We provide connectors for several programming languages and programs to simplify the integration of the data into existing workflows. Please contact us for access to specific connectors or if you require a connector for a language or program that is not yet listed.
ArcGIS is the de facto standard of geo information systems (GIS). Thanks to WMS and WFS capability, arbitrary data layers can be easily integrated into your personal ArcGIS application. For instance, the following example shows real-time radar images, satellite images, and lightning data with the power line network of a major transmission system operator. A time slider allows operators to see past and short-term forecasted data, which enables them to estimate the impacts of severe storms to their infrastructure. As well as the aforementioned variables like radar, satellite, and lightning data, the weather API provides short-term forecasts (nowcasts) in 5-minutes resolution.
C++ is our preferred internal language for high performance applications. The C++-API connector also supports binary communication to our API, which is to be preferred for large amounts of data.
Use the link below to access the most recent version of our C++ Weather API Connector:
You can use Microsoft Excel for easy and convenient access to weather data. This functionality can be used to do your own analysis of your business’ dependence on weather, e.g. how rain could affect sales activities, a marketing event, or wind farm maintenance.
Please contact us for the most recent version of the Excel weather API connector.
With Google Maps you have the possibility to have an overlook over the entire world. Our Weather API is WMS-compatible and easy to integrate into Google Maps.
In the picture you can see the integration of the Weather API into Google Maps.
As Google Earth can add image layers from WMS 1.1.1 services, you may also use it in combination with our Weather API. To add a layer in Google Earth, go to the menu
Add and select
Image Overlay. Name your overlay and click on
Refresh, where you’ll see a button named
WMS Parameters. Click on it and use
Add... to add our WMS server with the following URL:
Select it from the drop-down menu as
WMS Server and you’ll be asked to enter the account credentials for our API. Once they are accepted, Google Earth will fetch the available parameters and display them as a list of transparent layers. Choose what you’re interested in and click
OK to add the selected layer.
If things like the resolution, style or time of the displayed data are not to your liking, you may edit the WMS request in
Link before clicking
OK once more to display the result.
For details on how to change the request, please refer to the WMS Interface documentation.
It is recommended to increase
View Bound Scaleto something like 0.9 (Google Earth defaults to 0.75) to cover more of the visible surface.
Google Earth uses a default resolution of 512×512 for the image layer, which you can change by modifying the values for WIDTH and HEIGHT in
You can save the layer by saving it as a place (right click). This makes changes to the WMS request a lot easier.
- If you have KML Error Handling enabled, you can safely ignore all the
Unknown type <Extent>warnings.
In case Java is your preferred programming language, you can use our sample code as a starting point to retrieve all the weather content you need. Happy coding!
Use the link below to access the most recent version of our Java Weather API Connector on our GitHub repository:
Use the link below to get an example for create a HighCharts.
Many scientists and scientifically-oriented product developers use Matlab. For instance, energy market analysts use Matlab to load forecasts and to develop in-house models for wind and solar power. So that they can concentrate on the scientific modeling, we provide a Matlab weather API connector. This collection of samples codes shows how to retrieve historical weather model data with a single line of code, which allows you to compare the forecast skill of different weather models such as ECMWF, GFS, UK Met Office, etc. so that you can develop your own mixing strategies to to increase forecasting skill.
Use the link below to access the most recent version of our Matlab Weather API Connector:
You can download a simple example on how to use our API within PHP from Github:
Power BI is a business analytic service based on a cloud-system. With Power BI you have the possibility to compare the data from the Weather API with your own business data and visualize them as well. The data from the Weather API can be downloaded into Power BI by the use of our provided R-Script.
Use the link below to access the most recent version of our Weather API Connector for Power BI:
To make access to a variety of weather data as convenient as possible, you can use sample code and open source Python modules for access to all the weather content you need by typing a single line. This includes time series of various weather model data, station data, forecast data, radar and satellite images… Enjoy! 🙂
Use the link below to access the most recent version of our Python Weather API Connector on our GitHub repository:
Qlik is well known to the entire data science community. Thus, a good reason to also integrate with our weather API: data can be queried from our weather API and used for any further downstream analysis. Thanks to the built-in WMS capability all available meteorological and maritime variables can be either used just as a background map layer or also referenced in a numerical analysis. This covers not only radar and satellite images, but also any quantities that are derived from different meteorolgical quantities such as model information, downscaled temperature and humidity, wind speed, hail and lightning information etc. for historical, current or future points in time.
QGIS is a widely used open source GIS tool. Thanks to WMS and WFS capability, arbitrary data layers can be easily integrated into QGIS. For instance, the following example shows air temperature globally. Of course, as with every other connector, you can also access all the other parameters featured by the Meteomatics API, e.g. short-term forecasts (nowcasts) in 5-minutes resolution.
R is a language widely used in statistics. Weather often plays a role in many topics under study. Therefore, we also developed a connector to simplify access to weather data within your R framework.
Use the link below to access the most recent version of our R Weather API Connector:
Tableau is one of the most leading tools for data analysis and visualization. The Meteomatics Weather API connects with Tableau such that data can be queried and used for any downstream analysis. Thanks to the built-in WMS capability all available meteorological and maritime variables can also be used as a background map layer. This covers also radar and satellite images, but also any quantities that are derived from different meteorolgical quantities, such as drought indices, wild fire indices, frost and severe weather warnings etc.