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Simulating Mars

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Simulating Mars 5 Dipartimento di Matematica e Fisica “E. De Giorgi” Dottorato in Fisica e Nanoscienze 10 XXXII CYCLE PHD THESIS (SSD: FIS/05) SIMULATING MARS: 15 GENERAL CIRCULATION MODELS AND SURFACE REFLECTIVITY MAPS 20 Supervisors: Prof. Giorgio DE NUNZIO Prof. Vincenzo OROFINO 25 Prof. Giovanni ALOISIO PhD Student: Alessandro De Lorenzis 30 35 40 45 50 55 2 60 65 To my parents 70 75 80 85 3 CONTENTS INTRODUCTION 7 CHAPTER 1 PRESENT MARS CLIMATE CONDITIONS: LANDERS/ROVERS 90 OBSERVATIONS 9 1.1 Exploring Mars 10 1.2 Landing site climate situations 12 1.3 Viking 1 and Viking 2 12 1.4 Mars Pathfinder 14 95 1.5 Spirit and Opportunity (MER rovers) 15 1.6 Phoenix 17 1.7 Curiosity 18 1.8 InSight 20 CHAPTER 2 REPRODUCING MARS CLIMATE: SOFTWARE SIMULATORS 100 AND GENERAL CIRCULATION MODELS (GCMs) 23 2.1 An excursus on the GCMs applied to simulate present Mars climate conditions 24 2.2 Simulation of the ancient Mars climate: a challenging task 27 2.3 General description of the two GCMs compared 28 105 2.4 GCM-LMD 30 2.5 MarsCAM-NCAR 31 2.6 The MCD database derived from GCM-LMD 32 2.7 MarsCAM-NCAR simulations on the CMCC Athena cluster 33 CHAPTER 3 LANDERS/ROVERS DATA AND GCMs OUTPUT MANIPULATION 34 110 3.1 Scenarios/Runs considered for the comparison 35 3.2 Set of the initial physical parameters used in the simulations 37 3.3 Initial computational settings used to perform simulations 38 3.4 Changing albedo, thermal inertia and dust OD: impact on surface and 115 near-surface temperatures 39 3.5 Data collection: observational and GCMs output data 41 3.5.1 Landers/rovers observations 41 3.5.2 Keeping time on Mars 44 3.5.3 GCMs output 45 120 3.6 Managing of observational data: preparing lander/rover measurements for the comparisons 45 3.7 Managing of MarsCAM-NCAR output: CMCC Ophidia tool 47 3.7.1 Working with Ophidia terminal 51 3.7.2 An example of an Ophidia WF to process GCMs output 53 125 3.8 Import of NetCDF files into Matlab 54 4 CHAPTER 4 TG AND TSA COMPARISONS: SEASONAL/ANNUAL TRENDS (GROUP 1) AND DIURNAL CYCLE (GROUP 2) 57 130 4.1 Comparisons: Group 1, seasonal and annual trends 58 4.2 Group 1 58 4.3 Comparisons criteria 64 4.4 Modified Borda-Count (MBC) method 66 135 4.5 An example of the MBC for Group 1a and Group 1b 68 4.6 Exceptions for Group 1 analysis 71 4.7 Comparisons: Group 2, daily trends 71 4.7.1 Group 2: features 72 4.7.2 Diurnal data processing 76 4.7.3 Statistical approaches applied for Group 2 77 140 4.7.4 Cross-checks performed for Group 2 77 CHAPTER 5 RESULTS OF THE COMPARISONS BETWEEN GCM-LMD AND MARSCAM-NCAR OUTPUT WITH TG/TSA OBSERVATIONAL DATA 79 145 5.1 Discussion of the results obtained 80 5.2 Group 1 results 80 5.2.1 Evidences for Group 1a 80 5.2.2 Evidences for Group 1b 83 5.3 Group 2 results 86 150 5.3.1 Evidences for Group 2a 86 5.3.2 Evidences for Group 2b 89 5.4 Discussion 92 CHAPTER 6 REPRODUCTION OF OTHER CLIMATIC VARIABLES WITH GCMs 95 155 6.1 MarsCAM-NCAR output: further analyses 96 6.2 Running MarsCAM-NCAR with different spatial resolutions 96 6.3 Comparisons with 1-D model output 101 6.4 Surface pressure 102 160 6.5 Air temperature profiles and sub-surface temperatures 107 CHAPTER 7 GLOBAL REFLECTIVITY MAPS OF MARS BY MEANS OF THE MARSIS SIMULATOR 112 165 7.1 Research stay at INAF (Bologna) 113 7.2 The discover of liquid water on Mars 113 7.3 The radar equation 122 7.4 The MARSIS radar: description and data features 124 7.5 Simulating radar echoes: the MARSIS simulator 126 5 170 7.6 Installation of the MARSIS simulator on the CMCC Athena cluster 129 7.7 Reflectivity maps 131 7.7.1 Physical parameters 131 7.7.2 Mars global reflectivity maps 133 7.8 Discussion of the results obtained 134 175 CONCLUSIONS 139 BIBLIOGRAPHY 145 Appendix A 158 Appendix B 161 Appendix C 167 180 Appendix D 176 Appendix E 183 Appendix F 185 Appendix G 191 Appendix H 204 185 190 195 200 6 INTRODUCTION 205 During the last decades, Mars was visited by many spacecrafts in order to learn more about the composition of its surface and its atmosphere. The goals of each mission were multiple, covering different fields of research (astronomy, chemistry, physics, astrobiology, geology, space engineering, climatology), all to be considered simultaneously in order to reveal the secrets of the Red Planet. One of the main targets of all the principal national and international space agencies is 210 to plan, in the next future, a human exploration able to land on the planet: in order to achieve this ambitious result, it is fundamental to know as much as possible about the present climate of Mars. The chance to perform in situ experiments, already “robotically” performed by some of the landers/ rovers that visited Mars, could be also a turning point to verify the hypothesis according to which Mars in the past could have host conditions to support life. The indications are multiple: the 215 detection of methane in the atmosphere of the planet (Krasnopolsky et al., 2004; Formisano et al., 2004; Mumma et al., 2009; Webster et al., 2015; Giuranna et al., 2019; discussion about the biological provenience of this gas: Atreya et al., 2007; Yung et al., 2018); the numerous geological evidences of the activity of liquid water on the surface of the ancient Mars, in the form of rivers, lakes and maybe oceans (Howard et al., 2005; Irwin et al., 2005; Fasset and Head, 2008; Di Achille 220 and Hynek, 2010; Matsubara et al., 2013); the recent discovery of a lake of salty liquid water in the southern polar cap of Mars (Orosei et al., 2018). My PhD research activity was mainly focused on the reproduction of present climate situations of Mars by means of numerical simulations, performed with 3-D General Circulation Models 225 (hereinafter, GCMs), in order to analyze the space/time distribution of atmospheric and surface variables. The main topics can be summarized as follows: • installation and configuration of the MarsCAM-NCAR GCM on the Athena cluster of the “Centro Euro-Mediterraneo sui Cambiamenti Climatici” (CMCC) and optimization of the big-data managing CMCC Ophidia tool used for the first time to manipulate output data 230 referred to Mars; • study of the present Mars climate conditions with the MarsCAM-NCAR software by comparing climatic variables with landers/rovers observations; • installation of the Martian Climate Database (MCD) derived from GCM-LMD (Laboratoire de Météorologie Dynamique), validation with spacecraft measurements and comparisons 235 with MarsCAM-NCAR output; • porting of the MARSIS simulator to the Athena cluster (CMCC). Simulation of the echoes expected for some orbits and comparison with the radargrams obtained from MARSIS radar, in search for the presence of subsurface liquid water; • production of simulated surface reflectivity maps and testing with similar maps based on 240 observational data in order to identify the variations of the dielectric constant on the Martian surface. All the demanding computational tasks I performed were achieved thanks to the scientific affiliation I signed with the Advanced Scientific Computing (ASC) Division of the CMCC Foundation, unit of Lecce, covering all the 3 years of my PhD: Prot. n. 1659/CMCC/2016 for 2016/2017; Prot n. 245 268/CMCC/2018 for 2018; Prot. n. 020/CMCC/2018 for 2019. 7 The PhD thesis is structured as follows. In Chapter 1 a global description of the climate conditions of the eight lander/rover landing sites considered in this work is presented, together with the most important features of the missions. 250 Chapter 2 is dedicated to a brief historical excursus on the GCMs introduced in the literature to perform simulations able to reproduce present and past climate conditions of Mars. The two GCMs compared, GCM-LMD and MarsCAM-NCAR, are also introduced. A discussion on the most important features of the two climatic models is presented, together with some technical operations performed to install the MCD database (created by the developers starting from GCM-LMD 255 simulations) and the MarsCAM-NCAR program on the CMCC Athena cluster. In Chapter 3 a deep discussion on the initial physical parameters used by the two GCMs is provided, as well as the explanation of the features of the simulations performed with them and used in the comparing analysis. Moreover, the list of the available observational data compared (surface and near-surface temperatures), collected by the eight probes and considered as reference 260 values for the comparisons, is reported. Also model output features are presented, together with a discussion on how time is marked for Mars. The preliminary managing of both observational and model output data is described, with the procedures necessary for realizing comparisons as homogeneous as possible. In this occasion, the tool applied to manipulate MarsCAM-NCAR output, CMCC Ophidia terminal, is presented. 265 Chapter 4 introduces the two sets of tests performed on model output: Group 1, related to seasonal and annual trends, and Group 2, related to diurnal trend evolution. The statistical approaches used for the comparisons (Modified Borda Count method, Root Mean Square Error (RMSE), Chebyshev distance, Mean Signed Deviation and maximum and minimum residual, with sign) are also shown. 270 In Chapter 5 a detailed list of the findings obtained is reported, both from a global (i.e.
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