Interactions Between North African Vegetation and the African Easterly Jet: a Mechanism for Abrupt Climate Change
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INTERACTIONS BETWEEN NORTH AFRICAN VEGETATION AND THE AFRICAN EASTERLY JET: A MECHANISM FOR ABRUPT CLIMATE CHANGE A Thesis Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Master of Science by Christina Marie Patricola January 2007 © 2007 Christina Marie Patricola ABSTRACT Modeling studies and paleoclimate evidence of the mid-Holocene, 6,000 years ago, indicate that the potential for rapid climate change exists over northern Africa. A regional climate model that produces an excellent representation of today’s climate over northern Africa is used to simulate the summer climate under present day solar forcing and SSTs and several prescribed static idealized zonal vegetation distributions. The purpose is to isolate and understand the role of interactions between vegetation and the dynamics of the West African summer monsoon in generating rapid climate change. Simulations with prescribed and interactive vegetation distributions are analyzed. In simulations with prescribed idealized vegetation, the regional model simulates only small differences in precipitation when the southern desert border is located between 10.0°N and 17.9°N. However, when the desert border is moved only 180 km, from 17.9°N to 19.4°N, summer precipitation increases by a factor of 5 over the Sahara, and the zonal structure observed in the present day climate is eliminated. These precipitation anomalies are associated with a 50% reduction in the magnitude of the African easterly jet, a 20% increase in the magnitude of the low-level westerly jet and a deepening and moistening of the thermal low. The model suggests that when the southern desert border is located north of a threshold latitude, the positive soil moisture anomalies beneath the region of maximum vertical velocity associated with the thermal low support positive low-level moist static energy anomalies, which are indicative of strengthened convection. Asynchronous coupling with a simple vegetation model reveals that when the initial desert border is located at 20.9°N, a new equilibrium vegetation distribution results in which the central Sahara is vegetated, indicating that the interactions between vegetation and the atmosphere may produce rapid climate change. When the initial desert border is located at 10.0°N, the equilibrium vegetation distribution closely resembles that of the present day, suggesting that the atmospheric conditions may allow regrowth of vegetation in a deforestation scenario under present day solar and SST forcings. BIOGRAPHICAL SKETCH Christina Marie Patricola was born Christina Marie DiRosario on February 14th 1983 and was raised in Franklin, Massachusetts. She developed an interest in the atmosphere by the age of five, and pursued this interest as a volunteer weather watcher for WCVB TV – Boston during her teens. Christina also enjoys playing softball and guitar, drawing cartoons, painting, artistic expression with bright colors, candlepin bowling, and reciting scenes from comedies with Jennifer and Matthew, her sister and brother. After graduating from Franklin High School in June 2001, she attended Cornell University where she received a BS in geological sciences with a concentration in atmospheric science in May 2005. Having already begun researching as an undergraduate under Dr. Kerry Cook, and captivated by the Northeast, she accepted the opportunity to continue at Cornell for graduate work. iii This thesis is dedicated to: Mom and Dad, and Grandma and Grandpa, for all their love and encouragement. Jennifer and Matthew, my partners in mischief and laughter. (“Heeeere, Snowflake…”) My whole family who, even when the Ithaca winter was at its coldest and windiest and I hadn’t seen the sun for days, can always cheer me up with a call during which the phone was passed along to all the relatives, Scotty too. StormTeam1102, who actually made it fun to find all those misprints in the frontogenesis equation and who got as much amusement as I did out of making a script pi pie. You nerds. All my friends I have met along the way, you are too many to list, but you all have a special place in my heart. My teachers, from Kindergarten to present, who have taught me so much. All scientists, who work so hard for the world and are a great inspiration. iv ACKNOWLEDGMENTS I thank my committee members, Kerry H. Cook, Stephen J. Colucci, and Bryan L. Isacks, for all of their time and effort spent helping me to improve the thesis. I would like to express my gratitude and respect to my advisor, Kerry Cook. I thank her for the great learning opportunity she has provided by advising me as both an undergraduate and graduate student, for her strong motivation, energy, enthusiasm, understanding, humor, and for all that I have learned from her. I also express my gratitude and respect for Stephen Colucci, for his strong commitment to teaching and for helping his students grow by setting high standards. I thank Edward Vizy for his dedication to the research group and for all the time he selflessly spent teaching me how to run the regional climate model. Thanks to Steve Gallow for all his hard work in maintaining the computer systems. I also thank the instructors I have had at Cornell - Kerry Cook, Stephen Colucci, Peter Gierasch, Mark Wysocki, Art DeGaetano, and Dan Wilks, for teaching enthusiastically and providing me with a strong base in atmospheric science. I also thank Mark Wysocki for inspiring my interest in teaching. Thanks to my office mates and fellow graduate students for many engaging discussions and to all the members of the department for their support. I am very grateful to NSF Award ATM – 0145481 and the Cornell Graduate Fellowship for providing funding for this research. v TABLE OF CONTENTS Biographical Sketch………………………………...…………………………iii Dedication……………………………………………………….…….………iv Acknowledgements………………………………………………..…...….…...v Table of Contents……………………………………………………………...vi List of Figures………………………………………………………………...vii List of Tables……………………………………………………………….....ix List of Abbreviations……………………………..……………………………x Introduction .…………………………………………………………………...1 Background ……………………………………………………………………3 Model description, simulation design, and model validation ...……………….7 Results ………………………………………………………………………..18 Conclusions…………………………………………………………………...41 References ……………………………………………………………………45 vi LIST OF FIGURES Figure 1. Landuse on the simulation domain for the present day according to the 24 category USGS dataset…………………………………………………………………8 Figure 2. Prescribed vegetation for the idealized simulations……………………….10 Figure 3. JJAS averaged zonal wind (m/s) along 12.5°W for the (a) NCEP reanalysis and (b) present day simulation……….……………………………………………….14 Figure 4. Precipitation (mm/day) for the (a) CRU and CMAP data set and (b) RCM simulation averaged June-July, and for the (c) CRU and CMAP data set and (d) RCM simulation averaged August-September..…………………………………………….16 Figure 5. (a) Summer averaged maximum wind speed (m/s) and (b) percent change in summer averaged maximum wind speed from present day for the idealized simulations for the southerly winds from the Gulf of Guinea the African Easterly Jet, and the low- level westerly winds…………………………………………………………………..19 Figure 6. Summer averaged precipitation anomalies (mm/day) from present day for the idealized simulations………………………...……………………………………22 Figure 7. Percent change in summer averaged precipitation from present day for the idealized simulations for the Guinean Coast region, the Sahel, and the Sahara……...24 Figure 8. Summer averaged meridional temperature gradient taken along 15°W for the idealized simulations……………………………………………………………...26 Figure 9. Summer averaged vertical velocity (mm/s) and specific humidity (10-3 kg H2O/kg air) anomalies from present day along the prime meridian for the idealized simulations………………………………………………………………………...….28 Figure 10. Summer averaged geopotential height (gpm) and winds (m/s) vectors at 910 hPa for the idealized simulations………………………………..……………….29 Figure 11. Summer averaged geopotential height (gpm) and wind vectors (m/s) at 825 hPa for the idealized simulations……………………………………………………..31 Figure 12. Summer averaged geopotential height (gpm) and wind vectors (m/s) at 625 hPa for the idealized simulations………………………….………………………….32 Figure 13. The JJAS (a) total MSE, temperature term, geopotential energy, and moisture term for the present day simulation, (b) total MSE (c) temperature anomaly vii from present day and (d) moisture anomaly from present day for idealized averaged over 17-20˚N and 8-12˚E. Units are 104 m2 s-2.……………………………………..37 Figure 14. Landuse prescribed for the iterations (a) des20.9_2, (b) des20.9_3, (c) des20.9_4, (d) des10.0_2, (e) des10.0_3, (f) des10.0_4, (g) des10.0_5, and (h) des10.0_6.………………………………………………………………………….…40 viii LIST OF TABLES Table 1. Land-use changes from present day for the idealized RCM simulations…..11 Table 2. USGS vegetation and physical properties for summer……………………..11 ix LIST OF ABBREVIATIONS AEJ.…………………………………………………………………African easterly jet AHP.……………………………………………………………..African Humid Period AGCM….………………………………………atmospheric general circulation model CMAP…………………...Climate Prediction Center Merged Analysis of Precipitation COLA……………………………………………..Center for Ocean-Land-Atmosphere CRU.…………………………………………………………….Climate Research Unit GCM………………………………………………………….general circulation model gpm…………………………………………………………………geopotential meters hPa………………………………………………...………………….……hectopascals JJAS………………………………………………...……….…June