Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models
Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this pape...
Ausführliche Beschreibung
Autor*in: |
Zhang, Di [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2016transfer abstract |
---|
Schlagwörter: |
---|
Umfang: |
11 |
---|
Übergeordnetes Werk: |
Enthalten in: Posttranscriptional actions of triiodothyronine on - Bargi-Souza, Paula ELSEVIER, 2018, including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU), Amsterdam [u.a.] |
---|---|
Übergeordnetes Werk: |
volume:58 ; year:2016 ; number:6 ; day:15 ; month:09 ; pages:1033-1043 ; extent:11 |
Links: |
---|
DOI / URN: |
10.1016/j.asr.2016.05.055 |
---|
Katalog-ID: |
ELV013943995 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | ELV013943995 | ||
003 | DE-627 | ||
005 | 20230625112716.0 | ||
007 | cr uuu---uuuuu | ||
008 | 180602s2016 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.asr.2016.05.055 |2 doi | |
028 | 5 | 2 | |a GBVA2016008000005.pica |
035 | |a (DE-627)ELV013943995 | ||
035 | |a (ELSEVIER)S0273-1177(16)30278-2 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | |a 520 |a 620 | |
082 | 0 | 4 | |a 520 |q DE-600 |
082 | 0 | 4 | |a 620 |q DE-600 |
082 | 0 | 4 | |a 610 |a 570 |q VZ |
084 | |a 44.89 |2 bkl | ||
100 | 1 | |a Zhang, Di |e verfasserin |4 aut | |
245 | 1 | 0 | |a Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models |
264 | 1 | |c 2016transfer abstract | |
300 | |a 11 | ||
336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
337 | |a nicht spezifiziert |b z |2 rdamedia | ||
338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
520 | |a Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. | ||
520 | |a Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. | ||
650 | 7 | |a UNB3m |2 Elsevier | |
650 | 7 | |a Radiosonde |2 Elsevier | |
650 | 7 | |a Hopfield |2 Elsevier | |
650 | 7 | |a GPT2/GPT2w |2 Elsevier | |
650 | 7 | |a Zenith Hydrostatic Delay |2 Elsevier | |
650 | 7 | |a Saastamoinen |2 Elsevier | |
700 | 1 | |a Guo, Jiming |4 oth | |
700 | 1 | |a Chen, Ming |4 oth | |
700 | 1 | |a Shi, Junbo |4 oth | |
700 | 1 | |a Zhou, Lv |4 oth | |
773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Bargi-Souza, Paula ELSEVIER |t Posttranscriptional actions of triiodothyronine on |d 2018 |d including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) |g Amsterdam [u.a.] |w (DE-627)ELV000905844 |
773 | 1 | 8 | |g volume:58 |g year:2016 |g number:6 |g day:15 |g month:09 |g pages:1033-1043 |g extent:11 |
856 | 4 | 0 | |u https://doi.org/10.1016/j.asr.2016.05.055 |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a GBV_ELV | ||
912 | |a SYSFLAG_U | ||
912 | |a SSG-OLC-PHA | ||
936 | b | k | |a 44.89 |j Endokrinologie |q VZ |
951 | |a AR | ||
952 | |d 58 |j 2016 |e 6 |b 15 |c 0915 |h 1033-1043 |g 11 | ||
953 | |2 045F |a 520 |
author_variant |
d z dz |
---|---|
matchkey_str |
zhangdiguojimingchenmingshijunbozhoulv:2016----:uniaiesesetfeerlgclntoopeiznth |
hierarchy_sort_str |
2016transfer abstract |
bklnumber |
44.89 |
publishDate |
2016 |
allfields |
10.1016/j.asr.2016.05.055 doi GBVA2016008000005.pica (DE-627)ELV013943995 (ELSEVIER)S0273-1177(16)30278-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Zhang, Di verfasserin aut Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models 2016transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Elsevier Guo, Jiming oth Chen, Ming oth Shi, Junbo oth Zhou, Lv oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 https://doi.org/10.1016/j.asr.2016.05.055 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 58 2016 6 15 0915 1033-1043 11 045F 520 |
spelling |
10.1016/j.asr.2016.05.055 doi GBVA2016008000005.pica (DE-627)ELV013943995 (ELSEVIER)S0273-1177(16)30278-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Zhang, Di verfasserin aut Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models 2016transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Elsevier Guo, Jiming oth Chen, Ming oth Shi, Junbo oth Zhou, Lv oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 https://doi.org/10.1016/j.asr.2016.05.055 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 58 2016 6 15 0915 1033-1043 11 045F 520 |
allfields_unstemmed |
10.1016/j.asr.2016.05.055 doi GBVA2016008000005.pica (DE-627)ELV013943995 (ELSEVIER)S0273-1177(16)30278-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Zhang, Di verfasserin aut Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models 2016transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Elsevier Guo, Jiming oth Chen, Ming oth Shi, Junbo oth Zhou, Lv oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 https://doi.org/10.1016/j.asr.2016.05.055 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 58 2016 6 15 0915 1033-1043 11 045F 520 |
allfieldsGer |
10.1016/j.asr.2016.05.055 doi GBVA2016008000005.pica (DE-627)ELV013943995 (ELSEVIER)S0273-1177(16)30278-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Zhang, Di verfasserin aut Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models 2016transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Elsevier Guo, Jiming oth Chen, Ming oth Shi, Junbo oth Zhou, Lv oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 https://doi.org/10.1016/j.asr.2016.05.055 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 58 2016 6 15 0915 1033-1043 11 045F 520 |
allfieldsSound |
10.1016/j.asr.2016.05.055 doi GBVA2016008000005.pica (DE-627)ELV013943995 (ELSEVIER)S0273-1177(16)30278-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Zhang, Di verfasserin aut Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models 2016transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Elsevier Guo, Jiming oth Chen, Ming oth Shi, Junbo oth Zhou, Lv oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 https://doi.org/10.1016/j.asr.2016.05.055 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 58 2016 6 15 0915 1033-1043 11 045F 520 |
language |
English |
source |
Enthalten in Posttranscriptional actions of triiodothyronine on Amsterdam [u.a.] volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 |
sourceStr |
Enthalten in Posttranscriptional actions of triiodothyronine on Amsterdam [u.a.] volume:58 year:2016 number:6 day:15 month:09 pages:1033-1043 extent:11 |
format_phy_str_mv |
Article |
bklname |
Endokrinologie |
institution |
findex.gbv.de |
topic_facet |
UNB3m Radiosonde Hopfield GPT2/GPT2w Zenith Hydrostatic Delay Saastamoinen |
dewey-raw |
520 |
isfreeaccess_bool |
false |
container_title |
Posttranscriptional actions of triiodothyronine on |
authorswithroles_txt_mv |
Zhang, Di @@aut@@ Guo, Jiming @@oth@@ Chen, Ming @@oth@@ Shi, Junbo @@oth@@ Zhou, Lv @@oth@@ |
publishDateDaySort_date |
2016-01-15T00:00:00Z |
hierarchy_top_id |
ELV000905844 |
dewey-sort |
3520 |
id |
ELV013943995 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV013943995</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625112716.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.asr.2016.05.055</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016008000005.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV013943995</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0273-1177(16)30278-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">520</subfield><subfield code="a">620</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">520</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.89</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Zhang, Di</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">11</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">UNB3m</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Radiosonde</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Hopfield</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">GPT2/GPT2w</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Zenith Hydrostatic Delay</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Saastamoinen</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Guo, Jiming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Ming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shi, Junbo</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhou, Lv</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Bargi-Souza, Paula ELSEVIER</subfield><subfield code="t">Posttranscriptional actions of triiodothyronine on</subfield><subfield code="d">2018</subfield><subfield code="d">including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU)</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV000905844</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:58</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:6</subfield><subfield code="g">day:15</subfield><subfield code="g">month:09</subfield><subfield code="g">pages:1033-1043</subfield><subfield code="g">extent:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.asr.2016.05.055</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.89</subfield><subfield code="j">Endokrinologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">58</subfield><subfield code="j">2016</subfield><subfield code="e">6</subfield><subfield code="b">15</subfield><subfield code="c">0915</subfield><subfield code="h">1033-1043</subfield><subfield code="g">11</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">520</subfield></datafield></record></collection>
|
author |
Zhang, Di |
spellingShingle |
Zhang, Di ddc 520 ddc 620 ddc 610 bkl 44.89 Elsevier UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models |
authorStr |
Zhang, Di |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV000905844 |
format |
electronic Article |
dewey-ones |
520 - Astronomy & allied sciences 620 - Engineering & allied operations 610 - Medicine & health 570 - Life sciences; biology |
delete_txt_mv |
keep |
author_role |
aut |
collection |
elsevier |
remote_str |
true |
illustrated |
Not Illustrated |
topic_title |
520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen Elsevier |
topic |
ddc 520 ddc 620 ddc 610 bkl 44.89 Elsevier UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen |
topic_unstemmed |
ddc 520 ddc 620 ddc 610 bkl 44.89 Elsevier UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen |
topic_browse |
ddc 520 ddc 620 ddc 610 bkl 44.89 Elsevier UNB3m Elsevier Radiosonde Elsevier Hopfield Elsevier GPT2/GPT2w Elsevier Zenith Hydrostatic Delay Elsevier Saastamoinen |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
author2_variant |
j g jg m c mc j s js l z lz |
hierarchy_parent_title |
Posttranscriptional actions of triiodothyronine on |
hierarchy_parent_id |
ELV000905844 |
dewey-tens |
520 - Astronomy 620 - Engineering 610 - Medicine & health 570 - Life sciences; biology |
hierarchy_top_title |
Posttranscriptional actions of triiodothyronine on |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)ELV000905844 |
title |
Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models |
ctrlnum |
(DE-627)ELV013943995 (ELSEVIER)S0273-1177(16)30278-2 |
title_full |
Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models |
author_sort |
Zhang, Di |
journal |
Posttranscriptional actions of triiodothyronine on |
journalStr |
Posttranscriptional actions of triiodothyronine on |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
500 - Science 600 - Technology |
recordtype |
marc |
publishDateSort |
2016 |
contenttype_str_mv |
zzz |
container_start_page |
1033 |
author_browse |
Zhang, Di |
container_volume |
58 |
physical |
11 |
class |
520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl |
format_se |
Elektronische Aufsätze |
author-letter |
Zhang, Di |
doi_str_mv |
10.1016/j.asr.2016.05.055 |
dewey-full |
520 620 610 570 |
title_sort |
quantitative assessment of meteorological and tropospheric zenith hydrostatic delay models |
title_auth |
Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models |
abstract |
Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. |
abstractGer |
Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. |
abstract_unstemmed |
Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given. |
collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA |
container_issue |
6 |
title_short |
Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models |
url |
https://doi.org/10.1016/j.asr.2016.05.055 |
remote_bool |
true |
author2 |
Guo, Jiming Chen, Ming Shi, Junbo Zhou, Lv |
author2Str |
Guo, Jiming Chen, Ming Shi, Junbo Zhou, Lv |
ppnlink |
ELV000905844 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth oth oth oth |
doi_str |
10.1016/j.asr.2016.05.055 |
up_date |
2024-07-06T20:11:44.365Z |
_version_ |
1803861837078331392 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV013943995</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625112716.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.asr.2016.05.055</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016008000005.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV013943995</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0273-1177(16)30278-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">520</subfield><subfield code="a">620</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">520</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.89</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Zhang, Di</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quantitative assessment of meteorological and tropospheric Zenith Hydrostatic Delay models</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">11</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Tropospheric delay has always been an important issue in GNSS/DORIS/VLBI/InSAR processing. Most commonly used empirical models for the determination of tropospheric Zenith Hydrostatic Delay (ZHD), including three meteorological models and two empirical ZHD models, are carefully analyzed in this paper. Meteorological models refer to UNB3m, GPT2 and GPT2w, while ZHD models include Hopfield and Saastamoinen. By reference to in-situ meteorological measurements and ray-traced ZHD values of 91 globally distributed radiosonde sites, over a four-years period from 2010 to 2013, it is found that there is strong correlation between errors of model-derived values and latitudes. Specifically, the Saastamoinen model shows a systematic error of about −3mm. Therefore a modified Saastamoinen model is developed based on the “best average” refractivity constant, and is validated by radiosonde data. Among different models, the GPT2w and the modified Saastamoinen model perform the best. ZHD values derived from their combination have a mean bias of −0.1mm and a mean RMS of 13.9mm. Limitations of the present models are discussed and suggestions for further improvements are given.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">UNB3m</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Radiosonde</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Hopfield</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">GPT2/GPT2w</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Zenith Hydrostatic Delay</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Saastamoinen</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Guo, Jiming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Ming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shi, Junbo</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhou, Lv</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Bargi-Souza, Paula ELSEVIER</subfield><subfield code="t">Posttranscriptional actions of triiodothyronine on</subfield><subfield code="d">2018</subfield><subfield code="d">including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU)</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV000905844</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:58</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:6</subfield><subfield code="g">day:15</subfield><subfield code="g">month:09</subfield><subfield code="g">pages:1033-1043</subfield><subfield code="g">extent:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.asr.2016.05.055</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.89</subfield><subfield code="j">Endokrinologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">58</subfield><subfield code="j">2016</subfield><subfield code="e">6</subfield><subfield code="b">15</subfield><subfield code="c">0915</subfield><subfield code="h">1033-1043</subfield><subfield code="g">11</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">520</subfield></datafield></record></collection>
|
score |
7.4008837 |