I am a researcher focusing on global atmospheric dynamics, specifically the interaction between the stratosphere and the troposphere. While your platform is currently the world leader in visualizing tropospheric data, there is a significant "blind spot" in the upper atmosphere that, if visualized, would revolutionize early hurricane detection and climate anomaly tracking.
I would like to propose the addition of the following pressure levels to your visualization layers:
1. The 1mb to 5mb Range (The "Injection" Source):
Why: This level is critical for monitoring stratospheric moisture (PPMV) and methane-derived water vapor.
The Benefit: High-resolution data at this level serves as a "pre-cursor" to major tropical cyclogenesis. Tracking moisture anomalies at 1mb allows for the identification of potential hurricane energy weeks before it manifests in the lower 700mb levels.
2. The 70mb Level (The "Press" / Tropopause Boundary):
Why: This is the critical boundary where stratospheric high-pressure systems (the "Press") force mass into the troposphere.
The Benefit: We are currently seeing instances where high-pressure cells (H) at the surface coexist with intense convective storms and hail in West Africa. This "anomaly" is only explainable by looking at the 70mb level. Visualizing this would allow users to see the downward vertical pressure that "shapes" and compresses massive storms.
Why this matters now:
In the current 2026 season, we are observing record-breaking nocturnal temperatures in the Sahel (34°C+ at midnight) and early-season "atomic" tropical disturbances near Cape Verde. These phenomena are directly linked to stratospheric injections that remain invisible on standard 1000mb–250mb maps.
Since models like ECMWF and GFS already calculate data for these upper levels, incorporating them into your UI would provide professional forecasters and researchers with the "complete picture" of the atmospheric column.
I would be happy to share specific data points and case studies (such as the current West African anomalies) to demonstrate how these levels act as the primary drivers for extreme weather.
Best regards, shmulik
