Long-term trends in tropical cyclone tracks around Korea and Japan in late summer and early fall

This study investigates long-term trends in tropical cyclones (TCs) over the extratropical western North Pacific (WNP) over a period of 35 years (1982-2016). The area analyzed extended across 30-45 degrees N and 120-150 degrees E, including the regions of Korea and Japan that were seriously affected by TCs. The northward migration of TCs over the WNP to the mid-latitudes showed a sharp increase in early fall. In addition, the duration of TCs over the WNP that migrated northwards showed an increase, specifically in early to mid-September. Therefore, more recently, TC tracks have been observed to significantly extend into the mid-latitudes. The recent northward extension of TC tracks over the WNP in early fall was observed to be associated with changes in environmental conditions that were favorable for TC activities, including an increase in sea surface temperature (SST), decrease in vertical wind shear, expansion of subtropical highs, strong easterly steering winds, and an increase in relative vorticity. In contrast, northward migrations of TCs to Korea and Japan showed a decline in late August, because of the presence of unfavorable environmental conditions for TC activities. These changes in environmental conditions, such as SST and vertical wind shear, can be partially associated with the Pacific decadal oscillation

Cold‐pool‐driven convective initiation: using causal graph analysis to determine what convection‐permitting models are missing

Cold‐pool‐driven convective initiation is investigated in high‐resolution, convection‐permitting simulations with a focus on the diurnal cycle and organization of convection and the sensitivity to grid size. Simulations of four different days over Germany were performed using the ICON‐LEM model with grid sizes from 156 to 625 m. In these simulations, we identify cold pools, cold‐pool boundaries and initiated convection. Convection is triggered much more efficiently in the vicinity of cold pools than in other regions and can provide as much as 50% of total convective initiation, in particular in the late afternoon. By comparing different model resolutions, we find that cold pools are more frequent, smaller and less intense in lower‐resolution simulations. Furthermore, their gust fronts are weaker and less likely to trigger new convection. To identify how model resolution affects this triggering probability, we use a linear causal graph analysis. In doing so, we postulate a graph structure with potential causal pathways and then apply multi‐linear regression accordingly. We find a dominant, systematic effect: reducing grid sizes directly reduces upward mass flux at the gust front, which causes weaker triggering probabilities. These findings are expected to be even more relevant for km‐scale, numerical weather prediction models. We thus expect that a better representation of cold‐pool‐driven convective initiation will improve forecasts of convective precipitation

Models of Clouds, Precipitation, and Storms: Atmosphere and Precipitation, Ice and Glaciers, Oceans and Coasts, Soils and Mineral‐Water InterfaceAtmosphere and Precipitation

International audienceClouds play an important role in life on Earth. Apart from influencing the radiative balance of the atmosphere and the lifetime of atmospheric trace constituents, they are the essential element in the hydrological cycle.This article provides an introduction to the complex subject of cloud modeling, from their formation up to the production of precipitation, and the development of cloud and storm systems. The elements intervening in cloud modeling are exposed, starting from a description of the physical phenomena. On the basis of the occurring scale problem, a number of approaches for simplification are presented. These simplifications concern the dynamics as well as the microphysics. Bulk and bin modeling approaches as well as cumulus parameterizations are explained. Some numerical problems are discussed. This approach gives an insight into the current state‐of‐the‐art cloud modeling and the necessary balance between the degree of parameterization, the number of physical and chemical processes relevant to a particular problem, and the available computing resources