With decades of available data from observational datasets and reanalyses, indices are a useful tool to detect extreme events and characteristics of the Earth-atmosphere system in large datasets.  These allow for relatively simple definitions of climate phenomena that can be used in a variety of applied sectors.  Numerous indicators have been developed in the past to assist with analysis such as those used to detect or represent heat waves, extreme precipitation events, drought, sea ice extent, tropical cyclones, sea level, air quality, and more. However, the development of climate and extremes indices is not always straight forward as some include a baseline climatology or are percentile or return period based, while others are derived through artificial intelligence or data mining techniques. As the community strives towards an open science framework, tools are becoming more available and widespread for the calculation, detection, and visualization of indices that can be used for applied climatology research. A proper understanding of the indices themselves is essential as applied science results are often used for decision making, practical purposes, public health assessments, or are included in overarching reports such as the National Climate Assessment. Completing the research cycle are studies that make use of weather and climate indicators and tie these with other aspects of the atmosphere, ocean, land, and the world around us. This session welcomes studies focused on the development, analysis, and application of indices, spanning all aspects of the Earth system, created using large datasets.   

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