Seasonal and annual variation of AIRS retrieved CO2 over India during 2003–2011 View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-06

AUTHORS

Anju Gupta, S K Dhaka, Y Matsumi, R Imasu, S Hayashida, Vir Singh

ABSTRACT

The present study shows spatio-temporal variability in carbon dioxide (CO2) in the mid-tropospheric region over India (0–32oN, 60–100oE) during 2003–2011. The CO2 data used in the study is retrieved from Atmospheric Infra-Red Sounder (AIRS). Analysis of 9 yrs of data shows that the CO2 exhibits a linear increasing trend of 2.01 ppm/year. Besides displaying the linear increasing trend, data show strong seasonal and annual variability. Concentration of CO2 is observed to be highest around April–May (summer months), which decreases by 4–5 ppm during the monsoon months. Seasonal decrease in CO2 concentration appeared to be influenced by the monsoonal activity. Low OLR (proxy of convection) associated with high rainfall during summer monsoon via increasing vegetation index (NDVI) appears to be the primary cause for the seasonal decrease in CO2 through photosynthesis. Correlation coefficient between CO2 and NDVI is of the order of –0.90 suggesting vegetation as a seasonal sink of CO2. Decrease in CO2 concentration takes place at a delay of 2–3 months of rainfall. However, convection seems to be another component, which causes uplifting of CO2 during dry summer (April and May) making high concentration in the mid-troposphere as shown by increase in the planetary boundary layer (PBL) height in this period. Eastward propagating intra-seasonal oscillations with period 30–40 days in OLR anomalies are found to modulate (with a fluctuation of 1–2 ppm) mid-tropospheric CO2. Analysis of seasonal anomalies in CO2 over four different regions (northern, southern, western and eastern) of India is also being investigated. The regional variability of CO2 in northern region show marginal larger values suggesting more anthropogenic activities especially during late winter. More... »

PAGES

92

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12040-019-1108-7

DOI

http://dx.doi.org/10.1007/s12040-019-1108-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113055746


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/2008/0401", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Atmospheric Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Delhi", 
          "id": "https://www.grid.ac/institutes/grid.8195.5", 
          "name": [
            "Radio and Atmospheric Lab, Department of Physics, Rajdhani College, University of Delhi, 110 015, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gupta", 
        "givenName": "Anju", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Delhi", 
          "id": "https://www.grid.ac/institutes/grid.8195.5", 
          "name": [
            "Radio and Atmospheric Lab, Department of Physics, Rajdhani College, University of Delhi, 110 015, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dhaka", 
        "givenName": "S K", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nagoya University", 
          "id": "https://www.grid.ac/institutes/grid.27476.30", 
          "name": [
            "ISEE, Nagoya University, Nagoya, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matsumi", 
        "givenName": "Y", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Imasu", 
        "givenName": "R", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nara Women's University", 
          "id": "https://www.grid.ac/institutes/grid.174568.9", 
          "name": [
            "Nara Women\u2019s University, Nara, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hayashida", 
        "givenName": "S", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "West Bengal University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.440742.1", 
          "name": [
            "Guru Nanak Institute of Technology, Kolkata, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Singh", 
        "givenName": "Vir", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.atmosres.2012.02.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000529979"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12040-012-0254-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007194167", 
          "https://doi.org/10.1007/s12040-012-0254-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2008gl035022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007392404"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2003jd003489", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008593305"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2002gl014745", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009044355"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(1992)120<1900:caawtc>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011449565"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005gl024165", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012143642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/asl.277", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013607236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/asl.277", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013607236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2003jd003756", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015232911"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12040-011-0112-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017284674", 
          "https://doi.org/10.1007/s12040-011-0112-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2151/jmsj.84a.19", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018657159"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2006gl027026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022976750"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005jd006116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027226942"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005jd006116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027226942"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2010gl042823", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029248895"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005gl022907", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032737898"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005gl022907", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032737898"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005jd007020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034363267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(1980)108<1840:otmcza>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035091186"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2008jd010739", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037128078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(1994)122<0814:ootdto>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037164374"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.atmosenv.2012.11.040", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039737970"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/isprsarchives-xxxviii-8-w20-96-2011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040612059"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0442(2002)015<0722:ttboaa>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042821558"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2010jd014340", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044527262"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1364-6826(01)00040-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046526015"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2151/jmsj.81.1185", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050430346"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tgrs.2002.808247", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061608727"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tgrs.2002.808356", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061608744"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2151/jmsj1965.57.3_227", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084918172"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2151/jmsj1965.77.3_753", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085028962"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02843255", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085560754", 
          "https://doi.org/10.1007/bf02843255"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-06", 
    "datePublishedReg": "2019-06-01", 
    "description": "The present study shows spatio-temporal variability in carbon dioxide (CO2) in the mid-tropospheric region over India (0\u201332oN, 60\u2013100oE) during 2003\u20132011. The CO2 data used in the study is retrieved from Atmospheric Infra-Red Sounder (AIRS). Analysis of 9 yrs of data shows that the CO2 exhibits a linear increasing trend of 2.01 ppm/year. Besides displaying the linear increasing trend, data show strong seasonal and annual variability. Concentration of CO2 is observed to be highest around April\u2013May (summer months), which decreases by 4\u20135 ppm during the monsoon months. Seasonal decrease in CO2 concentration appeared to be influenced by the monsoonal activity. Low OLR (proxy of convection) associated with high rainfall during summer monsoon via increasing vegetation index (NDVI) appears to be the primary cause for the seasonal decrease in CO2 through photosynthesis. Correlation coefficient between CO2 and NDVI is of the order of \u20130.90 suggesting vegetation as a seasonal sink of CO2. Decrease in CO2 concentration takes place at a delay of 2\u20133 months of rainfall. However, convection seems to be another component, which causes uplifting of CO2 during dry summer (April and May) making high concentration in the mid-troposphere as shown by increase in the planetary boundary layer (PBL) height in this period. Eastward propagating intra-seasonal oscillations with period 30\u201340 days in OLR anomalies are found to modulate (with a fluctuation of 1\u20132 ppm) mid-tropospheric CO2. Analysis of seasonal anomalies in CO2 over four different regions (northern, southern, western and eastern) of India is also being investigated. The regional variability of CO2 in northern region show marginal larger values suggesting more anthropogenic activities especially during late winter.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12040-019-1108-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136531", 
        "issn": [
          "0253-4126", 
          "0973-774X"
        ], 
        "name": "Journal of Earth System Science", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "128"
      }
    ], 
    "name": "Seasonal and annual variation of AIRS retrieved CO2 over India during 2003\u20132011", 
    "pagination": "92", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8279b2fa313594a63ae5384c44e8a12fac2588c67a90a5aa7ecf79b80c8be50c"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12040-019-1108-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113055746"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12040-019-1108-7", 
      "https://app.dimensions.ai/details/publication/pub.1113055746"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:19", 
    "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/v90/0000000368_0000000368/records_78956_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs12040-019-1108-7"
  }
]
 

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.10.1007/s12040-019-1108-7'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12040-019-1108-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12040-019-1108-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12040-019-1108-7'


 

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

195 TRIPLES      21 PREDICATES      57 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12040-019-1108-7 schema:about anzsrc-for:04
2 anzsrc-for:0401
3 schema:author Nc2c38c2c845d4f11b56994705c3cef68
4 schema:citation sg:pub.10.1007/bf02843255
5 sg:pub.10.1007/s12040-011-0112-3
6 sg:pub.10.1007/s12040-012-0254-y
7 https://doi.org/10.1002/asl.277
8 https://doi.org/10.1016/j.atmosenv.2012.11.040
9 https://doi.org/10.1016/j.atmosres.2012.02.003
10 https://doi.org/10.1016/s1364-6826(01)00040-2
11 https://doi.org/10.1029/2002gl014745
12 https://doi.org/10.1029/2003jd003489
13 https://doi.org/10.1029/2003jd003756
14 https://doi.org/10.1029/2005gl022907
15 https://doi.org/10.1029/2005gl024165
16 https://doi.org/10.1029/2005jd006116
17 https://doi.org/10.1029/2005jd007020
18 https://doi.org/10.1029/2006gl027026
19 https://doi.org/10.1029/2008gl035022
20 https://doi.org/10.1029/2008jd010739
21 https://doi.org/10.1029/2010gl042823
22 https://doi.org/10.1029/2010jd014340
23 https://doi.org/10.1109/tgrs.2002.808247
24 https://doi.org/10.1109/tgrs.2002.808356
25 https://doi.org/10.1175/1520-0442(2002)015<0722:ttboaa>2.0.co;2
26 https://doi.org/10.1175/1520-0493(1980)108<1840:otmcza>2.0.co;2
27 https://doi.org/10.1175/1520-0493(1992)120<1900:caawtc>2.0.co;2
28 https://doi.org/10.1175/1520-0493(1994)122<0814:ootdto>2.0.co;2
29 https://doi.org/10.2151/jmsj.81.1185
30 https://doi.org/10.2151/jmsj.84a.19
31 https://doi.org/10.2151/jmsj1965.57.3_227
32 https://doi.org/10.2151/jmsj1965.77.3_753
33 https://doi.org/10.5194/isprsarchives-xxxviii-8-w20-96-2011
34 schema:datePublished 2019-06
35 schema:datePublishedReg 2019-06-01
36 schema:description The present study shows spatio-temporal variability in carbon dioxide (CO2) in the mid-tropospheric region over India (0–32oN, 60–100oE) during 2003–2011. The CO2 data used in the study is retrieved from Atmospheric Infra-Red Sounder (AIRS). Analysis of 9 yrs of data shows that the CO2 exhibits a linear increasing trend of 2.01 ppm/year. Besides displaying the linear increasing trend, data show strong seasonal and annual variability. Concentration of CO2 is observed to be highest around April–May (summer months), which decreases by 4–5 ppm during the monsoon months. Seasonal decrease in CO2 concentration appeared to be influenced by the monsoonal activity. Low OLR (proxy of convection) associated with high rainfall during summer monsoon via increasing vegetation index (NDVI) appears to be the primary cause for the seasonal decrease in CO2 through photosynthesis. Correlation coefficient between CO2 and NDVI is of the order of –0.90 suggesting vegetation as a seasonal sink of CO2. Decrease in CO2 concentration takes place at a delay of 2–3 months of rainfall. However, convection seems to be another component, which causes uplifting of CO2 during dry summer (April and May) making high concentration in the mid-troposphere as shown by increase in the planetary boundary layer (PBL) height in this period. Eastward propagating intra-seasonal oscillations with period 30–40 days in OLR anomalies are found to modulate (with a fluctuation of 1–2 ppm) mid-tropospheric CO2. Analysis of seasonal anomalies in CO2 over four different regions (northern, southern, western and eastern) of India is also being investigated. The regional variability of CO2 in northern region show marginal larger values suggesting more anthropogenic activities especially during late winter.
37 schema:genre research_article
38 schema:inLanguage en
39 schema:isAccessibleForFree false
40 schema:isPartOf N860fdc8054514035b36ae4f4fac0b030
41 N9bc2309759294bd9a3f7114356a021cf
42 sg:journal.1136531
43 schema:name Seasonal and annual variation of AIRS retrieved CO2 over India during 2003–2011
44 schema:pagination 92
45 schema:productId N0466cbc16f484184b4b0dbbf4fbf5840
46 Ndd07e9abeb5c4436af3b1b8277e3c6db
47 Ne873ddfe5c8f44b5aa3c02a772352d67
48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113055746
49 https://doi.org/10.1007/s12040-019-1108-7
50 schema:sdDatePublished 2019-04-11T13:19
51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
52 schema:sdPublisher N5ee668810fb8447f88e5247c7859902d
53 schema:url https://link.springer.com/10.1007%2Fs12040-019-1108-7
54 sgo:license sg:explorer/license/
55 sgo:sdDataset articles
56 rdf:type schema:ScholarlyArticle
57 N00d0e2dd7846478fb35670d73d39e688 rdf:first N99cdf8981f80480c9ab5df74bcfad09e
58 rdf:rest N4557e7621ff1412dbe85119f64a333ba
59 N0466cbc16f484184b4b0dbbf4fbf5840 schema:name readcube_id
60 schema:value 8279b2fa313594a63ae5384c44e8a12fac2588c67a90a5aa7ecf79b80c8be50c
61 rdf:type schema:PropertyValue
62 N190b5ff0a875430281ae66331fe65711 schema:affiliation https://www.grid.ac/institutes/grid.8195.5
63 schema:familyName Gupta
64 schema:givenName Anju
65 rdf:type schema:Person
66 N3365bcf4ade14723b5fa9ba6da4d70d3 rdf:first Nc225d85015d94dc88191f371b24efd99
67 rdf:rest Neb9b9914f41645b891672012b2ad7d48
68 N4557e7621ff1412dbe85119f64a333ba rdf:first N9b647f21112e45848d858a36a9d17626
69 rdf:rest N3365bcf4ade14723b5fa9ba6da4d70d3
70 N5ee668810fb8447f88e5247c7859902d schema:name Springer Nature - SN SciGraph project
71 rdf:type schema:Organization
72 N860fdc8054514035b36ae4f4fac0b030 schema:volumeNumber 128
73 rdf:type schema:PublicationVolume
74 N8fabcc777f27444f9cdaa6239b4b29e2 schema:affiliation https://www.grid.ac/institutes/grid.8195.5
75 schema:familyName Dhaka
76 schema:givenName S K
77 rdf:type schema:Person
78 N9645ba11ad1940818f73d720bee2da70 schema:affiliation https://www.grid.ac/institutes/grid.440742.1
79 schema:familyName Singh
80 schema:givenName Vir
81 rdf:type schema:Person
82 N99cdf8981f80480c9ab5df74bcfad09e schema:affiliation https://www.grid.ac/institutes/grid.27476.30
83 schema:familyName Matsumi
84 schema:givenName Y
85 rdf:type schema:Person
86 N9b647f21112e45848d858a36a9d17626 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
87 schema:familyName Imasu
88 schema:givenName R
89 rdf:type schema:Person
90 N9bc2309759294bd9a3f7114356a021cf schema:issueNumber 4
91 rdf:type schema:PublicationIssue
92 Nc225d85015d94dc88191f371b24efd99 schema:affiliation https://www.grid.ac/institutes/grid.174568.9
93 schema:familyName Hayashida
94 schema:givenName S
95 rdf:type schema:Person
96 Nc2c38c2c845d4f11b56994705c3cef68 rdf:first N190b5ff0a875430281ae66331fe65711
97 rdf:rest Nc6cf5f8e83fb4550976a7bf890e620b9
98 Nc6cf5f8e83fb4550976a7bf890e620b9 rdf:first N8fabcc777f27444f9cdaa6239b4b29e2
99 rdf:rest N00d0e2dd7846478fb35670d73d39e688
100 Ndd07e9abeb5c4436af3b1b8277e3c6db schema:name dimensions_id
101 schema:value pub.1113055746
102 rdf:type schema:PropertyValue
103 Ne873ddfe5c8f44b5aa3c02a772352d67 schema:name doi
104 schema:value 10.1007/s12040-019-1108-7
105 rdf:type schema:PropertyValue
106 Neb9b9914f41645b891672012b2ad7d48 rdf:first N9645ba11ad1940818f73d720bee2da70
107 rdf:rest rdf:nil
108 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
109 schema:name Earth Sciences
110 rdf:type schema:DefinedTerm
111 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
112 schema:name Atmospheric Sciences
113 rdf:type schema:DefinedTerm
114 sg:journal.1136531 schema:issn 0253-4126
115 0973-774X
116 schema:name Journal of Earth System Science
117 rdf:type schema:Periodical
118 sg:pub.10.1007/bf02843255 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085560754
119 https://doi.org/10.1007/bf02843255
120 rdf:type schema:CreativeWork
121 sg:pub.10.1007/s12040-011-0112-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017284674
122 https://doi.org/10.1007/s12040-011-0112-3
123 rdf:type schema:CreativeWork
124 sg:pub.10.1007/s12040-012-0254-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1007194167
125 https://doi.org/10.1007/s12040-012-0254-y
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1002/asl.277 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013607236
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.atmosenv.2012.11.040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039737970
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.atmosres.2012.02.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000529979
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/s1364-6826(01)00040-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046526015
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1029/2002gl014745 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009044355
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1029/2003jd003489 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008593305
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1029/2003jd003756 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015232911
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1029/2005gl022907 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032737898
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1029/2005gl024165 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012143642
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1029/2005jd006116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027226942
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1029/2005jd007020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034363267
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1029/2006gl027026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022976750
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1029/2008gl035022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007392404
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1029/2008jd010739 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037128078
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1029/2010gl042823 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029248895
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1029/2010jd014340 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044527262
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1109/tgrs.2002.808247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061608727
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1109/tgrs.2002.808356 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061608744
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1175/1520-0442(2002)015<0722:ttboaa>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042821558
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1175/1520-0493(1980)108<1840:otmcza>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035091186
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1175/1520-0493(1992)120<1900:caawtc>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011449565
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1175/1520-0493(1994)122<0814:ootdto>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037164374
170 rdf:type schema:CreativeWork
171 https://doi.org/10.2151/jmsj.81.1185 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050430346
172 rdf:type schema:CreativeWork
173 https://doi.org/10.2151/jmsj.84a.19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018657159
174 rdf:type schema:CreativeWork
175 https://doi.org/10.2151/jmsj1965.57.3_227 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084918172
176 rdf:type schema:CreativeWork
177 https://doi.org/10.2151/jmsj1965.77.3_753 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085028962
178 rdf:type schema:CreativeWork
179 https://doi.org/10.5194/isprsarchives-xxxviii-8-w20-96-2011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040612059
180 rdf:type schema:CreativeWork
181 https://www.grid.ac/institutes/grid.174568.9 schema:alternateName Nara Women's University
182 schema:name Nara Women’s University, Nara, Japan
183 rdf:type schema:Organization
184 https://www.grid.ac/institutes/grid.26999.3d schema:alternateName University of Tokyo
185 schema:name Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan
186 rdf:type schema:Organization
187 https://www.grid.ac/institutes/grid.27476.30 schema:alternateName Nagoya University
188 schema:name ISEE, Nagoya University, Nagoya, Japan
189 rdf:type schema:Organization
190 https://www.grid.ac/institutes/grid.440742.1 schema:alternateName West Bengal University of Technology
191 schema:name Guru Nanak Institute of Technology, Kolkata, India
192 rdf:type schema:Organization
193 https://www.grid.ac/institutes/grid.8195.5 schema:alternateName University of Delhi
194 schema:name Radio and Atmospheric Lab, Department of Physics, Rajdhani College, University of Delhi, 110 015, New Delhi, India
195 rdf:type schema:Organization
 




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


...