Weather data

Forecast information on Google Weather

The Google Weather forecast is created from an internal forecasting system that utilizes weather models and observations from global weather agencies.

Learn more about the Google Weather forecasting data sources:

Tip: In South Korea and Japan, Google weather forecast information isn't available.

In addition, weather data might not be available for users located where we don’t have a nearby weather station.

The Google nowcast

You can find short-term precipitation forecasts up to 12 hours in advance with the Google nowcast. The weather information box shows the Google nowcast when you search for weather data on a mobile device.

Important:

  • The start and end times that show are in the local time zone of the location you search for.
  • This high accuracy short-term precipitation information is available in the United States, Europe, Japan, India, Brazil, South Africa, Ghana, Australia, and Canada.

Our nowcast uses radar and numerical weather prediction data. published by various data sources.

Learn more about the Google nowcast data sources:

In Japan, Weathernews provides the nowcast forecast. It uses the technology we developed in collaboration with Weathernews. The technology leverages Google's AI analysis capabilities on Weathernews' high-precision data. The explanations about Japan here apply to other relevant sections below as well.

Tip: In addition to the short-term precipitation forecast, weather maps are also available on limited surfaces.

Should I expect precipitation during the day

You can check the next precipitation event with the Google nowcast. All precipitation shows in the hourly precipitation forecast.

Why can't I find the Google nowcast

If there’s no forecast for rain, hail or snow, or if the forecast is too uncertain, the Google nowcast data won’t display.

In such cases, all weather information is shown in the hourly precipitation forecast. In addition, the Google nowcast may not be available on all weather surfaces.

Reports on current weather conditions

When you search for weather info on Google, you might be asked to provide feedback on the current weather in your area. Your feedback helps us monitor the quality of weather results and update the data.

You can find and delete your feedback in My Activity. When you delete your feedback from your Google Account, it’s no longer associated with your account, but it can still help improve weather results.

Google excessive heat warning

Learn about excessive heat warning FAQs.

Climate information

You can find climate information in Google Weather, which includes:

  • Record temperatures: Alerts for record high or low temperatures today and tomorrow.
  • Unusual temperature trends: Information about upcoming periods of unusually warm or cool temperatures.
The data for the insights is provided by the National Oceanic and Atmospheric Administration (NOAA).

Air quality information

How is an Air Quality Index (AQI) near you selected

To show the air quality at your location, Google applies the air quality model. Learn how to understand and manage your location.

If you search a city’s air quality, such as “weather in London,” the result might be for a location far away from you. The air quality might be incorrect even if you're in the same city.

To get AQI for your location:

  1. On the header, click Choose area.
  2. Select your precise location.

What is the data source of Google’s Air Quality model & is it accurate at all times

Google’s air quality model combines data from various input sources and weights the layers in a sophisticated way. The input layers are:

  • Governmental reference monitoring stations
  • Commercial sensor networks
  • Global and regional dispersion models
  • Fire smoke and dust models
  • Satellite information
  • Traffic data
  • Auxiliary information such as land cover and meteorology

Learn more about air quality.

Air quality data sources

Google Air Quality model contains information available from the sources below.

Global data sources

Belgium

  • Modified IRCEL - CELINE information. License.

Canada

Denmark

Finland

France

Germany

Guernsey

Italy

Ireland

Japan

Mexico

  • These are operated and managed by the Air Quality Monitoring Directorate of the General Directorate of Air Quality (SEDEMA). This information is public and free, and it’s subject to quality processes that could modify it. The dissemination or use of this information by third parties is under the responsibility of the person who publishes or uses it.
  • SINAICA, https://sinaica.inecc.gob.mx/. Changes were made.

Spain

Sweden

  • Contains modified SMHIinformation.

UK

US

  • Texas TCEQ.
  • New York State, Department of Environmental Conservation: The data displayed here are from www.nyaqinow.net. This data is preliminary and subject to change.

Pollen information

Important: Pollen information isn't available on all Google surfaces and weather experiences.

What is the pollen index

Google's pollen model provides an effective and simple pollen index to help you determine the likelihood of experiencing allergy symptoms from upcoming pollen exposure. This index considers both concentration of allergenic pollen in the air and the likelihood of developing symptoms due to the specific types of pollen present. It focuses and tracks various plant species on:

  • Grass
  • Trees
  • Weeds pollen types

The pollen index consists of 5 categories:

  • 0: None
  • 1: Low
  • 2: Medium
  • 3: High
  • 4: Severe

Tip: Specific coverage and forecast days may be different based on your location.

How a Universal Pollen Index (UPI) near you is selected

Google applies its pollen model to show the pollen index at your location. This includes regional plant species and pollen types with a resolution of 1 x 1 kilometer or 0.6 x 0.6 mile, such as:

  • Grass
  • Trees
  • Weeds

What's the data source of Google’s pollen model & is it accurate at all times

To create a comprehensive and accurate prediction, Google's pollen model draws on a diverse range of data sources. This includes:

  • Regional numerical models
  • Land cover data
  • Insights on plants' pollen production and seasonality
  • Weather forecasts

This approach allows the model to weigh various factors and provide a view of pollen index levels. While Google strives for the highest accuracy, factors like local environmental fluctuations can still influence pollen data.

Accuracy of the model is verified against pollen monitoring stations measurements where available.

Model limitations

While our pollen model offers valuable insights, to ensure accurate interpretation of the data, it's important to understand its limitations:

  • The pollen model is updated daily and may not reflect real-time changes.
  • Our pollen forecast may not reflect localized factors, like the presence of allergenic plants in your backyard or neighborhood.
  • Limited availability of local pollen count may affect the accuracy of the model in your area.
  • Our pollen data covers a limited number of plant species and may not reflect all allergens present in your area.

Pollen data sources

Google’s pollen model contains information available from the sources below.

Global data sources

  • Contains European Commission information under CC-BY-4.0 license.
  • Contains Global Biodiversity Information Facility under CC-BY-4.0 license.
  • Modified Copernicus Atmosphere Monitoring Service information. Neither the European Commission nor the European Centre for Medium-Range Weather Forecasts (ECMWF) is responsible for any use that may be made of the Copernicus information or data it contains.

Germany

UK

  • Met Office. Contains public sector information licensed under the Open Government Licence v3.0.

Japan

Supported species per country

Country Name Supported Types Supported Plants
France trees, grass, weeds hazel, alder, ash, birch, cottonwood, oak, olive, pine, grasses, ragweed, mugwort
Germany trees, grass, weeds hazel, alder, ash, birch, cottonwood, oak, olive, pine, grasses, ragweed, mugwort
Italy trees, grass, weeds hazel, alder, ash, birch, cottonwood, oak, olive, pine, grasses, ragweed, mugwort
Japan trees, grass grasses, Japanese cedar, Japanese cypress
United Kingdom trees, grass, weeds hazel, alder, ash, birch, cottonwood, oak, olive, pine, grasses, ragweed, mugwort

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