Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Fenghua Ling"'
Autor:
Fenghua Ling, Zeyu Lu, Jing-Jia Luo, Lei Bai, Swadhin K. Behera, Dachao Jin, Baoxiang Pan, Huidong Jiang, Toshio Yamagata
Publikováno v:
npj Climate and Atmospheric Science, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract 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. Traditional approaches, includi
Externí odkaz:
https://doaj.org/article/43d223d7bb744dd89a5066d157088930
Autor:
Shixin Wang, Tiexi Chen, Jing-Jia Luo, Meng Gao, Hongchao Zuo, Fenghua Ling, Jianlin Hu, Chaoxia Yuan, Yuanjian Yang, Lina Wang, Huaming Huang, Naiang Wang, Yaojun Li, Toshio Yamagata
Publikováno v:
npj Climate and Atmospheric Science, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Understanding both positive and negative impacts of climate change is essential for comprehensively assessing and well adapting to the impacts of changing climate. Conventionally, climate warming is revealed to negatively impact human activi
Externí odkaz:
https://doaj.org/article/a959ea0822d5430eaffb467e4847bd9c
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-9 (2022)
A multi-task learning model is proposed to improve seasonal-to-annual prediction of the Indian Ocean Dipole (IOD). This model captures the inter-basin interactions between ENSO and IOD and distinctive precursors of positive and negative IOD events.
Externí odkaz:
https://doaj.org/article/3d029dd86bca46aa83ccf66b3627c4ea
Publikováno v:
Environmental Research Letters, Vol 19, Iss 5, p 054003 (2024)
The northwestern Pacific monsoon trough (NWPMT) deeply impacts socio-economic development and human security over East Asia by supplying moisture to the summer monsoon rainfall and modulating tropical cyclone activities. However, considerable inter-m
Externí odkaz:
https://doaj.org/article/8f3be5e69de84a318b79743ffbdb8889
Autor:
Ming Feng, Fabio Boschetti, Fenghua Ling, Xuebin Zhang, Jason R. Hartog, Mahmood Akhtar, Li Shi, Brint Gardner, Jing-Jia Luo, Alistair J. Hobday
Publikováno v:
Frontiers in Climate, Vol 4 (2022)
In this study, we train a convolutional neural network (CNN) model using a selection of Coupled Model Intercomparison Project (CMIP) phase 5 and 6 models to investigate the predictability of the sea surface temperature (SST) variability off the Sumat
Externí odkaz:
https://doaj.org/article/e5d02d169a2b49fab44c3331c842c145
Publikováno v:
Agriculture, Vol 13, Iss 5, p 927 (2023)
As one of the physical quantities concerned in agricultural production, soil moisture can effectively guide field irrigation and evaluate the distribution of water resources for crop growth in various regions. However, the spatial variability of soil
Externí odkaz:
https://doaj.org/article/03b537a9930444f6ac8983779b869bee
Publikováno v:
Environmental Research Letters, Vol 17, Iss 12, p 124025 (2022)
As most global climate models (GCM) suffer from large biases in simulating/predicting summer precipitation over China, it is of great importance to develop suitable bias-correction methods. This study proposes two pathways of bias-correction with dee
Externí odkaz:
https://doaj.org/article/e8eb126b276243f4917b01535b123f87
Publikováno v:
Atmospheric and Oceanic Science Letters. :100347
Publikováno v:
Nature communications. 13(1)
As one of the most predominant interannual variabilities, the Indian Ocean Dipole (IOD) exerts great socio-economic impacts globally, especially on Asia, Africa, and Australia. While enormous efforts have been made since its discovery to improve both
Variations in the El Niño/Southern Oscillation (ENSO) are associated with a wide array of regional climate extremes and ecosystem impacts. Robust, long-lead forecasts would therefore be valuable for managing policy responses. But despite decades of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03f0e5b81d83d03824a4d202e376a9d6
https://doi.org/10.5194/egusphere-egu2020-21603
https://doi.org/10.5194/egusphere-egu2020-21603