气候数据集指南:摘要和研究挑战

A. Karpatne, S. Liess, James H. Faghmous, Vipin Kumar
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引用次数: 1

摘要

最近气候数据的规模和种类的增长为了解地球气候系统的大数据分析研究提供了前所未有的机会。在过去的几十年里,使用各种获取模式(例如本地传感器记录或遥感仪器)、不同观测尺度(包括空间和时间)以及不同数据类型和格式收集的气候数据集激增。然而,气候数据集显示出一些独特的特征(例如,遵守物理性质和时空限制),这使得在气候科学应用中使用传统的以数据为中心的方法具有挑战性。在本文中,我们简要介绍了从各种来源获得的不同类别的气候数据集。我们进一步描述了在分析气候数据时以数据为中心的一些主要挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Guide to Climate Datasets: Summary and Research Challenges
Recent growth in the scale and variety of climate data has provided unprecedented opportunities to big data analytics research for understanding the Earth's climate system. There has been an upsurge of climate datasets in the past few decades that are collected using various modes of acquisition (e.g. local sensor recordings or remote sensing instruments), at different scales of observation (both in space and time), and in diverse data types and formats. Climate datasets however exhibit some unique characteristics (e.g. adherence to physical properties and spatio-temporal constraints) that makes it challenging to use traditional data-centric approaches for climate science applications. In this paper, we present a brief introduction of the different categories of climate datasets that are available from various sources. We further describe some of the major data-centric challenges in analyzing climate data.
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