36 1 Vol. 36 No Journal of the Meteorological Sciences Feb ZHANG Xi NIU Shengjie WEI Jincheng et al. Classificati

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36 1 Vol. 36No. 1 2016 2 Journal of the Meteorological Sciences Feb. 2016.. 2016 36 1121-127. ZHANG Xi NIU Shengjie WEI Jinchenget al. Classification and case study of macro and micro structures of spring sea fog in Xiamen. Journal of the Meteorological Sciences2016 36 1 121-127. doi 10. 3969 /2014jms. 0108 1 2 1 1 3 1 1 210044 2 710014 3 361100 2013 3 23 4 22 8 NCEP 3 0 ~ 1 2013 4 17 18 Junge P426. 4 doi 10. 3969 /2014jms. 0108 A Classification and case study of macro and micro structures of spring sea fog in Xiamen ZHANG Xi 1 2 NIU Shengjie 1 WEI Jincheng 1 3 ZHANG Shuting 1 1 School of Atmospheric PhysicsCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Abstract Nanjing University of Information Science & TechnologyNanjing 210044China 2 Shaanxi Meteorological Service CenterXi'an 710014China 3 Xiamen Meteorological BureauFujian Xiamen 361100China By using the visibilityfog droplet spectraautomatic weather station observation data the conventional weather data and NCEP Final Operational Global Analysis FNL data of eight fog processes from 23 March to 22 April2013 the macro and micro processes of spring sea fogs in Xiamen were studied. Results show that the weather situations promoting sea fog in Xiamen include cold front low pressure with an inverted trough and high pressure running into sea. The 0-1 temperature range in sea fog areas of Xiamen was important to sea fog forecast. In a typical case on 17-18 April 2013 the strong southwesterly flow with enhanced moisture triggered the formation of this sea fogwhich provided plenty of vapor for the development of this event. The average fog droplet size distribution was in agreement with the Junge distribution. The analysis on evolution of microphysical characteristicssuch as fog droplet number concentration liquid water content and fog droplet mean radius indicated that the dominant physical processes were condensational growth on the nuclei and subsequent reversible evaporation. Key words Fog Sea fog type Micro-structure of sea fog Air-sea temperature difference Xiamen Received2014-08-17 Revised2014-12-30 Published on-line2016-01-18 http / /www. cnki. net /kcms /detail /32. 1243. P. 20160118. 1600. 012. html 41275151 41375138 3502Z20124012 CXZZ13-0514 Corresponding author NIU Shengjie. niusj@ nuist. edu. cn

122 36 1 km 1 2 3 GAOet al 4 5 1 NCEP National Centers for Environmental Prediction 1 1 6 h2 3 hysplit 17 6 7 8 2 2. 1 9-11 1km 90% 2013 3 23 4 22 8 12 3 1 12 h 2 13 14 15 7 5 2. 2 2 14. 8 ~ 20. 9 90% 1. 3 m s - 1 2 m s - 1 1 Fig. 1 The observation sites 18 1 71% 2013 3 23 4 22 50% 1 24. 23 N 20% 39% 118. 19 E 16

1 123 1 2013 8 Table 1 A survey for 8 spring sea fog cases in 2013 /h 850 hpa /km 1 3 24 05 29 22 57 17. 5 h 0. 46 2 3 28 29 15 42 05 18 13. 6 h 0. 42 3 3 30 31 21 54 07 00 9. 1 h 0. 36 4 4 2 02 54 06 55 4. 0 h 0. 27 5 4 4 06 19 23 05 16. 8 h 0. 37 6 4 5 6 17 32 07 43 14. 2 h 0. 08 7 4 15 00 09 07 17 7. 1 h 0. 02 8 4 17 18 15 00 07 00 16. 0 h 0. 11 2 3 23 4 22 Fig. 2 Temperature profiles of sea fogs from 23 March to 22 April 2. 3 2. 3. 1 2013 4 17 18 200 m 500 5 h 4 17 08 500 hpa 4 17 15 92 E 18 3 2013 4 17 18 700 hpa 850 hpa 925 hpa 4 72 h 700 hpa

124 36 3 Fig. 3 2013 4 17 18 a b c de Temporal evolution of a visibility b air temperature c relative humidity d wind speed and e wind direction 4 4 17 15 72 h 0 m 500 m 1 000 m 3 Fig. 4 72 h backward trajectories of air masses at 15 00 on 17 April at 05001 000 m altitudesrespectively 3. 0 19 0 ~ 1 2. 3. 2 6 Vis C LW N 珋 r 0. 05 km Vis < 0. 5 km 0. 5 km Vis < 1 km 1 km Vis < 10 km 3 20 17 15 1 km 15 00 17 30 17 31 18 22 18 23 20 12 17 20 13 18 01 00 07 00 5 2 m C LW N 珋 r C LW 0 ~ 0. 041 g m - 3 C LW 1. 0 0. 003 g m - 3 2 0. 5 ~ 7 C LW

1 125 Fig. 5 5 a 4 17 14 b 4 18 02 Air-sea temperature difference at a 14 00 on 17 April b 02 00 on 18 April 6 2013 4 17 18 a b c d e C LW N 珋 r T 1 min Fig. 6 Temporal evolution of a visibilityb liquid water content C LW c number concentration N d average radius 珋 r and e auto-conversion threshold function T. Values of LWCN 珋 r and T were 1-min averaged 16 00 T 0. 09 15 20 16 40 珋 r C LW N 珋 r 18 01 00 3. 745 10-5 g m - 3 4 cm - 3 1. 6 μm 20 13 T 6e

126 36 7 Fig. 7 The droplet spectra distribution at different stages 8 Junge Fig. 8 Fitting of Junge distribution of average spectra 2 Table 2 Mean values of microphysical properties and variation range at different stages C LW g m - 3 N cm - 3 珋 r μm 0. 041 0 ~ 0. 35 0. 003 0 ~ 0. 05 3. 745 10-5 0 ~ 0. 01 73 5 ~ 326 15 0 ~ 90 4 0 ~ 33 3. 1 1. 5 ~ 5. 4 2. 2 1. 1 ~ 5. 5 1. 6 1. 1 ~ 3. 5 C LW N 珋 r r p 0. 016 g m - 3 36 cm - 3 2. 4 μm 1. 5 μm 21-22 0 ~ 1 N 89 cm - 3 2 C LW 珋 r 0. 37 g m - 3 11 μm N 珋 r 28cm - 3 2. 2 μm C LW C LW 1. 5 μm 3 3 5 a C LW N 珋 r 0. 041 g m - 3 73 cm - 3 3. 1 μm C LW C LW N 珋 r r p 0. 016 g m - 3 2. 3. 3 36 cm - 3 2. 4 μm 1. 5 μm 8 C LW junge Y = ax - b 4 Junge a = 112. 07 b = 2. 24 R 2 = 0. 98 N D = 112. 07D - 2. 24 0. 98 2 ~ 7 μm 2. 8 μm Deirmendjian 16 NASA CRYSTAL-FACE CSTRIPE Gamma 23 3 1

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