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Abstract Extreme precipitation events that occur during the warm season are commonly associated with high-intensity, short-duration rainfall that can lead to damaging flash-flood-related impacts. The NCEP High-Resolution Ensemble Forecast (HREF) system is an ensemble of convection-allowing models (CAMs) that provides both high-resolution precipitation guidance and forecast uncertainty information for anticipating these kinds of events. In this study, the probability-matched mean (PMM) and localized PMM (LPMM) from the HREF version 3, initialized at 0000 UTC, are evaluated for their ability to capture heavy and extreme precipitation in the warm-season months of June–August across the contiguous United States. Thresholds defined with the 2-, 10-, 50-, and 100-yr average recurrence interval (ARI) exceedances for 1-, 3-, and 6-h rainfall durations are assessed between forecast hours f = 12–36 to capture a complete convective cycle. The forecasts are evaluated against the Multi-Radar Multi-Sensor (MRMS) system quantitative precipitation estimation (QPE) pass 2 between 2021 and 2023 when the HREF membership remained unchanged. It was found that the HREF PMM is more skillful than the LPMM for almost all ARI thresholds and rainfall durations. The tendency for the PMM to overestimate ARI exceedances leads to a higher probability of detection (POD) and higher critical success index compared to the LPMM. In contrast, the HREF LPMM underestimates all ARI thresholds and durations in both the eastern and western United States. This is characterized by lower frequency bias and lower POD but a higher success ratio (i.e., lower false alarm rate) relative to the PMM. Significance Statement The High-Resolution Ensemble Forecast (HREF) system has been running operationally in a constant configuration for 3 years. Despite this, little evaluation has been done that quantifies how well the ensemble predicts extreme precipitation, particularly with regard to the HREF means. Here, we examine forecasts of summertime extreme precipitation from the HREF means, which include the arithmetic mean, probability-matched mean, and localized probability-matched mean. A climatology of each mean’s heavy and extreme precipitation and forecast performance are presented. The results from this study provide contextual information that can be used by forecasters using the HREF means for predicting extreme precipitation and by researchers for investigating how to produce the most skillful, ensemble-based QPF products.