Results 111 to 120 of about 1,500 (207)

DB-RNN: An RNN for Precipitation Nowcasting Deblurring

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Precipitation nowcasting based on artificial intelligence has garnered widespread attention in the meteorological and computer communities in recent years. While new models are continuously proposed to refresh the forecasting performance, the problem of gradual blurring of forecast maps as the forecast period extends is still serious.
Zhifeng Ma, Hao Zhang 0016, Jie Liu 0001
openaire   +2 more sources

Generative machine learning for skilful 3D radar nowcasting

npj Climate and Atmospheric Science
Timely, reliable, and robust radar nowcasting is an essential tool for extreme precipitation predictions and weather-dependent decision-making, yet existing methods still face two limitations: effective utilization of 3D radar data and robust prediction ...
Jiaquan Wan, Tao Yang, Qianhua Yu, Ranyu Liu, Weidong Li, Hao Song, Xing Wang, Junchao Wang, Fengchang Xue, Ziniu Xiao, Chunxiang Shi, Quan J. Wang, Jingyu Wang, Baoxiang Pan   +13 more
doaj   +1 more source

LangPrecip: Language-Aware Multimodal Precipitation Nowcasting

CoRR
Short-term precipitation nowcasting is an inherently uncertain and under-constrained spatiotemporal forecasting problem, especially for rapidly evolving and extreme weather events. Existing generative approaches rely primarily on visual conditioning, leaving future motion weakly constrained and ambiguous.
Xudong Ling, Tianxi Huang, Qian Dong, Tao He, Chaorong Li, Guiduo Duan   +5 more
openaire   +2 more sources

Precipitation Nowcasting Exploring the Impact of Echo Top Heights in Generative Models [PDF]

, 2023
Accurate short-term forecasting of rainfall, also known as precipitation nowcasting, is critical for a wide variety of sectors. From agriculture to early flood warning systems, reliable precipitation forecasts are essential for informed decision-making ...
Elsmann, Frederike
core  

LSTMAtU-Net: A Precipitation Nowcasting Model Based on ECSA Module. [PDF]

Sensors (Basel), 2023
Geng H, Ge X, Xie B, Min J, Zhuang X.
europepmc   +1 more source

Skilful precipitation nowcasting using deep generative models of radar. [PDF]

Nature, 2021
Ravuri S, Lenc K, Willson M, Kangin D, Lam R, Mirowski P, Fitzsimons M, Athanassiadou M, Kashem S, Madge S, Prudden R, Mandhane A, Clark A, Brock A, Simonyan K, Hadsell R, Robinson N, Clancy E, Arribas A, Mohamed S.   +19 more
europepmc   +1 more source

Improved nowcasting of precipitation based on convective analysis fields [PDF]

, 2007
The high-resolution analysis and nowcasting system INCA (Integrated Nowcasting through Comprehensive Analysis) developed at the Austrian national weather service provides three-dimensional fields of temperature, humidity, and wind on an hourly basis, and
T. Haiden, Haiden, T., M. Steinheimer, Steinheimer, M.   +3 more
core  

Precipitation Nowcasting Using Physics Informed Discriminator Generative Models [PDF]

Nowcasting leverages real-time atmospheric conditions to forecast weather over short periods. State-of-the-art models, including PySTEPS, encounter difficulties in accurately forecasting extreme weather events because of their unpredictable distribution ...
Uijlenhoet, Remko, Wang, Yanbo, Meo, Cristian, Roy, Ankush, Cher, Zeineh Bou, Dauwels, Justin, Yin, Junzhe, Imhoff, Ruben   +7 more
core   +1 more source

A Systematic Modular Approach for the Coupling of Deep-Learning-Based Models to Forecast Urban Flooding Maps in Early Warning Systems

Hydrology
Deep learning (DL) approaches to forecast precipitation and inundation areas in the short-term forecast horizon have up until now been treated as independent research problems from the model development perspective. However, for the urban hydrology area,
Juliana Koltermann da Silva, Benjamin Burrichter, Andre Niemann, Markus Quirmbach   +3 more
doaj   +1 more source

Rectifying Distribution Shift in Cascaded Precipitation Nowcasting

CoRR
Precipitation nowcasting, which aims to provide high spatio-temporal resolution precipitation forecasts by leveraging current radar observations, is a core task in regional weather forecasting. Recently, the cascaded architecture has emerged as the mainstream paradigm for deep learning-based precipitation nowcasting.
Fanbo Ju, Haiyuan Shi, Qingjian Ni
openaire   +2 more sources