Extreme precipitation events are becoming more frequent and more intense, causing devastating floods across the globe. Accurate prediction of extreme precipitation at both the weather and climate timescales is critically needed to address the increasing risk to infrastructure and human life. This project tackles the emergent relationship between extreme precipitation intensity (EPI) and temperature at the weather timescale and its implication for future predictions.  EPI is expected to increase as climate warms. However, at the weather timescale, EPI decreases when local temperature exceeds a certain threshold, which may result from the atmospheric moisture saturation deficit at high temperatures. Besides thermodynamics, results from our project suggest that the EPI contrast between mesoscale convective systems (MCSs) that occur predominantly at night and isolated convections during the daytime plays an important role in shaping the EPI-temperature relationship, and may be the primary cause for the negative scaling in MCS-prone regions such as the Central U.S. Our project also tackles the potential causes for model biases in capturing the quantitative relationship between EPI and local temperature. Observational data showed that EPI in saturated atmosphere increases with local surface air temperature monotonically at a rate close to the Clausius-Clapeyron (C-C) ratio. This emergent relationship is not well captured by ESMs; instead, ESMs produce a wide range of scaling ratios that are highly region-dependent. As a potential cause for this model deficiency, we examine the impact of model spatial resolution.  Results based on E3SM suggest that reducing the model grid size from 100km to 25km leads to more realistic simulations of precipitation characteristics but no clear improvement to the EPI-temperature relationship in the model. Preliminary results indicate that convection-permitting simulations may be needed to better capture the weather scale relationship. To examine whether model biases in simulating the weather-scale EPI-temperature relationship may propagate to influence future projections, we examine the potential link between the rate of extreme precipitation increase with global warming and the models’ scaling ratio at the weather timescale.  A moderate correlation between the two was found, despite a high degree of model dependence. Our ongoing research further assesses the potential role of the weather-scale scaling ratio as an emergent constraint for the projected future EPI changes.