温室气体的卫星遥感—进展与趋势
Satellite remote sensing of greenhouse gases: Progress and trends
- 2021年25卷第1期 页码:53-64
纸质出版日期: 2021-01-07
DOI: 10.11834/jrs.20210081
扫 描 看 全 文
浏览全部资源
扫码关注微信
纸质出版日期: 2021-01-07 ,
扫 描 看 全 文
刘毅,王婧,车轲,蔡兆男,杨东旭,吴林.2021.温室气体的卫星遥感—进展与趋势.遥感学报,25(1): 53-64
Liu Y,Wang J,Che K,Cai Z N,Yang D X and Wu L. 2021. Satellite remote sensing of greenhouse gases: Progress and trends. National Remote Sensing Bulletin, 25(1):53-64
二氧化碳和甲烷减排是控制全球增温最核心的手段,传统的人为碳排放计算主要依赖于在线监测和清单算法,2019年第49届IPCC全会明确了利用大气观测通过“自上而下”通量计算对排放清单进行支撑和验证,因此了解大气遥感碳监测发展趋势以及同化反演技术方法成为了中国应对国际气候变化事务亟待探明的重要问题。根据卫星遥感技术发展进程和监测需求,将碳监测遥感的发展划分为3个阶段(1999年—2008年,2009年—2019年,2019年—),前两个阶段和第三阶段对应卫星分别为第一代和第二代温室气体监测卫星。本文在分析日本、美国、欧洲和中国第一代段碳监测卫星遥感探测技术发展进程的基础上,重点介绍了第二代卫星遥感探测技术的创新及其在探测精度、分辨率和覆盖率等方面提升。为了满足全球和区域人为碳排放监测的重大需求,需要优化反演算法提高精度、科学规划卫星的组网观测提升监测效率。同时也进一步阐述了如何依据组网观测的全球高精度、高时空分辨率的卫星数据,利用“自上而下”数据同化方法获得独立源汇信息来补充和验证清单。最后,指出了卫星高光谱遥感和新一代碳监测卫星的未来发展趋势及估算人为碳排放的潜力。
Reduction of greenhouse gas (GHG) (carbon dioxide (CO
2
) and methane (CH
4
)) emissions is a crucial way to mitigate global warming. Traditional estimation of anthropogenic carbon emissions mainly relies on inventory method and lacks independent validation data. The 49th IPCC plenary session (2019) proposed the use of “top-down” inversion with atmospheric observations to support and verify GHG emission inventories. The “top-down” method depends on atmospheric concentration observations
chemical transport models
and data assimilation algorithms. Global covered atmospheric concentration measurement with high accuracy and precision is a key element in better using the “top-down” method in global carbon flux investigation. Measurements from space provide global and regional datasets that improve the spatial coverage of existing in-situ networks. Understanding the development of spaceborned GHG monitoring techniques and “top-down” method has become an important issue in China’s response to international climate change affairs.
We divided the carbon monitoring remote sensing technology into three phases (1999—2008
2009—2019
2019—) based on the development process of satellite remote sensing technology and monitoring requirements. The corresponding satellites in the first two phases were called the first generation
and the corresponding satellites in the third phases were called the second generation. The first generation of GHG satellites was tested in many aspects
such as measurement principle
calibration
and validation. These processes were performed to improve the observation accuracy and the spatial and temporal resolutions of measurements. These efforts made continuous improvement on measurement accuracy and obtained approximately 10 years of scientific data and research results. The first generation of GHG monitoring satellites mainly focused on technical verification and scientific target exploration flying a polar-orbit and onboarded passive remote sensing instrument with narrow swath
mainly aiming to obtain high-precision remote sensing data. The first generation laid the foundation
and the second generation entered the decade of rapid development and application from 2019 to 2028. The second generation of GHG monitoring satellites mainly aimed to improve the spatial and temporal resolutions of observations
such as increasing the swath and observation data in the cross-orbit direction (≥200 km) or using geostationary orbit to increase the observation frequency and data coverage
thereby greatly improving the observation efficiency. Active laser detectors can be used to obtain profile data with high accuracy (0.5 PPM)
which are unaffected by sunlight.
Optimizing the retrieval algorithm to improve the accuracy and scientifically planning the operational constellations of satellites to improve the monitoring efficiency are necessary. These processes are required to meet the major demand of global and regional monitoring of anthropogenic carbon emissions. Furthermore
the verification of the inventory algorithm is introduced by using the “top-down” data assimilation method with high precision
high spatial and temporal resolution measurements of the satellite constellations. The future development trend of hyperspectral remote sensing and new generation of carbon monitoring satellites and the potential of estimating anthropogenic carbon emissions are provided.
卫星遥感温室气体碳源汇MRV卫星组网
carbon monitoring satellitesgreenhouse gasescarbon source and sinkMRVsatellites virtual constellation
Basu S, Guerlet S, Butz A, Houweling S, Hasekamp O, Aben I, Krummel P, Steele P, Langenfelds R, Torn M, Biraud S, Stephens B, Andrews A and Worthy D. 2013. Global CO2 fluxes estimated from GOSAT retrievals of total column CO2. Atmospheric Chemistry and Physics, 13(17): 8695-8717 [DOI: 10.5194/acp-13-8695-2013http://dx.doi.org/10.5194/acp-13-8695-2013]
Bertaux J L, Hauchecorne A, Lefèvre F, Breon F M, Blanot L, Jouglet D, Lafrique P and Akaev P. 2019. The use of O2 1.27 µm absorption band revisited for GHG monitoring from space and application to MicroCarb. Atmospheric Measurement Techniques Discussion [DOI: 10.5194/amt-2019-54http://dx.doi.org/10.5194/amt-2019-54]
Boesch H, Baker D, Connor B, Crisp D and Miller C. 2011. Global characterization of CO2 column retrievals from shortwave-infrared satellite observations of the Orbiting Carbon Observatory-2 mission. Remote Sensing, 3(2): 270-304 [DOI: 10.3390/rs30 20270http://dx.doi.org/10.3390/rs3020270]
Buchwitz M, Schneising O, Reuter M, Heymann J, Krautwurst S, Bovensmann H, Burrows J P, Boesch H, Parker R J, Somkuti P, Detmers R G, Hasekamp O P, Aben I, Butz A, Frankenberg C and Turner A J. 2017. Satellite-derived methane hotspot emission estimates using a fast data-driven method. Atmospheric Chemistry and Physics, 17(9): 5751-5774 [DOI: 10.5194/acp-17-5751-2017http://dx.doi.org/10.5194/acp-17-5751-2017]
Cai B F, Zhu S L, Yu S M, Dong H M, Zhang C Y, Wang C K, Zhu J H, Gao Q X, Fang S X, Pan X B and Zheng X H. 2019. The interpretation of 2019 refinement to the 2016 IPCC guidelines for national greenhouse gas inventory. Environmental Engineering, 37(8): 1-11
蔡博峰, 朱松丽, 于胜民, 董红敏, 张称意, 王长科, 朱建华, 高庆先, 方双喜, 潘学标, 郑循华. 2019. 《IPCC 2006年国家温室气体清单指南2019修订版》解读. 环境工程, 37(8): 1-11 [DOI: 10.13205/j.hjgc.201908001http://dx.doi.org/10.13205/j.hjgc.201908001]
Chen L F, Zhang Y, Zou M M, Xu Q, Li L J, Li X Y and Tao J H. 2015. Overview of atmospheric CO2 remote sensing from space. Journal of Remote Sensing, 19(1): 1-11
陈良富, 张莹, 邹铭敏, 徐谦, 李令军, 李小英, 陶金花. 2015. 大气CO2浓度卫星遥感进展. 遥感学报, 19(1): 1-11 [DOI: 10.11834/jrs.20153331http://dx.doi.org/10.11834/jrs.20153331]
Chen Y D, Cai W J and Wang C. 2018. The characteristics of Intended Nationally Determined Contributions. Climate Change Research, 14(3): 295-302
陈艺丹, 蔡闻佳, 王灿. 2018. 国家自主决定贡献的特征研究. 气候变化研究进展, 14(3): 295-302 [DOI: 10.12006/j.issn.1673-1719.2017.124http://dx.doi.org/10.12006/j.issn.1673-1719.2017.124]
Chevallier F, Ciais P, Conway T J, Aalto T, Anderson B E, Bousquet P, Brunke E G, Ciattaglia L, Esaki Y, Fröhlich M, Gomez A, Gomez-Pelaez A J, Haszpra L, Krummel P B, Langenfelds R L, Leuenberger M, Machida T, Maignan F, Matsueda H, Morguí J A, Mukai H, Nakazawa T, Peylin P, Ramonet M, Rivier L, Sawa Y, Schmidt M, Steele L P, Vay S A, Vermeulen A T, Wofsy S and Worthy D. 2010. CO2 surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements. Journal of Geophysical Research: Atmospheres, 115(D21): D21307 [DOI: 10.1029/2010JD013887http://dx.doi.org/10.1029/2010JD013887]
Chevallier F, Palmer P I, Feng L, Boesch H, O’Dell C W and Bousquet P. 2014. Toward robust and consistent regional CO2 flux estimates from in situand spaceborne measurements of atmospheric CO2. Geophysical Research Letters, 41(3): 1065-1070 [DOI: 10.1002/2013GL058772http://dx.doi.org/10.1002/2013GL058772]
Conley S, Franco G, Faloona I, Blake D R, Peischl J and Ryerson T B. 2016. Methane emissions from the 2015 Aliso Canyon blowout in Los Angeles, CA. Science, 351(6279): 1317-1320 [DOI: 10.1126/science.aaf2348http://dx.doi.org/10.1126/science.aaf2348]
Crisp D. 2015. Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2)//Proceedings Volume 9607, Earth Observing Systems XX. San Diego, California, United States: SPIE: 960702 [DOI: 10.1117/12.2187291http://dx.doi.org/10.1117/12.2187291]
Crisp D, Fisher B M, O'Dell C, Frankenberg C, Basilio R, Bösch H, Brown L R, Castano R, Connor B, Deutscher N M, Eldering A, Griffith D, Gunson M, Kuze A, Mandrake L, McDuffie J, Messerschmidt J, Miller C E, Morino I, Natraj V, Notholt J, O’Brien D M, Oyafuso F, Polonsky I, Robinson J, Salawitch R, Sherlock V, Smyth M, Suto H, Taylor T E, Thompson D R, Wennberg P O, Wunch D and Yung Y L. 2012. The ACOS CO2 retrieval algorithm-Part II: global <math id="M5"><msub><mrow><mi mathvariant="normal">X</mi></mrow><mrow><mi mathvariant="normal">C</mi><msub><mrow><mi mathvariant="normal">O</mi></mrow><mrow><mn mathvariant="normal">2</mn></mrow></msub></mrow></msub></math>http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226731&type=http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226727&type=4.995333673.55599999 data characterization. Atmospheric Measurement Techniques, 5(4): 687-707 [DOI: 10.5194/amt-5-687-2012http://dx.doi.org/10.5194/amt-5-687-2012]
Crisp D, Pollock H R, Rosenberg R, Chapsky L, Lee R A M, Oyafuso F A, Frankenberg C, O’Dell C W, Bruegge C J, Doran G B, Eldering A, Fisher B M, Fu D J, Gunson M R, Mandrake L, Osterman G B, Schwandner F M, Sun K, Taylor T E, Wennberg P O and Wunch D. 2017. The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products. Atmospheric Measurement Techniques, 10(1): 59-81 [DOI: 10.5194/amt-10-59-2017http://dx.doi.org/10.5194/amt-10-59-2017]
Deng F, Jones D B A, Henze D K, Bousserez N, Bowman K W, Fisher J B, Nassar R, O’Dell C, Wunch D, Wennberg P O, Kort E A, Wofsy S C, Blumenstock T, Deutscher N M, Griffith D W T, Hase F, Heikkinen P, Sherlock V, Strong K, Sussmann R and Warneke T. 2013. Inferring regional sources and sinks of atmospheric CO2 from GOSAT XCO2 data. Atmospheric Chemistry and Physics, 14(7): 3703-3727 [DOI: 10.5194/acp-14-3703-2014http://dx.doi.org/10.5194/acp-14-3703-2014]
Dupuy E, Morino I, Deutscher N M, Yoshida Y, Uchino O, Connor B J, De Mazière M, Griffith D W T, Hase F, Heikkinen P, Hillyard P W, Iraci L T, Kawakami S, Kivi R, Matsunaga T, Notholt J, Petri C, Podolske J R, Pollard D F, Rettinger M, Roehl C M, Sherlock V, Sussmann R, Toon G C, Velazco V A, Warneke T, Wennberg P O, Wunch D, Yokota T. 2016. Comparison of XH2O retrieved from GOSAT short-wavelength infrared spectra with observations from the TCCON network. Remote Sensing, 8(5): 414 [DOI: 10.3390/rs8050414http://dx.doi.org/10.3390/rs8050414]
Ehret G, Bousquet P, Pierangelo C, Alpers M, Millet B, Abshire J B, Bovensmann H, Burrows J P, Chevallier F, Ciais P, Crevoisier C, Fix A, Flamant P, Frankenberg C, Gibert F, Heim B, Heimann M, Houweling S, Hubberten H W, Jöckel P, Law K, Löw A, Marshall J, Agusti-Panareda A, Payan S, Prigent C, Rairoux P, Sachs T, Scholze M and Wirth M. 2017. MERLIN: a French-German space Lidar mission dedicated to atmospheric methane. Remote Sensing, 9(10): 1052 [DOI: 10.3390/rs9101052http://dx.doi.org/10.3390/rs9101052]
Eldering A, Taylor T E, O’Dell C W and Pavlick R. 2019. The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data. Atmospheric Measurement Techniques, 12(4): 2341-2370 [DOI: 10.5194/amt-12-2341-2019http://dx.doi.org/10.5194/amt-12-2341-2019]
Eldering A, Wennberg P O, Crisp D, Schimel D S, Gunson M R, Chatterjee A, Liu J, Schwandner F M, Sun Y, O’Dell C W, Frankenberg C, Taylor T, Fisher B, Osterman G B, Wunch D, Hakkarainen J, Tamminen J and Weir B. 2017. The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes. Science, 358(6360):
eaam5745 [DOI: 10.1126/science.aa m5745http://dx.doi.org/10.1126/science.aam5745]
Feng L, Palmer P I, Deutscher N M, Feist D G, Kivi R, Morino I and Sussmann R. 2016. Estimates of European uptake of CO2 inferred from GOSAT <math id="M6"><msub><mrow><mi mathvariant="normal">X</mi></mrow><mrow><mi mathvariant="normal">C</mi><msub><mrow><mi mathvariant="normal">O</mi></mrow><mrow><mn mathvariant="normal">2</mn></mrow></msub></mrow></msub></math>http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226736&type=http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226734&type=4.995333673.55599999 retrievals: sensitivity to measurement bias inside and outside Europe. Atmospheric Chemistry and Physics, 16(3): 1289-1302 [DOI: 10.5194/acp-16-1289-2016http://dx.doi.org/10.5194/acp-16-1289-2016]
Han G, Xu H, Gong W, Liu J Q, Du J, Ma X and Liang A L. 2018. Feasibility study on measuring atmospheric CO2 in urban areas using spaceborne CO2-IPDA LIDAR. Remote Sensing, 10(7): 985 [DOI: 10.3390/rs10070985http://dx.doi.org/10.3390/rs10070985]
Hedelius J K, Feng S, Roehl C M, Wunch D, Hillyard P W, Podolske J R, Iraci L T, Patarasuk R, Rao P, O’Keefe D, Gurney K R, Lauvaux T and Wennberg P O. 2017. Emissions and topographic effects on column CO2(<math id="M7"><msub><mrow><mi mathvariant="normal">X</mi></mrow><mrow><mi mathvariant="normal">C</mi><msub><mrow><mi mathvariant="normal">O</mi></mrow><mrow><mn mathvariant="normal">2</mn></mrow></msub></mrow></msub></math>http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226741&type=http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226740&type=4.995333673.55599999) variations, with a focus on the Southern California Megacity. Journal of Geophysical Research: Atmospheres, 122(13): 7200-7215 [DOI: 10.1002/2017JD026455http://dx.doi.org/10.1002/2017JD026455]
IPCC. 2019. 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventoryies. Switzerland: IPCC
Lauvaux T, Miles N L, Deng A J, Richardson S J, Cambaliza M O, Davis K J, Gaudet B J, Gurney K R, Huang J H, O’Keefe D, Song Y, Karion A, Oda T, Patarasuk R, Razlivanov I, Sarmiento D, Shepson P, Sweeney C, Turnbull J and Wu K. 2016. High-resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX). Journal of Geophysical Research: Atmospheres, 121(10): 5213-5236 [DOI: 10.1002/2015JD024473http://dx.doi.org/10.1002/2015JD024473]
Liu D, Zheng Z F, Chen W B, Wang Z B, Li W J, Ke J, Zhang Y P, Chen S J, Cheng C H and Wang S B. 2019. Performance estimation of space-borne high-spectral-resolution Lidar for cloud and aerosol optical properties at 532 nm. Optics Express, 27(8): A481-A494 [DOI: 10.1364/OE.27.00A481http://dx.doi.org/10.1364/OE.27.00A481]
Liu J J and Bowman K. 2016. A method for independent validation of surface fluxes from atmospheric inversion: application to CO2. Geophysical Research Letters, 43(7): 3502-3508 [DOI: 10.1002/2016GL067828http://dx.doi.org/10.1002/2016GL067828]
Liu J J, Bowman K W, Schimel D S, Parazoo N C, Jiang Z, Lee M, Bloom A, Wunch D, Frankenberg C, Sun Y, O’Dell C W, Gurney K R, Menemenlis D, Gierach M, Crisp D and Eldering A. 2017. Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Niño. Science, 358(6360):
eaam5690 [DOI: 10.1126/science.aam5690http://dx.doi.org/10.1126/science.aam5690]
Liu Y, Wang J, Yao L, Chen X, Cai Z N, Yang D X, Yin Z S, Gu S Y, Tian L F, Lu N M and Lyu D. 2018. The TanSat mission: preliminary global observations. Science Bulletin, 63(18): 1200-1207 [DOI: 10.1016/j.scib.2018.08.004http://dx.doi.org/10.1016/j.scib.2018.08.004]
Liu Y, Yang D X and Cai Z N. 2013. A retrieval algorithm for Tansat XCO2 observation: retrieval experiments using GOSAT data. Chinese Science Bulletin, 58(13): 1520-1523 [DOI: 10.1007/s11434-013-5680-yhttp://dx.doi.org/10.1007/s11434-013-5680-y]
Lu F. 2017. Recent development and plans in CMA, expert team on satellite systems (ET-SAT) 11th SESSION, 4-6 April 2017, WMO Headquarters, Geneva, Switzerland, 2017. http://www.wmo.int/pages/prog/sat/meetings/ET-SAT-11/ET-SAT-11.htmlhttp://www.wmo.int/pages/prog/sat/meetings/ET-SAT-11/ET-SAT-11.html
Nakajima M, Suto H, Yotsumoto K, Shiomi K and Hirabayashi T. 2017. Fourier transform spectrometer on GOSAT and GOSAT-2//Proceedings Volume 10563, International Conference on Space Optics—ICSO 2014. Tenerife, Canary Islands, Spain: SPIE: 2014: 105634O [DOI: 10.1117/12.2304062http://dx.doi.org/10.1117/12.2304062]
Nassar R, Hill T G, McLinden C A, Wunch D, Jones D B A and Crisp D. 2017. Quantifying CO2 emissions from individual power plants from space. Geophysical Research Letters, 44(19): 10045-10053 [DOI: 10.1002/2017GL074702http://dx.doi.org/10.1002/2017GL074702]
O’Brien D M, Polonsky I N, Utembe S R and Rayner P J. 2016. Potential of a geostationary geoCARB mission to estimate surface emissions of CO2, CH4 and CO in a polluted urban environment: case study Shanghai. Atmospheric Measurement Techniques, 9(9): 4633-4654 [DOI: 10.5194/amt-9-4633-2016http://dx.doi.org/10.5194/amt-9-4633-2016]
O’Dell C W, Connor B, Bösch H, O’Brien D, Frankenberg C, Castano R, Christi M, Eldering D, Fisher B, Gunson M, McDuffie J, Miller C E, Natraj V, Oyafuso F, Polonsky I, Smyth M, Taylor T, Toon G C, Wennberg P O and Wunch D. 2012. The ACOS CO2 retrieval algorithm-Part 1: description and validation against synthetic observations. Atmospheric Measurement Techniques, 5(1): 99-121 [DOI: 10.5194/amt-5-99-2012http://dx.doi.org/10.5194/amt-5-99-2012]
O’Dell C W, Eldering A, Wennberg P O, Crisp D, Gunson M R, Fisher B, Frankenberg C, Kiel M, Lindqvist H, Mandrake L, Merrelli A, Natraj V, Nelson R R, Osterman G B, Payne V H, Taylor T E, Wunch D, Drouin B J, Oyafuso F, Chang A, McDuffie J, Smyth M, Baker D F, Basu S, Chevallier F, Crowell S M R, Feng L, Palmer P I, Dubey M, García O E, Griffith D W T, Hase F, Iraci L T, Kivi, R, Morino I, Notholt J, Ohyama H, Petri C, Roehl C M, Sha M K, Strong K, Sussmann R, Te Y, Uchino O and Velazco V A. 2018. Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm. Atmospheric Measurement Techniques, 11(12): 6539-6576 [DOI: 10.5194/amt-11-6539-2018http://dx.doi.org/10.5194/amt-11-6539-2018]
Palmer P I, Feng L, Baker D, Chevallier F, Bösch H and Somkuti P. 2019. Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal. Nature Communications, 10(1): 3344 [DOI: 10.1038/s41467-019-11097-whttp://dx.doi.org/10.1038/s41467-019-11097-w]
Parker R J, Boesch H, Byckling K, Webb A J, Palmer P I, Feng L, Bergamaschi P, Chevallier F, Notholt J, Deutscher N, Warneke T, Hase F, Sussmann R, Kawakami S, Kivi R, Griffith D W T and Velazco V. 2015. Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties. Atmospheric Measurement Techniques, 8(11): 4785-4801 [DOI: 10.5194/amt-8-4785-2015http://dx.doi.org/10.5194/amt-8-4785-2015]
Peylin P, Law R M, Gurney K R, Chevallier F, Jacobson A R, Maki T, Niwa Y, Patra P K, Peters W, Rayner P J, Rödenbeck C, van der Laan-Luijkx I T and Zhang X. 2013. Global atmospheric carbon budget: results from an ensemble of atmospheric CO2 inversions. Biogeosciences, 10(10): 6699-6720 [DOI: 10.5194/bg-10-6699-2013http://dx.doi.org/10.5194/bg-10-6699-2013]
Phil DeCola and WMO Secretariat. 2017. An integrated global greenhouse gas information system (IG3IS)[EB/OL].https://public.wmo.int/en/resources/bulletin/integrated-global-greenhouse-gas-information-system-ig3ishttps://public.wmo.int/en/resources/bulletin/integrated-global-greenhouse-gas-information-system-ig3is
Reuter M, Buchwitz M, Schneising O, Krautwurst S, O’Dell C W, Richter A, Bovensmann H and Burrows J P. 2019. Towards monitoring localized CO2 emissions from space: co-located regional CO2 and NO2 enhancements observed by the OCO-2 and S5P satellites. Atmospheric Chemistry and Physics, 19(14): 9371-9383 [DOI: 10.5194/acp-19-9371-2019http://dx.doi.org/10.5194/acp-19-9371-2019]
Saeki T, Maksyutov S, Saito M, Valsala V, Oda T, Andres R J, Belikov D, Tans P, Dlugokencky E, Yoshida Y, Morino I, Uchino O and Yokota T. 2013. Inverse modeling of CO2 fluxes using GOSAT data and multi-year ground-based observations. SOLA, 9: 45-50 [DOI: 10.2151/sola.2013-011http://dx.doi.org/10.2151/sola.2013-011]
Thompson R L, Patra P, Chevallier F, Maksyutov S, Law R M, Ziehn T, van der Laan-Luijkx I T, Peters W, Ganshin A, Zhuravlev R, Maki T, Nakamura T, Shirai T, Ishizawa M, Saeki T, Machida T, Poulter B, Canadell J G and Ciais P. 2016. Top-down assessment of the Asian carbon budget since the mid 1990s. Nature Communications, 7: 10724 [DOI: 10.1038/ncomms10724http://dx.doi.org/10.1038/ncomms10724]
Wang J, Feng L, Palmer P I, Liu Y, Fang S X, Bosch H, O’Dell C W, Tang X P, Yang D X, Liu L X, Xia C Z. Large Chinese land carbon sink estimated from atmospheric carbon dioxide data[J].Nature, 2020, 586:720-723 [DOI: 10.1038/s41586-020-2849-9].
Wu L H, Hasekamp O, Hu H L, Landgraf J, Butz A, ann de Brugh J, Aben I, Pollard D F, Griffith D W T, Feist D G, Koshelev D, Hase F, Toon G C, Ohyama H, Morino I, Notholt J, Shiomi K, Iraci L, Schneider M, de Mazière M, Sussmann R, Kivi R, Warneke T, Goo T Y and Té Y. 2018. Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements. Atmospheric Measurement Techniques, 11(5): 3111-3130 [DOI: 10.5194/amt-11-3111-2018http://dx.doi.org/10.5194/amt-11-3111-2018]
Wunch D, Wennberg P O, Osterman G, Fisher B, Naylor B, Roehl C M, O’Dell C, Mandrake L, Viatte C, Kiel M, Griffith D W T, Deutscher N M, Velazco V A, Notholt J, Warneke T, Petri C, De Maziere M, Sha M K, Sussmann R, Rettinger M, Pollard D, Robinson J, Morino I, Uchino O, Hase F, Blumenstock T, Feist D G, Arnold S G, Strong K, Mendonca J, Kivi R, Heikkinen P, Iraci L, Podolske J, Hillyard P W, Kawakami S, Dubey M K, Parker H A, Sepulveda E, García O E, Te Y, Jeseck P, Gunson M R, Crisp D and Eldering A. 2017. Comparisons of the Orbiting Carbon Observatory-2 (OCO-2)<math id="M8"><msub><mrow><mi mathvariant="normal">X</mi></mrow><mrow><mi mathvariant="normal">C</mi><msub><mrow><mi mathvariant="normal">O</mi></mrow><mrow><mn mathvariant="normal">2</mn></mrow></msub></mrow></msub></math>http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226745&type=http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=20226743&type=4.995333673.55599999 measurements with TCCON. Atmospheric Measurement Techniques, 10(6): 2209-2238 [DOI: 10.5194/amt-10-2209-2017http://dx.doi.org/10.5194/amt-10-2209-2017]
Xiong W. 2019. Greenhouse gases Monitoring Instrument (GMI) on GF-5 satellite (invited). Infrared and Laser Engineering, 48(3): 0303002
熊伟. 2019. “高分五号”卫星大气主要温室气体监测仪(特邀). 红外与激光工程, 48(3): 0303002 [DOI: 10.3788/IRLA201948.0303002http://dx.doi.org/10.3788/IRLA201948.0303002]
Yang D, Boesch H, Liu Y, Somkuti P, Cai Z, Chen X, Di Noia A, Lin C, Lu N, Lyu D, Parker R J, Tian L, Wang M, Webb A, Yao L, Yin Z, Zheng Y, Deutscher N M, Griffith D W T, Hase F, Kivi R, Morino I, Notholt J, Ohyama H, Pollard D F, Shiomi K, Sussmann R, Té Y, Velazco V A, Warneke T and Wunch D. 2020. Toward high precision XCO2 retrievals from TanSat observations: retrieval improvement and validation against TCCON measurements. Journal of Geophysical Research: Atmospheres, 125(22): e2020JD032794 [DOI: 10.1029/2020JD032794http://dx.doi.org/10.1029/2020JD032794]
Yang D X, Liu Y, Cai Z N, Chen X, Yao L and Lu D. 2018. First global carbon dioxide maps produced from Tansat measurements. Advances in Atmospheric Sciences, 35(6): 621-623 [DOI: 10.1007/s00376-018-7312-6http://dx.doi.org/10.1007/s00376-018-7312-6]
Yang D X, Liu Y, Cai Z N, Deng J B, Wang J and Chen X. 2015. An advanced carbon dioxide retrieval algorithm for satellite measurements and its application to GOSAT observations. Science Bulletin, 60(23): 2063-2066 [DOI: 10.1007/s11434-015-0953-2http://dx.doi.org/10.1007/s11434-015-0953-2]
Ye S, Fang Y H, Hong J, Qiao Y L and Xiong W. 2007. Experimental study on spatial heterodyne spectroscopy. Opto-Electronic Engineering, 34(5): 84-88
叶松, 方勇华, 洪津, 乔延利, 熊伟. 2007. 空间外差光谱技术实验研究. 光电工程, 34(5): 84-88 [DOI: 10.3969/j.issn.1003-501X.2007.05.019http://dx.doi.org/10.3969/j.issn.1003-501X.2007.05.019]
Yoshida Y, Kikuchi N, Morino I, Uchino O, Oshchepkov S, Bril A, Saeki T, Schutgens N, Toon G C, Wunch D, Roehl C M, Wennberg P O, Griffith D W T, Deutscher N M, Warneke T, Notholt J, Robinson J, Sherlock V, Connor B, Rettinger M, Sussmann R, Ahonen P, Heikkinen P, Kyrö E, Mendonca J, Strong K, Hase F, Dohe S and Yokota T. 2013. Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data. Atmospheric Measurement Techniques, 6(6): 1533-1547 [DOI: 10.5194/amt-6-1533-2013http://dx.doi.org/10.5194/amt-6-1533-2013]
相关作者
相关机构