What is the difference? What is the optimal length of time to separate signal from noise in a period of climate warming?
Happy new year!!! For the last couple of weeks I have been reading articles related to climate change and global warming and have found the use of certain technical terms very interesting. The notions of signal and noise are often misunderstood in conversations and within the media. Understanding the difference between the two is essential in climate science, particularly given the attention of scientists and the public on anthropogenic climate change. Here is the difference between signal and noise on climate change time scales:
Noise is the year-to-year variation that primarily results from natural internal variability, while signal is the variation in the mean, and resulting trend, that occurs in response to combined anthropogenic and natural external forcings. In other words noise is the short-term, rapidly fluctuating component of a climate time series and signal is the long-term smoothed component. Clearly understanding the difference between the two will help us to improve our understanding of the human contribution to global warming.
It is also very important to know the time scale at which we might be able to separate human-caused global warming from purely natural climate fluctuations. Is 10 years sufficient or do we require a longer time series? A recent paper by Santer et al. (2011) indicates that temperature records of at least 17 years are required for identifying the human impacts on global‐mean tropospheric temperature. The physical explanation is that shorter periods generally have small signal to noise ratios, making it difficult to identify an anthropogenic signal with high statistical confidence. Analysing longer, multi-decadal temperature records is essential to separate the large year-to-year temperature variability caused by purely natural phenomena, and to identify a slower-emerging signal arising from gradual human-caused changes in atmospheric levels of greenhouse gases. For example, a number of studies indicate that the decade from 2000 to 2010 was the warmest on record, but there was no significant rise in temperature over those 10 years. Nonetheless, this doesn’t mean global warming has stopped. 10 years is simply too short a time frame to reliably detect a climate signal as fluctuations (noise) from natural cycles such as El Niño and La Niña dominate the climate time series. Trends over a single decade often differ from the long-term trend. Therefore, looking at a single, noisy 10-year period does not provide sufficient information to determine the presence or absence of human effects on climate.
References:
Kaufmann, R. K., Kauppi, H., Mann, M. L., & Stock, J. H. (2011). Reconciling anthropogenic climate change with observed temperature 1998–2008. Proceedings of the National Academy of Sciences, 108(29), 11790-11793.
Santer BD, et al. (2011). Separating signal and noise in atmospheric temperature changes: The importance of timescale. J Geophys Res, 10.1029/2011JD016263.
Santer, B. D., Painter, J. F., Mears, C. A., Doutriaux, C., Caldwell, P., Arblaster, J. M., … & Zou, C. Z. (2013). Identifying human influences on atmospheric temperature. Proceedings of the National Academy of Sciences, 110(1), 26-33.