基于FY-4A溫濕廓線的強對流過程探空檢驗及應用分析
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廣西氣象科研計劃項目(桂氣科2022QN08)、國家自然科學基金項目(41905077)、廣西自然科學基金項目(2017GXNSFBA198133)、欽州科學技術項目(202014806),廣西區氣象局短臨臨近天氣預報技術創新團隊專項共同資助


Comparative Verification of Sounding Data of Strong Convective Processes Based on FY-4A Temperature and Humidity Profiles
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    摘要:

    選取2019年2月至2020年2月廣西區域內出現強對流天氣的時段,將區內6個探空站溫濕廓線資料以及ERA5數據作為基準檢驗,分析了FY-4A衛星溫濕廓線的誤差情況,結果表明:①無云條件下FY-4A溫濕度廓線的偏差相對較小。相對于探空數據,質量控制為0和1的樣本均方根誤差RMSE范圍在1.04~4.16 ℃,總體RMSE為2.61 ℃,850~700 hPa、600~500 hPa以及250 hPa上誤差較小,RMSE 均小于2 ℃。FY-4A與ERA5溫度廓線的差異分布與探空結果相近,RMSE范圍為1.01~4.15 ℃,總體RMSE為2.19 ℃,925~400 hPa以及250 hPa上RMSE 均小于2 ℃。②無云條件下FY-4A濕度廓線總體RMSE為61.06%,低值區位于900~700 hPa,平均約為20.51%。在500 hPa附近誤差最大,可能與干空氣入侵導致垂直方向上含水量突變有關??傮w而言對流層低層誤差較高層小。③個例中重構的T-Inp圖能一定程度上還原大氣上下層的溫濕結構特征,但對于層結穩定度以及不穩定能量的定量估計還存在一定偏差。經質量控制后的溫度數據較好地反映了冷暖空氣的活動特征,對于強對流潛勢的監測具有很好的提示作用。受云影響時可利用的高質量樣本減少,在業務應用時可以嘗試利用多源數據進行訂正。

    Abstract:

    The reliability of FY-4A temperature and humidity profiles are verified by using conventional sounding data and ERA5 data in Guangxi Province during the strong convection processes from February 2019 to February 2020. The results show that: (1) The FY-4A temperature and humidity profiles have lower deviation for the clear sky. Compared with radiosonde data, the root mean squared error (RMSE) of FY-4A temperature with quality control 0 and 1 data ranges from 1.04 ℃ to 4.16 ℃, and the overall RMSE is 2.61 ℃. The inversion accuracy of temperature is better in 850-700 hPa, 600-500 hPa and 250 hPa, all of which have a RMSE less than 2 ℃. The different distribution of temperature profiles between FY-4A and ERA5 is similar to the above. The RMSE ranges from 1.01 ℃ to 4.15 ℃, and the overall RMSE is 2.19 ℃. RMSE is less than 2 ℃ at 925-400 hPa and 250 hPa. (2) The overall RMSE of FY-4A humidity profile is 61.06% compared to radiosonde data under the clear sky, and there is a relatively small error in 900-700 hPa with an averaging RMSE of about 20.51%. The error reaches the maximum near 500 hPa, which may be related to the sudden change of water content in the vertical direction caused by dry air intrusion. In addition, the errors of the lower troposphere are generally smaller than those of the upper troposphere. (3) The reconstructed Tlnp diagram in the strong convection case can restore the temperature and humidity structure characteristics of the upper and lower layers of the atmosphere to a certain extent. However, there is still deviation in the quantitative estimation of stratification stability and unstable energy. The temperature data can better reflect the activity characteristics of cold and warm air after quality control, which provide a prompting effect on the monitoring of strong convective potential. The available high-quality samples are reduced when affected by the cloud, which needs to be corrected by multi-source data in the application.

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覃皓,黃明策,農孟松,韋美鬧,伍麗泉.基于FY-4A溫濕廓線的強對流過程探空檢驗及應用分析[J].氣象科技,2023,51(1):1~13

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  • 收稿日期:2021-07-05
  • 定稿日期:2022-11-07
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  • 在線發布日期: 2023-03-03
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