The Hadley circulation: assessing NCEP/NCAR reanalysis and sparse in-situ estimates View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1999-10

AUTHORS

D. E. Waliser, Zhixiong Shi, J. R. Lanzante, A. H. Oort

ABSTRACT

We present a comparison of the zonal mean meridional circulations derived from monthly in situ data (i.e. radiosondes and ship reports) and from the NCEP/NCAR reanalysis product. To facilitate the interpretation of the results, a third estimate of the mean meridional circulation is produced by subsampling the reanalysis at the locations where radiosonde and surface ship data are available for the in situ calculation. This third estimate, known as the subsampled estimate, is compared to the complete reanalysis estimate to assess biases in conventional, in situ estimates of the Hadley circulation associated with the sparseness of the data sources (i.e., radiosonde network). The subsampled estimate is also compared to the in situ estimate to assess the biases introduced into the reanalysis product by the numerical model, initialization process and/or indirect data sources such as satellite retrievals. The comparisons suggest that a number of qualitative differences between the in situ and reanalysis estimates are mainly associated with the sparse sampling and simplified interpolation schemes associated with in situ estimates. These differences include: (1) a southern Hadley cell that consistently extends up to 200 hPa in the reanalysis, whereas the bulk of the circulation for the in situ and subsampled estimates tends to be confined to the lower half of the troposphere, (2) more well-defined and consistent poleward limits of the Hadley cells in the reanalysis compared to the in-situ and subsampled estimates, and (3) considerably less variability in magnitude and latitudinal extent of the Ferrel cells and southern polar cell exhibited in the reanalysis estimate compared to the in situ and subsampled estimates. Quantitative comparison shows that the subsampled estimate, relative to the reanalysis estimate, produces a stronger northern Hadley cell (∼20%), a weaker southern Hadley cell (∼20–60%), and weaker Ferrel cells in both hemispheres. These differences stem from poorly measured oceanic regions which necessitate significant interpolation over broad regions. Moreover, they help to pinpoint specific shortcomings in the present and previous in situ estimates of the Hadley circulation. Comparisons between the subsampled and in situ estimates suggest that the subsampled estimate produces a slightly stronger Hadley circulation in both hemispheres, with the relative differences in some seasons as large as 20–30%. 6These differences suggest that the mean meridional circulation associated with the NCEP/NCAR reanalysis is more energetic than observations suggest. Examination of ENSO-related changes to the Hadley circulation suggest that the in situ and subsampled estimates significantly overestimate the effects of ENSO on the Hadley circulation due to the reliance on sparsely distributed data. While all three estimates capture the large-scale region of low-level equatorial convergence near the dateline that occurs during El Nino, the in situ and subsampled estimates fail to effectively reproduce the large-scale areas of equatorial mass divergence to the west and east of this convergence area, leading to an overestimate of the effects of ENSO on the zonal mean circulation. More... »

PAGES

719-735

Journal

TITLE

Climate Dynamics

ISSUE

10

VOLUME

15

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s003820050312

DOI

http://dx.doi.org/10.1007/s003820050312

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1045622519


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/2008/0405", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oceanography", 
        "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": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook, NY 11794-5000, USA E-mail: waliser@terra.MSRC.Sunysb.EDU, US"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Waliser", 
        "givenName": "D. E.", 
        "id": "sg:person.01112400134.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01112400134.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook, NY 11794-5000, USA E-mail: waliser@terra.MSRC.Sunysb.EDU, US"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shi", 
        "givenName": "Zhixiong", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Princeton University", 
          "id": "https://www.grid.ac/institutes/grid.16750.35", 
          "name": [
            "Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ 08542, USA, US"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lanzante", 
        "givenName": "J. R.", 
        "id": "sg:person.0610623062.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610623062.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Princeton University", 
          "id": "https://www.grid.ac/institutes/grid.16750.35", 
          "name": [
            "Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ 08542, USA, US"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Oort", 
        "givenName": "A. H.", 
        "id": "sg:person.016330125101.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016330125101.24"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "1999-10", 
    "datePublishedReg": "1999-10-01", 
    "description": "We present a comparison of the zonal mean meridional circulations derived from monthly in situ data (i.e. radiosondes and ship reports) and from the NCEP/NCAR reanalysis product. To facilitate the interpretation of the results, a third estimate of the mean meridional circulation is produced by subsampling the reanalysis at the locations where radiosonde and surface ship data are available for the in situ calculation. This third estimate, known as the subsampled estimate, is compared to the complete reanalysis estimate to assess biases in conventional, in situ estimates of the Hadley circulation associated with the sparseness of the data sources (i.e., radiosonde network). The subsampled estimate is also compared to the in situ estimate to assess the biases introduced into the reanalysis product by the numerical model, initialization process and/or indirect data sources such as satellite retrievals. The comparisons suggest that a number of qualitative differences between the in situ and reanalysis estimates are mainly associated with the sparse sampling and simplified interpolation schemes associated with in situ estimates. These differences include: (1) a southern Hadley cell that consistently extends up to 200 hPa in the reanalysis, whereas the bulk of the circulation for the in situ and subsampled estimates tends to be confined to the lower half of the troposphere, (2) more well-defined and consistent poleward limits of the Hadley cells in the reanalysis compared to the in-situ and subsampled estimates, and (3) considerably less variability in magnitude and latitudinal extent of the Ferrel cells and southern polar cell exhibited in the reanalysis estimate compared to the in situ and subsampled estimates. Quantitative comparison shows that the subsampled estimate, relative to the reanalysis estimate, produces a stronger northern Hadley cell (\u223c20%), a weaker southern Hadley cell (\u223c20\u201360%), and weaker Ferrel cells in both hemispheres. These differences stem from poorly measured oceanic regions which necessitate significant interpolation over broad regions. Moreover, they help to pinpoint specific shortcomings in the present and previous in situ estimates of the Hadley circulation. Comparisons between the subsampled and in situ estimates suggest that the subsampled estimate produces a slightly stronger Hadley circulation in both hemispheres, with the relative differences in some seasons as large as 20\u201330%. 6These differences suggest that the mean meridional circulation associated with the NCEP/NCAR reanalysis is more energetic than observations suggest. Examination of ENSO-related changes to the Hadley circulation suggest that the in situ and subsampled estimates significantly overestimate the effects of ENSO on the Hadley circulation due to the reliance on sparsely distributed data. While all three estimates capture the large-scale region of low-level equatorial convergence near the dateline that occurs during El Nino, the in situ and subsampled estimates fail to effectively reproduce the large-scale areas of equatorial mass divergence to the west and east of this convergence area, leading to an overestimate of the effects of ENSO on the zonal mean circulation.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s003820050312", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1049631", 
        "issn": [
          "0930-7575", 
          "1432-0894"
        ], 
        "name": "Climate Dynamics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "10", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "15"
      }
    ], 
    "name": "The Hadley circulation: assessing NCEP/NCAR reanalysis and sparse in-situ estimates", 
    "pagination": "719-735", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d9523d1df113a4f096f4012379655607bcb812dc24b6c355c483152d7bb1f75f"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s003820050312"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1045622519"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s003820050312", 
      "https://app.dimensions.ai/details/publication/pub.1045622519"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:09", 
    "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_8695_00000483.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s003820050312"
  }
]
 

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/s003820050312'

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/s003820050312'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s003820050312'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s003820050312'


 

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

84 TRIPLES      20 PREDICATES      27 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s003820050312 schema:about anzsrc-for:04
2 anzsrc-for:0405
3 schema:author N3f774cf5cd47476b9dfe57adef558d7f
4 schema:datePublished 1999-10
5 schema:datePublishedReg 1999-10-01
6 schema:description We present a comparison of the zonal mean meridional circulations derived from monthly in situ data (i.e. radiosondes and ship reports) and from the NCEP/NCAR reanalysis product. To facilitate the interpretation of the results, a third estimate of the mean meridional circulation is produced by subsampling the reanalysis at the locations where radiosonde and surface ship data are available for the in situ calculation. This third estimate, known as the subsampled estimate, is compared to the complete reanalysis estimate to assess biases in conventional, in situ estimates of the Hadley circulation associated with the sparseness of the data sources (i.e., radiosonde network). The subsampled estimate is also compared to the in situ estimate to assess the biases introduced into the reanalysis product by the numerical model, initialization process and/or indirect data sources such as satellite retrievals. The comparisons suggest that a number of qualitative differences between the in situ and reanalysis estimates are mainly associated with the sparse sampling and simplified interpolation schemes associated with in situ estimates. These differences include: (1) a southern Hadley cell that consistently extends up to 200 hPa in the reanalysis, whereas the bulk of the circulation for the in situ and subsampled estimates tends to be confined to the lower half of the troposphere, (2) more well-defined and consistent poleward limits of the Hadley cells in the reanalysis compared to the in-situ and subsampled estimates, and (3) considerably less variability in magnitude and latitudinal extent of the Ferrel cells and southern polar cell exhibited in the reanalysis estimate compared to the in situ and subsampled estimates. Quantitative comparison shows that the subsampled estimate, relative to the reanalysis estimate, produces a stronger northern Hadley cell (∼20%), a weaker southern Hadley cell (∼20–60%), and weaker Ferrel cells in both hemispheres. These differences stem from poorly measured oceanic regions which necessitate significant interpolation over broad regions. Moreover, they help to pinpoint specific shortcomings in the present and previous in situ estimates of the Hadley circulation. Comparisons between the subsampled and in situ estimates suggest that the subsampled estimate produces a slightly stronger Hadley circulation in both hemispheres, with the relative differences in some seasons as large as 20–30%. 6These differences suggest that the mean meridional circulation associated with the NCEP/NCAR reanalysis is more energetic than observations suggest. Examination of ENSO-related changes to the Hadley circulation suggest that the in situ and subsampled estimates significantly overestimate the effects of ENSO on the Hadley circulation due to the reliance on sparsely distributed data. While all three estimates capture the large-scale region of low-level equatorial convergence near the dateline that occurs during El Nino, the in situ and subsampled estimates fail to effectively reproduce the large-scale areas of equatorial mass divergence to the west and east of this convergence area, leading to an overestimate of the effects of ENSO on the zonal mean circulation.
7 schema:genre research_article
8 schema:inLanguage en
9 schema:isAccessibleForFree false
10 schema:isPartOf N39122edfd2be4c9289b653657c0ef407
11 N8eee13c548b04ee7b17230a372240466
12 sg:journal.1049631
13 schema:name The Hadley circulation: assessing NCEP/NCAR reanalysis and sparse in-situ estimates
14 schema:pagination 719-735
15 schema:productId N1d377ee5adce46189e3e1c8dc8a3e447
16 N3d214cf704a6454ea87dbf44a936bda9
17 N675b551d15e647d8a0ed5e76c2a72224
18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045622519
19 https://doi.org/10.1007/s003820050312
20 schema:sdDatePublished 2019-04-11T00:09
21 schema:sdLicense https://scigraph.springernature.com/explorer/license/
22 schema:sdPublisher Nceaee56e06c3470d874cd3e3a251c0b1
23 schema:url http://link.springer.com/10.1007/s003820050312
24 sgo:license sg:explorer/license/
25 sgo:sdDataset articles
26 rdf:type schema:ScholarlyArticle
27 N1d377ee5adce46189e3e1c8dc8a3e447 schema:name readcube_id
28 schema:value d9523d1df113a4f096f4012379655607bcb812dc24b6c355c483152d7bb1f75f
29 rdf:type schema:PropertyValue
30 N39122edfd2be4c9289b653657c0ef407 schema:issueNumber 10
31 rdf:type schema:PublicationIssue
32 N3d214cf704a6454ea87dbf44a936bda9 schema:name dimensions_id
33 schema:value pub.1045622519
34 rdf:type schema:PropertyValue
35 N3f774cf5cd47476b9dfe57adef558d7f rdf:first sg:person.01112400134.33
36 rdf:rest Nbfe2785c2ae84873932dc4c9f13b9570
37 N675b551d15e647d8a0ed5e76c2a72224 schema:name doi
38 schema:value 10.1007/s003820050312
39 rdf:type schema:PropertyValue
40 N8eee13c548b04ee7b17230a372240466 schema:volumeNumber 15
41 rdf:type schema:PublicationVolume
42 Nbfe2785c2ae84873932dc4c9f13b9570 rdf:first Nd6a6cefa011f495d89b2624572aede3a
43 rdf:rest Nd233f76aa30a4aa8892dc5592368bd94
44 Nceaee56e06c3470d874cd3e3a251c0b1 schema:name Springer Nature - SN SciGraph project
45 rdf:type schema:Organization
46 Nd233f76aa30a4aa8892dc5592368bd94 rdf:first sg:person.0610623062.47
47 rdf:rest Nfa59931c8e4b4ce8a6b02582b3545068
48 Nd6a6cefa011f495d89b2624572aede3a schema:affiliation https://www.grid.ac/institutes/grid.36425.36
49 schema:familyName Shi
50 schema:givenName Zhixiong
51 rdf:type schema:Person
52 Nfa59931c8e4b4ce8a6b02582b3545068 rdf:first sg:person.016330125101.24
53 rdf:rest rdf:nil
54 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
55 schema:name Earth Sciences
56 rdf:type schema:DefinedTerm
57 anzsrc-for:0405 schema:inDefinedTermSet anzsrc-for:
58 schema:name Oceanography
59 rdf:type schema:DefinedTerm
60 sg:journal.1049631 schema:issn 0930-7575
61 1432-0894
62 schema:name Climate Dynamics
63 rdf:type schema:Periodical
64 sg:person.01112400134.33 schema:affiliation https://www.grid.ac/institutes/grid.36425.36
65 schema:familyName Waliser
66 schema:givenName D. E.
67 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01112400134.33
68 rdf:type schema:Person
69 sg:person.016330125101.24 schema:affiliation https://www.grid.ac/institutes/grid.16750.35
70 schema:familyName Oort
71 schema:givenName A. H.
72 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016330125101.24
73 rdf:type schema:Person
74 sg:person.0610623062.47 schema:affiliation https://www.grid.ac/institutes/grid.16750.35
75 schema:familyName Lanzante
76 schema:givenName J. R.
77 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610623062.47
78 rdf:type schema:Person
79 https://www.grid.ac/institutes/grid.16750.35 schema:alternateName Princeton University
80 schema:name Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ 08542, USA, US
81 rdf:type schema:Organization
82 https://www.grid.ac/institutes/grid.36425.36 schema:alternateName Stony Brook University
83 schema:name Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook, NY 11794-5000, USA E-mail: waliser@terra.MSRC.Sunysb.EDU, US
84 rdf:type schema:Organization
 




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


...