arXiv subjects

Erhard Reschenhofer

Publications and source records attributed to Erhard Reschenhofer.

4 recordsLinked to original sources

arXiv2026

Bandwidth selection with a frequency-domain version of the AIC

When it comes to estimating an unknown spectral density as simply and reliably as possible, parametric spectral density estimation using AR models and order selection via AIC is the method of choice. In contrast, no standard method has yet emerged for automatic nonparametric spectral density estimation, and there seems to be little willingness to weigh the advantages and disadvantages of different risk functions and the various methods for estimating them on a case-by-case basis, particularly because it is unclear whether the effort is even worthwhile without concrete prior information about the unknown spectral density. As a result, subjective visual methods are still widely used in practice to determine the appropriate smoothing parameter for a nonparametric estimation. This article aims to encourage the increased use of objective automatic methods by presenting evidence that using what is arguably the simplest and most straightforward frequency-domain version of the AIC for the automatic determination of an appropriate bandwidth enables results that are comparable to those obtained using the standard parametric approach. This evidence is based on both real-world time series and synthetic time series with spectral densities of varying complexity.

stat.AP↗

arXiv2026

Remarks on the acceleration of global warming and the imminent breach of the 1.5°C Paris Agreement target

To answer the questions of whether global warming is accelerating and when the 1.5°C Paris Agreement target will be exceeded, the global mean surface temperature from 1880 to 2025 is first examined using a purely graphical approach and later, in a more conventional way, using various time-domain and frequency-domain methods. In an effort to reduce variability, exogenous variables such as El Niño and solar variations are taken into account. Although it ultimately remains unclear to what extent these variables are actually helpful, we feel confident in summarizing the empirical results of this study to suggest that global warming is indeed accelerating and that a breach of the 1.5°C Paris Agreement target is imminent. But when it comes to statistical significance, caution should still be exercised. While the acceleration hypothesis can be confirmed with a fair degree of certainty under reasonably plausible assumptions (albeit with the help of a bit of data snooping, which is unavoidable when building on the results of earlier studies that used virtually the same data), there is currently not enough evidence to prove that the 1.5°C target has already been exceeded. However, if 2026 and 2027 turn out to be very warm due to the approaching El Niño, that could change very soon.

physics.ao-ph↗

arXiv2025

The latest monthly highs suggest that the 1.5°C Paris Agreement threshold will probably be exceeded before 2028

An attempt is made to estimate and forecast the trend of the global annual and monthly mean temperatures. The results of a conventional statistical analysis suggest that in the absence of unforeseeable events such as a sudden acceleration in the rate of warming, the 1.5°C Paris Agreement threshold could be exceeded between 2027 and 2031. However, carrying out a proper seasonal adjustment and examining the autocorrelation structure carefully, we find in a subsequent purely statistical simulation study that even the pessimistic scenario of a breach in late 2027 is inconsistent with the recent monthly highs, which means that it will probably happen much sooner.

physics.ao-ph↗

arXiv2024

A new indicator for the AMOC strength still gives no indication of an imminent collapse

The results of a recent simulation with a complex global climate model suggest that the overturning component of the freshwater transport at the southern boundary of the Atlantic could be used as an early-warning indicator of an AMOC collapse. However, there are two shortcomings. Firstly, the simulation is based on some implausible assumptions. It is therefore not clear whether this new indicator will still be helpful in a more realistic setting. Secondly, the statistical methods employed in the simulation work only for time series that are much longer than the currently available historical series. As not much can be done in the short term about the first issue, this paper focuses on the second issue. It is shown that it is possible to use alternative statistical methods that can do the job at least as well and, moreover, are also suitable for short series. Applying these more appropriate methods to historical data obtained with an ocean reanalysis system, no indication of an imminent AMOC collapse is found.

physics.ao-ph↗