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Climate data dynamics: A high-volume real world structured weather dataset.

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Summary
This summary is machine-generated.

This study presents a unique, decades-long weather dataset from Bangladesh, covering rainfall, temperature, humidity, and sunshine. The organized data is ideal for machine learning, climate research, and weather forecasting applications.

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Climate ChangeHumidityMeteorologyRainfallSunshineTemperatureTime-seriesWet-bulb globe temperature

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Area of Science:

  • Meteorology and Climatology
  • Data Science

Background:

  • The Bangladesh Meteorological Department (BMD) is the sole government body for national weather monitoring.
  • Weather data collection in Bangladesh spans several decades from 35 weather stations.

Purpose of the Study:

  • To present a comprehensive, decades-long weather dataset from Bangladesh.
  • To restructure and process raw weather data into accessible formats for research and applications.

Main Methods:

  • Data was procured from the Bangladesh Meteorological Department.
  • Raw data was meticulously restructured and processed into four key parameters: Rainfall, Temperature, Humidity, and Sunshine.
  • Data organization facilitates machine learning and statistical analysis.

Main Results:

  • A unique, decades-long dataset of key weather parameters (Rainfall, Temperature, Humidity, Sunshine) is now available.
  • The dataset is presented in a highly organized and accessible format.

Conclusions:

  • The processed dataset serves as a valuable resource for machine learning model training.
  • This data is applicable to climate research, weather forecasting, and various statistical and machine learning applications.