Although Google disabled their weather API some time ago (except on their Android platform), many people continue to struggle to find a good replacement option that is both free for standard users and has a powerful forecast and rich history API. With the release of Visual Crossing Weather’s Timeline Weather API, there is now an easy, direct replacement for the Google Weather API. With a single call you can request an entire range of date including past observations, present conditions, and future forecast data.
What makes the Timeline API an ideal Google Weather API replacement?
The Timeline Weather API offers several key features that make it ideal for those looking for an improved Google Weather API.
One of the main features that people consider when they look for a Google Weather API replacement is cost. To many people, Google represents a source of free, or at least extremely low cost, and accurate data from web stats, to maps, to search results. And although Google services are not always free, even the ones that are not free typically have a free tier that covers most individual users and then an extremely low price-point where business and bulk users can purchase access very economically.
The Timeline API follows this model exactly. Users can get up to 1000 records per day completely free. This is enough for most individual users such as those who want to track their sports teams, plan their travel, or build a weather project using Raspberry Pi. For those who need more weather data for business intelligence applications, data science, research, and analysis purposes, Visual Crossing offers a Pay-as-you-go plan for only $0.0001 per record after the first 1000. This means that even heavy data users can get hundreds of thousands of weather records for only a few dollars.
Another hallmark of Google APIs and services is their ease-of-use. The Timeline Weather API was designed specifically with ease-of-use as its driving goal. One single API call can retrieve weather data covering an entire range of dates including times in the past and the weather forecast for the future. Also the API supplies current conditions and can even accommodate requests for ultra-long range forecasts by using historical averages to describe the likely conditions next month or even next year.
The Timeline API provides both hourly and daily result data using a single call. That simplifies the creation of interfaces and use cases where daily overview data is instantly expanded to show hourly details. No additional API round-trip or query cost required.
In addition, API features such as time period placeholders make it easy to request the weather conditions for “yesterday”, “tomorrow”, the “next7days”, or the “last7days” without having to worry about specifying an exact date range. Then, every time the query is rerun, the results will dynamically update to match the requested date window.
Deep and powerful data sources
Google is the world leader in managing huge data stores. From their core web search business to APIs such as maps, Google APIs are known for making data accessible in ways that hides the enormous volume and complexity behind the scenes. The Timeline Weather API follows this same mission by offering instant access to 50+ years of historical weather data from thousands of reporting stations around the world. This truly global reach means that you don’t need to worry where on the globe your target location lies. The Timeline API will use its vast pool of reporting stations and the most accurate interpolation algorithms to find the best weather results.
The same applies to current conditions and weather forecasts. Current conditions are updated from the reporting stations every few minutes where available. Weather forecasts employ various global and local models to determine the most reliable forecast for every worldwide location. Beyond the basic 5 or 7-day forecast that many APIs offer, the Timeline API provides a full 15-day standard forecast.
For dates beyond the traditional 15-day forecast window, the weather engine uses decades of historical weather data to provide an ultra-long-range “statistical forecast.” It does this by building a weather model based on the specific location, time, and date using historical data. It considers not only the specific date requested, but also nearby dates with similar weather patterns. The engine can then calculate an expected range of conditions for any date in the future.
In addition, the Timeline API offers other valuable data features such as weather alerts, astronomical data, and more. Weather alerts provide data on storms and other important weather conditions that affect a specific locations. Astronomical data includes sun rise and set times as well as phases of moon. These metrics can be valuable in various recreational activities such as star gazing and sports schedules as well as agricultural growing period calculations and evening business activities.
Get started in the next 5 minutes
You can get started making your first weather query in less than 5 minutes. Simply sign up for a free account, enter your account details, and you’ll be ready to get 1000 free results right away, every day. It is as simple as that. You can begin by using the web-based weather query UI to run a few example queries and even download sample datasets based on your own query parameters.
The real value, however, is in using the API to make automated queries in your own application, webpage, or app. Simply follow the documentation, and you can formulate any type of weather query that you need. For example, this simple API query will give you Washington DC’s weather for yesterday in both daily and hourly resolutions.
Just replace <YOUR_API_KEY> with the API key found in your Visual Crossing Weather account details.
If you want the forecast for the next 15-days, it is even easier.
Notice that for the standard forecast, you can omit the time parameter entirely. If you don’t specify any date, the weather engine assumes that you want the 15-day forecast.
By way of a final, more complex query example, we can request the weather for the entire year 2020. Since I’m executing this query in mid-November 2020, the Timeline weather engine has a lot of complex work to do, but my actual query is quite simple to understand and execute.
Notice that the query specifies two times. The first is the start time 1/1/2020 and the second is the end time 12/31/2020. This queries the daily and hourly records for the entire year of 2020.
Although the results will arrive as a single JSON, the weather engine must pull data from both the historical records, current conditions, the 15-day forecast, and the “statistical forecast” to produce the result. The first portion of the data (January through mid-November) will be retrieved from historical station observations. The data for the next 15-days, as of the time of my query execution (mid-November through the end of the month), will be pulled from the 15-day forecast.
Since the remainder of the requested period (December 2020) falls outside the standard forecast window, the weather engine will use the historical weather database to model the expected conditions for each day in December at the requested location, and provide those summary results. Finally, the results will include the current conditions at my location. These values are provided by the most recent observations (usually in the last few minutes) at weather stations near the location.
This example shows how one, simple weather query can combine the power of various weather sources to supply a lot of valuable weather data for any worldwide location. Of course, this is just the beginning of the clever and useful queries that you will run using the Timeline Weather API.
The Visual Crossing Weather Timeline API is the best weather data API for those seeking a replacement for the Google Weather API. It follows the week-known Google patterns of providing access to details within huge volumes of worldwide and historical data. It makes enormous volumes of weather data from many disparate sources easily accessible via a simple API (as well as a web query interface). And it provides all of this at a cost that is free for most individual users and is extremely cost-effective for commercial and bulk data users.