Identification

Title

Temporal comparisons involving paleoclimate data assimilation: Challenges and remedies

Abstract

Paleoclimate reconstructions are increasingly central to climate assessments, placing recent and future variability in a broader historical context. Several estimation methods produce plumes of climate trajectories that practitioners often want to compare to other reconstruction ensembles or to deterministic trajectories produced by other means, such as global climate models. Of particular interest are “offline” data assimilation (DA) methods, which have recently been adapted to paleoclimatology. Offline DA lacks an explicit model connecting time instants, so its ensemble members are not true system trajectories. This obscures quantitative comparisons, particularly when considering the ensemble mean in isolation. We propose several resampling methods to introduce a priori constraints on temporal behavior, as well as a general notion, called plume distance, to carry out quantitative comparisons between collections of climate trajectories (“plumes”). The plume distance provides a norm in the same physical units as the variable of interest (e.g., °C for temperature) and lends itself to assessments of statistical significance. We apply these tools to four paleoclimate comparisons: 1) global mean surface temperature (GMST) in the online and offline versions of the Last Millennium Reanalysis (v2.1); 2) GMST from these two ensembles to simulations of the Paleoclimate Modelling Intercomparison Project past1000 ensemble; 3) Last Millennium Reanalysis, version 2.1 (LMRv2.1), to the PAGES 2k Consortium ensemble of GMST; and 4) the Northern Hemisphere mean surface temperature from LMRv2.1 to the Büntgen et al. ensemble. Results generally show more compatibility between these ensembles than is visually apparent. The proposed methodology is implemented in an open-source Python package, and we discuss the possible applications of the plume distance framework beyond paleoclimatology.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.net/ark:/85065/d76t0s2p

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

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Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2025-03-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

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name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact