Development of Empirical Models for Estimating Daily Downward Longwave Radiation Using Meteorological Data in Thailand

Information from the abstract

This study developed models to estimate daily downward longwave radiation under general sky conditions using meteorological data. The input variables included air temperature, vapor pressure, daily minimum and maximum temperatures, relative humidity, and cloud cover. Data were collected from four meteorological stations, namely Chiang Mai, Ubon Ratchathani, Nakhon Pathom, and Songkhla, during the period from 2018 to 2023. Model development was based on data from 2018 to 2021 using graphical analysis and multiple linear regressions to identify strong relationships and build predictive equations. Seven models were formulated, each using different combinations of meteorological variables. These models were then validated using independent data from 2022–2023. The results showed that downward longwave radiation is largely correlated with meteorological parameters. The developed models provided accurate estimates, closely matching observed radiation values. The root mean square error relative to the mean measured values (RMSE) ranged from 1.7% to 4.4%, and mean bias error relative to the mean measured values (MBE) ranged from -1.4% to 3.9%. The developed model gave a more accurate value of daily longwave radiation. The findings indicate that the proposed models are effective tools for estimating longwave radiation in areas without direct measurements, supporting further research in climate and energy studies.

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Related topics: Atmospheric aerosols and clouds · Climate variability and models · Meteorological Phenomena and Simulations