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Remote Sensing of Typhoons Impact and Disaster Management Danling

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Remote Sensing of Typhoons Impact and Disaster Management Danling Remote Sensing of Typhoons Impact and Disaster Management - A New Ecological Index for SST Cooling Response to Typhoon 唐丹玲 DanLing Tang 唐丹玲 South China Sea Institute of Oceanology Chinese Academy of Sciences合 http://lingzis.51.net/ [email protected] Marine Silk Road Guangzhou Climate Changes /Natural Hazards 沙尘暴 台风玛姬 印度洋海啸2004 California Noctiluca ？ 2013 青岛浒苔 夜光藻赤潮 山东日照 阿拉伯海藻华 Distribution of typhoon (hurricane) 台风玛姬 ? 1 Typhoon impacts on marine ecosystem A New Ecological Index for SST Cooling 2 Response to Typhoon 3 Typhoon Disaster Management Remote Sensing Observations Marine Environment and ecology 中科院南海海洋研究所 唐丹玲 Typhoons impact 1 on Marine Ecosystems DanLing TANG B. Post-typhoon Chl-a B1. 2005 a HNI HNI Damrey, Sep 2005 b SCS A3. 22:36, Sep 25 China B2. 2002-2004 HNI SCS HNI A4. 11:26, Sep 26 China HNI Modis Chl-a (mg m-3) SCS 0.4 0.8 1.2 1.6 2.0 2.8 3.0 2.4 0 QuikScat Wind Vectors (m/s) Zheng and Tang, MEPS 2007 0 10 20 30 Offshore and nearshore chlorophyll increases induced by typhoon and typhoon rain. Offer shore Near shore Guangming Zheng and Danling Tang, 2007, Marine Ecology Progress Series, 333：61-74，2007 (SCI) TMI-AMSRE A B C DanLing TANG SST A B C (mg m-3) TRMM Rainfall (mm) Chl-a TMI-AMSRE SST ( C) Chl-a (mg m-3) TRMM Rainfall (mm) 25 26 27 28 29 30 0 0.4 0.8 1.2 1.6 2.03.0 2.4 0 60 120 180 240 25 26 30027 28 29 30 0 0.4 0.8 1.2 1.6 2.0 2.4 3.0 0 60 120 180 240 300 A1. Sep 21 B1. Sep 20-21 Modis C1. Sep 21 A7. Sep 27 C7. Sep 27 b A2. Sep 22 C2. Sep 22 A8. Sep 28 B2. Sep 28 Modis C8. Sep 28 a T1 Sep 23 A3. C3. Sep 23 T4 A9. Sep 29 B3. Sep 29 Modis C9. Sep 29 a A4. Sep 24 C4. Sep 24 No data. A10. Sep 30 B4. Sep 30 Modis C10. Sep 30 a A5. Sep 25 C5. Sep 25 b T2 T3 A11. Oct 1 B5. Oct 1 SeaWiFS C11. Oct 1 A6. Sep 26 C6. Sep 26 a a b http://lingzis.51.net/ DanLing TANG Sea level variation & sea surface cooling 0 A. 3-d pre-typhoon B. during typhoon 4 C 30 100 SST Center 29 SLA Typhoon 50 SLA 0 28 C) ˚ -50 ( 27 (cm) -100 26 -150 SST T1 T2 -200 25 C. 1-d post-typhoon D. 4-d post-typhoon 30 100 29 Center Center Typhoon 50 Typhoon SLA 0 28 -50 SLA 27 Sea level (SLA) anomalies level Sea -100 (SST) temperature surface Sea SST 26 -150 SST T3 T4 -200 25 16 17 18 19 20 21 22 16 17 18 19 20 21 22 Latitude (ºN) Zheng and Tang, MEPS 2007 http://lingzis.51.net/ DanLing TANG 19 20 21 22 23 24 25 26 27 28 29 30 1 2 3 4 5 6 7 8 9 10 11 12 0.9 0.6 Typhoon wind Sampling box (Pa) QuikScat 0.3 Wind Stress Wind 0.0 60 30 Multi-sensor (cm) SLA 0 -30 sea level variation -60 30 SST decrease 28 TMI-AMSRE (ºC) SST 26 24 Typhoon Modis ) 3 passage - a - 0.6 SeaWiFS Chl-a peak Chl (mg m (mg 0.3 0.0 19 20 21 22 23 24 25 26 27 28 29 30 1 2 3 4 5 6 7 8 9 10 11 12 September October (2005) Zheng and Tang, MEPS 2007 • intensities /Wind Speed? • translation speeds Zhao H, DanLingTang, Wang Y. 2008 MEPS Tang DanLing 唐丹玲 Strong, fast-moving (4.4m Weak, slow moving (2.87 m s-1) s-1) KT Wind SST Chl a MEPS 2008 Eddy-feature phytoplankton bloom induced by tropical cyclone in the South China Sea, m S-1 TWI 30+ 19 Jun China 25 a 20 20°N 15 Philippines 10 b 5 15°N 115°E 125°E 0 NB (Chen & Tang, 2010,IJRS) Prior Linfa After or during Linfa A. QuikScat wind speed 20 A1.7-13 Jun A2.19 Jun 30+ 20 China China 25 ) 1616 1 - 1 20 - 1212 15 m s m 88 10 44 vector QuikScat wind QuikScat 5 Luzon Luzon speed (m s (m speed 00 0 B. Ekman layer depth B1.15 Jun B2.18 & 19 Jun 1 - 450 00 1-Jul2-Jul3-Jul4-Jul5-Jul6-Jul7-Jul8-Jul9-Jul 14-Jun15-Jun16-Jun17-Jun18-Jun19-Jun20-Jun21-Jun22-Jun23-Jun24-Jun25-Jun26-Jun27-Jun28-Jun29-Jun30-Jun 10-Jul11-Jul12-Jul 360 m s m -50-50 6 270 - 180 -100-100 10 Luzon Luzon 90 -150-150 velocity Ekman pumping Ekman 0 -200(m) depth -200 -250-250 a C1. Jun 1998-2009 C2.23 Jun 1.00 - 14-Jun15-Jun16-Jun17-JunC.18-Jun19-Jun TRMM20-Jun21-Jun22-Jun23-Jun24-Jun rainfall25-Jun26-Jun27-Jun28-Jun29-Jun 30-Jun1-Jul2-Jul3-Jul4-Jul5-Jul6-Jul7-Jul8-Jul9-Jul10-Jul11-Jul12-Jul 0.80 3 – 100 0.60 100 0.40 8080 mg m mg 60 Luzon 0.20 60 Luzon MODIS Chl MODIS Concentration 0.00 4040 2020 D1.10-17 Jun D2.18-25 Jun 30.0 rainfall (mm)rainfall 00 - 29.2 28.4 D. GHRSST 1-Jul2-Jul3-Jul4-Jul5-Jul6-Jul7-Jul8-Jul9-Jul ℃ 14-Jun15-Jun16-Jun17-Jun18-Jun19-Jun20-Jun21-Jun22-Jun23-Jun24-Jun25-Jun26-Jun27-Jun28-Jun29-Jun30-Jun 10-Jul11-Jul12-Jul 27.6 30 30 Luzo n 26.8 Luzon ) 2929 26.0 ℃ MODIS Sea MODIS surface Temperature -35 2828 E1.15 Jun E2.26 Jun -25 27 SST ( SST -15 27 -5 26 0 cm 26 15 E. Chl-a concentration Luzon surface Height Height surface - 25 2-Jul 4-Jul 6-Jul 8-Jul Luzon 35 0.80.814-Jun 16-Jun 18-Jun 20-Jun 22-Jun 24-Jun 26-Jun 28-Jun 30-Jun 10-Jul 12-Jul ) 3 Sea (SHA) Anomaly F1.15 Jun F2.24 Jun - 0.60.6 14 1 12 - 0.4 100 0.4 0 80 a (mg m (mga 0.2 cm s cm 600 - 0.2 40 0 Chl 0 14 18 20 22 24 26 28 30 2 4 6 8 10 12 currents 20 16 Luzon Sea surface Sea Luzon 0 14- 17- June20- 23- 26- 29- 2- 5-July 8- 11- Jun Jun Jun Jun Jun Jun Jul Jul Jul Jul 1. Cyclone Linfa wind Yongqiang CHEN, DANLING TANG, 2012, A 2. Lingering & looping 5. phytoplankton bloom Eddy-feature 3. Vertical pumping phytoplankton bloom induced by tropical 4. Upwelling & entrainment B cyclone in the South China Sea, Chl-a mg m-3 International Journal of Remote Sensing. Vol. 33, No. 23, 10 December 2012, 7444–7457.（SCI） 50cm s-1 C Chen, Tang , 2011, IJRS 6. Sea surface currents (little white arrows) Chlorophyll on surface and subsurface 23 After typhoon 2 22 1.9 21 1.8 1.7 20 1.6 19 1.5 1.4 18 a 1.3 surface 1.2 17 111 112 113 114 115 116 117 118 119 120 1.1 1 23 0.9 0.8 22 0.7 21 0.6 0.5 20 0.4 0.3 19 0.2 18 50b m 0.1 0 17 -3 Ye and Tang, 2013, JMS 111 112 113 114 115 116 117 118 119 120 mg.m 25 23 21 Other area 19 17 3 1 15 109 112 115 118 121 124 25 23 21 19 Other years 17 4 2 15 109 112 115 118 121 124 chl a (mg m- HaiJun. Ye, Yi. Sui,3) Danling. Tang, Y. D. Afanasyev，2013, A Subsurface Chlorophyll a Bloom Induced by Typhoon in the South China Sea. Journal of Marine Systems （SCI）. Dissolved oxygen (DO) ? typhoon / tropical cyclone 20 the super-typhoon Nanmadol between 22 and 30 August 2011, 21 Horizontal distribution Fig.3 Horizontal distribution The Chl-a (mg m3) and SST (C) maps are 8-day composites retrieved from MODIS data the SLA (cm) maps are weekly composites retrieved from altimeter data of severalFig.6 satellites. Daily averaged Ekman pumping velocity (m s1) China 28 Aug 2011. Pacific ocean South China Sea Ekman Pumping Velocity Pumping Velocity Ekman (m/s) Fig.7 Sea surface current (m s1), the passage of the typhoon in Luzon Strait. a b 1 week before week 1 before c d Sea Surface Current (m/s) Current Surface Sea 1 week (c) week 1 after 2 weeks (d) after weeks 2 Fig.8 Typhoon Entrainment DO Kuroshio Vertical Increase mixing Nutrient + increase Upwelling Chl-a Temperature increase + decrease Fig.9 1. Surface water 2. TD uplifting eddy- diluted by heavy rain, driven high pCO2,sw with low pCO2,sw Freshwater Typhoon Strong from Mekong wind River Pre-existing Enhanced cold eddy Ekman cold eddy Dilution: low transport SSS Eddy-driven Enhanced eddy-driven uplifting uplifting Sink CO Source Wind-driven 2 uplifting change to a source temporarily (1) Increase in fish abundance during two typhoons in the South China Sea Yu & Tang, 2013, ASR ②species number New records Yu & Tang, 2013, ASR • Fish Primary production food phytoplankton nutrient fall down discharges deep water SST oceanic environment upwelling ……. • wind Typhoon 1. one of the most frequent and serious natural hazards ,causing enormous economic losses. 2. significant negative impacts on coastal environments 3. positive impacts on marine ecosystems A New Ecological Index for SST Cooling Response to Typhoons SST -- indicator or ecological factor of marine ecosystem environment conditions typhoons propagate over the ocean surface, affect both the atmosphere and the ocean: cause great changes in the upper ocean: Atmosphere dynamic processes thermodynamic processes Ocean TyphoonBackgrounds Indices from different aspects Saffir-Simpson Hurricane Intensity Scale Maximum Potential Intensity (MPI) [Emanuel, 1987] Using thermodynamic MPI model, Henderson-Sellers et al.
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