Deeplearning-based approach to improving numerical weather forecasts

• Published in: PROBLEMS IN PROGRAMMING
• Date: 2023
• Issue: 3
• Pages: 91-98
• ISSN: 1727-4907
• Author Affiliations: А.Yu. Doroshenko — Institute of Software Systems NAS of Ukraine; V.M. Shpyg — Ukrainian Hydrometeorological Institute of the State Emergency Service of Ukraine and the National Academy of Sciences of Ukraine; R.V. Kushnirenko — Institute of Software Systems NAS of Ukraine
• Keywords: чисельний прогноз погоди, чисельний прогноз, “глибоке навчання”, глибоке навчання, глибоке навчання з підкріпленням, прогнозування погоди, глибинне навчання, температура повітря, температура атмосферного повітря, метеорологічне прогнозування
• Main Authors: Doroshenko, А.Yu., Shpyg, V.M., Kushnirenko, R.V.
• Format: Article
• Language: Ukrainian
• Published: PROBLEMS IN PROGRAMMING 2023
• Subjects: deep learning; numerical weather prediction; COSMO; 2m temperature; UDC 51:681.3.06
• Online Access: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/585
• Journal Title: Problems in programming

This paper briefly describes the history of numerical weather prediction development. The difficulties, which occur in the modelling of atmospheric processes, their nature and possible ways of their mitigation, are described. It also indicates alternative methods of improving the quality of meteorol...