Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System
Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System
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DOI：
10.1007/s00376-021-0326-5
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发表时间：
2021-06
影响因子：
5.8
通讯作者：
M. Lindskog;A. Dybbroe;R. Randriamampianina
中科院分区：
文献类型：
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作者：
M. Lindskog;A. Dybbroe;R. Randriamampianina
MetCoOp是一个北欧合作的业务数值天气预报基于一个共同的有限区域公里尺度集合系统。初始状态是使用三维变分数据同化方案，利用大量的观测，从传统的现场测量，天气雷达，全球导航卫星系统，先进的散射计数据和卫星辐射从各种卫星平台。为加强微波辐射的同化作用，已经准备了一个预报系统版本，供今后使用。这一增强型数据同化系统将利用Metop-C和Fengyun-3 C/D极轨道卫星上的微波湿度探测器、高级微波探测单元A和微波湿度探测器2号仪器的辐射。实施过程包括通道选择，建立一个自适应偏差校正程序，并仔细监测数据的使用和质量控制的意见。额外的微波观测的好处，在数据覆盖面和影响分析，使用信号的自由度的方法，推导出，证明。对预报质量的积极影响，并对降水的影响进行了案例研究。最后，讨论了增强数据同化技术和适应临近预报的作用。
MetCoOp is a Nordic collaboration on operational Numerical Weather Prediction based on a common limited-area km-scale ensemble system. The initial states are produced using a 3-dimensional variational data assimilation scheme utilizing a large amount of observations from conventional in-situ measurements, weather radars, global navigation satellite system, advanced scatterometer data and satellite radiances from various satellite platforms. A version of the forecasting system which is aimed for future operations has been prepared for an enhanced assimilation of microwave radiances. This enhanced data assimilation system will use radiances from the Microwave Humidity Sounder, the Advanced Microwave Sounding Unit-A and the Micro-Wave Humidity Sounder-2 instruments on-board the Metop-C and Fengyun-3 C/D polar orbiting satellites. The implementation process includes channel selection, set-up of an adaptive bias correction procedure, and careful monitoring of data usage and quality control of observations. The benefit of the additional microwave observations in terms of data coverage and impact on analyses, as derived using the degree of freedom of signal approach, is demonstrated. A positive impact on forecast quality is shown, and the effect on the precipitation for a case study is examined. Finally, the role of enhanced data assimilation techniques and adaptions towards nowcasting are discussed.