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# Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall

doi:  10.1007/s00376-022-1380-3

• Assimilation of the Advanced Geostationary Radiance Imager (AGRI) clear-sky radiance in a regional model is performed. The forecasting effectiveness of the assimilation of two water vapor (WV) channels with conventional observations for the “21·7” Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study. The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition of the AGRI exceeds 500 mm, compared to a maximum value of 532.6 mm measured by the national meteorological stations, and that the location of the maximum precipitation is consistent with the observations. The results for the short periods of intense precipitation processes are that the simulation of the location and intensity of the 3-h cumulative precipitation is also relatively accurate. The analysis increment shows that the main difference between the two sets of assimilation experiments is over the ocean due to the additional ocean observations provided by FY-4A, which compensates for the lack of ocean observations. The assimilation of satellite data adjusts the vertical and horizontal wind fields over the ocean by adjusting the atmospheric temperature and humidity, which ultimately results in a narrower and stronger WV transport path to the center of heavy precipitation in Zhengzhou in the lower troposphere. Conversely, the WV convergence and upward motion in the control experiment are more dispersed; therefore, the precipitation centers are also correspondingly more dispersed.
• Figure 1.  Jacobian functions of (a) temperature and (b) WV of ch8-ch14 AGRI IR channels calculated by RTTOV.

Figure 2.  The horizontal distribution of (a) observed BT (K) of ch13 (white-grey-black shading) and confidently clear pixels (orange dots) and (b) assimilated conventional observations at 1200 UTC 19 July 2021.

Figure 3.  Probability density function (PDF) of observation-minus-background (OMB, innovation) (a)–(b) with and (c)–(d) without Varbc for the AGRI observations of (a), (c) ch9; (b), (d) ch10, respectively, while the PDF of both the OMB and the Observation Minus Analysis (OMA) using Varbc and QC are shown for ch9 in (e) and ch10 in (f). The gray shading covers the pixels left after QC, whose count is represented by the “Num after QC”. The “Mean” and “Stdv” in (a)–(d) represent mean and standard deviations of all samples before QC. The “Mean” and “Stdv” in (e)–(f) represent mean and standard deviations of samples after QC. Black lines are the auxiliary line of 0. The samples are collected from the analysis at 1200 UTC 19 July.

Figure 4.  Geopotential height (contours; gpm) at 500 hPa, specific humidity (shading; kg kg−1) and wind (vectors; m s−1) at 850 hPa of the ERA5 reanalysis at (a) 1200 UTC 19 July 2021; (b) 1200 UTC 20 July 2021. The all-sky observed BT (K) before QC are shown for ch9 in (c) and c10 in (d), and the observed and simulated BT (K) after QC of (e, g) ch9 and (f, h) ch10 at 1200 UTC 19 July 2021.

Figure 5.  Simulated area in ARW-WRF, the area shown in the figure is d01, and the area outlined by black line is d02.

Figure 6.  WVF value (shading; 10-2 g cm-1 hPa-1 s-1) and wind (vector; m s-1) increment at 850 hPa in the (a) AGRI+CONV and (b) CONV experiments, and difference of (c) specific humidity increment (10-4 kg kg-1) and (d) wind increment (vector; m s-1) and temperature increment (K) at 850 hPa between the AGRI+CONV and CONV experiments [(AGRI+CONV) - CONV)] at 1200 UTC 19 July 2021. The yellow lines in (a) represent the two enhanced water vaper transport paths. The red lines in (c) and (d) show the locations of the cross sections appearing in Fig. 10.

Figure 7.  (a) The observed 24-h accumulated rainfall (shading; mm) and the corresponding forecast rainfall (shading; mm) from the (b) CTRL, (c) CONV and (d) AGRI + CONV experiments from 1200 UTC 19 July 2021 to 1200 UTC 20 July 2021. The black box represents the Zhengzhou area.

Figure 8.  (a) The observed 3-h accumulated rainfall (shading; mm) from 0900 UTC 20 to 1200 UTC 20 July 2021 and the corresponding forecast rainfall (shading; mm) from the (b) CTRL, (c) CONV and (d) AGRI + CONV experiments from 0500 UTC 20 to 0800 UTC 20 July 2021. Panel (e) is the same as (a), but from 1300 UTC 20 to 1600 UTC 20 July 2021 and (f)–(h) is the same with (b) –(d), but from 0900 UTC 20 to 1200 UTC 20 July 2021. The black boxs in (a)–(d) represent the Zhengzhou and in (e)–(h) represent the Kaifeng and Zhoukou areas.

Figure 9.  Geopotential height (contours; gpm) at 500 hPa and WVF value (shading; 10-2 g cm-1 hPa-1 s-1), wind (vectors; m s-1) at 850 hPa in the AGRI+CONV experiment at (a) 1200 UTC 19 July 2021; (b) 0000 UTC 20 July 2021; (c) 0500 UTC 20 July 2021; (d) 0700 UTC 21 July 2021. Panels (e)–(h) are the same as (a)–(d), but for the CONV experiment. (i–l) Geopotential height (contours; units: gpm) at 500 hPa in the AGRI+CONV (blue contours) and CONV (purple contours) experiments and WVF (shading; units: 10-2 g cm-1 hPa-1 s-1) of ((AGRI+CONV) – CONV) at 850 hPa. The brown arrows in (a) represent the two water vaper transport paths. The red auxiliary lines represent the western edge of the subtropical ridge. The orange boxes in (c)–(d) and (g)-(h) represent the areas around the Dabie Mountains, and the black box in (l) represent the areas around Zhengzhou station.

Figure 10.  The cross sections between (30.6$^\circ$N, 112.6$^\circ$E) and (36.8$^\circ$N, 118.5$^\circ$E) of WVF value (shading; 10−2 g cm−1 hPa−1 s−1) and wind speed (contours; m s−1) at (a) 1200 UTC 19 July 2021, (b) 0000 UTC 20 July 2021, (c) 0500 UTC 20 July 2021 and (d) 0700 UTC 20 July 2021 from the AGRI+CONV experiment. (f)- (i) are the same as (a)−(d), but for the CONV experiment. (e) Longitude-pressure cross sections of water vaper flux divergence (shading; 10−2 g cm−2 hPa−1 s−1), zonal circulation (vectors; zonal wind, m s−1; vertical motion, 10−1 m s−1), and zonal distribution of 1 h accumulated rainfall forecast (mm) along 34.76$^\circ$N in the AGRI+CONV experiment at 0800 UTC 20 July 2021. Panel (j) is same as (e) but along 34.65$^\circ$N in the CONV experiment.

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## Manuscript History

Manuscript revised: 23 December 2021
Manuscript accepted: 14 January 2022
###### 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

## Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall

###### Corresponding author: Juanjuan LIU, ljjxgg@mail.iap.ac.cn;
• 1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
• 2. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
• 3. Beijing Institute of Applied Meteorology, Beijing 100029, China
• 4. Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 210044, China
• 5. Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
• 6. Public Meteorological Service Center, China Meteorological Administration, Beijing 100081, China

Abstract: Assimilation of the Advanced Geostationary Radiance Imager (AGRI) clear-sky radiance in a regional model is performed. The forecasting effectiveness of the assimilation of two water vapor (WV) channels with conventional observations for the “21·7” Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study. The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition of the AGRI exceeds 500 mm, compared to a maximum value of 532.6 mm measured by the national meteorological stations, and that the location of the maximum precipitation is consistent with the observations. The results for the short periods of intense precipitation processes are that the simulation of the location and intensity of the 3-h cumulative precipitation is also relatively accurate. The analysis increment shows that the main difference between the two sets of assimilation experiments is over the ocean due to the additional ocean observations provided by FY-4A, which compensates for the lack of ocean observations. The assimilation of satellite data adjusts the vertical and horizontal wind fields over the ocean by adjusting the atmospheric temperature and humidity, which ultimately results in a narrower and stronger WV transport path to the center of heavy precipitation in Zhengzhou in the lower troposphere. Conversely, the WV convergence and upward motion in the control experiment are more dispersed; therefore, the precipitation centers are also correspondingly more dispersed.

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