The EZWxBrief progressive app provides the capability to see a depiction of clouds on the EZRoute Profile and EZAirport Meteogram views. For ease of discussion, both of these views utilize the same technique in how the presence or absence of clouds are determined. But in this EZTip, we'll only utilize the EZRoute Profile view.
First and foremost, determining the presence of clouds along a proposed route of flight is incredibly difficult if not fundamentally impossible. So a probabilistic approach using numerical weather prediction models is required. Many of the heavyweight aviation apps on the market that also employ a route profile view will determine if clouds exist by utilizing a rudimentary relativity humidity scheme. In general, this is a horrible approach to determine the presence of absence of clouds and is unreliable especially for cold clouds (clouds at temperatures below -12°C). EZWxBrief, on the other hand, utilizes what is referred to as "cloud fractions" that are taken from several forecast models to determine the presence or absence of clouds along the proposed route.
Without getting into the weeds of the very complex algorithm employed by EZWxBrief, here's a high level view of how it is done. Once each hour, the EZWxBrief data server pulls a fresh new version of the numerical weather prediction data from several high resolution models. When a user activates a route, it will do a georeferenced lookup and pull all necessary model data that is within a 50 mile corridor along the route (25 miles on each side). Essentially, at the departure airport and every 5 km along the route up to the destination airport, it attempts to find at most four primary cloud layers aloft using a cloud fractions scheme. It may find no cloud layers or up to four layers.
Using the cloud fractions scheme mentioned above along with the icing and ceiling algorithm (for consistency) it determines if the sky is clear or if there is indeed some cloud coverage up to 50,000 feet. If there are no cloud layers found, the sky is shown to be clear above that point. If there's a single cloud layer, then it will determine the cloud coverage (few, scattered, broken or overcast) and depth and plot that on the route profile as a white or gray rectangle at that location and altitude in the main viewport. White is used for broken or overcast and gray is for few or scattered cloud coverage. Taller rectangles means the clouds have a greater depth.
The same is done when there are multiple cloud layers detected. Once a broken or overcast cloud layer is detected, any layers above that are also deemed to be broken or overcast. This approach may sometimes be overkill for those higher cloud layers but when deeper weather systems are present, it's very difficult to determine the sky coverage for those layers, especially when the area has a high likelihood of deep, moist convection.
Lastly, the equidistant segment points along the route depicted as circles below the main viewport show the flight category (colors) and the sky coverage (clear, few, scattered, broken or overcast). If you hover your mouse over those points as shown above (tap on it using a touch screen device), it will depict in tabular form the height of the lowest cloud layer(s). That height in the tabular data depicts height above the terrain. In the image above there are three layers above KILM (about 3/4ths along the route). The lowest layer is scattered at 6000 feet (gray rectangle) and there's a broken layer at 7,000 feet (which rectangle). The one above that begins around 14,000 feet MSL and is deemed to also be broken.
When rendering these on the route profile, the overall coverage area (length between segments shown) as well as the route corridor are considered. In other words, the segment points (circles at the bottom of the viewport) are point forecasts whereas the clouds (also turbulence and icing) are using an inverse distance weighting algorithm within the corridor to determine what color or block to place in the viewport area. This means that in some cases the segment point may not be consistent with the white/gray rectangles. For example, the segment point may show a cloud coverage of few or even scattered clouds when there are no white or gray rectangles shown above it. Or the opposite could be true. There could be gray rectangles depicting a few or scattered layer, but the segment circle shows a clear sky.
Interested in learning more about the Skew-T? You can order your copy of The Skew-T log (p) and Me eBook today.
Most pilots are weatherwise, but some are otherwise™
Dr. Scott Dennstaedt
Weather Systems Engineer
Founder, EZWxBrief™
CFI & former NWS meteorologist
