Vertical structure of the lower troposphere derived from MU radar, unmanned aerial vehicle, and balloon measurements during ShUREX 2015 View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Hubert Luce, Lakshmi Kantha, Hiroyuki Hashiguchi, Dale Lawrence, Tyler Mixa, Masanori Yabuki, Toshitaka Tsuda

ABSTRACT

The ShUREX (Shigaraki UAV Radar Experiment) 2015 campaign carried out at the Shigaraki Middle and Upper atmosphere (MU) observatory (Japan) in June 2015 provided a unique opportunity to compare vertical profiles of atmospheric parameters estimated from unmanned aerial vehicle (UAV), balloon, and radar data in the lower troposphere. The present work is intended primarily as a demonstration of the potential offered by combination of these three instruments for studying the small-scale structure and dynamics in the lower troposphere. Here, we focus on data collected almost simultaneously by two instrumented UAVs and two meteorological balloons, near the MU radar operated continuously during the campaign. The UAVs flew along helical ascending and descending paths at a nearly constant horizontal distance from the radar (~ 1.0 km), while the balloons launched from the MU radar site drifted up to ~ 3–5 km in the altitude range of comparisons (~ 0.5 to 4.0 km) due to wind advection. Vertical profiles of squared Brünt-Väisälä frequency N2 and squared vertical gradient of generalized potential refractive index M2 were estimated at a vertical resolution of 20 m from pressure, temperature, and humidity data collected by UAVs and radiosondes. Profiles of M2 were also estimated from MU radar echo power at vertical incidence at a vertical sampling of 20 m and various time resolutions (1–4 min). The balloons and the MU radar provided vertical profiles of wind and wind shear S so that two independent estimates of the gradient Richardson number (Ri = N2/S2) could be obtained at a range resolution of 150 m. The two estimates of Ri profiles also showed remarkable agreement at all altitudes. We show that all three instruments detected the same prominent temperature and humidity gradients, down to decameter scales in stratified conditions. These gradients extended horizontally over a few kilometers at least and persisted for hours without significant changes, indicating that the turbulent diffusion was weak. Large discrepancies between N2and M2 profiles derived from the balloon, UAV, and radar data were found in a turbulent layer generated by a Kelvin-Helmholtz (KH) shear flow instability in the height range from 1.80 to 2.15 km. The cause of these discrepancies appears to depend on the stage of the KH billows. More... »

PAGES

29

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s40645-018-0187-4

DOI

http://dx.doi.org/10.1186/s40645-018-0187-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104331856


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0915", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Interdisciplinary Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Universite De Toulon Et Du Var", 
          "id": "https://www.grid.ac/institutes/grid.12611.35", 
          "name": [
            "Meditterranean Insitute of Oceanography, CNRS/INSU, UMR7294, IRD, Universit\u00e9 de Toulon, La Garde, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Luce", 
        "givenName": "Hubert", 
        "id": "sg:person.014054430011.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014054430011.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kyoto University", 
          "id": "https://www.grid.ac/institutes/grid.258799.8", 
          "name": [
            "Research Institute for Sustainable Humanosphere, Kyoto University, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kantha", 
        "givenName": "Lakshmi", 
        "id": "sg:person.07513074607.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07513074607.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Colorado Boulder", 
          "id": "https://www.grid.ac/institutes/grid.266190.a", 
          "name": [
            "Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hashiguchi", 
        "givenName": "Hiroyuki", 
        "id": "sg:person.013500043445.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013500043445.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kyoto University", 
          "id": "https://www.grid.ac/institutes/grid.258799.8", 
          "name": [
            "Research Institute for Sustainable Humanosphere, Kyoto University, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lawrence", 
        "givenName": "Dale", 
        "id": "sg:person.016675237227.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016675237227.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kyoto University", 
          "id": "https://www.grid.ac/institutes/grid.258799.8", 
          "name": [
            "Research Institute for Sustainable Humanosphere, Kyoto University, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mixa", 
        "givenName": "Tyler", 
        "id": "sg:person.010261347426.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010261347426.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Colorado Boulder", 
          "id": "https://www.grid.ac/institutes/grid.266190.a", 
          "name": [
            "Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yabuki", 
        "givenName": "Masanori", 
        "id": "sg:person.015367202214.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015367202214.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Colorado Boulder", 
          "id": "https://www.grid.ac/institutes/grid.266190.a", 
          "name": [
            "Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsuda", 
        "givenName": "Toshitaka", 
        "id": "sg:person.011357206365.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011357206365.90"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1029/rs025i004p00477", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002425022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/angeo-19-899-2001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007808189"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/angeo-19-899-2001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007808189"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/angeo-24-791-2006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011894653"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/jtech-d-12-00089.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021030988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1364-6826(00)00147-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022784300"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/95rs00713", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023618859"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/2010jtecha1372.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028210275"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/rs020i006p01247", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029196079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/qj.807", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030283578"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jastp.2014.01.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031236734"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1985)042<2156:foeslo>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033429308"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2011gl050120", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034386079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10546-012-9774-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035763227", 
          "https://doi.org/10.1007/s10546-012-9774-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0426(2001)018<0817:vowmbm>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040470886"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/rs023i004p00655", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041222094"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/rs004i012p01179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041619084"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10546-007-9251-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044692475", 
          "https://doi.org/10.1007/s10546-007-9251-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10546-007-9251-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044692475", 
          "https://doi.org/10.1007/s10546-007-9251-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1994)051<0237:deoita>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046921299"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1998)055<2893:fisefc>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048347995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/rs023i006p01013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050967369"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112068001035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053803494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112068001035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053803494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112068001035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053803494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1049/piee.1964.0042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056894339"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/36.485110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061161410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/angeo-35-423-2017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084464816"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf03014515", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085173933", 
          "https://doi.org/10.1007/bf03014515"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40645-017-0133-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090741168", 
          "https://doi.org/10.1186/s40645-017-0133-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tgrs.2017.2772351", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100278347"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "The ShUREX (Shigaraki UAV Radar Experiment) 2015 campaign carried out at the Shigaraki Middle and Upper atmosphere (MU) observatory (Japan) in June 2015 provided a unique opportunity to compare vertical profiles of atmospheric parameters estimated from unmanned aerial vehicle (UAV), balloon, and radar data in the lower troposphere. The present work is intended primarily as a demonstration of the potential offered by combination of these three instruments for studying the small-scale structure and dynamics in the lower troposphere. Here, we focus on data collected almost simultaneously by two instrumented UAVs and two meteorological balloons, near the MU radar operated continuously during the campaign. The UAVs flew along helical ascending and descending paths at a nearly constant horizontal distance from the radar (~ 1.0 km), while the balloons launched from the MU radar site drifted up to ~ 3\u20135 km in the altitude range of comparisons (~ 0.5 to 4.0 km) due to wind advection. Vertical profiles of squared Br\u00fcnt-V\u00e4is\u00e4l\u00e4 frequency N2 and squared vertical gradient of generalized potential refractive index M2 were estimated at a vertical resolution of 20 m from pressure, temperature, and humidity data collected by UAVs and radiosondes. Profiles of M2 were also estimated from MU radar echo power at vertical incidence at a vertical sampling of 20 m and various time resolutions (1\u20134 min). The balloons and the MU radar provided vertical profiles of wind and wind shear S so that two independent estimates of the gradient Richardson number (Ri = N2/S2) could be obtained at a range resolution of 150 m. The two estimates of Ri profiles also showed remarkable agreement at all altitudes. We show that all three instruments detected the same prominent temperature and humidity gradients, down to decameter scales in stratified conditions. These gradients extended horizontally over a few kilometers at least and persisted for hours without significant changes, indicating that the turbulent diffusion was weak. Large discrepancies between N2and M2 profiles derived from the balloon, UAV, and radar data were found in a turbulent layer generated by a Kelvin-Helmholtz (KH) shear flow instability in the height range from 1.80 to 2.15 km. The cause of these discrepancies appears to depend on the stage of the KH billows. ", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s40645-018-0187-4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5874836", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1136393", 
        "issn": [
          "2197-4284"
        ], 
        "name": "Progress in Earth and Planetary Science", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "5"
      }
    ], 
    "name": "Vertical structure of the lower troposphere derived from MU radar, unmanned aerial vehicle, and balloon measurements during ShUREX 2015", 
    "pagination": "29", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "9dd4aaa4f1106b7b677a51de6ff40c2a3c7cf80418f735671dfe5f37eab9b285"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s40645-018-0187-4"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1104331856"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s40645-018-0187-4", 
      "https://app.dimensions.ai/details/publication/pub.1104331856"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T10:30", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000349_0000000349/records_113644_00000004.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs40645-018-0187-4"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s40645-018-0187-4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s40645-018-0187-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s40645-018-0187-4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s40645-018-0187-4'


 

This table displays all metadata directly associated to this object as RDF triples.

195 TRIPLES      21 PREDICATES      54 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s40645-018-0187-4 schema:about anzsrc-for:09
2 anzsrc-for:0915
3 schema:author Ndba044b66b2146e7a559eaf26612bf8f
4 schema:citation sg:pub.10.1007/bf03014515
5 sg:pub.10.1007/s10546-007-9251-0
6 sg:pub.10.1007/s10546-012-9774-x
7 sg:pub.10.1186/s40645-017-0133-x
8 https://doi.org/10.1002/qj.807
9 https://doi.org/10.1016/j.jastp.2014.01.005
10 https://doi.org/10.1016/s1364-6826(00)00147-4
11 https://doi.org/10.1017/s0022112068001035
12 https://doi.org/10.1029/2011gl050120
13 https://doi.org/10.1029/95rs00713
14 https://doi.org/10.1029/rs004i012p01179
15 https://doi.org/10.1029/rs020i006p01247
16 https://doi.org/10.1029/rs023i004p00655
17 https://doi.org/10.1029/rs023i006p01013
18 https://doi.org/10.1029/rs025i004p00477
19 https://doi.org/10.1049/piee.1964.0042
20 https://doi.org/10.1109/36.485110
21 https://doi.org/10.1109/tgrs.2017.2772351
22 https://doi.org/10.1175/1520-0426(2001)018<0817:vowmbm>2.0.co;2
23 https://doi.org/10.1175/1520-0469(1985)042<2156:foeslo>2.0.co;2
24 https://doi.org/10.1175/1520-0469(1994)051<0237:deoita>2.0.co;2
25 https://doi.org/10.1175/1520-0469(1998)055<2893:fisefc>2.0.co;2
26 https://doi.org/10.1175/2010jtecha1372.1
27 https://doi.org/10.1175/jtech-d-12-00089.1
28 https://doi.org/10.5194/angeo-19-899-2001
29 https://doi.org/10.5194/angeo-24-791-2006
30 https://doi.org/10.5194/angeo-35-423-2017
31 schema:datePublished 2018-12
32 schema:datePublishedReg 2018-12-01
33 schema:description The ShUREX (Shigaraki UAV Radar Experiment) 2015 campaign carried out at the Shigaraki Middle and Upper atmosphere (MU) observatory (Japan) in June 2015 provided a unique opportunity to compare vertical profiles of atmospheric parameters estimated from unmanned aerial vehicle (UAV), balloon, and radar data in the lower troposphere. The present work is intended primarily as a demonstration of the potential offered by combination of these three instruments for studying the small-scale structure and dynamics in the lower troposphere. Here, we focus on data collected almost simultaneously by two instrumented UAVs and two meteorological balloons, near the MU radar operated continuously during the campaign. The UAVs flew along helical ascending and descending paths at a nearly constant horizontal distance from the radar (~ 1.0 km), while the balloons launched from the MU radar site drifted up to ~ 3–5 km in the altitude range of comparisons (~ 0.5 to 4.0 km) due to wind advection. Vertical profiles of squared Brünt-Väisälä frequency N2 and squared vertical gradient of generalized potential refractive index M2 were estimated at a vertical resolution of 20 m from pressure, temperature, and humidity data collected by UAVs and radiosondes. Profiles of M2 were also estimated from MU radar echo power at vertical incidence at a vertical sampling of 20 m and various time resolutions (1–4 min). The balloons and the MU radar provided vertical profiles of wind and wind shear S so that two independent estimates of the gradient Richardson number (Ri = N2/S2) could be obtained at a range resolution of 150 m. The two estimates of Ri profiles also showed remarkable agreement at all altitudes. We show that all three instruments detected the same prominent temperature and humidity gradients, down to decameter scales in stratified conditions. These gradients extended horizontally over a few kilometers at least and persisted for hours without significant changes, indicating that the turbulent diffusion was weak. Large discrepancies between N2and M2 profiles derived from the balloon, UAV, and radar data were found in a turbulent layer generated by a Kelvin-Helmholtz (KH) shear flow instability in the height range from 1.80 to 2.15 km. The cause of these discrepancies appears to depend on the stage of the KH billows.
34 schema:genre research_article
35 schema:inLanguage en
36 schema:isAccessibleForFree true
37 schema:isPartOf N1466f0a774dd45d1af0fbf54d6190e7d
38 N4972e331a81e43f7b43dbe38c99c73ea
39 sg:journal.1136393
40 schema:name Vertical structure of the lower troposphere derived from MU radar, unmanned aerial vehicle, and balloon measurements during ShUREX 2015
41 schema:pagination 29
42 schema:productId N47a0b43083024d79bab50d1df6f257a8
43 N98c542b5d73944d4b3fb38a13b47138a
44 Nca2020e137bd48d1abcd7dbe470d2865
45 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104331856
46 https://doi.org/10.1186/s40645-018-0187-4
47 schema:sdDatePublished 2019-04-11T10:30
48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
49 schema:sdPublisher N56ae802b627442b8950885308374f53a
50 schema:url https://link.springer.com/10.1186%2Fs40645-018-0187-4
51 sgo:license sg:explorer/license/
52 sgo:sdDataset articles
53 rdf:type schema:ScholarlyArticle
54 N1466f0a774dd45d1af0fbf54d6190e7d schema:volumeNumber 5
55 rdf:type schema:PublicationVolume
56 N2813a205717848969dd00296ac013908 rdf:first sg:person.013500043445.62
57 rdf:rest N5c29f3529ba844309361cd3b5eaf58c0
58 N450664bc0e964bd0a4b325884630fa90 rdf:first sg:person.011357206365.90
59 rdf:rest rdf:nil
60 N47a0b43083024d79bab50d1df6f257a8 schema:name dimensions_id
61 schema:value pub.1104331856
62 rdf:type schema:PropertyValue
63 N4972e331a81e43f7b43dbe38c99c73ea schema:issueNumber 1
64 rdf:type schema:PublicationIssue
65 N56ae802b627442b8950885308374f53a schema:name Springer Nature - SN SciGraph project
66 rdf:type schema:Organization
67 N5c29f3529ba844309361cd3b5eaf58c0 rdf:first sg:person.016675237227.13
68 rdf:rest Nf6fe924364894200a2ae544f8bdb306b
69 N98c542b5d73944d4b3fb38a13b47138a schema:name doi
70 schema:value 10.1186/s40645-018-0187-4
71 rdf:type schema:PropertyValue
72 Nca2020e137bd48d1abcd7dbe470d2865 schema:name readcube_id
73 schema:value 9dd4aaa4f1106b7b677a51de6ff40c2a3c7cf80418f735671dfe5f37eab9b285
74 rdf:type schema:PropertyValue
75 Nd34d08ad7692424c9b6388988f7bed44 rdf:first sg:person.07513074607.55
76 rdf:rest N2813a205717848969dd00296ac013908
77 Ndade13d2c1514c89b6ee87647ced6f61 rdf:first sg:person.015367202214.05
78 rdf:rest N450664bc0e964bd0a4b325884630fa90
79 Ndba044b66b2146e7a559eaf26612bf8f rdf:first sg:person.014054430011.55
80 rdf:rest Nd34d08ad7692424c9b6388988f7bed44
81 Nf6fe924364894200a2ae544f8bdb306b rdf:first sg:person.010261347426.10
82 rdf:rest Ndade13d2c1514c89b6ee87647ced6f61
83 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
84 schema:name Engineering
85 rdf:type schema:DefinedTerm
86 anzsrc-for:0915 schema:inDefinedTermSet anzsrc-for:
87 schema:name Interdisciplinary Engineering
88 rdf:type schema:DefinedTerm
89 sg:grant.5874836 http://pending.schema.org/fundedItem sg:pub.10.1186/s40645-018-0187-4
90 rdf:type schema:MonetaryGrant
91 sg:journal.1136393 schema:issn 2197-4284
92 schema:name Progress in Earth and Planetary Science
93 rdf:type schema:Periodical
94 sg:person.010261347426.10 schema:affiliation https://www.grid.ac/institutes/grid.258799.8
95 schema:familyName Mixa
96 schema:givenName Tyler
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010261347426.10
98 rdf:type schema:Person
99 sg:person.011357206365.90 schema:affiliation https://www.grid.ac/institutes/grid.266190.a
100 schema:familyName Tsuda
101 schema:givenName Toshitaka
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011357206365.90
103 rdf:type schema:Person
104 sg:person.013500043445.62 schema:affiliation https://www.grid.ac/institutes/grid.266190.a
105 schema:familyName Hashiguchi
106 schema:givenName Hiroyuki
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013500043445.62
108 rdf:type schema:Person
109 sg:person.014054430011.55 schema:affiliation https://www.grid.ac/institutes/grid.12611.35
110 schema:familyName Luce
111 schema:givenName Hubert
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014054430011.55
113 rdf:type schema:Person
114 sg:person.015367202214.05 schema:affiliation https://www.grid.ac/institutes/grid.266190.a
115 schema:familyName Yabuki
116 schema:givenName Masanori
117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015367202214.05
118 rdf:type schema:Person
119 sg:person.016675237227.13 schema:affiliation https://www.grid.ac/institutes/grid.258799.8
120 schema:familyName Lawrence
121 schema:givenName Dale
122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016675237227.13
123 rdf:type schema:Person
124 sg:person.07513074607.55 schema:affiliation https://www.grid.ac/institutes/grid.258799.8
125 schema:familyName Kantha
126 schema:givenName Lakshmi
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07513074607.55
128 rdf:type schema:Person
129 sg:pub.10.1007/bf03014515 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085173933
130 https://doi.org/10.1007/bf03014515
131 rdf:type schema:CreativeWork
132 sg:pub.10.1007/s10546-007-9251-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044692475
133 https://doi.org/10.1007/s10546-007-9251-0
134 rdf:type schema:CreativeWork
135 sg:pub.10.1007/s10546-012-9774-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1035763227
136 https://doi.org/10.1007/s10546-012-9774-x
137 rdf:type schema:CreativeWork
138 sg:pub.10.1186/s40645-017-0133-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1090741168
139 https://doi.org/10.1186/s40645-017-0133-x
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1002/qj.807 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030283578
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.jastp.2014.01.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031236734
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/s1364-6826(00)00147-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022784300
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1017/s0022112068001035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053803494
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1029/2011gl050120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034386079
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1029/95rs00713 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023618859
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1029/rs004i012p01179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041619084
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1029/rs020i006p01247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029196079
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1029/rs023i004p00655 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041222094
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1029/rs023i006p01013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050967369
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1029/rs025i004p00477 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002425022
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1049/piee.1964.0042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056894339
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1109/36.485110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061161410
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1109/tgrs.2017.2772351 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100278347
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1175/1520-0426(2001)018<0817:vowmbm>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040470886
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1175/1520-0469(1985)042<2156:foeslo>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033429308
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1175/1520-0469(1994)051<0237:deoita>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046921299
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1175/1520-0469(1998)055<2893:fisefc>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048347995
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1175/2010jtecha1372.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028210275
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1175/jtech-d-12-00089.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021030988
180 rdf:type schema:CreativeWork
181 https://doi.org/10.5194/angeo-19-899-2001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007808189
182 rdf:type schema:CreativeWork
183 https://doi.org/10.5194/angeo-24-791-2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011894653
184 rdf:type schema:CreativeWork
185 https://doi.org/10.5194/angeo-35-423-2017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084464816
186 rdf:type schema:CreativeWork
187 https://www.grid.ac/institutes/grid.12611.35 schema:alternateName Universite De Toulon Et Du Var
188 schema:name Meditterranean Insitute of Oceanography, CNRS/INSU, UMR7294, IRD, Université de Toulon, La Garde, France
189 rdf:type schema:Organization
190 https://www.grid.ac/institutes/grid.258799.8 schema:alternateName Kyoto University
191 schema:name Research Institute for Sustainable Humanosphere, Kyoto University, Kyoto, Japan
192 rdf:type schema:Organization
193 https://www.grid.ac/institutes/grid.266190.a schema:alternateName University of Colorado Boulder
194 schema:name Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO, USA
195 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...