Surface Energy Budget, Albedo and Thermal Inertia at Jezero Crater, Mars, 2 as Observed from the Mars 2020 MEDA Instrument

Abstract 42 The Mars Environmental Dynamics Analyzer (MEDA) on board Perseverance includes first-of- 43 their-kind sensors measuring the incident and reflected solar flux, the downwelling atmospheric 44 IR flux, and the upwelling IR flux emitted by the surface. We use these measurements for the 45 first 350 sols of the Mars 2020 mission (Ls ~ 6°–174° in Martian Year 36) to determine the 46 surface radiative budget on Mars, and to calculate the broadband albedo (0.3–3 μm) as a function 47 of the illumination and viewing geometry. Together with MEDA measurements of ground 48 temperature, we calculate the thermal inertia for homogeneous terrains without the need for 49 numerical models. We found that: (1) the observed downwelling atmospheric IR flux is 50 significantly lower than model predictions. This is likely caused by the strong diurnal variation 51 in aerosol opacity measured by MEDA, which is not accounted for by numerical models. (2) The 52 albedo presents a marked non-Lambertian behavior, with lowest values near noon and highest 53 values corresponding to low phase angles (i.e., Sun behind the observer). (3) Thermal inertia 54 values ranged between 180 (sand dune) and 605 (bedrock-dominated material) SI units. (4) 55 Averages across Perseverance’ traverse of albedo and thermal inertia (spatial resolution of ~3–4 56 m2) are in very good agreement with collocated retrievals of thermal inertia from THEMIS 57 (spatial resolution of 100 m per pixel) and of bolometric albedo in the 0.25–2.9 m range from 58 (spatial resolution of ~300 km2). The results presented here are important to validate model 59 predictions and provide ground-truth to orbital measurements. 60 61 Plain Language Summary 62 We analyzed first-of-their-kind measurements from the weather station on board NASA’s 63 Perseverance rover. These include the incident solar radiation and the amount of it that is 64 reflected by the surface, as well as the thermal atmospheric forcing (greenhouse effect) and the 65 thermal heat released by the surface. These measurements comprise the radiant energy budget, 66 which is fundamental to understanding Mars’ weather through its impact on temperatures. From 67 the solar measurements, we obtained the surface reflectance for a variety of illuminating and 68 viewing geometries. We found that the thermal atmospheric forcing is weaker than expected 69 from models, likely because of the strong diurnal variation in atmospheric aerosols observed by 70 the rover, which is not accounted for by models. We also found that the surface reflectance is not 71 uniform from all directions, but that it decreases when the Sun is highest in the sky (near noon) 72 and increases when the Sun is directly behind the observer (sunset and sunrise), and thus the 73 shadows cast by their roughness elements (e.g., pores, pits) are minimized. Because models 74 neither consider diurnal variations in atmospheric aerosols nor in the surface reflectance, the 75 results presented here are important to validate model predictions for future human exploration. 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 manuscript submitted to replace this text with name of AGU journal Outline (to be removed if manuscript accepted for publication) 1. Introduction 2. The MEDA Instrument (Figs. 1-3; Table 1; Figs. S1 and S2) 3. Methodology 3.1. Surface Energy Budget 3.1.1. Shortwave Flux 3.1.1.1. Downwelling Solar Flux: RDS/TOP7 (ds01; ds02; Fig. S3) 3.1.1.2. Upwelling Flux Reflected by the Surface: TIRS/IR3 3.1.2. Longwave Flux 3.1.2.1. Downwelling Atmospheric Flux: TIRS/IR1(ds03) 3.1.2.2. Upwelling Flux Emitted by the Surface: TIRS/IR4 3.1.3. Turbulent and Latent Heat Flux 3.1.4. Net Heat Flux (Fig. 4; Fig. S4) 3.2. Albedo 3.3. Thermal Inertia (Fig. 5) 4. Results 4.1. Thermal Inertia (Figs. 6 and 7; Fig. S5) 4.2 Surface Energy Budget (Figs. 8 and 9) 4.2.1. Shortwave Flux (Fig. S6) 4.2.2. Longwave Flux (Figs. 10 and 11) 4.2.3. Turbulent Heat Flux (Fig. 12) 4.2.4. Net Heat Flux into the Ground (Fig. S7) 4.3. Albedo (Figs. 13 and 14; Figs. S8, S9 and S10) 5. Discussion: Atmospheric IR Flux (Fig. 15) 6. Summary and Conclusions manuscript submitted to replace this text with name of AGU journal 133 1. Introduction 134 The Mars 2020 Perseverance rover landed at Jezero Crater (77.5945°E, 18.3628°N, -2656 m) on 135 February 18, 2021, corresponding to a solar longitude (Ls) of ~5° in Martian Year (MY) 36. It 136 carries seven science instruments to fulfill four science goals: (1) understand the geology of the 137 landing site, (2) identify ancient habitable environments and look for preserved biosignatures, (3) 138 collect and document samples for future Earth return, and (4) enable future human exploration of 139 Mars (Farley et al., 2021). 140 141 Among these instruments, the Mars Environmental Monitoring Station (MEDA) is a 142 meteorological station selected by NASA to help achieve mission science goal 4 (Rodríguez- 143 Manfredi et al., 2021; Newman et al., 2022). In particular, the main programmatic objectives of 144 MEDA are to: (1) validate global atmospheric models by taking surface weather measurements, 145 and (2) characterize dust size and morphology to understand its effects on the operation of 146 surface assets and human health. Additionally, MEDA provides environmental context in 147 support of science goals 1–3 and the flights of Ingenuity, the helicopter included in the mission 148 as a technology demonstrator. 149 150 To achieve its objectives, MEDA carries six sensor packages: the Thermal Infrared Sensor 151 (TIRS; Pérez-Izquierdo et al., 2018; Sebastián et al., 2020, 2021), the Radiation and Dust Sensor 152 (RDS; Apéstigue et al., 2022), the Atmospheric Temperature Sensor (ATS), the Pressure Sensor 153 (PS), (5) the Relative Humidity Sensor (HS), and the Wind Sensor (WS). In addition, the RDS 154 incorporates an upward-viewing wide-angle camera to image the sky, informally called SkyCam. 155 Among these, TIRS and RDS are providing first-of-their-kind measurements from the surface of 156 Mars, and are the main the focus of this article. 157 158 RDS and TIRS allow the determination of the surface radiative budget on Mars for the first time 159 through measurements of the incident (SWd; 0.19–1.2 μm) and reflected (SWu; 0.3–3 μm) solar 160 flux, the downwelling atmospheric IR flux (LWd; 6.5–30 μm), and the upwelling IR flux emitted 161 by the surface (LWu; 6.5–30 μm). As required in quantifications of the radiative energy budget, 162 we explain in Section 3 how to extend these measurements to the entire shortwave (0.19–5 μm) 163 and longwave range (5–80 m). The surface radiative budget of Mars is fundamental to 164 understanding its weather and climate through its impact on the thermal structure and 165 atmospheric circulations (e.g., Creecy et al., 2022). Moreover, RDS and TIRS measurements are 166 critical to validate and improve predictive capabilities of numerical models. Therefore, 167 determination of the surface radiative budget is critical to achieve MEDA’s first programmatic 168 objective. Before Perseverance, this budget has been estimated using a combination of in-situ 169 measurements and numerical models (Martínez et al., 2021, and references therein). Here, we 170 expand and improve upon previous studies by analyzing in-situ measurements of the surface 171 radiative budget around the clock. 172 173 Together with the radiative fluxes, the turbulent heat flux (H0) and the latent heat flux (Lf) make 174 up the surface energy budget (SEB), which can be expressed as G = SWd – SWu + LWd – LWu – 175 H0 – Lf. Here, G represents the net heat flux into the ground, and Rn = SWd – SWu + LWd – LWu is 176 the net radiative flux derived from MEDA measurements (sign convention defined in Section 3). 177 Although not measured, H0 and Lf can be estimated using combined MEDA measurements from 178 TIRS, ATS, WS, PS, and HS using similarity theories (Section 3). These two terms play, at most, manuscript submitted to replace this text with name of AGU journal 179 a minor role in the Martian SEB (Sutton et al., 1978; Haberle et al., 1993; Martínez et al., 2014; 180 2021; Savijärvi et al., 2022, this issue). Therefore, MEDA provides a reasonable approximation 181 to the SEB at Jezero. 182 183 Another novel capability of MEDA is the direct determination of the broadband (0.3–3 μm) 184 albedo through measurements of the incident and reflected solar flux (see Section 3.2 for the 185 definition of albedo used in this article). Albedo is a key parameter in the radiative energy 186 budget, thus affecting the local weather and climate (Kahre et al., 2005; Fenton et al., 2007). In 187 previous surface-based missions, the albedo has been calculated either from radiometrically 188 calibrated images taken by panoramic cameras (Rice et al., 2018; Bell et al., 2008), or by using 189 numerical models to best fit observed values of ground temperature (Vasavada et al., 2017; 190 Piqueux et al., 2021). Additionally, telescope and satellite observations have been used to 191 retrieve albedo globally across the planet (e.g., Kieffer et al., 1977; Christensen 1988; 192 Christensen et al., 2001; Vincendon et al., 2015). In either case, the temporal coverage was 193 limited given the nature of the observations, with one image or satellite retrieval per day and 194 location at best. Accordingly, the geometry of incident and reflected solar fluxes was limited, 195 complicating assessments of the Lambertian (isotropically scattering surface) approximation, 196 which has been assumed in these studies. 197 198 Here we expand upon previous studies and obtain broadband albedo values for a variety of 199 illumination and viewing geometries, which allows us to study the degree to which the surface 200 materials depart from ideal Lambertian scattering (Section 4). This is important for improving 201 predictive capabilities of mesoscale and global models (Montmessin et al., 2007; Fenton et al., 202 2007), which typically incorporate albedo variations in subseasonal time scales (Haberle et al., 203 1993; Kahn et al., 2005; Fenton et al., 2007, Geissler et al., 2016), but not in diurnal timescales 204 arising from non-Lambertian behavior. Similarly, surface-based and satellite retrievals of thermal 205 inertia (Putzig et al., 2005; Fergason et al., 2006; Vasavada et al., 2017; Savijärvi et al., 2020; 206 Piqueux et al., 2021) typically consider a constant value of albedo throughout the day, and thus 207 also may benefit from non-Lambertian considerations. 208 209 Furthermore, MEDA measurements allow for the direct estimation of thermal inertia assuming 210 homogeneous terrains within the ground temperature sensor’s field of view (Section 3). Thermal 211 inertia is an important geophysical property of the terrain, which modulates the amount of energy 212 flux that is transported into the subsurface, and thus determines surface and shallow subsurface 213 temperatures. In previous studies, thermal inertia has been obtained by fitting thermal models to 214 measurements of ground temperature retrieved from satellite observations (e.g., Kieffer et al., 215 1977; Mellon et al., 2000; Fergason et al., 2006a; Fergason et al., 2012; Gondet et al., 2013), 216 measured by surface-based missions (e.g., Fergason et al., 2006b; Hamilton et al., 2014; 217 Martínez et al., 2014; Vasavada et al., 2019; Piqueux et al., 2021), or using both datasets 218 coincidently (Edwards et al., 2018; Christian et al., 2021). In either case, a thermal model is fed 219 with key parameters such as aerosol opacity, pressure, and albedo, among others, to simulate the 220 SEB at the surface. Then, these models solve the heat conduction at the ground for homogeneous 221 or heterogeneous terrains using the simulated SEB as the upper boundary condition, obtaining 222 the thermal inertia by best fitting their outputs to measured values of ground temperature. 223 manuscript submitted to replace this text with name of AGU journal 224 Here we obtain thermal inertia directly by using MEDA measurements of ground temperature 225 (Tg), albedo and SEB assuming homogeneous terrains. An in-depth analysis of the differences 226 between thermal inertia values derived assuming heterogeneous versus homogeneous terrains is 227 presented in Savijärvi et al. (2022; this issue). 228 229 In this article, we report results of the surface energy budget, broadband albedo, and thermal 230 inertia for the first 350 sols of the M2020 mission, corresponding to Ls 6°–174° in MY 36. The 231 structure of the article is the following. Section 2 describes MEDA observations, with focus on 232 TIRS and RDS. Section 3 explains the methods to calculate each term of the surface energy 233 budget (Section 3.1), albedo (Section 3.2) and thermal inertia (Section 3.3). Section 4 shows the 234 results, and it is also divided into three subsections devoted to the thermal inertia (Section 4.1), 235 surface energy budget (Section 4.2) and albedo (Section 4.3). Section 5 discusses discrepancies 236 between measured and modeled values of the downwelling atmospheric IR flux. Section 6 237 contains the summary and conclusions.