Meteomaticsm Historic and future weather forecast data - up to two years ahead (locally and regionally
CustomWeather - High-Resolution Weather Forecasts and Historical Weather Forecasts
OikoLab Weather: Global Weather Forecast (GFS Model, Delivered Hourly)
Global Weather Mapping - Marcus Weather Mapping (MWM)
Real Weather Observations | Hourly, Sub-hourly, and Daily observations | 30+ variables | 30k+ worldwide
Meteomatics Weather API: Global & Hyperlocal Weather Data (Forecasts updated 280 times daily)
CustomWeather - Global Severe Weather Data/ Advisories
Ambee: Air Quality Data API - Global Coverage, Real-Time Delivery, 1M+ Postcodes
Weather Data Graphics | Forecast or Observational data available | 100s of variables | Unlimited map
Meteomatics Global precipitation forecasts - forecast for any location, across all timescales
The Ultimate Guide to Local Weather Data 2021
What is Local Weather Data?
Weather data refers to information about the pre-existing and the projected climatic weather conditions of a given geographical location over a given period. Weather data can either be localized or regional. Local weather data is the atmospheric conditions within the immediate vicinity of the person experiencing these conditions. Local weather data is contrasted from regional weather which covers a wide-ranging geographical region such as a country or state.
How is Local Weather Data collected?
Local weather data is collected by advanced weather tools before the information is uploaded into supercomputers for analysis and projection. In the USA, the National Oceanic Atmospheric Administration (NOAA) is responsible for the collection of weather information. The tools employed for the collection of local weather data by the NOAA include Doppler radars, satellite data, radiosondes, and automated surface observing systems (ASOS). The collected weather data is extrapolated by advanced computer systems to produce complex models that accurately depict the atmospheric conditions of a given local geographical area. The developed models can then be programmed to project future weather conditions of given locations.
What are the attributes of Local Weather Data?
Local weather data attributes are made up of the main components of the aspect of weather. These attributes include temperature, atmospheric pressure, wind, humidity, precipitation, and cloudiness. The temperature attribute measures the degree of ‘hotness’ or ‘coldness’ of the atmosphere of a given location and is recorded either in Celsius or Fahrenheit. Atmospheric pressure measures the weight of the atmosphere over the surface of the earth. Wind-related attributes in weather datasets measure the movement of air that is brought about by changes in temperature and atmospheric pressure. Humidity is an attribute that highlights the amount of water vapor in the air for a given location that is expressed as relative humidity.
What are the uses of Local Weather Data?
The uses of local weather data are quite extensive in variety. Weather warnings are critical forecasts that are used to foretell the prospect of a natural disaster occurring hence saving lives as a result of disaster management and mitigation. However, local weather forecasts based on temperature and precipitation are crucial in daily activities of human life such as farming and trade. Local weather data can be used by businesses to project demand for various commodities over the coming days. The data can go as far as finding basic use in the determination of the clothes to wear for a given day for residents of a location. Therefore, local weather data is important for daily activities of human life as far as planning activities are concerned.
How can a user assess the quality of Local Weather Data?
Depending on the wide-ranging needs of weather data, users can assess the quality of this data by evaluating the critical aspects of accuracy and time. Grounded on the means through which the data was collected, the accuracy of local weather data is by far one of the most important aspects of quality for this dataset. The sensitive nature of weather data does not give room for inaccurate data because some of the projected weather conditions have a direct bearing on the lives of the data consumers. Time is also an important quality parameter because users are more often than not interested in the projected weather conditions than the past day conditions. Data that presents real-time and future view of the weather conditions of a locality has more quality in terms of projected use of this data. Therefore, when checking the quality of local weather data, users should determine the time when the data was precisely collected if they hope to get any meaningful insight from it.
Who are the best Local Weather Data providers?
Finding the right Local Weather Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Local Weather Data providers that you might want to buy Local Weather Data from are Ambee, Meteomatics, CustomWeather, OikoLab Weather, and AWIS Weather Services.
Where can I buy Local Weather Data?
Data providers and vendors listed on Datarade sell Local Weather Data products and samples. Popular Local Weather Data products and datasets available on our platform are Meteomaticsm Historic and future weather forecast data - up to two years ahead (locally and regionally) by Meteomatics, CustomWeather - High-Resolution Weather Forecasts and Historical Weather Forecasts by CustomWeather, and OikoLab Weather: Global Weather Forecast (GFS Model, Delivered Hourly) by OikoLab Weather.
How can I get Local Weather Data?
You can get Local Weather Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Local Weather Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Local Weather Data APIs, feeds and streams to download the most up-to-date intelligence.