Erratum to: A Two-plume Convective Model forPrecipitation Extremes

Erratum to:Yin,Z.H.,P.X.Dai,and J.Nie,2021:A two-plume convective model for precipitation extremes.Adv.Atmos.Sci.,38(6),957−965,https://doi.org/10.1007/s00376-021-0404-8.

A Two-plume Convective Model for Precipitation Extremes

In the study of diagnosing climate simulations and understanding the dynamics of precipitation extremes,it is an essential step to adopt a simple model to relate water vapor condensation and precipitation,which occur at cloudmicrophysical and convective scales,to large-scale variables.Several simple models have been proposed;however,improvement is still needed in both their accuracy and/or the physical basis.Here,we propose a two-plume convective model that takes into account the subgrid inhomogeneity of precipitation extremes.The convective model has three components,i.e.,cloud condensation,rain evaporation,and environmental descent,and is built upon the zero-buoyancy approximation and guidance from the high-resolution reanalysis.Evaluated against the CMIP5 climate simulations,the convective model shows large improvements in reproducing precipitation extremes compared to previously proposed models.Thus,the two-plume convective model better captures the main physical processes and serves as a useful diagnostic tool for precipitation extremes.

Climate change attribution of the 2021 Henan extreme precipitation: Impacts of convective organization

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.