Evidence map›Paper›PMID 37709805›Full record

ArticleScientific data2023

A pseudoproxy emulation of the PAGES 2k database using a hierarchy of proxy system models.

Feng Zhu, Julien Emile-Geay, Kevin J Anchukaitis, Nicholas P McKay, Samantha Stevenson, Zilu Meng

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Feng ZhuClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA. fengzhu@ucar.edu.ORCID http://orcid.org/0000-0002-9969-2953
Julien Emile-GeayDepartment of Earth Sciences, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0001-5920-4751
Kevin J AnchukaitisLaboratory of Tree-Ring Research, University of Arizona, Tucson, AZ, USA.ORCID http://orcid.org/0000-0002-8509-8080
Nicholas P McKaySchool of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA.ORCID http://orcid.org/0000-0003-3598-5113
Samantha StevensonBren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, CA, USA.
Zilu MengDepartment of Atmospheric Sciences, University of Washington, Seattle, WA, USA.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42205053National Science Foundation (NSF) 2303530National Science Foundation (NSF) EAR 1948822United States Department of Commerce | NOAA | Climate Program Office (NOAA Climate Program Office) NA18OAR4310420United States Department of Commerce | NOAA | Climate Program Office (NOAA Climate Program Office) NA18OAR4310426
6 · The paper itself

Abstract

Paleoclimate reconstructions are now integral to climate assessments, yet the consequences of using different methodologies and proxy data require rigorous benchmarking. Pseudoproxy experiments (PPEs) provide a tractable and transparent test bed for evaluating climate reconstruction methods and their sensitivity to aspects of real-world proxy networks. Here we develop a dataset that leverages proxy system models (PSMs) for this purpose, which emulates the essential physical, chemical, biological, and geological processes that translate climate signals into proxy records, making these synthetic proxies more relevant to the real world. We apply a suite of PSMs to emulate the widely-used PAGES 2k dataset, including realistic spatiotemporal sampling and error structure. A hierarchical approach allows us to produce many variants of this base dataset, isolating the impact of sampling bias in time and space, representation error, sampling error, and other assumptions. Combining these various experiments produces a rich dataset ("pseudoPAGES2k") for many applications. As an illustration, we show how to conduct a PPE with this dataset based on emerging climate field reconstruction techniques.

Identifiers

PMID37709805
PMCPMC10502095

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.