Chapter 1 - Big climate data

Abstract

Big climate data are being gathered mainly from remote sensing observations, in situ observations, and climate model simulations. State-of-the-art remote sensing techniques are the most efficient and accurate approaches for monitoring large-scale variability of global climate and environmental changes. A comprehensive integrated observation system is being developed to incorporate various multiple active and passive microwave, visible, and infrared satellite remote sensing data sources and in situ observation sources. The size of various observation datasets is increasing sharply to the terabyte, petabyte, and even exabyte scales. Past and current climatic and environmental changes are being studied in new and dynamic ways from such remote sensing and in situ big data. At the same time, big data from climate model simulations is used to predict future climate change trends and to assess related impacts. The resolution of climate models is increasing from about 2.8 degree (latitude or longitude) to 0.1–0.5 degree. Since more complex physical, chemical, and biological processes need to be included in higher-resolution climate models, increasing the resolution of climate models by a factor of two means about ten times as much computing power will be needed. The size of output data from climate simulations is also increasing sharply. Climate change predictions must be built upon these big climate simulation datasets using evolving interdisciplinary big data mining technologies.