arXiv subjects

Taylor Smith

Publications and source records attributed to Taylor Smith.

5 recordsLinked to original sources

arXiv2026

Estimating the Resilience of Non-Stationary Systems

A wide body of work has applied the concept of critical slowing down to estimate the stability of different Earth system components. Most of them -- such as global vegetation -- are inherently non-stationary, for example due to strong seasonal forcing, which complicates the estimation of their resilience to external perturbations. Here, we introduce a new method to account for non-stationarity in estimating resilience for diverse synthetic and real-world data sets via a regression-based formulation of the Langevin Equation. Our method does not require extensive data pre-processing, is robust to gaps in the data record, and does not require regular time sampling. We further show that our method can incorporate time-varying data uncertainties, recover uncertainty bounds in stability estimates, and can be natively extended to examine spatial systems. Our method is a drop-in replacement for widely-used autocorrelation-based resilience estimates, and can be widely applied across Earth system components.

nlin.CD↗

arXiv2025

Predicting Instabilities in Transient Landforms and Interconnected Ecosystems

Many parts of the Earth system are thought to have multiple stable equilibrium states, with the potential for rapid and sometimes catastrophic shifts between them. The most common frameworks for analyzing stability changes, however, require stationary (trend- and seasonality-free) data, which necessitates error-prone data pre-processing. Here we propose a novel method of quantifying system stability based on eigenvalue tracking and Floquet Multipliers, which can be applied directly to diverse data without first removing trend and seasonality, and is robust to changing noise levels, as can be caused by merging signals from different sensors. We first demonstrate this approach with synthetic data and further show how glacier surge onset can be predicted from observed surface velocity time series. We then show that our method can be extended to analyze spatio-temporal data and illustrate this flexibility with remotely sensed Amazon rainforest vegetation productivity, highlighting the spatial patterns of whole-ecosystem destabilization. Our work applies critical slowing down theory to glacier dynamics for the first time, and provides a novel and flexible method to quantify the stability or resilience of a wide range of spatiotemporal systems, including climate subsystems, ecosystems, and transient landforms.

nlin.CD↗

arXiv2025

The influence of data gaps and outliers on resilience indicators

The resilience, or stability, of major Earth system components is increasingly threatened by anthropogenic pressures, demanding reliable early warning signals for abrupt and irreversible regime shifts. Widely used data-driven resilience indicators based on variance and autocorrelation detect `critical slowing down', a signature of decreasing stability. However, the interpretation of these indicators is hampered by poorly understood interdependencies and their susceptibility to common data issues such as missing values and outliers. Here, we establish a rigorous mathematical analysis of the statistical dependency between variance- and autocorrelation-based resilience indicators, revealing that their agreement is fundamentally driven by the time series' initial data point. Using synthetic and empirical data, we demonstrate that missing values substantially weaken indicator agreement, while outliers introduce systematic biases that lead to overestimation of resilience based on temporal autocorrelation. Our results provide a necessary and rigorous foundation for preprocessing strategies and accuracy assessments across the growing number of disciplines that use real-world data to infer changes in system resilience.

nlin.AO↗

arXiv2023

Spatial correlation increase in single-sensor satellite data reveals loss of Amazon rainforest resilience

The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna-like state. Previous work suggesting declining resilience in recent decades was based only on local resilience indicators. Moreover, previous results are potentially biased by the employed multi-sensor and optical satellite data and undetected anthropogenic land-use change. Here, we show that the spatial correlation provides a more robust resilience indicator than local estimators and employ it to measure resilience changes in the ARF, based on single-sensor Vegetation Optical Depth data under conservative exclusion of human activity. Our results show an overall loss of resilience until around 2019, which is especially pronounced in the southwestern and northern Amazon for the time period from 2002 to 2011. The demonstrated reliability of spatial correlation in coupled systems suggests that in particular the southwest of the ARF has experienced pronounced resilience loss over the last two decades.

physics.geo-ph↗

arXiv2022

Conceptual design of an innovative UVC-LED air-cleaner to reduce airborne pathogen transmission

A conceptual design of a novel UVC-LED air-cleaner is presented as part of an international educational-research study. The main components are a dust-filter assembly, a UVC chamber and a fan. The dust-filter aims to suppress dust accumulation that will hamper the UVC chamber operation. The innovation is in the UVC chamber that includes a novel turbulence-generating grid to enhance air mixing in the chamber and a novel LEDs layout to achieve sufficient kill of the SARS-CoV-2 virus and TB bacterium aerosols with a reasonable power consumption. Both diseases have hit hard low to medium income countries and this study is part of an effort to offer non-pharmaceutical solutions to mitigate the air-transmission of such diseases. Low to high fidelity methods of computational fluid dynamics and UVC ray method are used to show that the design can provide a kill above 97% for Covid and TB, and above 92% for influenza-A. This is at a flow rate of 100 l/s, power consumption of less than 300W and a device size that is both portable and may also fit into ventilation ducts. Research and educational methodologies are discussed, along with analysis of the inexpensive dust-filter performance and the irradiation and flow fields.

physics.med-ph↗