[HTML][HTML] Statistical postprocessing for weather forecasts: Review, challenges, and avenues in a big data world
Statistical postprocessing techniques are nowadays key components of the forecasting
suites in many national meteorological services (NMS), with, for most of them, the objective …
suites in many national meteorological services (NMS), with, for most of them, the objective …
[HTML][HTML] Adoption of machine learning techniques in ecology and earth science
A Thessen - One Ecosystem, 2016 - oneecosystem.pensoft.net
Background The natural sciences, such as ecology and earth science, study complex
interactions between biotic and abiotic systems in order to understand and make …
interactions between biotic and abiotic systems in order to understand and make …
A deep learning method for bias correction of ECMWF 24–240 h forecasts
L Han, M Chen, K Chen, H Chen, Y Zhang, B Lu… - … in Atmospheric Sciences, 2021 - Springer
Correcting the forecast bias of numerical weather prediction models is important for severe
weather warnings. The refined grid forecast requires direct correction on gridded forecast …
weather warnings. The refined grid forecast requires direct correction on gridded forecast …
Comparative assessment of various machine learning‐based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in …
Forecasts of maximum and minimum air temperatures are essential to mitigate the damage
of extreme weather events such as heat waves and tropical nights. The Numerical Weather …
of extreme weather events such as heat waves and tropical nights. The Numerical Weather …
A novel ensemble learning for post-processing of NWP Model's next-day maximum air temperature forecast in summer using deep learning and statistical approaches
A reliable and accurate extreme air temperature in summer is necessary to prepare for and
respond to thermal disasters such as heatstroke and power outages. The numerical weather …
respond to thermal disasters such as heatstroke and power outages. The numerical weather …
数值天气预报多要素深度学习融合订正方法
张延彪， 陈明轩， 韩雷， 宋林烨， 杨璐 - 气象学报, 2022 - pubs.cstam.org.cn
数值天气预报作为现代天气预报的主流技术方法, 近年来不断朝着精细化方向发展,
但预报误差至今仍无法避免. 文中在CU-Net 模型中引入稠密卷积模块形成数值预报要素偏差 …
但预报误差至今仍无法避免. 文中在CU-Net 模型中引入稠密卷积模块形成数值预报要素偏差 …
数值模式的预报策略和方法研究进展
任宏利， 丑纪范 - 地球科学进展, 2007 - adearth.ac.cn
数值预报经历了半个多世纪的发展, 已成为当前主要的客观预报工具. 在模式和资料状况给定的
情况下, 预报效果的改善很大程度上依赖于所采用的预报策略和方法. 为此 …
情况下, 预报效果的改善很大程度上依赖于所采用的预报策略和方法. 为此 …
A hybrid multi-objective optimizer-based SVM model for enhancing numerical weather prediction: A study for the Seoul metropolitan area
Temperature forecasting is an area of ongoing research because of its importance in all life
aspects. However, because a variety of climate factors controls the temperature, it is a never …
aspects. However, because a variety of climate factors controls the temperature, it is a never …
Analysis of a Predictive Mathematical Model of Weather Changes Based on Neural Networks
BV Malozyomov, NV Martyushev, SN Sorokova… - Mathematics, 2024 - mdpi.com
In this paper, we investigate mathematical models of meteorological forecasting based on
the work of neural networks, which allow us to calculate presumptive meteorological …
the work of neural networks, which allow us to calculate presumptive meteorological …
A transformer neural network for predicting near‐surface temperature
E Alerskans, J Nyborg, M Birk… - Meteorological …, 2022 - Wiley Online Library
A new method based on the Transformer model is proposed for post‐processing of
numerical weather prediction (NWP) forecasts of 2 m air temperature. The Transformer is a …
numerical weather prediction (NWP) forecasts of 2 m air temperature. The Transformer is a …