Welcome to this month's newsletter!
In this issue:
In this issue, we'll try to explore how to predict weather and what tools to use for its forecast, both short- and long-term, anywhere in the world. After all, you never know where your next holiday will bring you, do you?
The topic drew my attention when I was planning my autumn holiday and trying to tell what weather to expect during its course. By chance, I stumbled upon a site which not only answered all my questions, but also provided a whole lot of other useful information.
Thus, this issue came into being.
In the beginning, weather was of little interest. Sure, hunters and gatherers could tell hunch-weather from its counterpart, but it was of little sense to contemplate it—wishing for better weather was the most they could do.
This changed when nomadic tribes started to settle and turn to agriculture—the very survival of man depended on weather. Predicting it and its effect on the annual crop became vital for survival.
In this time, people began to observe weather and its patterns trying to deduct rules which should tell how productive the summer season would be and what to expect from the coming winter, as early in the year as possible.
This approach still holds true today. To forecast local weather, we need to know how it is now, and how it used to progress from the same conditions in the past. A usual weather forecast became a matter of statistics.
The only catch is, weather statistics are scarce.
Statistics is only useful when it has a large data base. Alas, there are just about 10,500 stations gathering meteorological data for weather forecasting around the world.
This amounts to one weather station for 14,185 km2, or 5,475 sq. mi, of land mass on average. Had they be evenly spread, the neighbours would stand 130 km (80 mi) apart.
The average distance between 182 weather stations in Germany is 50 km (30 mi). Since the last weather ship has retired in 2010, close meteorological observations on the open sea are conducted solely by weather buoys. There exist 1,250 drifting ones and a couple dozen of the moored variety (France owns four).
This is hardly enough to reliably predict weather for every place in-between. The reality is even more sobering—this is how weather stations cover the world:
With so little data from so few places available, how would you build statistics to forecast weather anywhere on the planet?
Enter weather 3.0.
So, how would you extend the data base for your statistics? Well, by applying existing forecast models to fill the gaps.
This is the exact approach used by the Swiss company meteoblue. Starting with the real observation data, expanding it to places with the similar conditions, and using approved models to simulate meteorological events in the adjacent areas, the engineers are able to forecast weather in every place on Earth.
Consequently, they also applied this method to the available historical data, and created a unique database of weather simulations for each point in the world reaching 30 years into the past.
This accumulated data—however unconfirmed and uncertain it appears—is, surprisingly, enough to describe climate and reliably forecast weather anywhere on the planet.
The company routinely compares its forecasts with weather measurements, and verifies the former against the latter to further fine-tune its models. The comparison results are made available to both customers and the general public, and currently read as follows:
These forecasts are appreciated by professionals and amateurs alike in areas where conventional methods are not available or applicable. And they can do so much more:
Apropos widgets: Here is an example.
The widget is intended to show the weather forecast for a place in the vicinity of your whereabouts. The exact location should correspond to where Google Maps would open if you were to launch it. Depending on your position, this could be quite far away. In this case, alternative services will be invoked and averaged. As a fallback, the widget will work it out on its own, though my tests were rather disappointing in this regard.
Another bit of explanation for the above comment: The first point of call for your location is Google's Geolocation API. If its verdict is sure enough, it will suffice to configure the widget. If it is not, three other web services, all using different sources, are called to estimate your coordinates based on your IP address. Their results, and that from Google are mixed together to calculate an approximate geographic position which, in order, is used to find the populated place nearest to it. The widget is then set up to forecast the weather in this location.
In a certain regard, this is in line with the principles the company applies to make their weather forecasts.
The IP based geolocation is a topic in itself worth a dedicated coverage. Please comment below if you are interested in its closer discussion—or to share your experience with its application on this particular page.
If you manage a website or a blog dedicated to a specific place, be it your native town or a fashionable tourist destination, consider configuring the widget for your visitors—it is quite easy, and free!
Before you do, be sure to read and follow the requirements for hosting sites.
As to the long-term weather forecast for my holiday destinations from the introduction, the current outlook is quite favourable, showing the trend to be warmer and drier than usual. I know this is unreliable at this time, but I also know where to look for changes should they occur in the coming months!
The oldest, still active weather station in the world is located in Upper Austria within the Kremsmünster Abbey, a Benedictine monastery.
The monastery was founded in 777 AD by Tassilo III, the Duke of Bavaria, on site of his son's hunting accident involving a wild boar, as the legend has it.
An observatory built on the premises between 1749-58 became one of the first European skyscrapers rising 49 m above the ground and with another 5 m below, for a total of 59 yd.
The weather station was added in 1762, and started its observations in the following year. Since 1767, it has been keeping temperature recordings in one unprecedented series without interruption.
Guided tours of the observatory are possible from May to October. In winter, the unheated building remains closed.
Tags: #inplainlight #howtoforecastweather #weatherwidget
Unattributed images on this page are sourced from public domain via Pixabay.
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