Impact of cloud microphysical processes on the simulation of Typhoon Rananim near shore. Part I: Cloud structure and precipitation features View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-08

AUTHORS

Rui Cheng, Rucong Yu, Yunfei Fu, Youping Xu

ABSTRACT

By using the Advanced Regional Eta-coordinate Model (AREM), the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations. Five sets of experiments are designed to investigate the effects of the cloud microphysical processes on the model cloud structure and precipitation features. The importance of the ice-phase microphysics, the cooling effect related to microphysical characteristics change, and the influence of terminal velocity of graupel are examined. The results indicate that the cloud microphysical processes impact more on the cloud development and precipitation features of the typhoon than on its intensity and track. Big differences in the distribution pattern and content of hydrometeors, and types and amount of rainfall occur in the five experiments, resulting in different heating and cooling effects. The largest difference of 24-h rain rate reaches 52.5 mm h−1. The results are summarized as follows: 1) when the cooling effect due to the evaporation of rain water is excluded, updrafts in the typhoon’s inner core are the strongest with the maximum vertical velocity of −19 Pa s−1 and rain water and graupel grow most dominantly with their mixing ratios increased by 1.8 and 2.5 g kg−1, respectively, compared with the control experiment; 2) the melting of snow and graupel affects the growth of rain water mainly in the spiral rainbands, but much less significantly in the eyewall area; 3) the warm cloud microphysical process produces the smallest rainfall area and the largest percentage of convective precipitation (63.19%), while the largest rainfall area and the smallest percentage of convective precipitation (48.85%) are generated when the terminal velocity of graupel is weakened by half. More... »

PAGES

441

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13351-011-0405-0

DOI

http://dx.doi.org/10.1007/s13351-011-0405-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015687136


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": "Chinese Academy of Sciences", 
          "id": "https://www.grid.ac/institutes/grid.9227.e", 
          "name": [
            "State Key Laboratory of Numerical Simulation for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, CAS, 100029, Beijing, China", 
            "Graduate School of the Chinese Academy of Sciences, 100049, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cheng", 
        "givenName": "Rui", 
        "id": "sg:person.07463411534.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07463411534.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Atmospheric Physics", 
          "id": "https://www.grid.ac/institutes/grid.424023.3", 
          "name": [
            "State Key Laboratory of Numerical Simulation for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, CAS, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yu", 
        "givenName": "Rucong", 
        "id": "sg:person.015173077562.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015173077562.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Science and Technology of China", 
          "id": "https://www.grid.ac/institutes/grid.59053.3a", 
          "name": [
            "University of Science and Technology of China, 230026, Hefei, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fu", 
        "givenName": "Yunfei", 
        "id": "sg:person.013055300500.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013055300500.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Chinese Academy of Sciences", 
          "id": "https://www.grid.ac/institutes/grid.9227.e", 
          "name": [
            "State Key Laboratory of Numerical Simulation for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, CAS, 100029, Beijing, China", 
            "Graduate School of the Chinese Academy of Sciences, 100049, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xu", 
        "givenName": "Youping", 
        "id": "sg:person.012451313534.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012451313534.72"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1175/jas3597.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007050420"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/qj.49712354406", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010358074"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1984)041<2836:roapip>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015991146"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02661283", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022636376", 
          "https://doi.org/10.1007/bf02661283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02661283", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022636376", 
          "https://doi.org/10.1007/bf02661283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1984)041<1169:hsaeas>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025642332"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(2002)130<3022:aesotc>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025699358"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(1997)125<3073:amnsoh>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026363934"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(2001)129<1370:aesotc>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035777539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0450-30.7.985", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036535704"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0442(1998)011<2628:iobaaf>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037136199"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02658169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040471244", 
          "https://doi.org/10.1007/bf02658169"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02658169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040471244", 
          "https://doi.org/10.1007/bf02658169"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/mwr2989.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040671476"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/mwr2989.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040671476"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00703-006-0248-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043148658", 
          "https://doi.org/10.1007/s00703-006-0248-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00703-006-0248-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043148658", 
          "https://doi.org/10.1007/s00703-006-0248-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/jas3599.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051143909"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0442(1993)006<1825:lvnbld>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063421282"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-08", 
    "datePublishedReg": "2011-08-01", 
    "description": "By using the Advanced Regional Eta-coordinate Model (AREM), the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations. Five sets of experiments are designed to investigate the effects of the cloud microphysical processes on the model cloud structure and precipitation features. The importance of the ice-phase microphysics, the cooling effect related to microphysical characteristics change, and the influence of terminal velocity of graupel are examined. The results indicate that the cloud microphysical processes impact more on the cloud development and precipitation features of the typhoon than on its intensity and track. Big differences in the distribution pattern and content of hydrometeors, and types and amount of rainfall occur in the five experiments, resulting in different heating and cooling effects. The largest difference of 24-h rain rate reaches 52.5 mm h\u22121. The results are summarized as follows: 1) when the cooling effect due to the evaporation of rain water is excluded, updrafts in the typhoon\u2019s inner core are the strongest with the maximum vertical velocity of \u221219 Pa s\u22121 and rain water and graupel grow most dominantly with their mixing ratios increased by 1.8 and 2.5 g kg\u22121, respectively, compared with the control experiment; 2) the melting of snow and graupel affects the growth of rain water mainly in the spiral rainbands, but much less significantly in the eyewall area; 3) the warm cloud microphysical process produces the smallest rainfall area and the largest percentage of convective precipitation (63.19%), while the largest rainfall area and the smallest percentage of convective precipitation (48.85%) are generated when the terminal velocity of graupel is weakened by half.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s13351-011-0405-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1144445", 
        "issn": [
          "0894-0525", 
          "2191-4788"
        ], 
        "name": "Acta Meteorologica Sinica", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "25"
      }
    ], 
    "name": "Impact of cloud microphysical processes on the simulation of Typhoon Rananim near shore. Part I: Cloud structure and precipitation features", 
    "pagination": "441", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "4abe10ff835f122e625288b0f3f59628cf8e1d987a7e43e6f35c120701945204"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s13351-011-0405-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1015687136"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s13351-011-0405-0", 
      "https://app.dimensions.ai/details/publication/pub.1015687136"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T23:26", 
    "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/v90/0000000001_0000000264/records_8693_00000521.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs13351-011-0405-0"
  }
]
 

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/s13351-011-0405-0'

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/s13351-011-0405-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13351-011-0405-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13351-011-0405-0'


 

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

137 TRIPLES      21 PREDICATES      42 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s13351-011-0405-0 schema:about anzsrc-for:04
2 anzsrc-for:0401
3 schema:author N63cefc5aecac437aba22235e3fb8689d
4 schema:citation sg:pub.10.1007/bf02658169
5 sg:pub.10.1007/bf02661283
6 sg:pub.10.1007/s00703-006-0248-x
7 https://doi.org/10.1002/qj.49712354406
8 https://doi.org/10.1175/1520-0442(1993)006<1825:lvnbld>2.0.co;2
9 https://doi.org/10.1175/1520-0442(1998)011<2628:iobaaf>2.0.co;2
10 https://doi.org/10.1175/1520-0450-30.7.985
11 https://doi.org/10.1175/1520-0469(1984)041<1169:hsaeas>2.0.co;2
12 https://doi.org/10.1175/1520-0469(1984)041<2836:roapip>2.0.co;2
13 https://doi.org/10.1175/1520-0493(1997)125<3073:amnsoh>2.0.co;2
14 https://doi.org/10.1175/1520-0493(2001)129<1370:aesotc>2.0.co;2
15 https://doi.org/10.1175/1520-0493(2002)130<3022:aesotc>2.0.co;2
16 https://doi.org/10.1175/jas3597.1
17 https://doi.org/10.1175/jas3599.1
18 https://doi.org/10.1175/mwr2989.1
19 schema:datePublished 2011-08
20 schema:datePublishedReg 2011-08-01
21 schema:description By using the Advanced Regional Eta-coordinate Model (AREM), the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations. Five sets of experiments are designed to investigate the effects of the cloud microphysical processes on the model cloud structure and precipitation features. The importance of the ice-phase microphysics, the cooling effect related to microphysical characteristics change, and the influence of terminal velocity of graupel are examined. The results indicate that the cloud microphysical processes impact more on the cloud development and precipitation features of the typhoon than on its intensity and track. Big differences in the distribution pattern and content of hydrometeors, and types and amount of rainfall occur in the five experiments, resulting in different heating and cooling effects. The largest difference of 24-h rain rate reaches 52.5 mm h−1. The results are summarized as follows: 1) when the cooling effect due to the evaporation of rain water is excluded, updrafts in the typhoon’s inner core are the strongest with the maximum vertical velocity of −19 Pa s−1 and rain water and graupel grow most dominantly with their mixing ratios increased by 1.8 and 2.5 g kg−1, respectively, compared with the control experiment; 2) the melting of snow and graupel affects the growth of rain water mainly in the spiral rainbands, but much less significantly in the eyewall area; 3) the warm cloud microphysical process produces the smallest rainfall area and the largest percentage of convective precipitation (63.19%), while the largest rainfall area and the smallest percentage of convective precipitation (48.85%) are generated when the terminal velocity of graupel is weakened by half.
22 schema:genre research_article
23 schema:inLanguage en
24 schema:isAccessibleForFree false
25 schema:isPartOf N20907e23837642728809224d35d22a35
26 N51f2dba251f74c2b8bcdb220063b4dbd
27 sg:journal.1144445
28 schema:name Impact of cloud microphysical processes on the simulation of Typhoon Rananim near shore. Part I: Cloud structure and precipitation features
29 schema:pagination 441
30 schema:productId N0a83e4dd2ba44d488f11684c4339f520
31 N1a091ee8e1054a89806b878fede1b23f
32 Nb6dbad14418443c08bf8d701eeed3816
33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015687136
34 https://doi.org/10.1007/s13351-011-0405-0
35 schema:sdDatePublished 2019-04-10T23:26
36 schema:sdLicense https://scigraph.springernature.com/explorer/license/
37 schema:sdPublisher N6a6bd33a30944bbaac795c0783cff8df
38 schema:url http://link.springer.com/10.1007%2Fs13351-011-0405-0
39 sgo:license sg:explorer/license/
40 sgo:sdDataset articles
41 rdf:type schema:ScholarlyArticle
42 N0a83e4dd2ba44d488f11684c4339f520 schema:name dimensions_id
43 schema:value pub.1015687136
44 rdf:type schema:PropertyValue
45 N1a091ee8e1054a89806b878fede1b23f schema:name readcube_id
46 schema:value 4abe10ff835f122e625288b0f3f59628cf8e1d987a7e43e6f35c120701945204
47 rdf:type schema:PropertyValue
48 N20907e23837642728809224d35d22a35 schema:volumeNumber 25
49 rdf:type schema:PublicationVolume
50 N4f4715276441422299e437435c312ca4 rdf:first sg:person.013055300500.18
51 rdf:rest N64e6b12059914bfe9a9c1490af14acbf
52 N51f2dba251f74c2b8bcdb220063b4dbd schema:issueNumber 4
53 rdf:type schema:PublicationIssue
54 N63cefc5aecac437aba22235e3fb8689d rdf:first sg:person.07463411534.96
55 rdf:rest Na61ffded55f647c58899aadfe0a4a829
56 N64e6b12059914bfe9a9c1490af14acbf rdf:first sg:person.012451313534.72
57 rdf:rest rdf:nil
58 N6a6bd33a30944bbaac795c0783cff8df schema:name Springer Nature - SN SciGraph project
59 rdf:type schema:Organization
60 Na61ffded55f647c58899aadfe0a4a829 rdf:first sg:person.015173077562.22
61 rdf:rest N4f4715276441422299e437435c312ca4
62 Nb6dbad14418443c08bf8d701eeed3816 schema:name doi
63 schema:value 10.1007/s13351-011-0405-0
64 rdf:type schema:PropertyValue
65 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
66 schema:name Earth Sciences
67 rdf:type schema:DefinedTerm
68 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
69 schema:name Atmospheric Sciences
70 rdf:type schema:DefinedTerm
71 sg:journal.1144445 schema:issn 0894-0525
72 2191-4788
73 schema:name Acta Meteorologica Sinica
74 rdf:type schema:Periodical
75 sg:person.012451313534.72 schema:affiliation https://www.grid.ac/institutes/grid.9227.e
76 schema:familyName Xu
77 schema:givenName Youping
78 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012451313534.72
79 rdf:type schema:Person
80 sg:person.013055300500.18 schema:affiliation https://www.grid.ac/institutes/grid.59053.3a
81 schema:familyName Fu
82 schema:givenName Yunfei
83 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013055300500.18
84 rdf:type schema:Person
85 sg:person.015173077562.22 schema:affiliation https://www.grid.ac/institutes/grid.424023.3
86 schema:familyName Yu
87 schema:givenName Rucong
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015173077562.22
89 rdf:type schema:Person
90 sg:person.07463411534.96 schema:affiliation https://www.grid.ac/institutes/grid.9227.e
91 schema:familyName Cheng
92 schema:givenName Rui
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07463411534.96
94 rdf:type schema:Person
95 sg:pub.10.1007/bf02658169 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040471244
96 https://doi.org/10.1007/bf02658169
97 rdf:type schema:CreativeWork
98 sg:pub.10.1007/bf02661283 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022636376
99 https://doi.org/10.1007/bf02661283
100 rdf:type schema:CreativeWork
101 sg:pub.10.1007/s00703-006-0248-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1043148658
102 https://doi.org/10.1007/s00703-006-0248-x
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1002/qj.49712354406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010358074
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1175/1520-0442(1993)006<1825:lvnbld>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063421282
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1175/1520-0442(1998)011<2628:iobaaf>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037136199
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1175/1520-0450-30.7.985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036535704
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1175/1520-0469(1984)041<1169:hsaeas>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025642332
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1175/1520-0469(1984)041<2836:roapip>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015991146
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1175/1520-0493(1997)125<3073:amnsoh>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026363934
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1175/1520-0493(2001)129<1370:aesotc>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035777539
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1175/1520-0493(2002)130<3022:aesotc>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025699358
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1175/jas3597.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007050420
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1175/jas3599.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051143909
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1175/mwr2989.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040671476
127 rdf:type schema:CreativeWork
128 https://www.grid.ac/institutes/grid.424023.3 schema:alternateName Institute of Atmospheric Physics
129 schema:name State Key Laboratory of Numerical Simulation for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, CAS, 100029, Beijing, China
130 rdf:type schema:Organization
131 https://www.grid.ac/institutes/grid.59053.3a schema:alternateName University of Science and Technology of China
132 schema:name University of Science and Technology of China, 230026, Hefei, China
133 rdf:type schema:Organization
134 https://www.grid.ac/institutes/grid.9227.e schema:alternateName Chinese Academy of Sciences
135 schema:name Graduate School of the Chinese Academy of Sciences, 100049, Beijing, China
136 State Key Laboratory of Numerical Simulation for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, CAS, 100029, Beijing, China
137 rdf:type schema:Organization
 




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


...