Validation and forecasting accuracy in models of climate change
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Cited by:
- Meng, Xiaochun & Taylor, James W., 2022. "Comparing probabilistic forecasts of the daily minimum and maximum temperature," International Journal of Forecasting, Elsevier, vol. 38(1), pages 267-281.
- Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan, 2016. "Testing the historic tracking of climate models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1234-1246.
- Young, Peter C., 2018. "Data-based mechanistic modelling and forecasting globally averaged surface temperature," International Journal of Forecasting, Elsevier, vol. 34(2), pages 314-335.
- Jenny Cifuentes & Geovanny Marulanda & Antonio Bello & Javier Reneses, 2020. "Air Temperature Forecasting Using Machine Learning Techniques: A Review," Energies, MDPI, vol. 13(16), pages 1-28, August.
- Hassani, Hossein & Silva, Emmanuel Sirimal & Gupta, Rangan & Das, Sonali, 2018.
"Predicting global temperature anomaly: A definitive investigation using an ensemble of twelve competing forecasting models,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 121-139.
- Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Sonali Das, 2015. "Predicting Global Temperature Anomaly: A Definitive Investigation Using an Ensemble of Twelve Competing Forecasting Models," Working Papers 201561, University of Pretoria, Department of Economics.
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Keywords
Validation Long range forecasting Simulation models Global circulation models Neural networks Environmental modelling DePreSys Encompassing Decadal prediction;Statistics
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