Satellite measurements of carbon dioxide: analysis and reduction of scattering related retrieval errors
Carbon dioxide, remote sensing, clouds, aerosols, SCIAMACHY, scattering, satellite, retrieval algorithm. - The greenhouse gas carbon dioxide (CO2) is the most important human-made contributor to global warming. Despite its importance, our knowledge about its sources and sinks has large gaps. This li...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Abschlussarbeit Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
2013
|
Schlagworte: | |
Online-Zugang: | kostenfrei |
Zusammenfassung: | Carbon dioxide, remote sensing, clouds, aerosols, SCIAMACHY, scattering, satellite, retrieval algorithm. - The greenhouse gas carbon dioxide (CO2) is the most important human-made contributor to global warming. Despite its importance, our knowledge about its sources and sinks has large gaps. This limits a reliable climate prediction. Satellite observations of atmospheric CO2 combined with modelling can help to reduce these knowledge gaps. However, this requires to meet demanding accuracy and precision requirements for the satellite instrument, the retrieval algorithm and the model. One of the most important error sources for satellite retrievals of CO2 from reflected and backscattered solar radiation is unaccounted scattering by aerosols and clouds. In this context, the objectives of this thesis are to assess the quality of an existing satellite-based CO2 data set focussing on the investigation of these error source and to generate and validate an improved CO2 data set. The CO2 data bases on measurements of the passive remote sensing satellite instrument SCIAMACHY on-board ENVISAT, which has performed more than 10 years of radiance measurements in the short wave infrared spectral region. In the period 2003-2009, SCIAMACHY was the only satellite instrument measuring CO2 with high sensitivity down to the Earth's surface where the sources and sinks of CO2 are located. Therefore, the SCIAMACHY measurements are important in terms of generating an accurate global long-term atmospheric CO2 data set. Starting point for this thesis was an analysis of an existing 7-year (2003-2009) data set of column-averaged dry airmole-fraction of CO2, denoted XCO2, which was generated with version 2.1 of the Weighting Function Modified - Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm (WFMDv2.1). |
Internformat
MARC
LEADER | 00000nmm a2200000 c 4500 | ||
---|---|---|---|
001 | BV041357522 | ||
003 | DE-604 | ||
005 | 00000000000000.0 | ||
006 | a m||| 00||| | ||
007 | cr|uuu---uuuuu | ||
008 | 131014s2013 |||| o||u| ||||||eng d | ||
035 | |a (OCoLC)862818630 | ||
035 | |a (DE-599)GBV748772987 | ||
040 | |a DE-604 |b ger | ||
041 | 0 | |a eng | |
049 | |a DE-384 | ||
084 | |a UT 8130 |0 (DE-625)146848: |2 rvk | ||
100 | 1 | |a Heymann, Jens |e Verfasser |0 (DE-588)1037737172 |4 aut | |
245 | 1 | 0 | |a Satellite measurements of carbon dioxide |b analysis and reduction of scattering related retrieval errors |c von Jens Heymann |
264 | 1 | |c 2013 | |
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
502 | |a Bremen, Univ., Diss., 2013 | ||
520 | 8 | |a Carbon dioxide, remote sensing, clouds, aerosols, SCIAMACHY, scattering, satellite, retrieval algorithm. - The greenhouse gas carbon dioxide (CO2) is the most important human-made contributor to global warming. Despite its importance, our knowledge about its sources and sinks has large gaps. This limits a reliable climate prediction. Satellite observations of atmospheric CO2 combined with modelling can help to reduce these knowledge gaps. However, this requires to meet demanding accuracy and precision requirements for the satellite instrument, the retrieval algorithm and the model. One of the most important error sources for satellite retrievals of CO2 from reflected and backscattered solar radiation is unaccounted scattering by aerosols and clouds. In this context, the objectives of this thesis are to assess the quality of an existing satellite-based CO2 data set focussing on the investigation of these error source and to generate and validate an improved CO2 data set. The CO2 data bases on measurements of the passive remote sensing satellite instrument SCIAMACHY on-board ENVISAT, which has performed more than 10 years of radiance measurements in the short wave infrared spectral region. In the period 2003-2009, SCIAMACHY was the only satellite instrument measuring CO2 with high sensitivity down to the Earth's surface where the sources and sinks of CO2 are located. Therefore, the SCIAMACHY measurements are important in terms of generating an accurate global long-term atmospheric CO2 data set. Starting point for this thesis was an analysis of an existing 7-year (2003-2009) data set of column-averaged dry airmole-fraction of CO2, denoted XCO2, which was generated with version 2.1 of the Weighting Function Modified - Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm (WFMDv2.1). | |
533 | |a Online-Ausgabe |e Online-Ressource | ||
650 | 0 | 7 | |a Kohlendioxidbelastung |0 (DE-588)4129021-5 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Satellitenmeteorologie |0 (DE-588)4140530-4 |2 gnd |9 rswk-swf |
655 | 7 | |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
689 | 0 | 0 | |a Kohlendioxidbelastung |0 (DE-588)4129021-5 |D s |
689 | 0 | 1 | |a Satellitenmeteorologie |0 (DE-588)4140530-4 |D s |
689 | 0 | |5 DE-604 | |
776 | 0 | 8 | |i Reproduktion von |a Heymann, Jens |t Satellite measurements of carbon dioxide |d 2013 |
856 | 4 | 0 | |u https://nbn-resolving.org/urn:nbn:de:gbv:46-00103201-19 |x Verlag |z kostenfrei |3 Volltext |
912 | |a ebook | ||
999 | |a oai:aleph.bib-bvb.de:BVB01-026805944 |
Datensatz im Suchindex
_version_ | 1804151440028991489 |
---|---|
any_adam_object | |
author | Heymann, Jens |
author_GND | (DE-588)1037737172 |
author_facet | Heymann, Jens |
author_role | aut |
author_sort | Heymann, Jens |
author_variant | j h jh |
building | Verbundindex |
bvnumber | BV041357522 |
classification_rvk | UT 8130 |
collection | ebook |
ctrlnum | (OCoLC)862818630 (DE-599)GBV748772987 |
discipline | Physik |
format | Thesis Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03279nmm a2200397 c 4500</leader><controlfield tag="001">BV041357522</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="006">a m||| 00||| </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">131014s2013 |||| o||u| ||||||eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)862818630</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBV748772987</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">UT 8130</subfield><subfield code="0">(DE-625)146848:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Heymann, Jens</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1037737172</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Satellite measurements of carbon dioxide</subfield><subfield code="b">analysis and reduction of scattering related retrieval errors</subfield><subfield code="c">von Jens Heymann</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="a">Bremen, Univ., Diss., 2013</subfield></datafield><datafield tag="520" ind1="8" ind2=" "><subfield code="a">Carbon dioxide, remote sensing, clouds, aerosols, SCIAMACHY, scattering, satellite, retrieval algorithm. - The greenhouse gas carbon dioxide (CO2) is the most important human-made contributor to global warming. Despite its importance, our knowledge about its sources and sinks has large gaps. This limits a reliable climate prediction. Satellite observations of atmospheric CO2 combined with modelling can help to reduce these knowledge gaps. However, this requires to meet demanding accuracy and precision requirements for the satellite instrument, the retrieval algorithm and the model. One of the most important error sources for satellite retrievals of CO2 from reflected and backscattered solar radiation is unaccounted scattering by aerosols and clouds. In this context, the objectives of this thesis are to assess the quality of an existing satellite-based CO2 data set focussing on the investigation of these error source and to generate and validate an improved CO2 data set. The CO2 data bases on measurements of the passive remote sensing satellite instrument SCIAMACHY on-board ENVISAT, which has performed more than 10 years of radiance measurements in the short wave infrared spectral region. In the period 2003-2009, SCIAMACHY was the only satellite instrument measuring CO2 with high sensitivity down to the Earth's surface where the sources and sinks of CO2 are located. Therefore, the SCIAMACHY measurements are important in terms of generating an accurate global long-term atmospheric CO2 data set. Starting point for this thesis was an analysis of an existing 7-year (2003-2009) data set of column-averaged dry airmole-fraction of CO2, denoted XCO2, which was generated with version 2.1 of the Weighting Function Modified - Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm (WFMDv2.1).</subfield></datafield><datafield tag="533" ind1=" " ind2=" "><subfield code="a">Online-Ausgabe</subfield><subfield code="e">Online-Ressource</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Kohlendioxidbelastung</subfield><subfield code="0">(DE-588)4129021-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Satellitenmeteorologie</subfield><subfield code="0">(DE-588)4140530-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4113937-9</subfield><subfield code="a">Hochschulschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Kohlendioxidbelastung</subfield><subfield code="0">(DE-588)4129021-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Satellitenmeteorologie</subfield><subfield code="0">(DE-588)4140530-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Reproduktion von</subfield><subfield code="a">Heymann, Jens</subfield><subfield code="t">Satellite measurements of carbon dioxide</subfield><subfield code="d">2013</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://nbn-resolving.org/urn:nbn:de:gbv:46-00103201-19</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ebook</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-026805944</subfield></datafield></record></collection> |
genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
genre_facet | Hochschulschrift |
id | DE-604.BV041357522 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T00:54:50Z |
institution | BVB |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026805944 |
oclc_num | 862818630 |
open_access_boolean | 1 |
owner | DE-384 |
owner_facet | DE-384 |
psigel | ebook |
publishDate | 2013 |
publishDateSearch | 2013 |
publishDateSort | 2013 |
record_format | marc |
spelling | Heymann, Jens Verfasser (DE-588)1037737172 aut Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors von Jens Heymann 2013 txt rdacontent c rdamedia cr rdacarrier Bremen, Univ., Diss., 2013 Carbon dioxide, remote sensing, clouds, aerosols, SCIAMACHY, scattering, satellite, retrieval algorithm. - The greenhouse gas carbon dioxide (CO2) is the most important human-made contributor to global warming. Despite its importance, our knowledge about its sources and sinks has large gaps. This limits a reliable climate prediction. Satellite observations of atmospheric CO2 combined with modelling can help to reduce these knowledge gaps. However, this requires to meet demanding accuracy and precision requirements for the satellite instrument, the retrieval algorithm and the model. One of the most important error sources for satellite retrievals of CO2 from reflected and backscattered solar radiation is unaccounted scattering by aerosols and clouds. In this context, the objectives of this thesis are to assess the quality of an existing satellite-based CO2 data set focussing on the investigation of these error source and to generate and validate an improved CO2 data set. The CO2 data bases on measurements of the passive remote sensing satellite instrument SCIAMACHY on-board ENVISAT, which has performed more than 10 years of radiance measurements in the short wave infrared spectral region. In the period 2003-2009, SCIAMACHY was the only satellite instrument measuring CO2 with high sensitivity down to the Earth's surface where the sources and sinks of CO2 are located. Therefore, the SCIAMACHY measurements are important in terms of generating an accurate global long-term atmospheric CO2 data set. Starting point for this thesis was an analysis of an existing 7-year (2003-2009) data set of column-averaged dry airmole-fraction of CO2, denoted XCO2, which was generated with version 2.1 of the Weighting Function Modified - Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm (WFMDv2.1). Online-Ausgabe Online-Ressource Kohlendioxidbelastung (DE-588)4129021-5 gnd rswk-swf Satellitenmeteorologie (DE-588)4140530-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Kohlendioxidbelastung (DE-588)4129021-5 s Satellitenmeteorologie (DE-588)4140530-4 s DE-604 Reproduktion von Heymann, Jens Satellite measurements of carbon dioxide 2013 https://nbn-resolving.org/urn:nbn:de:gbv:46-00103201-19 Verlag kostenfrei Volltext |
spellingShingle | Heymann, Jens Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors Kohlendioxidbelastung (DE-588)4129021-5 gnd Satellitenmeteorologie (DE-588)4140530-4 gnd |
subject_GND | (DE-588)4129021-5 (DE-588)4140530-4 (DE-588)4113937-9 |
title | Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors |
title_auth | Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors |
title_exact_search | Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors |
title_full | Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors von Jens Heymann |
title_fullStr | Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors von Jens Heymann |
title_full_unstemmed | Satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors von Jens Heymann |
title_short | Satellite measurements of carbon dioxide |
title_sort | satellite measurements of carbon dioxide analysis and reduction of scattering related retrieval errors |
title_sub | analysis and reduction of scattering related retrieval errors |
topic | Kohlendioxidbelastung (DE-588)4129021-5 gnd Satellitenmeteorologie (DE-588)4140530-4 gnd |
topic_facet | Kohlendioxidbelastung Satellitenmeteorologie Hochschulschrift |
url | https://nbn-resolving.org/urn:nbn:de:gbv:46-00103201-19 |
work_keys_str_mv | AT heymannjens satellitemeasurementsofcarbondioxideanalysisandreductionofscatteringrelatedretrievalerrors |