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Statistical Analysis in Climate Research
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Intern. J Climatol. 24: 665–680 , 2004
We review the role of statistical analysis in the climate sciences. Special emphasis is given to attempts to construct dynamical knowledge from limited observational evidence, and to the ongoing task of drawing detailed and reliable information on the state, and change, of climate that is needed, for example, for short-term and seasonal forecasting. We conclude with recommendations of how to improve the practice of statistical analysis in the climate sciences by drawing more efficiently on relevant developments in statistical mathematics.
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- DOI: 10.2307/2669798
- Corpus ID: 1536010
Statistical Analysis in Climate Research
- H. Storch , F. Zwiers
- Published 1 December 2000
- Environmental Science, Mathematics
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Instead, we use probabilistic ideas and statistics to describe the ‘climate’ system. Four factors ensure that the climate system is amenable to statistical thinking. † The climate is controlled by innumerable factors. Only a small proportion of these factors can be considered, while the rest are necessarily interpreted as background noise.
This book provides a comprehensive introduction to the most commonly used statistical methods relevant in atmospheric, oceanic, and climate sciences. Each method is described step-by-step using plain language, and illustrated with concrete examples, with relevant statistical and scientific concepts explained as needed.
We review the role of statistical analysis in the climate sciences. Special emphasis is given to attempts to construct dynamical knowledge from limited observational evidence, and to the ongoing task of drawing detailed and reliable information on the state, and change, of climate that is needed, for example, for short-term and seasonal ...
Statistical Analysis in Climate Research. This chapter discusses statistical concepts in climate research, as well as time series and stochastic processes, and some of the techniques used to estimate covariance functions and spectra.
There is a wealth of real-world examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research. This book is suitable as a main text for graduate courses on statistics for climatic, atmospheric and oceanic science.
time series analysis, how we model and assess global temperatures using observations, and compares these measurements to historical climate model simulations.