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  • 标题:An Evaluation of the OpenWeatherMap API versus INMET Using Weather Data from Two Brazilian Cities: Recife and Campina Grande
  • 本地全文:下载
  • 作者:Anwar Musah ; Livia Màrcia Mosso Dutra ; Aisha Aldosery
  • 期刊名称:Data
  • 印刷版ISSN:2306-5729
  • 出版年度:2022
  • 卷号:7
  • 期号:8
  • 页码:1-13
  • DOI:10.3390/data7080106
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:Certain weather conditions are inadvertently related to increased population of variousmosquitoes. In order to predict the burden of mosquito populations in the Global South, it isimperative to integrate weather-related risk factors into such predictive models. There are a lot ofonline open-source weather platforms that provide historical, current and future weather forecastswhich can be utilised for general predictions, and these electronic sources serve as an alternate optionfor weather data when physical weather stations are inaccessible (or inactive). Before using datafrom such online source, it is important to assess the accuracy against some baseline measure. In thispaper, we therefore evaluated the accuracy and suitability of weather forecasts of two parametersnamely temperature and humidity from the OpenWeatherMap API (an online weather platform) andcompared them with actual measurements collected from the Brazilian weather stations (INMET). Theevaluation was focused on two Brazilian cites, namely, Recife and Campina Grande. The intentionis to prepare an early warning model which will harness data from OpenWeatherMap API formosquito prediction.
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