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Abstract
The Institut Pierre Simon Laplace (IPSL) encompasses a wide diversity of projects that focus on the Arctic. From these observations the IPSL has generated a large number of datasets gathering Arctic observations. These observations include measurements on atmospheric chemical composition, snow micro-physical properties or ocean measurements. However, some of these datasets remain locally stored and there is a lack of public awareness regarding these resources, which has hindered their visualisation and sharing. This motivated the creation of the LABEX L-IPSL Arctic metadata Portal ( http://climserv.ipsl.polytechnique.fr/arcticportal/ ), presented here, which improves the visibility of the variety of observations collected within the institute as well as the evaluation of numerical models. The LABEX L-IPSL Arctic metadata Portal will also promote new avenues in Arctic research within the IPSL and with other collaborating institutions.
Highlights
The Arctic region surrounds the Earth’s North Pole, its geographic limit varies depending on the criteria followed (Figure 1)
It is essential to improve the performance of global climate models, including treatments of many processes and their interactions within the atmosphere, ocean, sea ice, ice sheet and biosphere systems
The LABEX L-Institut Pierre Simon Laplace (IPSL) Arctic metadata portal presented here improves the visibility of the different o bservations carried out within the IPSL and links with other institutes as well as new activities related to the French Chantier Arcticque
Summary
The Arctic region surrounds the Earth’s North Pole, its geographic limit varies depending on the criteria followed (Figure 1). The observed increase in mass loss from the Greenland ice sheet during the last decade (Rignot and Kanagaratnam, 2006; Schrama and Wouters, 2011; Velicogna, 2009; van de Wal et al, 2008), is of great concern for its future contribution of sea level, since if melted completely, sea level would rise a global average of 7.3 m (Lemke et al, 2007) The causes of such changes and their impacts on the environment and society are not yet well understood, limiting our ability to predict the future climate challenges. Processes-based studies combining analysis of available observations and models of varying complexity and scales are needed to make climate models more realistic, which is an important task for future predictions of climate scenarios
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