Collaborative Research: EaSM-3: Understanding the Development of Precipitation Biases in CESM and the Superparameterized CESM on Seasonal to Decadal Timescales

合作研究：EaSM-3：了解CESM和超参数化CESM在季节到十年时间尺度上的降水偏差的发展

• 批准号: 1419507
• 负责人: Christopher Bretherton
• 金额: $ 48万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1419507&HistoricalAwards=false
• 关键词: Collaborative; Research; EaSM; Understanding; Development

The issue of bias in state-of-the-art global models that are used to study decadal climate variability and prediction has been a long-standing problem in the field of climate science. Biases in tropical precipitation, circulation, and sea-surface temperature (SST) affect simulations of seasonal to interannual, decadal, and longer-time climate variations. Additionally, under this effort three doctoral students will be trained for careers in climate modeling, contributing to national scientific workforce capabilities.The goal of this project is to reduce tropical precipitation biases in Community Earth System Model (CESM) and a new version of the CESM that incorporated the superparameterized cloud scheme, SP-CESM. Tropical precipitation biases have been attributed to poor cumulus parameterizations, ocean coupling feedbacks, ocean eddy mixing deficiencies, land-atmosphere interaction, and remote effects of insufficient low clouds. Sources of error will be separated by looking at the initial development of the biases over the first decade of simulations.Cumulus parameterization errors develop within days to weeks, local ocean coupling errors develop in months, and the remote effect of midlatitude low cloud biases may take years to affect tropical precipitation. This initial rainfall and SST bias development will be used to test improvements to the cloud microphysical parameterizations in CESM and SP-CESM, as well as changes to the cumulus parameterization in CESM. Changes affecting Southern Hemisphere midlatitude low cloud cover will be a focus. The goal will be to significantly reduce the tropical SST and precipitation bias in both models for both initialized multiyear forecasts and long-term projections while maintaining good ENSO variability.

用于研究年代际气候变异性和预测的最先进的全球模型的偏差问题一直是气候科学领域的一个长期问题。热带降水、环流和海面温度(SST)的偏差影响季节到年际、年代际和更长时间气候变化的模拟。此外，在这一努力下，三名博士生将接受气候建模职业的培训，为国家科学工作人员的能力做出贡献。该项目的目标是减少社区地球系统模式(CESM)中的热带降水偏差，以及纳入超参数云方案的CESM的新版本，SP-CESM。热带降水偏差归因于较差的积云参数化、海洋耦合反馈、海洋涡旋混合不足、陆地-大气相互作用以及低云不足的远程影响。误差来源将通过观察最初十年模拟偏差的发展来分离。积云参数化误差在几天到几周内发展，局部海洋耦合误差在几个月内发展，中纬度低云偏差的远程影响可能需要数年才能影响热带降水。这一初始降雨和SST偏差发展将用于测试CESM和SP-CESM中云微物理参数化的改进，以及CESM中积云参数化的变化。影响南半球中纬度低云量的变化将是一个焦点。其目标将是在保持良好的ENSO可变性的同时，显著减少两个模式中的热带SST和降水偏差，无论是初始的多年预报还是长期预报。