Global climate models: Past, present, and future

Stute, M.; Clement, A. C.; Lohmann, Gerrit

doi:10.1073/pnas.191366098

Cited by 24 publications

(12 citation statements)

References 19 publications

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“…2). Most probably, pronounced El Nin˜o events were more likely to develop due to the enhanced IPWP heat build up, and since large El Nin˜o's cause greater wave reflection that terminating the warm events and induce strong La Nin˜a conditions (Stute et al, 2001), the entire ENSO cycle intensified to maximum variability around 3 ka BP. This mechanism can, apart from the increase of modern ENSO frequencies around 5 ka BP recorded in the equatorial Pacific, further explain the increase around 3 ka BP of ENSO strength and associated environmental change in strongly teleconnected areas seen in the paleoclimatic proxy data.…”

Section: Discussionmentioning

confidence: 99%

“…Further controversy is related to the Holocene upwelling intensity in the Western Pacific, which is a crucial factor in the 'Bjerknes' feedback between sea surface temperature (SST) gradients and wind forcing for triggering ENSO warm events (Stute et al, 2001;Cane, 2005). Reduced early-Holocene ENSO activity was accompanied by mean warm conditions in the eastern equatorial Pacific according to some reconstructions (Sandweiss et al, 1996;Rodbell et al, 1999;Andrus et al, 2002).…”

Section: Article In Pressmentioning

confidence: 99%

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Integration of proxy data and model scenarios for the mid-Holocene onset of modern ENSO variability

Donders

Wagner-Cremer

Visscher

2008

Quaternary Science Reviews

126

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Section: Discussionmentioning

confidence: 99%

Section: Article In Pressmentioning

confidence: 99%

Integration of proxy data and model scenarios for the mid-Holocene onset of modern ENSO variability

Donders

Wagner-Cremer

Visscher

2008

Quaternary Science Reviews

126

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“…Alternative emission scenarios presented by the IPCC are global and based on changes in greenhouse-gas concentrations (SRES) or radiative forcing (RCP), necessitating complex conversion into a range of relevant climate variables at finer scales, using GCMs developed by several research organisations around the world. These models are based on the general principles of fluid dynamics and thermodynamics and have their origin in weather prediction (Stute et al 2001). GCMs describe the dynamics of the atmosphere and ocean in an explicit way, typically at horizontal spatial scales of 1-3 degrees, and with varying numbers of vertical layers in the ocean and atmosphere, and provide a way to run quantitative experiments on climate conditions during the past, present and future.…”

Section: Projecting Future Conditionsmentioning

confidence: 99%

Projected climate change in Australian marine and freshwater environments

Hobday

Lough

2011

Mar. Freshwater Res.

259

201

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Abstract. Changes in the physical environment of aquatic systems consistent with climate change have been reported across Australia, with impacts on many marine and freshwater species. The future state of aquatic environments can be estimated by extrapolation of historical trends. However, because the climate is a complex non-linear system, a more process-based approach is probably required, in particular the use of dynamical projections using climate models. Because global climate models operate on spatial scales that typically are too coarse for aquatic biologists, statistical or dynamical downscaling of model output is proposed. Challenges in using climate projections exist; however, projections for some marine and freshwater systems are possible. Higher oceanic temperatures are projected around Australia, particularly for south-eastern Australia. The East Australia Current is projected to transport greater volumes of water southward, whereas the Leeuwin Current on the western coast may weaken. On land, projections suggest that air temperatures will rise and rainfall will decline across much of Australia in coming decades. Together, these changes will result in reduced runoff and hence reduced stream flow and lake storage. Present climate models are particularly limited with regard to coastal and freshwater systems, making the models challenging to use for biological-impact and adaptation studies.

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“…Therefore, there is no need for real time processing and no particular pressure for incremental algorithms. Unless a very coarse spatial resolution is necessary or climate models (Stute et al 2001) need to be run in parallel to provide additional feedback for the analysis, it is reasonable and practical to have algorithms access and operate on all the historical data. In fact, data of the past is rather scarce, and the most recent data, for which labels are available, is more abundant.…”

Section: Relation To Transfer Learning and Concept Driftmentioning

confidence: 99%

Concept drift over geological times: predictive modeling baselines for analyzing the mammalian fossil record

Žliobaitė

2018

Data Min Knowl Disc

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Fossils are the remains organisms from earlier geological periods preserved in sedimentary rock. The global fossil record documents and characterizes the evidence about organisms that existed at different times and places during the Earth's history. One of the major directions in computational analysis of such data is to reconstruct environmental conditions and track climate changes over millions of years. Distribution of fossil animals in space and time make informative features for such modeling, yet concept drift presents one of the main computational challenges. As species continuously go extinct and new species originate, animal communities today are different from the communities of the past, and the communities at different times in the past are different from each other. The fossil record is continuously increasing as new fossils and localities are being discovered, but it is not possible to observe or measure their environmental contexts directly, because the time is gone. Labeled data linking organisms to climate is available only for the present day, where climatic conditions can be measured. The approach is to train models on the present day and use them to predict climatic conditions over the past. But since species representation is continuously changing, transfer learning approaches are needed to make models applicable and climate estimates to be comparable across geological times. Here we discuss predictive modeling settings for such paleoclimate reconstruction from the fossil record. We compare and experimentally analyze three baseline approaches for predictive paleoclimate reconstruction: (1) averaging over habitats of species, (2) using presence-absence of species as features, and (3) using functional characteristics of species communities as features. Our experiments on the present day African data and a case study on the fossil data from the Turkana Basin over the last 7 million of years suggest that presence-absence approaches are the most accurate over short time horizons, while species community approaches, also known as ecometrics, are the most informative over longer time horizons when, due to ongoing evolution, taxonomic relations between the present day and fossil species become more and more uncertain.

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Global climate models: Past, present, and future

Cited by 24 publications

References 19 publications

Integration of proxy data and model scenarios for the mid-Holocene onset of modern ENSO variability

Integration of proxy data and model scenarios for the mid-Holocene onset of modern ENSO variability

Projected climate change in Australian marine and freshwater environments

Concept drift over geological times: predictive modeling baselines for analyzing the mammalian fossil record

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