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Shu Wu, Momcilo Markus, David Lorenz, James R. Angel and Kevin Grady
Many studies have projected that as the climate changes, the magnitudes of extreme precipitation events in the Northeastern United States are likely to continue increasing, regardless of the emission scenario. To examine this issue, we analyzed observed ...
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Yong Liu, Xiaohui Yan, Wenying Du, Tianqi Zhang, Xiaopeng Bai and Ruichuan Nan
The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with t...
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Teerachai Amnuaylojaroen
Southeast Asia (SEA), known for its diverse climate and broad coastal regions, is particularly vulnerable to the effects of climate change. The purpose of this study is to enhance the spatial resolution of temperature projections over Southeast Asia (SEA...
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Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
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Bounhome Kimmany, Supattra Visessri, Ponleu Pech and Chaiwat Ekkawatpanit
This study evaluated the impacts of climate change on hydro-meteorological droughts in the Chao Phraya River Basin (CPRB), Thailand under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). We used three Reginal Climate Models (...
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Basma Latrech, Taoufik Hermassi, Samir Yacoubi, Adel Slatni, Fathia Jarray, Laurent Pouget and Mohamed Ali Ben Abdallah
Systematic biases in general circulation models (GCM) and regional climate models (RCM) impede their direct use in climate change impact research. Hence, the bias correction of GCM-RCMs outputs is a primary step in such studies. This study compares the p...
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Jian Hao and Jingwei Shen
Dysentery is still a serious global public health problem. In Chongqing, China, there were 37,140 reported cases of dysentery from 2015 to 2021. However, previous research has relied on statistical data of dysentery incidence rate data based on administr...
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Chi Xu, Chuanqi Liu, Wanchang Zhang, Zhenghao Li and Bangsheng An
Complex terrain, the sparse distribution of rain gauges, and the poor resolution and quality of satellite data in remote areas severely restrict the development of watershed hydrological modeling, meteorology, and ecological research. In this study, base...
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Pierre Goovaerts, Thomas Hermans, Peter F. Goossens and Ellen Van De Vijver
This paper addresses two common challenges in analyzing spatial epidemiological data, specifically disease incidence rates recorded over small areas: filtering noise caused by small local population sizes and deriving estimates at different spatial scale...
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Yan Jin, Yong Ge, Haoyu Fan, Zeshuo Li, Yaojie Liu and Yan Jia
Accurate spatial distribution of gridded gross domestic product (GDP) data is crucial for revealing regional disparities within administrative units, thus facilitating a deeper understanding of regional economic dynamics, industrial distribution, and urb...
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