Article
Geosciences, Multidisciplinary
Tsung-Lin Hsieh, Wenchang Yang, Gabriel A. Vecchi, Ming Zhao
Summary: The future projection of tropical cyclone frequency is highly uncertain. Recent studies suggest that the spread of seed patterns is correlated with the spread of cyclone patterns. The relationship between seed frequency and climate perturbations can be explained using a downscaling theory.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Engineering, Marine
Wei-Shiun Lu, Chi-Hsiang Tseng, Shih-Chun Hsiao, Wen-Son Chiang, Kai-Cheng Hu
Summary: Taiwan's coastal hazards may worsen due to climate change. Analyzing wave climate characteristics at different time scales provides a reference for understanding the impact of climate change on coastal environments.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Geosciences, Multidisciplinary
Xianyu Yang, Douwang Li, Zhou Yang, Kai Wu, Luyong Ji, Ziqiang Zhou, Yaqiong Lu
Summary: The warming climate driven by global change has the potential to alter regional and global hydrologic cycles, leading to significant changes in the spatial and temporal patterns of precipitation. This study examines the historical variations of precipitation in Northwest China (NW) from 1951 to 2020 and uses a regional climate model to investigate future precipitation patterns in this region. The findings suggest a significant decrease in precipitation, especially in summer, across the southern and eastern parts of NW in the 2050s under the SSP585 climate scenario. The study provides valuable information for regional mitigation and adaption strategies to potential impacts of future climate change on NW.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Multidisciplinary Sciences
Richard S. J. Tol
Summary: Poorer and hotter countries are more vulnerable to climate change, experiencing more negative impacts. The distribution of impacts within countries varies significantly, with almost three-quarters of people facing worse impacts than their country average. The differences between countries are larger than within-country variations overall.
ANNALS OF THE NEW YORK ACADEMY OF SCIENCES
(2021)
Article
Engineering, Civil
M. S. VishnuPriya, V Agilan
Summary: Understanding the impact of climate change on extreme precipitation is crucial for sustainable infrastructure development and water resources management. The daily scaling method proves to be the best change factor method for downscaling extreme precipitation, particularly the variants with 100 change factors.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Xianghua Niu, Xikun Wei, Wei Tian, Guojie Wang, Wenhui Zhu
Summary: Land evaporation is an important variable in climate change, water cycle, and water resources management. Using a deep learning-based model, researchers found that future land evaporation is projected to increase, with more significant changes in high emission scenarios and larger increases in spring and summer compared to autumn and winter.
Article
Engineering, Civil
Shadi Arfa, Mohsen Nasseri, Hassan Tavakol-Davani
Summary: This study assessed and compared the effects of different downscaling methods on an urban network in Tehran, Iran. The findings suggest that DMDM outperforms other techniques in daily downscaling, and the GEV distribution method is more effective in sub-daily disaggregation. Simulation results indicate a higher risk of urban flooding under the RCP 8.5 scenario compared to RCP 4.5 and RCP 2.6 scenarios.
WATER RESOURCES MANAGEMENT
(2021)
Article
Environmental Sciences
Erik Kusch, Richard Davy
Summary: Advances in climate science have made widely used observation data obsolete, prompting the development of a workflow to integrate improved data into biological analyses. The ERA5 product family offers high-resolution climate variables and can be downscaled using Kriging. KrigR provides a user-friendly tool for obtaining tailored climate data at high resolutions.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Meteorology & Atmospheric Sciences
Jose Gonzalez-Abad, Jorge Bano-Medina, Jose Manuel Gutierrez
Summary: This study evaluates deep downscaling models using explainable artificial intelligence techniques, introduces two new diagnostic methods, and demonstrates their role in design and evaluation. The results show the usefulness of incorporating explainable artificial intelligence techniques into statistical downscaling evaluation frameworks, especially when working with large regions and/or under climate change conditions.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Meteorology & Atmospheric Sciences
Aaron B. Wilson, Alvaro Avila-Diaz, Lais F. Oliveira, Cristian F. Zuluaga, Bryan Mark
Summary: The study analyzes the climate extremes in the Eastern Corn Belt Region (ECBR) and reveals significant changes in extreme temperatures and precipitation. However, the variability among different models and watersheds poses challenges in constraining the uncertainty in future climate models.
WEATHER AND CLIMATE EXTREMES
(2022)
Article
Meteorology & Atmospheric Sciences
Jose Gonzalez-Abad, Jorge Bano-Medina, Jose Manuel Gutierrez
Summary: This study compares multiple deep learning models extracted from the literature for downscaled temperature prediction under changing climatic conditions. The researchers introduce two novel explainable artificial intelligence techniques and demonstrate their applications in designing and evaluating deep learning models.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Environmental Sciences
Song Liu, Jia Xing, Daniel M. Westervelt, Shuchang Liu, Dian Ding, Arlene M. Fiore, Patrick L. Kinney, Yuqiang Zhang, Mike Z. He, Hongliang Zhang, Shovan K. Sahu, Fenfen Zhang, Bin Zhao, Shuxiao Wang
Summary: This study found that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, especially under the 2050 MTFR emissions scenario.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Energy & Fuels
Jose C. Fernandez-Alvarez, Xurxo Costoya, Albenis Perez-Alarcon, Stefan Rahimi, Raquel Nieto, Luis Gimeno
Summary: This study analyzes the future changes in wind speed in the North Atlantic Ocean and its impact on offshore wind energy resources in three potential subregions. The results show that wind speed is expected to decrease in winter and spring, but increase in summer and autumn, especially in tropical regions. Significant increases in wind power density are expected in the Iberian Peninsula subregion during the summer, while the US subregion may see decreases in winter but increases in summer and autumn. The Caribbean Sea will experience a decrease in the Yucatan Basin and considerable increases in the Colombia and Venezuela basins.
Article
Ecology
Shengqi Jian, Sijia Shi, Jingkai Cui, Tiansheng Zhu, Caihong Hu
Summary: Increasing climate change affects vegetation dynamics and the hydrological cycle. Studying the impact of climate change on vegetation is crucial for predicting future climate change and understanding its effects on the hydrological cycle. This study focuses on the Yellow River Basin in China and uses meteorological analysis and remote sensing data to investigate the relationship between climate change and vegetation. The results show an increasing trend in vegetation cover under different emission scenarios, with temperature being the dominant factor. This study provides insights into vegetation response to climate change and supports the formulation of ecological protection measures in the Yellow River Basin.
FRONTIERS IN FORESTS AND GLOBAL CHANGE
(2023)
Article
Environmental Sciences
Quang-Van Doan, Fei Chen, Hiroyuki Kusaka, Anurag Dipankar, Ansar Khan, Rafiq Hamdi, Matthias Roth, Dev Niyogi
Summary: In an urban agglomeration in the tropics, Singapore, future global warming is predicted to increase the frequency and intensity of extreme precipitation events. The intensification of extreme precipitation can reach maximum rates, implying that extreme events will become more extreme. However, the increase in intensity is less for moderate and light precipitation. Furthermore, global warming dampens the urban effect on extreme precipitation events.
Article
Multidisciplinary Sciences
Keila Rego Mendes, Willian Batista-Silva, Jaqueline Dias-Pereira, Marcos P. S. Pereira, Eliane V. Souza, Jose E. Serrao, Joao A. A. Granja, Eugenia C. Pereira, David J. Gallacher, Pedro R. Mutti, Duany T. C. da Silva, Rogerio S. de Souza Junior, Gabriel B. Costa, Bergson G. Bezerra, Claudio M. Santos e Silva, Marcelo F. Pompelli
Summary: Plant species in the Brazilian Caatinga region, such as Croton blanchetianus Baill, exhibit seasonal plasticity in leaf structure to optimize water use efficiency. In the wet season, shaded leaves have a larger specific leaf area, while in the dry season they are similar to leaves in full sunlight. Chloroplast structure also increases in size during the wetter months.
SCIENTIFIC REPORTS
(2022)
Article
Meteorology & Atmospheric Sciences
Haibo Du, Markus G. Donat, Shengwei Zong, Lisa Alexander, Rodrigo Manzanas, Andries Kruger, Gwangyong Choi, Jim Salinger, Hong S. He, Mai-He Li, Fumiaki Fujibe, Banzragch Nandintsetseg, Shafiqur Rehman, Farhat Abbas, Matilde Rusticucci, Arvind Srivastava, Panmao Zhai, Tanya Lippmann, Ibouraima Yabi, Michael C. Stambaugh, Shengzhong Wang, Altangerel Batbold, Priscilla Teles de Oliveira, Muhammad Adrees, Wei Hou, Claudio Moises Santos e Silva, Paulo Sergio Lucio, Zhengfang Wu
Summary: This study analyzes the changes in the frequency of extreme precipitation occurring on consecutive days (EPCD) using a global dataset and climate model simulations. The research shows that the frequency of EPCD is increasing in most land regions, particularly in North America, Europe, and the Northern Hemisphere high latitudes. The increase is primarily driven by an increase in precipitation intensity, with changes in the temporal correlation of extreme precipitation regionally amplifying or reducing the effects of intensity changes. The simulations suggest that further increases in EPCD are expected in the future under continued climate warming.
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
(2022)
Article
Meteorology & Atmospheric Sciences
Pedro R. Mutti, Vincent Dubreuil, Bergson G. Bezerra, Damien Arvor, Beatriz M. Funatsu, Claudio M. Santos E. Silva
Summary: This study characterizes the meteorological drought patterns in the Sao Francisco watershed in Brazil. The results show that water deficit periods are becoming more frequent and intense, especially in the middle and lower regions. The increase in PET trends plays a significant role in drought propagation, and large-scale teleconnection mechanisms drive drought occurrence.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Maria Leidinice da Silva, Cristiano Prestrelo de Oliveira, Joao Medeiros de Araujo, Claudio Moises Santos e Silva
Summary: This study evaluated the historical ability of 30 GCM models to simulate precipitation and temperature in different regions. The results showed that the models performed better in simulating temperature than precipitation, with lower dispersion. There were differences in the simulation abilities of different models in different regions.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2022)
Article
Agronomy
Bergson G. Bezerra, Claudio M. Santos e Silva, Keila R. Mendes, Pedro R. Mutti, Leonardo S. Fernandes, Thiago V. Marques, Clara L. Camara e Silva, Suany Campos, Mariana M. de Lima Vieira, Stela A. Urbano, Gelson dos S. Difante, Rosaria R. Ferreira, Duany T. Correa da Silva, Gabriel B. Costa, Pablo Eli S. Oliveira, Cristiano P. de Oliveira, Weber A. Gonsalves, Paulo S. Lucio
Summary: This study evaluates the impact of livestock farming on CO2 emissions budget in the Northeast region of Brazil. The research finds that grazed tropical forage has a higher carbon use efficiency and acts as a moderate CO2 sink.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Maria Leidinice da Silva, Cristiano Prestrelo de Oliveira, Claudio Moises Santos e Silva, Joao Medeiros de Araujo
Summary: In recent decades, the frequency and intensity of extreme weather events induced by global warming have significantly increased, impacting society and ecosystems. This study evaluated the performance of two climate models in simulating and projecting extreme climate indices over tropical South America. The results showed that the models have strengths and weaknesses, but overall provide important insights into the potential impacts of climate change on regional planning and development.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Bruce Kelly da Nobrega Silva, Rafaela Lisboa Costa, Fabricio Daniel dos Santos Silva, Mario Henrique Guilherme dos Santos Vanderlei, Helder Jose Farias da Silva, Jorio Bezerra Cabral, Djailson Silva da Costa, George Ulguim Pedra, Aldrin Martin Perez-Marin, Claudio Moises Santos e Silva
Summary: This study analyzed the sensitivity and vulnerability of agriculture to drought in the Northeast region of Brazil. The results showed high agricultural drought risk in the central region and semi-arid areas, as well as extreme climate vulnerability in the southern part of Bahia and western Pernambuco.
Article
Multidisciplinary Sciences
Daniele T. Rodrigues, Weber A. Goncalves, Claudio Moises S. E. Silva, Maria Helena C. Spyrides, Paulo Sergio Lucio
Summary: This article evaluates four statistical methods of multiple imputation to fill in the missing data of daily precipitation in Northeast Brazil (NEB). The BootEm method presented the best statistical results, with an average bias between the complete series and the imputed series values ranging between -0.91 and 1.30 mm/day. The Pearson correlation values ranged between 0.96, 0.91, and 0.86 for 10%, 20%, and 30% missing data, respectively. We conclude that this is an adequate method for the reconstruction of historical precipitation data in NEB.
ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS
(2023)
Article
Geochemistry & Geophysics
Maria Leidinice da Silva, Luiz Eduardo Nunes Cho-Luck, Jessica Cristina Gabriel da Silva, Cristiano Prestrelo de Oliveira, Claudio Moises Santos Silva
Summary: This study analyzes the seasonal variability of precipitation in the Amazon Basin and Northeast region of Brazil, focusing on the sensitivity of simulations using two different Planetary Boundary Layer parameterization schemes. The results show that the Reg_UW-PBL experiment performs better in simulating precipitation in the Amazon Basin, while the Reg_Holtslag experiment performs better in simulating precipitation in the Northeast region.
PURE AND APPLIED GEOPHYSICS
(2023)
Article
Geochemistry & Geophysics
Maria Leidinice da Silva, Cristiano Prestrelo de Oliveira, Claudio Moises Santos e Silva, Sullyandro Guimaraes de Oliveira, Marcele de Jesus Correa
Summary: The Regional Climate Model version 4 (RegCM4) driven by the general circulation model HadGEM2-ES from CMIP5 was used to evaluate the 1986-2005 climate simulation over tropical South America. Results show that while RegCM4 has drier biases, it provides a more realistic spatial distribution of rainfall intensity, especially in the AMZ Basin.
PURE AND APPLIED GEOPHYSICS
(2022)