Samuel C. Maina, Dorcas Mwigereri, Jonathan Weyn, Lester Mackey, Millicent Ochieng
{"title":"Evaluation of Dependency Structure for Multivariate Weather Predictors using Copulas","authors":"Samuel C. Maina, Dorcas Mwigereri, Jonathan Weyn, Lester Mackey, Millicent Ochieng","doi":"10.1145/3616384","DOIUrl":"https://doi.org/10.1145/3616384","url":null,"abstract":"In the Global South, the effects of climate change have resulted in more frequent and severe weather events such as droughts, floods, and storms, leading to crop failures, food insecurity, and job loss. These effects are expected to increase in intensity in the future, further disadvantaging already marginalized communities and exacerbating existing inequalities. Hence the need for prevention and adaptation is urgent, but accurate weather forecasting remains challenging, despite advances in machine learning and numerical modeling, due to complex interaction of atmospheric and oceanic variables. This research aims to explore the potential of vine copulas in explaining complex relationships of different weather variables in three African locations. Copulas separate marginal distributions from the dependency structure, offering a flexible way to model dependence between random variables for improved risk assessments and simulations. Vine copulas are based on a variety of bivariate copulas, including Gaussian, Student’s t, Clayton, Gumbel, and Frank copulas, and they are effective in high-dimensional problems and offer a hierarchy of trees to express conditional dependence. In addition, we propose how this framework can be applied within the subseasonal forecasting models to enhance the prediction of different weather events or variables.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135396369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Characterizing Swiss Alpine Lakes: from Wikipedia to Citizen Science","authors":"Yuanhui Lin, Daniel Gatica-Perez","doi":"10.1145/3617128","DOIUrl":"https://doi.org/10.1145/3617128","url":null,"abstract":"Within the scope of a citizen science project that aims to understand the ecological impact of climate change on bacteria communities in Swiss alpine lakes, we designed and implemented an interactive information platform using data collected from Wikipedia, project-specific data, and other sources. By presenting information about Swiss alpine lakes in an interactive way, the goal of the platform is to raise awareness among the public about the state of Swiss alpine lakes, and ultimately to contribute to the conservation of these ecosystems by engaging citizens. Volunteers were invited to use and assess the platform, by answering questions about alpine lake facts and platform usability. The results show that users can accurately extract factual information from the platform. User feedback was also used to improve the platform functionalities. Finally, an online crowdsourcing activity for lake polygon drawing was conducted to enrich the Swiss alpine lake database with this information. The results show that users can implement this task with high quality.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135740145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}