Applying Year of Polar Prediction-Southern Hemisphere (YOPP-SH) Targeted Observing Periods to Advance Winter Numerical Weather Forecasting for the U.S. Antarctic Program

应用极地预测年 - 南半球 (YOPP-SH) 目标观测周期推进美国南极计划的冬季数值天气预报

• 批准号: 2205398
• 负责人: David Bromwich
• 金额: $ 84.44万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2205398&HistoricalAwards=false
• 关键词: Applying; Year; Polar; Prediction; Southern

The project aims to promote the progress of science and advance national interests in improved numerical weather modeling capabilities for American researchers and for the United States Antarctic Program. The effort consists of atmospheric modeling work leveraging the international Year of Polar Prediction — Southern Hemisphere program. This effort includes a field campaign component in 2022 that features enhanced observations of the Antarctic atmosphere in winter during Targeted Observing Periods. The project seeks to improve numerical weather prediction capabilities for both research applications and weather forecasting support for the US Antarctic Program. The project goals include evaluating the use of special observations to improve atmospheric modeling, determining whether the new technique is superior to existing techniques for Antarctic atmospheric simulation and weather prediction, and assess how well the model is performing in its prediction of polar clouds and precipitation. The project will advance the field by applying an unprecedented dataset gathered in an international collaboration and determining its benefit for future science and forecasting. It will also advance the field by exploring a new method for the use of such information in atmospheric models for the polar regions. The benefits are increases in knowledge, improved weather modeling, and gains in the model weather forecasting capabilities that the Antarctic Program relies on, allowing for enhanced efficiency and safety for Antarctic operations. The project will also advance education and outreach by supporting the education and professional development of a graduate student along with interactive exposure of diverse audiences to the challenging task of weather modeling and prediction for the remote Southern Ocean and Antarctic regions.This project focuses on the value of special observations for improving Antarctic atmospheric simulation and weather prediction, and evaluate how the model performs in predicting polar clouds and precipitation. Specifically, within the Year of Polar Prediction — Southern Hemisphere (YOPP-SH) framework, this project has four aspects. First, the team will identify candidate Targeted Observing Periods (TOPs) from East Antarctica to the Ross Sea. Second, the dataset of special YOPP-SH radiosonde launches made in the TOPs will be assimilated into model experiments using the Weather Research and Forecasting (WRF) model, which is run in the Antarctic Mesoscale Prediction System (AMPS), the numerical weather prediction capability for USAP. These data assimilation experiments will apply the AMPS framework to determine the impact of the observations on predictions of major weather events affecting the US Antarctic Program (USAP) McMurdo and Palmer Stations, and to identify the governing processes. Third, a new data assimilation capability for the WRF Model— Multi-Resolution Incremental 4DVAR (MRI-4DVAR) —is being tested in these data impact experiments to determine its effectiveness for real-time use in AMPS and thus for possible future implementation as well as for research modeling. Fourth, cloud and precipitation observations collected during the TOPs at Davis and Vernadsky Stations will be applied to analyses of the WRF simulations to assess model weaknesses. This project aims to enhance WRF’s handling of clouds and precipitation to improve parameterization. The goal is to increase the accuracy of AMPS forecasts for USAP operations and to improve the WRF model for the research community. This project will ultimately promote the progress of science and advance national interests in improved numerical weather modeling capabilities for American researchers and for USAP.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在促进科学进步并促进美国研究人员和美国南极计划提高数值天气建模能力的国家利益，该项目包括利用国际极地预测年 - 南半球计划进行大气建模工作。该项目包括 2022 年的实地活动部分，其特点是在目标观测期内加强对冬季南极大气的观测。该项目旨在提高研究应用的数值天气预报能力和对美国南极洲的天气预报支持。该项目的目标包括评估使用特殊观测来改进大气建模，确定新技术是否优于南极大气模拟和天气预报的现有技术，以及评估该模型在预测极地云和天气方面的表现。该项目将通过应用在国际合作中收集的前所未有的数据集并确定其对未来科学和预测的益处来推动该领域的发展，还将探索在大气模型中使用此类信息的新方法来推动该领域的发展。好处是知识的增长、气候的改善。该项目还将通过支持研究生的教育和专业发展以及互动接触来推进教育和推广活动。该项目重点关注特殊观测对于改善南极大气模拟和天气预报的价值，并评估该模型在预测极地云和天气方面的表现。沉淀。首先，该团队将专门确定从南极洲东部到罗斯海的候选目标观测周期（TOP）；其次，在 TOP 中发射的特殊 YOPP-SH 无线电探空仪数据集将被纳入使用天气研究和预报的模型实验中。 WRF）模型，在南极中尺度预测中运行系统（AMPS），USAP的数值天气预报能力这些数据同化实验将应用AMPS框架来确定观测对影响美国南极计划（USAP）麦克默多站和帕尔默站的主要天气事件的预​​测的影响。第三，WRF 模型的新数据同化功能——多分辨率增量 4DVAR (MRI-4DVAR)——正在这些数据影响实验中进行测试，以确定其有效性。第四，在戴维斯和韦尔纳德斯基站的 TOP 期间收集的云和降水观测将用于分析 WRF 模拟，以评估该项目的模型缺陷。旨在增强 WRF 对云和降水的处理，以提高参数化，目标是提高 USAP 操作的 AMPS 预报的准确性，并改进研究界的 WRF 模型，该项目最终将促进科学进步并促进国家利益。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。