A New TanSat XCO_2 Global Product towards Climate Studies

The 1st Chinese carbon dioxide(CO2)monitoring satellite mission,TanSat,was launched in 2016.The 1st TanSat global map of CO2 dry-air mixing ratio(XCO2)measurements over land was released as version 1 data product with an accuracy of 2.11 ppmv(parts per million by volume).In this paper,we introduce a new(version 2)TanSat global XCO2 product that is approached by the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing(IAPCAS),and the European Space Agency(ESA)Climate Change Initiative plus(CCI+)TanSat XCO2 product by University of Leicester Full Physics(UoL-FP)retrieval algorithm.The correction of the measurement spectrum improves the accuracy(?0.08 ppmv)and precision(1.47 ppmv)of the new retrieval,which provides opportunity for further application in global carbon flux studies in the future.Inter-comparison between the two retrievals indicates a good agreement,with a standard deviation of 1.28 ppmv and a bias of?0.35 ppmv.     

Detection of Anthropogenic CO2 Emission Signatures with TanSat CO2 and with Copernicus Sentinel-5 Precursor (S5P) NO2 Measurements: First Results

China’s first carbon dioxide(CO₂) measurement satellite mission, TanSat, was launched in December 2016. This paper introduces the first attempt to detect anthropogenic CO₂ emission signatures using CO₂ observations from TanSat and NO₂ measurements from the TROPOspheric Monitoring Instrument(TROPOMI) onboard the Copernicus Sentinel-5 Precursor(S5P) satellite. We focus our analysis on two selected cases in Tangshan, China and Tokyo, Japan.We found that t...     

A New Global Solar-induced Chlorophyll Fluorescence (SIF) Data Product from TanSat Measurements

The Chinese Carbon Dioxide Observation Satellite Mission(TanSat)is the third satellite for global CO2 monitoring and is capable of detecting weak solar-induced chlorophyll fluorescence(SIF)signals with its advanced technical characteristics.Based on the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing(IAPCAS)platform,we successfully retrieved the TanSat global SIF product spanning the period of March 2017 to February 2018 with a physically based algorithm.This paper introduces the new TanSat SIF dataset and shows the global seasonal SIF maps.A brief comparison between the IAPCAS TanSat SIF product and the data-driven SVD(singular value decomposition)SIF product is also performed for follow-up algorithm optimization.The comparative results show that there are regional biases between the two SIF datasets and the linear correlations between them are above 0.73 for all seasons.The future SIF data product applications and requirements for SIF space observation are discussed.     

Validation of Column-Averaged Dry-Air Mole Fraction of CO<Subscript>2</Subscript> Retrieved from OCO-2 Using Ground-Based FTS Measurements

In order to correctly use the column-averaged atmospheric CO₂ dry-air mole fraction (XCO₂) data in the CO₂ flux studies, XCO₂ measurements retrieved from the Orbiting Carbon Observatory-2 (OCO-2) in 2015 were compared with those obtained from the global ground-based high-resolution Fourier Transform Spectrometer (FTS) participating in the Total Carbon Column Observing Network (TCCON). The XCO₂ retrieved from three observing modes adopted by OCO-2, i.e., nadir, target, and glint, were separately validated by the FTS measurements at up to eight TCCON stations located in different areas. These comparisons show that OCO-2 glint mode yields the best qualitative estimations of CO₂ concentration among the three operational approaches. The overall results regarding the glint mode show no obvious systematic biases. These facts may indicate that the glint concept is appropriate for not only oceans but also land regions. Negative systematic biases in nadir and target modes have been found at most TCCON sites. The standard deviations of XCO₂ retrieved from target and nadir modes within the observation period are similar, and larger than those from glint mode. We also used the FTS site in Beijing, China, to assess the OCO-2 XCO₂ in 2016. This site is located in a typical urban area, which has been absent in previous studies. Overall, OCO-2 XCO₂ agrees well with that from FTS at this site. Such a study will benefit the validation of the newly launched TanSat products in China.     

Monitoring Carbon Dioxide from Space:Retrieval Algorithm and Flux Inversion Based on GOSAT Data and Using CarbonTracker-China

Monitoring atmospheric carbon dioxide(CO_2) from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of "The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change: Carbon Budget and Relevant Issues". The carbon flux inversion system is composed of two separate parts: the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing(IAPCAS), and Carbon Tracker-China(CT-China), developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite(GOSAT) measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%–30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO_2(column-averaged CO_2dry-air mole fraction) is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO_2 product is used in carbon flux estimation by CT-China. The net ecosystem CO_2 exchange is-0.34 Pg C yr~(-1)(±0.08 Pg C yr~(-1)), with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion.     

European CO2 fluxes from atmospheric inversions using regional and global transport models

Approximately half of human-induced carbon dioxide (CO₂) emissions are taken up by the land and ocean, and the rest stays in the atmosphere, increasing the global concentration and acting as a major greenhouse-gas (GHG) climate-forcing element. Although GHG mitigation is now in the political arena, the exact spatial distribution of the land sink is not well known. In this paper, an estimation of mean European net ecosystem exchange (NEE) carbon fluxes for the period 1998–2001 is performed with three mesoscale and two global transport models, based on the integration of atmospheric CO₂ measurements into the same Bayesian synthesis inverse approach. A special focus is given to sub-continental regions of Europe making use of newly available CO₂ concentration measurements in this region. Inverse flux estimates from the five transport models are compared with independent flux estimates from four ecosystem models. All inversions detect a strong annual carbon sink in the southwestern part of Europe and a source in the northeastern part. Such a dipole, although robust with respect to the network of stations used, remains uncertain and still to be confirmed with independent estimates. Comparison of the seasonal variations of the inversion-based net land biosphere fluxes (NEP) with the NEP predicted by the ecosystem models indicates a shift of the maximum uptake period, from June in the ecosystem models to July in the inversions. This study thus improves on the understanding of the carbon cycle at sub-continental scales over Europe, demonstrating that the methodology for understanding regional carbon cycle is advancing, which increases its relevance in terms of issues related to regional mitigation policies.     

Determination of tropospheric mean carbon dioxide concentration from satellite high spectral resolution IR-sounder data

In view of the importance of studying a global carbon cycle and inadequacy of a ground-based network of observations of the atmospheric carbon dioxide (CO₂) concentrations and its fluxes, the feasibility of remote sensing of the atmospheric CO₂ concentration obtained from the satellite high-spectral resolution IR-sounder data is studied. In reference to the AIRS infrared-sounder measurements (the EOS Aqua satellite) the satellite data informativeness is analyzed, and a subset of most sensitive channels in respect to the CO₂ concentration variations is selected. A method of retrieving the carbon dioxide concentration \(X_{CO_2 } \) averaged over height from the AIRS data (in the middle and upper troposphere) is suggested and tested. The method is based on a numerical solution of an inverse problem. The comparison of satellite estimates of \(X_{CO_2 } \) averaged over a month with the aircraft (in situ) data on observations over the areas of boreal forests (the Novosibirsk region) and ecosystems (the region of Surgut) for 10 months of 2003 confirms the possibility to trace a seasonal trend of \(X_{CO_2 } \) with an error not worse than 1%.     

Characterization of Regional Combustion Efficiency using ΔXCO: ΔXCO2 Observed by a Portable Fourier-Transform Spectrometer at an Urban Site in Beijing

Measurements of column-averaged dry-air mole fractions of carbon dioxide and carbon monoxide, CO₂ (XCO₂) and CO (XCO), were performed throughout 2019 at an urban site in Beijing using a compact Fourier Transform Spectrometer (FTS) EM27/SUN. This data set is used to assess the characteristics of combustion-related CO₂ emissions of urban Beijing by analyzing the correlated daily anomalies of XCO and XCO₂ (e.g., ΔXCO and ΔXCO₂). The EM27/SUN measurements were calibrated to a 125HR-FTS at the Xianghe station by an extra EM27/SUN instrument transferred between two sites. The ratio of ΔXCO over ΔXCO₂ (ΔXCO:ΔXCO₂) is used to estimate the combustion efficiency in the Beijing region. A high correlation coefficient (0.86) between ΔXCO and ΔXCO₂ is observed. The CO:CO₂ emission ratio estimated from inventories is higher than the observed ΔXCO:ΔXCO₂ (10.46 ± 0.11 ppb ppm^?1) by 42.54%–101.15%, indicating an underestimation in combustion efficiency in the inventories. Daily ΔXCO:ΔXCO₂ are influenced by transportation governed by weather conditions, except for days in summer when the correlation is low due to the terrestrial biotic activity. By convolving the column footprint [ppm (μmol m^–2 s^–1)^–1] generated by the Weather Research and Forecasting-X-Stochastic Time-Inverted Lagrangian Transport models (WRF-X-STILT) with two fossil-fuel emission inventories (the Multi-resolution Emission Inventory for China (MEIC) and the Peking University (PKU) inventory), the observed enhancements of CO₂ and CO were used to evaluate the regional emissions. The CO₂ emissions appear to be underestimated by 11% and 49% for the MEIC and PKU inventories, respectively, while CO emissions were overestimated by MEIC (30%) and PKU (35%) in the Beijing area.     

Estimates of Large-Scale Fluxes in High Latitudes from Terrestrial Biosphere Models and an Inversion of Atmospheric CO2 Measurements

It is important to improve estimates of large-scale carbon fluxes over the boreal forest because the responses of this biome to global change may influence the dynamics of atmospheric carbon dioxide in ways that may influence the magnitude of climate change. Two methods currently being used to estimate these fluxes are process-based modeling by terrestrial biosphere models (TBMs), and atmospheric inversions in which fluxes are derived from a set of observations on atmospheric CO₂ concentrations via an atmospheric transport model. Inversions do not reveal information about processes and therefore do not allow for predictions of future fluxes, while the process-based flux estimates are not necessarily consistent with atmospheric observations of CO₂. In this study we combine the two methods by using the fluxes from four TBMs as a priori fluxes for an atmospheric Bayesian Synthesis Inversion. By doing so we learn about both approaches. The results from the inversion indicate where the results of the TBMs disagree with the atmospheric observations of CO₂, and where the results of the inversion are poorly constrained by atmospheric data, the process-based estimates determine the flux results. The analysis indicates that the TBMs are modeling the spring uptake of CO₂ too early, and that the inversion shows large uncertainty and more dependence on the initial conditions over Europe and Boreal Asia than Boreal North America. This uncertainty is related to the scarcity of data over the continents, and as this problem is not likely to be solved in the near future, TBMs will need to be developed and improved, as they are likely the best option for understanding the impact of climate variability in these regions.     

Optimization of the OCO-2 Cloud Screening Algorithm and Evaluation against MODIS and TCCON Measurements over Land Surfaces in Europe and Japan

A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2(OCO-2) cloud screening algorithms. Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations, which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO₂ dry air mole fraction(XCO₂). Based on the rad...     

Ground-Based Atmospheric CO2, CH4, and CO Column Measurements at Golmud in the Qinghai-Tibetan Plateau and Comparisons with TROPOMI/S5P Satellite Observations

Measurements of carbon dioxide(CO₂), methane(CH₄), and carbon monoxide(CO) are of great importance in the Qinghai-Tibetan region, as it is the highest and largest plateau in the world affecting global weather and climate systems. In this study, for the first time, we present CO₂, CH₄, and CO column measurements carried out by a Bruker EM27/SUN Fourier-transform infrared spectrometer(FTIR) at Golmud(36.42°E, 94.91°N, 2808 m) in August 2021. The mean and...     

陆地生态系统固碳速率立体监测方法:进展与挑战

全球CO₂浓度增加造成的全球变暖已成为人类亟需解决的问题,陆地生态系统在过去几十年一直扮演着重要的碳汇角色,吸收了30％左右的人类活动排放CO₂。本文调研分析了陆地生态系统固碳速率空间估算方法,包括样地调查、通量监测、模型模拟、遥感估算等,梳理了各种估算方法的研究现状与进展。样地调查、通量观测等方法可以提供点尺度的固碳速率直接测量信息,但存在观测样本有限、空间代表性不足等问题。模型模拟方法可以从机理的角度描述陆地碳、水、能量循环,模拟预测陆地生态系统固碳速率的状态和变化。然而,在模型建立过程中,抽象和简化会引入结构与假设的不确定性,以及模型驱动数据引入的不确定性等问题是碳循环模型模拟方法面临的重大挑战。卫星遥感具有全球覆盖、分辨率精细、时间序列观测等优点,结合机器学习方法,为地球大数据驱动的全球碳源汇估算提供了新的研究范式。但是,当前各种固碳速率的监测方法还没有满足高度时空异质性的陆地生态系统固碳量监测需求,未来需要整合地面观测、模型模拟和卫星遥感等多种技术手段,提供区域和全球尺度的陆地生态系统碳汇精确估算方法体系和科学数据产品。     

Consequences of Incomplete Surface Energy Balance Closure for CO2 Fluxes from Open-Path CO2/H2O Infrared Gas Analysers

We present an approach for assessing the impact of systematic biases in measured energy fluxes on CO₂ flux estimates obtained from open-path eddy-covariance systems. In our analysis, we present equations to analyse the propagation of errors through the Webb, Pearman, and Leuning (WPL) algorithm [Quart. J. Roy. Meteorol. Soc. 106, 85–100, 1980] that is widely used to account for density fluctuations on CO₂ flux measurements. Our results suggest that incomplete energy balance closure does not necessarily lead to an underestimation of CO₂ fluxes despite the existence of surface energy imbalance; either an overestimation or underestimation of CO₂ fluxes is possible depending on local atmospheric conditions and measurement errors in the sensible heat, latent heat, and CO₂ fluxes. We use open-path eddy-covariance fluxes measured over a black spruce forest in interior Alaska to explore several energy imbalance scenarios and their consequences for CO₂ fluxes.     

The Turbulent Lagrangian Time Scale in Forest Canopies Constrained by Fluxes,Concentrations and Source Distributions

One-dimensional Lagrangian dispersion models, frequently used to relate in-canopy source/sink distributions of energy, water and trace gases to vertical concentration profiles, require estimates of the standard deviation of the vertical wind speed, which can be measured, and the Lagrangian time scale, T _L , which cannot. In this work we use non-linear parameter estimation to determine the vertical profile of the Lagrangian time scale that simultaneously optimises agreement between modelled and measured vertical profiles of temperature, water vapour and carbon dioxide concentrations within a 40-m tall temperate Eucalyptus forest in south-eastern Australia. Modelled temperature and concentration profiles are generated using Lagrangian dispersion theory combined with source/sink distributions of sensible heat, water vapour and CO₂. These distributions are derived from a multilayer Soil-Vegetation-Atmospheric-Transfer model subject to multiple constraints: (1) daytime eddy flux measurements of sensible heat, latent heat, and CO₂ above the canopy, (2) in-canopy lidar measurements of leaf area density distribution, and (3) chamber measurements of CO₂ ground fluxes. The resulting estimate of Lagrangian time scale within the canopy under near-neutral conditions is about 1.7 times higher than previous estimates and decreases towards zero at the ground. It represents an advance over previous estimates of T _L , which are largely unconstrained by measurements.     

Estimation of Nocturnal Area Fluxes of Carbon Cycle Gases in Saint Petersburg Suburbs

Carbon dioxide, methane, and carbon monoxide are the carbon cycle gases, the data on their emissions are needed when monitoring air pollution and developing methods for reducing anthropogenic emissions to the atmosphere and for climate forecasting. The estimates of nocturnal area fluxes for CO₂, CH₄, and CO presented for a suburb of Saint Petersburg (Peterhof) are obtained using the box model and continuous observations of concentration of these gases. The mean values of CH₄, CO₂, and CO fluxes estimated for Peterhof for 2014–2015 are 44 ± 27, 6100 ± 4000, and 90 ± 100 t/(km² year), respectively. The intensity of the CO area flux has pronounced seasonal variations characterized by the maximum of ~(160 ± 120) t/(km² year) in November—February and by the minimum of ~(30 ± 20) t/(km² year) in June-July. The analysis of the ratio of CO/CO₂ fluxes identified the main types of anthropogenic sources typical of Peterhof: motor transport, natural gas combustion, and the use of wood stoves for the heating of private low-rise buildings (in the cold season).     

Surface turbulent flux measurements over the Loess Plateau for a semi-arid climate change study

In order to provide high quality data for climate change studies, the data quality of turbulent flux measurements at the station of SACOL (Semi-Arid Climate & Environment Observatory of Lanzhou University), which is located on a semi-arid grassland over the Loess Plateau in China, has been analyzed in detail. The effects of different procedures of the flux corrections on CO₂, momentum, and latent and sensible heat fluxes were assessed. The result showed that coordinate rotation has a great influence on the momentum flux but little on scalar fluxes. For coordinate rotation using the planar fit method, different regression planes should be determined for different wind direction sectors due to the heterogeneous nature of the ground surface. Sonic temperature correction decreased the sensible heat flux by about 9%, while WPL correction (correction for density fluctuations) increased the latent heat flux by about 10%. WPL correction is also particularly important for CO₂ fluxes. Other procedures of flux corrections, such as the time delay correction and frequency response correction, do not significantly influence the turbulent fluxes. Furthermore, quality tests on stationarity and turbulence development conditions were discussed. Parameterizations of integral turbulent characteristics (ITC) were tested and a specific parameterization scheme was provided for SACOL. The ITC test on turbulence development conditions was suggested to be applied only for the vertical velocity. The combined results of the quality tests showed that about 62%–65% of the total data were of high quality for the latent heat flux and CO₂ flux, and as much as about 76% for the sensible heat flux. For the momentum flux, however, only about 35% of the data were of high quality.     

Cross‐shore variations of near‐surface wind velocity and atmospheric turbulence at the land‐sea boundary during CASP

Abstract

Airborne measurements of mean wind velocity and turbulence in the atmospheric boundary layer under wintertime conditions of cold offshore advection suggest that at a height of 50 m the mean wind speed increases with offshore distance by roughly 20% over a horizontal scale of order 10 km. Similarly, the vertical gust velocity and turbulent kinetic energy decay on scales of order 3.5 km by factors of 1.5 and 3.2, respectively. The scale of cross‐shore variations in the vertical fluxes of heat and downwind momentum is also 10 km, and the momentum flux is found to be roughly constant to 300 m, whereas the heat flux decreases with height. The stability parameter, z/L (where z = 50 m and L is the local Monin‐Obukhov length), is generally small over land but may reach order one over the warm ocean. The magnitude and horizontal length scales associated with the offshore variations in wind speed and turbulence are reasonably consistent with model results for a simple roughness change, but a more sophisticated model is required to interpret the combined effects of surface roughness and heat flux contrasts between land and sea.

Comparisons between aircraft and profile‐adjusted surface measurements of wind speed indicate that Doppler biases of 1–2 m s^?1 in the aircraft data caused by surface motions must be accounted for. In addition, the wind direction measurements of the Minimet anemometer buoy deployed in CASP are found to be in error by 25 ± 5°, possibly due to a misalignment of the anemometer vane. The vertical fluxes of heat and momentum show reasonably good agreement with surface estimates based on the Minimet data.     

The Variability of Air-sea O2 Flux in CMIP6: Implications for Estimating Terrestrial and Oceanic Carbon Sinks

The measurement of atmospheric O₂ concentrations and related oxygen budget have been used to estimate terrestrial and oceanic carbon uptake. However, a discrepancy remains in assessments of O₂ exchange between ocean and atmosphere (i.e. air-sea O₂ flux), which is one of the major contributors to uncertainties in the O₂-based estimations of the carbon uptake. Here, we explore the variability of air-sea O₂ flux with the use of outputs from Coupled Model Intercomparison Project phase 6 (CMIP6). The simulated air-sea O₂ flux exhibits an obvious warming-induced upward trend (~1.49 Tmol yr^?2) since the mid-1980s, accompanied by a strong decadal variability dominated by oceanic climate modes. We subsequently revise the O₂-based carbon uptakes in response to this changing air-sea O₂ flux. Our results show that, for the 1990?2000 period, the averaged net ocean and land sinks are 2.10±0.43 and 1.14±0.52 GtC yr^?1 respectively, overall consistent with estimates derived by the Global Carbon Project (GCP). An enhanced carbon uptake is found in both land and ocean after year 2000, reflecting the modification of carbon cycle under human activities. Results derived from CMIP5 simulations also investigated in the study allow for comparisons from which we can see the vital importance of oxygen dataset on carbon uptake estimations.     

基于涡度相关法的中国农田生态系统碳通量研究进展

农田生态系统是受人为活动强烈控制和干扰的系统,对其碳源/汇的评价是全球碳循环研究的热点.首先概括了以涡度相关法为手段的中国农田生态系统碳通量的研究进展,重点总结了中国农田生态系统碳通量的时间变化、驱动机制和模型模拟等方面的研究成果,并在此基础上对今后中国农田生态系统碳通量研究提出了建议,认为长期观测与研究、多因子协同作用、模型开发与尺度推绎、数据质量监控和评价是今后研究的重点方向.