The Central Greenland surface temperature from GISP2 project for the past 4000 years (blue line) and the modeled temperature adopting only 3 periods at 2804-year, 1186-year and 556-year. The 3-period model was able to replicate most of the observed changes (with one major exception at around the warming peak of 3 to 400 AD) and forecasted a large cooling trend in contrast to the IPCC-predicted rising atmospheric CO2 scenario from computer climate models. [caption from the NIPCC report] |
Identifying natural contributions to late Holocene climate change
- a Department of Geosciences, University of Oslo, Oslo, Norway
- b Department of Geology, University Centre in Svalbard (UNIS), Svalbard, Norway
- c Institute of Theoretical Astrophysics, University of Oslo, Oslo, Norway
- d Telenor Norway, Finance, Fornebu, Oslo, Norway
- Received 16 June 2011. Accepted 9 September 2011. Available online 17 September 2011.
Abstract
Analytic climate models have provided the means to predict potential impacts on future climate by anthropogenic changes in atmospheric composition. However, future climate development will not only be influenced by anthropogenic changes, but also by natural variations. The knowledge on such natural variations and their detailed character, however, still remains incomplete. Here we present a new technique to identify the character of natural climate variations, and from this, to produce testable forecast of future climate. By means of Fourier and wavelet analyses climate series are decomposed into time–frequency space, to extract information on periodic signals embedded in the data series and their amplitude and variation over time. We chose to exemplify the potential of this technique by analysing two climate series, the Svalbard (78°N) surface air temperature series 1912–2010, and the last 4000 years of the reconstructed GISP2 surface temperature series from central Greenland. By this we are able to identify several cyclic climate variations which appear persistent on the time scales investigated. Finally, we demonstrate how such persistent natural variations can be used for hindcasting and forecasting climate. Our main focus is on identifying the character (timing, period, amplitude) of such recurrent natural climate variations, but we also comment on the likely physical explanations for some of the identified cyclic climate variations. The causes of millennial climate changes remain poorly understood, and this issue remains important for understanding causes for natural climate variability over decadal- and decennial time scales. We argue that Fourier and wavelet approaches like ours may contribute towards improved understanding of the role of such recurrent natural climate variations in the future climate development.
Highlights
► We identified persistent cyclic variations in records from Svalbard and Greenland. ► Some identified cycles correspond to variations in the Moons' orbit around Earth. ► Some identified cycles correspond to solar variations. ► Warming since 1850 is mainly the result of natural climatic variations. ► Persistence of cycles makes climate forecasting feasible for limited time ranges.
Full paper available here
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