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Shan Nan, He Ping, Wu Lei. The application to temperature advection retrieval based on wind profile radar data. J Appl Meteor Sci, 2016, 27(3): 323-333. DOI: 10.11898/1001-7313.20160307.
Citation: Shan Nan, He Ping, Wu Lei. The application to temperature advection retrieval based on wind profile radar data. J Appl Meteor Sci, 2016, 27(3): 323-333. DOI: 10.11898/1001-7313.20160307.
shu

The Application to Temperature Advection Retrieval Based on Wind Profile Radar Data

  • 1.

    Nanjing University of Information Science & Technology, Nanjing 210044

  • 2.

    CMA Meteorological Observation Center, Beijing 100081

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    Abstract
  • Temperature advection is a basic physical variable in the weather prediction. It directly leads to the change of atmospheric thermal structure and further brings about the alteration of atmospheric physics field, and can reflect the development of weather systems better. In recent years, the technology of wind profile radar (WPR) improves greatly, and WPR data has both high precision and high spatial-temporal resolution and could continuously provide the distribution of horizontal winds over time. Based on the concept of temperature advection and the principle of thermal wind, retrieving the temperature advection with high precision and spatial-temporal resolution is feasible by algorithms established.The temperature advection information is retrieved from WPR data at Yanqing Station of Beijing, whose results are compared to temperature advection prediction products of Global Medium Range Forecast System of T639L60 (hereinafter, T639L60 model). A cold air invasion process on 15 Nov 2014 in the night is analyzed in detail and 6 more samples occurring from Sep to Nov in 2015 are statistically analyzed for evaluation too. Results show that the horizontal wind of the WPR is highly consistent with the wind prediction data of T639L60 model within a certain amount of prediction time (about 6 to 12 h). The order of magnitude is consistent and the value is close between the retrieval of temperature advection by the WPR data and the initial data of T639L60 model. The quality of retrieving temperature advection depends on the quality of horizontal wind profile data. Temperature advection prediction products of T639L60 model and the real-time retrieval products are accordant within a period of 6-12 h depending on the temporal scale of different weather system. The derivation gradually increases as the prediction time lengthens, sometimes even reverse prediction advection attribute may appear. Temperature advection with real-time, continuous attribute and high precision can be provided through WPR observations whose time and vertical resolution is 6 min and 120 m, respectively. And some prediction results can be calculated using the measured results by linear extrapolation in a short period. Thus, the precision of numerical forecast can be improved with WPR data assimilated in the future. Preliminary results show that the real-time 3D products and forecast products of temperature advection with high precision, spatial and temporal resolution could be generated through high quality WPR network data assimilated.
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  • Fig  1.   Real-time data of wind feathers at Yanqing Station of Beijing from 1900 BT to 2100 BT on 15 Nov 2014

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    Fig  2.   Wind of analysis fields by T639L60 model of 850 hPa (a) and 700 hPa (b) at 2000 BT 15 Nov 2014 in Beijing-Tianjin-Hebei region

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    Fig  3.   Temperature advection at Yanqing Station of Beijing from 1900 BT 15 Nov to 0500 BT 16 Nov in 2014

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    Fig  4.   Temperature advection by T639L60 model at 850 hPa and 500 hPa at 2000 BT 15 Nov 2014 in Beijing-Tianjin-Hebei region

    (a) at 850 hPa in the analysis field, (b) at 500 hPa in the analysis field, (c) at 850 hPa in the forecast field after 3 h, (d) at 500 hPa in the forecast field after 3 h, (e) at 850 hPa in the forecast field after 6 h, (f) at 500 hPa in the forecast field after 6 h, (g) at 850 hPa in the forecast field after 9 h, (h) at 500 hPa in the forecast field after 9 h

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    Fig  5.   Comparison of 500 hPa (a) and 850 hPa (b) temperature advection by WPR and T639L60 model at Yanqing Station of Bejing at 2000 BT 15 Nov 2014

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    Fig  6.   Comparison of temperature advection by WPR and T639L60 model at Yanqing Station of Beijing

    (a)850 hPa at 0800 BT 4 Sep 2015, (b)850 hPa at 0800 BT 11 Sep 2015, (c)850 hPa at 2000 BT 20 Oct 2015, (d)500 hPa at 0800 BT 6 Oct 2015, (e)500 hPa at 0800 BT 15 Oct 2015, (f)500 hPa at 2000 BT 17 Nov 2015

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    Table  1   WPR of 700 hPa real-time wind and corresponding forecasted wind at Yanqing Station of Beijing

    时间 WPR T639L60 预报时效/h
    风速/(m·s-1) 风向/(°) 风速/(m·s-1) 风向/(°)
    2014-11-15T 20：00 8.8 247 9.6 269 0
    2014-11-15T 23：00 9.3 244 8.3 278 3
    2014-11-16T 02：00 9.6 261 4.7 313 6
    2014-11-16T 05：00 8.3 287 3.0 333 9
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    Table  2   WPR of 850 hPa real time wind and corresponding forecasted wind at Yanqing Station of Beijing

    时间 WPR T639L60 预报时效/h
    风速/(m·s-1) 风向/(°) 风速/(m·s-1) 风向/(°)
    2014-11-15T 20：00 7.1 270 5.6 235 0
    2014-11-15T 23：00 6.8 270 6.9 282 3
    2014-11-16T 02：00 5.7 299 9.3 311 6
    2014-11-16T 05：00 4.7 323 10.1 331 9
    DownLoad: CSV

    Table  3   WPR of 500 hPa real-time temperature advection and corresponding forecasted temperature advection at Yanqing Station of Beijing

    时间 WRP T639L60 预报时效/h
    强度/(10-4 K·s-1) 属性 强度/(10 -4 K·s -1) 属性
    2014-11-15T20：00 -2.50 冷 -2.10 冷 0
    2014-11-15T23：00 0.55 暖 0.30 暖 3
    2014-11-16T02：00 0.90 暖 0.90 暖 6
    2014-11-16T05：00 1.50 暖 0.20 暖 9
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    Table  4   WPR of 850 hPa real-time temperature advection and corresponding forecasted temperature advection at Yanqing Station of Beijing

    时间 WRP T639L60 预报时效/h
    强度/(10-4 K·s-1) 属性 强度/(10-4 K·s-1) 属性
    2014-11-15T20：00 0.85 暖 0.85 暖 0
    2014-11-15T23：00 0.55 暖 0.25 暖 3
    2014-11-16T02：00 -0.20 冷 -0.20 冷 6
    2014-11-15T05：00 0.60 暖 -0.50 冷 9
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    • Received : 2015-09-21
    • Accepted : 2016-02-02
    • Published : 2016-05-30
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