Application of Cloud Analysis in GRAPES_RAFS
Lijuan ZHU[1], Dehui CHEN[1], Jiandong GONG[1], Youming QU[2]Zhifang XU[1]Liping LIU[3]
[1]National Meteorological Centre (NMC), Beijing 100081
[2]Hunan Meteorological Bureau, Changsha 410007
[3]Chinese Academy of Meteorological Sciences (CAMS), Beijing 100081
China Meteorological Administration (CMA)

The requirements have been increasing in more accurate and rapid update short-term forecast & nowcasting of the severe high impact weather which occurred more frequently in recent years in China, such as the flash flooding in Beijing on July 10, 2004; the sever thunderstorm in He-nan on June, 2009; the mud-rock flow on August 07, 2010 in Zhou-qu of Shanxi province. The increasing requirements have been also demanded to support the important opening-air activities, such as Beijing-2008-Olympic Games, Shanghai-Expos-2010, Guangzhou-2010 Asian Games. Therefore, a Rapid Analysis and Forecast System (RAFS), which was based on GRAPES_Meso (GRAPES is short form of Global/Regional Assimilation and PrEdiction System; Chen et al., 2008; Xue et al. 2008), has been in recent years developed at NMC of CMA. The initialization scheme of RAFS consists of the main components as data quality control, 3DVAR data assimilation and the cloud analysis scheme. The radar observation data quality control scheme was developed in CAMS of CMA (Liu et al., 2010). The cloud analysis scheme of ADAS (ARPS Data Analysis System) of CAPS/Oklahoma University (Hu et al., 2006; 2001; Xue et al., 2003; Albers et al., 1996) was adapted in GRAPES_RAFS for enhancement to provide a capability for initializing GRAPES_Meso with clouds and precipitation present in the initial fields. Some modifications or improvements has been conducted in the cloud analysis scheme in RAFS, such as optimizing back-ground cloud scheme, adding the calculation method of saturated mixing ratio over ice surface for better quantitatively analyzing the cloud parameters. Currently, 3 dimensional radar reflectivity, surface observations of cloud bases and cloud fraction, radio-sounds data collected every 1 mn, Chinese-made satellite FY-2 ‘s visible images and inferred brightness temperature TBB were used in the cloud analysis of GRAPES_RAFS. After the cloud analysis, the 3 dimensional cloud parameters are introduced by nugging technique for initialization of the GRAPES_Meso model integration. In comparison to the observations of FY2’s cloud fractions, cloud tops of MODIS, and TRMM, the cloud fraction, the cloud top and microphysical species of cloud were successfully reproduced by inclusion of a cloud analysis scheme.

The case study showed that the cloud analysis had a significant positive impact on the very short term forecast (from 1 hour until to 12 hours of range) in reducing the spin-up time, the quantitative precipitation forecasts (QPF), as well as in providing full of the cloud analysis products (such as cloud fraction, 3 dimensional structure of cloud types, cloud base and top, and the associated vertical velocity), and other extreme weather analysis parameters (such as stability criteria). However, the cloud analysis is still a complicated issue. A lot of works are ongoing for real-time implementation at NMC/CMA.


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