Details:

Journal Title:
Advances in Statistical Climatology, Meteorology and Oceanography
Personal Author:
DelSole, Timothy ; Tippett, Michael K.
DelSole, Timothy ; Tippett, Michael K. Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research)
Description:
This paper proposes a criterion for deciding whether climate model simulations are consistent with observations. Importantly, the criterion accounts for correlations in both space and time. The basic idea is to fit each multivariate time series to a vector autoregressive (VAR) model and then test the hypothesis that the parameters of the two models are equal. In the special case of a first-order VAR model, the model is a linear inverse model (LIM) and the test constitutes a difference-in-LIM test. This test is applied to decide whether climate models generate realistic internal variability of annual mean North Atlantic sea surface temperature. Given the disputed origin of multidecadal variability in the North Atlantic (e.g., some studies argue it is forced by anthropogenic aerosols, while others argue it arises naturally from internal variability), the time series are filtered in two different ways appropriate to the two driving mechanisms. In either case, only a few climate models out of three dozen are found to generate internal variability consistent with observations. In fact, it is shown that climate models differ not only from observations, but also from each other, unless they come from the same modeling center. In addition to these discrepancies in internal variability, other studies show that models exhibit significant discrepancies with observations in terms of the response to external forcing. Taken together, these discrepancies imply that, at the present time, climate models do not provide a satisfactory explanation of observed variability in the North Atlantic.
Keywords:
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Applied Mathematics Atmospheric Science Oceanography Statistics And Probability
Source:
Advances in Statistical Climatology, Meteorology and Oceanography, 7(2), 73-85
DOI:
https://doi.org/10.5194/ascmo-7-73-2021
ISSN:
2364-3587
Format:
PDF
Publisher:
Copernicus GmbH
Document Type:
Journal Article
Funding:
Grant no. NA20OAR4310401
License:
https://creativecommons.org/licenses/by/4.0/
Rights Information:
CC BY
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:534566125b9a19fb8bd31a28295f16a8c4aad3c931b9d01d7ed101e2d21dc206
Download URL:
https://repository.library.noaa.gov/view/noaa/58075/noaa_58075_DS1.pdf
File Type:

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