[PDF][PDF] 基于机器学习的高精度高分辨率气象因子时空估计
方颖， 李连发 - 地球信息科学学报, 2019 - sssampling.cn
气象变量常作为重要的影响因子出现在环境污染, 疾病健康和农业等领域,
而高分辨率的气象资料可作为众多研究的基础数据, 对推进相关研究的发展意义重大 …
而高分辨率的气象资料可作为众多研究的基础数据, 对推进相关研究的发展意义重大 …
[PDF][PDF] An optimal method for high-resolution population geo-spatial data
RSA Al Kloub - CMC-COMPUTERS MATERIALS & CONTINUA, 2022 - cdn.techscience.cn
Mainland China has a poor distribution of meteorological stations. Existing models'
estimation accuracy for creating high-resolution surfaces of meteorological data is restricted …
estimation accuracy for creating high-resolution surfaces of meteorological data is restricted …
Mapping near-surface air temperature, pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution
T Li, X Zheng, Y Dai, C Yang, Z Chen, S Zhang… - … in Atmospheric Sciences, 2014 - Springer
As part of a joint effort to construct an atmospheric forcing dataset for mainland China with
high spatiotemporal resolution, a new approach is proposed to construct gridded near …
high spatiotemporal resolution, a new approach is proposed to construct gridded near …
An Optimal Method for High-Resolution Population Geo-Spatial Data.
R Sameer, AA Kloub - Computers, Materials & Continua, 2022 - search.ebscohost.com
Mainland China has a poor distribution of meteorological stations. Existing models'
estimation accuracy for creating high-resolution surfaces of meteorological data is restricted …
estimation accuracy for creating high-resolution surfaces of meteorological data is restricted …
[HTML][HTML] 基于深度学习方法的气温预报技术应用与评估
陈鹤， 蔡荣辉， 陈静静， 傅承浩， 周莉， 陈龙 - 气象, 2022 - qxqk.nmc.cn
基于2017—2019 年欧洲中期天气预报中心的全球预报系统(ECMWF-IFS), 结合对应时间段站点
观测实况, 采用深度学习方法建立了多层全连接神经网络模型(简称DL 模型), 对未来84 h …
观测实况, 采用深度学习方法建立了多层全连接神经网络模型(简称DL 模型), 对未来84 h …
[HTML][HTML] 基于机器学习的数值天气预报风速订正研究
孙全德， 焦瑞莉， 夏江江， 严中伟， 李昊辰， 孙建华… - 气象, 2019 - qxqk.nmc.cn
对风速进行准确预测是精细化天气预报服务(如风能发电, 冬季奥运会赛场条件保障等)
的重要环节. 本文基于三种机器学习算法(LASSO 回归, 随机森林和深度学习) …
的重要环节. 本文基于三种机器学习算法(LASSO 回归, 随机森林和深度学习) …
[HTML][HTML] 基于机器学习的复杂地形下短期数值天气预报误差分析与订正
任萍， 陈明轩， 曹伟华， 王在文， 韩雷， 宋林烨， 杨璐 - 气象学报, 2020 - html.rhhz.net
初步研发了一套基于机器学习方法XGBoost 且考虑地形特征影响的数值预报多模式集成技术,
并与传统的等权重平均和线性回归方法的集成效果进行了对比分析. 利用北京地区快速更新循环 …
并与传统的等权重平均和线性回归方法的集成效果进行了对比分析. 利用北京地区快速更新循环 …
[HTML][HTML] Evaluation of MSWX bias-corrected meteorological forcing datasets in China
H Lin, Y Yang, S Wang, S Wang, J Tang, G Dong - Sustainability, 2023 - mdpi.com
Near-surface meteorological forcing (NSMF) datasets, mixed observations, and model
forecasts are widely used in global climate change and sustainable development studies …
forecasts are widely used in global climate change and sustainable development studies …
[HTML][HTML] Geographically weighted machine learning and downscaling for high-resolution spatiotemporal estimations of wind speed
L Li - Remote Sensing, 2019 - mdpi.com
High-resolution spatiotemporal wind speed mapping is useful for atmospheric
environmental monitoring, air quality evaluation and wind power siting. Although modern …
environmental monitoring, air quality evaluation and wind power siting. Although modern …
[HTML][HTML] Spatiotemporal forecasting model based on hybrid convolution for local weather prediction post-processing
L Xiang, J Xiang, J Guan, L Zhang, Z Cao… - Frontiers in Earth …, 2022 - frontiersin.org
Future weather conditions can be obtained based on numerical weather prediction (NWP);
however, NWP is unsatisfied with precise local weather prediction. In this study, we propose …
however, NWP is unsatisfied with precise local weather prediction. In this study, we propose …