arXiv subjects

Jasmine Noory

Publications and source records attributed to Jasmine Noory.

4 recordsLinked to original sources

arXiv2026

Cusp Bifurcation in Conceptual Thermohaline Circulation Model

The Atlantic Meridional Overturning Circulation (AMOC) is often analyzed using low-order box models to understand tipping points. Historically, these studies focus on freshwater flux as the primary bifurcation parameter, treating the temperature gradient as a fixed restoring target. However, the erosion of the equator-to-pole temperature contrast due to polar amplification suggests that thermal forcing should be treated as a dynamic control parameter. In this study, we use Cessi's reduced box model to map the global bifurcation structure of the thermohaline circulation. We relax the assumption of a fixed thermal background and analyze the system's behavior under joint thermal and haline forcing. We prove the existence of a cusp bifurcation, identifying the specific geometry of pitchfork and saddle-node bifurcations that bound the stable regime. This geometric characterization reveals that thermal erosion acts as a distinct mechanism for destabilization, capable of driving the system across critical thresholds even in the absence of anomalous freshwater forcing.

math.DS↗

arXiv2025

Temperature induced tipping in a two box ocean circulation model

Climate tipping points are critical thresholds in Earth's climate system where a small change can cause abrupt and potentially irreversible shifts towards a new state. Tipping points in the Atlantic Meridional Overturning Circulation (AMOC) are of much scientific concern because of the large-scale impacts on Earth's climate. A two-box model representing the AMOC, introduced by oceanographer Paola Cessi (1994), revealed a multistable system, and was used to develop a tipping analysis framework to capture critical thresholds under freshwater forcing. Sustained increases in planetary energy uptake motivate the inspection of the model, shifting the focus to thermal dynamics. In this paper, we demonstrate that tipping can occur in the model where the temperature gradient acts as the forcing parameter instead of the freshwater forcing parameter.

physics.ao-ph↗

arXiv2025

Detecting the Indian Monsoon using Topological Data Analysis

A monsoon is a wind system that seasonally reverses its direction, accompanied by corresponding changes in precipitation. The Indian monsoon is the most prominent monsoon system, primarily affecting India's rainy season and its surrounding lands and water bodies. Every year, the onset and withdrawal of this monsoon happens sometime in May-June and September-October, respectively. Since monsoons are very complex systems governed by various weather factors with random noise, the yearly variability in the dates is significant. Despite the best efforts by the India Meteorological Department (IMD) and the South Asia Climate Outlook Forum (SCOF), forecasting the exact dates of onset and withdrawal, even within a week, is still an elusive problem in climate science. We interpret the onset and withdrawal of the Indian monsoon as abrupt regime shifts into and out of chaos. During these transitions, topological signatures (e.g., persistence diagrams) show rapid fluctuations, indicative of chaotic behavior. To detect these shifts, we reconstruct the phase space using Takens' embedding of the Indian monsoon index and apply topological data analysis (TDA) to track the birth and death of $k$-dimensional features. Applying this approach to historical monsoon index data (1948-2015) suggests a promising framework for more accurate detection of monsoon onset and withdrawal.

physics.ao-ph↗

arXiv2020

Tracking the variety of interleavings

In topological data analysis persistence modules are used to distinguish the legitimate topological features of a finite data set from noise. Interleavings between persistence modules feature prominantly in the analysis. One can show that for $ε$ positive, the collection of $ε$-interleavings between two persistence modules $M$ and $N$ has the structure of an affine variety, Thus, the smallest value of $ε$ corresponding to a nonempty variety is the interleaving distance. With this in mind, it is natural to wonder how this variety changes with the value of $ε$, and what information about $M$ and $N$ can be seen from just the knowledge of their varieties. In this paper, we focus on the special case where $M$ and $N$ are interval modules. In this situation we classify all possible progressions of varieties, and determine what information about $M$ and $N$ is present in the progression.

math.AT↗