A Truly Magical Weather Station That Multiplies

James Stalker, Ph.D., President & CEO of RESPR, Inc.

Everyone wants to know what the weather was like in the past, what it is like right now, and what it will be like in the future (from minutes ahead to hours, to days, and beyond). These are some of the fundamental expectations of everyday life. How are these expectations met today? Surface (traditional) weather stations, installed at a limited number of locations, that measure temperature, humidity, wind speed and wind direction, etc. meet such expectations to an extent in that they provide measurements of current weather conditions. Such measurements collected by these weather stations, over a period of time, can lead to a record of those past weather conditions as well. Measurements of weather conditions for the future are a different matter altogether and are not provided by these weather stations. There are several other sources of weather data from such diverse platforms as radars, satellites, aircraft, ships, and atmospheric and other earth system models to augment the weather station data. Even after combining measurements from weather stations and all of the above-mentioned measurement platforms and model output, the available weather data constitute a small percent of the required weather data (read the blog post, tilted “There Appear To Be Only 3 Options For Weather Data: Or Maybe Not,” by Dr. James Stalker for further details).

While temporal limitations are clearly impossible to overcome by traditional weather stations alone, spatial limitations are equally significant too. In other words, weather stations can only collect weather information at the locations where these weather stations are installed. Given these significant limitations of the weather stations, both in time and space, wouldn’t it be critically important to find other ways to obtain the missing weather data for the past, the present, and the future and for all locations of interest? Fortunately, there is a way. This way is through the application of robust, high-resolution, physics-based atmospheric and other earth system models which will produce weather data for the past, current, and future periods and for all locations of interest. Imagine a “weather station” that “multiplies” itself in space and time-travels from the past to the future and back to the past seamlessly. That type of weather station would be truly magical, wouldn’t it?

One such magical weather station is made possible by a robust atmospheric simulation technology developed by Dr. James Stalker at Regional Earth System Predictability Research [RESPR], Inc. RESPR atmospheric simulation technology (AST) essentially enables the underlying atmospheric processes that shape weather variables of interest, in space and time, where measurements are not available, as these processes are known to do so in the real atmosphere.

This magical weather station has many other unique characteristics. For one thing, this magical weather station is invisible. Is there a better anemometer than an invisible one? Is there a better sodar than an invisible one? Is there a better lidar than an invisible one?

Today, many weather data users may take comfort in the fact that they have sufficient measurements at their location and don’t see the critical need for the magical weather station that multiplies. The problem with this short-sighted complacency is that the moment they require weather data at other locations, as they usually do, other than where they have measurements for, their ability to obtain weather information at the other locations, based just on measurements from their own weather station, is extremely limited. This is because of the fact that weather at each location is continually affected by what is happening at numerous other locations around that location of interest. The bottom line is that your single weather station (or even a handful of them for that matter) will not have the ability to capture all the relevant effects (i.e., the underlying physical processes) occurring at these numerous other locations.

This is a significant realization all weather data users and weather data providers must come to, in order to harness the full potential benefits of more accurate weather information. In other words, you shouldn’t believe you can determine weather (e.g., wind) at another location based on the wind measurements at your location. This is because wind at another location is dependent on weather—not just wind—and at many other locations—not just at your own location. Current methods/approaches employed in producing weather data are classified as the ten-percent methods by Dr. James Stalker (read his other blog posts for details).

It should be noted that Dr. James Stalker is not suggesting that actual weather measurements by traditional weather stations are no longer required. Such measurements are indeed very important but their use is more for validating and correcting the weather output of the magical weather station than for actual use. Such traditional measurements should not be used for extrapolation and direct weather data consumption because of their severely limited ability to produce weather data of value at locations other than where they collect measurements.

In other words, don’t settle for inadequate weather information resulting from limited measurements by traditional weather stations and ineffective models. Instead, reach out to Dr. James Stalker at jrstalker@respr.com for further details about how you can obtain comprehensive and more accurate weather data by using the magical weather station that multiplies.