| Session Details | |
| Section | AS - Atmospheric Sciences |
| Session Title | Atmospheric Blocking and Improvement of Earth System Modeling |
| Main Convener | Prof. Joong-Bae Ahn (Pusan National University, Korea, South) |
| Co-convener(s) | Dr. Vladimir Kryjov (Hydrometcenter of Russia, Russian Federation) Dr. Wei-Liang Lee (Academia Sinica, Taiwan) Prof. Masahiro Watanabe (The University of Tokyo, Japan) Dr. Hsi-Yen Ma (Lawrence Livermore National Laboratory, United States) |
| Session Description | This session covers two different subjects: blocking and earth system modeling. Blocking defined as a stagnant or slowly moving quasi-stationary ridge that normally builds up over the North Atlantic, Ural Mountains and North Pacific during boreal winter is usually related to extreme weather events such as an anomalous warm or cold and wet or dry weather. For these reasons, a better understanding on the causes, influences, simulation and prediction of the phenomenon is necessary. The atmospheric blocking caused possibly by the atmospheric internal dynamics, surface boundary forcing due to snow cover and sea-ice and anomalous equatorial SST forcing is known to be closely related to NAO, AO, ENSO, WP pattern and Asian Monsoon. In this session, we will particularly focus on 1) the possible reasons for the formation of the blocking, 2) its influences on climate and weather in different regions and seasons as well as its relations with other large-scale indices and 3) the prediction and simulation skills using climate models. The second topic of this session is on the representation of physical and chemical processes in current Earth system models (ESMs), which has made significant progress since CMIP5. These processes, such as cloud microphysics, convection, and aerosols, are critical to radiative forcing, hydrological cycle, and climate feedback. In addition, new dynamic cores are also employed in climate models in response to the need of accuracy and efficiency for high-resolution simulations. This session invites papers focusing on: 1) advances in representation of physical, chemical, and dynamical processes in CMIP6 models; 2) improvements in ESMs using observation to quantify model biases and to characterize the sources of uncertainties. |