Evaluation of models for the dew point temperature determination

Krzysztof Górnicki

Radosław Winiczenko

Agnieszka Kaleta

Aneta Choińska


The accuracy of the available from the literature models for the dew point temperature determination was compared. The proposal of the modelling using artificial neural networks was also given. The experimental data were taken from the psychrometric tables. The accuracies of the models were measured using the mean bias error MBE, root mean square error RMSE, correlation coefficient R, and reduced chi-square χ2. Model M3, especially with constants A=237, B=7.5, gave the best results in determining the dew point temperature (MBE: -0.0229 – 0.0038 K, RMSE: 0.1259 – 0.1286 K, R=0.9999, χ2: 0.0159 – 0.0166 K2). Model M1 with constants A=243.5, B=17.67 and A=243.3, B=17.269 can be also considered as appropriate (MBE=-0.0062 and -0.0078 K, RMSE=0.1277 and 0.1261 K, R=0.9999, χ2=0.0163 and 0.0159 K2). Proposed ANN model gave the good results in determining the dew point temperature (MBE=-0.0038 K, RMSE=0.1373 K, R=0.9999, χ2=0.0189 K2).


dew point temperature, relative humidity, model, artificial neural networks

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Cited by

Górnicki, K., Winiczenko, R., Kaleta, A., & Choińska, A. (2017). Evaluation of models for the dew point temperature determination. Technical Sciences, 20(3), 241–257. https://doi.org/10.31648/ts.5425

Krzysztof Górnicki 

Radosław Winiczenko 

Agnieszka Kaleta 

Aneta Choińska