Conference Agenda

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 advance 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 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 uncertainties in current 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; and WP2: Advancement of physical understanding and quantification of changes of water and energy budgets in the TPE.

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 (Zheng et al., 2017, TGRS) to examine land-atmosphere interactions. We report here recent results of these experiments in combined radiative transfer and heat-water transfer processes and in understanding satellite observation signals and data products – these are related to a new insight of the penetration depth and its quantification for soil moisture products (Lv et al., 2018, RS; Lv et al., 2019, TGRS), benefit of synergistic use of active and passive microwave observations for soil moisture retrieval (Wang et al., 2018, RSE; Wang et al., 2019, JAG) and its use in closing water and energy budgets in TP, as well as inference of subsurface parameters from radiometric observations.

A reflection is made on modeling land-atmosphere radiative and heat-water transfer processes as a key component of Earth System Model (Zhao et al., 2018, ESSD; Yu et al., 2018, JGR).

A specific investigation has also been conducted, as part of the ESM, on the turbulent flux and energy budget over a high-altitude lake on the Tibetan Plateau (Wang et al., 2015, 2017, JGR; Wang et al., 2018, TAC).

As part of capacity building, three PhD (will) have graduated at the University of Twente (Q. Wang, S. Lv and B. Wang) in 2018-2019 and five new students have contributed to different aspects of the project (J. Du, Y. Yu, P. Zhang, M. Li, S. Mwangi).

In the past one year, based on in-situ measurements, reanalysis data, 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 (TP). (1) Based on geostationary and polar orbiting satellite data, the surface energy balance system (SEBS) was used to derive hourly land surface heat fluxes at a spatial resolution of 10 km. Six stations scattered through the TP and equipped for flux tower measurements were used to perform cross-validation. The results showed good agreement between derived fluxes and in situ measurements through 3738 validation samples. The RMSEs for net radiation flux, sensible heat flux, latent heat flux and soil heat flux were 76.63 Wm^-2, 60.29 Wm^-2, 71.03 Wm^-2 and 37.5 Wm^-2, respectively. The derived results were also found to be superior to GLDAS flux products. (2) Based on field albedo measurements, moderate resolution imaging spectrometer (MODIS) albedo products and numerical simulation, we evaluated the ice albedo parameterization schemes in existing lake models and investigate the characteristics of the ice surface albedo in six typical TP lakes, as well as the influence of ice albedo error in the FLake model. Compared with observations, several ice albedo schemes all clearly overestimate the lake ice albedo by 0.26 to 0.66, while the average bias of MODIS albedo products is only 0.07. The MODIS-observed albedo of a snow-covered lake varies with the snow proportion, and the lake surface albedo in a snow-free state is approximately 0.15 during the frozen period. The simulated lake surface temperature is sensitive to variations in lake ice albedo especially in the spring and winter. (3) The climatological characteristics of water vapor and its interannual variability over the TP were investigated by using the ERA-interim monthly mean reanalysis datasets from 1979 to 2014. The analyses show that the TP is a water vapor convergence area, where the convergence was enhanced from 1979 to 2014. The TP is a moisture sink at a climatological mean, with an annual average net water vapor flux of . Detailed features in the water vapor flux and transport changes across the TP’s four boundaries were explored by simulating backward trajectories with a Lagrangian trajectory model (hybrid single-particle Lagrangian integrated trajectory model, HYSPLIT). In the study period, the water vapor contribution rate of midlatitude westerlies to the eastern and southern boundaries increased. However, the South Asian monsoon’s water vapor contribution decreased. (4) Six numerical experiments using the Weather Research and Forecasting (WRF) model were conducted to simulate a snow event over the TP in March 2017. The best performance was achieved when applying the CLM land surface physics. A potentially important factor is the advanced parameterization of albedo in CLM. The WRF model has a certain advantage to identify the snow event, but poor performance on accurate snow depth simulation; Sensitivity of total solid precipitation over the entire event to the land surface physics was larger than to the initial and boundary conditions. (5) Training of young scientists in the area of climate and environment. Six PhD students have been sent to European partner for joint training. Three of them have got PhD degree in University of Twente under the supervision of European PI (Prof. Zhongbo 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.

It is well known that the distribution of cloud and precipitation is affected by atmospheric parameters such as water vapor and updraft motion, as well as by topography. Due to the high altitude of Qinghai-Xizang Plateau (QXP) impacting on cloud and precipitation associated with latent heat release, lots of little known characteristics of them has been revealed continuously based on the measurements of Precipitation Radar (PR) onboard the Tropical Rainfall Measurement Mission (TRMM) satellite. In this study, the characteristics of the vertical structure of precipitation on QXP were studied and compared with the surrounding areas based on the 15 years' measurements of the PR. The results show that, firstly, there is no obvious brightness band in the vertical structure of precipitation over QXP, but it occurs in vertical structure measured by ground based precipitation radar that has the vertical resolution of 33 meters. The thickness of the brightness band is so thin that it is speculated that the PR with vertical resolution of 250 meters is not enough to distinguish the brightness band of precipitation over QXP. Secondly, according to the characteristics of sounding temperature and humidity profile, the precipitation in QXP can be divided into three types: deep strong convection, deep weak convection and shallow convection The Statistical calculations show that the precipitation over QXP is mainly in the form of week deep convection, which occupies 67. 8% followed by the form of shallow precipitation with 26. 4% and the strong deep convection with 5. 8%. Thirdly, the precipitation frequency peaks of deep strong convection and deep weak convection occurred at 16:00 (local time, the same below), and the precipitation intensity peaks for both types at 18:00 and 13:00, respectively. There is second peak at 0:00 for deep strong convection. The peak of precipitation frequency and intensity for shallow precipitation appeared at 20:00, which showed the characteristics of night rain. Finally, the shape of the average profile of deep strong convective precipitation over the QXT is similar to that of deep convective precipitation on the mainland of the Mid-East China, but different from that on the ocean surface.

Key Words: Precipitation, TRMM PR, Vertical Structure, Diurnal Variation

Surface soil moisture (SSM) plays a significant role in the water and energy fluxes at the land-atmosphere interface and its spatiotemporal dynamics is of crucial importance for e.g. water resources and agricultural management. In recent decades, with the development of remote sensing technologies, regional/global soil moisture estimation has been proceeding rapidly. The validation of soil moisture products from remote sensing is normally conducted by in-situ measurements directly or by interpolated soil moisture. However, the problem of mismatching scales between satellite imagery and ground-based observations typically imposes a large range of uncertainty in assessing the accuracy of remote sensing based soil moisture products. Interpolation schemes to upscale soil moisture from point measurements are a suitable alternative option of validating remote sensing soil moisture retrievals. This study aims to evaluate four upscaling methods (Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Universal Kriging (UK) and Spline function (S)) individually on analysing a specific data source over a typical study area (Maqu in the north-eastern Qinghai-Tibet Plateau, HiWATER in the Heihe river basin and REMEDHUS in the semi-arid parts of the Duero Basin of Spain). The strengths and weaknesses of four upscaling methods are explained in detail by cross validation to enumerate all possibilities, thereby maximally reducing the generation of error. In summary, OK and UK show two best upscaling results at similar level, while IDW is inferior to them. S is the least suitable method for soil moisture upscaling, showing weak performance. As expected, a dense soil moisture network with a high number of stations is an important factor for a reliable upscaling of soil moisture. It is found that at least 30 stations (5.5 km × 5.5 km square area) over HiWATER are required to accurately compute geostatistical algorithms (UK, OK or IDW), among which OK performs best in upscaling soil moisture. In cases with less than 30 stations, it’s not recommended to apply geostatistical algorithms to upscale soil moisture, especially for Maqu and REMEDHUS, two research areas which are widely used for soil moisture validation.

With combined remote sensing observations in the microwave- and optical- region of the electromagnetic spectrum we intend to study the dynamics of an alpine meadow floral ecosystem. The microwave observations are made with a broadband (1 – 10 GHz) full polarimetric ground-based scatterometer. From these observations we want to retrieve the soil moisture content, above-ground biomass, and Leaf Area Index. Installed next to the scatterometer is a dual field-of-view (upwelling and downwelling) high resolution (up to 0.1 nm) spectrometer system covering the 400 – 900 nm range. From the spectrometer observations we want to retrieve chlorophyll fluorescence vegetation water content, and pigment factions. Both observations are done over multiple month periods with one measurement every hour.

During the conference we will present a poster on the experimental approach, the technical specifications, and measured observations of the scatterometer. The scatterometer setup was designed to be simple consisting of commercial off-the -shelf components: a Vector Network Analyser and two dual polarization broadband antennas, one for transmit, the other for receive. Also, the experimental approach for the long-term observations entails the two antennas fixed in one position, so that an (automated) rotational stage was not necessary.

Due to the broadband approach the antennas used have broad Gain patterns, especially for the lower frequencies. This property, together with the antenna’s close proximity to the ground (5 m above the surface) requires that for the derivation of the backscattering coefficient (s⁰) the ground surface mapping of G²/R⁴ must be evaluated to deduce the scatterometer’s footprint and associated angle of incidence interval.

To reduce the fading-induced uncertainty of s⁰ we employ frequency averaging techniques. In order to select proper bandwidths over which to average we use predictions of the frequency- and angle dependent behaviour of s⁰ calculated with the Advanced Integral Equation model (I²Em).

We will present an analysis on the spatial variability of s⁰ at our measurement site. Data for this analysis were obtained by measuring the s⁰ over different antenna elevation- and azimuth angles. Additionally, we show the temporal behaviour of the measured s⁰ during some of the key seasonal moments: frozen soil with senescent vegetation, thawing period, spring period (low vegetation) and summer period (maximum vegetation biomass).

L-band passive 1 microwave remote sensing is one of the most effective methods to map the global soil moisture distribution, yet, at which soil depth satellites are measuring is still inconclusive. Recently, with the Lv’s multilayer soil effective temperature scheme, such depth information can be revealed in the framework of the zeroth-order incoherent model when soil temperature varies linearly with soil optical depth. In this paper, we examine the relationships between soil temperature microwave sensing depth, penetration depth, and soil effective temperature, considering the nonlinear case. The soil temperature sensing depth often also named penetration depth is redefined as the depth where soil temperature equals the soil effective temperature. A method is developed to estimate soil temperature sensing depth from one pair of soil temperature and moisture measurement at an arbitrary depth, the soil surface temperature, and the deep soil temperature which is assumed to be constant in time. The method can be used to estimate the soil effective temperature and soil temperature sensing depth.

With combined remote sensing observations in the microwave- and optical- region of the electromagnetic spectrum we intend to study the dynamics of an alpine meadow floral ecosystem. The microwave observations are made with a broadband (1 – 10 GHz) full polarimetric ground-based scatterometer. From these observations we want to retrieve the soil moisture content, above-ground biomass, and Leaf Area Index. Installed next to the scatterometer is a dual field-of-view (upwelling and downwelling) high resolution (up to 0.1 nm) spectrometer system covering the 400 – 900 nm range. From the spectrometer observations we want to retrieve chlorophyll fluorescence vegetation water content, and pigment factions. Both observations are done over multiple month periods with one measurement every hour.

During the conference we will present a poster on the experimental approach, the technical specifications, and measured observations of the scatterometer. The scatterometer setup was designed to be simple consisting of commercial off-the -shelf components: a Vector Network Analyser and two dual polarization broadband antennas, one for transmit, the other for receive. Also, the experimental approach for the long-term observations entails the two antennas fixed in one position, so that an (automated) rotational stage was not necessary.

Due to the broadband approach the antennas used have broad Gain patterns, especially for the lower frequencies. This property, together with the antenna’s close proximity to the ground (5 m above the surface) requires that for the derivation of the backscattering coefficient (s⁰) the ground surface mapping of G²/R⁴ must be evaluated to deduce the scatterometer’s footprint and associated angle of incidence interval.

To reduce the fading-induced uncertainty of s⁰ we employ frequency averaging techniques. In order to select proper bandwidths over which to average we use predictions of the frequency- and angle dependent behaviour of s⁰ calculated with the Advanced Integral Equation model (I²Em).

We will present an analysis on the spatial variability of s⁰ at our measurement site. Data for this analysis were obtained by measuring the s⁰ over different antenna elevation- and azimuth angles. Additionally, we show the temporal behaviour of the measured s⁰ during some of the key seasonal moments: frozen soil with senescent vegetation, thawing period, spring period (low vegetation) and summer period (maximum vegetation biomass).

In this project we study air quality over China using satellite observations, especially their spatial and temporal variability. The latest years of satellite observations of NO2 and SO2 concentrations have been used to infer NOx and SO2 emissions to augment our earlier trend analysis.
In addition, a new SO2 inversion algorithm for use with TROPOMI SO2 observations is under development. Since February 2018 NO2 observations became routinely available from the TROPOMI instrument on S5p. For this a snow-cloud differentiation method has been developed to drastically increase the number of observations over snow surfaces, like Norther China in winter and regions in the Himalaya mountains.
Both the SO2 and NOx 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.

Solar Global Radiation And Its Variation Mechanism At A Subtropical Site In China

Jianhui Bai¹ Gerrit De Leeuw² Larisa Sogacheva² Ronald Van Der A³ Yimei Wu¹ Xiaowei Wan¹

1. LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

2. Finnish Meteorological Institute, Climate Research Unit, Helsinki, Finland

3. Royal Netherlands Meteorological Institute, De Bilt, The Netherlands

Abstract Measurements Of Solar Radiation And Meteorological Parameters Were Carried Out At A Subtropical Pinus Forest Site In China From May, 2013 To December, 2016. An Empirical Model Of Solar Global Radiation Has Been Developed For Different Atmospheric Conditions And The Calculated Solar Global Radiation Is In Agreement With The Observed. This Empirical Model Was Used To Calculate The Attenuation Of Solar Global Irradiance In The Atmosphere Caused By Absorbing And Scattering Substances. Sensitivity Analysis Shows That Solar Global Radiation Is More Sensitive To Changes In Water Vapor Absorption Than To Changes In Scattering Factors, S/Q (S And Q Are Solar Direct And Global Radiation, Respectively). Aerosol Optical Depth (AOD) Is An Important Parameter To Improve The Understanding Of The Scattering Of Solar Radiation. The Relationship Between The Attenuation Factor (AF) And AOD Was Determined And Used To Estimate AOD.

Key Words: Solar Global Radiation, Absorbing And Scattering Factors, Energy, AOD, Climate.

Sentinel 5 Precursor (S5P) satellite was launched into a polar orbit in October 2017, carrying the
TROPOMI instrument. S5P has sun synchronous orbit with an equator crossing time of 13:30 LT.
TROPOMI achieves an almost daily coverage, due to the wide swath width of 2600 km.
The near-real-time (NRTI) ozone total column is based on the two step DOAS approach, consisting of a
slant column retrieval and an iterative AMF-calculation. In this study we present tropospheric ozone
columns based on total column from S5P and stratospheric column based on 4D-Var assimilation of
Aura MLS ozone profiles. To avoid potential errors we use d only cloud free TROPOMI data.
After a brief introduction of the methods the data will be compared to other tropospheric data
satellite data i.e. HCHO and NO2 S5P. The study will focus be on the first year of TROPOMI
observation over East Asia.

Dose-Response Functions (DRFs) are a very important model 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. In current international literature, available DRFs use ground-based air pollution and climatological data to model materials’ deterioration. This limits DRFs use only to areas where the necessary ground based data, is available. In a previous study were presented the results of the attempt to develop a new type of DRFs that modeled the deterioration – degradation of materials, especially carbon steel and limestone, using only satellite data. The term “Satellite Sensed Data-Dose Response Functions (SSD-DRFs)” was proposed for this new kind of DRFs. This study presents the preliminary results of the attempt on the development of SSD-DRFs to assess the deterioration – degradation of zinc and modern glass materials. Modern glass is used to monitor materials surface soiling rather than as structural material. The development of SSD-DRFs provides the opportunity to monitor cultural heritage monuments in areas where ground-based data are not available, extends the use of satellite data by introducing a completely new field of implementation and is largely in line with the European Commission’s effort supporting the Cultural Heritage preservation and management by using Copernicus data and services.

Analysis of PM_2.5 readings taken at the US embassy in Beijing since 2009 reveals that winter haze over North China Plain (NCP) peaked in 2012 and 2013 and there was an improvement in air quality until 2016. The variation of wintertime PM_2.5 from 2009 to 2016 is influenced by both emission changes and meteorology conditions, and in this study we quantified the relative contributions from these two aspects. The sensitivity simulation by the GEOS-Chem model suggested that the emission reductions over NCP in 2013-2017 caused a 10% decrease of the regional mean PM_2.5 concentration in 2016 winter compared to the 2012 winter level. We removed the emission influence on PM_2.5 concentration to get the PM_2.5 that influenced by meteorology (met-influenced PM_2.5). For the met-influenced PM_2.5, compared to the original observation, the percentage of clean days (daily PM_2.5 concentration less than 75 μg/m³) decreases while that of the polluted (daily PM_2.5 concentration between 75 μg/m³ and150 μg/m³) and heavily polluted (daily PM_2.5 concentration between 150 μg/m³and250 μg/m³) days increases. However, proportion of the extremely polluted (daily PM_2.5 concentration exceeds 250 μg/m³) days stays unchanged, even if the emission reduction is doubled, indicating that the extremely polluted situation over NCP is dominated by the meteorological conditions, and the emission control from 2013 to 2017 has little effects on the extremely polluted days. We developed an effective haze day index (HDI) to represent the weather conditions conducive to haze days. HDI is constructed based on the normalized near surface meridional wind (V850), temperature difference (δT) between near surface (850hPa) and upper atmosphere (250hPa), and the relative humidity on 1000hPa (RH1000). HDI correlates well with daily PM_2.5 with the correlation coefficient of 0.65, and is skillful to detect 72% of the severe haze days (daily PM_2.5 concentration exceeds 150 μg/m³), ranging 48% in 2014 winter to 94% in 2012 winter. The components of HDI can also reveal the relative importance of the three meteorological variables in haze days. On average, the anomalously high meridional winds is the main cause of severe haze these years, while in 2012 winter, the relative humidity favorable for secondary aerosols formation is the largest contributor to haze.

In this poster, we present ground based remote sensing activities at Hefei, China. It includes site report for both TCCON and NDACC-IRWG observations and some research activities based on these observations.

Abstract: A ground-based low-resolution (0.5 cm⁻¹) Fourier Transform Spectrometer (FTS), the EM27/SUN, is used for determining the total column XCO2 and XCH4 of the atmosphere by analysing direct solar radiation. A ground-based high-resolution Fourier transform spectrometer (FTS) station has been established in Hefei, China to remotely measure CO2, CO and other greenhouse gases based on near-infrared solar absorption spectra. The observations of low-resolution FTS were compared with the temporally coinciding on-site measurements taken with a high-resolution FTIR spectrometer. EM27 captures the seasonal variation of CO2 and CH4.Also, there is a offset between the values of EM27 and FTS, ranging from about 1.35ppm to 1.55ppm for XCO2, and about 7.01ppb to 9.74ppb for XCH4, respectively. The observation results demonstrate the ability of the portable EM27 spectrometer as a promising addition to the TCCON FTIR sites, suitable for remote areas with low infrastructure.

In this poster, the seasonal evolution of O3 and its photochemical production regime in a polluted region of eastern China between 2014 and 2017 has been investigated. We used tropospheric ozone (O3), carbon monoxide (CO) and formaldehyde (HCHO, a marker of VOCs (volatile organic compounds)) partial columns derived from high resolution Fourier transform spectrometry (FTS), tropospheric nitrogen dioxide (NO2, a marker of NOx (nitrogen oxides)) partial column deduced from Ozone Monitoring Instrument (OMI), surface meteorological data, and a back trajectory cluster analysis technique.

The multi-field-of-view solar photometer was developed by Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences which consists of three wavelengths (442 nm, 670 nm, 880 nm) and three fields of view (0.8°, 2°, 5°) for direct sunlight. In this paper, we explores the possibility to retrieve the cloud optical thickness and effective particle radius of thin cirrus clouds by using forward scatter radiation in small angles in terms of model simulation. The radiant fluxes of different wavelengths in different fields of view are calculated based on the ice cloud characters of scattering phase function and single scattering albedo of nine ice crystal particles provided by Yang (2013) by using libRadtran software and their trends varying with the cloud optical thickness and the effective particle radius are analyzed. It is obvious that the radiant fluxes change with the cloud optical thickness for larger cloud optical thickness means longer the ice water path and more portion of the radiation is scattered. They change much more slowly with the effective particle radius and only at a small cloud optical thickness they increase with the increasing of the effective particle radius. Therefore, it is possible to retrieve the cloud optical thickness and the effective particle radius of the thin cirrus (namely the cloud optical thickness is small) simultaneously by using small angle scattering. At the same time, we calculate the difference of the radiant flux between two different fields of view, no matter which two field of view are used, the radiance flux difference is not sensitive to the effective particle radius, but sensitive to the cloud optical thickness. With the increasing of cloud optical thickness, the radiant flux difference becomes smaller gradually. This feature can also be used to retrieve the cloud optical thickness. The radiant flux ratios for arbitrary different fields of view show a good tendency to decrease gradually for droxtal particles as the effective particle radius increases,but it is not sensitive to other particle habits. Fortunately there will be a significant improvement with the effective particle radius when we find the ratio of the radiant flux difference, especially for plates. The ratios of the radiant flux difference increase gradually with the increasing of the effective particle radius. It can be seen that the inversion of the effective particle radius needs to be used several values in combination with each other. In summary, the radiant flux difference between two field of view to retrieve the cloud optical thickness and the ratio or difference ratio to retrieve the effective particle radius can be useful to ensure that it is not sensitive to another factor while doing retrievals of one factor. But this is only the analysis result of theoretical simulation calculation and We still need to do a lot of work for experimental observation and combine them together for more detailed analysis in the future.

Over a decade of OMI observations provide insight into the rapidly changing air quality levels in China. Global documentation of key atmospheric pollutant gases such as nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) allow the study of anthropogenic and natural emissions on different spatial scales.

Based on bottom-up emissions inventories, Chinese SO₂ emissions were the world’s largest, particularly over the North China Plain. SO₂ sources are related to major coal-fired power plants and industrial activities such as oil and gas refining, and metal smelting. Similarly, the highest NOx emissions are observed over the world’s most populated (increased mobile sources), highly urbanized and industrialized regions.

Despite the growth of the economy in the rapidly developing China over the past two decades, a substantial overall decrease in the SO₂ and NOx emissions has been observed with different patterns between the species. We investigate the spatial variability of these trends and we identity their origin. The differences between the spatial distributions of SO₂ and NOx emissions over the Chinese domain are related to differences in economic and technological activity, and regional environmental policies.

Government efforts to restrain emissions from power plants and industrial sectors (e.g. installation of de-sulfurization devices) have resulted in decreasing SO₂ and NOx emissions since approximately 2007 and 2011, respectively. We use the SO₂/NOx ratio to locate and characterize the emissions sources since, to some extent, it reflects the level of the regional modernization and helps us identify the source sector. For instance, the megacity of Shanghai and the areas around it are highly populated with cleaner power plants compared to other regions, therefore a relatively low SO₂/NOx ratio is observed.

Tropospheric ozone plays an important role in atmospheric processes. Hence, the acquisition of tropospheric ozone content from satellite observations is a crucial challenge for atmospheric pollution research. In this study, tropospheric ozone columns over China were retrieved from total ozone columns measured by the Ozone Monitoring Instrument (OMI) and ozone profile of the Microwave Limb Scanner (MLS). Inversion results were then compared and validated with Electrochemical Concentration Cell (ECC) ozonesonde observations, ground-based surface ozone measurements, and simulation results from the Regional Atmospheric Modeling System – Community Multiscale Air Quality Model (RAMS-CMAQ). Validation results in China during 2005–2014 showed a correlation coefficient of 0.67 between the OMI-MLS tropospheric ozone and ozonesonde data, although lower correlations (~0.36) were found over northeastern China, which were attributed to satellite observation errors at high latitudes. Comparisons between ground-based surface data and RAMS-CMAQ simulated results also demonstrated high correlations. Except for in Northeast and South China, the OMI-MLS tropospheric ozone correlates well with ground-based data (0.63) and RAMS-CMAQ simulated results (0.71). The weak correlation in South China was likely caused by the presence of ozone-generating mechanisms or sources in the upper troposphere, in addition to anthropogenic surface emissions of ozone precursors. Moreover, long-term seasonal and spatial distribution characteristics of tropospheric ozone over China were also determined, and the results show that the OMI-MLS tropospheric ozone has a trend consistent with that of ground-based and model data, accurately reflecting the seasonal changes of tropospheric ozone in China. Thus, this study demonstrates that OMI-MLS tropospheric ozone can accurately indicate changes of surface ozone concentrations. Satellite remote sensing can compensate for ground-based surface ozone observation shortages and improve the spatiotemporal coverage of near-surface ozone monitoring.

The concentration of carbon dioxide (CO₂) in the atmosphere has been rapidly increasing since the 1750s, and CO₂ has been recognized as one of the most significant greenhouse gases responsible for global climate warming. To understand and mitigate anthropogenic CO₂ emissions, regional carbon flux estimation is required for identifying CO₂ sources and sinks. The first scientific experimental CO₂ satellite of China - Chinese carbon dioxide observation satellite (TanSat) was launched in 22 Dec, 2016. After on-broad test and calibration, TanSat has been measuring the backscattered sunlight in scientific earth observation mode and produces XCO₂ data for more than two years.

The inter-comparison study between UoL-FP and IAPCAS retrieval algorithm provide a valuable experiment and help to improvement on TanSat data retrieval and results accuracy. The TCCON validation indicate a well-agreed result that need to be further investigate the in future studies. The solar induced chlorophyll fluorescence (SIF) can be approached from clear solar lines from TanSat. The TanSat SIF product indicate the seasonal variations of vegetation growth. Aerosols significantly impact CO₂ retrieval precision by modifying the light path in hyperspectral measurements in the NIR/SWIR. After investigate the information contain in measurement, a new approach is proposed to optimize the aerosol model used in the TanSat CO₂ retrieval algorithm to reduce CO₂ uncertainties associated with aerosols. The TanSat preliminary results has been compared with GEOS-Chem model, and show a consistent picture. We also find a stronger North-South gradient in the satellite dataset compared to the model. The model also shows a shallower seasonal amplitude by as much as 2 ppm when compared to the satellite observation. The validation campaign in Beijing, inner Mongolia with multiple instrument coordinate measurement, incl. EM27/SUN, AirCore and POPS shows a preliminary result in Greenhouse satellite validations.

The Chinese scientist has been visiting the Sodankyla station that has been significant contribute to greenhouse gas measurement relative issues communities, join the AirCore experiment and visiting for a joint research on TanSat data retrieval that greenhouse gas data applications in the cooperation framework of Dragon programme among U.K., Finland and China.

The atmospheric carbon dioxide (CO₂) concentration has increased to more than 405 parts per million (ppm) in 2017 due to human activities such as deforestation, land-use change and burning of fossil fuels. Although there is broad scientific consensus on the damaging consequences of the change in climate associated with increasing concentrations of greenhouse gases, fossil CO₂ emissions have continued to increase in recent years mainly from rapidly developing economies and China is now the largest emitter of CO₂ generating about 30% of all emissions globally. To allow more reliable forecast of the future state of the carbon cycle and to support the efforts for mitigation greenhouse gas emissions, a better understanding of the global and regional carbon budget is needed. Space-based measurements of CO₂ can provide the necessary observations with dense coverage and sampling to provide improved constrains on of carbon fluxes and emissions.

The Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (TanSat) was established by the National High Technology Research and Development Program of China with the main objective of monitoring atmospheric CO₂ and CO₂ fluxes at the regional and global scale. TanSat has been successfully launched in December 2016 to continue and extend space-based observations from the Japanese GOSAT and the NASA OCO-2 missions. In this presentation, we will focus on an evaluation of satellite observations of CO2 and CH4 from GOSAT over China and the wider Eastern Asia region. We will contrast GOSAT observations against state-of-the-art model calculations and ground-based validation data and we discuss how well we can observe signals from anthropogenic emissions.

In this presentation we give an overview of the recent recearch activities that have taken place at the Finnish Meteorological Institute related to remote sensing 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 satellite remote sensing of greenhouse gases using SWIR wavelengths is becoming more and more important method to understand the global distribution of methane and carbon dioxide concentrations. This is highlighted by the growing number of satellite missions targeted for greenhouse gases including GOSAT, OCO-2, TanSat, Sentinel 5P and most recently GOSAT-2 (2018) and OCO-3 with launch in April 2019 as well as ambitious plans like the proposed Copernicus high priority anthropogenic CO2 Monitoring mission. The satellite observations rely heavily on ground-based validation and bias correction and therefore, the stringent requirements on satellite observation are reflected also on the requirements for ground-based validation.

The FTIR instrument in Finnish Meteorological Institute’s premise in Sodankylä is one of the core high latitude sites for satellite validation as part of the Total Carbon Column Observing Network (TCCON) with regular observations from March till October since 2009. The AirCore balloon launches have been performed since 2013 to obtain accurate in-situ profiles of methane, carbon dioxide and carbon monoxide from troposphere to lower stratosphere. During summer 2018 a UAV version of AirCore system was tested. Sodankylä is also an ICOS site providing high quality in-situ concentration observations and eddy-covariance flux estimates at different altitudes in the new 25 m tower. These different GHG measurements together with additional measurements e.g. solar induced fluorescence provide valuable information for satellite validation. We present recent and on-going validation activities of OCO-2, TROPOMI and GOSAT and validation campaigns that have taken place in Sodankylä.

The improved data quality of the satellite observations facilitates further analysis of the global distribution of greenhouse gases and its variability. We have studied the seasonal variability and spatiotemporal distribution of greenhouse gases by analysing spatially/temporally OCO-2 and GOSAT data. The developed methods are applicable to TanSat data as well.

Carbon Dioxide (CO₂) is a main anthropogenic greenhouse gas whose concentration increase leads to heating of the troposphere and subsequently to global warming. The well-developed ground-based networks either using remote sensing or in-situ technology provide highly accurate reference measurement but their coverage is too coarse to inform reliable on regional carbon fluxes. Satellite measurement of the total column CO₂ from shortwave infrared hyperspectral measurement can provide highly accurate and precision measurements from space with sufficient coverage and resolution to improve the situation and help to advance our understanding of CO₂ and carbon fluxes.

The Chinese carbon dioxide observation satellite (TanSat), which is the first Chinese greenhouse gas monitoring satellite and a ESA third party mission and has been supported by the Ministry of Science and Technology of China, the Chinese Academy of Sciences, and the China Meteorological Administration, was launched on 22 Dec 2016, Following the European Space Agency (ESA) SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the ENVIronmental SATellite (ENVISAT), which is the first space-based instrument to provide SWIR CO₂ band hyperspectral detection, the next generation satellites GOSAT and OCO-2 launched in 2009 and 2014, respectively.

A hyperspectral grating spectrometer onboard the TanSat is monitoring the column-averaged CO₂ dry-air mixing ratio (XCO₂) over the globe. In-orbit calibration tests were completed in the summer of 2017, and the performance of the instrument has since been evaluated in test sessions. Subsequent to on-board testing and calibration, TanSat has been operationally measuring backscattered sunlight in its scientific earth observation mode and produces XCO₂ data for more than two years now.

In this study, we use two retrieval algorithms to approach the XCO₂ from TanSat hyperspectral measurements, (1) IAPCAS, Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS), is TanSat retrieval algorithm that has also been used for GOSAT (ATANGO) and OCO-2 retrieval studies. (2) UoL-FP, The University of Leicester ‘full physical’ algorithm, has been used for GOSAT retrieval and provide XCO₂ product to the ESA Climate Change Initiative (CCI) and the Copernicus Climate Change Service. The retrieval accuracy and precision of both, the IAPCAS and UoL algorithm, has been well investigated by verifying them against TCCON measurement. The fitting residual has been analyzed, and PCA based analysis method and retrieval show an improvement on residual. The approaches for aerosol and cirrus treatment have been inter compared and indicate that the methods adopted by both algorithms are reasonable to deal with the particle scattering. Validation against TCCON measurement show a well agreement on both algorithms. The method used in this study and results can help to improve the XCO₂ retrieval from TanSat and subsequently the level-2 products.

Top-down flux inversions have been used to infer surface CO2 fluxes from the observed variations of atmospheric CO2 concentrations, which has led to substantial improvements in our understanding of the global carbon cycle. Most of top-down inversions rely on the in-situ observation network with sparse and unevenly distributed spatial coverage. As a result, the inferred surface fluxes have limited temporal and spatial resolutions, with large uncertainty over many regions critical to global carbon cycle.

Recently, space-based instruments such as the JAXA GOSAT, the NASA OCO-2 satellite and the Chinese TanSat,have been developed to measure column dry-air mole fraction of the targeted greenhouse gases (such as XCO₂ or XCH₄) with unprecedented precision. However top-down inversions based on space-borne observations can be comprised by varied observation coverage, and by small uncharacterized biases, reflecting the complexity in accurately modelling the radiative transfer in the atmosphere, particularly in the presence of cloud and aerosol scattering.

To examine observation constraints on CO₂ flux over China by the three different satellite measurements, we experimentally assimilated recent versions of the GOSAT, OCO-2 and TanSat XCO₂ retrievals over the same time periods. We compared the resulting fluxes with the prior estimates as well as with the fluxes inferred from the in-situ atmospheric CO₂ observations. We further validated our results by comparing the posterior model CO₂ simulations with independent in-situ observations.

The extensive burning of fossil fuels and cement production has increased the global mean carbon dioxide (CO₂) concentration from 280 ppm before the Industrial Revolution to 410 ppm today. More specifically, urban areas are responsible for 70% of global anthropogenic emissions, playing a key role in climate change. Of particular interest is China’s recent economic growth, which has resulted in the country becoming the largest emitter of CO₂,generating about 30% of all anthropogenic emissions. In this work, we aim to use satellite data to more precisely quantify urban CO₂ emissions.

NASA’s OCO-2 satellite launched in 2014 and TanSat from China Aerospace Science launched in 2016. These instruments have the capability to resolve CO₂ concentrations at a high spatial resolution over polluted areas, allowing emission sources to be observed for the first time from space. Using data from OCO-2, an estimation of regional enhancement of ΔXCO₂ over the city of Los Angeles has been quantified compared to the background area. However, from these measurements it is not possible to distinguish the origin of the measured CO₂, since satellite observations occur at a specific time and location. Because of this, column footprints of the air particles using the high-resolution Numerical Atmospheric-dispersion Modelling Environment (NAME) have been calculated in order to evaluate which part of an urban area contributed to the satellite observations. To ultimately estimate how much CO₂ is emitted from cities, a combination of these footprints along with fluxes from different emission inventories such as EDGAR are needed to quantify the enhancement of CO₂.

An estimation of the background CO₂ concentration also needs to be performed to understand its contribution to the satellite measurements. In this work, the background concentration of CO₂ will be estimated from the global chemistry transport model CarbonTracker and the NAME calculation of the air mass history, at the same resolution as the model.

The methodology presented in this work for Los Angeles serves as a test case for future analyses over Chinese cities in order to better quantify their contribution to global emissions.

Methane is the second most important greenhouse gas in the atmosphere. Globally, the largest natural source of methane is almost equal to the largest anthropogenic source of methane: a little over 30% of the total methane emissions are from agriculture and waste (largest anthropogenic source) and approximately 30% are from wetlands (largest natural source). Currently, most of the wetland methane emissions originate from the tropics but the amount and evolution of Arctic and subarctic methane emissions are highly uncertain and involve several open questions. These questions need to be answered in order to understand the role of the Arctic and subarctic regions in the changing climate.

The common characteristics for the Arctic and subarctic regions are high seasonal temperature variations and snow cover over frozen ground during winter. These are important properties for the wetland methane emissions, as the amount of emitted methane from a specific wetland depends on, for instance, soil moisture and the temperature of the ground. Frost and snow have both direct and indirect effects on how the wetlands acts as methane source or sinks, for example, during spring, after the snowmelt, methane flux from the ground increases when the soil temperature increases. These correlations between the seasonality of frost, snow and methane have been previously studied mainly based on in situ measurements. In situ measurements have spatial limitations, especially in the Arctic and subarctic areas: due to the remote locations and infrastructures, it is almost impossible to create a spatially comprehensive measurement network. To increase the spatial distribution of methane observations, the observations are increasingly made from satellites.

Here we investigate the seasonal variability of column-averaged methane and its correlation with the seasonality of soil frost and snow, using different Earth Observation data. We combine several different data sets and show the large-scale seasonal dependencies between methane and frost or snow, noting also special features in the different parts of the Arctic and subarctic regions.

To study the seasonal variability of methane, we use space-based column-averaged methane observations from the Greenhouse Gases Observing Satellite (GOSAT), from the Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel-5 Precursor satellite and ground-based column-averaged methane retrievals from Fourier Transform Infrared Spectrometer (FTIR) measurements made at Sodankylä, Finland. The Sodankylä FTIR is part of the Total Carbon Column Observing Network (TCCON) that is a global network of ground-based observations of column-averaged greenhouse gases. The TCCON observations are the main validation source for space-based greenhouse gas observations. To detect the state of soil freezing, we use the Soil Freeze/Thaw product, which applies the observations from European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite. The Soil Freeze/Thaw product is developed at Finnish Meteorological Institute (FMI). The seasonality of snow cover is studied with GlobSnow snow extent (SE) and snow water equivalent (SWE) products that are also developed at FMI. In addition, we show inverse model results for methane concentrations and fluxes from CarbonTracker Europe - CH4 data assimilation system, and compare the fluxes to the freezing periods estimated from space-based Soil Freeze/Thaw product.

The global wind profile has a significant impact on the atmospheric circulation, the atmospheric carbon cycle, marine–atmosphere circulation, and aerosol activities. On the other hand, aerosols in the whole troposphere play a key role in the climate change and the air quality because of its direct, semi-direct, and indirect effects on the radiation budget. 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 carried the first wind lidar in space (ALADIN) and launched in August 2018. EarthCARE will carry cloud profiling radar, HSRL (High Spectral Resolution Lidar) and multispectral imager and is scheduled for launch in 2021. 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 atmospheric measurement at Cape Verde, 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). The measurement results will support the CAL/VAL of the Aeolus. 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. These devices were deployed for the CAL/VAL field campaigns. The ground-based co-located and simultaneous measurements with lidars and sun photometer during overpasses of Aeolus are foreseen over Qingdao (for example: 17:37 LT on 18 November 2018 and 06:10 LT 19 November 2018). The CAL/VAL campaigns will contribute to exploit the Aeolus wind observations for the study of atmospheric dynamics. 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. 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 (IAP) 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-IAP conducted several flights in the Mediterranean area which aimed at aerosol (incl. Saharan dust) detection using the ALADIN Airborne Demonstrator (A2D). DLR leads the Aeolus Data Innovation and Science Cluster (DISC) after launch to provide recommendations for the Aeolus instrument operation, retrieval algorithms as well as the calibration and validation procedures. The campaigns including airborne rehearsal campaign, airborne CAL/VAL campaigns and Tropical airborne campaign are ongoing/scheduled for 2018-2020.

The 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. As an outlook, combing the aerosol data from other atmospheric lidar mission with the wind/aerosol products from ADM-Aeolus, 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 can be implemented. Furthermore, by means of the back trajectories model, it is possible to determine the long range transportation of dust and to reveal its impact on marine ecosystem.

Launched on 22 August 2018, Aeolus is the first satellite mission to measure atmospheric wind profiles on a global scale. The wind observations contribute to the improvement in numerical weather prediction (NWP), as they help to close the gap in wind data coverage, especially over the oceans and in the tropics, which has been identified as one of the major deficiencies in the current Global Observing System. For this purpose, it provides profiles of one line-of-sight (LOS) component of the horizontal wind vector from ground throughout the troposphere up to the lower stratosphere with a vertical resolution of 0.25 km to 2 km depending on altitude and precision of 2 m/s to 4 m/s. The obtained near-real-time data allow for greater accuracy of the initial atmospheric state in NWP models and thus improve the quality of weather forecasts as well as the understanding of atmospheric dynamics and climate processes.

At the heart of Aeolus is the Atmospheric Laser Doppler Instrument, ALADIN, which is composed of a frequency-stabilized, ultraviolet laser, a 1.5 m-diameter telescope and a highly sensitive receiver. The revolutionary instrument works by emitting short, powerful laser pulses through the atmosphere and collecting the backscattered light from air molecules, particles and hydrometeors which move with the ambient wind. The wind speed is then derived from the frequency difference between emitted and backscattered pulses, which is caused by the Doppler effect, while the travel time of the pulses contains the altitude information. The algorithms and processors needed to derive wind profiles from ALADIN's raw data were developed by a European team of DLR institutes, the software company DoRIT as well as several European meteorological services (ECMWF, Météo-France and the Dutch weather service KNMI).

After a four-month commissioning phase dedicated to the initial in-orbit characterization and optimization of the instrument, its data processing, and as such the improvement of the wind data quality, the mission is currently in the transition to its operational phase. During this transition phase, data is released to an extended group of calibration/validation teams in order to receive important data quality assessments and further feedback, e.g. from co-located measurements. This allows for the necessary refinements of the data processing and mission operation in preparation of the official data release which is scheduled for 2019.

This presentation will provide an overview and status report of the Aeolus mission and present first impressive results obtained with the first wind lidar in space.

Since the successful launch of ESA’s Earth Explorer mission Aeolus in August 2018, atmospheric wind profiles from the ground to the lower stratosphere are being acquired on a global scale deploying the first-ever satellite-borne wind lidar system ALADIN (Atmospheric LAser Doppler INstrument). ALADIN provides one component of the wind vector along the instrument’s line-of-sight (LOS) with a vertical resolution of 0.25 km to 2 km depending on altitude, while the precision in wind speed is between 2 m/s to 4 m/s. The near-real-time wind observations contribute to improving the accuracy of numerical weather prediction and advance the understanding of tropical dynamics and processes relevant to climate variability.

Already several years before the satellite launch, an airborne prototype of the Aeolus payload, the ALADIN Airborne Demonstrator (A2D), was developed at DLR (German Aerospace Center). Due to its representative design and operating principle, the A2D has since delivered 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. Broad vertical and horizontal coverage across the troposphere is achieved thanks to the complementary design of the A2D receiver, which, like ALADIN, comprises a Rayleigh and Mie channel for analysing both molecular and particulate backscatter signals. In addition to the A2D, DLR’s research aircraft carries a well-established coherent Doppler wind lidar (2-µm DWL) which allows determining the wind vector with accuracy of better than 0.1 m/s and precision of better than 1 m/s. Hence, both instruments represent key instruments for the calibration and validation activities during the Aeolus mission.

Over the past years, the A2D and 2-µm DWL were deployed in several field experiments for the purpose of pre-launch validation of the satellite instrument and of performing wind lidar observations under various atmospheric conditions. In autumn of 2018, the first airborne campaign after the launch of Aeolus was carried out from the airbase in Oberpfaffenhofen, Germany. Aside from extending the existing dataset of wind observations, this field experiment aimed to perform several underflights of Aeolus in Central Europe in order to provide first comparative results between the two airborne wind lidars (A2D and 2-µm DWL) and the satellite instrument. At the same time, the campaign served to optimize the operational procedures, particularly in terms of flight planning, to be applied during the forthcoming Cal/Val campaigns in the operational phase of Aeolus. In particular, two campaigns are scheduled for May 2019 in Central and Southern Europe and September 2019 in the North Atlantic region.

This work will provide an overview of the most recent airborne wind lidar campaigns and present their results both from an instrument and a meteorological point-of-view. Furthermore, an outlook on the upcoming Aeolus Cal/Val campaigns will be presented.

A ground-based 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 operated in Xinglong Station. Two PICARRO G2301 instruments carry out simultaneous measurement for surface CO₂ concentration. Also, there is a MAXDOAS instrument in Xianghe, which 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. 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 Xianghe Station is now doing conventional observation of CO2 and CH4 concentration, providing a high quality dataset for validating the CO₂-measuring satellites over the world.

Key words: FTIR, PICARRO, CO₂, CH₄, Xianghe Station

As the improvement of high temporal, spatial, spectral resolution optical sensor technology, remote sensing becomes a more and more important way to understand the status and changing in both local and global scale. How to accurately calibrate the remotely sensed data becomes one of the primary problems before remotely sensed data used in different quantitative researches and applications. Consistency transfer calibration, which the measurement benchmark is obtained with ground-based and airborne standard instrument and then transferred to satellite sensors, is an efficient approach to improve the quality of satellite remotely sensed data, and it is also a key technology for operational application of the space-borne radiometric measurement benchmark. The composition of the calibration system includes: 1) the ground-based and airborne hyperspectral imager, 2) the matchup of different observation elements between different observations and 3) the standard transfer technology. Supported by the National High Technology Research and Development Program of China, the whole system has been established. And consistency transfer calibration field campaigns have also been carried out to comprehensively validate related sensors, targets and methods.

1) Totally three ground-based hyperspectral imagers and three airborne hyperspectral imagers have been developed, covering VNIR (400-1000nm), SWIR (1000-2500nm) and TIR (8-12.5μm). The spectral resolutions are 2nm, 5nm and 40nm for VNIR, SWIR and TIR ground-based imagers, respectively, and 3.5nm, 10nm and 80nm for VNIR, SWIR and TIR airborne imagers, respectively. The total field of view (FOV) of ground-based imagers is 22°, and that of the airborne imagers is up to 60°. All of the imagers have self-calibration units to guarantee the performance under actual working conditions.

2) Multi-scale data multi-element matchup methods have been developed. A spatial registration method for large resolution difference images has been proposed. The spectral matchup methods for two hyperspectral imagers and for hyperspectral imager to multispectral imager have been developed. Angular normalization models were built up for reflective solar band (RSB) and thermal emissive band (TEB), respectively. Sensitivity analysis and uncertainty analysis were performed for these methods and models.

3) Considering difference in atmospheric radiative transfer processes for different bands, consistency transfer calibration schemes were designed for RSB and TEB, respectively. Through uncertainty analysis on field non-uniformity, surface BRDF and radiative transfer calculation, the total accuracy in transfer calibration is shown to be better than 5% for RSB, and better than 1K for TEB. As to spectral calibration, the method based on atmospheric absorption lines was adopted, and brings out calibration accuracy better than 0.5nm for RSB, and better than 8nm for TEB. These indices can satisfy the specification of this sub-project.

In the last September, consistency transfer calibration experiments were carried out in the National Calibration and Validation Site for High Resolution Remote Sensors (the Baotou site). The artificial targets and natural scenes were employed as reference. More than 60 air lines were flied acquiring airborne data. Ground measured hyperspectral imager data, surface feature measurement data and atmospheric measurement data were simultaneously obtained during the flight. Overpassed high-resolution satellite data (Sentinel-2B, SV1) were used to validate the whole system. Results indicate that the total transfer calibration chain is basically feasible and reasonable. The advantages of consistent transfer radiometric calibration technology include: Firstly, in benchmark obtainment, the “ground truth” covering large area can be obtained rapidly. Therefore, the errors due to the heterogeneity of surface and temporal variance of environment can be efficiently decreased. Secondly, the airborne imager can be comprehensively calibrated by the self-calibrator and “ground truth” measured by ground-based imager so as to decrease the uncertainty. However, lots of work is still needed to improve the system, and the uncertainty traced to SI should be analyzed much more elaborately with more experimental data.

The nadiral satellite-based brightness observations were made using the Microwave Humidity and Temperature Sounder (MWHTS) instrument aboard the FY-3C polar-orbiting platform since Sept 30, 2013. Separate retrievals are demonstrated for mid-latitude conditions in extreme weather. The retrieved profile root-mean-square errors are about 0.9 K with bias error less than 1.5K. These are substantially smaller than the a priori temperature profile variations, demonstrating that 118-GHz aircraft or satellite observations can provide useful information on atmospheric vertical thermal structure. Combined with 183GHz and window channels, water vapor profiles are also retrieved accurately to be used in Sandy typhoon data assimilation model.

This paper is organized as follows. The microwave instrument is first introduced, and it is demonstrated that multiple receiver arrays can be used to multiplex a large set of channels onto a single spot on the ground. We next point out that opacity due to water vapor continuum absorption is a fundamental limitation of conventional millimeter-wave sounding and show how a multi-channel millimeter-wave approach can be used to complement the temperature-sensitive observation and overcome this limitation. We then adapt two methods to realize data assimilation based on profiles and radiance separately and in combination, and then compare with current impact in WRFDA model. Temperature, water vapor, and precipitation retrieval performance comparisons are then presented, and the impact of correlated error sources on performance is examined. Finally, we summarize and provide suggestions for further research and development of data application about polar-orbital satellite.

We present work on use a compact solar-tracking Fourier Transform Spectrometer (Bruker EM27/SUN) to precisely derive total column averaged amount of Greenhouse gases.

In order to ensure the high quality of the retrieved data, XCO₂ measured from Bruker EM27/SUN are compared to well calibrated IFS125HR in Xianghe (39.798˚N, 116.958˚E, 50m a.s.l.) as reference. We also processed the EM27/SUN data using PROFFAST and GGG2014 for further investigation the performance of the EM27/SUN. The comparison between EM27/SUN and IFS125HR shows a 0.24% bias with GGG2014+EGI, while a bias of 0.53% approached by PROFFAST. To further characteristics the differences between the two algorithms, Xgas has been measured by EM27/SUN in Beijing (IAPCAS) with coordinate weather record by WS500 weather station. The GGG2014 and PROFAST are involved in data processing, but found a bias of 0.20%, 1.23%, -1.0% for XCO₂, XCH₄ and XCO respectively. X_air calculated by the above two algorithms are approximately 1.0012、0.9831. The correlation coefficient is 0.9979 for daily median XCO₂ between the result of these two retrieval algorithms. Reasons for these differences could be attributed to the difference in pre-processing method, solar model, instrument lines shape model, gas spectroscopy.

Furthermore, field campaign collaborating EM27/SUN and aircore soundings will contribute to the greenhouse gases validation for TanSat, Sentinel-5P as well as other greenhouse gas satellites, GOSAT and OCO-2.

The surface albedo characterizes the ability of the Earth's surface to reflect solar radiation. It is an important land surface characteristic parameter that affects the radiation and energy balance of the Earth system, and determines the distribution process of radiant energy between the Earth's surface and the atmosphere. This study aims to use the Chinese FY-3C polar-orbiting meteorological satellite data to invert and verify the surface Albedo.

The inversion algorithm uses the RossThick-LiTransit semi-empirical kernel-driven BRDF (Bidirectional Reflectance Distribution Function)model, and uses the constrained least squares method to fit the model coefficients , and . The BRDF of any zenith angle and observation angle can be obtained by nuclear extrapolation . The BRDF is hemispherically integrated in the observation direction to obtain the narrow band BSA(Black-Sky Albedo) of the FY-3C band 1-4,and the double hemisphere integral is obtained in the incident and observation directions to obtain the narrow band WSA(White-Sky Albedo) of the FY-3C band 1-4.The 6S atmospheric radiation transmission model is used to simulate the surface downward radiant flux and the surface upward radiation flux covering a variety of atmospheric conditions, multiple observation angles, and various BRDF characteristics, so as to obtain the broadband albedo albedo of visible band.Using the method of multiple linear regression analysis, a linear conversion equation between narrow band albedo and broadband albedo is constructed. Using this equation, the broadband albedo of the FY-3C MERSI visible band (0.4-0.7 μm) can be obtained.

The clear sky Data of FY-3C surface albedo data, MODIS-MCD43A3, CGLS-SA and GLASS-ABD in the study area were randomly selected as the verification data, and the correlation analysis, absolute deviation analysis and root mean square error analysis were performed with these surface albedo product data. It can be seen intuitively from the scatter plot that the scatter distribution of the FY-3C surface albedo product and MODIS-MCD43A3, CGLS-SA and GLASS-ABD surface albedo product are relatively regular. The four surface albedo products have good consistency in narrowband and visible band, the correlation coefficient is about 0.88, the overall absolute deviation is 0.068, and the minimum root mean square error is 0.02, indicating FY and MODIS-MCD43A3, CGLS-SA and GLASS-ABD Have a high degree of fit.The causes of the differences in the surface albedo data verification were analyzed: (1) After geometric revision, there is a geometric error of 2~10 pixels in the MERSI reflectivity data, and the surface reflectance inversion using 16 days of clear sky data will produce a large error where the underlay surface is not uniform. (2) There is a difference between the surface reflectivity data of FY-3C after atmospheric correction and the surface reflectivity products such as MODIS-MCD43A3, CGLS-SA and GLASS-ABD, which leads to the difference of inversion.

The results showed that the surface albedo products of FY-3C and MODIS-MCD43A3, CGLS-SA and GLASS-ABD showed good correlation. The inversion algorithm of FY-3C surface albedo still needs to be studied deeply, and the improvement of inversion accuracy also depends on the key links such as data location, atmospheric revision and so on. In addition, the FY-3C surface albedo verification also needs to use the ground station point measured data for further comparative analysis.