The time for a new type of query, the route query, has come!
The route query allows you to query the weather along your travel route. All you need to provide is a sorted list of times and a list of locations, both of the same length, and make use of the new optional parameter
A simple example explains it all:
The following query provides you the temperature and precipitation along a route from St. Gallen (ZIP code 9000) via Zurich (ZIP code 8000) to Basel (ZIP code 4000), when you start now, arrive in Zurich in 1 hour and arrive in Basel in 2 hours from now:
lat;lon;validdate;t_2m:C;precip_1h:mm 47.4239;9.3748;2018-10-23T15:47:46Z;10.9;0.02 47.3828;8.5307;2018-10-23T16:47:46Z;12.5;0.00 47.5577;7.5936;2018-10-23T17:47:46Z;13.0;0.00
Route queries are supported for the file formats CSV, JSON and XML.
A possible application in a webpage:
The API has learned to handle queries with comma-separated time lists consisting of single time points and/or time ranges. This increase in expressive power allows you to combine certain queries into a single one or to query data for very specific dates without including redundant ones. For example you can now query the periods from 06Z to 18Z in 30 minute steps for both today and tomorrow with
todayT06ZPT12H:PT30M,tomorrowT06ZPT12H:PT30M in one go, or query for very specific times such as
2018-10-21T02:15Z,2018-10-22T13:25Z,2018-10-23T21:10Z in a single request. You may also mix time points and ranges, say
All the list has to satisfy is that each element of the list conforms to our already existing rules for time points and ranges, and the resulting list of times has to be sorted in non-decreasing order.
Once again, the API was significantly extended:
It now features the new shiny ECMWF-ERA5 model for historic reanalysis data in hourly resolution!
Finally we could get hold of the hourly resolution data of the ECMWF-IFS model for all four daily runs.
Everything is available in the usual quality: interpolated to whatever point you are interested in, downscaled to 90m horizontal resolution and delivered in your preferred format.
In case you are interested and need help, please don't hesitate to contact your account manager.
Keep posted, several models are being queued to be integrated or updated!
The Meteomatics weather API downscales on the fly from the models' native resolutions to 90m horizontal resolution by using NASA's SRTM topography measured by the space shuttles. Since the weather models typically have a much coarser resolution (1km to 25km or even coarser) topographically challenging environments as e.g. alpine regions, are not very well modelled and the difference between the actual elevation and the modelled elevation can be rather large. That of course has an influence on the quality of the forecasted parameters.
An example is mount Säntis in Switzerland. It is roughly 2600m above mean sea level and Schwägalp, the lower terminus, which is located at a horizontal distance of just about 1km to mount Säntis, is about 1000m lower. Due to their horizontal proximity, both locations end up being in the same simulation cell and the model forecasts roughly the same temperature for both locations. In reality, however, we know that mount Säntis, with its high altitude, typically is much colder. In dry adiabatic conditions, the temperature is about 10 degrees lower on Säntis than at Schwägalp. That means that the temperature on Säntis is often forecasted too high and the temperature at Schwägalp too low.
By applying our downscaling technique, we can significantly reduce these systematic errors. The whole computation is done on the fly, so whenever you query the temperature at a certain location, we don't just deliver that one single precomputed value, but we look at the whole atmosphere and deliver the best possible forecast for you!
WMS via Cesium showing the difference between our downscaled temperature forecasts (on the left) and raw model output (on the right) in the Alps.
Have you ever wondered to get weather data directly ingested into Qlik? The following screenshot shows how powerful such an integration can be: For instance, you can access temperature information at resolution of 90m. From there, you can start overlaying that information with the data that you like to analyze. Our weather API enables you to retrieve any location specific weather and maritime information around the globe directly into your Qlik project.
Have you ever wondered to get weather data directly ingested into Tableau? This can be either done than with a web data connector (WDC) or directly via WMS. The following screenshot shows how powerful such an integration can be: You can access satellite and radar images, storm, maritime data etc. to overlay that with your data that you like to analyze. Our weather API enables you to retrieve location specific weather and maritime information around the globe directly into your Tableau project.
A lot of our customers require to add weather API functionality to a Google spreadsheet. Now, this can easily be done with the Meteomatics weather API. Our API enables you to retrieve location specific weather and maritime information around the globe directly into your spreadsheet. This covers historical, current and also forecast data like temperature, rainfall, hail, frost, wind speed, wave data and many more.
Hail is one of these weather events that literally hurt if you ignore them. Finally, you can get a hail index from our API that warns you ahead of time, or allows you to reconstruct past events.
In addition to lightning and storm data you can now access station data by using our WFS interface. In combination with the WMS interface this allows to query, visualize and compare area data from weather models and point data from stations through a single interface, for example with commonly used GIS software.
Satellite imagery is still the fastest way to get an overview of the current weather situation. Now, you can get visible satellite channels as well as derived products, as for example cloud type images, directly from our API and cut to the area you are interested in.
The data that you receive from the API depends on the request that you make. There are a few core criteria required for each API request; time, parameters, location and output format. From our vast array of parameter options it is possible to go deep and into great detail, to request coordinates, not only are you able to request data for a single point or a point list, but now you can also query parameters against postal (zip) codes.
The data delivered via the Weather API is based on a variety of different models and observational sources. Models can be combined in an intelligent mix. This means that the best available data source is automatically offered for each time and location. Alternatively individual models or ensemble members can be queried directly instead. What`s new? MOS, based on observational weather stations’ data, is now available.
Our API is continuously updated and improved to fulfill as many of our customer's wishes as we can. To keep you updated, and to let you know about the new features, we will keep posting news here.