Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature

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Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature. / Hillebrand, Eric; Johansen, Søren; Schmith, Torben.

I: Econometrics, Bind 8, Nr. 4, 41, 12.2020.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Hillebrand, E, Johansen, S & Schmith, T 2020, 'Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature', Econometrics, bind 8, nr. 4, 41. https://doi.org/10.3390/econometrics8040041

APA

Hillebrand, E., Johansen, S., & Schmith, T. (2020). Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature. Econometrics, 8(4), [41]. https://doi.org/10.3390/econometrics8040041

Vancouver

Hillebrand E, Johansen S, Schmith T. Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature. Econometrics. 2020 dec.;8(4). 41. https://doi.org/10.3390/econometrics8040041

Author

Hillebrand, Eric ; Johansen, Søren ; Schmith, Torben. / Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature. I: Econometrics. 2020 ; Bind 8, Nr. 4.

Bibtex

@article{c2e31f22cc734eb19ab5a7603074f2ee,
title = "Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature",
abstract = "We study the stability of estimated linear statistical relations of global mean temperature and global mean sea level with regard to data revisions. Using four different model specifications proposed in the literature, we compare coefficient estimates and long-term sea level projections using two different vintages of each of the annual time series, covering the periods 1880-2001 and 1880-2013. We find that temperature and sea level updates and revisions have a substantial influence both on the magnitude of the estimated coefficients of influence (differences of up to 50%) and therefore on long-term projections of sea level rise following the RCP4.5 and RCP6 scenarios (differences of up to 40 cm by the year 2100). This shows that in order to replicate earlier results that informed the scientific discussion and motivated policy recommendations, it is crucial to have access to and to work with the data vintages used at the time.",
keywords = "sea level, temperature, semi-empirical models, data revisions, IMPACT, STABILIZATION, PATHWAY, TRENDS, RISE",
author = "Eric Hillebrand and S{\o}ren Johansen and Torben Schmith",
year = "2020",
month = dec,
doi = "10.3390/econometrics8040041",
language = "English",
volume = "8",
journal = "Econometrics",
issn = "2225-1146",
publisher = "MDPI AG",
number = "4",

}

RIS

TY - JOUR

T1 - Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature

AU - Hillebrand, Eric

AU - Johansen, Søren

AU - Schmith, Torben

PY - 2020/12

Y1 - 2020/12

N2 - We study the stability of estimated linear statistical relations of global mean temperature and global mean sea level with regard to data revisions. Using four different model specifications proposed in the literature, we compare coefficient estimates and long-term sea level projections using two different vintages of each of the annual time series, covering the periods 1880-2001 and 1880-2013. We find that temperature and sea level updates and revisions have a substantial influence both on the magnitude of the estimated coefficients of influence (differences of up to 50%) and therefore on long-term projections of sea level rise following the RCP4.5 and RCP6 scenarios (differences of up to 40 cm by the year 2100). This shows that in order to replicate earlier results that informed the scientific discussion and motivated policy recommendations, it is crucial to have access to and to work with the data vintages used at the time.

AB - We study the stability of estimated linear statistical relations of global mean temperature and global mean sea level with regard to data revisions. Using four different model specifications proposed in the literature, we compare coefficient estimates and long-term sea level projections using two different vintages of each of the annual time series, covering the periods 1880-2001 and 1880-2013. We find that temperature and sea level updates and revisions have a substantial influence both on the magnitude of the estimated coefficients of influence (differences of up to 50%) and therefore on long-term projections of sea level rise following the RCP4.5 and RCP6 scenarios (differences of up to 40 cm by the year 2100). This shows that in order to replicate earlier results that informed the scientific discussion and motivated policy recommendations, it is crucial to have access to and to work with the data vintages used at the time.

KW - sea level

KW - temperature

KW - semi-empirical models

KW - data revisions

KW - IMPACT

KW - STABILIZATION

KW - PATHWAY

KW - TRENDS

KW - RISE

U2 - 10.3390/econometrics8040041

DO - 10.3390/econometrics8040041

M3 - Journal article

VL - 8

JO - Econometrics

JF - Econometrics

SN - 2225-1146

IS - 4

M1 - 41

ER -

ID: 255346972