A CRITIC-weighted composite meteorological indicator incorporating solar radiation and its assessment against residential natural-gas consumption: a case study of Sakarya, Türkiye

Composite indicators are used to summarize several meteorological variables for energy studies, but objective weighting schemes are rarely tested against measured energy use. This study builds a Composite Meteorological Indicator (CMI) from monthly mean temperature, relative humidity, wind speed, global solar radiation and atmospheric pressure (Sakarya, Türkiye; 130 months, 2015–2025) using min–max normalization and CRITIC weights (0.249, 0.175, 0.142, 0.232 and 0.202), and tests it against measured residential natural-gas consumption using nested regressions, a seasonality-only benchmark, autocorrelation-adjusted statistics and a chronological train–test split (2015–2022/2023–2025). CMI explained less of the variance in gas consumption than temperature alone (R 2 = 0.642 vs. 0.876) and added no information to it (partial F p = 0.87); as the only predictor it did not outperform the climatology benchmark (test R 2 = 0.71–0.79 vs. 0.886). The heating degree indicator of the previous month was the best predictor (r = 0.97; test R 2 = 0.916, RMSE = 20.4 vs. 23.7 Sm 3 for climatology), and Shapley analysis attributed about 89% of the importance to temperature, against a CRITIC weight of 25%. Because of autocorrelation, effective sample sizes were only 13–15 of 130, so p-values are descriptive. The study shows that objective CRITIC weights reflect climatic covariance rather than energy relevance, and that a heating degree term carries most of the useable information in a heating-dominated climate; CMI is a reproducible but dataset-specific composite that requires recalibration at other sites.