Weather Data Retriever

A tool for retrieving weather data from multiple sources.
(Currently supporting NASA's POWER Project and Open-Meteo)

Requirements

Python Version

• Main supported version: 3.11
• Other supported versions: 3.8, 3.9, 3.10

Ensure one of these Python versions is installed on your computer.

Environment & Dependencies

To install this repository, you have two options:

• Install as a project repository.
• Install directly from Pypu using pip within your preferred environment.

Project Installation

Ensure Python is installed, then create a virtual environment and activate it:

python3 -m venv /path/to/new/virtual/environment

source /path/to/new/virtual/environment/bin/activate

Install dependencies with:

pip install -r requirements.txt

Package Installation

To use it as a package within your project, execute:

pip install weather-data-retriever

Functionality Overview

This package aggregates weather data from various open APIs into a simplified form. It utilizes:

• Nasa's weather open API (larc-power) and 'POWER' tools and application for historical weather data across different aggregation levels and community cases.
• Open-Meteo's weather API collaborating with national weather services providing open data for both historical and forecasted weather data from national weather services.

NASA's POWER API

Fetch historical weather data at various aggregation levels:

Aggregation

• Climatology: Provides parameters as climatologies for a pre-defined period with monthly average, maximum, and/or minimum values available.
• Monthly: Provides parameters by year; the annual and each month's average, maximum, and/or minimum values.
• Daily: Provides parameters by day with average, maximum, and/or minimum values.
• Hourly: Provides parameters by hour with average values.

Communities

• AG: The Agroclimatology (AG) solar and meteorological parameters are available as daily mean time series formats. All parameters are provided on the original resolution grid, which is dependent on the parameter. The daily time series include the basic solar and meteorology parameters to support agricultural decision support tools such as the Decision Support System for Agro-technology Transfer. The hourly time series is a smaller subset of the solar and meteorology parameters.
• RE: The Renewable Energy (RE) solar and meteorological parameters are available as climatologically and inter-annual (monthly and annual) averaged values, as well as in a daily time series format for user selected grids. All RE parameters are provided on the original resolution grid, which is dependent on the parameter. The climatologically averaged parameters are calculated to support applications such as solar cooking, sizing solar panels, and sizing battery backup systems. The monthly and annually averaged parameters are provided as monthly and annual averaged values by year for each of the base solar and meteorological data parameters. The daily and hourly time series include the basic solar and meteorology parameters as well as additional calculated parameters such as diffuse and direct normal radiation.
• SB: The Sustainable Buildings (SB) solar and meteorological parameters are available as climatologically, monthly, and annually average values, as well as in a daily time series format. All parameters are provided on the original resolution grid, which is dependent on the parameter. The climatologically averaged parameters are calculated to support the preliminary design and site selection for building projects. Monthly and annually averaged parameters are provided as monthly and annual averaged values by year. The daily time series include a range of the basic solar and meteorology parameters as well as additional calculated parameters such as diffuse and direct normal radiation, heating and cooling degree days, climate zones, etc. The hourly time series is a smaller subset of the solar and meteorology parameters.

The current implementation of the package also supports "point", or "regional" cases. Point vase be used for cities, or small areas, or for geting data of the center of a country.

Regional can be used for cases of geting data based on bounded boxes of a country in order to get the different values.

The different variables that can be fetched are:

• "T2M": Temperature at 2 Meters (°C)
• "T2MDEW": Dew/Frost Point at 2 Meters (°C)
• "T2MWET": Wet Bulb Temperature at 2 Meters (°C)
• "TS": Earth Skin Temperature (°C)
• "T2M_RANGE": Temperature at 2 Meters Range (°C)
• "T2M_MAX": Temperature at 2 Meters Maximum (°C)
• "T2M_MIN": Temperature at 2 Meters Minimum (°C)
• "RH2M: Relative" Humidity at 2 Meters (%)
• "PRECTOTCORR": Precipitation Corrected (mm/day)
• "WS2M": Wind Speed at 2 Meters (m/s)
• "ALLSKY_SFC_SW_DWN": All Sky Surface Shortwave Downward Irradiance (kW-hr/m^2/day)

Each aggregation level permits a specific set of variables to be used: The "T2M", "T2MDEW", "T2MWET", "TS", "RH2M", "PRECTOT", "WS2M", and "ALLSKY SFC SW DWN" variables are the lowest-level variables that can be used in any of the aggregation levels. Additional "T2M RANGE," "T2M MAX," and "T2M MIN" can be utilized at all aggregation levels outside the hourly level.

Statistics and availability of the data can be found at power dashboard.

Refer to the POWER API Documentatio for detailed information on available data types and the quick start notebook for guidance.

Open-Meteo API

Suitable for accessing both historical and forecasted data:

Aggregation

• Daily: Provides parameters by day with average, maximum, and/or minimum values.
• Hourly: Provides parameters by hour with average values.

The main different variables that can be fetched are:

• temperature_2m: Temperature at 2 Meters (°C)
• temperature_2m_max: Maximum daily air temperature at 2 meters above ground (°C)
• temperature_2m_min: Minimum daily air temperature at 2 meters above ground (°C)
• apparent_temperature: Apparent temperature (°C)
• apparent_temperature_max: Maximum daily apparent temperature (°C)
• apparent_temperature_min: Minimum daily apparent temperature (°C)
• relativehumidity_2m: Relative humidity at 2 meters above ground (%)
• dewpoint_2m: Dew point temperature at 2 meters above ground (°C)
• sunrise: Time of sunrise
• precipitation: Total precipitation (rain, showers, snow) sum of the preceding hour (mm)
• precipitation_sum: Total precipitation sum (rain, showers, snow) (mm)
• rain_sum: Rain from large scale weather systems of the preceding hour in millimeter
• snowfall: Snowfall amount of the preceding hour in centimeters
• showers: Showers from convective precipitation in millimeters from the preceding hour
• showers_sum: Showers sum from convective precipitation in millimeters
• snowfall_sum: Snowfall sum amount in centimeters

Each aggregation level permits a specific set of variables to be used. In addition, more variables than the above are supported by this API. In order to choose your prefered ones to use, have a look at historical weather api and at forecast weather api.

Open-Meteo's source code is available on GitHub.

Please follow the quick start notebook in order to understand how to easily get started.

Licence

• Open-Meteo APIs are free for non-commercial use. The access is not restricted, but it is asked for fair use.
• All data is provided as is without any warranty.

API data are offered under Attribution 4.0 International (CC BY 4.0)

You must include a link next to any location, Open-Meteo data are displayed like:

<a href="https://open-meteo.com/">Weather data by Open-Meteo.com</a>

How to contribute?

We welcome any suggestions, problem reports, and contributions! For any changes you would like to make to this project, we invite you to submit an issue.

For more information, see CONTRIBUTING instructions.

References

1. How To Create a Python Package for Fetching Weather Data