Classification: no_prediction Confidence: The model's confidence remains fragile. It has struggled with both overprediction and underprediction in recent weeks. The failure to generate any output for a historic flood event highlights a significant limitation in handling extreme intensity or rapid-onset storms within the current nightly batch processing window.
No physics prediction was generated for today's extreme high-tier flood event (7300 CFS), and no empirical forecast headline was issued, classifying the day as 'no_prediction' despite the massive observed response.
| Metric | Predicted | Actual | Error |
|---|---|---|---|
| Peak CFS | N/A | 7300 CFS | N/A |
| Total rise | — | 7255.2 CFS | — |
| Band | Zone | Precip | Predicted Rise | Intensity |
|---|---|---|---|---|
The physics prediction engine failed to generate a forecast for a catastrophic rainfall event in the Boxley basin. The MRMS QPE data indicates an intense, short-duration storm with 3.623 inches of rain falling primarily between 09:05 and 13:05 UTC. The peak observed flow reached 7300 CFS, far exceeding the 'high' threshold of 2000 CFS. Under current calibration logic, a no_prediction classification is assigned because no predicted peak value was outputted by the system. This suggests the event either occurred too rapidly for the overnight scheduler to capture, or the input data processing failed to trigger a forecast run before the event peaked.
Regarding calibration adjustments, it is unsafe to tune the response coefficient based on a missed prediction. The previous adjustments have oscillated between overprediction (false positive on 2026-06-13) and severe underprediction (false negative on 2026-06-08). The current coefficient of 234.6 CFS/inch, when applied to 3.623 inches under saturated conditions (2.0 multiplier), would theoretically yield approximately 1697 CFS. This is still a massive underestimation compared to the observed 7300 CFS, suggesting the basin's response to extreme, high-intensity rainfall is non-linear and significantly exceeds the current linear model's capacity. However, without a generated prediction to compare against, the analyzer cannot attribute the error to a specific coefficient bias versus a systemic failure to predict extreme intensity events. Therefore, no coefficient change is recommended.
The empirical forecast also did not issue a headline for this event. Given the severity of the flood, a headline should have been issued. The lack of output from both the physics and empirical models indicates a failure in the daily reporting pipeline for this specific event window. The saturated moisture tier and high intensity multipliers are already set to their maximums (2.0 and 1.4 respectively), implying that further linear scaling is unlikely to capture the magnitude of such extreme events without a fundamental model change. Thus, the calibration remains unchanged, and confidence is not upgraded due to the missed prediction.
No changes made.