Behind the Radar: How We Forecast & Monitor Severe Weather in Real Time

(A technical deep‑dive for weather enthusiasts and anyone who wants to understand the science behind My Storm Alert’s personalized alerts.)

1. The Big Picture: Synoptic‑Scale Forecasting

We start the day by looking at the synoptic environment and sounding data to evaluate several key levels and parameters throughout the atmosphere. These broad‑scale patterns set the stage for severe weather.

Key ingredients we look for every morning:

• Shear: Deep‑layer and low‑level wind shear, both speed and direction • Why it matters: Determines storm type (supercell vs. QLCS) as well as tornado potential and hail size

• Moisture: PWAT, surface dew points, theta‑e ridges • Why it matters: Fuels instability, can affect hail size and wind threat

• Instability (CAPE): Surface‑based, 0-3 km, hail-CAPE, mixed‑layer, and most‑unstable CAPE • Why it matters: Dictates updraft strength, hail growth, and tornado potential

• Forcing: Jet streaks, shortwave troughs, surface boundaries • Why it matters: Provides the lift storms need to initiate

We combine these fields with:

• Satellite-trend analysis to gauge cloud cover, surface heating, and convective initiation.

• High‑resolution, convection‑allowing models (CAMs) to visualize storm timing and mode.

Bottom line: Before storms develop, we’ve mapped the where and when of potential risk zones.

2. Mesoscale Magic: Real‑Time Boundary & Storm Analysis

Once storms develop, the game shifts from broad‑scale to mesoscale detail.

What we track in the live environment:

• Observational & satellite data: Surface observations, wind profilers, mesonet networks, and high‑resolution satellite imagery.

• Boundaries: Warm fronts, stationary fronts, outflow boundaries—key zones where storms ingest streamwise vorticity and intensify.

• Real‑time mesoscale parameters: Shear, CAPE, helicity, STP, and numerous other rapid‑update parameters that highlight pockets of enhanced risk.

3. Live Radar Interrogation: Our Toolkit

We interrogate every storm with all‑tilts procedures—0.5° to 19.5°—plus advanced products that go far beyond what most apps show.

We use:

• Reflectivity, Velocity, & Storm‑Relative Velocity (all tilts): Spot core intensification, mesocyclone depth, and rear‑inflow jets.

• Dual‑Pol Suite (CC, ZDR, Spectrum Width): Detect debris, hail type & size, and evolution of updraft/downdraft couplets.

• MRMS Layers (Mesh, Rotation Tracks, AzShear): Multi‑radar, multi‑sensor perspective for hail and low‑level and mid-level rotation.

• ProbSevere / ProbTor: These algorithms investigate each storm cell and give probabilities for severe and tornado potential.

• Machine Learning: Rapid-update datasets that aim to predict risks in near-real-time.

• NROT (Normalized Rotation): Objective metric that flags strengthening mesocyclones before warnings are issued.

Some things we look for:

• Tight, persistent couplets that maintain depth through multiple elevation tilts.

• Rear‑inflow jets that signal extreme winds or aid QLCS tornado genesis.

• BWERs, storm‑top divergence, MARC signatures, lightning jumps—hallmarks of an intensifying storm.

• Three-body scatter spikes.

Debris‑Signature Confirmation vs. False Alarms

• CC drop (< 0.90) collocated with the velocity couplet: Confirms debris lofted into the air and sampled by the radar beam—objective evidence of a tornado in progress.

• Side‑lobe contamination: A velocity couplet that is displaced. Leads to high false alarm rate for tornadoes without proper evaluation. Most likely a radar artifact (side lobes, range‑folding, or beam overshoot). In these cases, tornado potential is much lower than the velocity data would suggest; we look for consistency and feature alignment across tilts.

• Without CC drop: Even with a classic reflectivity signature and tight couplet with vertical continuity, you must have visual confirmation or damage reports before confirming a tornado on the ground.

4. Why It Matters

Most apps can toss basic radar data on your screen—some even show dual‑pol or machine‑learning overlays—but data isn’t protection. Without training and experience, it’s nearly impossible to process the incoming stream, filter out artifacts, and interpret what truly matters.

A tight velocity couplet may look like a tornado, yet seasoned forecasters know to cross‑check vertical continuity and placement, CC, NROT, boundary placement, and the latest storm reports before sounding the alarm. Side‑lobe contamination can also be tough to deal with to the untrained eye. Context, training, and experience are everything.

We handle all that for you. Our meteorologists synthesize dozens of data feeds in real time, recognize subtle pattern shifts, and translate them into a single, clear decision—am I in danger, yes or no? That’s the difference between staring at colors on a screen and having actionable confidence when seconds count.

Check out our 24/7 monitoring plans today and become a subscriber. You’ll get the location-specific details others don’t.