Results 121 to 130 of about 1,490 (205)

TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting. [PDF]

Sci Data, 2020
Franch G, Maggio V, Coviello L, Pendesini M, Jurman G, Furlanello C.   +5 more
europepmc   +1 more source

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

, 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  

Precipitation Nowcasting Using Physics Informed Discriminator Generative Models

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  

Extreme Precipitation Nowcasting using Transformer-based Generative models

Extreme precipitation, like floods and landslides, poses major risks to safety and the economy, underscoring the need for sophisticated weather forecasting to predict these events accurately, enhancing readiness and resilience.
Roy, Ankush (author)
core   +1 more source

Axial-UNet: A Neural Weather Model for Precipitation Nowcasting

Accurately predicting short-term precipitation is critical for weather-sensitive applications such as disaster management, aviation, and urban planning. Traditional numerical weather prediction can be computationally intensive at high resolution and short lead times. In this work, we propose a lightweight UNet-based encoder-decoder augmented with axial-
Sumit Mamtani, Maitreya Sonawane
openaire   +2 more sources

PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling

Precipitation nowcasting plays a pivotal role in socioeconomic sectors, especially in severe convective weather warnings. Although notable progress has been achieved by approaches mining the spatiotemporal correlations with deep learning, these methods ...
Bai, Lei, Yang, Xiaokang, Ouyang, Wanli, Gong, Junchao, Zhang, Wenlong, Chen, Kun, Fei, Ben, Tu, Siwei, Yang, Weidong   +8 more
core  

Self-supervised Spatial-Temporal Learner for Precipitation Nowcasting

Nowcasting, the short-term prediction of weather, is essential for making timely and weather-dependent decisions. Specifically, precipitation nowcasting aims to predict precipitation at a local level within a 6-hour time frame. This task can be framed as
Li, Haotian, Siebes, Arno, Mehrkanoon, Siamak   +2 more
core  

Precipitation Analysis from AMSU (Nowcasting SAF)

, 1999
We describe a method to remotely sense precipitation and classify its intensity over water, coast, and land surfaces. This method is intended to be used in a nowcasting environment.
Bennartz, Ralf, Thoss, Anke, Dybbroe, Adam, Michelson, Daniel   +3 more
core  

Skillful Precipitation Nowcasting Using Physical‐Driven Diffusion Networks

Accurate and timely precipitation nowcasting is essential for numerous applications including emergency services, infrastructure management, and agriculture. Recently, deep learning (DL) techniques have shown promise in enhancing nowcasting capabilities.
Alexis K. H. Lau, Jimmy C. H. Fung, Fung, Jimmy C.H., Lau, Alexis K.H., Rui Wang, Wang, Rui   +5 more
core   +1 more source

GSMaP RIKEN Nowcast: Global Precipitation Nowcasting with Data Assimilation

Journal of the Meteorological Society of Japan. Ser. II, 2019
OTSUKA, Shigenori, KOTSUKI, Shunji, OHHIGASHI, Marimo, MIYOSHI, Takemasa   +3 more
openaire   +2 more sources