Baselight

Daily Precipitation Indicators For India

Exploring Weather and Climate Conditions

@kaggle.thedevastator_daily_precipitation_indicators_for_india_2015_20

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About this Dataset

Daily Precipitation Indicators For India


Daily Precipitation Indicators for India

Exploring Weather and Climate Conditions

By Humanitarian Data Exchange [source]


About this dataset

This dataset comprises of five years of precipitation indicators from base stations across India, providing an in-depth insight into the country's climate. The four indicators provide a comprehensive assessment of weather and climate conditions, including: Total Precipitation (TPCP), Maximum Snow Depth (MXSD), Total Snowfall (TSNW) and Extreme Maximum Daily Precipitation (EMXP).

These indicators are compiled by the National Centers for Environmental Information which is administrated by the renowned United States government agency, the National Oceanic and Atmospheric Administration (NOAA). This data has been collected from thousands of base stations dispersed around India and provides users with valuable information.

However, because data sometimes arrives late there may be underrepresentation in recent records. Nonetheless it can still be a useful tool for understanding weather and climatic trends over time. So if you're wanting to get up close with India's climate this dataset is here to help! Last updated at 2021-09-23 with public domain license

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How to use the dataset

This dataset contains information on five key precipitation indicators from base stations across India. In order to utilize this data, it is important to first understand the four main indicators represented in this dataset:
Total Precipitation (TPCP), Maximum Snow Depth (MXSD), Total Snow Fall (TSNW) and Extreme Maximum Daily Precipitation (EMXP).

Research Ideas

  • Estimating the future climate of India by analyzing long-term trends in precipitation levels.
  • Comparing meteorological data between populated and less populated areas in India to understand the effects that human activity has on climate change.
  • Creating a tracking system for extreme weather events such as floods, droughts, and hurricanes, to help better prepare for potential disasters in these areas

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: precipitation-ind-csv-1.csv

Column name Description
date Date of the observation. (Date)
datatype Type of data collected. (String)
station Name of station where observation was recorded. (String)
value Observation value. (Float)
fl_miss Flag indicating if there’s missing values. (Boolean)
fl_cmiss Flag indicating if there’s complete/incomplete observations. (Boolean)
country Country where observation was reported. (String)
indicator Type of indicator being measured. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Humanitarian Data Exchange.

Tables

Precipitation Ind 1

@kaggle.thedevastator_daily_precipitation_indicators_for_india_2015_20.precipitation_ind_1
  • 205 KB
  • 32000 rows
  • 9 columns
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CREATE TABLE precipitation_ind_1 (
  "index" BIGINT,
  "date" TIMESTAMP,
  "datatype" VARCHAR,
  "station" VARCHAR,
  "value" BIGINT,
  "fl_miss" BIGINT,
  "fl_cmiss" BIGINT,
  "country" VARCHAR,
  "indicator" VARCHAR
);

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