Recently, with the rapid developments of economy and industry, how to reduce heavy air pollution has been a challenging task for Chinese people and the Chinese government. In order to study air pollutants and their chemical transformation in North China, variations of the concentrations of atmospheric constituents were analyzed for four representative sites in North China during 2005-2015. Satellite-derived vertical column densities (VCDs) of SO₂, NO₂, O₃, HCHO, and aerosol optical depth (AOD) over these four sites were used together with ground-based radiation and meteorological measurements at each site. On the base of the analysis, a photochemical mechanism relating the formation of PM_2.5 and O₃ in North China was given. In particular, the key role of volatile organic compounds (VOCs) in chemical and photochemical reactions is found to be prominent in the summer season. We make some suggestions for air pollution control in North China, especially to reduce anthropogenic VOC emissions and artificial biogenic VOC emissions.

Key words: Trace gases, particulate matter (PM), emission, solar radiation, air pollution control.

We study air quality over China using satellite observations, especially their spatial and temporal variability. For the period 2007-2017 we derived monthly SO₂ and NO_x emissions for China on a provincial level. To derive NO_x emission we applied the inversion algorithm DECSO v5.1 to OMI NO₂ retrievals of the newly developed QA4ECValgorithm. In DECSO modelled NO₂ concentrations are constraint by the NO₂ satellite observations using a Kalman filter technique. SO₂ is derived for each year by applying a correction factor to the MEIC SO₂ emissions based on the derived provincial trend in SO₂.
Both the SO₂ and NO_x emissions are used in the regional chemical-transport model CHIMERE. This model participates in an ensemble forecast of 9 operational models for East China. The ensemble forecast is compared to in-situ observations and performs better than each individual model.
The results will be validated using ground observations of the network of in-situ instruments in the cities and also using measurements at specific ground stations in different types of forests.

Using the inversion algorithm DECSO we derived monthly NO_x emissions on a 0.25 x 0.25 degree resolution over East Asia for an 11-year period (2007 to 2017) based on OMI observations. We used these emissions to analyse trends and seasonal cycle of maritime emissions over Chinese seas. No effective regulations on NO_x emissions have been implemented for ships in China, which is reflected in the trend analysis of maritime emissions. The effect of maritime emissions on the air quality over land will be discussed. Simulations by an atmospheric chemistry transport model show a notable influence of maritime emissions on air pollution over coastal areas, especially in summer. The satellite-derived spatial distribution and the magnitude of maritime emissions over Chinese seas are in good agreement with bottom-up studies based on the Automatic Identification System of ships.

Dose-Response Functions (DRFs) are a very important tool for estimating the deterioration – degradation of structural materials, used in both modern constructions and cultural heritage monuments, due to atmospheric pollution and climatological parameters. To date, the available in literature DRFs make use of ground based air pollution and climatological data in order to model materials’ deterioration. This limits the possibility of using DRFs only in areas where the necessary ground based data, are available. In this study are presented the first results of the attempt to develop new kind of DRFs that will model the deterioration – degradation of materials, in particular carbon steel and limestone, using only satellite data. This new kind of DRFs is expected to help in monitoring materials deterioration – degradation to areas where there are no available ground based data as well as expanding the usage of satellite data by introducing a totally new field of implementation. The term “Satellite Sensed Data-Dose Response Functions (SSD-DRFs)” is proposed for this new kind of DRFs.

Atmospheric particulate matter (PM) from both natural and anthropogenic emission sources can bring adverse effects on public health. Long-term exposure to particular matter with aerodynamic diameters less than 2.5 μm (PM_2.5) can cause lung and respiratory diseases and even premature death. PM_2.5 not only threatens people's health, but also causes the decrease of atmospheric visibility and the degradation of the city scenery. In recent years, with the rapid development of industrialization and urbanization, PM_2.5 has become the primary air pollutant in China, especially in most major cities, such as Beijing, Shanghai and Guangzhou, where the fastest economic growth has occurred. To understand the effects of PM_2.5 on the Earth’s environmental system and human health, it is necessary to routinely monitor PM_2.5. Given the considerable advantages of satellite remote sensing, especially the large coverage provided at the spatial scale and stable continuity at the time scale, aerosol optical depth (AOD) retrieved from satellite sensors has been widely considered to be a good method for atmospheric PM monitoring. There was a distinct spatial pattern of correlation between AOD retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based in situ PM concentrations. In this study we established three types of AOD-PM_2.5 retrieving model based on Physical and Artificial Neural Network technology. Firstly, we using satellite retrieved AOD and other meteorological parameters such as the planetary boundary layer height (PBLH), temperature (TEMP), relative humidity (RH), U wind component (U), V wind component (V), surface pressure (SP), and large-scale precipitation (LSP), to establish GA-BP ANN AOD-PM_2.5 retrieve model. The test correlation coefficient R reached 0.83. This model is seasonally and regionally stable. The satellite AOD and ANN retrieved PM_2.5 has the similar trend and distribution, and the trained model have practical as well as theoretical value. Then, a physically-based model is developed to estimate the concentration of PM_2.5, in which, fine mode aerosol optical depth (AOD) at 440, 550 and 675nm, Effective Radius of the Fine particles, ground-based fine particulate matter (PM_2.5) data, relative humidity (RH) and boundary layer height (BLH) data are used. We proposed a new way to derive the integrated extinction efficiency <Qext> by using aerosol parameters in AERONET together with PM_2.5observations. The results show that R²can reach to 0.70 and Root Mean Square Error (RMSE) is 33.67 μg/m³ at Beijing site at 440 nm. The results are comparable with other findings based on physically-based methods. Finally, we also tested the performance of Specific Particle Swarm Extinction Mass Conversion Algorithm using remotely sensed data. Ground-level observed PM_2.5, Planetary Boundary Layer Height (PBLH) and relative humidity (RH) reanalyzed by European Centre for Medium-Range Weather Forecasts (ECMWF), aerosol optical depth (AOD), Fine Mode Fraction (FMF), particle size distribution, refractive indices from AERONET of Beijing area are used. The validation of PM_2.5 from SPSEMCA algorithm to AERONET observation data and MODIS monitoring data achieve acceptable results, R = 0.70, RMSE = 58.75μg/m³ for AERONET data, R = 0.6, RMSE = 48.36 μg/m³ for MODIS data, respectively. Then the trend of temporal and spatial distribution of Beijing and surrounding areas has been revealed. On the whole, this study will provide practical method for PM_2.5 estimation based on satellite data.

The present study aims to investigate spatio-temporal evolution and trend in the aerosol optical properties (aerosol optical depth, AOD; Ångström exponent, AE), qualitatively identify different aerosol types and sources over an urban city, Nanjing in the Yangtze River Delta, East China. For this purpose, the Collection 5.1 Level-2 data obtained from the MODIS sensor onboard Terra and Aqua satellites, the MISR, and the OMI for the period between 2002 and 2015 have been analyzed. A notable spatiotemporal heterogeneity was observed in the optical properties of aerosols on the seasonal scale over East China. The seasonal mean AOD₅₅₀ (AE_470-660) was found to be maximum with 0.97 ± 0.48 during summer (summer) (1.16 ± 0.33) and a minimum of 0.61 ± 0.28 during the winter (spring) season (0.80 ± 0.28). AE_470-660 found higher in summer indicate relative abundance of fine mode aerosols over the coarse mode. Annual mean Terra AOD₅₅₀ showed a strong decreasing trend (–0.70% year^-1), while the Aqua exhibited a slight increasing trend (+0.01 year^-1) during the study period. We also used the HYSPLIT model for presenting cluster trajectory analysis which revealed that the airmasses from different source regions contributed greatly to aerosol loading. Using the AOD-AE method (hereafter called as Technique-I), five major aerosol types were identified. In all the seasons, the mixed (MX) type of aerosol is dominant followed by the biomass burning/urban-industrial (BU) and desert dust (DD) aerosol types during summer and spring seasons, respectively. Further, the sub-classification of aerosol types was carried out considering into account of the characteristics of absorbing aerosol index (AAI) (hereafter called as Technique-II). The two clustering techniques showed reasonable consistency in the obtained results. The various aerosol types (absorbing and non-absorbing) and their change over a region are highly helpful in fine tuning the models to decrease the uncertainty in the radiative and climatic effects of aerosols.

With the rapid development of China's economy and high rate of industrialization, environmental pollution has become a major challenge for the country. The present study is aimed at analyzing spatiotemporal heterogeneities and changes in trends of different aerosol optical properties observed over China. To achieve this, Collection 6 Level 3 data retrieved from the MODerate resolution Imaging Spectroradiometer (MODIS; 2002-2016) and Ozone Monitoring Instrument (OMI; 2005-2016) sensors were used to investigate aerosol optical depth (AOD₅₅₀), Ångstrӧm exponent (AE_470-660) and absorption aerosol Index (AAI). The spatial distribution of annual mean AOD₅₅₀ was noticed to be high over economically and industrialized regions of east, south and northeast regions of China; while low aerosol loadings were located over rural and less developed areas of west and northeast of China. High AE_470-660 (>1.0) values were characterized by the abundance of fine-mode particles and vice-versa, likely attributed to large anthropogenic activities. Similarly, high AOD with corresponding high AE and low AAI were characterized over the urban-industrialized regions of central, east and south of China during most of the months; being more pronounced in June and July. On seasonal scale, AOD values were found to be high during spring followed by the summer and autumn, and low during the winter season. It is also evident that all aerosol parameters showed a single peak frequency distribution in all seasons over entire China. Further, the annual, monthly and seasonal spatial trends revealed a decreasing trend in AOD over most regions of China, except in the southwest of China which showed a positive increasing trend. Significant increasing trends were noted in AAI for all the seasons, particularly during autumn and winter, resulted in a large amount of absorbing type of aerosols produced from biomass burning and desert dust.

Cloud and aerosol are the important part of the gas system and plays an important role in the radiation budget. The Changes in aerosols and associated radiative forcing, and their impact on the climate system have been highly valued by the scientific community in the recent years due their large uncertainty factor. In recent decades, the rapid development of social economy in East China, aerosol particles emissions and production of secondary aerosol pollutants by photochemical reactions are also increasing, caused serious environmental and climate problems. Hence, it is important to study the temporal and spatial distribution of aerosols in this region, and understand the aerosol-cloud interactions.

In the present study, we examined the spatial and temporal variations in aerosol optical depth (AOD) at 550 nm and its relationship with various cloud parameters derived from the Moderate resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra satellite during 2000-2016. High mean AOD values were observed in almost all regions during the summer season, with low values in autumn/winter seasons. The Angstrom exponent that increases with AOD is opposite; to what would be the case if swelling of particles due to hygroscopic growth near cloudy areas played a major role in the MODIS data. We then analyzed the relationships between AOD and four other cloud parameters, namely water vapor (WV), cloud fraction (CF), cloud top temperature (CTT), and cloud top pressure (CTP). The correlation between AOD and CF was greater than 0.5 in Shandong province, and in the northern part of the study area, it is lower than 0.2. The analyses showed strong positive correlations between AOD and WV over Fujian and Zhejiang Provinces. The correlation between AOD and CF was positive for urban and desert regions; and negative over coastal locations of East China. AOD showed a similar correlation with CTP and CTT in all regions with negative correlation coefficient which also follows the second indirect effect of aerosols; but positive correlations were found in some parts of the southern region.

Thirteen years of continuous tropospheric NO₂ observations from OMI provide insight into the air quality levels in China. The use of these daily NO₂ concentrations for emission estimates of NO_x attempts to fill in for inaccuracies and temporal discontinuities of the bottom-up emission inventories, keeping the NO_x emission estimates up-to-date. Furthermore, this top-down approach inherently takes into account rapid changes in emissions caused by economic activity, political regulations or even events such as fires.

Within the framework of the newly developed EU QA4ECV project and the GlobEmission project, algorithms have been developed to derive NO₂ concentrations and NO_x emissions, respectively, from space with more accuracy. We demonstrate the detection of spatially and temporally heterogeneous changes in NO_x emissions derived from the DECSO v5.1 algorithm after it is applied to OMI NO₂ observations derived with the DOMINO v2 and QA4ECV algorithms over China from 2004 up to 2017. QA4ECV provides improved OMI NO₂ retrieval products with detailed uncertainty estimates and quality indicators. We investigate to what extent it is now possible to also improve trend detection limit as compared to the previous DOMINO v2 datasets. We observe a distinct increasing trend until about 2012 and a distinct decreasing trend from about 2012 onwards.

To put these trends into perspective we compare them with public data on energy consumption, traffic records, shipping and economic activity, and the environmental policies of China and we study their impact on the emission trends. The emissions are also compared to bottom-up emissions and their inconsistencies are discussed.

Tropospheric vertical column densities (VCDs) of NO2, HCHO, O3 and SO2 retrieved from MAX-DOAS network can be used to study temporal and spatial evolution of atmospheric pollution, and its transport and regional characteristics. Besides, MAX-DOAS network measurements can also be used to validate results from WRF-Chem model and products derived from spaced-based instrument, such as OMI and OMPS. We apply the MAX-DOAS profiles to the satellite retrievals and find that the accuracy of these modified satellite products has been improved. These modified satellite products can be performed every day with high spatial resolution and can be used to monitor air pollutants in real time and analysis chemical processes. The combination of results from ground-based and space-based measurements assists government in establishing appropriate emission control strategies.

The Environmental trace gas Monitoring Instrument (EMI) onboard Chinese high-resolution remote sensing satellite GaoFen-5 is an UV-VIS imaging spectrometer. The primary objective of EMI is to quantitatively measure global distribution of tropospheric and stratospheric trace gas. EMI is a nadir-viewing push broom spectrometer with a moderate resolution of 0.3 to 0.5 nm in the range 240 to 710 nm. The oxygen A-band is the best suited to retrieve cloud information. But the oxygen A-band lies outside the spectral range of EMI. So we retrieve the effective cloud fraction and effective cloud altitude using the O₂-O₂ absorption band at 477nm and 360nm. Similar to OMI cloud algorithm, from the measured radiance and irradiance spectra a reflectance spectrum is made, and a DOAS fit is applied to this reflectance spectrum, yielding the continuum reflectance and O₂-O₂ slant column density. Then these parameters are converted into cloud fraction and cloud height by interpolating in the look-up table. The look-up tables are generated by DOAS fit on spectra simulated using the VLIDORT, in the forward and inverse model, the cloud is replaced by a Lambertian surface with the albedo A_L=0.8. For fixed values of geometry, ground surface albedo, and ground surface altitude, which is obtained from the DOAS fit continuum reflectance as of function of cloud fraction and cloud height, the O₂-O₂ SCD is also a function with these parameters. So look-up tables are created for all relevant geometries, ground surface albedo and altitudes. Simultaneously, we use the O₂-O₂absorption bandaround 360nm to retrieve the cloud fraction and cloud height. The results of the two methods are integrated as the final cloud parameters. The effective cloud fraction and effective cloud height are used for cloud correction in the retrieval of trace gas like NO₂ and O₃.

The stationary satellite of Himawari-8 has high spatial and temporal resolution, so it can be monitored in real time. In the visible(VIS) band ,assuming different surface cover type, solar and the satellite angle and the aerosol type ,using discrete ordinate radiative transfer model (vlidort), combined with the historical data of aerosol profile and singe scattering albedo of ground-based instruments and calipso lidar ,to establish a simulation of the albedo of the top of the atmosphere .In the inversion process, it can assimilate modis high-precision surface reflectivity products, and adopt different inversion method and cloud removal algorithm according to different surface characteristics.Through the spring test in Beijing, the absorption of aerosol has a major influence on the inversion of aerosol optical thickness, and the wind and sand weather in Beijing spring has high scattering characteristics.

China Ozone pollution caused by photochemical reaction becomes a serious problem in China in the recent years. In this study, ozone profiles retrieved from the Ozone Monitoring Instrument (OMI) and the Ozone Mapper and Profiler Suite (OMPS) using the Optimal Estimation method (OEM) over China from 2013 to 2017. We apply soft calibration to OMI and OMPS radiance to eliminate the systematic component of fitting residuals. Tropospheric Ozone Columns (TOCs) is directly derived from the total column using the known tropopause. Hyper-spectral resolution Fourier transform infrared spectrometry (FTS) data at Hefei (31.86˚N, 117.27˚E), ozonesonde data at Hong Kong (22.20˚N, 114.10˚E) and Beijing (39.92˚N, 116.46˚E) are used to validate the tropospheric ozone column (TOC). The monthly variation of tropospheric ozone column (TOC) from 2013 to 2017 are also evaluated. In addition, we characterize the ozone and aerosol concentrations in the troposphere and surface UV irradiance to quantify the effects of aerosol particles and surface UV irradiance on the variability of tropospheric ozone.

We retrieve sulfur dioxide (SO2) vertical columns from the Ozone Monitoring instrument (OMI) and Ozone Mapping and Profiler Suomi National Polar-orbiting Partnership spacecraft (OMPS) using optimal estimation method (OEM) over China from 2013 to 2017. Comparison between OEM retrievals and the principal component analysis (PCA) product shows that a general good agreement between using the different algorithms is obtained with a correlation coefficient of 0.7249 and a slope of 0.8789 over eastern China. Validations with ground-based Multi Axis Differential Optical Absorption Spectroscope (MAX-DOAS) measurements show that a monthly averaged ground-based SO2 results and coincident OMI SO2 results using OEM agree very well. The seasonal cycle of SO2 is consistent in both data sets with a maximum in winter, on average, 6×10e16 molecules*cm−2 in Xianghe (a key pollution area), and a minimum in summer, which has a mean value of 2×10e16 molecules*cm−2 there. Winter is the domestic heating season. Both show that SO2 originates mainly form human sources rather than natural ones. The spatio-temporal distribution over China shows that the pollution is mainly concentrated in Beijing-Tianjin-Hebei area and Sichuan Basin. And the yearly averaged SO2 results show that the SO2 vertical columns are decreasing from 2013, 4.57×10e16 molecules*cm−2, to 2017, 0.89×10e16 molecules*cm−2 in those key pollution areas. SO2 and NO2 are major aerosol precursors, and SO2 and NO2 respectively are sources of pollution mainly from coal- fired power plants and motor vehicle emissions. We also investigate the relationship between SO2 emission and aerosol production in Beijing. A stronger correlation between the SO2 concentrations and aerosol optical depths (AODs) measured by the MODIS satellite instrument than NO2 concentrations with AODs obtained in winter suggests that anthropogenic SO2 is the major contributor to the aerosol content during the period of the year.

The TROPOspheric Monitoring Instrument (TROPOMI) is a passive nadir-viewing satellite borne imaging spectrometer on board the Sentinel-5 Precursor (S5P) satellite which was launched on 13^th October 2017. Compared to previous satellite instruments such as SCIAMACHY, GOME-2 and OMI, TROPOMI provides much higher spatial resolution with a ground pixel size of ~25km² (3.5km × 7km) at nadir. TROPOMI provides global observation of cloud, aerosol and multiple atmospheric trace gases and greenhouse gases. The operational NO₂, HCHO and O₃ products of TROPOMI are compared to ground based MAX-DOAS and FTS observations in China. In addition, the influence of aerosol and trace gases vertical distribution profiles on TROPOMI retrieval are estimated by using MAX-DOAS derived aerosol and trace gases profiles in the satellite retrieval. The Environmental Monitor Instrument (EMI) is one of the hyper-spectral payloads on board on the Chinese Gao Fen 5 (GF-5) satellite. The satellite is expected to be launch in May 2018. EMI provides global observations of atmospheric trace gases with a moderate resolution of ~624km² (48km × 13km). Combing with the higher spatial resolution TROPOMI data, we could estimate the spatial averaging effect over pollution hotspot of the EMI observations.

This paper presents formaldehyde (HCHO) column observed by Ozone Mapping and Profiler Suite (OMPS) and the TROPOspheric Monitoring (TROPOMI) instrument. OMPS-NM on board the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite was launched successfully on 28 October 2011, and TROPOMI on board the Copernicus Sentinel-5 Precursor satellite was launched successfully on 13 October 2017. Both of them cross the equator each afternoon at about 13:30 local time (LT), thus provides a great opportunity to compare HCHO column observed by OMPS and TROPOMI instruments. Besides, tropospheric HCHO columns observed by OMPS was compared with that measured by the high resolution Fourier transform infrared spectrometry (FTS) which is located in the western suburbs of Hefei (117.17E, 31.9N) in this paper, and they show the similar trend with the correlation coefficient (R) of 0.78. Tropospheric HCHO column observed by OMPS and TROPOMI both keeps good agreement with that measured by MAX-DOAS with the correlation coefficient (R) of 0.76.

Chinese carbon dioxide observation satellite (TanSat) launched in 22 Dec 2016, after on-broad test and calibration, the TanSat starts to record the back-scattered sunlight spectrum from scientific earth observation and produced first XCO₂ data from February to July in 2017.

The optimal estimation theory was involved in TanSat XCO₂ retrieval algorithm in a full physics way with simulation of the radiance transfer in atmosphere. Gas absorption, aerosol and cirrus scattering and surface reflectance associate with wavelength dispersion have been considered in inversion for better correction the interference errors to XCO₂. In this presentation, I will show the preliminary results of XCO₂ retrieved from TanSat measurements, and inter-compared with OCO-2 results in an overlap footprint measurement over north Australia. Validation study with TCCON measurements indicate a better than 4 ppm with 8 stations. The first global XCO₂ map has represented a milestone in Chinese GHGs satellite. TanSat will release level 2 and higher level products to support carbon emission estimations and climate change studies.

Satellites have the power to provide new insights into the regional sources and sinks of the major greenhouse gases (GHG) CO₂ and CH₄ thanks to their high data density and coverage. Satellite observations play an important role in diagnosing regions where carbon is taken up and released and how these fluxes respond to climate extremes such as droughts. Recently, the focus has further expanded with the aim of separating natural from anthropogenic emission sources.

Since the launch of the first dedicated GHG sensor GOSAT almost a decade ago, a series of new sensors have been launched (NASA OCO-2, TanSat, S5P…) with further sensors expected to be launched in the coming years (GOSAT-2, MicroCarb, OCO-3…). As a consequence, we are now presented with the opportunity of an emerging ad-hoc constellation of GHG satellites providing us with an opportunity to intercompare and eventually combine observations from multiple satellites to increase data coverage and density. However, one concern is potential biases between the datasets and careful validation against ground-based datasets is essential.

China is a key region for the global carbon and methane cycle with significant emission sources. However, the frequent occurrence of high aerosol loads over China combined with insufficient ground-based validation opportunities leaves satellite observations uncertain. In this presentation, we will focus on an evaluation of satellite observations of CO2 and CH4 over China. We will intercompare GOSAT, OCO2 and TanSat datasets and assess them against model calculations that are constrained with surface in-situ data. Finally, we will discuss the use of space-based data to identify and highlight main emission areas of GHGs.

We discuss the recent recearch activities that have taken place at the Finnish Meteorological Institute related to satellite observations of greenhouse gases with links to the DRAGON project “Monitoring greenhouse gases from space: Cal/Val and applications with focus in China and high latitudes“.

The FTIR instrument in Finnish Meteorological Institute’s premise in Sodankylä is one of the sites participating in the Total Carbon Column Observing Network (TCCON). The retrievals include column-averaged, dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4). Since 2013, series of AirCore balloon launches have been performed to obtain accurate in-situ profiles of methane, carbon dioxide and carbon monoxide from troposphere to lower stratosphere. As a high latitude site, Sodankylä contributes to the validation of satellite observations of greenhouse gases in boreal and arctic regions. The recent and on-going validation activities and campaigns that have taken place in Sodankylä are also discussed.

In addition, we have studied the spatiotemporal distribution of greenhouse gases by analysing spatially and temporally OCO-2 and GOSAT data. The developed methods and results are applicable also to TanSat data.

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. In our recent work [Hakkarainen et al., 2016] we provided a new approach to study anthropogenic CO₂ emission areas by deseasonalizing and detrending OCO-2 XCO₂ observations for deriving XCO₂ anomalies. The spatial distribution of the XCO₂ anomaly matches the features observed in the maps of the Ozone Monitoring Instrument NO₂ tropospheric columns, used as an indicator of atmospheric pollution, as well as the features observed in the ODIAC emission dataset. In addition, the results of a cluster analysis confirmed the correlation between CO₂ and NO₂ spatial patterns.

In this work, we study this idea further and provide the global XCO₂ anomaly maps for three full years 2015, 2016 and 2017. The patterns observed in these maps are compared with inventory-based estimates given by the Lagrangian particle dispersion model FLEXPART driven by the high-resolution ODIAC emission dataset. We also analyze the changes observed in XCO₂ anomaly maps and compare these changes to the inventory-based estimates, as well as to the changes observed in other trace gases (NO₂ and SO₂).

References

Hakkarainen, J., I. Ialongo, and J. Tamminen (2016), Direct space-based observations of anthropogenic CO2 emission areas from OCO-2, Geophys. Res. Lett., 43, 11,400–11,406, doi:10.1002/2016GL070885.

CO₂ anthropogenic emissions contribute 37 Gt CO₂ to the global carbon budget. The emissions of carbon dioxide arise from different anthropogenic activities with the dominant contribution from burning of fossil fuel especially for power generation and the industry and transport sectors. The quickly growing economy of China has, in recent years, become the largest emitter of CO₂ generating about 30% of all emissions. Cities and urban areas, where the human activities are very intense, are responsible for over 70% of all CO₂ emissions highlighted the need for a better understanding of emissions form these urban areas.

New satellite observations of CO₂, in particular from NASA’s OCO-2 launched in 2014 and the Chinese TanSat launched in 2016 provide the opportunity to monitor CO₂ concentration over polluted areas in the scale of big cities and individual point sources due to the small size of its footprint of ~ 4 km².

The goal of this study is to investigate if and how well we can observe anthropogenic enhancement of total column dry air CO₂ mole fraction (XCO₂) from space over densely populated areas as well as for individual large cities. We will focus on Eastern China as well as selected megacities globally.

We will show an evaluation of current model calculations such as Copernicus Atmosphere Monitoring Service (CAMS) against space-based data and present first result based on a high-resolution modelling approach that allows interpretation of individual soundings/orbits.

In recent years, the continuous rise in the concentrations of greenhouse gases has drawn a great attention of the international community, especially for carbon dioxide (CO₂) and methane (CH₄). The sources and sinks of CO₂ and CH₄ in the atmosphere are distributed unevenly and subjected to a variety of transport. The high-precision observation of CO₂ and CH₄ provides a foundation for the assessment of carbon emissions and a basis for the study of carbon cycle Much effort has been done by the government and research groups to monitor and quantify the magnitude and distribution of greenhouse gases, including both domestic and international.

High-accuracy continuous measurements of CO₂ and CH₄ at Xinglong (40°24'N, 117°30'E, 940 m a.s.l.) located at ~150km northeast of Beijing from May 2016 to December 2017 were made based on cavity ring down spectroscopy (CRDS) analyzer. The calibration data, seasonal and diurnal variations, influence of local wind and regional transport have been discussed. To understand different regional background in China, the seasonal cycles of CO₂ and CH₄ at Xinglong have been compared the results from Mt.Waliguan and Shangdianzi.

The calibration result shows that the accuracies of measurements of the instrument meet the compatibility goals of WMO/GAW. CO₂ concentration is high in winter and low in summer while CH₄ concentration is high in summer as well as in middle autumn and low in spring. The seasonal variation for CO₂ is mainly due to the combination influence of photosynthesis and respiration of plants. The regional transportation is another important factor. The air mass from southwest-south-southeast of the station such as Beijing, Hebei and Jinan may contribute to the relative high concentrations, especially in summer and autumn. The higher CH₄ concentration occurs in summer and middle autumn due to the gradual degradation of anaerobic microorganisms emitting large quantities of CH₄ in local area and fossil combustion emissions from Beijing-Tianjin-Hebei in summer and autumn. What’s more, Mongolia is another potential source area for both CO₂ and CH₄ in autumn and winter.

The diurnal patterns of CO₂ and CH₄ both show relatively low value in the noon. For CO₂ it is because the strong sunshine in the noon which is conductive to the stronger mixing of near-surface air with lower CO₂ concentrations aloft. While for CH₄ it is the increasing OH radicals in the atmosphere after sunrise that leads to the decrease of CH₄.The stable boundary in the afternoon and at night helps the accumulations of CO₂ and CH₄ in the afternoon.

The seasonal variations of CO₂ comparisons between Xinglong, Shangdianzi and Mt.Waliguan show that the patterns are the similar in the 3 sites for CO₂,high in summer and low in other seasons. The pattern for CH₄ at Xinglong is high in summer, middle autumn and winter while low in spring. However, the variation of atmospheric CH₄ in Mt.Waliguan and Shangdianzi is only high in summer and smaller than other 2 stations.

The Third Pole Environment 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: The warm season characteristics of turbulence structure and transfer of turbulent kinetic energy over alpine wetlands and alpine meadow are analyzed. We found that the turbulence intensities decrease rapidly with increasing wind velocity under conditions of wind velocity smaller than 2 m s^-1 and the pulse of CO₂ flux is very small at noon time because of the high temperatures. We also identified that variations in soil moisture had important effects on carbon exchange in the alpine steppe ecosystem. Both the photosynthesis and respiration were active under high soil moisture content, and suppressed during periods of water shortage. Further, precise measurements of evaporation and understanding of the physical controls on turbulent heat flux at different time scales over a high-elevation small lake are also performed. A total evaporation value of 812 mm is reported for the small lake and the energy budget is generally closed during the open water period. Also we analyzed the variability and trends of daily precipitation extremes over the northern and southern side of central Himalaya. The results suggest that increases in precipitation have been accompanied by an increasing frequency of extremes over the southern central Himalaya while no relation could be established between the precipitation extreme indices and circulation indices for higher altitudes. (2) Remote sensing: an accurate estimate of monthly mean LST based on averaging of the multidaily overpasses of MODIS sensors was established, with RMSE value of 2.65℃ and mean bias of smaller than 1 ℃. Combining 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 (C_t). In addition, a parameterization approach of effective roughness length was introduced into the SEBS model to account for subgrid-scale topographical influences. The results show that sensible heat flux decreased overall while latent heat flux increased over the majority TP over 2001 to 2012. (3) Model simulation: 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. A new land surface model (LSM) with coupled snow and frozen soil physics was developed based on a hydrologically improved LSM (HydroSiB2) and the results show significant improvements in snow internal process and soil water phase changes. 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.

The Third Pole Environment plays a significant role in global atmospheric circulation and is highly sensitive to climate change and its impact on Asia’s largest rivers which provide water to 1.5 billion people across ten countries. A fundamental understanding of intensive exchanges of water and energy fluxes between the Asian monsoon, the plateau land surface and the plateau atmosphere at various temporal and spatial scales especially at the climate scale is crucial to understand the role of TPE on global climate and the impact of climate change on TPE.

The CLIMATE-TPE project aims to improve understanding 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 to address three specific objectives. 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. 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 ensure 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.

Since 2006 the Tibetan plateau observatory for soil moisture and soil temperature (Tibet-Obs, Su et al., 2011, HESS) has been in operation and has provided valuable dataset for land-atmosphere process studies. The networks and collected data have been used for calibration and validation of satellite soil moisture retrieval algorithms and data products as well as for improving numerical model parameterizations (Su et al., 2013, JGR; Zheng et al., 2015a, b, JHM; 2017a, JHM, b, JGR) and for understanding passive and active microwave signals (Dente et al., 2015, RSE; Wang et al., 2016, JAG; Lv et al., 2014, RSE). Most recently an in-situ microwave radiometer (ELBARA III from ESA) has been operating at the Maqu site of the Tibet-Obs, as such coherent process observation, process modeling and radiative transfer modeling can be conducted to examine land-atmosphere interactions. We report here recent results of these experiments in combined radiative transfer and heat-water transfer processes (Zheng et al., 2017, TGRS) and in understanding SMOS/SMAP observation signals and data products (Lv et al., 2018, RS).

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 (ITP) land-atmosphere interactions, boundary layer processes
5. Dr. Donghai Zheng (ITP) water cycle in the upper Yellow River basin, hydrological modelling
6. Shaoning Lv (PhD student, UT-NIEER) Microwave emission and soil moisture, SMOS/SMAP signals
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. Lian Liu (PhD student, ITP) Retrieval of thermal and hydraulic parameters from satellite observations on the glaciers
14. Dr. Cristina Aguilar, University of Cordoba, e-mail: caguilar@uco.es, ecohydrological modelling
15. Dr. Rafael Pimentel(postdoc, UC)remotely sensed data fusion and assimilation for snow and hydrological modelling
16. Gabriel Delgado Leal(PhD student, UC) Water and energy fluxes regime in snow mountain regions
17. Marta Sáenz de Rodrigáñez (PhD student, UC) Remote sensing data fusion to generate long and high resolution time series of snow and hydrological variables
18. Dr. Jian Peng (LMU/OU) Thermal and microwave remote sensing of surface energy and water fluxes
19. Dr. Christiaan van der Tol, University of Twente, email: c.vandertol@utwente.nl, remote sensing of fluorescence
20. Jan Hofste (PhD student, UT),University of Twente, email: j.g.hofste@utwente.nl, remote sensing of land surface by scatterometry and spectroscopy

A global daily evapotranspiration product without spatial-temporal gaps for 2000-2017 is delivered by using an energy balance (EB) algorithms and MODIS satellite data. A global turbulent exchange parameterization scheme was developed and used in an energy balance model, which uses land-air temperature gradient to estimate the turbulent sensible heat (H), and take the latent heat flux as a residual of the available energy (net radiation minus ground heat flux) and sensible heat. It provides us with the first ever moderate resolution estimates of ET without spatial-temporal gaps on a global scale. The performance of evapotranspiration (ET) data has been evaluated in comparison to 230 flux sites measurements representative of a broad range of biomes and climates at the global scale. The gap-filling algorithm reproduces observed ET with reasonable accuracy. The daily ET product has a mean bias of 0.04 mm/day, with the RMSE value of 1.56 (±0.25) mm/day.

Surface soil moisture (SSM) plays a significant role in various domains of science, including agriculture, hydrology, meteorology and ecology. However, the spatial resolution of microwave SSM products is too coarse for regional applications. This study estimates SSM directly from data of the Chinese geostationary meteorological satellite FY-2E, without establishing empirical relationships between SSM measurements and satellite derived proxies of SSM. The derived SSM has a spatial resolution of 5 km and is based on an elliptical-new SSM retrieval model developed from the synergistic use of the diurnal cycles of Land Surface Temperature (LST) and Net Surface Shortwave Radiation (NSSR). Validation of the model is conducted based on ground measurements over the source area of the Yellow River (SAYR) on the northeastern Tibet Plateau. The FY-2E-derived SSM using the elliptical-new model exhibited good consistency with the ground measurements, with R of 0.845, RMSE of 0.064 m³/m³ and bias of 0.017 m³/m³. In addition, since the spatial resolution of microwave SSM products is too coarse, various downscaling methods are proposed to improve the spatial information. In this study, the CCI SSM product is downscaled to 5 km through a simple vegetation-temperature-condition-index (VTCI) method, which is simpler in terms of input requirements and implementation and has similar accuracy compared to other downscaling methods. The comparison of the VTCI downscaling model against in-situ measurement in Maqu, Luqu and Ruoergai also shows good agreement with R of 0.73, RMSE of 0.08 m³/m³ and bias of 0.04 m³/m³. Furthermore, the spatial patterns of elliptical-new SSM retrieval and VTCI downscaled SSM are also compared. The results show that FY-2E-derived SSM is similar to the downscaled SSM, with SSM over the Eastern region higher where has lakes than SSMs in the west. Lowest SSMs from both methods appear in the northernmost region. In order to provide more accurate SSM for these two methods, high accuracy vegetation indexes, LST and NSSR are still needed.

There are tens of thousands of lakes on the Tibetan Plateau and lakes show significant influences on catchment scale water and heat budget and influence local climate modeling. However, the observation and simulation of the high-elevation lakes are still quite limited. Thus, based on eddy covariance observations and meteorological data over open water periods from a small lake in 2012-2013 on the Tibetan Plateau, we achieved the goals of understanding the characteristics and driving forces of lake-air interaction process, obtaining the evaporation and energy budget, and testing evaporation estimation methods at temporal scale of 10 days over high altitude small lakes. The optimized parameters of roughness length for momentum are suitable for lake-atmosphere heat flux simulation by bulk aerodynamic transfer method. Wind speed shows high correlations at temporal scale of 30 minutes while temperature gradient and water vapor gradient has much higher correlations at temporal scales of daily and monthly. Under neutral conditions, the water vapor gradients have no influence on latent heat flux. The accumulated heat during April to August is fast released during September to November. The average evaporation over the entire open water period is 812 mm and the energy budget is generally closed with a closure ratio of 0.97. The constructed data series provide a good data set for evaporation methods evaluation. The energy budget based method show much better performances than methods of radiation based and Dalton type.

To promote the radiometric quality of satellite remote sensing products and assure the comparability of product quality amongst multi-series satellites, we should build a continuous transfer chain from remote sensor to the radiometric reference standard, estimate those parameters characterizing sensor’s performance, and conduct quality controls on remote sensing data and products during sensor lifetime. However, when the sensor is on-orbit, its radiometric quality is usually hard to be traced to SI because of breakage of the reference transfer chain. The traditional field vicarious radiometric calibration method which uses ground target measurement value as radiometric reference, can be influenced by various uncertainties due to scaling effect, atmospheric condition, environment change, etc., so it is hard to reach high calibration accuracy. In pursuit of on-orbit optical sensor high-accuracy calibration and product quality consistence, we carried out the following exploratory work:
1) Research on the ground-based radiometric reference transfer chain in sensor calibration under the framework of RadCalNet (the Radiometric Calibration Network, initiated by CEOS/WGCV). The RadCalNet initiative was sponsored cooperatively by NASA, ESA, CNES and AOE, with object to verify EO sensor’s radiometric calibration accuracy and ensure radiometric measurement consistency from different EO sensors. Through the activities of establishment of calibration sites, increasing observation frequencies, decreasing of total calibration errors, RadCalNet ensures the traceability of radiometric measurement benchmark for space remotely sensors. And moreover, it can provide the opportunities to carry out on-obit calibration for those space agencies who do not have the conditions for organizing the in-situ calibration activities. Under the framework of RadCalNet, AOE designed and manufactured automated surface spectrum measurement system. Now, this system has been deployed on different permanent targets in Baotou site. It can automatically measure the surface reflected radiance and atmospheric parameters continuously. Then, following the requirement of data products defined by RadCalNet data center, Level 1 BOA (bottom of atmosphere) reflectance standard products and level 2 TOA (top of atmosphere) sensor-independent reflectance products are generated automatically. Besides, AOE and NPL carried out cooperation research on uncertainty analysis of the whole chain of radiometric calibration benchmark product generation for Baotou site. In this study, the contributions to the total uncertainty for different factors, including obtaining of surface reflectance, homogeneity and BRDF of surface target, measurement of atmospheric parameters, atmospheric radiative transfer calculation, solar irradiance spectra model, and etc., have been elaborately analyzed to calculate the uncertainty of radiometric calibration in Baotou site.
2) Research on space radiometric benchmark transfer calibration. Introducing radiometric benchmark sources, which can be traced to SI, in some specific benchmark satellite, via synchronously observation of surface scenes between benchmark satellite and other satellite, is a feasible way to transfer the space radiometric measurement benchmark from spaceborne standard radiometric calibration system to operational optical remote sensing satellite with high accuracy. Under this framework, we can provide high accurate and consistent space radiometric measurement benchmark for those optical satellite, to significantly promote calibration accuracy and ensure the consistency and stability of data quality amongst multi-series satellites. Based on this idea, we design a space radiometric benchmark transfer calibration plan with accurate spatial-temporal-spectral-angular matching and coupling transform as core techniques. In this plan, we comprehensively use the ground surface scene model, atmospheric radiative transfer model and optical sensor model, build the satellite-satellite radiometric measurement mapping relationship, carry out the spatial-temporal variety and anisotropy characteristic analysis for surface stable targets, establish the constraint mechanism in spatial-temporal-spectral-angular matching, construct the satellite-satellite radiometric measurement transform model though simulation and observation data, to finally realize space radiometric benchmark transfer calibration.
The above two researches have been validated and the superiority of each method have been analyzed with Chinese and European satellite, such as Sentinel-2a/2b、GF-1/2、ZY301/02, with ground-based and aerial-based campaign. This work points out the direction of the next step.

Long-term aerosol data records provide information on changes in the aerosol properties due to both natural (meteorological, climatological, dust storm, fires) and anthropogenic effects (such as industrialization, urbanization and policy measures aimed at improvement of air quality). An often-used indicator for the aerosol burden is the aerosol optical depth (AOD), i.e. the column-integrated extinction coefficient. AOD can be monitored from satellites using radiometers, but instruments used for this purpose have a limited lifetime and often are not designed for aerosol monitoring. As part of the Aerosol-cci project, the Along Track Scanning Radiometer (ATSR-2) flying on the European Space Agency (ESA) ERS-2 satellite from 1995 to 2003 and the advanced ATSR (AATSR) flying on ESA’s ENVISAT (2002-2012) were used together to create a 17-years (1995-2012) global AOD data record over land and ocean (Popp et al., 2016). This data set is planned to be extended with AOD retrieved from the Sea and Land Surface Temperature Radiometer (SLSTR), an instrument similar to ATSR but with a backward instead of forward view, the first of which flies on Sentinel-3A launched in early 2016. However, this leaves a gap of about 4 years between the end of the AATSR and the start of the SLSTR data records. To fill this gap, we investigated the use of AOD data available from the application of the ALAD algorithm developed by RADI for AOD retrieval over land using data from the Advanced Very High Resolution Radiometer (AVHRR) (Xue et al., 2017). ALAD combines eight different AVHRR instruments to produce an AOD time series starting in 1983 (Xue et al., 2017). Hence, the ALAD AOD data set could also be used to extent the information from the ATSR data record backward from 1995 to 1983, provided that a satisfactory match can be obtained between the overlapping ATRS and AVHRR data sets.

In this study we used ATSR AOD data produced with FMI’s Aerosol Dual View (ADV) algorithm (Kolmonen et al., 2016; Sogacheva et al., 2017) and ALAD data sets retrieved for the whole period from 1983 to 2014 over the North China Plain (NCP). In addition, MODIS-Terra AOD C6.1 data are used for comparison and ground-based sun photometer AOD data from AERONET (Holben et al., 1998) are used as reference. The validation versus AERONET shows the good performance of the AVHRR AOD up to about 0.5 and for ATSR up to about 1.3, which leads to large differences during high AOD episodes such as often observed over the NCP in the summer. However, during the winter, when AOD is often moderate, AVHRR provides better coverage. Part of the difference between AVHRR and ATSR AOD may be explained by the difference in wavelength between the ATSR- and AVHRR-retrieved AOD (550 nm and 630 nm, respectively).

References

Kolmonen, P., Sogacheva, L., Virtanen, T.H., de Leeuw, G. , and Kulmala, M.: The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD data set, International Journal of Digital Earth, 9:6, 545-561, doi: 10.1080/17538947.2015.1111450, 2016.

Popp, T., de Leeuw, G., Bingen, C., Brühl, C., Capelle, V., Chedin, A., Clarisse, L., Dubovik, O., Grainger, R., Griesfeller, J., Heckel, A., Kinne, S., Klüser, L., Kosmale, M., Kolmonen, P., Lelli, L., Litvinov, P., Mei, L., North, P., Pinnock, S., Povey, A., Robert, C., Schulz, M., Sogacheva, L., Stebel, K., Stein Zweers, D., Thomas, G., Tilstra, L.G., Vandenbussche, S., Veefkind, P., Vountas, M., and Xue, Y.: Development, production and evaluation of aerosol Climate Data Records from European satellite observations (Aerosol_cci), Remote Sens. 2016, 8, 421; doi:10.3390/rs8050421, 2016.

Sogacheva, L., Kolmonen, P., Virtanen, T. H., Rodriguez, E., Saponaro, G., and de Leeuw, G.: Post-processing to remove residual clouds from aerosol optical depth retrieved using the Advanced Along Track Scanning Radiometer, Atmos. Meas. Tech., 10, 491-505, doi:10.5194/amt-10-491-2017, 2017.

Xue, Y., He, X., de Leeuw, G., Mei, L., Che, Y., Rippin, W., Guang, J., Hu, Y. : Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe. Remote Sensing of Environment, 198: 471-489, 2017.

Different from the work last year, the paper develops a all-weather and all-day 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，and some preliminary results can be shown in the conference materials.

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 validating 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 used for validation of GOSAT products. Some new progresses in validating satellite products over northern China using ground-based FTIR and MAX-DOAS instruments will be reported here.

Atmospheric aerosol optical remote sensing makes use of ultraviolet, visible and infrared sensors to collect information of the particles in atmosphere by detecting radiation scattered from targets. Black carbon (BC) is the most important light-absorbing aerosol in the current atmosphere because of its strong positive climate forcing from direct radiative and snow albedo effects. Both effects are significantly affected by BC optical properties. Observations have shown that BC particles have complex structures due to stochastic aggregating. Thus, a reliable remote sensing of BC aerosols and estimate of BC climatic effects requires accurate computations of optical properties for BC particles with complex structures. Currently most simulation methods employ single-sized spherical particle as primary spherule to construct the whole aggregates, this may introduce some extra uncertainty. In this study we use DDA method to compute optical properties of aggregates constructed by nonspherical and spherical particle with same structural parameters. Preliminary results are presented and show great differences exist between them, the results could be used for evaluating uncertainty introduced by particle modelling and calibrating results of remote sensing.

The Baotou site is one of four instrumented sites being established as part of the Radiometric Calibration Network (RadCalNet). RadCalNet is an initiative of the CEOS WGCV. It has been designed to provide satellite operators with SI (Système International d'Unités)-traceable top-of-atmosphere (TOA) spectrally-resolved reflectances from a coordinated network of instrumented land-based test sites. An automated radiometric calibration system was established on the Baotou Cal&Val test site in China to provide an operational high-accuracy and high-stability vicarious calibration and validation site for high resolution remote sensing instruments.
The composition of the system is first described in this paper, which provides bottom-of-atmosphere (BOA) reflectance in 30 minutes intervals in 10 nm steps over the spectral range from 400 nm to 1000 nm. The sources of uncertainty from the laboratory calibration of the spectrometer, through to field observations of radiance and the calculation of ground reflectance, through to the propagation to TOA reflectance were analyzed in this paper. An initial uncertainty analysis of the automated radiometric calibration was made by considering three aspects: uncertainty associated with the spectrometer (ground viewing instrument) measurements; uncertainty associated with the BOA reflectance calculation; and the uncertainty associated with averaging this to the requirements of the Radiometric Calibration Network, RadCalNet. Preliminary analysis shows that the combined uncertainty associated with RadCalNet BOA reflectance would be approximatively 3.0 % within the spectral range 500 nm ~ 900 nm. The uncertainty associated with the TOA reflectance propagated from BOA reflectance measured by single observation is approximatively estimated as 3.5% ~ 5.0%, ignoring the influence of the surrounding pixels.

Here we applied our tropospheric nitrogen dioxide (NO2) retrieval algorithm, which was implemented for the Chinese Environmental trace gases Monitoring Instrument (EMI), to the TROPOspheric Monitoring Instrument (TROPOMI). Generally, the Differential Optical Absorption Spectroscopy (DOAS) technique was used to retrieve slant column densities (SCDs) of NO2, and air mass factor (AMF) are calculated for light path correction. The solar and viewing geometries, surface albedo and pressure, cloud properties, and modelled gas profile was used as input parameters for online AMF calculations. The tropospheric NO2 was estimated from the total column by using the modified reference sector method. Results show good agreements with independent ground-based MAX-DOAS measurements.

Atmospheric particles have a remarkable impact on the global environment and climate change. The mineral dust, marine, polluted marine, absorbing, and other types of aerosols are important parts of the global biogeochemical cycles. The land-sea-wind circulation, different heights of boundary layers over sea and continents, the thermal and mechanical turbulence and the pollution emissions in the coastal zones have pronounced impact on the optical properties of the aerosols. In view of these, vertical resolved measurements of optical aerosol properties with calibrated and QA/QC checked lidar systems are necessary. Hence, evaluation and calibration of the data quality of observation equipment are needed urgently. The proposed project tasks are to intercalibrate the lidars from both partners by using EARLINET QA/QC procedures side by side. For this, the lidars from China are scheduled to be transported to Europe. The intercalibration and intercomparison will be conducted at TROPOS in Leipzig/Germany (http://www.tropos.de/) since often particle layers of dust, polluted marine aerosol and other types of aerosol had been observed at TROPOS, the technical infrastructure at TROPOS together with the running systems there is well established. Afterwards, the lidars will be theoretically and experimentally analyzed (including the determination of Müller Matrixes) to determine the contributions of the optical parts to the total system parameters and their uncertainties. With this system calibration and validation results, the optical particle parameters like the extinction coefficient, the backscatter coefficient, the lidar ratio, the aerosol optical thickness, the depolarization ratio, and the Ångström exponent will be measured at TROPOS during a following intensive measurement campaign of about 3 months. The mentioned intensive particle parameters will be used for aerosol type characterization from the observed data.

After this crosscheck, also the intercomparison of the measurement results from the ground-based lidars and from spaceborne lidars (carried by EARTHCARE, ADM-Aeolus, CALIPSO) will be conducted. Furthermore, the wind profiles, the turbulence, and the dynamic structure inside the atmospheric boundary layer will also be observed, which will support the research on the vertical mixing and lateral transport (including sea-land-wind) of aerosols. Through vertical wind speed detection, aerosol flux will be calculated, and thus the strength and deposition of aerosols can be estimated. After the transportation of the lidar systems to Changdao Island / China, a second joint intensive joint measurement campaign will be carried out in this project. This task will enhance the cognition of aerosols like polluted marine, polluted dust, dust, and other aerosol types. It is expected that the aerosols consist mainly of mixtures of mineral dust, pollution, and marine within the planetary boundary layer and in the lofted layers (above) at Changdao Island.

After its launch in autumn 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) on-board ESA’s Earth Explorer satellite Aeolus will allow for global observation of atmospheric wind profiles. Being the first ever satellite-borne Doppler wind lidar instrument, ALADIN will significantly contribute to the improvement in numerical weather prediction by providing one component of the wind vector along the instrument’s line-of-sight (LOS) from ground throughout the troposphere up to the lower stratosphere. The vertical resolution is 0.25 km to 2 km depending on altitude, while the precision in wind speed is envisaged to be between 1 m·s^-1 to 3 m·s^-1.

Over the past years, an airborne prototype of the Aeolus payload, the ALADIN Airborne Demonstrator (A2D), has been developed at DLR (German Aerospace Center) and deployed in several field experiments, aiming at pre-launch validation of the satellite instrument and at performing wind lidar observations under various atmospheric conditions. The A2D features a high degree of commonality with ALADIN in terms of laser source and Doppler lidar receiver design. Thus, it represents the key instrument for the planned calibration and validation activities during the Aeolus mission, as it allows validating the instrument concept, operating procedures as well as wind retrieval algorithms.

In autumn 2016, the A2D was engaged in the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). Based in Keflavík, Iceland, this international field campaign had the overarching goal to investigate the influence of diabatic processes, related to clouds and radiation, on the evolution of the North Atlantic jet stream. Apart from providing accurate wind observations for quantifying effects of disturbances on the downstream propagation of the jet, the research flights performed during NAWDEX considerably extended the wind dataset obtained with the A2D as well as with the 2-µm coherent wind lidar on-board the same aircraft – the DLR-Falcon F20. Hence, NAWDEX was an ideal platform for assessing the performance of the two wind lidar systems in heterogeneous atmospheric scenes including strong wind shear and varying cloud conditions.

Besides the DLR-Falcon, three additional aircraft were involved in the campaign being equipped with diverse state-of-the art remote sensing instruments which enabled the observation of a large set of atmospheric parameters, while ground stations delivered a comprehensive suite of further measurements to complement the meteorological analysis. For the first time, coordinated flights were conducted involving the DLR-Falcon, the German HALO deploying an aerosol lidar, a cloud radar and dropsondes as well as the French Falcon SAFIRE with an on-board cloud radar and a UV Doppler lidar instrument. Comparative analysis of the wind data obtained during the collocated flight legs allowed quantifying the accuracy and the precision of the various instruments and demonstrated the complementarity of the different technologies for measuring wind speeds. This work will provide an overview of the NAWDEX campaign and present the results from the wind data analysis both from a meteorological and an instrument point-of-view.

The spaceborne Aerosol and Carbon dioxide Detection Lidar (ACDL) will measure the global column concentrations of carbon dioxide (CO₂) and aerosols profiles simultaneously . The column concentrations of carbon dioxide are measured by 1572 nm double-pulsed integrated path differential absorption (IPDA) lidar technique. The aerosols and clouds profiles are obtained by 532 nm 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 2020. The spaceborne lidar prototype is being developed. An airborne Aerosol and Carbon dioxide Detection Lidar (AACDL) is developed and high altitude flight validation experiments are scheduled to implement in 2018.

For a double-pulsed 1.57-μm integrated path differential absorption (IPDA) lidar, the transmitted laser pulse energy is an important factor which can influence the uncertainty of the CO₂ Column concentrations measurement. Designing an 1.57μm double-pulsed laser energy monitor and to improve the accuracy of the normalized energy ratio of the transmitter pulse energies to returned echo pulse energies are presented. In the experiments, each pulse is divided into two parts .One is received by the detector directly and the other is delayed by the 200 m multimode fiber. Ground glass diffusers in front of the integrating sphere are used to reduce speckles generated by integrating sphere. Ground glass diffusers with different grits and the rotational speeds are compared. The results show that the rotated ground glass diffuser with 120 grits has the minimum standard deviation of the normalized energy ratio after a moving average. Compared to the situations without the ground glass diffuser or with static ground glass diffuser, the slopes of the Allan deviations of normalized energy ratio with rotated ground glass diffusers are more close to -0.5 in logarithmic coordinates.

In preparation of ESA’s upcoming Earth Explorer mission Aeolus which strives for the global observation of wind profiles from the ground to the lower stratosphere deploying the first-ever satellite-borne wind lidar system ALADIN, the ALADIN airborne demonstrator (A2D) has been developed at DLR (German Aerospace Center). Due to its representative design and operating principle, the A2D provides valuable information on the wind measurement strategies of the satellite instrument as well as on the optimization of the wind retrieval and related quality-control algorithms. Hence, it represents an essential testbed for the planned calibration and validation activities after the launch of Aeolus which is scheduled for end of August 2018.

The A2D was successfully employed for wind observations in the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) conducted in Iceland in autumn 2016. Within the scope of the campaign, which aimed to study the influence of diabatic processes on the evolution of the North Atlantic jet stream, 14 research flights were performed extending the wind and calibration dataset of the A2D. In particular, the recording of very high wind speeds above 80 m·s^-1 and strong wind shear of 10 m·s^-1·km^-1 was obtained by sampling an intensified jet stream close to Scotland on 27 September 2016. Broad vertical and horizontal coverage across the troposphere was achieved thanks to the complementary design of the A2D receiver comprising a Rayleigh and Mie channel for analysing both molecular and particulate backscatter signals. Validation of the instrument performance and retrieval algorithms was conducted by comparison with DLR’s coherent wind lidar which was operated in parallel on-board the same aircraft. The systematic error of the A2D line-of-sight (LOS) wind speeds was determined to be less than 0.5 m·s^-1 for both receiver channels, while the random errors range from 1.5 m·s^-1 (Mie) to 2.7 m·s^-1 (Rayleigh). This work will present the operation principle of the A2D and demonstrate selected wind results obtained during NAWDEX.

Ground-based measurements were carried out during field campaigns in April–June of 2010, 2011 and 2012 over northwestern China at Minqin, the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) and Dunhuang, respectively. In this study, three dust cases were examined, and the statistical results of dust occurrence, along with physical and optical properties were analyzed. The results show that both lofted dust layers and near-surface dust layers were characterized by extinction coefficients of 0.25–1.05 km⁻¹ and high particle depolarization ratios (PDRs) of 0.25–0.40 at 527 nm wavelength. During the three campaigns, the frequencies of dust occurrence retrieved from the lidar observations were all higher than 88%, and the highest frequency was in April. The vertical distributions revealed that the maximum height of dust layers typically reached 7.8–9 km or higher. The high intensity of dust layers mostly occurred within the planetary boundary layer (PBL). The monthly averaged PDRs decreased from April to June, which implies a dust load reduction. Comparing the relationship between the aerosol optical depth at 500 nm (AOD₅₀₀) and the Angstrom exponent at 440–870 nm (AE_440–870) confirms that there is a more complex mixture of dust aerosols with other types of aerosols when the effects of human activities become significant.