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Influences of Tropical Deep Convection on Upper Tropospheric

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Influences of Tropical Deep Convection on Upper Tropospheric Influences of Tropical Deep Convection on Upper Tropospheric Humidity A Thesis Presented to The Academic Faculty by Jonathon S. Wright In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy School of Earth and Atmospheric Sciences Georgia Institute of Technology August, 2006 Influences of Tropical Deep Convection on Upper Tropospheric Humidity Approved by: Professor Rong Fu, Adviser School of Earth & Atmospheric Sciences Georgia Institute of Technology Professor Robert Dickinson School of Earth & Atmospheric Sciences Georgia Institute of Technology Professor Athanasios Nenes School of Earth & Atmospheric Sciences School of Chemical & Biomolecular Engineering Georgia Institute of Technology Professor Andrew Dessler Department of Atmospheric Sciences Texas A&M University Date Approved: July 3, 2006 ACKNOWLEDGEMENTS I acknowledge the immeasurable contributions of Dr. Rong Fu to this study and to my graduate experience. I express appreciation for the Goddard Earth Science and Technology Center’s Graduate Student Summer Program, which supported the work that grew into this study. I also thank Dr. Andy Dessler for serving as my mentor in the aforementioned pro- gram and for productive dialogue since. I thank Drs. Andy Heymsfield and Walt Petersen for provision of and useful discussions regarding relationships between radar reflectivity and ice water content, Drs. Annmarie Eldering, Ed Olsen, and Eric Fetzer for clarifying aspects of the AIRS data, and Dr. Mark Schoeberl for providing assistance with the trajectory model. Finally, I thank Drs. Robert Dickinson, Thanos Nenes, and Andy Dessler for agree- ing to read this thesis. This work has been supported by a National Defense Science and Engineering Graduate Fellowship, a Georgia Institute of Technology President’s Fellowship, the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology, the NASA Global Energy and Water Cycle Program, and the NASA Terra and Aqua Project. iii TABLE OF CONTENTS ACKNOWLEDGEMENTS .............................. iii LIST OF TABLES ................................... vi LIST OF FIGURES .................................. vii LIST OF SYMBOLS OR ABBREVIATIONS .................. xi SUMMARY ........................................ xiii I INTRODUCTION ................................. 1 II DATA AND METHOD .............................. 9 2.1 Data . 9 2.1.1 Precipitation Radar . 9 2.1.2 Moderate Resolution Imaging Spectroradiometer . 12 2.1.3 Atmospheric Infrared Sounder . 12 2.1.4 Meteorological Data . 15 2.2 Trajectory Model . 15 2.2.1 Formulation . 16 2.2.2 Criteria and Application . 16 2.2.3 Advection-Condensation Model . 17 2.2.4 Imposed Temperature Perturbations . 18 2.3 Analysis Domains . 19 2.4 Statistical Treatment . 21 III A TRAJECTORY ANALYSIS OF THE EVOLUTION OF CONVEC- TIVE DETRAINMENT ............................. 24 3.1 Downstream Water Vapor in the Global Tropics . 24 3.1.1 Comparison of Detrainment Temperature and Ice Water Content . 24 3.1.2 Comparison of Detrainment Temperature and Ice Effective Radius 30 3.1.3 Coefficients of Determination . 34 3.2 Regional Variations . 35 iv IV THE ROLE OF AMBIENT RELATIVE HUMIDITY .......... 40 4.1 Water Vapor Changes With Trajectory Passage . 40 4.2 Impact of Ice . 47 4.3 Comparison with the Global Tropics . 50 4.4 Potential Applications . 52 V EVALUATION OF AN ADVECTION-CONDENSATION MODEL . 53 5.1 Comparison with Observations . 53 5.1.1 Detrainment Temperature . 56 5.1.2 Cloud Ice Parameters . 58 5.1.3 Sensitivity to Condensation Threshold . 60 5.2 Temperature Distribution . 61 5.2.1 Impact of Assimilating AIRS Temperatures . 61 5.2.2 Impact of Imposing Sub-Scale Temperature Fluctuations . 63 VI CONCLUSIONS AND FUTURE WORK .................. 65 APPENDIX A — RADIATIVE PROPERTIES OF UPPER TROPO- SPHERIC WATER VAPOR .......................... 74 APPENDIX B — VINCENTY’S FORMULAE ............... 79 REFERENCES ..................................... 82 v LIST OF TABLES 1 Definition and general classification of the thirteen tropical regions chosen for study. 22 2 Evolution of mean humidity in 10 K detrainment temperature bins . 26 3 Coefficient of determination between downstream water vapor and the des- ignated parameter. 34 vi LIST OF FIGURES 1 A schematic illustration of the water vapor feedback. 2 2 A schematic representation of the Hadley cell. Low and high surface pressures are marked with L and H, respectively, and differences in surface temperature are designated as warm (red) or cool (blue) by the color of the circulation path......................................... 4 3 A schematic representation of the equatorial Walker circulation. 5 4 A comparison of five methods for computing IWC from Ze. 11 5 Schematic illustration of the method used in this study. (a) Tropical deep convective events are identified and categorized; (b) the position is integrated forward in space and time using a trajectory model; and (c) the calculated positions are matched to observations of water vapor wherever possible. 16 6 Arbitrary temperature perturbation, such as might be imposed on a time series of trajectory temperature. 19 7 Frequency of TRMM PR 2A25 volumetric radar reflectivities greater then 20 dBZ and above an altitude of 10 km (filled contours) for (a) January 1-March 31 (JFM); (b) April 1-June 30 (AMJ); (c) July 1-September 30 (JAS); and (d) October 1-December 31, 2004 (OND). The 15◦S and 15◦N boundaries for the observation of deep convection are marked as dashed lines. Regions selected for further study are marked as solid boxes. See Table 1 for region definitions and further explanation. 20 8 Normalized number density of points that are connected to both TRMM via trajectory integration and AIRS via spatial and temporal matching during the first 24 hours following convection (See Subsection 2.2.2 for details). Grid values are normalized relative to the total number of trajectory points that are successfully matched to AIRS throughout this time period. 21 9 Composite means of AIRS water vapor observations matched to TRMM deep convection throughout the global tropics during (a) hours 0-6 following con- vection, (b) hours 6-12, (c) hours 12-18, and (d) hours 18-24. Observations are binned according to estimated detrainment temperature and IWC derived from TRMM PR radar reflectivity at the point of detrainment. 25 10 Seasonal composite means of AIRS water vapor observations matched to TRMM deep convection within 24 hours throughout the global tropics dur- ing (a) January-March, (b) April-June, (c) July-September, and (d) October- December. Observations are binned according to estimated detrainment tem- perature and IWC derived from TRMM PR radar reflectivity at the point of detrainment. 27 vii 11 Composite mean dehydration rate of AIRS water vapor matched to TRMM deep convection throughout the global tropics. Observations are binned ac- cording to estimated detrainment temperature and IWC derived from the TRMM PR radar reflectivity at the point of detrainment. Contours corre- sponding to dehydration rates of 1% and 2% per hour are plotted in solid gray and labeled. 29 12 Seasonal composite means of dehydration rate along the trajectory during (a) January-March, (b) April-June, (c) July-September, and (d) October- December. Observations are binned according to estimated detrainment tem- perature and IWC derived from TRMM PR radar reflectivity at the point of detrainment. Contours corresponding to dehydration rates of 1% and 2% per hour are plotted in solid gray and labeled. 30 13 As in Figure 9, but observations are binned according to estimated detrain- ment temperature and MODIS mean rei at the point of detrainment. 31 14 As in Figure 11, but observations are binned according to estimated detrain- ment temperature and MODIS mean rei at the point of detrainment. 32 15 As in Figure 10, but observations are binned according to estimated detrain- ment temperature and MODIS mean rei at the point of detrainment. 33 16 As in Figure 12, but observations are binned according to estimated detrain- ment temperature and MODIS mean rei at the point of detrainment. 34 17 Regional breakdown of relationships between regional convective frequency [events km−2 h−1] and mean downstream AIRS water vapor within 24 hours of convection for (a) January-March; (b) April-June; (c) July-September; and (d) October-December . 36 18 As in Figure 17, but for mean IWC in place of convective frequency. 37 19 As in Figure 17, but with MODIS mean ice cloud effective radius in place of convective frequency. 38 20 PDF of AIRS ambient RHi vs. change in AIRS mass mixing ratio along trajectories detraining from deep convection during January 2004 for the global tropics. 41 21 As in Figure 20, but for normalized changes in AIRS water vapor mass mixing ratio. 42 22 PDF for (a) detrainment from continental convection; (b) detrainment from oceanic convection. 43 23 PDF for (a) detrainment from continental convection; (b) detrainment from oceanic convection. 44 24 PDFs for trajectories originating with continental convection (filled contours) and oceanic convection (solid gray contours) detraining at (a) θdet < 340 K; (b) 340 K ≤ θdet < 345 K; (c) 345 K ≤ θdet < 350 K; (d) θdet ≥ 350 K. Gray contours are plotted at probabilities of 0.06%, 1%, 2%, and 3%. 44 viii 25 PDFs for trajectories originating with continental convection and detraining at (a) θ < 240 K; (b) 240 K ≤ θ < 245 K; (c) 245 K ≤ θ < 250 K; (d) θ ≥ 250 K. 45 26 As in Figure 20, but for lag time following convection of (a) 0-12 hours, (b) 12-18 hours, (c) 18-24 hours, and (d) 24-36 hours. 46 27 As in Figure 20, but for travel distances from convection of (a) 100-200 km, (b) 200-400 km, (c) 400-600 km, (d) greater then 600 km. 47 28 As in Figure 20, but for (a) IWC ≤ 2 g m−3; (b) 2 g m−3 < IWC ≤ 3 g m−3; (c) 3 g m−3 < IWC ≤ 4 g m−3; and (d) IWC > 4 g m−3 . 48 29 As in Figure 20, but for (a) rei ≤ 15 µm; (b) 15 µm < rei ≤ 25 µm; (c) 25 µm < rei ≤ 35 µm; and (d) rei > 35 µm...................
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