# Implementation of the Incremental Analysis Update Initialization Scheme in the Tropical Regional Atmospheric Modeling System under the Replay Configuration

• Corresponding author: Daosheng XU, dsxu@gd121.cn
• Funds:

Supported by the National Natural Science Foundation of China (U1811464) and Science and Technology Planning Project of Guangdong Province, China (2018B020208004)

• doi: 10.1007/s13351-021-0078-2
• In traditional simulations of heavy rainfall events, the regional model is often initialized by using a global reanaly-sis dataset and a cold start method. An alternative to using global analysis data is to gradually introduce the analysis field via an incremental analysis update (IAU) method under the replay configuration. We found substantial differences in the forecast of a heavy rainfall event in southern China between a precipitation forecast using the traditional method and a forecast using the IAU method in the Tropical Regional Atmospheric Modeling System (TRAMS), based on the ECMWF global analysis. The IAU method is efficient in removing spurious high-frequency gravity wave noise, especially when the relaxation time is more than 90 min. The regional model needs to be pre-integrated for about 12 h to warm up the convective system in the background field. The improvement by the IAU method is supported by verification of simulations over 1 month (1–30 April 2019). In general, the IAU technique improves the initialization and spin-up process in the simulation of the heavy rainfall event.
• Fig. 1.  Schematic representation of the IAU technique under the replay configuration. The regional model was first integrated freely forward (blue arrow) for ∆t (warm-up time) to generate the background field Fback. The replay corrector segment $\delta X$ was then calculated according to the increment (FanaFback) and the relaxation time $\tau$. The model was back-tracked to t0 − ∆t (the black arrow) to run a second time with IAU, and the corrector segment was added to the forecast at every time step during the IAU time window.

Fig. 2.  Synoptic environments (500-hPa geopotential height contours in gpm and 850-hPa horizontal vector winds in m s−1) of the heavy rainfall event in South China at (a) 1200 UTC 12 April and (b) 0000 UTC 13 April 2019, based on the ECMWF global analysis data. Color shading denotes wind speed in m s−1.

Fig. 3.  Hourly area-averaged precipitation in western Guangdong Province from 0000 UTC 13 to 0000 UTC 14 April 2019.

Fig. 4.  Combined radar reflectivity (dBZ) in western Guangdong Province at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 13 April 2019. The red rectangle shows the area in which heavy rainfall occurred in the warm sector.

Fig. 5.  Sensitivity of initialization process to varied relaxation time. (a) Surface pressure tendency, (b) cloud water content Qc averaged between 850 and 500 hPa, and (c) rainfall rate. These three variables were area-averaged over western Guangdong Province and output every 10 minutes. The IAU time window is shown by the blue dotted rectangle.

Fig. 6.  As in Fig. 5, but for sensitivity of forecast results to different warm-up lengths of time (∆t).

Fig. 7.  The 3-h accumulated precipitation (mm) between 0600 and 0900 UTC 13 April. (a) Observed rainfall, (b) test-ctrl, (c) test-IAU-6h-90min, and (d) test-IAU-12h-90min. The observed rainfall was obtained from the hourly surface meteorological station observations of China, available at http://data.cma.cn/data/detail/dataCode/A.0012.0001.html.

Fig. 8.  Radar reflectivity (color shading; dBZ) and wind field (vector) at 0700 UTC 13 April in western Guangdong Province. (a) Test-IAU-6h-90min at 1-km height, (b) test-IAU-12h-90min at 1-km height, (c) test-IAU-6h-90min, cross-section along the black line in (a), and (d) test-IAU-12h-90min, cross-section along the black line in (b).

Fig. 9.  (a) Threat score and (b) bias score of test-ctrl and test-IAU based on the hourly precipitation during 1–30 April 2019.

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###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## Implementation of the Incremental Analysis Update Initialization Scheme in the Tropical Regional Atmospheric Modeling System under the Replay Configuration

###### Corresponding author: Daosheng XU, dsxu@gd121.cn;
• Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640
Funds: Supported by the National Natural Science Foundation of China (U1811464) and Science and Technology Planning Project of Guangdong Province, China (2018B020208004)

Abstract: In traditional simulations of heavy rainfall events, the regional model is often initialized by using a global reanaly-sis dataset and a cold start method. An alternative to using global analysis data is to gradually introduce the analysis field via an incremental analysis update (IAU) method under the replay configuration. We found substantial differences in the forecast of a heavy rainfall event in southern China between a precipitation forecast using the traditional method and a forecast using the IAU method in the Tropical Regional Atmospheric Modeling System (TRAMS), based on the ECMWF global analysis. The IAU method is efficient in removing spurious high-frequency gravity wave noise, especially when the relaxation time is more than 90 min. The regional model needs to be pre-integrated for about 12 h to warm up the convective system in the background field. The improvement by the IAU method is supported by verification of simulations over 1 month (1–30 April 2019). In general, the IAU technique improves the initialization and spin-up process in the simulation of the heavy rainfall event.

Reference (37)

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