GNSS precipitable water vapor from an Amazonian rain forest flux tower
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional do INPA |
Texto Completo: | https://repositorio.inpa.gov.br/handle/1/16175 |
Resumo: | Understanding the complex interactions between water vapor fields and deep convection on the mesoscale requires observational networks with high spatial (kilometers) and temporal (minutes) resolution. In the equatorial tropics, where deep convection dominates the vertical distribution of the most important greenhouse substance-water-these mesoscale networks are nonexistent. Global Navigational Satellite System (GNSS) meteorological networks offer high temporal/spatial resolution precipitable water vapor, but infrastructure exigencies are great. The authors report here on very accurate precipitable water vapor (PWV) values calculated from a GNSS receiver installed on a highly nonideal Amazon rain forest flux tower. Further experiments with a mechanically oscillating platform demonstrate that errors and biases of approximately 1 mm (2%-3% of PWV) can be expected when compared with a stable reference GNSS receiver for two different geodetic grade receivers/antennas and processing methods [GPS-Inferred Positioning System (GIPSY) andGAMIT]. The implication is that stable fixed antennas are unnecessary for accurate calculation of precipitable water vapor regardless of processing techniques or geodetic grade receiver. © 2011 American Meteorological Society. |
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Adams, David K.Silva Fernandes, Rui Manuel daMaia, Jair Max Furtunato2020-05-25T20:59:14Z2020-05-25T20:59:14Z2011https://repositorio.inpa.gov.br/handle/1/1617510.1175/JTECH-D-11-00082.1Understanding the complex interactions between water vapor fields and deep convection on the mesoscale requires observational networks with high spatial (kilometers) and temporal (minutes) resolution. In the equatorial tropics, where deep convection dominates the vertical distribution of the most important greenhouse substance-water-these mesoscale networks are nonexistent. Global Navigational Satellite System (GNSS) meteorological networks offer high temporal/spatial resolution precipitable water vapor, but infrastructure exigencies are great. The authors report here on very accurate precipitable water vapor (PWV) values calculated from a GNSS receiver installed on a highly nonideal Amazon rain forest flux tower. Further experiments with a mechanically oscillating platform demonstrate that errors and biases of approximately 1 mm (2%-3% of PWV) can be expected when compared with a stable reference GNSS receiver for two different geodetic grade receivers/antennas and processing methods [GPS-Inferred Positioning System (GIPSY) andGAMIT]. The implication is that stable fixed antennas are unnecessary for accurate calculation of precipitable water vapor regardless of processing techniques or geodetic grade receiver. © 2011 American Meteorological Society.Volume 28, Número 10, Pags. 1192-1198Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessAmazon RainforestComplex InteractionConvective StormsDeep ConvectionGnss ReceiversInstrumentation/sensorsMeso ScaleMesoscale NetworksMesoscale ProcessNavigational SatellitesNonidealOscillating PlatformPositioning SystemPrecipitable Water VaporProcessing MethodProcessing TechniqueRain ForestsVertical DistributionsWater Vapor FieldsForestryGeodesyGeodetic SatellitesGlobal Positioning SystemNatural ConvectionNavigation SystemsProcessingRainSignal ReceiversWater VaporAccuracy AssessmentConvective SystemGnssGpsMesoscale MeteorologyPrecipitation AssessmentPrecipitation IntensityRainforestSpatial ResolutionTemporal VariationWater VaporForestryProcessingRainSatellitesSensorsSignalsWater VaporAmazoniaGNSS precipitable water vapor from an Amazonian rain forest flux towerinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleJournal of Atmospheric and Oceanic Technologyengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALGNSS.pdfGNSS.pdfapplication/pdf1734177https://repositorio.inpa.gov.br/bitstream/1/16175/1/GNSS.pdf78a2ba09df673e9b21d4845f2c811b8cMD511/161752020-07-14 11:27:29.08oai:repositorio:1/16175Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-07-14T15:27:29Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false |
dc.title.en.fl_str_mv |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
title |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
spellingShingle |
GNSS precipitable water vapor from an Amazonian rain forest flux tower Adams, David K. Amazon Rainforest Complex Interaction Convective Storms Deep Convection Gnss Receivers Instrumentation/sensors Meso Scale Mesoscale Networks Mesoscale Process Navigational Satellites Nonideal Oscillating Platform Positioning System Precipitable Water Vapor Processing Method Processing Technique Rain Forests Vertical Distributions Water Vapor Fields Forestry Geodesy Geodetic Satellites Global Positioning System Natural Convection Navigation Systems Processing Rain Signal Receivers Water Vapor Accuracy Assessment Convective System Gnss Gps Mesoscale Meteorology Precipitation Assessment Precipitation Intensity Rainforest Spatial Resolution Temporal Variation Water Vapor Forestry Processing Rain Satellites Sensors Signals Water Vapor Amazonia |
title_short |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
title_full |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
title_fullStr |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
title_full_unstemmed |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
title_sort |
GNSS precipitable water vapor from an Amazonian rain forest flux tower |
author |
Adams, David K. |
author_facet |
Adams, David K. Silva Fernandes, Rui Manuel da Maia, Jair Max Furtunato |
author_role |
author |
author2 |
Silva Fernandes, Rui Manuel da Maia, Jair Max Furtunato |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Adams, David K. Silva Fernandes, Rui Manuel da Maia, Jair Max Furtunato |
dc.subject.eng.fl_str_mv |
Amazon Rainforest Complex Interaction Convective Storms Deep Convection Gnss Receivers Instrumentation/sensors Meso Scale Mesoscale Networks Mesoscale Process Navigational Satellites Nonideal Oscillating Platform Positioning System Precipitable Water Vapor Processing Method Processing Technique Rain Forests Vertical Distributions Water Vapor Fields Forestry Geodesy Geodetic Satellites Global Positioning System Natural Convection Navigation Systems Processing Rain Signal Receivers Water Vapor Accuracy Assessment Convective System Gnss Gps Mesoscale Meteorology Precipitation Assessment Precipitation Intensity Rainforest Spatial Resolution Temporal Variation Water Vapor Forestry Processing Rain Satellites Sensors Signals Water Vapor Amazonia |
topic |
Amazon Rainforest Complex Interaction Convective Storms Deep Convection Gnss Receivers Instrumentation/sensors Meso Scale Mesoscale Networks Mesoscale Process Navigational Satellites Nonideal Oscillating Platform Positioning System Precipitable Water Vapor Processing Method Processing Technique Rain Forests Vertical Distributions Water Vapor Fields Forestry Geodesy Geodetic Satellites Global Positioning System Natural Convection Navigation Systems Processing Rain Signal Receivers Water Vapor Accuracy Assessment Convective System Gnss Gps Mesoscale Meteorology Precipitation Assessment Precipitation Intensity Rainforest Spatial Resolution Temporal Variation Water Vapor Forestry Processing Rain Satellites Sensors Signals Water Vapor Amazonia |
description |
Understanding the complex interactions between water vapor fields and deep convection on the mesoscale requires observational networks with high spatial (kilometers) and temporal (minutes) resolution. In the equatorial tropics, where deep convection dominates the vertical distribution of the most important greenhouse substance-water-these mesoscale networks are nonexistent. Global Navigational Satellite System (GNSS) meteorological networks offer high temporal/spatial resolution precipitable water vapor, but infrastructure exigencies are great. The authors report here on very accurate precipitable water vapor (PWV) values calculated from a GNSS receiver installed on a highly nonideal Amazon rain forest flux tower. Further experiments with a mechanically oscillating platform demonstrate that errors and biases of approximately 1 mm (2%-3% of PWV) can be expected when compared with a stable reference GNSS receiver for two different geodetic grade receivers/antennas and processing methods [GPS-Inferred Positioning System (GIPSY) andGAMIT]. The implication is that stable fixed antennas are unnecessary for accurate calculation of precipitable water vapor regardless of processing techniques or geodetic grade receiver. © 2011 American Meteorological Society. |
publishDate |
2011 |
dc.date.issued.fl_str_mv |
2011 |
dc.date.accessioned.fl_str_mv |
2020-05-25T20:59:14Z |
dc.date.available.fl_str_mv |
2020-05-25T20:59:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio.inpa.gov.br/handle/1/16175 |
dc.identifier.doi.none.fl_str_mv |
10.1175/JTECH-D-11-00082.1 |
url |
https://repositorio.inpa.gov.br/handle/1/16175 |
identifier_str_mv |
10.1175/JTECH-D-11-00082.1 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Volume 28, Número 10, Pags. 1192-1198 |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Journal of Atmospheric and Oceanic Technology |
publisher.none.fl_str_mv |
Journal of Atmospheric and Oceanic Technology |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do INPA instname:Instituto Nacional de Pesquisas da Amazônia (INPA) instacron:INPA |
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Instituto Nacional de Pesquisas da Amazônia (INPA) |
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INPA |
institution |
INPA |
reponame_str |
Repositório Institucional do INPA |
collection |
Repositório Institucional do INPA |
bitstream.url.fl_str_mv |
https://repositorio.inpa.gov.br/bitstream/1/16175/1/GNSS.pdf |
bitstream.checksum.fl_str_mv |
78a2ba09df673e9b21d4845f2c811b8c |
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Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA) |
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1801499131099742208 |