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Diagnosing atmosphere‐ocean general circulation model errors relevant to the terrestrial biosphere using the Köppen climate classification

Geophysical Research Letters(2006)10.1029/2006gl028098Source: DataRank Database

Diagnosing atmosphere‐ocean general circulation model errors relevant to the terrestrial biosphere using the Köppen climate classification is a research paper published in Geophysical Research Letters (2006). On theSindex it has a DataRank of 5.1. It has been cited 65 times, with 65 citing works in its 1-hop citation network.

N/A
5.1DataRank · unranked
5.1
65 citations · base score 4.2
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Coupled atmosphere‐ocean‐land‐sea ice climate models (AOGCMs) are often tuned using physical variables like temperature and precipitation with the goal of minimizing properties such as the root‐mean‐square error. As the community moves towards modeling the earth system, it is important to note that not all biases have equivalent impacts on biology. Bioclimatic classification systems provide means of filtering model errors so as to bring out those impacts that may be particularly important for the terrestrial biosphere. We examine one such diagnostic, the classic system of Köppen, and show that it can provide an “early warning” of which model biases are likely to produce serious biases in the land biosphere. Moreover, it provides a rough evaluation criterion for the performance of dynamic vegetation models. State‐of‐the art AOGCMs fail to capture the correct Köppen zone in about 20–30% of the land area excluding Antarctica, and misassign a similar fraction to the wrong subzone.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    Interoperable (0/2)
      Reusable (0/3)

        FAIR checklist signals are shown for context only and do not affect DataRank scoring.

        DataRank Breakdown

        Base Score 12%Citation Network 88%

        Base Score Contribution

        0.628

        From this paper's citation signal

        Citation Network Contribution

        4.5

        From 55 citing papers with measurable signal

        Learn more about DataRank methodology →

        Top 3 citers driving the network score

        Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

        1. Updated world map of the Köppen-Geiger climate classification
          Hydrology and Earth System Sciences200712,684 citationsDataRank 17.3Top 9%
        2. Köppen's climate classification map for Brazil
          Meteorologische Zeitschrift201311,573 citationsDataRank 1.4
        3. An Approach toward a Rational Classification of Climate
          Geographical Review19488,981 citationsDataRank 1.4
        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 12% comes from its base citations and 88% from the citation network (55 citing papers contributed measurable signal).

        Base score B(p)
        log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
        Network N(p)
        Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
        Damping factor d = 0.85
        DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
        Self-citations excluded
        Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

        Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

        Read the full methodology →

        Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

        Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

        Authors (2)

        Ronald J. StoufferORCID,Anand Gnanadesikan

        Related Papers (1)