Results 1 to 10 of about 12,074 (267)

Dynamical and statistical downscaling of seasonal temperature forecasts in Europe: Added value for user applications

Climate Services, 2018
This work describes the results of a comprehensive intercomparison experiment of dynamical and statistical downscaling methods performed in the framework of the SPECS (http://www.specs-fp7.eu) and EUPORIAS (http://www.euporias.eu) projects for seasonal ...
R. Manzanas, J.M. Gutiérrez, J. Fernández, E. van Meijgaard, S. Calmanti, M.E. Magariño, A.S. Cofiño, S. Herrera   +7 more
doaj   +1 more source

Evaluation of dynamical downscaling prediction of BCC second-generation model system product to precipitation over Chongqing during the flood season of 2016

暴雨灾害, 2019
To evaluate the dynamical downscaling prediction skill on the averaged precipitation in flood season over Chongqing, using WRF model based on Beijing Climate Center (BCC) second-generation seasonal prediction model system (BCCv2) product, we have ...
Haonan ZHU, Xiaoran LIU, Yao WU, Xinning DONG, Hongyu TANG, Bingyan CHENG   +5 more
doaj   +1 more source

Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction

npj Climate and Atmospheric Science
As our planet is entering into the “global boiling” era, understanding regional climate change becomes imperative. Effective downscaling methods that provide localized insights are crucial for this target.
Fenghua Ling, Zeyu Lu, Jing-Jia Luo, Lei Bai, Swadhin K. Behera, Dachao Jin, Baoxiang Pan, Huidong Jiang, Toshio Yamagata   +8 more
doaj   +1 more source

A downscaling algorithm for obtaining hourly gross primary productivity maps at the global scale

International Journal of Applied Earth Observations and Geoinformation
Monitoring global vegetation gross primary productivity (GPP) at an hourly scale is critical for understanding terrestrial carbon dynamics, while recent global GPP products often suffer from limitations in their temporal resolutions.
Yong Wang, Jiyan Wang, Wei Zhao, Yanqing Yang, Jiujiang Wu, Xiaobin Guan, Xinyao Xie   +6 more
doaj   +1 more source

PhySoilNet: A deep learning downscaling model for microwave satellite soil moisture with physical rule constraint

International Journal of Applied Earth Observations and Geoinformation
Surface soil moisture (SM) plays an important role in water and energy cycles. Passive microwave remote sensing observation has become the main means of obtaining large-scale surface SM.
Zhenheng Xu, Hao Sun, JinHua Gao, Yunjia Wang, Dan Wu, Tian Zhang, Huanyu Xu   +6 more
doaj   +1 more source

Study on the Effect of Shortwave Radiation in Land Surface Temperature Downscaling over Rugged Terrain

Remote Sensing
Land surface temperature (LST) is an important parameter in the surface system with drastic variation in spatial and temporal domains. The protection of the ecological environment in mountainous areas and the monitoring of natural disasters require the ...
Shumin Wang, Jie Cheng, Qiang Liu
doaj   +1 more source

A New Surface Waters Downscaling Approach Applicable at Global Scale

Remote Sensing
A surface water extent downscaling framework was developed in the past using a floodability index based on topography. We presented here a new downscaling approach including several improvements.
Thu-Hang Nguyen, Filipe Aires
doaj   +1 more source

A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System

Atmosphere, 2015
Based on the operational regional ensemble prediction system (REPS) in China Meteorological Administration (CMA), this paper carried out comparison of two initial condition perturbation methods: an ensemble transform Kalman filter (ETKF) and a dynamical
Hanbin Zhang, Jing Chen, Xiefei Zhi, Yanan Wang   +3 more
doaj   +1 more source

Spatial Downscaling of Nighttime Land Surface Temperature Based on Geographically Neural Network Weighted Regression Kriging

Remote Sensing
Land surface temperature (LST) has a wide application in Earth Science-related fields, and spatial downscaling is an important method to retrieve high-resolution LST data.
Jihan Wang, Nan Zhang, Laifu Zhang, Haoyu Jing, Yiming Yan, Sensen Wu, Renyi Liu   +6 more
doaj   +1 more source

Differences between Machine Learning and Traditional Downscaling Method in Processing Summer Meteorological Elements in the Yellow River Basin

Gaoyuan qixiang
Global Climate Models （GCMs） are the primary tools currently used to predict future climate change； however， their coarse spatial resolution limits their ability to assess localized impacts of climate change.To address this issue， statistical downscaling
Han CHEN, Xiaodan GUAN, Tingting MA
doaj   +1 more source