A revised vertical diffusion package with an explicit treatment of entrainment processes in the planetary boundary layer (PBL) is proposed. Based on the study of Noh et al. and the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm suitable for weather forecasting and climate prediction models is developed. The major change is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme improves several features compared to the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, alleviating the well-known problems in the MRF PBL. Excessive mixing in the mixed layer in the presence of strong winds is resolved. Overly rapid growth of the PBL in the case of the Hong and Pan is also rectified. The scheme has been successfully implemented in the Weather Research and Forecast model, producing a more realistic structure of the PBL and its development. In a case study of a frontal tornado outbreak, some systematic biases of the large-scale features such as an afternoon cold bias at 850 hPa in the MRF PBL are resolved. Consequently, the new scheme does a better job in reproducing the convective inhibition. Because the convective inhibition is accurately predicted, widespread light precipitation ahead of a front, in the case of the MRF PBL, is reduced. In the frontal region, the YSU PBL scheme improves some characteristics, such as a double line of intense convection. This is because the boundary layer from the YSU PBL scheme remains less diluted by entrainment, leaving more fuel for severe convection when the front triggers it. The YSU PBL scheme is more accurate in representing the PBL-top entrainment explicitly than implicitly. The results show that the new scheme is a promising option in mesoscale models, alleviating several problems inherent in its predecessor (the MRF PBL). The enhancements to the YSU PBL scheme have little impact on its efficiency, making it a viable option for real-time forecasting and computer-intensive regional climate runs. Since its addition in the WRF, it has been used regularly in real-time forecasts at NCAR, including hurricane forecasts, and has proved to be robust and realistic in its behavior in a wide variety of situations since its first inclusion in 2003.A revised vertical diffusion package with an explicit treatment of entrainment processes in the planetary boundary layer (PBL) is proposed. Based on the study of Noh et al. and the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm suitable for weather forecasting and climate prediction models is developed. The major change is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme improves several features compared to the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, alleviating the well-known problems in the MRF PBL. Excessive mixing in the mixed layer in the presence of strong winds is resolved. Overly rapid growth of the PBL in the case of the Hong and Pan is also rectified. The scheme has been successfully implemented in the Weather Research and Forecast model, producing a more realistic structure of the PBL and its development. In a case study of a frontal tornado outbreak, some systematic biases of the large-scale features such as an afternoon cold bias at 850 hPa in the MRF PBL are resolved. Consequently, the new scheme does a better job in reproducing the convective inhibition. Because the convective inhibition is accurately predicted, widespread light precipitation ahead of a front, in the case of the MRF PBL, is reduced. In the frontal region, the YSU PBL scheme improves some characteristics, such as a double line of intense convection. This is because the boundary layer from the YSU PBL scheme remains less diluted by entrainment, leaving more fuel for severe convection when the front triggers it. The YSU PBL scheme is more accurate in representing the PBL-top entrainment explicitly than implicitly. The results show that the new scheme is a promising option in mesoscale models, alleviating several problems inherent in its predecessor (the MRF PBL). The enhancements to the YSU PBL scheme have little impact on its efficiency, making it a viable option for real-time forecasting and computer-intensive regional climate runs. Since its addition in the WRF, it has been used regularly in real-time forecasts at NCAR, including hurricane forecasts, and has proved to be robust and realistic in its behavior in a wide variety of situations since its first inclusion in 2003.