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: 1419518
• 负责人: Michael Pritchard
• 金额: $ 46.83万
• 依托单位: University of California-Irvine
• 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=1419518&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率和预测的最先进全球模式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、环流和海表温度（SST）的偏差影响季节到年际、年代际和较长时间气候变化的模拟。此外，在这项努力下，三名博士生将接受气候模拟方面的职业培训，为国家科学劳动力能力做出贡献。该项目的目标是减少社区地球系统模式（CESM）和包含超参数化云方案SP-CESM的CESM新版本中的热带降水偏差。热带降水偏置归因于积云参数化差、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。通过观察在模拟的头十年中偏差的初始发展，可以区分出误差的来源。积云参数化误差在数天到数周内形成，局地海洋耦合误差在数月内形成，而中纬度低云偏差的远程影响可能需要数年时间才能影响热带降水。该初始降雨和海温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覆盖的变化将是一个焦点。目标是在保持良好的ENSO变率的同时，在初始多年预测和长期预测中显著减少两个模式中的热带海温和降水偏倚。