[HTML][HTML] Recent frontiers of climate changes in East Asia at global warming of 1.5° C and 2° C
East Asia is undergoing significant climate changes and these changes are likely to grow in
the future. It is urgent to characterize both the mechanisms controlling climate and the …
the future. It is urgent to characterize both the mechanisms controlling climate and the …
Methods for assessing climate uncertainty in energy system models—A systematic literature review
Due to anthropological climate change, climate scientists project a significant change in
climate in the coming years. Despite the advances in climate modeling, future climate is still …
climate in the coming years. Despite the advances in climate modeling, future climate is still …
[HTML][HTML] Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100)
Dynamical downscaling is an important approach to obtaining fine-scale weather and
climate information. However, dynamical downscaling simulations are often degraded by …
climate information. However, dynamical downscaling simulations are often degraded by …
[HTML][HTML] A dynamically downscaled ensemble of future projections for the California current system
Given the ecological and economic importance of eastern boundary upwelling systems like
the California Current System (CCS), their evolution under climate change is of considerable …
the California Current System (CCS), their evolution under climate change is of considerable …
[HTML][HTML] Statistical downscaling and projection of future temperatures across the Loess Plateau, China
X Fan, L Jiang, J Gou - Weather and Climate Extremes, 2021 - Elsevier
Abstract The Loess Plateau in China is one of the most erosive regions in the world,
especially under warming climate conditions, which are aggravating evapotranspiration and …
especially under warming climate conditions, which are aggravating evapotranspiration and …
Using machine learning to cut the cost of dynamical downscaling
Global climate models (GCMs) are commonly downscaled to understand future local climate
change. The high computational cost of regional climate models (RCMs) limits how many …
change. The high computational cost of regional climate models (RCMs) limits how many …
[HTML][HTML] An evaluation framework for downscaling and bias correction in climate change impact studies
Climate change impact studies commonly use impact models (such as hydrological or crop
models) forced with corrected climate input data from global climate models. A range of …
models) forced with corrected climate input data from global climate models. A range of …
Wrf gray-zone dynamical downscaling over the Tibetan Plateau during 1999–2019: Model performance and added value
Abstract The Tibetan Plateau (TP) is an important component of the global climate system,
while the characteristics of its climate are poorly represented in most regional climate …
while the characteristics of its climate are poorly represented in most regional climate …
Deep learning in statistical downscaling for deriving high spatial resolution gridded meteorological data: A systematic review
Y Sun, K Deng, K Ren, J Liu, C Deng, Y Jin - ISPRS Journal of …, 2024 - Elsevier
Nowadays, meteorological data plays a crucial role in various fields such as remote sensing,
weather forecasting, climate change, and agriculture. The regional and local studies call for …
weather forecasting, climate change, and agriculture. The regional and local studies call for …
Methodology of the constraint condition in dynamical downscaling for regional climate evaluation: A review
The dynamical downscaling method with a regional climate model (RCM) is widely used to
assess the spatially detailed information about regional climate. However, the RCM result is …
assess the spatially detailed information about regional climate. However, the RCM result is …