{"title":"Climate data dynamics: A high-volume real world structured weather dataset","authors":"Md Zubair , Md. Nafiz Ishtiaque Mahee , Khondaker Masfiq Reza , Md. Shahidul Salim , Nasim Ahmed","doi":"10.1016/j.dib.2024.111156","DOIUrl":null,"url":null,"abstract":"<div><div>The dataset at hand is a unique resource, officially procured from the Bangladesh Meteorological Department, the sole government institution that diligently monitors weather through 35 strategically placed weather stations across the nation. This dataset is a treasure trove of actual data spanning several decades, from the inception of each weather station to the present. It has been meticulously restructured and processed into four (Rainfall, Temperature, Humidity, and Sunshine) key weather parameters, presented in a highly organized and accessible format. This format not only facilitates its use in the machine-learning training process but also opens up avenues for its application in climate research, weather forecasting, and a myriad of other statistical and machine-learning applications.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"57 ","pages":"Article 111156"},"PeriodicalIF":1.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924011181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The dataset at hand is a unique resource, officially procured from the Bangladesh Meteorological Department, the sole government institution that diligently monitors weather through 35 strategically placed weather stations across the nation. This dataset is a treasure trove of actual data spanning several decades, from the inception of each weather station to the present. It has been meticulously restructured and processed into four (Rainfall, Temperature, Humidity, and Sunshine) key weather parameters, presented in a highly organized and accessible format. This format not only facilitates its use in the machine-learning training process but also opens up avenues for its application in climate research, weather forecasting, and a myriad of other statistical and machine-learning applications.
期刊介绍:
Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.