Conference Agenda

The Swarm satellite mission were launched on 22 November 2013, it is the first European Space Agency’s constellation of three satellites, dedicated to monitoring geomagnetic field changes. The three satellites have delivered more than 7 year measurements to date, which provide an unprecedented opportunity for conducting a broad range of applications at global scale, including earthquake prediction study. However, for the past years, relatively little advancement has been achieved on establishing a systematic approach for detecting anomalies from the satellite data and integration with ground-based measurements for predicting earthquakes. In Dragon 3 we developed the Wavelet Maxima-based method, Geometric Moving Average Martingale (GMAM) based on the Martingale theory, the integration of Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) called CUSUM-EWMA, and applied these methods to analyse the Wenchuan and Lushan earthquakes.

This report will present the further development and comparative analysis results achieved in the Dragon 4 project. These include the development of a Fuzzy Inspired Approach to Seismic Anomaly Detection (FIAD), Anomaly Detection in Sequential Data Augmented with new features and Enhanced Martingale methods as well as analysis results of the Peru earthquake, Jinggu, Taoyuan, Ludian and Peloponnese earthquakes occurred in China and Greece, respectively. These results demonstrated possible automatic approaches for detecting anomalies from the satellite data and the effectiveness of these methods. The studies conducted have laid down a good basis for the project team to carry out large and more comprehensive studies of analyzing the data observed by China Seismo-Electromagnetic Satellite Mission (CSES) satellite and ground-based networks in order to improve understanding of earthquake preparation and occurrence processes.

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements, but cannot provide information about subsurface structures. In this work InSAR measurements were integrated with seismic noise in-situ measurements to analyse both the surface and subsurface characteristics of a complex slow-moving landslide exhibiting multiple failure surfaces. The landslide body involves a town of around 6,000 inhabitants, Villa de la Independencia (Bolivia), where extensive damages to buildings have been observed. To investigate the spatial-temporal characteristics of the landslide motion, Sentinel-1 displacement time series from October 2014 to December 2019 were produced. A new geometric inversion method is proposed to determine the best-fit sliding direction and inclination of the landslide. Our results indicate that the landslide is featured by a compound movement, where three sub-blocks slide with diverse geometries and magnitudes. This is further evidenced by seismic noise measurements which identified that the different dynamic characteristics of the three sub-blocks were possibly due to the different properties of shallow and deep slip surfaces. Determination of the slip surface depths allows estimating the overall landslide volume (9.18·10⁷ m³). Furthermore, Sentinel-1 time series show that the landslide movements manifest substantial accelerations in early 2018 and 2019, coinciding with increased precipitations in the late rainy season which are identified as the most likely triggers of the observed accelerations. This study reveals the potential of integrating InSAR and seismic noise techniques to understand the landslide mechanism from ground to subsurface.

Reference:

Song, C., Yu, C., Li, Z., Pazzi, V., Del Soldato, M., Cruz, A. and Utili, S. (2021), Landslide geometry and activity in Villa de la Independencia (Bolivia) revealed by InSAR and seismic noise measurements, Landslides, https://doi.org/10.1007/s10346-021-01659-9.

The present project Three- and Four-Dimensional Topographic Measurement and Validation (ID: 32278) has been developed with continuity since Dragon-1. In Dragon­1 and Dragon­2, the focus was on DEM generation and surface motion estimation with medium resolution Synthetic Aperture Radar (SAR) data. Since Dragon­3, SAR datasets of high spatial and temporal resolution (TerraSAR­X, COSMO­SkyMed) were made available, and nowadays, thanks to the availability of dense time series from Sentinel­1, accurate and frequent global coverage has become reality. Moreover, the capabilities of SAR-based Earth Observation are on their way for a further improvement in the very near future, thanks to new low-frequency Missions such as BIOMASS and ROSE-L that will grant enhanced wave penetration in natural media such as forests and ice. This is the context in which this Dragon-4 project is framed. The overarching goal of the project is to develop new methodologies to deliver a most complete characterization of targets on land surfaces and deepen the current knowledge on the exploitation of SAR data. The project is split into three subprojects focused on specific tasks, namely:

• Validation of elevation and deformation maps produced by SAR Interferometry.
• Handling temporal effects on interferometric and tomographic analyses of natural scenarios.
• Near-real time target motion estimation, considering efficient algorithms to allow for the digestion of new acquisitions and for a change in the parameterization of the estimation problem.

Non-climate-related anthropogenic processes and frequently encountered natural hazards exacerbate the risk in coastal zones and megacities and amplify local vulnerability. Coastal risk is amplified by the combination of sea level rise (SLR) resulting from climate change, associated tidal evolution, and the local sinking of land resulting from anthropogenic and natural hazards. In this framework, the authors of this investigation have actively contributed to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon IV initiative through a project (ID. 32294) that was explicitly designed to address the issue of monitoring coastal and delta river regions through Earth Observation (EO) technologies. The project's primary goals were to provide a complete characterization of the changes in target scenes over time and provide estimates of future regional sea level changes to derive submerged coastal areas and wave fields. It also provided suggestions for implementing coastal protection measures to adapt and mitigate the multifactor coastal vulnerability. To achieve these tasks, well-established remote sensing technologies, based on the joint exploitation of multi-spectral information gathered at different spectral wavelengths, the exploitation of advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques for the retrieval of ground deformations, the realization of geophysical analyses, and the use of satellite altimeters and tide gauge data, have effectively been employed. The achieved results provide essential assets for planning present and future scientific activities devoted to monitoring such fragile environments. These analyses are crucial to assess the factors that will amplify the vulnerability of low-elevation coastal zones.

Geological disasters, or geohazards, can occur in remote and highly populated areas, causing several fatalities and high economic damage every year. Due to their wide spatial and temporal coverage, remote sensing data, acquired from most recent satellite missions, is the perfect tool for detailed reconstruction of past events and to monitor currently occurring phenomena. This Dragon-4 project aims to apply different techniques and methods for extensive exploitation and analysing of remote sensing data with special emphasis given to landslide hazard, risk management and disaster prevention. Multi temporal SAR interferometry, SAR tomography, high-resolution image matching and data modelling are extensively used to map landslides and other geohazards, and to evaluate their activity. In this project, various areas and various geohazard problems are explored, in the Chinese territory, including: (1) surface deformation of mountain slopes and glaciers in the Tibetan plateau; (2) land surface displacement in the Beijing region; (3) geohazards in the Longnan area; and (4) subsidence, landslides and ground fissure in the Benxi-Anshan/Shenyang-Fushun (BASF) region. Each of these themes is explored in four different sub-projects in which Chinese and European researchers collaboratively contribute. The results obtained from the processing and analysis of a huge dataset of earth observation (EO) multi-source data allow to conclude that geohazards can be identified, studied and monitored in an effective way using new techniques applied to EO data.

Improvement of InSAR time series analysis over the past years, combined with increased temporal resolution and spatial coverage of InSAR data, made it possible to explore in more detail and with more accuracy various surface deformation processes (tectonic, hydrological, related to human activities...). A major challenge associated with this is to better separate the different signal sources in InSAR velocity maps. We report here the main results obtained during our Dragon 4 project dedicated to the monitoring of seismic activity and the detection of lithospheric deformation by InSAR in China.

Starting from the analysis of the Envisat archive and moving toward exploiting the high-temporal resolution and wide coverage of Sentinel-1 data, we mainly focus on the recovery of small deformation signals associated with strain accumulation during the interseismic period along the main active fault systems on the northwestern and eastern edges of the Tibetan plateau (Altyn Tagh, Kunlun and Xianshuihe faults in particular). We present new methodological approaches to discriminate between such tectonic signals and non tectonic processes such as permafrost active layer’s response to climate forcing in sedimentary basins and other seasonal hydrological and atmospheric processes. We also show the potential of Sentinel-1 to capture such processes at the continental scale, presenting examples of average velocity maps obtained in eastern tibet by the FLATSIM automated processing chain. FLATSIM (ForM@Ter LArge-scale multi-Temporal Sentinel-1 InterferoMetry) is a service developed by CNES in the framework of the french Data and Services center ForM@Ter. The large scale products it provides enable refined 3D block modeling of joint GPS and InSAR data to discuss the present-day strain partitioning in eastern tibet. Finally, we present a case of investigation of potentially induced seismicity in the Sichuan basin : the occurrence of the 2019 Mw5.8 Changning earthquake in China.

The Dragon 4 project 32292 dealt with using new Earth Observation data for developing and improving new products obtained from radar altimetry and for operational monitoring of sea ice and surface salinity (SSS). To improve sea ice thickness retrieval, a new method was developed to match the Cryosat-2 radar waveform. Also, an automated sea ice drift detection scheme was developed and tested on Sentinel-1 data, and the sea ice drifty capability of Gaofen-4 geostationary optical data was evaluated. A second topic included implementation and validation of a prototype of a Fully-Focussed SAR processor adapted for Sentinel-3 and Sentinel-6 altimeters and evaluation of its performance with Sentinel-3 data over the Yellow Sea; the assessment of sea surface height (SSH), significant wave height (SWH), and wind speed measurements using different altimeters and CFOSAT SWIM; and the fusion of SSH measurements in mapping sea level anomaly (SLA) data to detect mesoscale eddies. Thirdly, the investigations on the retrieval of SSS include simulations to analyse the performances of the Chinese payload configurations of the Interferometric Microwave Radiometer and the Microwave Imager Combined Active and Passive, SSS retrieval under rain conditions, and the combination of active and passive microwave to study extreme winds.

It is presented in this paper the final results of ESA-MOST China Dragon Cooperation Program “Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-Sensors (ID. 32249)” including: (1) GF-3 SAR ocean wind retrieval: the first view and preliminary assessment; (2) Preliminary analysis of Chinese GF-3 SAR quad-polarization measurements to extract winds in each polarization; (3) Assessments of ocean wind retrieval schemes and geophysical model functions used for Chinese GF-3 SAR data at each polarization; (4) Combined co- and cross-polarized SAR measurements under extreme wind conditions; (5) Joint retrieval of directional ocean wave spectra from SAR and RAR; (6) Wind and waves remote sensing by using interferometric imaging radar altimeter onboard the Chinese Tiangong-2 Space Laboratory (TG-2); (7) Top cloud motion field of Typhoon Megi–2016 revealed by GF-4 Images; (8) Using satellite altimetry to calibrate the simulation of typhoon Seth storm surge off southeast china.

In this paper, we presented our collaboration on studies retrieval of ocean wave parameters, i.e., integral wave parameters by spaceborne SAR data, in the global and regional oceans.

By using the ENVISAT/ASAR wave mode data acquired in its full life cycle (2002 – 2012) over the global ocean, we developed a dataset consisting of integral ocean wave parameters of significant wave height (SWH) and mean wave period (MWP). Both parameters are calibrated and validated against buoy data. A cross-validation between the ASAR SWH and radar altimeter (RA) data is also performed to ensure that the SAR-derived wave height data are of the same quality as the RA data. These data are stored in the standard NetCDF format, which are produced for each ASAR wave mode Level1B data provided by the European Space Agency. This is for the first time that a full sea state product is derived from spaceborne SAR data over the global ocean for a decadal temporal scale. Using similar algorithm, i.e., parametric model, which relates SAR observed normalized radar cross section (NRCS) and other radar parameters with ocean wave parameters, we further developed Sentinel-1 SAR wave mode data product for global oceans.

In regional scale, SAR data acquired in stripmap or ScanSAR modes are used to derive ocean wave parameters. These data have not only high spatial resolution but also relatively large spatial coverages, and therefore are useful for mapping of ocean wave in regional scales. Compared with wave mode data with fixed radar incidence angles, they vary significantly from near to far ranges, particularly for ScanSAR and wide ScanSAR modes. Therefore, by adopting previously developed parametric model, effect of incidence angles is included. The SAR-derived SWH is systematically validated by comparing RA data and buoy measurements and shows a good accuracy.

High resolution, in the temporal, spatial or spectral dimensions is one of the major trends of satellite remote sensing, with which one may derive more detailed information from the earth observation data. The paper summarizes the main results of the Dragon-4 coastal zone project (2016-2020), the objective of which is to explore and demonstrate the technical possibility and capability of the high resolution remote sensing in the monitoring of suspended sediment and coastal wetlands, whose variability is of vital importance to human being. Specifically, in the monitoring of suspended sediment, new retrieval algorithms were developed and applied to the geostationary and the polar-orbiting optical satellite images for spatio-temporal variability analysis. For the monitoring of coastal wetlands, new algorithms were developed for wetland types classification in fine scale to identify invasive species from hyperspectral images, aboveground carbon storage and water clarity estimation from high spatial resolution satellite images. With these algorithms, the distribution of the invasive species S. alterniflora in the wetlands were mapped, and the carbon storage per unit area of the estuarine wetlands was estimated.

In this paper, the main outcomes relevant to the European Space Agency (ESA) – Ministry of Science and Technology Dragon 4 cooperation project ID 32235 “Microwave satellite measurements for coastal area and extreme weather monitoring” are reported. The project is to strengthen the Sino-European research cooperation in the framework of the exploitation of ESA, Chinese and third-party mission Earth Observation microwave satellite data to perform an effective monitoring of coastal areas, even under extreme weather conditions. An integrated approach, based on the use of complementary microwave sensors (e.g.; multi-frequency and multi-polarization Synthetic Aperture Radar, scatterometer and radiometer), together with ancillary information coming from independent sources, i. e., optical imagery, numerical simulations and ground measurements, is designed.

The main outcomes are both theoretical (i.e.; new models and algorithms have been developed to deal with marine target detection, sea pollution, sea surface wind estimation, coastline extraction) and applicative (i.e.; user-friendly maps have been provided that, based on an intelligent processing of remotely sensed measurements, can coastal area management).

In studies of upwelling, usually data from infrared and optical sensors are used which provide information on the sea surface temperature (SST) and the chlorophyll-a (Chl-a) concentration. However, when including synthetic aperture (SAR) additional information on upwelling can be obtained. Areas of cold upwelled water becomes visible on SAR images as areas of reduced image intensity because cold water changes the stability of the air-sea interface which causes a reduction of the normalized cross section (NRCS). Since SAR is ultra-sensitive to variations in the small-scale sea surface roughness, and since variable surface currents associated upwelling modulate, boundaries of upwelling become visible on SAR images as bright lines. Due to its high resolution, SAR also can detect internal waves and sub-mesoscale eddies, which are sometimes present in upwelling areas. In this paper, we analyze SAR images acquired by the European satellites Sentinel-1A and 1B and the Chinese satellite Guofen-3 (GF-3) satellite that show radar signatures of upwelling caused by coastal winds, cyclonic eddies, and cyclonic meanders. The investigation is focused on the upwelling areas south of Sicily in the Mediterranean Sea, south of South Africa, the Strait of Taiwan, and north of Taiwan.

Abstract submission pending by 31/05/2021

Complex agricultural systems comprise a large array of biophysical and physiological processes so that novel approaches and algorithms are needed to optimize the contribution of Earth Observation (EO) data to the monitoring capability with the aim of developing more sustainable management practices. This paper presents the results of research activities carried out within the ESA-MOST Dragon4 framework focused on the topic of agricultural resources. SINO and EU research groups exploited ESA and Third Party Mission data together with the Chinese EO resources in the agricultural domain both considered at regional or local scale. On different test cases, SINO-EU satellite data have been processed to retrieve biophysical variables related to crop vegetation status and to the derivation of proxy variables linked to the water and nitrogen cycling in the cereals agro-ecosystems. The paper encompasses two research avenues: i) retrievals of biophysical variables of crop and yield prediction; ii) food security. Firstly, optimal procedures (spectral indices, non-kernel-based and kernel-based Machine Learning Regression Algorithms) for retrieving biophysical crop variables (LAI and pigment) by exploiting the spectral information of current multispectral optical satellite were analyzed. Secondly assimilation of multivariate and multi-scale remotely sensed variables into crop models have been performed to retrieve yield and quality estimation under abiotic stress factors both at farm and regional scale. Lastly, field studies allowed to derives spectral index sensitive to the biotic stress (pathogen) of crops. Pathogen models combined to EO data products aim to estimate the rate of pests and diseases recognition and spreading. The combined results of these activities showed that most of the research objectives in the agricultural domain are interconnected and dependent on knowledge flow between them and that the EO exploitation in Chinese and European agriculture, can promote best practices for environmentally and profitable sustainable production through improving resource use efficiency.

This Dragon 4 project 32194 was to investigate the methodology of combined use of European and Chinese high and Medium Satellite data to assess crop and produce crop maps. This project was composed of two subprojects. One was focusing on the high-resolution satellite data and another was focusing on the medium resolution satellite data. The first subproject was entitled crop mapping with time series of high resolution European and Chinese satellite data. The Sentinel-2 and GF-1(GaoFen or high resolution in English) onboard European and Chinese satellites, respectively, were supposed to use as both have quite similar spectral bands. This subproject aimed to take both advantages of Sentinel-2 and GF-1 data to produce a better and earlier crop mapping. The team was supposed to apply and adapt the crop mapping approach of ESA (European Space Agency) Sent2Agri project to a Chinese site with time series of European and Chinese satellite images. The second subproject was entitled assessing crops with PROBA-V (PRoject for On-Board Autonomy–Vegetation) and FY-3 MERSI (Fengyun, Wind and Cloud in English, Medium Resolution Spectral Imager) data. The PROBA-V and FY3-MERSI both have quite similar channels and their own advantages. The new development of this kind of medium resolution satellite data in Europe and China was providing us an opportunity to investigate the possibility and the potential of using both PROBA-V and FY-3 MERSI Data for the crop assessment for large area. This subproject was going to focus on the crop mapping with both satellite data. The team developed the methods to handle both data and then get the information retrieved. With the implementation of this dragon project, the crop type maps were produced in the irrigated area in Northwest China with the sentinel 2A/B,GF-1,PROBA-V and FY3B-MERSI. The overall accuracies of resulting crop type maps from S-2 and GF-1 reached 94-97% while the overall accuracies from PROBA-V and FY3B-MERSI reached 88%. The methodology for the crop type classification was improved and benefited from the Sent2Agri system.

This project made profound studies on the in-orbit calibration and the product quality traceability of space-borne optical sensors, in-orbit calibration and product generation of microwave sensors, MAXDOAS benchmark observation in eastern China, and ground-based FTIR spectrometer benchmark measurement, the related achievements mainly include the following aspects:

(1) In this project, we have developed an SI-traceable automated radiometric calibration system, and established a whole uncertainty transfer link for field calibration. These achievements have been integrated in the "National high resolution remote sensing comprehensive calibration site", namely Baotou site, one of demonstrated sites of the International Committee on earth observation (CEOS)/Global Radiometric Calibration Network (RadCalNet). Under the framework of RadCalNet project, Baotou site could regularly provide the radiometric calibration standard product together with Europe Space Agency (ESA), and supporting the in-orbit performance evaluation of high-resolution sensors onboard series satellites in China, such as GF, ZY, TH, GJ.

(2) According to the higher requirements on radiometric accuracy of microwave RS sensors in the global meteorological and climate research, this project has developed a radiation benchmark transfer model from ground to satellite, and a traceability model from satellite to ground. These models improve the calibration accuracy of single satellite by 17% and improves the consistency of the sensors between generations by 11%.

(3) In-orbit radiometric calibration algorithm of hyperspectral payload also has been developed, and these channels shorter than 312 nm of TROPOMI have been re-calibrated, so that the fitting residual of SO2 spectrum was reduced from 0.40%～0.92% to 0.07%～0.14%. On basis of this, this project has proposed an SO₂ retrieval method from the UV-VIS hyperspectral sensor onboard GF-5 satellite, and the retrieved result has been validated with 121 sets of weekly average in situ data in 12 months. It is demonstrated that bias for this method is reduced by 41%～123% comparing to the official TROPOMI products published by NASA/ESA, this confirms that the official products of ESA seriously overestimate the concentration of SO₂ in China.

In this project, there are 10 participants with senior titles, 15 intermediate titles and 18 graduate students. Among them, Cheng Liu from the University of the Science and Technology of China won the 16th China Youth Science and Technology Award in 2020; Lingling Ma from the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), and Marc Bouvet from ESA, won the International Cooperation Partner Award for young scientists of CAS in 2020.

The CLIMATE-TPE project aimed to advance understanding the interactions between the Asian monsoon, the Tibetan Plateau surface and the plateau atmosphere in terms of water and energy budgets, which is essential for assessing and understanding the causes of changes in cryosphere, and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in the Third Pole Environment. A core innovation of the project was to verify or falsify recent hypotheses (e.g. links between plateau heating and monsoon circulation, snow cover and monsoon strength, soil moisture and timing of monsoon) and projections of the changes of glaciers and permafrost in relation to surface and tropospheric heating on the Tibetan Plateau as precursors of monsoon pattern changes and glaciers retreat, and their impacts on water resources in South East Asia. This paper reports results related to: (1) A platform of in-situ observation stations of hydrosphere-pedosphere-atmosphere-cryosphere-biosphere interactions over the Tibetan Plateau, (2) Multiyear in-situ L-Band microwave radiometry of land surface processes, (3) Evaluation and generation of land surface heat fluxes and evapotranspiration, (4) Climate scale monitoring of soil moisture and soil temperature and validation of large scale soil moisture products, (5) Trajectory of water vapor transport in the canyon area of Southeast Tibet, and (6) Vertical characteristics of water vapor exchange between upper troposphere and lower stratosphere.

The strong economic growth in China in recent decades, together with meteorological factors, has resulted in serious air pollution problems, in particular over large industrialized areas with high population density. To reduce the concentrations of pollutants, air pollution control policies have been successfully implemented, resulting in the gradual decrease of air pollution in China during the last decade, as evidenced from both satellite and ground-based measurements. The aim of the DRAGON4 project “Air quality over China” was the determination of trends in the concentrations of aerosols and trace gases, quantification of emissions using a top-down approach and gain a better understanding of the sources, transport and underlying processes contributing to air pollution. This was achieved through (a) satellite observations of trace gases and aerosols to study the temporal and spatial variability of air pollutants (b) derivation of trace gas emissions from satellite observations to study sources of air pollution and improve air quality modeling and (c) study effects of haze on air quality. In these studies, the satellite observations are complemented with ground-based observations and modeling.

The increase in atmospheric greenhouse gas concentrations of CO₂ and CH₄ due to human activities is the main driver of the observed increase in surface temperature by more than 1^oC since the pre-industrial area. To limit the increase in global surface temperature to 1.5°C, the 2015 United Nations Climate Change Conference held in Paris, most nations agreed to reduce greenhouse gas emissions.

Atmospheric observations of greenhouses gas concentrations from satellites will play an important tole for monitoring the effectiveness of any policies aimed at reducing emission. Satellite remote sensing of CO₂ and CH₄ is now well established thanks to missions such as NASA OCO-2, Japanese GOSAT and the Chinese TanSat missions which have allowed us to build a long-term record of atmospheric GHG concentration from space. They also give us a first glimpse into CO₂ and CH₄ enhancements related to anthropogenic emission which helps to pave the way towards the future missions aimed at a Moni­toring & Verification Support (MVS) capacity for the global stock take of the Paris agreement.

The pioneering GOSAT and OCO-2 missions have demonstrated the power of satellite observations to constrain surface fluxes of CO₂ and CH₄ and to inform on regional budgets but it has also emphasised the importance to utilise ground- based measurement to validate the satellite products and intercomparisons of multiple retrieval algorithms, especially to improve the accuracy of satellite retrievals to reduce the interference by many other factors, such as aerosols, clouds or ground surface properties.

The overall goals of this project has been to characterize and improve the TanSat XCO2 retrieval and their uncertainty quantification by retrieval intercomparisons and experiments using Chinese and European algorithms and by using TCCON and Chinese ground-based measurements and extend the validation previously applied for GOSAT and OCO-2 data to TanSat XCO2 and also analyse Sentinel 5 Precursor XCH4 observations. AirCore profile observations of greenhouse gases at Sodankylä has been used to support the validation at high latitudes. The XCO2 datasets obtained from TanSat have also been evaluated against model calculations and we have used XCO2 from satellites data to constrain surface fluxes over China and globally using surface flux inverse calculations.

In this presentation, we will describe the project, summarize the project objectives and give an overview over the project achievements.

The global wind field effects the atmospheric circulation, the atmospheric carbon cycle, marine–atmosphere circulation, and aerosol activities. Aerosols play a key role in climate change and air quality because of its direct, semi-direct, and indirect effects on the radiation budget. As the most important anthropogenic greenhouse gas, carbon dioxide plays a key role in climate studies and for environment monitoring. The European Space Agency (ESA) developed the Aeolus mission to provide global profiles of wind, clouds and aerosols properties. Aeolus carries the first wind lidar in space (ALADIN) and was successfully launched in August 2018. The lidar mission ACDL (Aerosol and Carbon dioxide Detection Lidar) implemented by China is currently scheduled for launch in 2021 to measure CO₂ and aerosol from space. The activities of the project aim at validating Aeolus, the study of long-range transport of aerosol, and the preparation of the Chinese CO₂ spaceborne lidar mission. The first objective is to validate Aeolus wind products based on ground-based and airborne wind lidar observations, and is undertaken by DLR (Deutsches Zentrum f. Luft- und Raumfahrt) and OUC (Ocean University of China). The second objective is to carry out the preparation of ACDL through ground-based and airborne lidar observations by CAS-SIOM (Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences), building on the experience made with the validation of Aeolus. The third objective is to study the long-range dust transport, based on ground-based and satellite lidar observations, by OUC.

Already within the first weeks after the launch of ESA´s Earth Explorer mission Aeolus on 22 August 2018, the first atmospheric backscatter measurements and wind profiles were obtained on 5 and 12 September 2018, respectively. This swift availability of observations from ALADIN after launch is considered as a great success for ESA, space industry as well as the algorithm and processor developer teams that had been working together for more than 15 years before launch. This cooperation from the pre-launch phase of Aeolus was extended within a new framework for exploitation activities named Data Innovation and Science Cluster (DISC) and started in January 2019. The Aeolus instrument performance wrt. random and systematic errors for the wind products were assessed by the Aeolus DISC using the numerical weather prediction (NWP) model from the European Centre for Medium-Range Weather Forecasts (ECMWF). In addition, a number of airborne and ground-based validation campaigns were performed for assessing the wind and aerosol product quality by means of collocated observations. DLR performed 3 airborne validation campaigns since the launch of Aeolus with the DLR Falcon 20 aircraft which was equipped with the airborne demonstrator of Aeolus (A2D) and a 2-µm Doppler lidar as a wind reference instrument. The first two campaigns took place in Central Europe and the third one in the region of the North Atlantic around Iceland and Greenland, delivering a comprehensive dataset to be used for the validation of the Aeolus wind product quality. The aim of the Aeolus mission is to provide global observations of vertical profiles of one component of the horizontal wind vector with sufficient accuracy and precision to demonstrate a positive impact on NWP analysis and forecasts. Impact experiments using the ECMWF model show a significant positive impact of Aeolus on the analysis and weather forecast. Today Aeolus observations are used operationally by several NWP centres including ECMWF, German Weather Service (DWD), Météo-France and UK Met Office.

To validate the data products of Aeolus and to varify the measurement principles of ACDL, the following activities are carried out from China side. Ground-based WACAL (WAter vapor, Cloud and Aerosol Lidar) was developed by the lidar group at OUC (Ocean University of China) and deployed during several field campaigns, including the third Tibetan Plateau Experiment of Atmospheric Sciences (TIPEX III) in Naqu (31.5°N, 92.05°E) with a mean elevation of more than 4500 m above MSL in summer of 2014. For validation of Aeolus wind HLOS data products, CDLs (Coherent Doppler Wind Lidars) developed by OUC were also deployed at 17 observation stations in the coastal zone and China Seas for long-term simultaneous observations with Aeolus. The CAL/VAL campaign contributes to exploit the Aeolus wind observations for the study of atmospheric dynamics. As the science application, a long-term large-scale Sahara dust transport event occurred during 14 June and 27 June 2020 is tracked with the spaceborne lidars ALADIN and CALIOP observations and the models ECMWF and HYSPLIT analysis. During 9 and 19 March 2019, an IPDA CO₂ lidar airborne demostrator was mounted on an aircraft to perform the observation of CO₂. The simultaneous ground-based lidars, Fourier Transform infrared Spectrometer (FTS) and sun photometers are emplored for the validation of CO₂ lidar airborne demostrator. Accordingly, the calibration and retrieval method for aerosol optical properties with CDL are developed with the co-located sun photometer measurements.