Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Alan J. Geer
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引用次数: 0

Abstract

Satellite‐observed microwave radiances provide information on both surface and atmosphere. For operational weather forecasting, information on atmospheric temperature, humidity, cloud, and precipitation is inferred directly using all‐sky radiance data assimilation. In contrast, information on the surface state, such as sea‐surface temperature (SST) and sea‐ice concentration (SIC), is typically provided through third‐party retrieval products. Scientifically, this is a sub‐optimal use of the observations, and practically it has disadvantages such as time delays of more than 48 h. A better solution is to estimate the surface and atmospheric state jointly from the radiance observations. This has not been possible until now, due to incomplete knowledge of the surface state and the radiative transfer that links this to the observed radiances. A new approach based on an empirical state and an empirical sea‐ice surface emissivity model is used here to add sea‐ice state estimation, including SIC, to the European Centre for Medium‐range Weather Forecasts atmospheric data assimilation system. The sea‐ice state is estimated using augmented control variables at the observation locations. The resulting SIC estimates are of good quality and they highlight apparent defects in the existing OCEAN5 sea‐ice analysis. The SIC estimates can also be used to track giant icebergs, which may provide a novel maritime application for passive microwave radiances. Further, the SIC estimates should be suitable for onward use in coupled ocean–atmosphere data assimilation. There is also increased coverage of microwave observations in the proximity of sea ice, leading to improved atmospheric forecasts out to day 4 in the Southern Ocean.
利用微波成像仪联合估计业务天气预报中的海冰和大气状态
卫星观测到的微波辐射可提供地表和大气信息。在业务天气预报中,有关大气温度、湿度、云层和降水的信息是利用全天空辐射数据同化直接推断出来的。相比之下,海面温度(SST)和海冰浓度(SIC)等地表状态信息通常由第三方检索产品提供。从科学角度看,这是对观测数据的次优利用,在实际应用中也存在时间延迟超过 48 小时等缺点。更好的解决方案是通过辐射观测数据联合估算地表和大气状态。由于对地表状态以及将地表和大气状态与观测到的辐射量联系起来的辐射传递的了解不全面,到目前为止还无法做到这一点。这里使用了一种基于经验状态和经验海冰表面辐射率模型的新方法,将海冰状态估计(包括 SIC)添加到欧洲中期天气预报中心大气数据同化系统中。海冰状态是利用观测地点的增强控制变量估算出来的。由此得出的 SIC 估计值质量很高,突出了现有 OCEAN5 海冰分析中的明显缺陷。SIC 估计值还可用于跟踪巨型冰山,这可能会为被动微波辐射提供一种新的海洋应用。此外,SIC 估计值应适合在海洋-大气耦合数据同化中继续使用。海冰附近的微波观测覆盖范围也有所扩大,从而改进了南大洋第 4 天的大气预报。
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来源期刊
CiteScore
16.80
自引率
4.50%
发文量
163
审稿时长
3-8 weeks
期刊介绍: The Quarterly Journal of the Royal Meteorological Society is a journal published by the Royal Meteorological Society. It aims to communicate and document new research in the atmospheric sciences and related fields. The journal is considered one of the leading publications in meteorology worldwide. It accepts articles, comprehensive review articles, and comments on published papers. It is published eight times a year, with additional special issues. The Quarterly Journal has a wide readership of scientists in the atmospheric and related fields. It is indexed and abstracted in various databases, including Advanced Polymers Abstracts, Agricultural Engineering Abstracts, CAB Abstracts, CABDirect, COMPENDEX, CSA Civil Engineering Abstracts, Earthquake Engineering Abstracts, Engineered Materials Abstracts, Science Citation Index, SCOPUS, Web of Science, and more.
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