A Data Driven, Zero-Dimensional Time Delay Model with Radiative Forcing for Simulating Global Climate

TL;DR

This paper introduces a simplified, data-driven zero-dimensional climate model using a non-linear delay differential equation to simulate temperature fluctuations under radiative forcing, aiming to improve understanding and prediction of climate change.

Contribution

It presents a novel reduced climate model based on delay differential equations that captures key climate dynamics with less computational complexity.

Findings

Model effectively simulates temperature fluctuations under radiative forcing

Simplified equations reveal potential mechanisms influencing climate variability

Results support use in climate prediction and policy development

Abstract

Several complicated non-linear models exist which simulate the physical processes leading to fluctuations in global climate. Some of these more advanced models use observations to constrain various parameters involved. However, they tend to be very computationally expensive. Also, the exact physical processes that affect the climate variations have not been completely comprehended. Therefore, to obtain an insight into global climate, we have developed a physically motivated reduced climate model. The model utilizes a novel mathematical formulation involving a non-linear delay differential equation to study temperature fluctuations when subjected to imposed radiative forcing. We have further incorporated simplified equations to test the effect of speculated mechanisms of climate forcing and evaluated the extent of their influence. The findings are significant in our efforts to predict climate change and help in policy framing necessary to tackle it.