Interpolation and Extrapolation of Annual Precipitation 
Data for Daytona Beach, Florida

Luke Piatt; Keshav Acharya

doi:https://doi.org/10.14445/22315373/IJMTT-V72I2P104

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 72 | Issue 2 | Year 2026 | Article Id. IJMTT-V72I2P104 | DOI : https://doi.org/10.14445/22315373/IJMTT-V72I2P104

Interpolation and Extrapolation of Annual Precipitation Data for Daytona Beach, Florida

Luke Piatt, Keshav Acharya

Received	Revised	Accepted	Published
15 Dec 2025	20 Jan 2026	10 Feb 2026	26 Feb 2026

Citation :

Luke Piatt, Keshav Acharya, "Interpolation and Extrapolation of Annual Precipitation Data for Daytona Beach, Florida," International Journal of Mathematics Trends and Technology (IJMTT), vol. 72, no. 2, pp. 24-33, 2026. Crossref, https://doi.org/10.14445/22315373/IJMTT-V72I2P104

Abstract

In this paper, we analyze annual precipitation records from Daytona Beach, Florida, by utilizing interpolation and extrapolation, focusing on years where the data are missing or unevenly spaced. We apply several interpolation methods to fill the gaps and extrapolation techniques to predict the future precipitation. We use polynomial interpolation based on a Vandermonde matrix and compare it with MATLAB’s built-in interpolation functions. Specifically, we test linear interpolation, piecewise cubic interpolation, and higher-degree polynomial models to see how each method behaves when the data contains large gaps. We also use a least-squares approach to extrapolate short-term trends in annual precipitation. In our observation, we found that piecewise interpolation provides the most stable estimates for the missing values. Although extrapolation is less reliable, it suggests a slight upward trend in precipitation over the selected period. These results show that interpolation methods can be practically useful, but they also remind us of the uncertainty that comes with making long-term climate predictions.

Keywords

Interpolation, Extrapolation, Precipitation Modeling, Precipitation Data Analysis, MATLAB.

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