Privalsky V.E., Yushkov V.P. Getting It Right Matters: Climate Spectra and Their Estimation // Pure and Applied Geophysics. 2018. V. 175. № 8. Pp. 3085-3096
In many recent publications, climate spectra estimated with different methods from observed, GCM-simulated and reconstructed time series contain many peaks at time scales from a few years to many decades and even centuries. However, respective spectral estimates obtained with the autoregressive (AR) and multitapering (MTM) methods showed that spectra of climate time series are smooth and contain no evidence of periodic or quasi-periodic behavior. Four order selection criteria for the autoregressive models were studied and proven sufficiently reliable for 25 time series of climate observations at individual locations or spatially averaged at local to global scales. As time series of climate observations are short, an alternative reliable nonparametric approach is Thomson’s MTM. These results agree with both the earlier climate spectral analyses and the Markovian stochastic model of climate.
2021Rets, E.P., Durmanov, I.N., Kireeva, M.B. et al. Past ‘peak water’ in the North Caucasus: deglaciation drives a reduction in glacial runoff impacting summer river runoff and peak discharges. Climatic Change 163, 2135–2151 (2020)
2021Kornilova E.D., Krylenko I.N., Rets E.P., Motovilov Y.G., Bogachenko E.M., Krylenko I.V., Petrakov D.A. Modeling of Extreme Hydrological Events in the Baksan River Basin, the Central Caucasus, Russia // Hydrology 2021, 8(1), 24