In this study, we investigate the climate attribution of the 21·7 Henan extreme precipitation event. A conditional storyline attribution method is used, based on simulations of the event with a small-domain high-...In this study, we investigate the climate attribution of the 21·7 Henan extreme precipitation event. A conditional storyline attribution method is used, based on simulations of the event with a small-domain high-resolution cloud-resolving model. Large-scale vertical motion is determined by an interactive representation of large-scale dynamics based on the quasigeostrophic omega equation, with dynamical forcing terms taken from observation-based reanalysis data. It is found that warming may lead to significant intensification of both regional-scale(10–14% K, depending on convective organization) and station-scale precipitation extremes(7–9% K^(-1)). By comparing clustered convection organized by a localized surface temperature anomaly and squall-line convection organized by vertical wind shear, we further explored how convective organization may modify precipitation extremes and their responses to warming. It is found that shear convective organization is much more sensitive to large-scale dynamic forcing and results in much higher precipitation extremes at both regional and station scales than unorganized convection is. The clustered convection increases station-scale precipitation only slightly during heavy precipitation events. For regional-scale extreme precipitation sensitivity, shear-organized convection has a larger sensitivity by 2–3% Kthan that of unorganized convection, over a wide temperature range, due to its stronger diabatic heating feedback. For the station-scale extreme precipitation sensitivity, no systemic dependence on convective organization is found in our simulations.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 42075146 & 41875050)the support from U.S. National Science Foundation (Grant No. AGS-1933523)。
文摘In this study, we investigate the climate attribution of the 21·7 Henan extreme precipitation event. A conditional storyline attribution method is used, based on simulations of the event with a small-domain high-resolution cloud-resolving model. Large-scale vertical motion is determined by an interactive representation of large-scale dynamics based on the quasigeostrophic omega equation, with dynamical forcing terms taken from observation-based reanalysis data. It is found that warming may lead to significant intensification of both regional-scale(10–14% K, depending on convective organization) and station-scale precipitation extremes(7–9% K^(-1)). By comparing clustered convection organized by a localized surface temperature anomaly and squall-line convection organized by vertical wind shear, we further explored how convective organization may modify precipitation extremes and their responses to warming. It is found that shear convective organization is much more sensitive to large-scale dynamic forcing and results in much higher precipitation extremes at both regional and station scales than unorganized convection is. The clustered convection increases station-scale precipitation only slightly during heavy precipitation events. For regional-scale extreme precipitation sensitivity, shear-organized convection has a larger sensitivity by 2–3% Kthan that of unorganized convection, over a wide temperature range, due to its stronger diabatic heating feedback. For the station-scale extreme precipitation sensitivity, no systemic dependence on convective organization is found in our simulations.
