Anthropogenic CO2 monitoring satellite mission: the need for multi-angle polarimetric observations

Atmospheric aerosols have been known to be a major source of uncertainties in CO2 concentrations retrieved from space. In this study, we investigate the added value of multi-angle polarimeter (MAP) measurements in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. To this end, we compare aerosolinduced XCO2 errors from standard retrievals using a spectrometer only (without MAP) with those from retrievals using both MAP and a spectrometer. MAP observations are expected to provide information about aerosols that is useful for improving XCO2 accuracy. For the purpose of this work, we generate synthetic measurements for different atmospheric and geophysical scenes over land, based on which XCO2 retrieval errors are assessed. We show that the standard XCO2 retrieval approach that makes no use of auxiliary aerosol observations returns XCO2 errors with an overall bias of 1.12 ppm and a spread (defined as half of the 15.9–84.1 percentile range) of 2.07 ppm. The latter is far higher than the required XCO2 accuracy (0.5 ppm) and precision (0.7 ppm) of the CO2M mission. Moreover, these XCO2 errors exhibit a significantly larger bias and scatter at high aerosol optical depth, high aerosol altitude, and low solar zenith angle, which could lead to worse performance in retrieving XCO2 from polluted areas where CO2 and aerosols are co-emitted. We proceed to determine MAP instrument specifications in terms of wavelength range, number of viewing angles, and measurement uncertainties that are required to achieve XCO2 accuracy and precision targets of the mission. Two different MAP instrument concepts are considered in this analysis. We find that for either concept, MAP measurement uncertainties on radiance and degree of linear polarization should be no more than 3 % and 0.003, respectively. A retrieval exercise using MAP and spectrometer measurements of the synthetic scenes is carried out for each of the two MAP concepts. The resulting XCO2 errors have an overall bias of −0.004 ppm and a spread of 0.54 ppm for one concept, and a bias of 0.02 ppm and a spread of 0.52 ppm for the other concept. Both are compliant with the CO2M mission requirements; the very low bias is especially important for proper emission estimates. For the test ensemble, we find effectively no dependence of the XCO2 errors on aerosol optical depth, altitude of the aerosol layer, and solar zenith angle. These results indicate a major improvement in the retrieved XCO2 accuracy with respect to the standard retrieval approach, which could lead to a higher data yield, better global coverage, and a more comprehensive determination of CO2 sinks and sources. As such, this outcome underlines the contribution of, and therefore the need for, a MAP instrument aboard the CO2M mission.

[1]  Hartmut Boesch,et al.  Impact of Aerosol Property on the Accuracy of a CO2 Retrieval Algorithm from Satellite Remote Sensing , 2016, Remote. Sens..

[2]  O. P. Hasekamp,et al.  A linearized vector radiative transfer model for atmospheric trace gas retrieval , 2002 .

[3]  Ilse Aben,et al.  Evidence of systematic errors in SCIAMACHY-observed CO 2 due to aerosols , 2005 .

[4]  F. Bréon,et al.  Remote sensing of aerosols by using polarized, directional and spectral measurements within the A-Train: the PARASOL mission , 2011 .

[5]  Gang Li,et al.  The HITRAN 2008 molecular spectroscopic database , 2005 .

[6]  R. DeFries,et al.  Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system , 2013 .

[7]  Rebecca Castano,et al.  A method for evaluating bias in global measurements of CO 2 total columns from space , 2011 .

[8]  A. Lacis,et al.  Aerosol retrievals over the ocean by use of channels 1 and 2 AVHRR data: sensitivity analysis and preliminary results. , 1999, Applied optics.

[9]  Tatsuya Yokota,et al.  Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra , 2010 .

[10]  Otto P. Hasekamp,et al.  Linearization of vector radiative transfer with respect to aerosol properties and its use in satellite remote sensing , 2005 .

[11]  Ilse Aben,et al.  Retrievals of atmospheric CO2 from simulated space-borne measurements of backscattered near-infrared sunlight: accounting for aerosol effects. , 2009, Applied optics.

[12]  Christoph U. Keller,et al.  Accurate spectrally modulating polarimeters for atmospheric aerosol characterization , 2015, SPIE Optical Engineering + Applications.

[13]  O. Hasekamp,et al.  XCO2 observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements , 2019, Atmospheric Measurement Techniques.

[14]  Jean-Michel Hartmann,et al.  Line mixing and collision-induced absorption by oxygen in the A band: Laboratory measurements, model, and tools for atmospheric spectra computations , 2006 .

[15]  A. Strahler,et al.  On the derivation of kernels for kernel‐driven models of bidirectional reflectance , 1995 .

[16]  Akihiko Kuze,et al.  Toward accurate CO2 and CH4 observations from GOSAT , 2011 .

[17]  Pavel Litvinov,et al.  Models for surface reflection of radiance and polarized radiance: Comparison with airborne multi-angle photopolarimetric measurements and implications for modeling top-of-atmosphere measurements , 2011 .

[18]  Tatsuya Yokota,et al.  PPDF‐based method to account for atmospheric light scattering in observations of carbon dioxide from space , 2008 .

[19]  O. Hasekamp,et al.  Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm , 2020 .

[20]  A. Bucholtz,et al.  Rayleigh-scattering calculations for the terrestrial atmosphere. , 1995, Applied optics.

[21]  Dominik Brunner,et al.  Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission , 2019 .

[22]  Otto P. Hasekamp,et al.  Aerosol measurements by SPEXone on the NASA PACE mission: expected retrieval capabilities , 2019, Journal of Quantitative Spectroscopy and Radiative Transfer.

[23]  Otto Hasekamp,et al.  Retrieval of aerosol microphysical and optical properties over land using a multimode approach , 2018, Atmospheric Measurement Techniques.

[24]  Maximilian Reuter,et al.  A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2 , 2017, Remote. Sens..

[25]  Ilse Aben,et al.  CH4 retrievals from space‐based solar backscatter measurements: Performance evaluation against simulated aerosol and cirrus loaded scenes , 2010 .

[26]  David L. Phillips,et al.  A Technique for the Numerical Solution of Certain Integral Equations of the First Kind , 1962, JACM.

[27]  Michael J. Garay,et al.  Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA , 2018, Journal of Applied Remote Sensing.

[28]  Ruediger Lang,et al.  The multi-viewing multi-channel multi-polarisation imager – Overview of the 3MI polarimetric mission for aerosol and cloud characterization , 2018, Journal of Quantitative Spectroscopy and Radiative Transfer.

[29]  C. O’Dell,et al.  The impact of improved aerosol priors on near-infrared measurements of carbon dioxide , 2019, Atmospheric Measurement Techniques.

[30]  Otto P. Hasekamp,et al.  Efficient calculation of intensity and polarization spectra in vertically inhomogeneous scattering and absorbing atmospheres , 2008 .

[31]  Sonoyo Mukai,et al.  Polarimetric remote sensing of atmospheric aerosols: Instruments, methodologies, results, and perspectives , 2019, Journal of Quantitative Spectroscopy and Radiative Transfer.

[32]  Anthropogenic CO2 monitoring satellite mission: the need for multi-angle polarimetric observations , 2021 .

[33]  Haili Hu,et al.  The operational methane retrieval algorithm for TROPOMI , 2016 .

[34]  Jochen Landgraf,et al.  Retrieval of aerosol properties over land surfaces: capabilities of multiple-viewing-angle intensity and polarization measurements. , 2007, Applied optics.

[35]  Bernard Pinty,et al.  An operational anthropogenic CO2 emissions monitoring and verification support capacity. Baseline requirements, model components and functional architecture , 2017 .

[36]  Tatsuya Yokota,et al.  Impact of aerosol and thin cirrus on retrieving and validating XCO2 from GOSAT shortwave infrared measurements , 2013 .

[37]  Henrique M. J. Barbosa,et al.  The Harp Hype Ran Gular Imaging Polarimeter and the Need for Small Satellite Payloads with High Science Payoff for Earth Science Remote Sensing , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[38]  Annick Bricaud,et al.  The POLDER mission: instrument characteristics and scientific objectives , 1994, IEEE Trans. Geosci. Remote. Sens..

[39]  Fabienne Maignan,et al.  Polarized reflectances of natural surfaces: Spaceborne measurements and analytical modeling , 2009 .

[40]  Pavel Litvinov,et al.  Aerosol properties over the ocean from PARASOL multiangle photopolarimetric measurements , 2011 .

[41]  V. Malathy Devi,et al.  Spectroscopic challenges for high accuracy retrievals of atmospheric CO2 and the Orbiting Carbon Observatory (OCO) experiment , 2005 .

[42]  Brian Cairns,et al.  Aerosol retrieval from multiangle, multispectral photopolarimetric measurements: importance of spectral range and angular resolution , 2015, Atmospheric Measurement Techniques.

[43]  G. Toon,et al.  Spaceborne measurements of atmospheric CO2 by high‐resolution NIR spectrometry of reflected sunlight: An introductory study , 2002 .

[44]  Annmarie Eldering,et al.  Orbiting Carbon Observatory-3 (OCO-3), remote sensing from the International Space Station (ISS) , 2019, Remote Sensing.

[45]  B. Drouin,et al.  Spectroscopic uncertainty impacts on OCO-2/3 retrievals of XCO2 , 2020 .

[46]  Haili Hu,et al.  Full-physics carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite by only using the 2.06 µm band , 2019 .

[47]  Ilse Aben,et al.  TROPOMI aboard Sentinel-5 Precursor: Prospective performance of CH4 retrievals for aerosol and cirrus loaded atmospheres , 2012 .

[48]  Jean-François Léon,et al.  Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust , 2006 .

[49]  Ilse Aben,et al.  Uncertainties in the space-based measurements of CO2 columns due to scattering in the Earth's atmosphere , 2007 .

[50]  O. Hasekamp,et al.  XCO2 observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements , 2019, Atmospheric Measurement Techniques.

[51]  Brian Cairns,et al.  Passive remote sensing of aerosol layer height using near‐UV multiangle polarization measurements , 2016, Geophysical research letters.

[52]  Olga V. Kalashnikova,et al.  Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager , 2017 .

[53]  E. Shettle,et al.  Models for the aerosols of the lower atmosphere and the effects of humidity variations on their optical properties , 1979 .

[54]  Ilse Aben,et al.  Improved water vapour spectroscopy in the 4174-4300 cm-1 region and its impact on SCIAMACHY HDO/H2O measurements , 2012 .

[55]  C. Keller,et al.  Spectral modulation for full linear polarimetry. , 2009, Applied optics.

[56]  Christopher W. O'Dell,et al.  Aerosol information content analysis of multi-angle high spectral resolution measurements and its benefit for high accuracy greenhouse gas retrievals , 2012 .