LGM hosing approach to Heinrich Event 1: results and perspectives from data–model integration using water isotopes

Abstract. Abrupt climate changes from 18 to 15 thousand years before present (kyr BP) associated with Heinrich Event 1 (HE1) had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). We calculated mega-biomes from the plant-functional types (PFTs) generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America. The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote effects of a Heinrich event under a glacial climate background.

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Catastrophic Drought in the Afro-Asian Monsoon Region During Heinrich Event 1

Science ◽

10.1126/science.1198322 ◽

2011 ◽

Vol 331 (6022) ◽

pp. 1299-1302 ◽

Cited By ~ 150

Author(s):

J. C. Stager ◽

D. B. Ryves ◽

B. M. Chase ◽

F. S. R. Pausata

Keyword(s):

Asian Monsoon ◽

Monsoon Region ◽

Asian Monsoon Region ◽

Heinrich Event ◽

Heinrich Event 1

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Warmings in the far northwestern Pacific promoted pre-Clovis immigration to America during Heinrich event 1

Geology ◽

10.1130/g22200.1 ◽

2006 ◽

Vol 34 (3) ◽

pp. 141 ◽

Cited By ~ 51

Author(s):

Michael Sarnthein ◽

Thorsten Kiefer ◽

Pieter M. Grootes ◽

Henry Elderfield ◽

Helmut Erlenkeuser

Keyword(s):

Northwestern Pacific ◽

Heinrich Event ◽

Heinrich Event 1

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Beyond Modeling: A Roadmap to Community Cyberinfrastructure for Ecological Data-Model Integration

10.20944/preprints202001.0176.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Istem Fer ◽

Anthony K. Gardella ◽

Alexey N. Shiklomanov ◽

Shawn P. Serbin ◽

Martin G. De Kauwe ◽

...

Keyword(s):

Global Change ◽

21St Century ◽

Data Model ◽

Model Integration ◽

Science And Society ◽

Model Data ◽

Ecological Data ◽

New Era ◽

Natural Systems ◽

New Knowledge

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks in our ability to process information have reduced our capacity to fully exploit the growing volume and variety of data. Here, we take a critical look at the information infrastructure that connects modeling and measurement efforts, and propose a roadmap that accelerates production of new knowledge. We propose that community cyberinfrastructure tools can help mend the divisions between empirical research and modeling, and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, transparent tools that integrate the expertise of the whole community, not just a clique of ‘modelers’. This roadmap focuses on five key opportunities for community tools: the underlying backbone to community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is key to meeting the pressing needs of science and society in the 21st century.

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Querying Multidimensional Data

Encyclopedia of Information Science and Technology, First Edition ◽

10.4018/978-1-59140-553-5.ch423 ◽

2005 ◽

pp. 2392-2396

Author(s):

Leonardo Tininini

Keyword(s):

Data Model ◽

Data Cube ◽

Level Of Detail ◽

Multidimensional Data ◽

Model Integration ◽

Integration Policy ◽

Multidimensional Database ◽

The Core ◽

Core Concepts ◽

Logical Data

A powerful, easy-to-use querying environment is without doubt one of the most important components in a multidimensional database. Its effectiveness is influenced by many aspects, both logical (data model, integration, policy of view materialization, etc.) and physical (multidimensional or relational storage, indexes, etc.). Multidimensional querying is often based on the core concepts of multidimensional data modeling, namely the metaphor of the data cube and the concepts of facts, measures and dimensions (Agrawal, Gupta, & Sarawagi, 1997; Gyssens & Lakshmanan, 1997). In contrast to conventional transactional environments, multidimensional querying is often an exploratory process, performed by navigating along dimensions and measures, increasing/decreasing the level of detail and focusing on specific subparts of the cube that appear “promising” for the required information.

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