Clouds are the primary source of uncertainty in the prediction of climate change. To reduce the uncertainty of cloud simulations and overcome this difficulty in prediction, many climate modeling centers are now developing a new type of climate model, the global nonhydrostatic atmospheric model, which reduces the uncertainty arising from a cumulus parameterization by computing clouds explicitly using a cloud microphysics scheme. Among the global nonhydrostatic atmospheric models used in recent intercomparison studies, NICAM aims to project climate change by improving our understanding of cloud changes due to warming and related physical processes. NICAM is the first global nonhydrostatic model and was developed by our research team. This review summarizes the outcomes of a recent major five-year research program in Japan for studying climate using NICAM, as well as providing an overview of current issues regarding the use of global kilometer-scale simulations in high-resolution climate modeling.

云是气候变化预测中不确定性的主要来源。为了减少云模拟的不确定性并克服预测中的这一困难，许多气候建模中心现在正在开发一种新型气候模型，即全球非静水大气模型，该模型通过使用云显式计算云来减少积云参数化所产生的不确定性微观物理方案。在最近的比对研究中使用的全球非静水大气模型中，NICAM 旨在通过提高我们对变暖和相关物理过程导致的云变化的理解来预测气候变化。 NICAM是全球第一个非静水压模型，由我们的研究团队开发。本综述总结了日本最近一项利用 NICAM 研究气候的重大五年研究计划的成果，并概述了在高分辨率气候模型中使用全球公里尺度模拟的当前问题。