Dataset Information

Dataset of global extreme climatic indices due to an acceleration of ice sheet melting during the 21st century.

ABSTRACT: This article describes extreme indices maps (Data Cube, raster X Time) for different scenarios with a more important contribution to the sea level rise from Greenland and/or Antarctica during the 21st century under the Representative Concentration Pathway (RCP) 8.5 emission scenario. The indices are produced annually and globally with a resolution of 0.5° × 0.5° from 1951 to 2099. The data were generated by simulating daily maximum and minimum temperature and precipitation from the IPSL-CM5A-LR model from Coupled Model Intercomparison Project Phase 5 (CMIP5). These climatic data are unbiased and downscaled to the 0.5°x0.5 scale with the Cumulative Distribution Function transform (CDFt) and EWEMBI dataset compiled to support the bias correction of climate input data for ISIMIP. Finally, each extreme indice is computed on the unbiased data on each grid cell on all continents.

SUBMITTER: Defrance D

PROVIDER: S-EPMC6817647 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dataset of global extreme climatic indices due to an acceleration of ice sheet melting during the 21st century.

Defrance Dimitri D

Data in brief 20190928

This article describes extreme indices maps (Data Cube, raster X Time) for different scenarios with a more important contribution to the sea level rise from Greenland and/or Antarctica during the 21st century under the Representative Concentration Pathway (RCP) 8.5 emission scenario. The indices are produced annually and globally with a resolution of 0.5° × 0.5° from 1951 to 2099. The data were generated by simulating daily maximum and minimum temperature and precipitation from the IPSL-CM5A-LR ...[more]

PMID: 31673587

Similar Datasets

Project description:There is no good science in bad models. Cell culture is especially prone to artifacts. A number of novel cell culture technologies have become more broadly available in the 21st century, which allow overcoming limitations of traditional culture and are more physiologically relevant. These include the use of stem-cell derived human cells, cocultures of different cell types, scaffolds and extracellular matrices, perfusion platforms (such as microfluidics), 3D culture, organ-on-chip technologies, tissue architecture, and organ functionality. The physiological relevance of such models is further enhanced by the measurement of biomarkers (e.g., key events of pathways), organ specific functionality, and more comprehensive assessment cell responses by high-content methods. These approaches are still rarely combined to create microphysiological systems. The complexity of the combination of these technologies can generate results closer to the in vivo situation but increases the number of parameters to control, bringing some new challenges. In fact, we do not argue that all cell culture needs to be that sophisticated. The efforts taken are determined by the purpose of our experiments and tests. If only a very specific molecular target to cell response is of interest, a very simple model, which reflects this, might be much more suited to allow standardization and high-throughput. However, the less defined the end point of interest and cellular response are, the better we should approximate organ- or tissue-like culture conditions to make physiological responses more probable. Besides these technologic advances, important progress in the quality assurance and reporting on cell cultures as well as the validation of cellular test systems brings the utility of cell cultures to a new level. The advancement and broader implementation of Good Cell Culture Practice (GCCP) is key here. In toxicology, this is a major prerequisite for meaningful and reliable results, ultimately supporting risk assessment and product development decisions.

Dataset Information

Dataset of global extreme climatic indices due to an acceleration of ice sheet melting during the 21st century.

Publications

Dataset of global extreme climatic indices due to an acceleration of ice sheet melting during the 21st century.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets