Scientific design and preliminary results of three-dimensional variational data assimilation system of GRAPES

Jishan, Xue; Zhuang, Shiyu; Zhu, Guijie; Zhang, Hua; Liu, Zhiquan; Liu, Yan; Zhuang, Zhaorong

doi:10.1007/s11434-008-0416-0

Cited by 47 publications

(30 citation statements)

References 13 publications

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“…Vertical profiles of horizontal winds measured by 14 WPRs over Gua ngdong were assimilated into a partialcycle data assimilation system based on the threedimensional variational method, using the Global/ Regional Assimilation and Prediction System (GR A PES; Zha ng a nd Shen 2008; Chen et al 2008;Xue et al 2008) with horizontal resolution of 0.03° × 0.03° in regular latitude-longitude coordinates. The impact of assimilating t he WPR data on the 0-12-h QPF in southern China during May 2014 was evaluated by comparing the forecasts from two monthly continuous experiments: one with the WPR data assimilated (WPR_DA) and the other without it (no_WPR_DA).…”

Section: Preliminary Research Highlightsmentioning

confidence: 99%

The Southern China Monsoon Rainfall Experiment (SCMREX)

Wan¹,

Wang²,

Wong

et al. 2017

Bulletin of the American Meteorological Society

156

114

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During the presummer rainy season (April–June), southern China often experiences frequent occurrences of extreme rainfall, leading to severe flooding and inundations. To expedite the efforts in improving the quantitative precipitation forecast (QPF) of the presummer rainy season rainfall, the China Meteorological Administration (CMA) initiated a nationally coordinated research project, namely, the Southern China Monsoon Rainfall Experiment (SCMREX) that was endorsed by the World Meteorological Organization (WMO) as a research and development project (RDP) of the World Weather Research Programme (WWRP). The SCMREX RDP (2013–18) consists of four major components: field campaign, database management, studies on physical mechanisms of heavy rainfall events, and convection-permitting numerical experiments including impact of data assimilation, evaluation/improvement of model physics, and ensemble prediction. The pilot field campaigns were carried out from early May to mid-June of 2013–15. This paper: i) describes the scientific objectives, pilot field campaigns, and data sharing of SCMREX; ii) provides an overview of heavy rainfall events during the SCMREX-2014 intensive observing period; and iii) presents examples of preliminary research results and explains future research opportunities.

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Section: Preliminary Research Highlightsmentioning

confidence: 99%

The Southern China Monsoon Rainfall Experiment (SCMREX)

Wan¹,

Wang²,

Wong

et al. 2017

Bulletin of the American Meteorological Society

156

114

View full text Add to dashboard Cite

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“…The geographical positions of typical plumes, as observed on 9 April, 15 April and 7 May of 2006, are depicted in Figure 2. Also shown in Figure 2 are the wind fields and spatial tracer distributions over the region concurrent with the plume observations, which were simulated by the regional meteorological forecast model GRAPES with passive tracers added [29,34,35]. To show the regional transport of urban plumes, the tracers were released in the lowest layer of the model from the locations of the five major cities Beijing, Tianjin, Tangshan, Shijiazhuang and Taiyuan [29].…”

Section: General Features Of the Plumesmentioning

confidence: 99%

Pollution plumes observed by aircraft over North China during the IPAC-NC field campaign

Wang

Liu

et al. 2013

Chin. Sci. Bull.

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Strong pollution emissions from large urban and industrial centres in eastern China are thought to greatly impact regional air quality and global atmospheric chemistry. In this study, we investigate extensive pollution plumes over North China, observed by aircraft during the IPAC-NC (Influence of Pollution on Aerosols and Cloud Microphysics in North China) field campaign in spring 2006. Several pollution plumes were encountered, characterized by sharp and strong increases of SO 2 and NO x (NO plus NO 2 ) as well as remarkable O 3 variability. During a flight performed downwind of the megacity Tianjin on 9 April, O 3 was found to be depleted at NO x >15 ppbv and enhanced at NO x mixing ratios of 6-7 ppbv. Our analysis indicates that the plumes had recently been released by industrial plants, and partly mixed with urban emissions, giving rise to the large-scale transport of air pollution and substantial degradation of air quality.

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“…Empirical orthogonal functions (EOFs) were used for the vertical component of the background error covariance. Recursive filtering (RF) was applied to the horizontal increment fields of the control variables (Chen et al, 2008;Xue et al, 2008).…”

Section: Description Of Grapes Model and Assimilation Systemmentioning

confidence: 99%

Radar data assimilation of the GRAPES model and experimental results in a typhoon case

Liu

Jishan

Gu³

et al. 2012

Adv. Atmos. Sci.

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Constructing β-mesoscale weather systems in initial fields remains a challenging problem in a mesoscale numerical weather prediction (NWP) model. Without vertical velocity matching the β-mesoscale weather system, convection activities would be suppressed by downdraft and cooling caused by precipitating hydrometeors. In this study, a method, basing on the three-dimensional variational (3DVAR) assimilation technique, was developed to obtain reasonable structures of β-mesoscale weather systems by assimilating radar data in a next-generation NWP system named GRAPES (the Global and Regional Assimilation and Prediction System) of China. Single-point testing indicated that assimilating radial wind significantly improved the horizontal wind but had little effect on the vertical velocity, while assimilating the retrieved vertical velocity (taking Richardson's equation as the observational operator) can greatly improve the vertical motion. Experiments on a typhoon show that assimilation of the radial wind data can greatly improve the prediction of the typhoon track, and can ameliorate precipitation to some extent. Assimilating the retrieved vertical velocity and rainwater mixing ratio, and adjusting water vapor and cloud water mixing ratio in the initial fields simultaneously, can significantly improve the tropical cyclone rainfall forecast but has little effect on typhoon path. Joint assimilating these three kinds of radar data gets the best results. Taking into account the scale of different weather systems and representation of observational data, data quality control, error setting of background field and observation data are still requiring further in-depth study.

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Scientific design and preliminary results of three-dimensional variational data assimilation system of GRAPES

Cited by 47 publications

References 13 publications

The Southern China Monsoon Rainfall Experiment (SCMREX)

The Southern China Monsoon Rainfall Experiment (SCMREX)

Pollution plumes observed by aircraft over North China during the IPAC-NC field campaign

Radar data assimilation of the GRAPES model and experimental results in a typhoon case

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