Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TAN...Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TANSAT）, a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager （CAPI）, which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloud- screening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer （VIRR） onboard the Chinese FengYun-3A Polar-orbiting Meteoro- logical Satellite （FY-3A）, which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas （desert, snow, ocean, forest） for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.展开更多
China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observati...China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observations from TanSat and NO_(2) 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 the TanSat XCO_(2) measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO_(2) observations.The linear fit between TanSat XCO_(2) and TROPOMI NO_(2) indicates the CO_(2)-to-NO_(2) ratio of 0.8×10^(-16) ppm(molec cm^(-2))^(-1) in Tangshan and 2.3×10^(-16) ppm(molec cm^(-2))^(-1) in Tokyo.Our results align with the CO_(2)-to-NOx emission ratios obtained from the EDGAR v6 emission inventory.展开更多
Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon ...Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr^(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.展开更多
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...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.展开更多
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 te...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.展开更多
The Chinese global carbon dioxide monitoring satellite(TanSat)was successfully launched in December 2016 and has completed its on-orbit tests and calibration.TanSat aims to measure the atmospheric Carbon Dioxide colum...The Chinese global carbon dioxide monitoring satellite(TanSat)was successfully launched in December 2016 and has completed its on-orbit tests and calibration.TanSat aims to measure the atmospheric Carbon Dioxide column-averaged dry air mole fractions(X_(CO_2))with a precision of 4 ppm at the regional scale,and further to derive the CO_2 global and regional fluxes.Progress toward these objectives is reviewed and the first scientific results from TanSat measurements are presented.During the design phase,Observation System Simulation Experiments(OSSE)on TanSat measurements performed prior to launch measurements using a nadir and a glint alternative mode when considering the balance of stable measurements and reduces the flux uncertainty(64%).The constellation measurements of two satellites indicate an extra 10%improvement in flux inversion if the satellite measurements have no bias and similar precision.The TanSat on-orbit test indicates that the instrument is stable and beginning to produce X_(CO_2)products.The preliminary TanSat measurements have been validated with Total Carbon Column Observing Network(TCCON)measurements and have inter-compared with OCO-2 measurements in an overlap measurement.展开更多
The first Chinese Carbon Dioxide Observation Satellite Mission(TanSat), which was launched on December 21, 2016, is intended to measure atmospheric CO_2 concentration.The high spectral resolution(0.044 nm) and high SN...The first Chinese Carbon Dioxide Observation Satellite Mission(TanSat), which was launched on December 21, 2016, is intended to measure atmospheric CO_2 concentration.The high spectral resolution(0.044 nm) and high SNR(360 at 15.2 mW m^(-1) sr^(-1) nm^(-1)) measurements in the region of the O_2-A band of the Atmospheric Carbon dioxide Grating Spectroradiometer(AGCS) module onboard TanSat make it possible to retrieve solar-induced chlorophyll fluorescence(SIF) from TanSat observations at the global scale.This paper aims to explore the potential of the TanSat data for global SIF retrieval.A singular vector decomposition(SVD) statistical method was employed to retrieve SIF using radiance over a micro spectral window(～2 nm) around the Fe Fraunhofer lines(centered at 758.8 nm).The global SIF at 758.8 nm was successfully retrieved with a low residual error of 0.03 mW m^(-1) sr^(-1) nm^(-1).The results show that the spatial and temporal patterns of the retrieved SIF agree well with the global terrestrial vegetation pattern.The monthly SIF products retrieved from the TanSat data were compared with other remote sensing datasets, including OCO-2 SIF, MODIS NDVI, EVI and GPP.The overall consistency between TanSat and OCO-2 SIF products(R^2= 0.86) and the consistency of the spatial patterns and temporal variations between the TanSat SIF and MODIS vegetation indices and GPP enhance our confidence in the potential and feasibility of TanSat data for SIF retrieval.TanSat, therefore, provides a new opportunity for global sampling of SIF at fine spatial resolution(2 km × 2 km), thus improving photosynthesis observations from space.展开更多
The Chinese global carbon dioxide monitoring satellite （TanSat） was launched successfully in December 2016 and has completed its on-orbit tests and calibration. TanSat aims to measure the atmospheric column-averaged...The Chinese global carbon dioxide monitoring satellite （TanSat） was launched successfully in December 2016 and has completed its on-orbit tests and calibration. TanSat aims to measure the atmospheric column-averaged dry air mole fractions of carbon dioxide （XCO2） with a precision of 4 ppm at the regional scale, and in addition, to derive global and regional CO2 fluxes. Progress towards these objectives is reviewed and the first scientific results from TanSat measurements are presented. TanSat on-orbit tests indicate that the Atmospheric Carbon dioxide GratingSpectrometer is in normal working status and is beginning to produce LIB products. The preliminary TanSat XCO2 products have been retrieved by an algorithm and compared to NASA Orbiting Carbon Observatory-2 （OCO-2） measurements during an over- lapping observation period. Furthermore, the XCO2 retrievals have been validated against eight groundsite measurement datasets from the Total Carbon Column Observing Network, for which the preliminary conclusion is that TanSat has met the precision design requirement, with an average bias of 2.11 ppm. The first scientific observations are presented, namely, the seasonal distributions of XCO2 over land on a global scale.展开更多
Accurate monitoring of changes in atmospheric carbon dioxide(C02)coneentration and carbon sinks/sources distribution are an important prerequisite for comprehensively understanding the global carbon cycle and correctl...Accurate monitoring of changes in atmospheric carbon dioxide(C02)coneentration and carbon sinks/sources distribution are an important prerequisite for comprehensively understanding the global carbon cycle and correctly predicting future climate change.Satellite remote sensing is the only method to achieve this monitoring with high resolution.Although spaceborne hyperspectral remote sensing sensors have been successfully applied to monitor the concentration of C02 in the upper troposphere,they are not sensitive to changes in C02 concentrations near the Earth's surface.W让h the rapid development of sensor technology,quantitative remote sensing algorithms,satellites equipped with near-infrared and short-wave infrared hyperspectral sensors dedicated to C02 monitoring have been successively launched.展开更多
We present a study on the retrieval sensitivity of the column-averaged dry-air mole fraction of CO2(XCO2) for the Chinese carbon dioxide observation satellite(TanSat) with a full physical forward model and the optimal...We present a study on the retrieval sensitivity of the column-averaged dry-air mole fraction of CO2(XCO2) for the Chinese carbon dioxide observation satellite(TanSat) with a full physical forward model and the optimal estimation technique. The forward model is based on the vector linearized discrete ordinate radiative transfer model(VLIDORT) and considers surface reflectance, gas absorption, and the scattering of air molecules, aerosol particles, and cloud particles. XCO2 retrieval errors from synthetic TanSat measurements show solar zenith angle(SZA), albedo dependence with values varying from 0.3 to 1 ppm for bright land surface in nadir mode and 2 to 8 ppm for dark surfaces like snow. The use of glint mode over dark oceans significantly improves the CO2 information retrieved. The aerosol type and profile are more important than the aerosol optical depth, and underestimation of aerosol plume height will introduce a bias of 1.5 ppm in XCO2. The systematic errors due to radiometric calibration are also estimated using a forward model simulation approach.展开更多
This study developed a highly accurate retrieval algorithm for the column-averaged CO2 dry-air mixing ratio (XCO2) to be observed by TanSat, China's carbon dioxide observation satellite that will be launched in 20...This study developed a highly accurate retrieval algorithm for the column-averaged CO2 dry-air mixing ratio (XCO2) to be observed by TanSat, China's carbon dioxide observation satellite that will be launched in 2015. The Greenhouse Gases Observing Satellite (GOSAT) L1B spectrum was applied in retrieval experiment, and the results were validated with ground-observed measurements from the Total Column Carbon Observing Network (TCCON). At mid-latitudes, most results fell in the 1% error region, which correspond to the performance of GOSAT algorithm. The results also showed seasonal variation in XCO2 in both hemispheres.展开更多
The spectral sampling rate and range of CO2absorption bands are critical for the optimal design of hyperspectral instrument for CO2observation satellite.Undersampling of spectra in space-based spectrometer significant...The spectral sampling rate and range of CO2absorption bands are critical for the optimal design of hyperspectral instrument for CO2observation satellite.Undersampling of spectra in space-based spectrometer significantly contaminates signals measured in the CO21.61 lm-band.The CO2dry-air column(XCO2)error due to spectral undersampling can be up to*1 ppm,which is the target precision of the Chinese Carbon Satellite(TanSat)for a single sounding.Undersampling error depends on surface albedo,solar zenith angle,and scattering properties in the atmosphere.The spectral sampling rate is recommended to be greater than 2.0 pixels per full width at half maximum to avoid undersampling.Reduction of spectral resolution and the use of narrower spectral regions can improve spectral sampling with little changes in CO2retrieval sensitivity without losing much information.The full-band approach provides direct constraints on the wavelength-dependent surface albedo and particle scattering from the measurements.To keep a broader band,we recommend reduction of the spectral resolution by a factor of two.展开更多
基金sponsored by the National Basic Research(973)Program of China from the Ministry of Science and Technology of China(Grant No.2013CB430104)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA05040201)
文摘Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TANSAT）, a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager （CAPI）, which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloud- screening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer （VIRR） onboard the Chinese FengYun-3A Polar-orbiting Meteoro- logical Satellite （FY-3A）, which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas （desert, snow, ocean, forest） for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.
基金supported by the National Key Research And Development Plan (2019YFE0127500)International Partnership Program of the Chinese Academy of Sciences (060GJHZ2022070MI)+2 种基金the Key Research Program of the Chinese Academy of Sciences (ZDRWZS-2019-1)the Finland-China mobility cooperation project funded by the Academy of Finland (No. 348596)Financial support for the Academy of Finland (No. 336798)
文摘China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observations from TanSat and NO_(2) 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 the TanSat XCO_(2) measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO_(2) observations.The linear fit between TanSat XCO_(2) and TROPOMI NO_(2) indicates the CO_(2)-to-NO_(2) ratio of 0.8×10^(-16) ppm(molec cm^(-2))^(-1) in Tangshan and 2.3×10^(-16) ppm(molec cm^(-2))^(-1) in Tokyo.Our results align with the CO_(2)-to-NOx emission ratios obtained from the EDGAR v6 emission inventory.
基金supported by the National Key R&D Program of China (Grant No.2016YFA0600203)the National Key R&D Program of China (Grant No.2017YFB0504000)+3 种基金the Key Research Program of the Chinese Academy of Sciences (ZDRW-ZS-2019-1)the Youth Program of the National Natural Science Foundation of China (Grant No.41905029)supported by the UK NERC National Centre for Earth Observation (NCEO)The TanSat L1B data service is provided by IRCSD and CASA (131211KYSB20180002)。
文摘Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr^(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.
基金This work was supported by the National Key R&D Program of China(Grant No.2016YFA0600203)the Key Research Program of the Chinese Academy of Sciences(Grant No.ZDRW-ZS-2019-1)+4 种基金the International Partnership Program of the Chinese Academy of Sciences(Grant No.GJHZ201903)the National Natural Science Foundation of China(Grant No.41905029)ESA Climate Change Initiative CCI+(GhG theme),Earthnet Data Assessment Pilot(EDAP)project and ESA-MOST Dragon-4 programme(ID 32301)supported by the UK NERC National Centre for Earth Observation(NCEO)(Grant Nos.nceo020005 and NE/N018079/1)The TanSat L1B data service is provided by IRCSD and CASA(131211KYSB20180002).
文摘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.
基金This study was supported by the National Key R&D Program of China(No.2016YFA0600203)the Key Research Program of the Chinese Academy of Sciences(ZDRW-ZS-2019-1&ZDRW-ZS-2019-2)the Youth Program of the National Natural Science Foundation of China(41905029).The TanSat L1B data service was provided by the International Reanalysis Cooperation on Carbon Satellite Data(IRCSD)(131211KYSB20180002)and the Cooperation on the Analysis of Carbon Satellite Data(CASA).The authors thank the OCO-2 team for providing the Level-2 SIF data products.
文摘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.
基金Supported by National Key R＆D Program of China(2016YFA0600203,2017YFB0504000) the National High-tech Research and Development Program(2011AA12A104) External Cooperation Program of the Chinese Academy of Sciences(GJHZ1507)
文摘The Chinese global carbon dioxide monitoring satellite(TanSat)was successfully launched in December 2016 and has completed its on-orbit tests and calibration.TanSat aims to measure the atmospheric Carbon Dioxide column-averaged dry air mole fractions(X_(CO_2))with a precision of 4 ppm at the regional scale,and further to derive the CO_2 global and regional fluxes.Progress toward these objectives is reviewed and the first scientific results from TanSat measurements are presented.During the design phase,Observation System Simulation Experiments(OSSE)on TanSat measurements performed prior to launch measurements using a nadir and a glint alternative mode when considering the balance of stable measurements and reduces the flux uncertainty(64%).The constellation measurements of two satellites indicate an extra 10%improvement in flux inversion if the satellite measurements have no bias and similar precision.The TanSat on-orbit test indicates that the instrument is stable and beginning to produce X_(CO_2)products.The preliminary TanSat measurements have been validated with Total Carbon Column Observing Network(TCCON)measurements and have inter-compared with OCO-2 measurements in an overlap measurement.
基金supported by the National Key Research and Development Program of China (2017YFA0603001)Scientific Research Satellite Engineering of Civil Space Infrastructure Projectthe National Natural Science Foundation of China (41671349, 41701396)
文摘The first Chinese Carbon Dioxide Observation Satellite Mission(TanSat), which was launched on December 21, 2016, is intended to measure atmospheric CO_2 concentration.The high spectral resolution(0.044 nm) and high SNR(360 at 15.2 mW m^(-1) sr^(-1) nm^(-1)) measurements in the region of the O_2-A band of the Atmospheric Carbon dioxide Grating Spectroradiometer(AGCS) module onboard TanSat make it possible to retrieve solar-induced chlorophyll fluorescence(SIF) from TanSat observations at the global scale.This paper aims to explore the potential of the TanSat data for global SIF retrieval.A singular vector decomposition(SVD) statistical method was employed to retrieve SIF using radiance over a micro spectral window(～2 nm) around the Fe Fraunhofer lines(centered at 758.8 nm).The global SIF at 758.8 nm was successfully retrieved with a low residual error of 0.03 mW m^(-1) sr^(-1) nm^(-1).The results show that the spatial and temporal patterns of the retrieved SIF agree well with the global terrestrial vegetation pattern.The monthly SIF products retrieved from the TanSat data were compared with other remote sensing datasets, including OCO-2 SIF, MODIS NDVI, EVI and GPP.The overall consistency between TanSat and OCO-2 SIF products(R^2= 0.86) and the consistency of the spatial patterns and temporal variations between the TanSat SIF and MODIS vegetation indices and GPP enhance our confidence in the potential and feasibility of TanSat data for SIF retrieval.TanSat, therefore, provides a new opportunity for global sampling of SIF at fine spatial resolution(2 km × 2 km), thus improving photosynthesis observations from space.
基金supported by the National Key R & D Program of China (2016YFA0600203)the National High-tech Research and Development Program (2011AA12A104)+1 种基金External Cooperation Program of the Chinese Academy of Sciences (GJHZ1507)the National Key R & D Program of China (2017YFB0504000)
文摘The Chinese global carbon dioxide monitoring satellite （TanSat） was launched successfully in December 2016 and has completed its on-orbit tests and calibration. TanSat aims to measure the atmospheric column-averaged dry air mole fractions of carbon dioxide （XCO2） with a precision of 4 ppm at the regional scale, and in addition, to derive global and regional CO2 fluxes. Progress towards these objectives is reviewed and the first scientific results from TanSat measurements are presented. TanSat on-orbit tests indicate that the Atmospheric Carbon dioxide GratingSpectrometer is in normal working status and is beginning to produce LIB products. The preliminary TanSat XCO2 products have been retrieved by an algorithm and compared to NASA Orbiting Carbon Observatory-2 （OCO-2） measurements during an over- lapping observation period. Furthermore, the XCO2 retrievals have been validated against eight groundsite measurement datasets from the Total Carbon Column Observing Network, for which the preliminary conclusion is that TanSat has met the precision design requirement, with an average bias of 2.11 ppm. The first scientific observations are presented, namely, the seasonal distributions of XCO2 over land on a global scale.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19070204)
文摘Accurate monitoring of changes in atmospheric carbon dioxide(C02)coneentration and carbon sinks/sources distribution are an important prerequisite for comprehensively understanding the global carbon cycle and correctly predicting future climate change.Satellite remote sensing is the only method to achieve this monitoring with high resolution.Although spaceborne hyperspectral remote sensing sensors have been successfully applied to monitor the concentration of C02 in the upper troposphere,they are not sensitive to changes in C02 concentrations near the Earth's surface.W让h the rapid development of sensor technology,quantitative remote sensing algorithms,satellites equipped with near-infrared and short-wave infrared hyperspectral sensors dedicated to C02 monitoring have been successively launched.
基金supported by the Strategic Priority Research Program- Climate Change: Carbon Budget and Relevant Issues (Grant No. XDA05040200)the National High-tech Research and Development Program of China (Grant No. 2011AA12A104)
文摘We present a study on the retrieval sensitivity of the column-averaged dry-air mole fraction of CO2(XCO2) for the Chinese carbon dioxide observation satellite(TanSat) with a full physical forward model and the optimal estimation technique. The forward model is based on the vector linearized discrete ordinate radiative transfer model(VLIDORT) and considers surface reflectance, gas absorption, and the scattering of air molecules, aerosol particles, and cloud particles. XCO2 retrieval errors from synthetic TanSat measurements show solar zenith angle(SZA), albedo dependence with values varying from 0.3 to 1 ppm for bright land surface in nadir mode and 2 to 8 ppm for dark surfaces like snow. The use of glint mode over dark oceans significantly improves the CO2 information retrieved. The aerosol type and profile are more important than the aerosol optical depth, and underestimation of aerosol plume height will introduce a bias of 1.5 ppm in XCO2. The systematic errors due to radiometric calibration are also estimated using a forward model simulation approach.
基金supported by the Strategic Priority Research Program-Climate Change:Carbon Budget and Relevant Issues (XDA05040200)the National High-tech R&D Program (2011AA12A104)
文摘This study developed a highly accurate retrieval algorithm for the column-averaged CO2 dry-air mixing ratio (XCO2) to be observed by TanSat, China's carbon dioxide observation satellite that will be launched in 2015. The Greenhouse Gases Observing Satellite (GOSAT) L1B spectrum was applied in retrieval experiment, and the results were validated with ground-observed measurements from the Total Column Carbon Observing Network (TCCON). At mid-latitudes, most results fell in the 1% error region, which correspond to the performance of GOSAT algorithm. The results also showed seasonal variation in XCO2 in both hemispheres.
基金supported by the Strategic Priority Research Program-Climate Change: Carbon Budget and Relevant Issues (XDA05040200)the National High-tech R&D Program of China (2011AA12A104)the National Natural Science Foundation of China (41205018)
文摘The spectral sampling rate and range of CO2absorption bands are critical for the optimal design of hyperspectral instrument for CO2observation satellite.Undersampling of spectra in space-based spectrometer significantly contaminates signals measured in the CO21.61 lm-band.The CO2dry-air column(XCO2)error due to spectral undersampling can be up to*1 ppm,which is the target precision of the Chinese Carbon Satellite(TanSat)for a single sounding.Undersampling error depends on surface albedo,solar zenith angle,and scattering properties in the atmosphere.The spectral sampling rate is recommended to be greater than 2.0 pixels per full width at half maximum to avoid undersampling.Reduction of spectral resolution and the use of narrower spectral regions can improve spectral sampling with little changes in CO2retrieval sensitivity without losing much information.The full-band approach provides direct constraints on the wavelength-dependent surface albedo and particle scattering from the measurements.To keep a broader band,we recommend reduction of the spectral resolution by a factor of two.
