Mineral desert dust: Comparison. between Tel-Aviv University dust forecasts and PM10 data. 3-rd Year Lab course.

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1 3-rd Year Lab course Mineral desert dust: Comparison between Tel-Aviv University dust forecasts and PM10 data Pavel Kishcha Tel-Aviv University

2 The Objectives of the Lab The main goal is to evaluate TAU 24-hour dust forecasts by using Israel PM10 data. This will help to better understand the model s capabilities for providing reliable dust forecasts. PM10 measurements taken at the Tel-Aviv University site (Yad Avner Building, 32.1N, 34.8E) will be used for model evaluation; To distinguish between different routes of Saharan dust transport into Israel by using the on-line archive of dust forecasts: from the eastern part of the Sahara, through Egypt, into Israel; or from the western part of the Sahara, through Southern Europe, into the Eastern Mediterranean and Israel; To estimate seasonal variations and the long-term tendency of desert dust events over Tel-Aviv, by using PM10 data.

3 Lab Course Realization 1. Download daily PM10 data from March 30, 1999, to the present taken at the Tel-Aviv site (Yad Avner Building) Obtain seasonal variations of desert dust by analyzing monthly numbers of days with PM µg/m Obtain year-to-year variations of annual numbers of days with PM µg/m 3 and their linear fit, which illustrates the long-term tendency of desert dust over Tel-Aviv. 4. Select some examples of different routes of desert dust intrusions into Israel, by using the on-line archive of TAU dust forecasts: 5. Compare model-predicted surface dust concentrations with PM10 data taken at the Tel-Aviv University site for two dust events in Israel, February 23 26, 2007, and March 10 14, Compare model-predicted surface dust concentrations for all consecutive days from February to April 2006 with corresponding PM10 data and estimate their correlation.

4 Geographical distribution of arid regions Sahara The Sahara is the world s most important dust source; it is responsible for up to half of the global mineral dust emissions.

The dust storm over North Africa on February 23, 2006.

5 The dust storm over North Africa on February 23, The Moderate Resolution Imaging Spectroradiometer (MODIS) flying onboard the NASA Aqua satellite took this image.

6 The dust intrusion into the Atlantic Ocean on September 29, The MODIS image from the NASA Aqua satellite is used.

quantities as to dirty everything on board, and to hurt people s eyes; vessels even have

It has often fallen on ships when several hundred, and even more than a thousand miles

7 The Voyage of H.M.S. Beagle Around the World ( ) The Beagle Charles Darwin The dust falls in such quantities as to dirty everything on board, and to hurt people s eyes; vessels even have run on shore owing to the obscurity of the atmosphere. It has often fallen on ships when several hundred, and even more than a thousand miles from the coast of Africa. In some dust which was collected on a vessel, I was much surprised to find particles of stone above the thousandth of an inch square, mixed with finer matter [Charles Darwin, 1831].

8 Interface of the on-line data base of the Israeli Ministry of Environmental Protection

9 Ministry of Environment Download Page

10 Ministry of Environment Download Page

11 The long-term tendency of dust events over Israel ( ) as inferred from year-to-year variations of annual numbers of dusty days with PM10 greater than 100 µg/m Number of days Years PM10 measurements at the Tel-Aviv University s campus (Yad Avner Building) were used

12 Averaged seasonal variations of dust events over Israel ( ) as inferred from monthly numbers of dusty days with PM10 greater than 100 µg/m Number of days Month PM10 measurements at the Tel-Aviv University s campus (Yad Avner Building) were used

13 Diagram of the DREAM-8 dust prediction system. Global meteorological data from the National Centre of Environmental Prediction (NCEP) 8 particle size bins dust production Horizontal and vertical advection Dry/wet deposition Numerical weather forecast model (Eta) Previous dust forecast DREAM-8 is based on the NCEP Eta model; A detailed set of 8 particle size classes with effective size between 1 and 8 microns (0.15, 0.25, 0.45, 0.78, 1.3, 2.2, 3.8, and 7.1µm) was used; Simulates all major processes of atmospheric dust cycle; Dust production scheme with introduced viscous sub-layer (Shao, 1993; Janjic, 1994); Dry (Georgi, 1986) and wet deposition processes are included. OUTPUT

14 Mean atmospheric lifetime for the eight size classes of mineral dust aerosols between 0.1 and 10 µm based on model results by Tegen and Lacis (JGR, 1996) Effective size, µm Lifetime, hours The new DREAM-8 model was capable of taking into account most of long-lived dust aerosols, in contrast to the old DREAM model.

Tel-Aviv University desert dust forecasts are available via the Internet. http://wind.tau.ac.il/dust8/yymmdd/dust.html where YY stands for year, MM for month, and DD for day.

15 Tel-Aviv University desert dust forecasts are available via the Internet. where YY stands for year, MM for month, and DD for day. For example, to get the model-predicted dust transport on March 13, 2006, one can use the following link to the forecast of March 12, 2006 (the previous date):

16 Surface dust concentrations in the ascii format in Tel- Aviv are available by using the following link: Here is some explanation of those files: Within each file you will see 13 numbers of predicted surface dust concentrations (X1, X2,, X13) started from 12:00 UTC of the forecast day for consecutive intervals of 6 hours up to 72 hours ahead. # UTC Forecast Model time data [microgram/m^3] 1 12:00 0 X1 2 18:00 6 X2 3 24:00 12 X3 4 06:00 18 X4 5 12:00 24 X5 6 18:00 30 X6 7 24:00 36 X7 8 06:00 42 X8 9 12:00 48 X :00 54 X :00 60 X :00 66 X :00 72 X13

17 The model-predicted surface dust concentrations based on the model forecast of March 12, ramat-aviv-ascii.dat 2.721e e e e e e e e e e e e e+01 PM10 data taken at the Tel-Aviv University site on March 13, 2006: יד אבנר - רמת אביב חלקיקים נשימים (PM10) שעה תאריך מיקרוגרם/מטר קוב 13/03/ :00: /03/ :00: /03/ :00: /03/ :00:

18 Comparisons between PM10 data in Tel-Aviv and 24-h modelpredicted data from March 11-15, PM10 dust forecast Concentration, ug/m^3 11/03/ :00 11/03/ :00 12/03/ :00 12/03/ :00 13/03/ :00 13/03/ :00 14/03/ :00 14/03/ :00 15/03/ :00 15/03/ :00

Typical dust transport into Israel in spring (March 13, 2006): from the Sahara, through Egypt, into Israel SeaWIFS satellite data 700 600 500 400

300 200 100 0 Aviv and 24-h model-predicted data show that the TAU dust system produces dust forecast of acceptable accuracy.

19 Typical dust transport into Israel in spring (March 13, 2006): from the Sahara, through Egypt, into Israel SeaWIFS satellite data Concentration, ug/m^ PM10 DREAM Comparisons between PM10 data in Tel- TAU fcst DREAM orig 500 Concentration, ug/m^ Aviv and 24-h model-predicted data show that the TAU dust system produces dust forecast of acceptable accuracy. 11/03/ :00 11/03/ : : :00 13/03/ :00 13/03/ :00 14/03/ :00 14/03/ :00 15/03/ :00 15/03/ :00

Long-distance dust transport from the Western Sahara, through Southern Europe, into the Eastern Mediterranean between 4-9 April, 2006 250 200 150 100 50 0 250 Concentration, ug/m^3 Concentration,

20 Long-distance dust transport from the Western Sahara, through Southern Europe, into the Eastern Mediterranean between 4-9 April, Concentration, ug/m^3 Concentration, ug/m^3 PM10 Comparisons between PM10 data in Tel-Aviv and 24-h model-predicted data DREAM-8 DREAM orig /04/ :00 07/04/ :00 08/04/ :00 08/04/ :00 09/04/ :00 09/04/ :00 10/04/ :00 10/04/ :00

21 Dust transport from Saudi Arabia into Israel on March 17, MODIS satellite data The DREAM-8 dust forecast Tel-Aviv University Weather Research Center (TAU WeRC)

22 Comparisons between 24-h DREAM-predicted dust concentration and PM10 data at Tel-Aviv in March March /03/ :00 02/03/ :00 04/03/ :00 06/03/ :00 07/03/ :00 09/03/ :00 10/03/ :00 11/03/ :00 14/03/ :00 15/03/ :00 18/03/ :00 20/03/ :00 21/03/ :00 22/03/ :00 24/03/ :00 25/03/ :00 26/03/ :00 28/03/ :00 29/03/ :00 30/03/ :00 31/03/ :00 Dust concentration, ug/m^3 Dust concentration, ug/m^3 Correlation: R (DREAM-8) = 0.76; R (DREAM orig) = PM10 DREAM-8 DREAM orig.

23 The lab course realization 1. Download daily PM10 data taken at the Tel-Aviv site (Yad Avner Building) from March 30, 1999, to the present Obtain seasonal variations of desert dust by analyzing monthly numbers of days with PM µg/m Obtain year-to-year variations of annual numbers of days with PM µg/m 3 and their linear fit, which illustrates a long-term tendency of desert dust over Tel-Aviv. 4. Determine some examples of different routes of desert dust intrusions into Israel, by using the on-line archive of TAU dust forecasts: 5. Compare model-predicted surface dust concentrations with PM10 data taken at the Tel-Aviv University site for two dust events in Israel, February 23 26, 2007, and March 10 14, Compare model-predicted surface dust concentrations for all consecutive days from February to April 2006 with corresponding PM10 data and estimate a correlation coefficient.

24 Report A report includes five Excel work sheets with the following five figures and their data: Fig. 1. Seasonal variations of desert dust over Tel-Aviv based on monthly numbers of days with PM µg/m 3. Fig. 2. The long-term tendency of desert dust over Tel-Aviv based on annual numbers of days with PM µg/m 3. Fig. 3 and 4. Comparisons between model-predicted surface dust concentrations and PM10 data taken at the Tel-Aviv University site for two dust events, February 23 26, 2007, and March 10 14, Fig. 5. Comparison between model-predicted surface dust concentrations and PM10 data taken at the Tel-Aviv University site for all consecutive days from February to April 2006.

Mineral desert dust: Comparison. between Tel-Aviv University dust forecasts and PM10 data. 3-rd Year Lab course.

3-rd Year Lab course Mineral desert dust: Comparison between Tel-Aviv University dust forecasts and PM10 data Pavel Kishcha Tel-Aviv University email: pavelk@post.tau.ac.il The Objectives of the Lab The