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The Intertropical Convergence Zone Over the Middle East and North Africa: Detection and Trends

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The Intertropical Convergence Zone Over the Middle East and North Africa: Detection and Trends The Intertropical Convergence Zone over the Middle East and North Africa: Detection and Trends Thesis by Anna Ailene Scott In Partial Fulllment of the Requirements For the Degree of Masters of Science King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia The thesis of Anna Ailene Scott is approved by the examination committee Committee Chairperson: Georgiy Stenchikov Committee Member: Matthew McCabe Committee Member: Stoitchko Kalenderski 2 Copyright c 2013 Anna Ailene Scott All Rights Reserved 3 ABSTRACT The Intertropical Convergence Zone over the Middle East and North Africa: Detection and Trends Anna Ailene Scott This thesis provides an overview of identifying the Intertropical Convergence Zone (ITCZ) in the Middle East and North Africa (MENA) region. The ITCZ is a zone of wind convergence around the equator that coincides with an area of intense precipitation that is commonly termed a tropical rainbelt. In Africa, these two concepts are frequently confounded. This work studies the correlation between precipitation and commonly used ITCZ indicators. A further attempt is made to detect movement in the African ITCZ, based on earlier paleontological studies showing historical changes in precipitation. Zonally averaged wind convergence is found to be the most reliable indicator of the African ITCZ, one having a low correlation with zonally averaged precipitation. Precipitation is found only to be a reliable indicator for the African ITCZ in zones near the wind convergence, which reaches as far north as 20◦N in the summer. No secular change in location of the African ITCZ is found for the time of available data. Finally, historical data shows that any increase in precipitation in the Sahel, a region where precipitation is driven by the ITCZ, is mildly negatively correlated with precipitation in the rainbelt area, suggesting that shifts in the ITCZ result in a widening of the precipitation prole as well as a shift of the entire zone. 4 ACKNOWLEDGEMENTS I would like to extend a special thanks to Prof. Stenchikov for his help and support with this research, as well as to my committee members for generously donating their time. I would also like to thank my friends, classmates and colleagues, whose help and technical support was invaluable these past months at KAUST. 5 Contents Examination Committee Approval 2 Copyright 3 Abstract 4 Acknowledgements 5 1 Introduction 10 2 Background on data sources 14 2.1 Reanalysis Data . 15 2.1.1 ERA-Interim . 15 2.2 Observation Data . 16 2.2.1 TRMM . 16 2.2.2 LIS-OTD . 18 2.3 Historical Data . 18 2.3.1 Nicholson's Dataset . 18 3 ITCZ identication methods 20 3.1 Introduction . 20 3.2 Identication methods . 21 3.2.1 Wind . 21 3.2.1.1 Surface wind patterns . 21 3.2.1.2 Zonally averaged meridional wind . 21 3.2.2 Rainfall . 24 3.2.3 Lightning . 27 3.2.4 Convergence . 29 3.3 Relationship between convergence, wind and precipitation . 31 3.4 Conclusions . 42 4 ITCZ shift 43 4.1 From historical data . 43 4.2 ERA-Interim . 46 4.3 Conclusions . 49 6 5 Conclusions 51 Bibliography 52 7 List of Figures 1.1 Greening of the Sahel from (author?) [13]. The results of trend analyses of time series of NDVI amplitude (top) and NDVI seasonal integral (bottom) of NOAA AVHRR NDVI-data from 1982 to 1999. Areas with trends of <95% probability in white. Data from 40 climate observation stations, showing percent change between the periods 19821990 and 19911999, have been superimposed on the top gure. 13 2.1 ERA-Interim RMS forecast errors for (a) tropical wind vectors and (b) temperatures at 200 hPa, averaged over all forecasts issued daily at noon UTC in 1989, for ERA- Interim (red), ERA-40 (blue), and for ECMWF forecasting system (green). Forecast errors are relative to a xed set of radiosonde observations. (c,d) are as (a,b) but for 850 hPa. From (author?) [3]. 15 2.2 Number of observations assimilated into ERA-Interim's atmospheric analysis compo- nent, daily, on a logarithmic scale. From (author?) [3] . 17 3.1 Low-level wind vectors in Africa for August (left), January (right). 900hPa (top), 950hPa (middle), 1000hPa (bottom) . 22 3.2 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the global tropics (left), tropics land (middle), and tropical oceans (right), for January (bold blue), April (green), July (bold red), Octo- ber (light blue), and annual average (black). Methodology follows that of (author?) [22]. ............................................ 23 3.3 Number of wet months in MENA since 1997 from TRMM monthly data. Wet months are dened as months having average precipitation rates of 0:01mm/hr or higher. 24 3.4 Histogram of rainfall rates over MENA during TRMM period, 1997-2011 . 25 3.5 Composite of rainfall rate time series from each grid point in MENA during TRMM period, 1997-2011 . 26 3.6 Linear trends in TRMM precipitation rates over TRMM period, 1997-2011 . 26 3.7 Lightning ash rate density full climatology, for 1997-2011, from LIS-OTD dataset. 27 3.8 Correlation between TRMM anomaly rainfall rate and LIS-OTD anomaly lightning ash rate . 28 3.9 Correlation between TRMM rainfall rate and LIS-OTD lightning ash rate . 29 3.10 Dierence in time-averaged lighting ash rate between rst half of TRMM period (1997-2004) and second half (2004-2011) . 30 8 3.11 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the Africa for January (bold blue), April (green), July (bold red), October (light blue), and annual average (black). 32 3.12 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for West Africa. Colors show the months: January (bold blue), April (green), July (bold red), October (light blue), and annual average (black). 33 3.13 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for East Africa. Colors show the months: January (bold blue), April (green), July (bold red), October (light blue), and annual average (black). 34 3.14 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the Ethiopian Highlands. Colors show the months: January (bold blue), April (green), July (bold red), October (light blue), and annual average (black). 36 3.15 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the Arabian Peninsula. Colors show the months: January (bold blue), April (green), July (bold red), October (light blue), and annual average (black). 37 3.16 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the Atlas Mountains. 38 3.17 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for Central Africa. 39 3.18 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the Western Sahel, north. 40 3.19 Zonally averaged proles of precipitation (rst row), meridional wind (second row), and divergence (third row) for the Western Sahel, south. 41 4.1 Interregional correlations for nineteenth century Africa. Point to point correlation of precipitation anomaly (time series of yearly data, 1800-1899) between starred region and other regions of Africa. Starred regions all belong to Sahel. 44 4.2 Interregional correlations for wet years in Africa. Point to point correlation of precip- itation anomaly (time series of yearly data, years when the starred region experiences ooding) between starred region and other regions of Africa. Starred regions all be- long to Sahel. 45 4.3 Time series of the ITCZ latitude on a submonthly scale, using zonally averaged con- vergence maximum and the zero crossing point of meridional wind data as indicators for ITCZ location. For tropical East Africa. 47 4.4 Time series of the ITCZ latitude on a submonthly scale, using zonally averaged con- vergence maximum and the zero crossing point of meridional wind data as indicators for ITCZ location in tropical West Africa. 47 4.5 Composite time series of African precipitation at each longitude point along 20◦N (ERA-Interim Data). Dierent colors represent dierent locations. 48 4.6 Composite time series of African precipitation at each longitude point along 20◦N (ERA-Interim Data). Dierent colors represent dierent locations. 48 9 Chapter 1 Introduction The Intertropical Convergence Zone, or ITCZ, marks the zone of tropical Hadley cell-related up- welling where northern and southern trade winds converge near the equator and rise, producing intense convection, clouds and rainfall. The Hadley cell circulation is a simple overturning convec- tion mechanism, driven by solar radiation. Solar radiation in the tropics warms air, which rises and spreads polewards before subsiding and then owing equator-wards again. As incoming solar radi- ation (insolation) is most intense in the tropics, the Hadley cells are centered around the equator, where the location of convergence and upwelling marks the ITCZ. While the Hadley cell circulation picture is an idealization, it is one that works well when speaking of a global zonal average. These features are even visible to the naked eye the ITCZ can be recognized qualitatively in satellite images as a thick band of clouds and storms that encircles the Earth. The phenomena is most apparent over the Pacic where the ITCZ is clearly dened. This denition can be lost over the land masses, particularly Africa. The ITCZ is certainly a key component of global atmospheric circulation, but its connection to tropical precipitation has more direct impact on human interests. The ITCZ includes the tropical rainbelt, a region of dense clouds, abundant storms, and frequent rain.
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