The central United States frequently exhibits warm and dry biases in simulations of summertime conditions, a persistent feature that remains challenging to resolve. While previous studies have linked these biases to misrepresented land-atmosphere energy exchanges, the role of belowground processes remains poorly understood. Here, we demonstrate that inadequate representation of root water uptake in land surface models contributes substantially to errors in surface energy partitioning and ultimately to regional hydroclimatic biases. Using both offline Noah-MP and coupled WRF-Noah-MP simulations with static and dynamic root water uptake schemes, we show that the inclusion of dynamic root processes reduces 2-m air temperature biases and enhances precipitation over transitional climate zones, primarily by increasing the rain rate of convective systems. Offline and coupled simulations further reveal that the cooling effects and precipitation increases are amplified through positive land--atmosphere feedbacks, active only in the coupled model. These findings highlight the critical role of plant-root dynamics in modulating land-atmosphere interactions and underscore the need to refine root-zone processes to improve regional atmospheric simulations.

Recent studies have shown that direct root water uptake from the capillary fringe and groundwater can lead to transpiration that is greater than precipitation by a factor of 10 in hyper-arid conditions. In this study, a dynamic root water uptake scheme in the Noah-MP land surface model has been coupled to the Weather Research and Forecasting (WRF) model to investigate its impact on the surface climate variables and land-atmosphere interactions. Different from the traditional big-leaf approach that parameterizes transpiration as function of soil moisture states, the root water uptake scheme explicitly represents plant water storage and its impact on transpiration. The dynamic root scheme shows promising results by alleviating biases in the simulated gross primary product, leaf area index, precipitation, temperature, surface energy fluxes, and soil moisture. Two different mechanisms through which root affects land-atmosphere coupling have been identified. Over the transitional climate zone between the dry and wet climate, the dynamic root affects surface climate and land-atmosphere coupling mainly through changes in soil moisture through hydraulic redistribution by plant root system. Over the energy-limited mesic zone, the dynamic root affects regional land-atmosphere coupling mainly through changes in carbon allocation. Deficiency in evapotranspiration partitioning is identified, underscoring the need for future improvement.

To understand the future summer precipitation changes over the Great Lakes Region (GLR), we perform an ensemble of regional climate simulations through the Pseudo-Global Warming (PGW) approach. We found that different types of convective precipitation respond to the PGW signal differently. Isolated deep convection (IDC), which is usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), which are usually concentrated upstream of the GLR, shows a shift to the downstream region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to be increased in almost the entire studied domain, providing a potential environment more (less) favorable for stronger (weaker) convection systems. Meanwhile, changes in lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, underscoring the significance of these thermodynamic factors in controlling precipitation over the domain. Results show that decreased LCL and LCF over places where convective precipitation is increased, is mainly contributed by the atmospheric moisture increase. In response to the prescribed warming perturbation, MCSs show more frequent occurrences downstream, while localized IDCs show more intense rain rate, longer duration, and larger rainfall area.