Analysis of wind-induced dynamic pressure fluctuations during one and a half Martian years at Gale Crater

Accepted Manuscript

Analysis of wind-induced dynamic pressure fluctuations during one and a half Martian years at Gale Crater Aurora Ullan, ´ Mar´ı a-Paz Zorzano, Francisco Javier Mart´ı n-Torres, Patricia Valent´ı n-Serrano, Henrik Kahanpa¨ a, ¨ Ari-Matti Harri, Javier Gomez-Elvira, Sara Navarro ´ PII: DOI: Reference:

S0019-1035(17)30057-X 10.1016/j.icarus.2017.01.020 YICAR 12342

To appear in:

Icarus

Received date: Revised date: Accepted date:

28 November 2015 22 December 2016 23 January 2017

Please cite this article as: Aurora Ullan, Mar´ı a-Paz Zorzano, Francisco Javier Mart´ı n-Torres, ´ Patricia Valent´ı n-Serrano, Henrik Kahanpa¨ a, Sara Navarro, ¨ Ari-Matti Harri, Javier Gomez-Elvira, ´ Analysis of wind-induced dynamic pressure fluctuations during one and a half Martian years at Gale Crater, Icarus (2017), doi: 10.1016/j.icarus.2017.01.020

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Highlights • Detection of synchronous modulations of pressure and air and ground

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surface temperatures.

• Diurnal and seasonal variation of dynamic pressure fluctuations. • Novel method to estimate winds at Gale Crater.

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• Year-to-year repeatability of these environmental phenomena.

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Aurora Ull´ana,∗, Mar´ıa-Paz Zorzanob,c , Francisco Javier Mart´ın-Torresb,d , Patricia Valent´ın-Serranod , Henrik Kahanp¨aa¨e,f , Ari-Matti Harrie , Javier G´omez-Elvirac , Sara Navarroc

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Analysis of wind-induced dynamic pressure fluctuations during one and a half Martian years at Gale Crater

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Departamento de Teor´ıa de la Se˜ nal y Comunicaciones, Escuela Polit´ecnica Superior, Universidad de Alcal´ a, Madrid, Spain. b Division of Space Technology, Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, Kiruna, Sweden. c Centro de Astrobiolog´ıa (CSIC-INTA), Torrej´ on de Ardoz, Madrid, Spain. d Instituto Andaluz de Ciencias de la Tierra (CSIC-UGR), Armilla, Granada, Spain. e Finnish Meteorological Institute, Helsinki, Finland. f School of Electrical Engineering, Aalto University, Espoo, Finland.

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Abstract

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The Rover Environmental Monitoring Station (REMS) instrument on-board

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the Mars Science Laboratory (MSL) has acquired unprecedented measure-

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ments of key environmental variables at the base of Gale Crater. The pres-

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sure measured by REMS shows modulations with a very structured pattern of

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short-time scale (of the order of seconds to several minutes) mild fluctuations

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(typically up to 0.2 Pa at daytime and 1 Pa at night-time). These dynamic

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pressure oscillations are consistent with wind, air and ground temperature

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modulations measured simultaneously by REMS. We detect the signals of

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a repetitive pattern of upslope/downslope winds, with maximal speeds of

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about 21 m/s, associated with thermal changes in the air and surface tem-

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peratures, that are initiated after sunset and finish with sunrise proving that

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Gale, a 4.5 km deep impact crater, is an active Aeolian environment. At

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nighttime topographic slope winds are intense with maximal activity from ∗ Preprint submitted de to Icarus January 28, 2017 Departamento Teor´ıa de la Se˜ nal y Comunicaciones, Escuela Polit´ ecnica Superior, Universidad de Alcal´ a, Campus Externo NII, km 33600, 28805, Alcal´ a de Henares, Madrid, Spain. Email address: [email protected] (Aurora Ull´ an)

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17:00 through 23:00 Local Mean Solar Time, and simultaneous changes of

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surface temperature are detected. During the day, the wind modulations are

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related to convection of the planetary boundary layer, winds are softer with

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maximum wind speed of about 14 m/s. The ground temperature is mod-

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ulated by the forced convection of winds, with amplitudes between 0.2 K

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and 0.5 K, and the air temperatures fluctuate with amplitudes of about 2 K.

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The analysis of more than one and a half Martian years indicates the year-

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to-year repeatability of these environmental phenomena. The wind pattern

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minimizes at the beginning of the south hemisphere winter (Ls 90) season

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and maximizes during late spring and early summer (Ls 270). The procedure

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that we present here is a useful tool to investigate in a semi-quantitative way

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the winds by: i) filling both seasonal and diurnal gaps where wind measure-

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ments do not exist, ii) providing an alternative way for comparisons through

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different measuring principia and, iii) filling the gap of observation of short

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time-wind variability, where the REMS wind-sensor is blind.

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Keywords:

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Mars, REMS, Gale Crater, Planetary boundary layer (PBL), Pressure

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fluctuations, winds

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1. Introduction

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The Mars Science Laboratory mission (MSL) successfully delivered the

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Curiosity rover to Gale Crater, a 154 km wide impact crater located near the

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foot of a steep section of the dichotomy boundary, whose floor is at 4.5 km

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below the datum. The landing site, at 6 ◦ S, 137.4◦ E, is NW of Aeolis Mons

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(Mt. Sharp) which rises about 5.5 km above the northern crater floor, see 3

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(Wray, 2013). Gale crater presents a basin with variable rim height which

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rises about 4.5 km with respect to the floor. The landing time on August 6,

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2012 (05:18 UTC Spacecraft Event Time), was a few sols (one sol is a Mar-

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tian day) after the middle of the southern winter at areocentric longitude

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(Ls) 150.7. On June 26, 2014, the Curiosity rover completed its first Martian

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year (687 Earth days) completing its prime mission, exploring 8 km of the

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crater floor and heading towards the foothills of Aeolis Mons. One of the

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instruments on board Curiosity is the Rover Environmental Monitoring Sta-

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tion (REMS). Although there have been other meteorological measurements

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(Hess et al., 1977; Sutton et al., 1978; Murphy et al., 1990; Tillman et al.,

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1994; Schofield et al., 1997; Holstein-Rathlou et al., 2010; Taylor et al., 2010;

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Petrosyan et al., 2011) on the surface of Mars, REMS in-situ meteorological

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observations are the first of its kind from the South hemisphere. In addition

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to that, Curiosity’s landing site shows the peculiarities of strong topographic

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contrasts and a close to the equator location. The fact that Curiosity resides

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at the bottom of a large crater in the Martian tropics provides a unique

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opportunity to sample a different environment than previous landers and

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rovers, as explained by Golombek et al. (2012) and (Haberle et al., 2013;

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G´omez-Elvira et al., 2012).

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REMS consists of a suite of meteorological instruments that measures

pressure, temperature (in the air and on the ground), wind speed and direction, relative humidity, and the Ultraviolet (UV) flux, see (G´omez-Elvira

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et al., 2012, 2014). The standard cadence of REMS measurements consists of

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five-minute acquisitions of 1-Hz frequency every hour. Thus, all sensors are

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read with 1 s sampling interval when the instrument is used. Additionally,

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it is typical to sample between three and seven one-hour in a row extended

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blocks every sol, also at 1-Hz frequency. The timing of the extended blocks

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is rotated to cover the diurnal cycle completely over several sols, see Figure

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1 in (G´omez-Elvira et al., 2014) for a summary of the scheduled observations

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taken during the first 100 sols of the mission. Thus REMS has provided

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unprecedented simultaneous observations of key environmental variables of

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Mars routinely for one full Martian year (nominal MSL mission), including

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nighttime, providing a novel insight into the Martian boundary layer environ-

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ment (G´omez-Elvira et al., 2014; Haberle et al., 2014; Harri et al., 2014a,b;

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Hamilton et al., 2014; Mart´ınez et al., 2014; Rafkin et al., 2014a; Kahanp¨aa¨

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et al., 2016), and is still measuring as part of the extended surface phase (the

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extended surface mission began on Sol 670). All the data analyzed in this

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work (1048 sols, roughly one and a half Martian years) are published and doc-

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umented regularly at the NASA Planetary Data System (PDS) [Planetary

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Atmosphere Node at http://atmos.nmsu.edu/PDS/data/].

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According to global and mesoscale circulation models, at Gale, surface

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winds are not expected to follow the larger-scale behaviour, see (Haberle

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et al., 2014; Pla-Garc´ıa et al., 2016; Rafkin et al., 2016). Instead of that,

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inside Gale crater, winds are dominated by much smaller-scale (mesoscale)

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slope flows excited by the rim walls and at the center of the crater by Aeolis

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Mons (Mt. Sharp), which rises about 5.5 km above the floor, see (Tyler and

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Barnes, 2013; Pla-Garc´ıa et al., 2016; Rafkin et al., 2016).

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1.1. REMS pressure observations

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Design details of the REMS pressure sensor, assessment of its performance

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and an introduction to the first 100 sols observations have been published by 5

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Harri et al. (2014b). A preliminary analysis of the observations at different

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timescales of the first 100 sols of REMS pressure data has shown that the

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REMS pressure sensor is performing outstandingly well and has revealed

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the existence of phenomena undetected by previous missions that include

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possible gravity waves excited by evening downslope topographic flows, for

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more details see (Haberle et al., 2014; Harri et al., 2014b; Mart´ın-Torres et al.,

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2014).

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Pressure data are unique in the sense that variations in pressure are asso-

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ciated with meteorological phenomena ranging in spatial scale from meters to

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global and on temporal scales from seconds to years. As explained by Haberle

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et al. (2014) no other meteorological parameter has that capability. Differ-

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ential solar heating on the planet causes pressure gradients, which induces

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three planetary-scale motions of air masses in the atmosphere of Mars: the

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Hadley circulation, the thermal tides and the CO2 condensation/sublimation

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flows. The Hadley cell and condensation flows leave distinguishable varia-

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tions on a seasonal scale. On a diurnal scale thermal tides induce a very

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strong diurnal variation (the main part of about 90 Pa is due to the thermal

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tide, while some fraction of that variation is due to the crater circulation

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(Haberle et al., 2014)). The smallest scale of interest is the one of sharp

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pressure drops related to convective wind vortices or whirlwinds. Analyses

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of data measured during Curiosity’s first Martian year show that the pressure

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drops of these vortices ranged up to circa 3 Pa with an average of circa 0.6

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Pa, see for instance (Steakley and Murphy, 2016; Kahanp¨aa¨ et al., 2016). As

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explained in (Renn´o et al., 2000; Ellehoj et al., 2010), vortices extend usually

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over the course of a few to tens of seconds. Apart from that, as we present in

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this paper, REMS pressure observations show small amplitude fluctuations

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(or modulations) that last from 1 minute to a few tens of minutes, that can

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be associated with pressure changes related to winds.

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REMS has a wind sensor on board, however the wind sensor can only

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provide 5-minutes averaged values, for winds that do not come from rear,

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and during the warm hours of the day. The accuracy of the wind sensor is

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±50%, for the wind speed, and ±20%, for the wind direction, and can only

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resolve for about half of the potential directions in the daytime and early

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evening hours. This does not permit to perform comparisons of global day

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and night wind patterns and does not resolve for short time phenomena..

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Given the high resolution of the pressure sensor observations, and in the

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absence of accurate wind-measurements, we shall use these short-time scale

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measured pressure oscillations, ∆P , as a proxy for wind activity.

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Due to the low range of velocities studied, 1-20 m/s, the Mach number of

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the CO2 atmosphere is low enough (M≈ 4−20e10−33 ) and because of the fact

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that the measured pressure deviation is small in comparison to the pressure

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base state, we can apply the principles of incompressible fluid dynamics. In

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this regime, the dynamic pressure or velocity pressure is the quantity defined

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by ∆P =

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m/s).

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ρ v 2 (in pascals) with ρ the fluid density (in kg/m3 ), and v (in

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The principle of measurement is similar to the one of the Pitot tube.

Pitot tube anemometers measure the overpressure in a tube that is kept

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aligned with the wind vector by means of a direction vane. On Earth, this is

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widely used in the aerospace sector to determine the airspeed of an aircraft,

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and in industrial applications to measure liquid, air and gas flow veloci-

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ties. It is actually recognised as one of the standard wind sensing techniques

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for surface measurements by the World Metereological Organisation (see for

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instance the ”Guide to Meteorological Instruments and Methods of obser-

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vation” [https://www.wmo.int/pages/prog/gcos/documents/gruanmanuals/

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CIMO/CIMO Guide-7th Edition-2008.pdf]).

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In this work, we present and describe for the first time the measured

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short-period dynamic pressure data during one and a half Martian years at

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Gale Crater as a function of season and time of day. Moreover, we use our

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study to assess in a novel way the diurnal and seasonal patterns of wind

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variation at Gale Crater. Due to the extreme topography of our landing site,

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these REMS data are truly unique.

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This paper is organized as follows: In section 2 we describe the method

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used to quantify the pressure perturbations. In section 3 we contextualize

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this work in the framework of the wind-related measurements by REMS.

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In section 4 we present the analysis of pressure data, and in section 5 we

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apply our pressure perturbations study to improve REMS wind observations.

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Finally, in section 6 we show the results of our analysis.

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2. The method

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Because of the high resolution (0.2 Pa) of the REMS pressure measure-

ments (Harri et al., 2014b), and because this magnitude provides information

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at a wide range of scales, we shall study the short-time scale variations of

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the pressure field. The pressure at Gale varies largely both on a diurnal

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scale (as stated in the Introduction, mainly due to the thermal tide, with

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a contribution from the crater circulation) and on a seasonal scale (due to 8

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the condensation and sublimation of the CO2 in the polar caps that leads

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to variations of about 25% in the average pressure). To quantify the small

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scale pressure perturbations that modulate the diurnal and seasonally vary-

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ing pressure profile, a reference pressure profile must be defined for every sol.

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We have generated a diurnal smooth pressure profile using a cubic-spline that

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passes through a set of hourly reference points (averaged blocks of consecu-

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tive 5 minutes data, in such a way that they include the 5 minutes hourly

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acquisitions and the extended 1-hour acquisitions). An example of evening

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pressure perturbations for a certain window of LMST is shown in Figure 1.

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The raw pressure data for sol 74 (Ls 192) between 19:00 and 20:05 (dots)

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show an oscillation with respect to the smooth cubic spline reference curve

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(line) for that particular day. As mentioned above, these night-time pressure

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anomalies have been related to winds of topographic nature, see (Haberle

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et al., 2014; G´omez-Elvira et al., 2014; Pla-Garc´ıa et al., 2016).

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The raw pressure data set is then smoothed with a sliding window. The

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length of this window is taken from 60 s, for the general analysis, to 240 s, for

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some illustrating examples that compare pressure, ground and air thermal

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fluctuations in the extended (1-hour) observations. This process allows to

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filter out short time scale phenomena (such as electronic noise, turbulences,

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quick vortices -pressure drops of just a few seconds of duration- or instrumen-

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tal artifacts). Then, the fit is subtracted from the smoothed data to reveal

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the amplitude ∆P of the pressure variation for every REMS measurement

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during 1048 sols.

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3. Pressure and thermal fluctuations In addition to the pressure fluctuations, the analysis of REMS air tem-

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perature (Ta) sensors (ATS 1 and 2 at two different booms mounted on the

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rover mast at 1.6 m above the surface) and of the IR remote ground tem-

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perature (Tg) sensor (GTS), reveals the existence of thermal fluctuations all

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along the day. Notice that the GTS monitors the temperature of an area

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of about 100 m2 to the side of the rover. During the day, the pressure,

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air and ground temperature show modulations of quasi-periodic nature, see

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Figure 2. It is important to mention that second-by-second pressure and

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temperature information are given by the respective sensors. In Figure 2,

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we show day-time air (Ta) and ground temperature (Tg, shown with a 25 K

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offset for clariry) regular fluctuations during the extended acquisition of sol

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82 (Ls 197). We also display the amplitude of pressure perturbations, ∆P ,

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for comparison. All the data are smoothed with a 240 s sliding window. The

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ground surface temperature shows a quasi periodic modulation that seem to

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be anticorrelated with the amplitude of pressure oscillations.

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Around noon, when the solar heating of the ground surface is maximal,

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there is a strong vertical thermal gradient in the planetary boundary layer

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(notice the temperature difference of 25 K, between T g and T a in Figure 2,

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within merely 1.6 m) and convection is active. For this reason, the pressure,

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air and ground temperature fluctuations observed by REMS within these

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hours are probably related to convective winds. The skin-temperature of

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the ground, with an amplitude of 0.2 K to 0.5 K, is modulated by what is

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known as forced convection, namely the heat transfer from the surface to

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the air is forced by the flow of the air (see Soria-Salinas et al. (2016) for an 10

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example of wind-induced forced convection on the hardware of REMS). In

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Figure 2 we show this modulation of the temperature of the ground, while

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the air temperatures fluctuate with amplitudes of about 2 K. The pattern

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of this small ground temperature modulation is very repetitive and shows a

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duration that varies from 2 to 10 minutes.

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A similar analysis is shown for a night-time extended observation, see

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Figure 3. Here the ground temperature data have been filtered with sliding

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windows of 240 s to reduce the sensor noise. During these hours the REMS

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observations indicate that the air temperature has a large variability. This

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example shows large synchronous perturbations in the air temperature (Ta),

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of about 10 K amplitude, and of the ground temperature (Tg), of about 1

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K to 2 K. When the hot mass of incoming air is detected a simultaneous

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perturbation of the pressure field is observed. This fact could be explained

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with the existence of variable topographic winds that mix masses of air with

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very different temperatures. As a result of that, the air temperature shows

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large variations and this affects slightly the surface temperature inducing

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a synchronous modulation on the ground skin temperature too, however of

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lower amplitude. These large modulations may last up to about 10 minutes

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and repeat in an irregular pattern every 20 to 40 minutes roughly, ending

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with sunrise.

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The IR ground temperature sensor described by Sebasti´an et al. (2010)

provides the ground brightness temperature with an accuracy of ±4.5 K at

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213 K, improving to ±1 K at 273 K, whereas both ATS’ are performing

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with an accuracy better than 5 K and a time response in the range of 20

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to 80 s, depending on the regime of wind (natural or forced convection), see

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(G´omez-Elvira et al., 2014). It is worth emphasizing that, both during the day and night, all the sen-

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sors reveal the same pattern of environmental fluctuations in an independent

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manner, in spite of having different electronics, locations in the rover as well

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as different sensing principles and physical magnitudes of observations. This

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fact provides more confidence on the quality of the measurements. Minor

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discrepancies are attributed to different sensitivity of the sensors because of

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their implementation at different locations within the rover. In particular,

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the GTS is mounted on a boom attached to the rovers mast and has an ellip-

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soidal field of view covering a footprint area of 100 m2 slightly rearward and

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to the right side of the rover. The pressure sensor is mounted on the rover

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deck. And the two booms that host the ATS’ are angled at 120◦ to each

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other, one pointing to the front (boom 2) and the other to the side (boom

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1). During the day the ATS of the two booms do not necessarily provide

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the same temperature due to the irregular day-time mixing of air around the

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sun-illuminated rover, as explained by Zorzano et al. (2014).

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4. Pressure data analysis

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Next we analyze more than one and a half Martian years (1048 sols) of

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REMS pressure observations to detect all the situations when, during the

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REMS observation window, the amplitude ∆P of the pressure fluctuation is

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larger than a predefined threshold limit. The resolution of the pressure sensor

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is 0.2 Pa, see (Harri et al., 2014b), and raw pressure observations are weighted

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over a sliding window of 60 seconds. We therefore set 4σ = 4 √0.2 ≈ 0.1 as a 60

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threshold indicating that an instantaneous measurement of pressure shows a 12

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significant deviation from the daily trend. The main conclusions of this work

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do not change if this threshold limit is further reduced.

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4.1. Diurnal variation

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The analysis of pressure modulations reveals the existence of a charac-

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teristic diurnal distribution. The MSL rover landed on Gale at the end of

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the winter season and Ls 180 marks the beginning of spring in the Southern

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Hemisphere. Figure 4 shows the variation of the amplitude of the pressure

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oscillations along the day for 10 consecutive sols during the beginning of lo-

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cal spring. Each color represents a different Martian day (sol). Reference

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pressure lines are shown for completeness. The diurnal pressure modulation,

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mainly produced by the thermal tide, can be clearly seen. During these sols

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the pressure increases as expected for this season due to the CO2 sublimation

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of the polar cap. The smooth reference lines show also marks where pressure

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fluctuations have been detected together with the corresponding amplitude

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∆P of the pressure deviation. The strongest amplitude modulations take

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place after sunset, from 17:00 through 23:00 LMST, whereas around noon

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the amplitudes are smaller. Figures 5, 6 and 7 show the same behaviour for

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the beginning of summer, autumn and winter respectively. The ∆P diurnal

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pattern is consistent throughout the year: mid-intensity day-time modula-

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tions most probably associated with convective winds are active from about

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8:00 to 16:00 LMST. Nighttime slope winds are strongest from 18:00 through

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23:00 LMST, then of varying intensity through the night to sunrise. And

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there are periods of low wind activity in the transit from the day-time to the

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night-time. The maximal amplitude of the night-time fluctuations is of the

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order of 1.2 Pa, whereas the maximal ∆P for daytime fluctuations is about

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0.2-0.3 Pa. At the beginning of winter the amplitude of pressure fluctuations

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is minimized all through the day.

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4.2. Seasonal variation

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The procedure described above has been applied to the analysis of mea-

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sured short-time scale pressure oscillations in the REMS environmental data

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set during 1048 sols. To save power during winter the REMS acquisition ca-

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dence was reduced during some sols to the nominal 5 minute hourly measure-

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ments only, in addition some sols have been lost because because REMS was

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not operative (sols 193-194,201-214,216-221, 263-266, 359-364, 445-453,458-

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461, 479-484, 874-879, 938 and 956). This may skew partially the analysis.

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Figure 8 shows the variation along the course of the mission of the mea-

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sured ∆P amplitude in the interval 10:00 to 18:00 LMST in comparison

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with the opacity (i.e. with the atmospheric aerosol load) as derived from

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the REMS UVS by comparison with the radiation at the top of the atmo-

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sphere and applying radiative transfer methods. The color coding indicates

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the Ls. The seasonal variation of atmospheric dust and the seasonal changes

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of wind-induced dynamic pressures changes, in the 10:00 to 18:00 period, go

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in parallel. This can be caused by at least one of these two reasons: i) the

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global dust distribution cycle, and the physical processes behind it, affect at

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a smaller scale the winds at Gale crater too or ii) alternatively when the ∆P

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produced by surface winds is high then this can overcome the near surface

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wind-stress, leading to dust lifting and a locally increased atmospheric dust

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load. It is well known that strong winds are able to lift dust from the surface

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into the air. The dust-lifting mechanism explains how dust can be lifted from

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the surface and transported into the atmosphere by surface winds and wind

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stress. For a given density, if the wind speed at the surface is above a certain

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threshold, or drag velocity Ut , then the near surface wind stress τ = ρ U t 2

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is surpassed and dust can be lifted (Spiga and Lewis, 2010). Notice that

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the wind stress limit τ is just the measured dynamic pressure change, ∆P ,

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evaluated for the threshold drag velocity.

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In spite of the frequent mobility of the MSL rover along the traverse,

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and of the divided and varying pattern of observation of the extended ac-

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quisitions hours, the results clearly indicate a seasonal dependency of the

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measured pressure perturbations, which minimizes at the beginning of the

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south hemisphere winter (Ls 90) time and maximizes during late spring and

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early summer (Ls 270). The analysis of more than one and a half Martian

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years allow us to confirm the year-to-year repeatability of these environ-

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mental phenomena. Thus, we can see in Figure 8 that measured pressure

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fluctuations are maximal during both springs and summers (sols 50 to 350

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and from sol 650 on), while they are minimal in winter (sols 450 to 600).

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4.3. Duration of pressure modulations

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In this section we estimate the timescales of the pressure modulations

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that we find. Figure 9 shows the annually averaged mean and maximal

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duration of the measured pressure fluctuations as a function of the hour of

342

acquisition (i.e. the mean time where the measured deviation amplitude,

343

∆P , is greater than 0.1 Pa with respect to the reference pressure fit). It

344

shows a clear variation along the day, indicating that the regular pattern of

345

measured pressure modulations around noon are of short duration, with an

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annually mean duration of about 40 seconds and maximal duration of about

347

300 seconds. These modulations are typical of convective cells (Lorenz, 2012;

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Spiga, 2012). On the contrary, the measured night-time modulations are consistent with

350

larger scale processes with mean durations of up to 100 seconds and maxi-

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mal durations of about 600 seconds. These pressure perturbations that are

352

irregular in time and are detected simultaneously as strong air and ground

353

temperature variations, are typically related to topographic winds (Spiga,

354

2011). Figures 10 and 11 show the autumn-winter and spring-summer av-

355

eraged mean and maximal duration of the pressure oscillations. The main

356

difference between both Figures is that the maximal duration of the mea-

357

sured pressure perturbations in spring-summer is around 600 seconds, while

358

this value is about 500 seconds during autumn-winter. Moreover, the spring-

359

summer mean duration of measured ∆P around noon is about 40 seconds and

360

in autumn-winter is around 30 seconds. It is important to note that the num-

361

ber of events (pressure deviations) detected in the spring-summer period was

362

14621, while only 9267 were detected when considering the autumn-winter

363

interval. Taking into account that the number of sols analysed in both cases

364

was more or less similar, we detect a significantly larger number of events in

365

the spring-summer seasons. In any case, the different timescales of the two

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types of pressure amplitude perturbations is an independent confirmation of

367

the different nature of the winds that models suggest are associated with the

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day-time (convection) and night-time (slope winds) fluctuations.

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5. Application of our study to improve REMS wind observations

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5.1. REMS wind observations Unfortunately the wind sensor of REMS was partly damaged likely due

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to damage by surface materials lofted during landing, see (G´omez-Elvira

375

et al., 2014). A preliminary analysis indicated short lived wind gusts were

376

also measured and displayed a quasi-repeatable pattern occurring most fre-

377

quently between 18:00 and 22:00 LMST (although these later hours were less

378

reliable since they were often subject to high electronic noise). Regarding

379

the nature of these winds, they have been identified as topographic winds,

380

see (G´omez-Elvira et al., 2014), because of their direction, the timing of oc-

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currence (near sunset), their repeatability and their time coincidence with

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pressure anomalies.

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New retrieval algorithms have been used to get partial measured wind

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information from the undamaged boom and the observations of the first

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years of MSL operation on Mars have been recently released. The wind-

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sensor measuring principle is hot-dice anemometry which is sensitive to the

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Reynolds number, and in turn depends on the product of the fluid speed

388

v and the fluid density ρ. These wind retrievals are limited to horizontal

389

velocity, as measured from the boom 2 wind sensor during daytime and early

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evening (when temperatures are above 213 K, i.e. for half of day roughly

391

from about 7:00 to 23:00 Local Mean Solar Time (LMST)) and only for half

392

the potential directions (winds blowing toward the front of the rover).

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In particular, wind speed calculation is done as follows: the output of

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the inverse algorithm is the Reynolds number second by second (Resec ). The

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wind speed is calculated every second (Vsec ) using the following formula:

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Vsec =

Resec × Dynamic V iscosity , Density × D 17

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where D is the characteristic length of the sensor, in this case D = 0.03m, the

397

width of the wind sensor boom. The Dynamic Viscosity is calculated using

398

Sutherland’s formula, with Tair as input to the formula. For all calculations

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related to the wind speed, in which the air temperature is an input, the

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following temperature is used:

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Tair = min(BOOM 1 T IP AIR T EM P, BOOM 2 T IP AIR T EM P ).

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Density is calculated as following: Density =

P ressure , (R/M ) × Tair

where R/M is the Gas Constant for Mars environment.

With the sec-

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ond by second wind speed as input, the average wind speed of the 5 min

405

interval is calculated.

This is done only in the case the most frequent

406

direction is not rear.

In case the wind direction for the 5-min interval

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is rear, no wind speed value is given. This information can be found at

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the NASA Planetary Data System (PDS) [Planetary Atmosphere Node at

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http://atmos.nmsu.edu/PDS/data].

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Because of the noisiness of the signal the resulting data are published as

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averages over 5 minutes. This impedes the detailed study of both the short-

412

time daytime convective wind modulations and the night-time topographic

413

winds. Under these conditions the estimated accuracy shall be 50% for wind

414

speed and 20◦ for direction, see (G´omez-Elvira et al., 2014). Furthermore

415

all the wind measurements are local, at the MSL platform, and the plat-

416

form is significantly warmer than the environment. In particular during day

417

time when the solar irradiance heats up the mast where the wind sensor is

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mounted by up to 30 K, this induces a strong variation of the density in the

419

vicinity of the mast which invalidates the velocity retrievals. The maximal

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daytime measured wind speeds (11:00 to 17:00 LMST) are of the order of 14

421

m/s, see Figure 12, however there is a clear dependency with the daytime

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density variation along the year (which is derived, from the pressure and air

423

temperature measurements). During some sols the wind sensor has provided

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measurements at night-time. These intensities are much stronger and seem

425

to reach wind speeds of up to 21 m/s (not shown).

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5.2. Dynamic pressure and wind speed on Mars

In Figure 13 we show the diurnal variation of the measured pressure

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and air temperature of sol 664. Pressure decreases while temperature rises

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around the central hours of the day. This diurnal variation is caused by

431

the solar insolation and the thermal tide. During the daytime the surface is

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warmer than the atmosphere, this activates convection within the planetary

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boundary layer and, as a result of the movement of the air due to differences

434

in the air temperature, short-period wind fluctuations appear. Apart from

435

that, small oscillations can be seen around 8:00, 12:00 and 20:00 LMST both

436

in pressure and air temperature. As explained above the REMS wind data

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are not available at a 1 Hz rate, and the measurements are not possible for

438

all the hours of the day, instead averaged values have been calculated for

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some hour and some sols. The variation of the wind speed magnitude along

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the year seems to be contaminated by the atmospheric density changes, as

441

shown in Figure 12 . This effect is currently being further investigated. In

442

this work we shall use the measured short scale fluctuations of the P as a 19

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proxy for wind activity. This shall serve to provide an overview of the near

444

surface dynamics at the surface during three Earth years, and as validation

445

for the future recalibration of the wind observations.

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An example of the approach is shown next. In Figure 14 we show hori-

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zontal wind speed 5-minute averages measured by REMS at boom 2 on sol

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664 at certain hours, as well as the amplitude of the measured dynamic pres-

449

sure variations ∆P detected during the extended hours of the same sol, and

450

for the previous and next ones. The wind pattern is clearly distinguished

451

in both sensors. We associate daytime-winds with convective activity, and

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night time strong winds with topographic winds. The wind speed can be

453

estimated from ∆P =

454

∆P = 0.3 Pa detected around noon, when the density was ρ = 0.0135 kg/m3

455

(see Figure 12), to be v = 6.7 m/s (derived velocity). This can be compared

456

with the (5 minute-averaged) wind sensor measurement. Our calculations

457

suggest that REMS wind measurements (filled squares) are overestimated

458

around the central hours of the day. This example shows in which way the

459

measured short-scale fluctuations of pressure can be correlated with surface

460

winds, and therefore the systematic analysis of the diurnal and seasonal mea-

461

sured short-term P fluctuations can be used as a proxy for wind activity.

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ρ v 2 for the measured dynamic pressure change

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In order to estimate the error associated with the derived wind velocity,

we will use error propagation rules. On one hand, the velocity of the wind can be obtained from the formula in the previous paragraph. On the other

465

hand, from the ideal gas law we have Density = P ressure/((R/M ) × Tair ).

466

Combining both formulas we have:

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v=

√  (R/M ) × Tair × ∆P 1/2 2 P 20

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468

. If we denote A =

∆P P

and use error propagation theory we have: δv 1 δTair 1 δA = + |v| 2 |Tair | 2 |A|

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where δv and δTair are the uncertainty values for the wind velocity an the

470

air temperature. As we have already shown in this paper δTair = 5 K,

471

δ∆P = 0.1 Pa and δP = 0.2 Pa. Thus, if we know the values of measured

472

air temperature, pressure and ∆P we can estimate the error of the derived

473

wind speed. If we take logarithms and apply the error formula we obtain an

474

estimation of 26 % for the derived wind.

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Figure 15 compare the amplitude of measured pressure modulations ∆P

476

with the velocity of the wind that take place within the interval of time 18:00

477

LMST of one sol to 10:00 LMST of the next sol (during the night). The color

478

coding indicates the Ls. There is an apparent correlation between measured

479

surface wind activity and the dynamic pressure changes. Moreover, in Figure

480

8 we showed a possible correlation between the atmospheric dust load and

481

these dynamic pressure modulations. According to this the atmospheric dust

482

load is reduced in periods of low wind activity. Recently an annual study

483

of the opacity variations within the crater and outside the crater rim has

484

indicated a connection between the local dust cycle and the boundary layer

485

height: when the boundary layer height increases the crater atmospheric

486

dynamics and the one above the rim allow for the mixing and injection of

487

dust (Moore et al., 2016). The apparent correlation between the short time

488

fluctuations of P, and plausibly of surface winds, and the atmospheric dust

489

dynamics may be connected with this.

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Finally, we have estimated the probability to have a pressure perturbation 21

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within a certain hour of observation. It can be done by weighting the number

492

of data flagged with pressure deviations greater than 0.1 Pa with respect to

493

the volume of REMS acquisitions within an hour. Since larger dynamic

494

pressure changes variations are related to stronger winds, this probability

495

can be used as a proxy for wind intensity. This analysis, shown in Figure

496

16, indicates that, on a yearly average, typically at 12:00 LMST there is

497

a maximum in wind activity, and that at 10:00 and 16:00 LMST there is

498

little or no wind, whereas after sunset the maximal intensity of winds peaks

499

at 21:00-23:00 LMST. Wind speed REMS measurements for sol 664 have

500

also been plotted with filled squares. This sol has been chosen because for

501

the given conditions of that sol (namely temperature and orientation of the

502

wind) many wind sensor observations were acquired, including some in the

503

early night. Only five-minute averaged data of the horizontal component of

504

the wind sensor at boom 2 were detected. There is a very good agreement

505

between the estimated probability and the wind measurements before 10:00

506

and after 16:00 LMST, despite our limited conditions when measuring the

507

wind velocity. Nevertheless, when the solar heating is maximal, between

508

12:00 and 16:00 LMST, the wind sensor is affected by high temperatures

509

and the wind speed measurements obtained might be overestimated. In the

510

published comparisons between mesoscale circulation model simulations (Pla-

511

Garc´ıa et al., 2016) and REMS wind speeds, the REMS retrieved winds were

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reported to be at least three times stronger than the model. A considerable

513

doubt for the wind speed retrieval, which is based on hot-dice anemometry,

514

is the local air density variability that is due to the large thermal fluctuations

515

observed near the platform.

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6. Results There have been other meteorological measurements on the surface on

518

Mars (Hess et al., 1977; Sutton et al., 1978; Murphy et al., 1990; Tillman

519

et al., 1994; Schofield et al., 1997; Holstein-Rathlou et al., 2010; Taylor et al.,

520

2010; Petrosyan et al., 2011). The Mars Pathfinder ASI/MET instrument

521

detected large rapid temperature fluctuations after sunrise until the early

522

afternoon caused by convection. Moreover, short-time scale pressure varia-

523

tions were detected by the ASI/MET sensors and both, wind and tempera-

524

ture, appeared to be correlated. During this mission, nighttime temperature

525

fluctuations were associated with downslope winds, drainage flow down from

526

Ares Vallis (Schofield et al., 1997). It is important to take into account that

527

the Mars Pathfinder lander studied a flat topography, in contrast with the

528

Gale Crater, a place with very strong topographic contrasts.

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The aim of this study is to characterize the variability of pressure on short

530

time scales and to derive winds, assuming incompressibility, from dynamic

531

pressure to guide analysis of the compromised REMS wind measurements.

532

The dynamic pressure perturbations have a characteristic diurnal distribu-

533

tion, in that they are large during the afternoon hours when convection is

534

likely to be active and larger still (and so associated winds are strongest) at

535

night when models predict topographic slope winds. These periods of large

536

winds are separated by almost quiet periods before and after convection is

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expected to be active (roughly 10:00 and 16:00 LMST). As for seasonal depen-

538

dencies, the short-period fluctuations are minimal at the beginning of winter

539

and maximum in late spring, showing some correlation with UV opacity.

540

A major implication here is that the existence of large short-period pres23

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sure fluctuations occurring after sunset and finishing with sunrise suggest

542

that the topographic winds at night in Gale Crater are highly fluctuating,

543

possibly due to the uneven cooling of the surrounding surface environment

544

and/or to different mesoscale dynamical instabilities (Haberle et al., 2014;

545

Harri et al., 2014b; Mart´ın-Torres et al., 2014; G´omez-Elvira et al., 2014;

546

Pla-Garc´ıa et al., 2016; Rafkin et al., 2014b, 2016). Such short-period effects

547

should be included in the modeling of the dynamic atmosphere inside Gale

548

Crater.

549

7. Acknowledgments

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A.U., M.-P.Z., F. J. M-T., and P. V-S., would like to acknowledge financial

551

support provided by the Spanish Ministry of Economy and Competitiveness

552

(AYA2011-25720 and AYA2012-38707). A.-M. H. acknowledge the support

553

from the Finnish Academy. We also acknowledge the strong support, hard

554

work and dedication of members of the MSL ENV group responsible for plan-

555

ning environmental observations on MSL. We also thank the MSL Science

556

Team for their support of the REMS investigation, and we deeply appreciate

557

the REMS PULs and PDLs involved in operations and the engineering and

558

science team that developed REMS sensors.

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References

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560

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562

563

Ellehoj, M. D., et al., 2010. Convective vortices and dust devils at the phoenix mars mission landing site. J. Geophys. Res. 115, E00–E16.

Golombek, M., et al., 2012. Selection of the mars science laboratory landing site. Space Sci. Rev. 170, 641–737. 24

ACCEPTED MANUSCRIPT

564

565

G´omez-Elvira, J., et al., 2012. Rems: The environmental sensor suite for the mars science laboratory rover. Space Sci. Rev. 170, 583–640. G´omez-Elvira, J., et al., 2014. Curiosity’s rover environmental monitoring

567

station: Overview of the first 100 sols. J. Geophys. Res. Planets 119 (7),

568

1680–1688.

570

Haberle, R., et al., 2013. Meteorological predictions for the first 100 sols of the rems experiment on msl. Mars.

AN US

569

CR IP T

566

571

Haberle, R. M., et al., 2014. Preliminary interpretation of the rems pressure

572

data from the first 100 sols of the msl mission. J. Geophys. Res. Planets

573

119, 440–453.

Hamilton, V. E., et al., 2014. Observations and preliminary science results

575

from the first 100 sols of msl rover environmental monitoring station

576

ground temperature sensor measurements at gale crater. J. Geophys. Res.

577

Planets 119(4), 745–770.

580

ED

vations: Initial results. J. Geophys. Res. Planets 119 (9), 2132–2147. Harri, A.-M., et al., 2014b. Pressure observations by the curiosity rover: Initial results. J. Geophys. Res. Planets 119, 82–92.

AC

581

PT

579

Harri, A.-M., et al., 2014a. Mars science laboratory relative humidity obser-

CE

578

M

574

582

583

584

585

Hess, S. L., et al., 1977. Meteorological results from the surface of mars: Viking 1 and 2. J. Geophys. Res. 82, 45594574.

Holstein-Rathlou, C., et al., 2010. Winds at the phoenix landing site. J. Geophys. Res. Planets 115, E00–E18. 25

ACCEPTED MANUSCRIPT

Kahanp¨a¨a, H., et al., 2016. Convective vortices and dust devils at the msl

587

landing site: Annual variability. J. Geophys. Res. Planets 121, 1514–1549.

588

Lorenz, R. D., 2012. Observing desert dust devils with a pressure logger.

589

CR IP T

586

Geosci. Instrum. Method. Data Syst. Discuss. 2, 477–505.

Mart´ın-Torres, F. J., et al., 2014. Highlights from the rover environmental

591

monitoring station (rems) on board the mars science laboratory: New

592

windows for atmospheric research on mars. In: The Fifth International

593

Workshop on the Mars Atmosphere: Modelling and Observation, Oxford,

594

UK.

AN US

590

Mart´ınez, G. M., et al., 2014. Surface energy budget and thermal inertia at

596

gale crater: Calculations from ground-based measurements. J. Geophys.

597

Res. Planets 119 (8), 1822–1838.

M

595

Moore, C. A., et al., 2016. A full martian year of line-of-sight extinction

599

within gale crater, mars as acquired by the msl navcam through sol 900.

600

Icarus 264, 102–108.

603

viking lander 1 site. J. Geophys. Res. 95, 14555–14576. Petrosyan, A., et al., 2011. The martian atmospheric boundary layer. Rev. Geophys. 49 (3).

AC

604

PT

602

Murphy, J. R., et al., 1990. Observations of martian surface winds at the

CE

601

ED

598

605

Pla-Garc´ıa, J., et al., 2016. The meteorology of gale crater as determined from

606

rover environmental monitoring station observations and numerical mod-

607

eling. part i: Comparison of model simulations with observations. Icarus

608

280, 103–113. 26

ACCEPTED MANUSCRIPT

Rafkin, S. C. R., et al., 2014a. Diurnal variations of energetic particle radi-

610

ation at the surface of mars as observed by the mars science laboratory

611

radiation assessment detector. J. Geophys. Res. Planets 119 (6), 1345–

612

1358.

CR IP T

609

Rafkin, S. C. R., et al., 2014b. The meteorology of gale crater determined

614

from msl rems data and mesoscale modeling. In: Eighth International

615

Conference on Mars, Pasadena, California.

AN US

613

616

Rafkin, S. C. R., et al., 2016. The meteorology of gale crater as determined

617

from rover environmental monitoring station observations and numerical

618

modeling. part ii: Interpretation. Icarus 280, 114–138.

Renn´o, N. O., Nash, A. A., Luninne, J., Murphy, J., 2000. Martian and

620

terrestrial dust devils: Test of a scaling theory using pathfinder data. J.

621

Geophys. Res. 105, 1859–1866.

ED

M

619

Schofield, J. T., et al., 1997. The mars pathfinder atmospheric structure

623

investigation /meteorology (asi/met) experiment. Science 278, 1752–1758.

624

Sebasti´an, E., Armiens, C., G´omez-Elvira, J., Zorzano, M.-P., Mart´ınez-

625

Fr´ıas, J., Esteban, B., Ramos, M., 2010. The rover environmental monitoring station ground temperature sensor: A pyrometer for measuring ground temperature on mars. Sensors 10 (10), 9211–9231.

AC

627

CE

626

PT

622

628

Soria-Salinas, A., et al., 2016. Thermal and heat transfer studies using the

629

habit instrument on the exomars 2018 surface platform. In: 67th Interna-

630

tional Astronautical Congress (IAC), Guadalajara, Mexico.

27

ACCEPTED MANUSCRIPT

Spiga, A., Lewis, S. R. 2010. Martian mesoscale and microscale wind variabil-

632

ity of relevance for dust lifting. The International Journal of Mars Science

633

and Exploration. Mars 5, 146–158. doi: 10.1555/mars.2010.0006

CR IP T

631

634

Spiga, A., 2011. Elements of comparison between martian and terrestrial

635

mesoscale meteorological phenomena: katabatic winds and boundary layer

636

convection. Planet. Space Sci. 59, 915–922.

Spiga, A., 2012. Comment on observing desert dust devils with a pressure

638

logger by lorenz (2012) insights on measured pressure fluctuations from

639

large-eddy simulations. Geosci. Instrum. Method. Data Syst. 1, 151–154.

640

641

AN US

637

Steakley, K., Murphy, J., 2016. A year of convective vortex activity at Gale crater. Icarus 278, 180–193.

Sutton, J. L., et al., 1978. Diurnal variations of the martian surface layer

643

meteorological parameters during the first 45 sols at two viking lander

644

sites. J. Atmos. Sci. 35, 2346–2355.

ED

M

642

Taylor, P. A., et al., 2010. On pressure measurement and seasonal pressure

646

variations during the Phoenix mission. J. Geophys. Res. 115, E00E15. doi:

647

10.1029/2009JE003422

CE

PT

645

Tillman, J. E., et al., 1994. The boundary layer of mars: Fluxes, stability,

649

turbulent spectra and growth of the mixed layer. J. Atmos. Sci. 51, 1709–

AC

648

650

1727.

651

Tyler, D. J., Barnes, J. R., 2013. Mesoscale modeling of the circulation in the

652

gale crater region: An investigation into the complex forcing of convective

653

boundary layer depths. Mars 8, 58–77. 28

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654

655

Wray, J. J., 2013. Gale crater: the mars science laboratory/curiosity rover landing site. Int. J. Astrobiol. 12, 25–38. Zorzano, M.-P., et al., 2014. Rems instrument design and operation status:

657

Monitoring the environmental from a moving hot exploration rover on

658

mars. In: The Fifth International Workshop on the Mars Atmosphere:

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Modelling and Observation, Oxford, UK.

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785 784.5 784

783

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P[Pa]

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782.5 782 781.5

780.5 19:10

19:20

19:30

19:40 LMST

19:50

20:00

20:10

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Figure 1: Detail of the raw pressure data (blue) showing the evening pressure modulations observed after sunset at Gale Crater floor during the sol 74 of MSL surface operations, in

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the extended acquisition that took place from 19:00 to 20:05 LMST. On this sol (Ls 192) the local sunset time was at 17:21. The green line shows the smooth cubic spline of the full diurnal acquisitions which is used as reference for pressure oscillation detection.

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12:50

0.04 0.02

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Tg - 25 K Ta ATS 1 Ta ATS 2 Delta P

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∆P[Pa]

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Figure 2: Detail of day-time air (Ta) and ground temperature (Tg, here shown with a 25 K offset for clarity) regular fluctuations during the extended acquisition of sol 82 (Ls 197). The amplitudes of pressure perturbations, ∆P , are also plotted. All the data

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are smoothed with a 240 s sliding window. Modulations are detected independently by the ground and air temperature sensors. It is important to note that second-by-second pressure and temperature information are given by the respective sensors.

31

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Tg + 10 K Ta ATS 1 Ta ATS 2 P

230 228

836

832

224

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222 220 218 216

828 826 824

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830

P[Pa]

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226 T[K]

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Figure 3: Detection of night-time air (Ta of booms 1 and 2, ATS1 and ATS2) and ground temperature (Tg, here with a 10 K offset for clarity) irregular fluctuations synchronous with pressure modulations, during the extended acquisition of sol 95 (Ls 205). Here the

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raw ground temperature data are smoothed with a 240 s sliding window to reduce the ground temperature measurement noise, and the air temperatures and pressure data data with 60 s. The pressure and thermal fluctuations extend over 10 minutes, while the wind brings a mass of warmer air.

32

Sols 80-89, Ls 195-201 860

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0.8 0.6 0.4 0.2

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Figure 4: Diurnal dependence of the amplitude (dots) of pressure modulations at the

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beginning of local (south hemisphere) spring and pressure variation along the day (lines) within a 10 sols interval. Each color represents a different Martian day (sol).

33

Sols 190-199, Ls 265-271 1000

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850 800

M

750 700

1.2 1

∆P[Pa]

1.4

900 P[Pa]

CR IP T

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0.8 0.6 0.4 0.2

CE

PT

ED

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 LMST

Figure 5: Diurnal dependence of the amplitude (dots) of pressure modulations at the

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beginning of local (south hemisphere) summer and pressure variation along the day (lines) within a 10 sols interval. Each color represents a different Martian day (sol).

34

Sols 340-349, Ls 354-359 900

CR IP T

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2

1.8 1.6

850

800

750

M

700

1.2 1

∆P[Pa]

AN US

P[Pa]

1.4

0.8 0.6 0.4 0.2

CE

PT

ED

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 LMST

Figure 6: Diurnal dependence of the amplitude (dots) of pressure modulations at the

AC

beginning of local (south-hemisphere) autumn and pressure variation along the day (lines) within a 10 sols interval. Each color represents a different Martian day (sol).

35

Sols 540-549, Ls 88-92 900

CR IP T

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2

1.8

880

1.6

AN US

P[Pa]

840 820

M

800

1.2 1

∆P[Pa]

1.4

860

0.8 0.6 0.4 0.2

CE

PT

ED

780 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 LMST

Figure 7: Diurnal dependence of the amplitude (dots) of pressure modulations at the

AC

beginning of local (south-hemisphere) winter and pressure variation along the day (lines) within a 10 sols interval. Each color represents a different Martian day (sol).

36

PT

ED

M

AN US

CR IP T

ACCEPTED MANUSCRIPT

CE

Figure 8: Evolution along the first 1048 sols of MSL operation on Mars (approximately one and a half Martian years) of the amplitude of pressure modulations ∆P in the interval 10:00 to 18:00 LMST and comparison with the UV opacity. The color coding indicates

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the Ls. The amplitude of pressure modulations minimizes at the beginning of winter and is maximal at late spring. There is a significant correlation between UV opacity and these magnitudes during seasons.

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CR IP T

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120

700

AN US

Mean duration [s]

500

80 60 40 20

300 200

M

100

0 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 LMST

CE

PT

ED

0

Mean duration Max duration

400

Maximal duration [s]

600

100

Figure 9: Annually averaged mean and maximal duration of the pressure modulation as

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a function of hour of acquisition. The maximum duration of pressure perturbations takes place at about 20:00-24:00 LMST and lasts about 10 minutes.

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120

Mean duration Max duration

600 500

80

AN US

Mean duration [s]

100

700

60

200 100

0 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 LMST

CE

PT

ED

20

300

M

40

400

Maximal duration [s]

Autumn-Winter, Ls 0-179

CR IP T

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Figure 10: Autumn-winter averaged mean and maximal duration of the pressure modula-

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tion as a function of hour of acquisition. The maximum duration of pressure perturbations is around 500 seconds.

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Spring-Summer, Ls 180-359 120

700

500

AN US

80

60

40

300 200

M

100

0 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 LMST

CE

PT

ED

20

Mean duration Max duration

400

Maximal duration [s]

600

100 Mean duration [s]

CR IP T

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Figure 11: Spring-summer averaged mean and maximal duration of the pressure modula-

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tion as a function of hour of acquisition. The maximum duration of pressure perturbations takes place at about 20:00-24:00 LMST and lasts around 600 seconds.

40

0.014

12

0.015

11

0.016

AN US

10 9

0.017

8

0.018

7 6

270

180

Ls

13

90

0.019

5

0.02 0 100 200 300 400 500 600 700 800 9001000 Sol

0

CE

PT

ED

4

360

REMS PS, ATS: ρday [Kg/m3]

14

0.013

vmax ρday

M

REMS WS: vmax [m/s] [11:00:17:00]

15

CR IP T

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Figure 12: Maximum horizontal wind speed measured by REMS during the central hours of the day (11:00 to 17:00, black dots) and the mean air density of each sol (color points).

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There is a clear dependency between both parameters when we consider annual variations of wind speed.

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770

P T

760

270

240

AN US

730 720 710

08:00

12:00 LMST

16:00

20:00

220 210 200

190 00:00

CE

PT

ED

04:00

M

700

230

T [K]

250

740 P[Pa]

280

260

750

690 00:00

CR IP T

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Figure 13: Measured pressure and air temperature of sol 664. If we consider the global behaviour along the day, we can see that there is an anticorrelation between both environ-

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mental variables. Apart from that, small oscillations can be seen around 8:00, 12:00 and 20:00 LMST both in pressure and air temperature.

42

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10 9

0.3

8

AN US

∆P[Pa]

0.35

0.25 0.2 0.15

M

0.1

6 5 4

CE

PT

ED

06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 LMST

7

v [m/s]

0.4

11

∆P v

CR IP T

0.45

Figure 14: Wind measured by REMS at certain hours and the amplitude of the pressure oscillations detected in this work, ∆P . There are three colors for the pressure modulations

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that show the behaviour of sols 663, 664, and 665, three consecutive martian days. Wind measurements are plotted with filled squares. The intensity of winds is higher when pressure oscillations are bigger.

43

PT

ED

M

AN US

CR IP T

ACCEPTED MANUSCRIPT

CE

Figure 15: Evolution along the first 1048 sols of MSL operation on Mars (approximately one and a half Martian years) of the amplitude of pressure modulations ∆P and comparison with the velocity of the wind that take place within the interval of time 18:00 MLST

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of one sol to 10:00 LMST of the next sol (during the night). The color coding indicates the Ls. The wind speed minimizes at the beginning of winter (Ls 90) and is maximal at late spring and summer (Ls 270). There is a correlation between the amplitude of pressure modulations and the measured wind velocity.

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CR IP T 10

0.3

9

0.25

8

0.2 0.15 0.1 0.05

03:00 06:00 09:00 12:00 15:00 18:00 21:00 LMST

6 5 4

PT

ED

M

0

7

v [m/s]

0.35

11

Probability Wind

AN US

Pressure fluctuation probability [%]

0.4

CE

Figure 16: Probability of having a pressure modulation as a function of time along the day, averaged over one Martian year. Measurements of Horizontal wind speed on sol 664 are also plotted with filled squares.There is a very good agreement between the estimated

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probability and the wind measurements before 10:00 and after 16:00 LMST. Nevertheless, when the solar heating is maximal, between 12:00 and 16:00 LMST, the wind sensor is affected by high temperatures and the wind speed measurements obtained might be overestimated.

45