deployed. The standardized Level 1 data will serve as input for any further processing of lidar data, within the SCC as well as in other processing algorithms (e.g., combined retrievals with sun photometer, combined retrievals with Cloudnet, see below).
-    The efforts to calculate improved Level 2 optical and geometrical data products (e.g., combined optical data, layer products, and statistical products will be continued. New data products following from the implementation of new measurement capabilities (see Task 2.1.1) will be considered.
-    A new, advanced product level (Level 3) of the EARLINET database will be developed and implemented. Level 3 products include climatological products from long-term observations, microphysical aerosol products based on inversion of multi-channel lidar data, and microphysical aerosol products from combined lidar and sun-photometer observations based on algorithms developed in the previous JRA on “Lidar and sun photometer”. Processing of the latter products will be partly implemented at the ICARE Data Centre. All developments will include standardization of the products, definition of metadata, definition and implementation of error products, and documentation.

Task 2.2: Optimization of cloud profiling
(UNIVLEEDS, CNR, CNRS, TROPOS, FMI, KNMI, RIUUK, DWD, NUIG)

The objective of Task 2.2 is the innovative and sustainable advancement of cloud-related observations within Cloudnet. In contrast to EARLINET, the fully commercial equipment of Cloudnet allowed the installation of a continuously (24/7) measuring network with NRT data provision and direct links to six NWP models already during the first implementation phase in the Fifth Framework Programme (2001-2005). Cloudnet was considerably enhanced during ACTRIS, when the number of stations was increased from four to nine, despite the high costs involved in the setup of a standard Cloudnet station, consisting of at least a cloud-profiling radar, a microwave radiometer and a ceilometer.
Cloudnet stations possess a relatively high level of standardization of instruments as well as data processing. A common, modular, level-based processing chain has been implemented, and automated transfer of data to the Cloudnet database is possible. A challenge for Cloudnet is the immense amount of data delivered in particular by the cloud radars, which so far leads to restrictions in the full storage and exploitation of radar information. Furthermore, radar retrievals of cloud and precipitation microphysical properties suffer from the uncertainty in the absolute calibration of the instruments and the attenuation of up to 10 dB when the radome/antenna is wet. Both challenges will be tackled in close collaboration with the commercial cloud-radar supplier in ACTRIS-2.

Task 2.2.1: Improvement of observing strategies, implementation of new data products and optimization of the processing chain
(UNIVLEEDS, TROPOS, FMI, KNMI, CNR, RIUUK, CNRS, DWD, NUIG)

Cloud radar Doppler spectra contain the full hydrometeor vertical motion distribution. Hence, it is possible to diagnose the presence of two or more distinct hydrometeor classes within a single volume, separate each component, and perform microphysical retrievals on the two components independently. Discrimination between liquid and ice in mixed-phase cloud, precipitation and liquid cloud, and between multiple ice populations arising from competing growth mechanisms, are all achievable. However, storing raw Doppler spectra from continuous measurements over longer periods runs into practical issues because of the huge data volume. Therefore, specific storing and evaluation strategies will be developed with the aim to evaluate Doppler spectra during the observation and store only compressed information on multiple peaks and skewness of the spectra, from which higher-level data can be obtained off-line. Other new data products planned to be implemented in the Cloudnet processing chain are the turbulent kinetic energy calculated from radar and lidar velocity information (see also Task 2.3) and cloud microphysical products as, e.g., obtained from the Doppler spectra. The developments will include standardization of the products, definition of metadata, definition and implementation of error products, and documentation.

Task 2.2.2: Calibration and standardization of cloud radars
(KNMI, CNRS, UNIVLEEDS)

Deducing quantitative information on cloud microphysical parameters requires the absolute calibration of radar reflectivity measurements and the quantification of errors. Calibration information is usually provided by the manufacturer, but with limited accuracy. A standardized methodology for radar calibration is not available yet. Therefore, it is proposed to evaluate different approaches within ACTRIS-2 and to develop a standard calibration procedure for cloud radars in order to better harmonize Cloudnet observations. Three complementary approaches are considered. The calibration with atmospheric targets, in particular rain, will be investigated by comparing cloud-radar and precipitation-radar observations for known rainfall rates using the facilities at Chilbolton and Cabauw. Calibration with external sources using reflectors or transponders mounted on side-arms of a tower or flown on drones will be examined at the Cabauw site. Both methods will be cross-checked with a mobile FMCW (frequency-modulated continuous wave) radar that is calibrated against a corner reflector at the Palaiseau site. A radar attenuation correction for the wet radome/antenna, based on the detection of increased background noise caused by the attenuator, will be implemented. Recommendations for calibration activities at all Cloudnet sites will be provided.

Task 2.3: Integration of aerosol and cloud observation capabilities
(TROPOS, CNR, CNRS, NOA, FMI, INOE, KNMI, RIUUK, DWD, UNIVLEEDS, CNISM, NUIG)

This task is dedicated to the synergy of EARLINET and Cloudnet. It is driven by the increasing scientific interest in combined aerosol and cloud observations to study aerosol-cloud interactions. Up until now, four permanent Cloudnet and EARLINET stations have been co-located. It is expected that this number will grow in future and that the number of joint deployments of mobile Cloudnet and EARLINET instrumentation in field campaigns will increase as well. Beside such direct combination of sites, there is common interest in the implementation of additional observing capabilities in both networks. In particular, profiles of water vapor and vertical wind are of high importance, e.g., to study aerosol vertical exchange, hygroscopic particle growth and the formation of clouds in the planetary boundary layer (PBL). Therefore, the exploitation of synergies and the development of common observing strategies and standards are the main objectives of this task.

Task 2.3.1: Instrument synergy
(CNR, CNRS, TROPOS, NOA, FMI, INOE, JRC, KNMI, RIUUK, DWD, UNIVLEEDS, CNISM, NUIG)

Joint efforts of Cloudnet and EARLINET regarding instrument synergies are focusing on three aspects: -    Implementation of Doppler lidar at selected Cloudnet and EARLINET sites: Several Cloudnet and EARLINET sites have started to implement Doppler lidars, which have recently become commercially available for reasonable prices. It is expected that all Cloudnet sites will deploy Doppler lidars in the near future. Doppler lidars allow the observation of horizontal and vertical wind in the PBL and at cloud base. They can complement Doppler radar observations, but are also capable of obtaining aerosol vertical fluxes when combined with aerosol lidar (see JRA2).
-    Implementation of multi-wavelength/polarization lidars at Cloudnet sites: Aerosol information at standard Cloudnet sites is limited to the qualitative recognition of aerosol presence by ceilometers. Quantitative retrievals, classification of aerosols, e.g., in terms of pollution or dust, and investigation of aerosol-cloud interactions are only possible with more sophisticated lidars based on multiwavelength and polarization techniques as applied in EARLINET.
-    Implementation of water-vapour Raman lidars at selected Cloudnet and EARLINET sites: Water-vapor profiles are of particular interest to investigate hygroscopic particle growth and cloud formation. Many EARLINET lidars are already equipped with water-vapor Raman channels, but the measurements are not standardized and the information content is not made available yet in the network. Since Raman-lidar observations are limited at daytime and in the presence of clouds, the combination of Raman lidar and microwave radiometer to synergistically derive water-vapor profiles at combined stations is planned.

Task 2.3.2: Optimization of observing strategies, standardization and quality assessment
(TROPOS, UNIV-LEEDS, CNR)

Both EARLINET and Cloudnet have developed their own observing strategies and quality standards in the past. Work has to be performed to harmonize and synchronize the standards at integrated stations. For instance, continuous high-resolution observations with NRT data provision following Cloudnet procedures require new methodologies to obtain absolutely calibrated lidar signals in near-real time. The development and implementation of such procedures is one goal that will also serve as input for Task 2.1. On the other hand, there are no sophisticated aerosol products available from Cloudnet. Here, EARLINET expertise will be used to implement the quality standards for Level 2 aerosol products at Cloudnet sites equipped with sophisticated lidar instruments. Another objective is the provision of standards for EARLINET and Cloudnet stations equipped with Doppler lidar, e.g., the recommendation of a scan strategy to obtain horizontal and vertical winds from Doppler lidar with sufficient resolution. Task 2.3.3: Development of common data products and processing (UNIVLEEDS, CNR, TROPOS, RIUUK)

Following the developments in Tasks 2.3.1 and 2.3.2, common algorithms to obtain new data products will be put in place in the processing chains. The preprocessor of the EARLINET SCC will be adapted to derive standardized Cloudnet Level 1 lidar signals. Afterwards, an improved target classification for aerosols and clouds and the implementation of data products describing aerosol-cloud interaction will be possible. Products following from the implementation of Doppler lidar (horizontal and vertical wind, PBL height, skewness, turbulent kinetic energy, energy dissipation rate) will be provided via a common processor module. Further common modules will be developed for combined lidar and sun photometer optical products (optical depth, Angström exponent) and for water-vapour retrievals (see Task 2.3.1). Again, all developments shall include standardization of the products, definition of metadata, definition and implementation of error products, and documentation.

Task 2.4: Exchange of expertise, support to campaigns and new users
(UGR, CNR, CNRS, TROPOS, NOA, FMI, INOE, LMU, JRC, UGR, KNMI, CyI, RIUUK, DWD, UNIVLEEDS, IPNASB, CNISM, INRNE, NUIG, IGF PAS)

This task will be the backbone of the networking activity through which the participants get the opportunity to interact, exchange their expertise, discuss new ideas and concepts, share the outcomes of the tasks, and provide education and critical insight to (young) scientists. In addition, it provides a means of interfacing with the other activities of the project in a more focused way than in the GA and, to some extent, reaching out to the external scientific and technical community, the industry (in particular SMEs) as well as the general public. The task will support the following items:
-    Organization of annual workshops and task-related technical meetings (UGR, CNR, UNIVLEEDS, TROPOS): Annual technical workshops will be organized to discuss progress of the tasks as well as specific topics (e.g., user requirements, instrument and data analysis optimization, external collaboration). The workshop participants are in particular the partners (full and associated) involved in aerosol and cloud remote-sensing observations, but the workshops will be open to all ACTRIS partners. Scientific or technical external stakeholders will be invited for specific topics. Next to the workshops, task-related technical meetings will be fostered to facilitate progress of specific developments.
-    Implementation of EARLINET and Cloudnet processors, products and QA procedures during campaigns (CNR, UNIVLEEDS, TROPOS): The increasing use of EARLINET- and Cloudnet-like mobile systems in field experiments requires specific support such as adaption of the processing chains and databases, including model links, consideration of specific sites and platforms (e.g., ships) etc. Respective expertise will be provided to users on request.
-    Support to new stations (INOE, UNIVLEEDS, LMU, TROPOS): EARLINET and Cloudnet are still growing. New stations must fulfill a large number of requirements to adjust to the networks’ standards. Necessary guidance and support will be provided. Documentation, websites, and outreach (UGR, CNR, UNIVLEEDS, TROPOS): Documentation of meeting results, task-related documentations, standardization protocols, technical descriptions and any information relevant for the users will be made available through publication on the ACTRIS website and via task-related websites and interfaces.