|
|
|
|
|
Yang Lu, Xiaochun Wang, Yijun He, Jiping Liu, Jiangbo Jin, Jian Cao, Juanxiong He, Yongqiang Yu, Xin Gao, Mirong Song and Yiming Zhang
Two coupled climate models that participated in the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0), and the Nanjing University of Information Science and Technol...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lijun Jin, Changsheng Yan, Baojun Yuan, Jing Liu and Jifeng Liu
The source area of the Yellow River (SAYR) in China is an important water yield and water-conservation area in the Yellow River. Understanding the variability in rainfall and flood over the SAYR region and the related mechanism of flood-causing rainfall ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kai Mao, Chang Liu, Shaoqing Zhang and Feng Gao
Satellite remote sensing can provide observation information of the sea surface, and using the sea surface information to reconstruct the subsurface temperature (ST) and subsurface salinity (SS) information has significant application values. This study ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juanjuan Feng, Jia Li, Wenjie Zhong, Junhui Wu, Zhiqiang Li, Lingshuai Kong and Lei Guo
Arctic sea ice prediction is of great practical significance in facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Stanislav Myslenkov, Ksenia Silvestrova, Viktor Krechik and Mariia Kapustina
Upwelling leads to a sharp and strong decrease in water temperature in the coastal zone of the southeastern Baltic Sea. The quality of existing hydrodynamic models cannot fully meet the requirements of accurate upwelling forecasts. This study provides in...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chouaib El Hachimi, Salwa Belaqziz, Saïd Khabba, Badreddine Sebbar, Driss Dhiba and Abdelghani Chehbouni
Smart management of weather data is an essential step toward implementing sustainability and precision in agriculture. It represents an important input for numerous tasks, such as crop growth, development, yield, and irrigation scheduling, to name a few....
ver más
|
|
|
|
|
|
|
|
|
|
|
Vinayak Bhanage, Han Soo Lee, Tetsu Kubota, Radyan Putra Pradana, Faiz Rohman Fajary, I Dewa Gede Arya Putra and Hideyo Nimiya
This study evaluates the performance of 6 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating temperature, precipitation, wind speed, and relative humidity over 29 cities in Indonesia. Modern-Era Ret...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andre D. L. Zanchetta, Paulin Coulibaly and Vincent Fortin
The use of machine learning (ML) for predicting high river flow events is gaining prominence and among its non-trivial design decisions is the definition of the quantitative precipitation estimate (QPE) product included in the input dataset. This study p...
ver más
|
|
|
|
|
|
|
|
|
|
|
Frans van Eeden, Georgios Klonaris, Jeffrey Verbeurgt, Peter Troch and Alain De Wulf
This paper presents the analysis of spectral wind-wave modelling (using SWAN) of the North Sea focusing on the modelled wave parameters along the Belgian coast. Two wind databases were used to drive the model: ECMWF-ERA5 reanalysis and the Dutch Offshore...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giuseppe Frustaci, Samantha Pilati, Cristina Lavecchia and Enea Marco Montoli
Temperature is the most used meteorological variable for a large number of applications in urban resilience planning, but direct measurements using traditional sensors are not affordable at the usually required spatial density. On the other hand, spacebo...
ver más
|
|
|
|
|
|