Accounting for surface reflectance spectral features in TROPOMI methane retrievals

<p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p< Ausführliche Beschreibung

Gespeichert in:

Autor*in:	A. Lorente [verfasserIn] T. Borsdorff [verfasserIn] M. C. Martinez-Velarte [verfasserIn] J. Landgraf [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Übergeordnetes Werk:	In: Atmospheric Measurement Techniques - Copernicus Publications, 2009, 16(2023), Seite 1597-1608
Übergeordnetes Werk:	volume:16 ; year:2023 ; pages:1597-1608

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.5194/amt-16-1597-2023

Katalog-ID:	DOAJ087464063

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allfields	10.5194/amt-16-1597-2023 doi (DE-627)DOAJ087464063 (DE-599)DOAJ6e72616759074053a8686c5e4a51a05e DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 A. Lorente verfasserin aut Accounting for surface reflectance spectral features in TROPOMI methane retrievals 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p< Environmental engineering Earthwork. Foundations T. Borsdorff verfasserin aut M. C. Martinez-Velarte verfasserin aut J. Landgraf verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 16(2023), Seite 1597-1608 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:16 year:2023 pages:1597-1608 https://doi.org/10.5194/amt-16-1597-2023 kostenfrei https://doaj.org/article/6e72616759074053a8686c5e4a51a05e kostenfrei https://amt.copernicus.org/articles/16/1597/2023/amt-16-1597-2023.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1597-1608
spelling	10.5194/amt-16-1597-2023 doi (DE-627)DOAJ087464063 (DE-599)DOAJ6e72616759074053a8686c5e4a51a05e DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 A. Lorente verfasserin aut Accounting for surface reflectance spectral features in TROPOMI methane retrievals 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p< Environmental engineering Earthwork. Foundations T. Borsdorff verfasserin aut M. C. Martinez-Velarte verfasserin aut J. Landgraf verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 16(2023), Seite 1597-1608 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:16 year:2023 pages:1597-1608 https://doi.org/10.5194/amt-16-1597-2023 kostenfrei https://doaj.org/article/6e72616759074053a8686c5e4a51a05e kostenfrei https://amt.copernicus.org/articles/16/1597/2023/amt-16-1597-2023.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1597-1608
allfields_unstemmed	10.5194/amt-16-1597-2023 doi (DE-627)DOAJ087464063 (DE-599)DOAJ6e72616759074053a8686c5e4a51a05e DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 A. Lorente verfasserin aut Accounting for surface reflectance spectral features in TROPOMI methane retrievals 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p< Environmental engineering Earthwork. Foundations T. Borsdorff verfasserin aut M. C. Martinez-Velarte verfasserin aut J. Landgraf verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 16(2023), Seite 1597-1608 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:16 year:2023 pages:1597-1608 https://doi.org/10.5194/amt-16-1597-2023 kostenfrei https://doaj.org/article/6e72616759074053a8686c5e4a51a05e kostenfrei https://amt.copernicus.org/articles/16/1597/2023/amt-16-1597-2023.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1597-1608
allfieldsGer	10.5194/amt-16-1597-2023 doi (DE-627)DOAJ087464063 (DE-599)DOAJ6e72616759074053a8686c5e4a51a05e DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 A. Lorente verfasserin aut Accounting for surface reflectance spectral features in TROPOMI methane retrievals 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p< Environmental engineering Earthwork. Foundations T. Borsdorff verfasserin aut M. C. Martinez-Velarte verfasserin aut J. Landgraf verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 16(2023), Seite 1597-1608 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:16 year:2023 pages:1597-1608 https://doi.org/10.5194/amt-16-1597-2023 kostenfrei https://doaj.org/article/6e72616759074053a8686c5e4a51a05e kostenfrei https://amt.copernicus.org/articles/16/1597/2023/amt-16-1597-2023.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1597-1608
allfieldsSound	10.5194/amt-16-1597-2023 doi (DE-627)DOAJ087464063 (DE-599)DOAJ6e72616759074053a8686c5e4a51a05e DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 A. Lorente verfasserin aut Accounting for surface reflectance spectral features in TROPOMI methane retrievals 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p< Environmental engineering Earthwork. Foundations T. Borsdorff verfasserin aut M. C. Martinez-Velarte verfasserin aut J. Landgraf verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 16(2023), Seite 1597-1608 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:16 year:2023 pages:1597-1608 https://doi.org/10.5194/amt-16-1597-2023 kostenfrei https://doaj.org/article/6e72616759074053a8686c5e4a51a05e kostenfrei https://amt.copernicus.org/articles/16/1597/2023/amt-16-1597-2023.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1597-1608
language	English
source	In Atmospheric Measurement Techniques 16(2023), Seite 1597-1608 volume:16 year:2023 pages:1597-1608
sourceStr	In Atmospheric Measurement Techniques 16(2023), Seite 1597-1608 volume:16 year:2023 pages:1597-1608
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Environmental engineering Earthwork. Foundations
isfreeaccess_bool	true
container_title	Atmospheric Measurement Techniques
authorswithroles_txt_mv	A. Lorente @@aut@@ T. Borsdorff @@aut@@ M. C. Martinez-Velarte @@aut@@ J. Landgraf @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
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By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. 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author	A. Lorente
spellingShingle	A. Lorente misc TA170-171 misc TA715-787 misc Environmental engineering misc Earthwork. Foundations Accounting for surface reflectance spectral features in TROPOMI methane retrievals
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title	Accounting for surface reflectance spectral features in TROPOMI methane retrievals
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title_full	Accounting for surface reflectance spectral features in TROPOMI methane retrievals
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title_sort	accounting for surface reflectance spectral features in tropomi methane retrievals
callnumber	TA170-171
title_auth	Accounting for surface reflectance spectral features in TROPOMI methane retrievals
abstract	<p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p<
abstractGer	<p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p<
abstract_unstemmed	<p<Satellite remote sensing of methane (CH<span class="inline-formula"<<sub<4</sub<</span<) using the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5-P) satellite is key to monitor and quantify emissions globally. Overall, the S5-P methane data are of satisfying quality, demonstrated by the product validation with ground-based measurements from the Total Carbon Column Observing Network (TCCON). However, analysis of TROPOMI dry-air column mixing ratio (XCH<span class="inline-formula"<<sub<4</sub<</span<) data has pointed to a few false methane anomalies up to 20–40 ppb that can potentially be misinterpreted as enhancements due to strong emission sources. These artefacts are caused by spectral features of the underlying surfaces of specific materials (e.g. carbonate rocks), which are not well represented in the forward model of the retrieval algorithm. In this study we show that the observed anomalies are due to the surface model which describes the spectral dependence of the Lambertian albedo by a second-order polynomial in wavelength. By analysing the ECOSTRESS library that contains laboratory spectra for different types of surfaces, we find that a quadratic function might not be the most optimal representation of the surface reflectance spectral dependencies in the short-wave infrared (SWIR) range. Already the use of a third-order polynomial improves the methane data such that the anomalies disappear at several locations (e.g. Siberia, Australia and Algeria) without affecting the data quality elsewhere, and the quality of the fit significantly improves. We also found that the known bias in retrieved methane for low-albedo scenes slightly improves, but still, a posterior correction needs to be applied, leaving open the question about the root cause of the albedo bias. After applying the adjusted surface model globally, we perform the routine validation with TCCON and Greenhouse gases Observing SATellite (GOSAT) data. GOSAT comparison does not significantly improve, while TCCON validation results show a small improvement in some stations of 2–4 ppb, up to a factor of 10 smaller than the artificial XCH<span class="inline-formula"<<sub<4</sub<</span< enhancements. This reflects that TCCON stations are not close to any of the corrected artefacts, hinting at a limitation of the current validation approach of the S5-P XCH<span class="inline-formula"<<sub<4</sub<</span< data product.</p<
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title_short	Accounting for surface reflectance spectral features in TROPOMI methane retrievals
url	https://doi.org/10.5194/amt-16-1597-2023 https://doaj.org/article/6e72616759074053a8686c5e4a51a05e https://amt.copernicus.org/articles/16/1597/2023/amt-16-1597-2023.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548
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Accounting for surface reflectance spectral features in TROPOMI methane retrievals

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