Astrospheric logo What makes Astrospheric different

Weather forecasting for astronomers

As astronomers and astrophotographers (amateur or professional), our field requires a caliber of weather data that exceeds a basic civilian weather forecast.  It also requires a better understanding of weather models on our part in order to be successful. The following tries to clear some of the confusion around weather forecasts and help you get the best info to optimize a night of observing.  Please note that Astrospheric is for North American astronomers (more info on that later) and as such, the models and tools below are focused on North America.

The Weather App Overload

Type “weather” into any search engine or app store and thousands of results will come back, each claiming to provide more accurate forecasts than the next with up to the minute data. Often, amateurs will download many of these apps, consult them all and try to make an informed decision.  This can lead to a lot of confusion which stems from a simple fact that the vast majority of these weather apps are showing the exact same data in slightly different ways. In fact, there are roughly three weather models for North America that offer the resolution and variables necessary for Astronomy forecasts and they update four times a day.

Models appropriate for North American Astronomy forecasts

High resolution

  1. North American Mesoscale Model (NAM, USA)
  2. Regional Deterministic Prediction System (RDPS, Canada)
  3. High Resolution RDPS (HRDPS, Canada)

Lower resolution but long range

  1. Global Forecast System (GFS, USA)
  2. Global Deterministic Prediction System (GDPS, Canada)
There are of course other model available, but they lack either the spatial resolution (both 2d and 3d) or the variables needed to compute astronomical forecasts effectively.

 

So given there are only a handful of forecast models that can be used, how is it that there are thousands of weather apps all showing slightly different results?  The answer is usually a mixture of the following

Getting good weather data

Luckily, there are a couple basic principles we can follow to help get the best weather data

  1. Look at multiple sources, but be aware of which weather model you’re getting data from
    1. Over time, knowing the model will help you determine which may be overly optimistic or overly pessimistic for your observing location.  If you’re lucky, one model will be just right. Because models prioritize different aspects of forecasting, expect different results between models.
  2. Look at the data on a map
    1. As astronomers and astrophotographers, a simple point forecast will never be accurate enough.  Viewing the data on a map is the only way to view trends necessary to make the best decision.
    2. Another benefit of viewing data on a map is that it’s a quick way to weed out the three issues described above.  Creating map overlays requires processing entire variable(s) from a model, which is not easily done by services simply repackaging weather data from other sources.

Astrospheric’s Approach

Astrospheric follows these basic principles to ensure accurate representation of the model data

  1. Provide graphical access to raw model data in the form of map overlays and point forecasts
  2. Never present mixed models for key variables
  3. Build the forecast dynamically, exactly at the requested location

 

Astrospheric uses the Canadian RDPS model for the primary astronomy variables displayed.  For additional variables (Aerosol optical depth, long range cloud cover and jet stream) Astrospheric uses the GFS model.  The RDPS model covers Canada, USA, and portions of Mexico, which is why Astrospheric works in these regions only.

Seeing and Transparency data are provided by Allan Rahill’s incredible astronomy variables, which are derived from the RDPS model.  The “Enhanced” astronomy variables Astrospheric is introducing are also derived off of RDPS and are based on the latest scientific research and tuned through input from observers like you.

When you request a forecast using Astrospheric, the server parses through ~200 million raw data points to build a specialized astronomy forecast for that exact location.  Sun and Moon data is also built for the exact location. This is why it can take a few seconds to generate a forecast which is considered an acceptable trade off to ensure that the most relevant data is being returned.  

Because of the way Astrospheric approaches weather forecasts, it stands apart from the myriad of other options available.  It is the reason it continues to be picked up and used by observatories, professional astronomers, and amateurs alike.

I hope you enjoy it too! www.Astrospheric.com

Clear Skies

-Daniel