Satellite data for African applications

Transcription

1 Satellite data for African applications Henk Verschuur, EUMETSAT

2 Introduction Some examples of satellite products which are useful for Africa

3 Satellite products Tropical cyclones Floods Dust storms Industrial Fires Wildfires Heatwave Severe Convection Divergence product Air Mass Dynamics Volcano monitoring

4 Tropical Cyclones One of the most damaging natural disasters With the advent of satellites no TC s escaped from discovery Increasing role of satellites and NWP models An unusual number a major hurricanes struck the US between August and September in 2004 and 2005 killing a large number of people and causing damage of billions of dollars Source of TC s in the ITCZ over Africa

5 Hurricane Isabel Mali Guinea MSG-1, 3-15 September 2003,RGB Composite, R=NIR1.6, G=VIS0.8, B=VIS0.6

6 8 September 2003, 12:00 UTC Hurricane "Isabel" Small Ice Particles (intense precip.) MFG IR Channel i MSG RGB 05-06,04-09,03-01

7 Satellite products IR VIS MSG-1 8 May :15 UTC RGB Composite R = NIR1.6 G = VIS0.8 B = VIS0.6

8 Floods Seasonal flooding in Zambia and Niger river in Mali

9 Floods Example Angola and Zambia 3rd Feb :30

10 Sand and dust storms Sand and dust storms Severe health risks Much damage to aircraft engines tons of dust yearly transported from the Sahara to the Caribbean and the US

11 Sand and dust storms

12 Sand and Dust Colour change from dark pink into light pink : Channel R G B Dark pink % 18% 42% Light pink % 14% 40% Note: Larger dust particles are falling faster than the smaller ones The particle size is playing an important role in the rate of emissivity At the end of this loop the temperature is increasing due to diurnal cycle The diurnal cycle of the temperature has an influence on the severity of the dust storm Due to these complexities it is difficult to fully understand the changing colours

13 Sand and Dust A single analysed grain of sediment from Trona (USA). The grain has an a-axis >200µm and a b-axis of 120µm (very fine sand grain). It also has grains of silt and clay adhering to the outside of the grain. The elements of the sand grain show high Silica (Si) and Oxygen (O) values but also relatively high Aluminium (Al), Sodium (Na) and Magnesium (Mg) peaks, indicating that it is a Feldspar grain. In addition, some of the smaller grains show concentrations of Calcium (Ca) and Iron (Fe), probably Calcium carbonate and Iron oxide respectively. (Adrian Palmer) General electron microscope image of sand grain

14 Industrial Fires Iraq sulphur plant: tons of sulphur burnt Buncefield Oil Refinery explosion, UK SO2 particles have specific absorption properties which makes recognition possible Watchdog function of the 3.9 ųm Channel for hot spots

15 25 June 2003, 12:00 UTC Fire Sulphur Plant Iraq MSG, Difference IR IR8.7

16 Smoke Tracking from Buncefield Oil Refinery, UK (note hot spot detection)

17 Wild Fires Watchdog function of the 3.9 ųm Channel for hot spots Forest fires are accidents Dangerous to the population Severe damage to the environment African Wild fires are seasonal and scheduled

18 3 Aug 2003 Forest Fires Portugal & Spain Portugal Smoke from Forest Fires Burned Area MSG, HRV Channel

19 Wild Fires Diurnal cycle of fires Kongo and Angola MSG-1, Channel 04 (IR3.9)16 July :00-15:00 UTC

20 Heat Wave The European heat wave of the summer of 2003 was an extreme climatic anomaly, the summer might have been the warmest since 1540 (Beniston, 2004; Schär et al., 2004) In France alone, officials estimated that wheat and corn harvests decreased by 15 and 28%, respectively, with losses totalling between US$1.1 and $4.4 billion (Housego, 2003) Some death above average reported The July 2006 heat wave in Europe might show similar results

21 Heat Wave A combination of MODIS satellite imagery, meteorological station data, and the NCEP/NCAR reanalysis has been used to explore the spatial and temporal evolution of the 2003 heat wave in France. Beyond its immediate impact, the 2003 heat wave has been interpreted by many as a harbinger of long-term climate change. Satellite will play an increasingly role in climate studies.

22 (A) (B) Figure : 2003 NDVI anomaly (NDVI, unitless) calculated from MODIS 16-day composites for (A) 23 April 8 May (B) June (C) July (D) August (C) (D) The ASTER footprint is indicated by the black box Ecological zones are outlined in grey B. F. ZAITCHIK ET AL

23 Severe convection

24 Low-Level Clouds Overshooting Top 8 Sep 2003 Convection Niger Dust front Thin Cirrus Niger MSG, RGB i

25 Severe Convection over Congo Information on: Particle size Water phase This RGB might be interesting for a radar and cloud seeding project

26 Severe convection Information on: Squall line with Dust

27 Divergence Product Very Recent Product: Severity of individual cells can be assessed Might be interesting for a radar and cloud seeding project

28 Air Mass Dynamics Merge of Water Vapour absorption and IR window channels

29 Air Mass Dynamics Rapid developing storm 7-8 Jan 2005 MSG RGB: 05-06, 08-09, 05

30 Volcano monitoring Volcano monitoring

31 Volcano monitoring Unexpected applications Watchdog function of the 3.9 ųm Channel for hot spots Watchdog for eruptions and SO2 emissions Unique set of sensors on board MSG : 1,6-3,9-8,7 ųm not available on another geo satellite Information from these channels might be relevant for cloud seeding!!!!!!!

32 The Karthala Eruption seen in MSG Imagery SO2 Thin Cirrus Ash plume

33 Volcano monitoring The next Karthala Eruption Sc field RGB :IR12.0-IR10.8, IR10.8-IR8.7, IR10.8 Light green indicates the SO2 emission, which started on 29 May 2006 No ash emitted

34 CHANNEL 8.7 μm Ash and SO2 Fine volcanic ash particle (Image from A.M. Sarna-Wojcicki)

35 CHANNEL 8.7 μm Ash and SO Metastable silica glass SO 2 Emissivity University of Hawaii Paul G. Lucey μm 10.8 μm 8.7 μm reduced emissivity for SO2 and silicates in volcanic ash Wavelength (microns)

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47 Summary Several products might be useful for radar and cloud seeding project proposals Including: RGB products Data from the archive (free of charge) Instability products Training assistance Software tools, Note the unique set of sensors on board MSG : 1,6-3,9-8,7 ųm together

48 Please visit us at : ops@eumetsat.int or ask more information at Thank you for your kind attention