A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor
Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m}...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Huang, Liangke [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of geodesy - Springer Berlin Heidelberg, 1995, 93(2018), 2 vom: 15. Mai, Seite 159-176 |
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| Übergeordnetes Werk: |
volume:93 ; year:2018 ; number:2 ; day:15 ; month:05 ; pages:159-176 |
| Links: |
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| DOI / URN: |
10.1007/s00190-018-1148-9 |
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OLC2058949994 |
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| 520 | |a Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. | ||
| 650 | 4 | |a GGTm model | |
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| 700 | 1 | |a Ye, Shirong |4 aut | |
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10.1007/s00190-018-1148-9 doi (DE-627)OLC2058949994 (DE-He213)s00190-018-1148-9-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Huang, Liangke verfasserin aut A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. GGTm model GGOS GPT2w model Precipitable water vapor GPS meteorology Jiang, Weiping (orcid)0000-0002-3267-9682 aut Liu, Lilong aut Chen, Hua aut Ye, Shirong aut Enthalten in Journal of geodesy Springer Berlin Heidelberg, 1995 93(2018), 2 vom: 15. Mai, Seite 159-176 (DE-627)191686298 (DE-600)1302972-1 (DE-576)051377373 0949-7714 nnns volume:93 year:2018 number:2 day:15 month:05 pages:159-176 https://doi.org/10.1007/s00190-018-1148-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_11 GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 93 2018 2 15 05 159-176 |
| spelling |
10.1007/s00190-018-1148-9 doi (DE-627)OLC2058949994 (DE-He213)s00190-018-1148-9-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Huang, Liangke verfasserin aut A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. GGTm model GGOS GPT2w model Precipitable water vapor GPS meteorology Jiang, Weiping (orcid)0000-0002-3267-9682 aut Liu, Lilong aut Chen, Hua aut Ye, Shirong aut Enthalten in Journal of geodesy Springer Berlin Heidelberg, 1995 93(2018), 2 vom: 15. Mai, Seite 159-176 (DE-627)191686298 (DE-600)1302972-1 (DE-576)051377373 0949-7714 nnns volume:93 year:2018 number:2 day:15 month:05 pages:159-176 https://doi.org/10.1007/s00190-018-1148-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_11 GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 93 2018 2 15 05 159-176 |
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10.1007/s00190-018-1148-9 doi (DE-627)OLC2058949994 (DE-He213)s00190-018-1148-9-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Huang, Liangke verfasserin aut A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. GGTm model GGOS GPT2w model Precipitable water vapor GPS meteorology Jiang, Weiping (orcid)0000-0002-3267-9682 aut Liu, Lilong aut Chen, Hua aut Ye, Shirong aut Enthalten in Journal of geodesy Springer Berlin Heidelberg, 1995 93(2018), 2 vom: 15. Mai, Seite 159-176 (DE-627)191686298 (DE-600)1302972-1 (DE-576)051377373 0949-7714 nnns volume:93 year:2018 number:2 day:15 month:05 pages:159-176 https://doi.org/10.1007/s00190-018-1148-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_11 GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 93 2018 2 15 05 159-176 |
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10.1007/s00190-018-1148-9 doi (DE-627)OLC2058949994 (DE-He213)s00190-018-1148-9-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Huang, Liangke verfasserin aut A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. GGTm model GGOS GPT2w model Precipitable water vapor GPS meteorology Jiang, Weiping (orcid)0000-0002-3267-9682 aut Liu, Lilong aut Chen, Hua aut Ye, Shirong aut Enthalten in Journal of geodesy Springer Berlin Heidelberg, 1995 93(2018), 2 vom: 15. Mai, Seite 159-176 (DE-627)191686298 (DE-600)1302972-1 (DE-576)051377373 0949-7714 nnns volume:93 year:2018 number:2 day:15 month:05 pages:159-176 https://doi.org/10.1007/s00190-018-1148-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_11 GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 93 2018 2 15 05 159-176 |
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10.1007/s00190-018-1148-9 doi (DE-627)OLC2058949994 (DE-He213)s00190-018-1148-9-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Huang, Liangke verfasserin aut A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. GGTm model GGOS GPT2w model Precipitable water vapor GPS meteorology Jiang, Weiping (orcid)0000-0002-3267-9682 aut Liu, Lilong aut Chen, Hua aut Ye, Shirong aut Enthalten in Journal of geodesy Springer Berlin Heidelberg, 1995 93(2018), 2 vom: 15. Mai, Seite 159-176 (DE-627)191686298 (DE-600)1302972-1 (DE-576)051377373 0949-7714 nnns volume:93 year:2018 number:2 day:15 month:05 pages:159-176 https://doi.org/10.1007/s00190-018-1148-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_11 GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 93 2018 2 15 05 159-176 |
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a new global grid model for the determination of atmospheric weighted mean temperature in gps precipitable water vapor |
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A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor |
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Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
| abstractGer |
Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
| abstract_unstemmed |
Abstract In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, $$T_\mathrm{m}$$, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing $$T_\mathrm{m} $$ models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that $$T_\mathrm{m} $$ is highly correlated with both latitude and altitude. In this study, a new global grid empirical $$T_\mathrm{m} $$ model, named as GGTm, was established by a sliding window algorithm using global gridded $$T_\mathrm{m} $$ data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded $$T_\mathrm{m} $$ data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded $$T_\mathrm{m} $$ data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean $$\hbox {RMS}_{\mathrm{PWV}} $$ and $$\hbox {RMS}_{\mathrm{PWV}} /\hbox {PWV}$$ values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate $$T_\mathrm{m} $$ value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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