utci_sparse: Calculate UTCI with a sparse regression approximation

In varunayan: Download and Process 'ERA5', IMD, 'HadEX3' and 'CRU TS' Data

Calculate UTCI with a sparse regression approximation

Description

This function uses the sparse regression approximation of Roman et al. (2025) to calculate UTCI. This approximation uses Legendre polynomials. It is more accurate than the original polynomial of Bröde et al. (2012). It has fewer terms and better numerical stability.

Usage

utci_sparse(temp_c, tmrt, wind_speed, rh)

Arguments

temp_c	Air temperature in Celsius (-50 to 50)
tmrt	Mean radiant temperature in Celsius
wind_speed	Wind speed at 10m height in m/s (0.5 to 30.3)
rh	Relative humidity as a percentage (5 to 100)

Value

UTCI in Celsius

References

Roman, S., Todorovski, L., Dzeroski, S., & Skok, G. (2025). Approximating the universal thermal climate index using sparse regression with orthogonal polynomials. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2508.11307")}

Roman, S. (2025). Code for Approximating the universal thermal climate index (UTCI) using sparse regression with orthogonal polynomials. Zenodo. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.5281/zenodo.17465548")}

Examples

utci_sparse(30, tmrt = 40, wind_speed = 2, rh = 60)
utci_sparse(35, tmrt = 35, wind_speed = 1, rh = 80)

varunayan documentation built on Oct. 30, 2026, 1:07 a.m.