The objective of this CLIMATE-TPE project is: To improve the understanding of the interactions between the Asian monsoon, the plateau surface (including its permafrost and lakes) and the Tibetan plateau atmosphere in terms of water and energy budgets in order to assess and understand the causes of changes in cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and to predict the possible changes in water resources in the Third Pole Environment. A core innovation of the project is 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 heatings on the Tibetan plateau as precursors of monsoon pattern changes and glaciers retreat, and their impacts on water resources in South East Asia.

We use earth observation, in-situ measurements and modelling to advance process understanding relevant to monsoon scale predictions, and improve and develop coupled regional scale hydroclimatic models to explain different physical links and scenarios that cannot be observed directly. Three work-packages (WP) are defined in the project to address three specific objectives. Objective 1) advancement of the understanding of microwave scattering and emission under complex terrains with permafrost and freeze – thawing conditions. The focus is to reduce current uncertainties in microwave satellite observations over complex terrain and improve retrieval accuracies of soil moisture and freeze-thaw states by deploying in-situ observations, laboratory experiment and numerical modelling. Objective 2) Advancement of physical understanding and quantification of changes of water and energy budgets in the TPE. The focus here is to integrate current understandings in the mechanism of changes in water and energy budget in TPE using satellite data products and numerical modelling. Objective 3) Advancement of quantifying changes in surface characteristics and monsoon interactions. All variables related to water and energy budgets in TPE will be subject to systematic analysis to endure their consistence in terms of climate data records. The variables will include albedo, vegetation coverage, soil thermal and hydraulic properties, LST, soil moisture, lake levels and land use changes among others.

In this contribution we focus on WP1: Observation and modelling of microwave scattering and emission under complex terrains and including permafrost and freeze and thawing.

We have deployed the ESA L-band (1.41 GHz) Radiometer (ELBARA-III, Schwank et al. 2010) since the beginning of 2016 at the central micrometeorological station (latitude: 33.919750, longitude: 102.153183, WGS’84) of the Maqu network of the Tibetan Plateau. ELBARA-III is provided by ESA for experimental observation for the calibration and validation of SMOS data and products.

1) We have conducted ELBARA measurements, covering one complete freeze-thawing cycles, for advancing understanding of the mass and energy exchanges involved in the freeze/thaw process.

2) The collected ELBARA observations are analysed with the recently developed effective temperature model by Lv et al. (2014) to better understand the microwave emission signals, including the validation of ESA’s SMOS and NASA’s SMAP radiometer brightness temperatures (T_B).

3) The collected ELBARA and other in-situ data are used to investigate the effectiveness in two recently developed methods to merge existing satellite data of different frequencies (e.g. for low resolution data SCAT/ASCAT, SSM/I, AMSRE-E/2, SMOS, and high resolution data ASAR/S-1) (Dente et al. 2014; Lv et al. 2014), so that a consistent soil moisture data product can be generated by using the same consistent framework, contributing to the ESA Climate Change Initiative.

Young scientists engaged in this project:

1. Dr. Rogier van der Velde, University of Twente, email: r.vandervelde@utwente.nl, remote sensing of soil moisture
2. Dr. Yijian Zeng, University of Twente, email: y.zeng@utwente.nl, data assimilation
3. Dr. Xin Wang, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China, remote sensing of soil moisture
4. Dr. Xuelong Chen (postdoc, UT) land-atmosphere interactions, boundary layer processes
5. Dr. Donghai Zheng (postdoc, UT) water cycle in the upper Yellow River basin, hydrological modelling
6. Shaoning Lv (PhD student, UT-NIEER) Microwave emission, Soil Moisture and its Impacts on Climate Forecasting
7. Qiang Wang (PhD student, UT) Soil moisture monitoring using Aquarius data
8. Binbin Wang (PhD student, UT-ITP) Energy balance of high plateau lakes
9. Xu Yuan (PhD student, UT) The role of sea surface salinity in the Indian Ocean and its effect on the South Asian monsoon
10. Hong Zhao (PhD student, UT) Retrieval of soil thermal and hydraulic parameters from satellite observations
11. Dongyu Jia (PhD student, NIEER) land-atmosphere interaction study in cold region
12. Prof. Weiqiang Ma, Institute of Tibetan Plateau, CAS, email: wqma@itpcas.ac.cn, remote sensing and atmospheric modelling of land-atmosphere processes
13. Dr. Cunbo Han (postdoc, ITP) land surface processes modelling
14. Lian Liu (PhD student, ITP) Retrieval of thermal and hydraulic parameters from satellite observations on the glaciers
15. Dr. Cristina Aguilar, University of Cordoba, e-mail: caguilar@uco.es
16. Dr. Rafael Pimentel(postdoc, UC)remotely sensed data fusion and assimilation for snow and hydrological modelling. University of Cordoba
17. Gabriel Delgado Leal(PhD student, UC) Water and energy fluxes regime in snow mountain regions
18. Marta Sáenz de Rodrigáñez (PhD student, UC) Remote sensing data fusion to generate long and high resolution time series of snow and hydrological variables
19. Dr. Jian Peng (postdoc, LMU) Thermal and microwave remote sensing of surface energy and water fluxes.
20. Dr. Christiaan van der Tol, University of Twente, email: c.vandertol@utwente.nl, remote sensing of fluorescence
21. Jan Hofste (PhD student, UT),University of Twente, email: j.g.hofste@utwente.nl, remote sensing of land surface by scatterometry and spectroscopy

The Third Pole Environment (TPE) centered on the Tibetan plateau and the Himalayas feeds Asia s largest rivers which provide water to 1.5 billion people across ten countries. Due to its high elevation, TPE plays a significant role in global atmospheric circulation and is highly sensitive to climate change. Intensive exchanges of water and energy fluxes take place between the Asian monsoon, the plateau land surface (lakes, glaciers, snow and permafrost) and the plateau atmosphere at various temporal and spatial scales, but a fundamental understanding of the details of the coupling is lacking especially at the climate scale.
Based on in-situ measurements, satellite remote sensing and numerical modeling, several main achievements have been acquired to promote the understanding of water and energy cycles over the Tibetan Plateau. (1) In-situ measurements: Systematic underestimations of soil heat flux by soil heat flux plate have been proved with estimation from in-situ soil moisture and temperature measurements in CAMP/Tibet. The comparison between in-situ soil heat flux and estimated values from temperature prediction-correction method shows that they have the same heat flux flow direction and phase. However, the in-situ values measured by heat flux plate are generally smaller than the estimation. It was also identified that variations in soil moisture had important effects on carbon exchange in this alpine steppe ecosystem. Both the photosynthesis and respiration were active under high soil moisture content, and suppressed during periods of water shortage. Precise measurements of evaporation and understanding of the physical controls on turbulent heat flux over lakes at different time scales have fundamental significance for catchment-scale water balance analysis and local-scale climate modeling. To test the performance of lake-air turbulent exchange models over high-altitude lakes and to understanding the driving forces for turbulent heat flux and obtain the actual evaporation over the small high-altitude lakes, an eddy covariance observational system was built above the water surface of the small Nam Co Lake. Also we analyzed the variability and trends of daily precipitation extremes over the northern and southern side of central Himalaya, case study on evaluation of future precipitation scenario using statistical downscaling model over humid, sub humid and arid region of Nepal. (2) Remote sensing: Combing satellite remote sensing data and surface meteorological forcing data, land surface heat fluxes at multi-spatiotemporal scales over the Tibetan Plateau have been achieved. The parameterization schemes for diffused and reflected downward shortwave radiation flux of the TESEBS model were improved by introducing the parameters sky-view factor (SVF) and terrain configuration factor (Ct). (3) Model simulation: WRF model was used to estimate surface parameters and related meteorological elements over the Tibetan Plateau. The ground-measured surface variables and land surface heat fluxes were compared to WRF model values. The comparisons show good consistency. Lake-air interactions at Nam Co lake were analyzed through evaluating two popular lake-air exchange models: a bulk aerodynamic transfer model (B Model) and a multi-layer model (M Model). It was found that both models underestimated turbulent fluxes. This was due to inaccurate values of the Charnock coefficient and the roughness Reynolds number which are both important parameters for calculating the roughness length for momentum over water. Also Regional Atmospheric Modeling System (RAMS) was applied to the study of the effect of the topographical altitude of the Tibetan Plateau (TP) on a severe drought event which took place in eastern China from November 2008 to January 2009. (4) Hydrological model: Flow generated from Upper Indus Basin (UIB) originates in Hindukush-Karakoram-Himalaya region, Pakistan. The initial water supply reinstates after winter, depending upon the accumulated snow aggregate and subsequent temperature. Seasonal temperature dictates the state and fate of snow and glacier melt during summer. Recently, developing evidence of warming at high-mountains is accelerated regarded as Elevation dependent warming (EDW). We have identified trends, analyzed variability, and assessed changes in annual and seasonal maximum, minimum, mean and diurnal temperature range. (5) Training of young scientists in the area of climate and environment. Four PhD students have been sent to European partner for joint training. Two of them have got PhD degree in University of Twente under the supervision of European PI (Prof. Z. (Bob) Su) and Chinese PI (Prof. Yaoming Ma). Several European students from our partner also come to China regularly for joint field visiting and academic exchange.

Surface soil moisture (SSM) plays a significant role in various domains of science such as agriculture, hydrology, meteorology and ecology. However, the spatial resolution of microwave SSM products is too coarse for regional and local applications. Most of the current optical/thermal infrared SSM retrieval models cannot estimate the quantitative volumetric soil water content directly without establishing empirical relationships between SSM measurements and satellite derived proxies of SSM. Therefore, this study mainly estimates SSM directly from Chinese geostationary meteorological satellite FY-2E data with a high spatial resolution of 5 km based on an improved elliptical SSM retrieval model developed from the synergistic use of the diurnal cycles of Land Surface Temperature (LST) and Net Surface Shortwave Radiation (NSSR). The original model is developed with bare soil. The coefficients of the original model are not distinguished from different Fractional Vegetation Cover (FVC). To optimize the model for SSM estimation at regional scale, the present study improved the original model by accounting for the influence of FVC, which is based on a dimidiate pixel model and MODIS NDVI product. Ultimately, a preliminary validation was conducted using the ground measurements in the south of Maqu City, in the source area of the Yellow River. A correlation coefficient (R) of 0.620, a root mean square error (RMSE) of 0.146 m³/m³ and a bias of 0.038 m³/m³ are found between in-situ measurement and FY-2E-derived SSM from original model. While it reveals a better relationship between FY-2E-derived SSM from improved model and ground measurement with a R of 0.845, a RMSE of 0.064 m³/m³ and a bias of 0.017 m³/m³. In order to provide more accurate SSM, high accuracy FVC, LST and NSSR are still needed. In addition to the point scale validation, cross comparison with other existing SSM products will be conducted in the future studies.

Urbanization leads to modifications of surface energy balance which governs the momentum, heat and mass transfer between urban canopy layer and the atmosphere, thus impacts dynamic processes in the urban ABL and ultimately influence the local, regional and even global climate. It is essential to obtain accurate urban ABL observations to enhance our understanding of land-atmosphere interaction process over the urban area and help to improve the prediction ability of numerical model. However, up to now, there are rarely observations in high-altitude cities. This poster introduced the urban flux observation conducted in a high-altitude city, Lhasa, using eddy-covariance technique and large aperture Scintillometer. As the first results, the diurnal patterns of the surface energy balance and energy partitioning in the winter of 2016 were discussed.

Lakes are an important part of the landscape on the Tibetan Plateau. The area that contains most of the plateau lakes has been expanding in recent years, but the impact of lakes on lake-atmosphere energy and water interactions is poorly understood and precise measurements of evaporation and understanding of the physical controls on turbulent heat flux over lakes at different time scales is rarely studied due to lack of observational data. To meet the above demands, an eddy covariance observational system was built above the water surface of the small Nam Co Lake (with an altitude of 4715 m and an area of approximately 1.4 km2, mean depth of 7 m) in April 2012 and the results are given by using data over ice free periods in 2012 and 2013 as follows: Firstly, the roughness length for momentum is 3.35×10-4 m over the small lake and the atmosphere is dominated by unstable and neutral conditions. The proper Charnock coefficient (α=0.031) and the roughness Reynolds number (R_r=0.56) for z_0m simulation are obtained for Bulk aerodynamic transfer model (B model) simulation. The simulated heat flux is validated independently with observations in 2013. The B model, with parameters optimized for the specific wave pattern in the small lake, could provide reliable and consistent results with EC measurements, and B model simulations are suitable for data interpolation due to inadequate footprint or malfunction of the EC instrument. Secondly, wind speed shows significance at half-hourly time scales, whereas water vapor and temperature gradients have higher correlations over daily and monthly time scales in lake-air turbulent heat exchange. Lastly, the total evaporation in this small lake (approximately 812 mm) is approximately 200 mm larger than that from adjacent Nam Co (approximately 627 mm) during their ice-free seasons. Moreover, the energy stored during April to June is mainly released during September to November, suggesting an energy balance closure value of 0.97 over the entire ice-free season. These results provide a foundation for application of remote sensing data over the high-altitude small lakes.

To monitor air quality trends in China for the period 2005-2015 we derived SO2 columns and NOx emissions on a provincial level. To put these trends into perspective they are compared with public data on energy consumption and the environmental policies of China. We distinguish the effect of air quality regulations from economic growth by comparing them relatively to fossil fuel consumption. Pollutant levels, per unit of fossil fuel, are used to assess the effectiveness of air quality regulations. We note that the desulphurisation regulations enforced in 2005-2006 only had a significant effect in the years 2008-2009 when a much stricter control of the actual use of the installations began. For national NOx emissions a distinct decreasing trend is only visible since 2012, but the emission peak year differs from province to province. The last three years show both a reduction in SO2 and NOx emissions per fossil fuel unit, since the authorities have implemented several new environmental regulations. Despite an increasing fossil fuel consumption and a growing transport sector, the effects of air quality policy in China are clearly visible.

As a part of our research during the implementation of the DRAGON 3 project we have developed a new technique of using satellite observations to estimate the level of deterioration of the materials used in constructions and cultural monuments. This technique is mainly based on the already developed Dose Response Functions (DRFs) in which the ground-based measurements of various atmospheric pollutants (e.g. nitrogen oxides, sulphur dioxide, ozone) and several climatic parameters, such as air temperature and others, are often used as input data. The values of DRFs of specific materials provide a measure of their corrosion or soiling caused by their outdoor exposure to weather and the air pollution factors. In this work, we evaluate the performance of our proposed technique using the available deterioration experimental data from more than 10 European sites. These data were obtained during different periods since 2005 for cases of four materials (carbon steel, limestone, zinc, modern glass). The term “Remotely Sensed Data-Dose Response Functions (RSD-DRFs)” is proposed for this technique.

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci, there are three Aerosol Optical Depth (AOD) datasets of Advanced Along Track Scanning Radiometer (AATSR) data. These are obtained using the ATSR-2/ATSR dual-view aerosol retrieval algorithm (ADV) by the Finnish Meteorological Institute (FMI)/University of Helsinki (UHEL), the Oxford-RAL Retrieval of Aerosol and Cloud algorithm (ORAC) by the University of Oxford/ Rutherford Appleton Laboratory (RAL) and the Swansea algorithm (SU) by the University of Swansea. The three AOD datasets vary widely. Each has unique characteristics, so none is significantly better than the others, and each has shortcomings that limits the scope of its application. To address this, we propose a method for converging these three products to create a single dataset with higher spatial coverage and better accuracy. The fusion algorithm consists of three parts: the first part is to remove the system errors; the second part is to calculate the uncertainty and fusion of datasets using the maximum likelihood estimate (MLE) method; and the third part is to mask outliers with a threshold of 0.12. The ensemble AOD results show that the spatial coverage of fused dataset after mask is 148%, 13% and 181% higher than ADV, ORAC and SU respectively, and the root mean square (RMSE), mean absolute error (MAE), mean bias error (MBE) and relative mean bias (RMB) are superior to the three original datasets. Thus, the accuracy and spatial coverage of the fused AOD dataset after mask are improved compared to the original data. Finally, we discuss the selection of mask thresholds.

Satellite data from several different instruments are used to study the spatial and temporal distribution of aerosols over China since 1995. In particular ATSR-2 (1995-2003), AATSR (2002-2012), MODIS (2000-present) are used to provide the spatial distribution of the AOD, while CALIOP (2007-present) also provides information on the vertical structure of aerosols, including aerosol type information and in particular dust. The AOD data sets are validated and evaluated versus sun photometer data from AERONET and the Chinese network CARSNET. This is particularly valuable because aerosol retrieval algorithms are developed and validated over areas where many independent ground-based observations are available, such as over the eastern USA and Europe. However, over these areas the AOD levels are often relatively low as compared to China where the occurrence of very high AOD, combined with the variation in aerosol type and surface characteristics, poses particular problems as regards data selection and discrimination between high AOD and the occurrence of clouds.

The spatial distributions over China varies significantly as a result of the multitude of sources, both natural and anthropogenic, which in turn vary with the season. These include anthropogenic sources such as industry and traffic, agricultural and natural biomass, dust from two major deserts, as well as the seasonal production of precursor gases. In addition, economic development and measures to improve air quality affect the long term variation of aerosol concentrations. Meteorology and large scale circulation including the seasonally progressing monsoon have a substantial effect on the aerosol physical properties as well as on production and removal of the aerosol particles. All of these effects vary with location over China and their seasonal and year-to-year variatons.

An initial analysis of the spatial and vertical variability of the AOD will be presented together with time series showing the variation over representative areas. Satellite derived information on aerosol precursor gases NO₂, SO₂ and BVOCs will be used in the analysis.

These activities are undertaken as part of the EU-FP7 project MarcoPolo. The main objective of the MarcoPolo project is to improve air quality monitoring, modelling and forecasting over China using satellite-retrieved information on aerosols, NO_x, SO₂, and biogenic gases. This information will be used in air quality models to invert emission estimates. The results, together with known information from ground-based measurements, will then be used to construct an emission database over China. The MarcoPolo project finished in March 2017 and will in part be continued in the framework of the ESA DRAGON4 initiative.

Atmospheric pollution is a severe problem in China, it is an important to keep on our monitoring and satellite validation of trace gases, BVOC emissions, aerosols in China, especially at some representative sites. Our main activities are ground observations, validation of satellite retrievals and satellite data applications. To fulfill one of all above tasks, measurements of BVOC emissions, O₃ and solar radiation were carried out in a subtropical Pinus plantation in China during 2013-2016. BVOC emissions were measured using a relaxed eddy accumulation (REA) technique and a gradient technique. Monoterpenes were the dominant VOCs in this subtropical Pinus plantation. Isoprene and monoterpene emissions showed obvious diurnal, seasonal and inter-annual variations. In comparison with 2013, annual BVOC emissions decreased in 2015, which were associated with decreases of PAR, temperature and water vapor. O₃ concentration above the canopy level also displayed clear diurnal variation. It was found that BVOC emissions were influenced by biomass burning smoke and pine florescence. The mean emission factors determined using the MEGAN model emission algorithms and empirical model of BVOC emissions were 0.71 and 1.19 mg m^-2 h^-1 for isoprene and 1.39 and 1.65 mg m^-2 h^-1 for monoterpenes, respectively. Flux measurements of BVOCs at a subtropical bamboo plantation in China were used to evaluate the bottom-up inventory of isoprene emissions and the satellite-based MarcoPolo (Monitoring and Assessment of Regional air quality in China using space Observations) emission inventory for isoprene derived using inversion of satellite columns of formaldehyde. Generally, the space-based inventory provides a satisfactory agreement with the observations in summer. Further validation in this subtropical plantation will be carried out in the future. All measure and validated data will be provided for air quality models, so as to improve our abilities in the forecast of air quality.

Key words: Biogenic volatile organic compounds; emission fluxes; ground measurement; validation; satellite.

We compare 9 emission inventories of nitrogen oxides including four satellite-derived NO_x inventories and the following bottom-up inventories for East Asia: REAS (Regional Emission inventory in ASia), MEIC (Multi-resolution Emission Inventory for China), CAPSS (Clean Air Policy Support System) and EDGAR (Emissions Database for Global Atmospheric Research). Two of the satellite-derived inventories are estimated by using the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm, which is based on an extended Kalman filter applied to observations from OMI or from GOME-2. The other two are derived with the EnKF algorithm, which is based on an ensemble Kalman Filter applied to observations of multiple species using either the chemical transport model CHASER and MIROC-chem. The temporal behaviour and spatial distribution of the inventories are compared on a national and regional scale. A distinction is also made between urban and rural areas. The intercomparison of all inventories shows good agreement in total NO_x emissions over Mainland China, especially for trends, with an average bias of about 20% for yearly emissions. All the inventories show the typical emission reduction of 10% during the Chinese New Year and a peak in December. Satellite-derived approaches using OMI show a summer peak due to strong emissions from soil and biomass burning in this season. Biases in NO_x emissions and uncertainties in temporal variability increase quickly when the spatial scale decreases. The analyses of the differences show: the importance of using observations from multiple instruments and a high spatial resolution model for the satellite-derived inventories, while for bottom-up inventories, accurate emission factors and activity information are required. The advantage of the satellite derived approach is that the emissions are soon available after observation, while the strong point the bottom-up inventories is that they include detailed information of emissions for each source category.

The accuracy requirements of satellite remote sensing of atmospheric composition and, in particular, greenhouse gases are challenging. The validation of the measurements is highly important in the development of satellite remote sensing systems.

The Chinese team has developed XCO₂ retrieval algorithm for TanSat Level 2 data processing and has updated it after the successful launch of TanSat in December 22, 2016. The FMI team has carried out validation studies of GOSAT and OCO-2 satellite retrieval results and they plan to contribute to the validation of TanSat observations. To support the satellite validation using FTS observations, AirCore CO₂ profile observations at Sodankylä will be used. Both FMI and IAP teams will work together to verify and investigate the precision of the retrieval results.

It is well established that the increase in atmospheric concentrations of CO₂ and CH₄ due to anthropogenic activities is a major driver for climate change. However, our understanding of the role of natural and anthropogenic contributions to the carbon cycle within a dynamic Earth system is still insufficient which leaves predictions of our future climate uncertain.

We have now access to dedicated satellite observations of atmospheric CO₂ and CH₄ concentrations which provide us with densely sampled data over regions poorly sampled by surface networks. This allows us to critically test and evaluate models of the carbon exchange for key regions such as China.

Currently, three CO₂ satellite sensors are in orbit, JAXA’s GOSAT, NASA’s OCO-2 and the Chinese TanSat mission, which gives us an unique opportunity to intercompare observations from multiple space-based CO₂ datasets over China and to use them jointly to assess model calculations.

Due to the anthropogenic greenhouse gas emissions our climate is changing. Climate forecasts are needed so that we can prepare, mitigate and adapt to the changing climate. The high northern latitudes are especially sensitive to climate change. The quantification and monitoring of the carbon cycle processes are crucial for the understanding of climate system feedbacks. Recently launched satellite instruments mesuring greenhouse gases provide important information related to the carbon cycle processes that can jointly be analysed with ground based observations and compared/combined with modeling. In this presentation we discuss recent recearch activities that have taken place at the the Finnish Meteorological Instiute related to satellite observation of greenhouse gases. Moreover, we present our plans to participate in the validation of Chinese TanSat satellite’s carbon dioxide observations using ground based instruments at Sodankylä as well as our plans on using the TanSat data for studying spatial and teporal variability of carbon dioxide and emisison regions.

Atmospheric Carbon dioxide (CO₂)is one of the major anthropogenic greenhouse gas that remains significant uncertainties in global carbon cycle and climate change studies. Hyper spectral near infrared and shortwave infrared (NIR/SWIR) measurement from space could provide global column-average CO₂ dry-air mixing ratio (XCO₂) in advanced accuracy and precisions to reduce the uncertain of climate prediction. After the Greenhouse gas monitoing satellite including GOSAT and OCO–2 from USA-NASA and Japan-JAXA, China’s carbon dioxide observation satellite (TanSat) has been successful launched in 2016. TanSat is a carbon dioxide observation satellite funded and supported by the Ministry of Science and Technology of the People’s Republic of China and the Chinese Academy of Sciences. The TanSat retreival algorithm has been developed to approeach the XCO₂ in a highly accuracy and precision reqiurment. The TanSat algortihm has been applied on GOSAT (ATANGO) and OCO-2 measumrent and well optimaized before it applied in TanSat operational data processing. The retrieval algorithm and its perfomance over China has been studied. The ATANGO data product has been used in carbon flux inversion in China.

Anthropogenic CO₂ emissions from fossil fuel combustion have large impacts on climate. In order to monitor the increasing CO₂ concentrations in the atmosphere, accurate spaceborne observations—as available from the Orbiting Carbon Observatory-2 (OCO-2)—are needed. This work provides the first direct observation of anthropogenic CO₂ from OCO-2 over the main pollution regions: eastern USA, central Europe, and East Asia. This is achieved by deseasonalizing and detrending OCO-2 CO₂ observations to derive CO₂ anomalies. Several small isolated emission areas (such as large cities) are detectable from the anomaly maps. The spatial distribution of the CO₂ anomaly matches the features observed in the maps of the Ozone Monitoring Instrument NO₂ tropospheric columns, used as an indicator of atmospheric pollution. The results of a cluster analysis confirm the spatial correlation between CO₂ and NO₂ data over areas with different amounts of pollution. We found positive correlation between CO₂ anomalies and emission inventories. The results demonstrate the power of spaceborne data for monitoring anthropogenic CO₂ emissions.

China represents a significant contribution to global observed variations of atmospheric carbon dioxide (CO₂) due to its large landmass, and its high fossil fuel emissions associated with unprecedented economic growth. We report CO₂ fluxes in 2014 and 2015 inferred, using an ensemble Kalman Filter [Feng et al, 2009], from data collected from five new regional background ground-based sites over China (together with available NOAA sites), and fluxes inferred from OCO-2 (version 7) and GOSAT (UoL v7) XCO₂ data. We find that the resulting posterior CO₂ concentrations are generally consistent with independent validation data downwind of the Chinese mainland. To better understand the response of the Chinese biosphere to the 2015 El Niño we compare the magnitude and distribution of CO₂ fluxes inferred from different data sets. We find that the net CO₂ emissions over China inferred from GOSAT and OCO-2 XCO₂ retrievals are higher than those from the in-situ data. Our results highlight the importance of space-based observations for top-down flux inversions. Chinese TanSat project, together with existing and planned missions, will significantly improve flux estimates over China.

CO₂ is a long-lived trace gas which acts as the most important greenhouse to the global climate. For its short-wavelength transparent and long-wavelength absorbed characteristic, the increase of CO₂ caused by human activities induces global warming and a series of climate changes since the industrial revolution. Although it is almost well-mixed in the atmosphere, CO₂ mixing ratio varies with time, decreases with altitude, and spaces between sources and sinks, the temporary emissions such as fires and burning occurring near the surface on regional scale changing CO₂ mixing ratio sharply and damped by atmospheric transport and diffusion in a short time. It is necessary to infer the spatial distribution of carbon sources and sinks distribution with repeated CO₂ measurements on a large scale, and this requires very demanding measurement accuracy to the relative small variation of CO₂ in the atmosphere. A stringent precision of space-borne CO₂ data, for example 1 ppm or better, is required to address the largest number of carbon cycle science questions. A high measurement sensitivity and global covered observation is expected by space-borne IPDA (Integrated Path Differential Absorption) lidar which has been designed as the next generation measurement. By selecting the absorption features of the lidar operating wavelength appropriately, IPDA lidar could obtain the dry air total column CO₂ mixing ratio named XCO₂ by compared two echo pulse signals reflected from the Earth with a high weight to the boundary layer. In this paper an assessment is made to describe the various error sources limiting the accuracy and precision of the measurement. An overview is presented of the relative contribution of each error source including the inadequate knowledge of the atmosphere pressure and temperature, surface reflectivity, reflected surface elevation, and errors from lidar system such as shot noise, dark noise and spectral purity. A global simulation is used to investigate the sources of errors associated with the configurations of lidar system and the environment parameters. The simulation is carried out over global scale with atmosphere pressure and temperature from NCEP, surface elevation model and surface reflectivity from MODIS, and the CO₂ distribution is from OCO-2 dataset. The results identifies that surface albedo plays an important role in the process of satellite remote sensing. It may be inferred that errors impacted by reflectance of the Earth vary with seasons. This would need an improved acknowledge on seasonal variations of surface reflectivity and provide a guidance for improving the accuracy of space-borne IPDA detection.

The atmospheric particles have a remarkable impact on the global environment and climate change. The long-range transport of dust is an important part of the global biogeochemical cycles. It is significant and urgent to investigate dust on its optical properties, long-range transport, aging, and deposition. ESA decided to implement the Atmospheric Dynamics Mission ADM-Aeolus and the Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) to provide global profiles of wind, clouds, aerosols, and properties together with derived radiative fluxes and heating rates. ADM-Aeolus will carry the first wind lidar in space and launch is currently scheduled for the end of 2017. EarthCARE will carry cloud profiling radar, HSRL (High Spectral Resolution Lidar) and multispectral imager and is scheduled for launch in 2018. The research goals of TROPOS are investigations to aerosol type characterizations and the impact of aerosols on clouds and their properties. For this purpose, TROPOS developed several multiwavelengths and polarization Raman lidar systems (about 10 PollyXTs, MARTHA and BERTHA) and is using these systems at different continents. The recent and ongoing campaigns are the Central Asian Dust Experiment (CADEX), the Widefield Sky Scatterer Tomography by Lidar Anchor together with Technion Haifa, the Atlantic atmospheric observation experiment (OCEANET), and the Cyprus Clouds and Aerosol and precipitation experiment (CyCARE). 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. HSRL and CDL (Coherent Doppler Wind Lidar) developed by OUC were also deployed in several field campaigns in the coastal zone and China Seas. Lanzhou University (LZU) established a Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) and conducted lidar observations of dust aerosol physical optical characteristics near the resource area in the northwest of China. In order to investigate the characterization of atmospheric bioaerosols along transported pathways of dust aerosols, a multi-channel lidar spectrometer system was developed to observe Mie, Raman scattering and laser-induced fluorescence excitation at 355 nm from the atmosphere. Long-range transport of Asian dust from the Taklimakan and Gobi deserts was studied based on CALIPSO lidar measurements. German Aerospace Center's (Deutsches Zentrum für Luft- und Raumfahrt; DLR) Institute of Atmospheric Physicsa (IPA) is a member of ESA´s ADM-Aeolus Mission Advisory Group, Head of ESA funded pre-launch campaign study and contributor to algorithm and processor studies for Aeolus data products. DLR-IPA conducted several flights in the Mediterranean area which aimed at aerosol (incl. Saharan dust) detection using the ALADIN Airborne Demonstrator (A2D).

The first project objective is the comprehensive observations of vertical profiles of optical properties, flux and the deposition of dust during the long-range transport over continents of Europe and Asia. Based on the ground-based PollyXT, WACAL, CDL and HSRL, ADM-Aeolus and EarthCARE satellites, combining back trajectory model from NOAA, it is available to determine the dust source region, the main transport route and the main deposition areas. The second project objective is to validate the ADM-Aeolus and EarthCARE wind, cloud and aerosol data products. Ground-based co-located measurements with PollyXT, BERTHA, WACAL, CDL and HSRL lidars during overpasses of Aeolus and EarthCARE are foreseen in China (Costal cities, China Seas, inland cities, Tibetan Plateau, Taklimakan desert) and in Central Europe. An overview of the field campaigns will be presented in this report together with observation results from the ongoing data analysis.

The spaceborne wind lidar ALADIN shall provide vertical wind profiles
within the ESA Earth Explorer Atmospheric Dynamics Mission (ADM) Aeolus. After
launch end of 2017 such profiles will be available on a global scale for the
first time to improve the quality of numerical weather prediction (NWP). The ALADIN
Airborne Demonstrator (A2D) was developed at DLR (German Aerospace Center)
focusing on a high degree of commonality in terms of laser source and Doppler
lidar receiver design. With these features operating at the same ultraviolet
wavelength of 355 nm as the satellite, it is the key instrument for the
planned calibration and validation activities. Since 2005, A2D has been
deployed in a series of ground and airborne campaigns to support the Aeolus
mission by validating retrieval algorithms, the instrument concept and
operation procedures. In September and October 2016, the international airborne
campaign NAWDEX (North Atlantic Waveguide and Downstream Impact Experiment)
based in Iceland was the framework to significantly extend the wind data-set
from A2D and the coherent 2-µm wind lidar, both on-board the DLR Falcon
research aircraft. While the Falcon mainly focused on jet-stream intersections
and calibration-validation procedures, other aircraft and ground stations
delivered a comprehensive suite of additional measurements to complement the
meteorological picture. For the first time flights with this payload of the
Falcon were performed in coordination with the German HALO deploying an aerosol
lidar, cloud radar and dropsondes as well as the French Falcon with on-board
cloud radar and UV aerosol Doppler lidar. Subsequent to the NAWDEX campaign additional
flights were conducted in the Mediterranean area which aimed at aerosol (incl. Saharan
dust) detection using the A2D. An overview of the field experiments will be
presented together with first results from the ongoing data analysis.

The spaceborne Aerosol and Carbon dioxide Detection Lidar (ACDL) will measure the global column concentrations of carbon dioxide (CO₂) and aerosols profiles. The column concentrations of carbon dioxide are measured by integrated path differential absorption (IPDA) lidar technique. The aerosols and clouds profiles are obtained by high resolution spectrum lidar (HRSL) technique. Both techniques are combined in the ACDL lidar payload. The dedicated atmosphere and environment monitoring satellite will carry the ACDL lidar and is scheduled to launch in about 2020. The spaceborne engineering prototype of the lidar with 1m SiC telescope was developed in 2016. And the single frequency and three wavelength laser with high pulse energy was developed and the environmental vibration testing was carried out. A ground-based double-pulse 1572 nm IPDA lidar is developed for carbon dioxide concentrations measurements. The lidar measured carbon dioxide concentrations continuously by receiving the scattered echo signals from a building about 1300 m away. On the same time the other two instruments of TDLAS (Tunable Diode Laser Absorption Spectroscopy) and in-situ carbon dioxide analyzer measured the carbon dioxide concentrations. The carbon dioxide concentrations bias between IPDA lidar and TDLAS measurement was validated to be less than 2 ppm. An airborne lidar prototype with high altitude platform is being developed to verify the retrieval algorithms of spaceborne ACDL lidar. The lidar will also be implemented to validate the Chinese passive CO₂ measurement satellite TanSat in future.

The Microwave Radiometer (MWR) flown on Envisat, ERS-1 and ERS-2 provides a nearly uninterrupted time series of microwave observations over a period almost 21 years between 1991 and 2012. This dataset is complementary to other microwave datasets. From 2011, the Atmospheric Correction Microwave Radiometer (ACMR) on HY-2 provides similar measurement.

Firstly, we report on our efforts towards a fully inter-calibrated and validated physical retrieval of TCWV and LWP for MWR. We will address issues related to satellite inter-calibration, homogeneity of the derived time series of brightness temperatures, observation-simulation biases, and provided first results of fully physical retrievals.

Secondly, an outlook on ongoing and planned activities within Dragon-4 will be given and the importance of the results in light of the upcoming Sentinel-3 mission and the HY-2 series will be discussed.

Calibration and validation (Cal&Val) is one of the most important means for assuring satellite payload performance and data quality. It could guarantee the accuracy of the retrieved information, make the remote sensing data consistent and traceable, and maintain the sensor performance during the operational phase. The challenges in the Cal&Val include the lack of consistent remote sensing (RS) product assessment standards, the uncertainties introduced by atmospheric effect, as well as the gaps in non-synchronous measurements between satellite observation and in situ measurements. In this project, great achievement has been done in carrying out cooperative research on the high-frequency optical calibration with the aid of the Radiometric Calibration Network (RadCalNet) activities and permanent targets over Baotou site in China.

(1) Development of automated radiometric calibration system and its operations. On benefit of RadCalNet and the cooperation of the Cal&Val experts from European and Chinese intuitions in the DRAGON programme, the automated surface spectral reflectance measurement system has being developed and installed over four permanent targets with different reflectance in Baotou site, which can automatically and traceably acquire the target characteristics and atmospheric parameters. In consideration of the land surface variety and the adjacent effect, the TOA radiance is simulated with the input of a background reflectance driving the MODTRAN, and the Level 1 BOA reflectance product is generated according to the input files defined by RadCalNet data center.

(2) Automated radiometric calibration demonstration for Chinese and European satellites. The data portal for standard product service has been established under the leadership of ESA, and now is in operation. Since the late last year, ESA have organized test users to calibrate their satellites using the RadCalNet standard products over four demonstrated sites. Among them, the predicted TOA radiance over Baotou site is compared with the observations of Sentinel-2a, ZY-3, GF-1, etc. This is not only important to validate the calibration capability of Baotou site, but also would greatly benefit improving the calibration accuracy of optical sensors, and assuring the data consistency from different sensors.

(3) The uncertainty analysis on the standard radiometric calibration product. The calibration uncertainty over Baotou site include the following aspects: 1) Traceable accuracy and measurement repeatability of the automated measurement system, traced to the primary standard of NPL through the transfer calibrator; 2) Non-uniformity and BRDF effect of the ground standard targets; 3) Measurement errors of typical atmospheric parameters, which are given by AERONET since the sun-photometer Cimel CE-318 in Baotou site has been included in AERONET; 4）Adjacent effect, caused by the point spread function (PSF) of the imaging system and the multiple scattering among surface and atmosphere; 5) Uncertainty aroused by radiative transfer calculation of MODTRAN, which is simulated based on Monte-Carlo theory.

A ground-based MAX-DOAS and a Bruker IFS 125HR have been deployed in Xianghe Station, Northern China, of the Institute of Atmospheric Physics, Chinese Academy of Sciences, and another Bruker IFS 125M has been installed in Xinglong Station. The MAX-DOAS has been running for more than ten years, providing a large number of high quality data of NO₂, SO₂, etc., for deriving their trends, and for validating the satellite products of OMI, GOME-2, and SCIMACHY. In Xianghe station, CIMEL sunphotometer, gas analyzers, automatic meteorological station, and a 100-meter tower can provide aerosol optical properties, air quality status, and meteorological conditions in the planet boundary layers. The two Bruker FTIR instruments in Xianghe and Xinglong stations aim at providing the greenhouse gas such as CO₂, CH₄, N₂O, and for validation of GOSAT, OCO-2, and TanSat products in future. The FTIR in Xinglong station has been operating for more than one year, and some data has been obtained, which has been used for validation of GOSAT products.

Key words: MAX-DOAS, FTIR, NO₂, CO₂, Xianghe Station.

Global monitoring of precipitation is important because of its significant human consequences. However, the multiplicity of hydrometeor types and their small- and large-scale spatial inhomogeneities make accurate measurements difficult. For example, rain gauge measurements are significantly impaired by wind, poor global coverage, and the non-uniformity of rain. Both ground-based radars and passive microwave satellite sensors sense precipitation aloft and are generally unable to discern how much of that precipitation evaporates before impact.

The paper develops a passive sub-millimeter precipitation retrievals algorithm for Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Feng Yun 3C (FY-3C) satellite. The retrieval algorithm employs a number of neural network estimators trained and evaluated using the validated global reference physical model NCEP/WRF/ARTS, and works for seawater. NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF, and derive the typical precipitation data from the whole world. The Atmospheric Radiative Transfer Simulator ARTS is feasible for performing simulations of atmospheric radiative transfer. Rain detection algorithm has been used to generate level 2 products. Retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution, which is in good agreement with those retrieved using the Precipitation retrieval algorithm version 1(ATMP-1) for Advanced Technology Microwave Sounder (ATMS) aboard Suomi NPP satellite.

Meanwhile, calibration and validation between similar instruments onboard different satellites are also important to ensure the validity of observations and accuracy of precipitation retrievals. In the ongoing work, we are going to carry out the calibration and validation among FY-3C MWHTS, FY-3B MWHS and ATMS.

The Environmental trace gases Monitoring Instrument (EMI) onboard Chinese high-resolution remote sensing satellite GF-5 is an imaging differential optical absorption spectrometer, expected to be launched in September of 2017. The EMI instrument will measure earthshine radiances with the wavelength range from 240 to 710 nm at moderate spectral resolution (0.3-0.5nm) at nadir. The EMI is tasked with quantitatively measuring global distribution of tropospheric and stratospheric trace gases such as NO2, O3, and SO2. The prelaunch calibration phase is essential to acquire necessary knowledge on the properties and performance of the EMI instrument as well as support data processing and retrieval. This work focus on nitrogen dioxide retrieval from on-ground measurements of gas cell and atmospheric scattering light, and an evaluation of the performance of the EMI instrument from the retrieval.