A supervised learning tool for heatwave predictions using daily high summer temperatures

Author:

Iqbal Gazi Md Daud1ORCID,Rosenberger Jay2ORCID,Rosenberger Matthew3,Alam Muhammad Shah4,Ha Lidan1,Anoruo Emmanuel1,Gregory Sadie1,Mazzone Tom5

Affiliation:

1. College of Business, Coppin State University Baltimore Maryland USA

2. Department of Industrial, Manufacturing, and Systems Engineering University of Texas at Arlington Arlington Texas USA

3. The Business School Worcester Polytechnic Institute Worcester Massachusetts USA

4. Department of Geography and Environment Govt. Bangla College Dhaka Bangladesh

5. Department of Technology Management and Innovation New York University Brooklyn New York USA

Abstract

AbstractGlobal temperature is increasing at an alarming rate, which increases the number of heatwaves. Heatwaves have significant impacts, both directly and indirectly, on human and natural systems and can create considerable risk to public health. Predicting the occurrence of a heatwave can save lives, increase the production of crops, improve water quality, and reduce transportation restrictions. Because of its geographical location, Bangladesh is particularly vulnerable to cyclones, droughts, earthquakes, floods, and heatwaves. The Bangladesh Meteorological Department collects temperature data at multiple weather stations, and we use data from 10 weather stations in this research. Data show that most heatwaves occur in the summer months, namely, April, May, and June. In this research, we develop Classification and Regression Tree (CART) models that use daily temperature data for the months of March, April, May, and June to predict the likelihood of a heatwave within the next 7 days, the next 28 days, and on any particular day based on daily high temperatures from the previous 14 days. We also use different model parameters to evaluate the accuracy of the models. Finally, we develop treed Stepwise Logistic Regression models to predict the probability of heatwaves occurring. Even though this research uses data from Bangladesh Meteorological Department, the developed modeling approach can be used in other geographic regions.

Publisher

Wiley

Reference29 articles.

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4. Deadly Heatwave in Europe. (2021).Deadly Heatwave in Europe.https://www.ville-ge.ch/cjb/reagir/pdf_reagir/reagir_changements_climatiques.pdf

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