Abstract:
Long term memory (LTM) scaling behavior in worldwide tree-ring proxies and subsequent climate
reconstructions is analyzed for and compared with the memory structure inherent to instrumental
temperature and precipitation data. Detrended fluctuation analysis is employed to detect LTM, and its
scaling exponent ? is used to evaluate LTM. The results show that temperature and precipitation
reconstructions based on ringwidthmeasurements (mean ? = 0.8) containmorememory than
records based onmaximumlatewood density (mean ? = 0.7). Both exceed thememory inherent to
regional instrumental data (? = 0.6 for temperature, ? = 0.5 for precipitation) in the time scales
ranging from1 year up to 50 years.We comparememory-free (? = 0.5) pseudo-instrumental
precipitation datawith pseudo-reconstructed precipitation datawith LTM (? > 0.5), and demonstrate
the biasing influences ofLTMon climate reconstructions. Wecall for attention to statistical
analysis with regard to the variability of proxy-based chronologies or reconstructions, particularly
with respect to the contained (i) trends, (ii) past warm/cold period and wet/dry periods; and (iii)
extreme events.
