Winds in the Lower Cloud Level on the Nightside of Venus from VIRTIS-M (Venus Express) 1.74 Μm Images

atmosphere

Article Winds in the Lower Cloud Level on the Nightside of Venus from VIRTIS-M (Venus Express) 1.74 µm Images

Dmitry A. Gorinov * , Ludmila V. Zasova, Igor V. Khatuntsev, Marina V. Patsaeva and Alexander V. Turin

Space Research Institute, Russian Academy of Sciences, 117997 Moscow, Russia; [email protected] (L.V.Z.); [email protected] (I.V.K.); [email protected] (M.V.P.); [email protected] (A.V.T.) * Correspondence: [email protected]

Abstract: The horizontal wind velocity vectors at the lower cloud layer were retrieved by tracking the displacement of cloud features using the 1.74 µm images of the full Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M) dataset. This layer was found to be in a superrotation mode with a westward mean speed of 60–63 m s−1 in the latitude range of 0–60◦ S, with a 1–5 m s−1 westward deceleration across the nightside. Meridional motion is significantly weaker, at 0–2 m s−1; it is equatorward at latitudes higher than 20◦ S, and changes its direction to poleward in the equatorial region with a simultaneous increase of wind speed. It was assumed that higher levels of the atmosphere are traced in the equatorial region and a fragment of the poleward branch of the direct lower cloud Hadley cell is observed. The fragment of the equatorward branch reveals itself in the middle latitudes. A diurnal variation of the meridional wind speed was found, as east of 21 h local time, the direction changes from equatorward to poleward in latitudes lower than 20◦ S. Significant correlation with surface topography was not found, except for a slight decrease of zonal wind speed, which was connected to the volcanic area of Imdr Regio. Citation: Gorinov, D.A.; Zasova, L.V.; Khatuntsev, I.V.; Patsaeva, M.V.; Keywords: Venus; atmosphere; circulation; wind tracking Turin, A.V. Winds in the Lower Cloud Level on the Nightside of Venus from VIRTIS-M (Venus Express) 1.74 µm Images. Atmosphere 2021, 12, 186. 1. Introduction https://doi.org/10.3390/ atmos12020186 The thick cloud layer of Venus rotates around the planet in the westward direction with a peak velocity 60 times higher than that of the planet itself at approximately 100 m s−1 for Academic Editor: the altitudes of 65–70 km (upper cloud level) above the surface [1,2]; this is a phenomenon Alessandra Migliorini known as retrograde superrotation. In the altitude range from the surface up to 90 km, Received: 25 December 2020 the atmospheric motion is predominantly zonal. The velocity decreases for altitude levels Accepted: 27 January 2021 farther from the upper cloud level and for latitudes closer to the poles [3]. Published: 30 January 2021 Thermal emissions from the hot lower atmosphere and surface are observed on the nightside in the near-infrared range in spectral “windows” between CO2 bands. The lower Publisher’s Note: MDPI stays neutral clouds have nonhomogeneous distribution of the cloud opacity, which leads to a complex with regard to jurisdictional claims in morphology of small-scale features of various observed contrasts [4]. By tracking the published maps and institutional affil- displacement of these cloud features with time, one can derive horizontal wind speed at iations. the altitude of remote sensing [5]. In the spectral window of 1.74 µm on the nightside, the thermal radiance comes from the lower clouds and from beneath the main cloud level. The effective level of emissions was estimated at the altitudes of 44–48 km [5], which we will use in this paper. Thus, Copyright: © 2021 by the authors. motion of the observed cloud features is associated with the atmosphere dynamics at these Licensee MDPI, Basel, Switzerland. altitudes. This article is an open access article Before the Venus Express mission, the lower clouds of Venus were studied by the distributed under the terms and infrared spectrometer NIMS (Near-Infrared Mapping Spectrometer) onboard Galileo space- conditions of the Creative Commons craft [6] and from Earth-based telescopes [7–10]. Attribution (CC BY) license (https:// Results of two cloud tracking analyses of the partial dataset of VIRTIS-M (Venus creativecommons.org/licenses/by/ Express) images, acquired in 2006–2008 [5,11] during 18 and 45 orbits, respectively, showed 4.0/).

Atmosphere 2021, 12, 186. https://doi.org/10.3390/atmos12020186 https://www.mdpi.com/journal/atmosphere Atmosphere 2021, 12, 186 2 of 13

a consistent zonal wind speed of ~60 m s−1 between 0 and 70◦ S. Those works also analyzed meridional wind speed values, local time (LT), latitude and time dependence of the wind velocity in the lower clouds. Improvements brought by our analysis of the full VIRTIS-M dataset will be shown in the following sections. More recent lower cloud tracking results came from the IR2 camera onboard JAXA’s Akatsuki spacecraft in 2016 [12,13]. Although mean meridional speed values are consistent with the VIRTIS-M results, zonal speed shows a different shape of the latitudinal proﬁle, an “equatorial jet”, with zonal wind speed values that reached ~75 m s−1 near the equator.

2. Materials and Methods The infrared channel of the Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M) spectrometer onboard the Venus Express covered a wavelength range between 1 and 5 µm with a spectral resolution of 14 nm and obtained images of Venus from a distance range of 40,000–70,000 km with a pixel size of 10–40 km [14]. Images were taken on the approach trajectory, when the spacecraft was moving along the high elliptical orbit towards the pericenter (located above the Northern Pole) [15]. Thus, the ﬁeld of view of VIRTIS primarily captured Southern Hemisphere. In this work, we analyzed the entire VIRTIS-M dataset, from which 195 orbits were found to be suitable (see details on analysis methods further) and from which 44,480 horizontal velocity vectors were extracted in turn (Table1). The number of analyzed orbits amounts to about 4 times the number used in previous research [11]. It allowed us to decrease the errors of the mean speed values, to provide more coverage in the equatorial latitudes and more spacious longitudinal coverage. The database of retrieved vectors can be found in the Supplementary Materials.

Table 1. Number of retrieved vectors from Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M) data depending on observation periods. Data are artiﬁcially grouped into four datasets, with approximately 2-month long intervals between them.

Dataset Begin/End Orbit Numbers Orbits Vectors I 28 May 2006/5 October 2006 0038–0167 29 2605 II 4 December 2006/6 June 2007 0228–0411 97 23,904 III 18 July 2007/24 January 2008 0454–0644 44 12,774 IV 9 April 2008/27 October 2008 0720–0921 25 6007 All 28 May 2006/27 October 2008 0038–0921 195 44,480

VIRTIS-M 1.74 µm data cover mostly (99.8%) Southern Hemisphere. Figure1 shows how the retrieved velocity vectors are distributed across the nightside. Cloud features are most pronounced between 10 and 40◦ S, and as a result, this latitude range contains more than a half—51.2% of all vectors. Vectors are distributed almost symmetrically related to the midnight meridian: 45.9% are located before, 54.1%—after 0 h local time (LT). The number of retrieved vectors decreases towards both terminators. Figure2 shows distribution of retrieved velocity vectors in the longitude-latitude coordinates. Longitudes between 50–150◦ only contain 5.8% of all data. In the Southern Hemisphere, this longitude range includes Aphrodite Terra, a massive geological formation that was previously suggested to influence the atmosphere at the cloud top level on the dayside [16–18]. Our research took a step to investigate a possible influence of Venus topography on dynamics in the lower clouds. Unfortunately, data in the aforementioned longitude range are scarce, however some works indicated that other topographical features may also influence the atmosphere—in the upper mesosphere [19] and at the cloud top [20]. Atmosphere 2021, 12, x FOR PEER REVIEW 3 of 16

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Figure 1. Coverage of Venus nightside by velocity vectors retrieved in this work. This distribution uses 40 min LT × 10° latitude bins. (a): number of orbits (per bin) that were eligible for velocity retrieval. (b): number of vectors (per bin) retrieved in total.

Figure 2 shows distribution of retrieved velocity vectors in the longitude-latitude coordinates. Longitudes between 50–150° only contain 5.8% of all data. In the Southern Hemisphere, this longitude range includes Aphrodite Terra, a massive geological formation that was previously suggested to influence the atmosphere at the cloud top level on the dayside [16–18]. Our research took a step to investigate a possible influence of Venus Figure 1. Coverage of Venus nightside by velocity vectors retrieved in this work. This distribution topography on dynamics in the lower clouds. Unfortunately, data in the aforementioned uses 40 min LT × 10◦ latitude bins. (a): number of orbits (per bin) that were eligible for velocity longitude range are scarce, however some works indicated that other topographical features retrieval.Figure 1. ( bCoverage): number of of Venus vectors nightside (per bin) by retrieved velocity invector total.s retrieved in this work. This distribution usesmay 40 also min influence LT × 10° latitudethe atmosphere—in bins. (a): number the upperof orbits mesosphere (per bin) that [19] were and eligible at the cloudfor velocity top [20]. retrieval. (b): number of vectors (per bin) retrieved in total.

Figure 2. Coverage of Venus nightside in longitude—latitude coordinates by velocity vectors retrieved in this work. This distribution uses 10◦ longitude × 10◦ latitude bins. (a): number of orbits (perFigure bin) 2. that Coverage were eligible of Venus for velocitynightside retrieval. in longitude—latitude (b): number of vectorscoordinates (per by bin) velocity retrieved vectors in total. retrieved in this work. This distribution uses 10° longitude × 10° latitude bins. (a): number of orbits (perVIRTIS-M bin) that were images eligible in for the velocity 1.74 µm retrieval. channel (b): are number characterized of vectors by(per complex bin) retrieved cloud in mor- total. phology (Figure3), caused by varying opacity, and the abundance of cloud features that are stretched along the zonal direction due to the superrotation. Subsequent images of the same cloud area contain stable cloud features, and tracking of their displacement allows us to retrieve velocity vectors. In this work, we used images separated by 3600–7200 s intervals. To retrieve the velocity of the displacement of identiﬁed cloud features, we used the

visual method [21,22]. For a selected pair of images, acquired with a ∆t interval, coordinates ofFigure any identiﬁed2. Coverage detailof Venus were nightside precise in enoughlongitude—latitude to calculate coordinates zonal (u by) and velocity meridional vectors re- (v) componentstrieved in this of work. the horizontal This distribution wind uses by using 10° longitude the following × 10° latitude formulas: bins. (a): number of orbits (per bin) that were eligible for velocity retrieval. (b): number of vectors (per bin) retrieved in total.

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VIRTIS-M images in the 1.74 µm channel are characterized by complex cloud morphology (Figure 3), caused by varying opacity, and the abundance of cloud features that are stretched along the zonal direction due to the superrotation. Subsequent images of the same cloud area contain stable cloud features, and tracking of their displacement allows us to retrieve velocity vectors. In this work, we used images separated by 3600–7200 s intervals. To retrieve the velocity of the displacement of identified cloud features, we used the visual method [21,22]. For a selected pair of images, acquired with a Δt interval, coordinates of any identified detail were precise enough to calculate zonal (u) and meridional (v) components of the horizontal wind by using the following formulas: Atmosphere 2021, 12, 186 λ − λ + ϕ 4 of 13 ( 2 1)(R h)cos( 1) u = (1) Δ t

(λ2 − λ1ϕ)(R−+ϕh) cos(+ϕ1) u = ( 2 1)(R h) (1) v = ∆t (2) Δt (ϕ − ϕ )(R + h) v = 2 1 (2) where λ1,2 and φ1,2 are, respectively, longitudes∆t and latitudes of the tracked cloud features

wherein theλ1,2 firstand andϕ1,2 theare, second respectively, images; longitudes R = 6051.8 and kmlatitudes is the radius of the of tracked Venus; cloud h = 46 features km is the inassumed the ﬁrst and mean the altitude second of images; the features;R = 6051.8 Δt iskm the istime the interval radius of between Venus; htwo=46 images. km is the assumed mean altitude of the features; ∆t is the time interval between two images.

Figure 3. Examples of images by VIRTIS in 1.74 µm, taken from a slant distance of 60,000–65,000 km: (a)Figure orbit 71, 3. Examples data cube of 01, images 30 June by 2006VIRT 15:06;IS in 1.74 (b) µm, orbit taken 367, from data a cube slant 02, distance 22 August of 60,000–65,000 2007 21:44; (c)km: orbit (a 569,) orbit data 71, cube data 05, cube 10 November01, 30 June 20072006 16:11;15:06; ((db)) orbitorbit 812,367, datadata cubecube 04,02, 1022 JuneAugust 2008 2007 20:15. 21:44; (c) orbit 569, data cube 05, 10 November 2007 16:11; (d) orbit 812, data cube 04, 10 June 2008 20:15. VIRTIS-M nightside images in 1.74 µm have a low contrast value. To increase contrast of the cloud features, we used 2D-wavelet filtering with the Registax software (http: //www.astronomie.be/registax/)[18,23,24]. An example of this filter application is shown in Figure4, increasing the Michelson contrast value of the image from 0.75 to 0.99. This technique is especially efficient for cloud details in middle latitudes. It allows us to increase the number of identified cloud features per image pair and provide more uniform spatial coverage through retrieved velocity vectors. In the equatorial region at 0–40◦ S latitude, cloud details are small and have high contrast, and therefore can be easily identified (markers 1–4 in Figure4a). In middle latitudes, cloud details become low-contrast and stretched along the latitudes. Their identification improves after the 2D-wavelet filtering (markers 5, 6 in Figure4b). Atmosphere 2021, 12, x FOR PEER REVIEW 5 of 16

VIRTIS-M nightside images in 1.74 µm have a low contrast value. To increase contrast of the cloud features, we used 2D-wavelet filtering with the Registax software (http://www.astronomie.be/registax/) [18,23,24]. An example of this filter application is shown in Figure 4, increasing the Michelson contrast value of the image from 0.75 to 0.99. This technique is especially efficient for cloud details in middle latitudes. It allows us to increase the number of identified cloud features per image pair and provide more uniform spatial coverage through retrieved velocity vectors. In the equatorial region at 0–40° S latitude, cloud details are small and have high contrast, and therefore can be easily identified (markers 1–4 in Figure 4a). In middle latitudes, cloud details become low-contrast and stretched along the latitudes. Their identification improves after the Atmosphere 2021, 12, 186 2D-wavelet filtering (markers 5, 6 in Figure 4b). 5 of 13

Figure 4. Example of applying a 2D-wavelet filter to a VIRTIS-M image (data cube 569_13). Arrows indicate examples of identified cloud details used in the wind velocity retrieval. (a): original image, Figure 4. Example of applying a 2D-wavelet filter to a VIRTIS-M image (data cube 569_13). Arrows (bindicate): same image examples after of filter identified application. cloud details used in the wind velocity retrieval. (a): original image, (b): same image after filter application. A single measurement error can be attributed to each retrieved velocity vector. It is a positioning error of the coordinates of the identified cloud details, and it is dependent on A single measurement error can be attributed to each retrieved velocity vector. It is a the pixel size. The errors vary from 5–10 m s−1 closer to the center of the planetary disk positioning error of the coordinates of the identified cloud details, and it is dependent on (usually in near polar latitudes) to 30–40 m s−1 near the limb (usually in near equatorial the pixel size. The errors vary from 5–10 m s−1 closer to the center of the planetary disk latitudes), as was estimated for the VIRTIS-M images previously [19]. Due to high errors (usually in near polar latitudes) to 30–40 m s−1 near the limb (usually in near equatorial and potential cloud feature distortions, the 5–10◦ area near the limb, and therefore was latitudes), as was estimated for the VIRTIS-M images previously [19]. Due to high errors avoided during the analysis. and potential cloud feature distortions, the 5–10° area near the limb, and therefore was 3.avoided Results during the analysis. Most of the data obtained by VIRTIS-M covers middle and high latitudes of the 3. Results Southern hemisphere on the night side with the majority of the data cubes around midnight. However,Most we of obtained the data a disproportionatelyobtained by VIRTIS-M high numbercovers middle of vectors and at thehigh low latitudes and middle of the latitudesSouthern because hemisphere of finer on cloud the morphology,night side with which the resultedmajority in of more the data cloud cubes features around to track mid- (Figuresnight. 1However, and2). The we 1.74 obtainedµm VIRTIS-Ma disproportiona data, separatedtely high innumber four periods of vectors of observations, at the low and aremiddle described latitudes in Table because1. of finer cloud morphology, which resulted in more cloud fea- turesWhen to track obtaining (Figures mean 1 and values 2). The for 1.74 our research,µm VIRTIS-M a two-step data, approachseparated wasin four made periods every of time.observations, First, the velocity are described vectors in were Table averaged 1. on a longitude-latitude or local time-latitude grid withinWhen each obtaining orbit. Second,mean values orbits for were our averagedresearch, ona two-step the same approach grid. Characteristics was made every of thetime. analyzed First, the mean velocity atmospheric vectors motionwere averaged will be consideredon a longitude-latitude in the subsections or local below. time-latitude grid within each orbit. Second, orbits were averaged on the same grid. Characteristics of the 3.1.analyzed Local Time mean Dependence atmospheric motion will be considered in the subsections below. The distributions of mean zonal and meridional wind speed in local time-latitude are given in Figure5. The mean zonal speed in the middle latitudes reaches −60 m s−1, and this result is in agreement with the superrotation mode and previous measurements [5,11]. There is a slight westward deceleration (1–5 m s−1, depending on the latitude) of the zonal speed, i.e., towards the morning terminator. The nightside lowest speed (in absolute values), −58 m s−1, is found at 4–5 h LT, whereas the highest u maxima of −64 m s−1 are located at 19.5–21 and 23–24 h LT. Figure6 shows local time profiles of zonal speed for cloud features found in three latitude ranges. For a confidence interval of 99% standard error, the evening-to-morning deceleration in middle latitudes is statistically significant. In the equatorial region, two zonal speed minima at 21 and 4 h LT are observed. Atmosphere 2021, 12, x FOR PEER REVIEW 6 of 16

3.1. Local Time Dependence The distributions of mean zonal and meridional wind speed in local time-latitude are given in Figure 5. The mean zonal speed in the middle latitudes reaches –60 m s−1, and this result is in agreement with the superrotation mode and previous measurements [5,11]. There is a slight westward deceleration (1–5 m s−1, depending on the latitude) of the zonal speed, i.e., towards the morning terminator. The nightside lowest speed (in absolute values), –58 m s−1, is found at 4–5 h LT, whereas the highest u maxima of –64 m s−1 are located at 19.5–21 and 23–24 h LT. Figure 6 shows local time profiles of zonal speed for cloud features found in three latitude ranges. For a confidence interval of 99% standard error, the evening-to-morning deceleration in middle latitudes is statistically signifi- Atmosphere 2021, 12, 186 cant. In the equatorial region, two zonal speed minima at 21 and 4 h LT are observed.6 of 13

AtmosphereFigure 2021 5. Mean, 12, x zonalFOR PEER (a) and REVIEW meridional (b) speed in the lower clouds as a function of local time and latitude. Areas where7 of 16

no velocity vectors were available are left blank. Figure 5. Mean zonal (a) and meridional (b) speed in the lower clouds as a function of local time and latitude. Areas where no velocity vectors were available are left blank.

◦ Figure 6. Local time profiles of the zonal wind speed constrained in latitude bins of 5–20 S(a), 20–40◦ S(b) and 40–60◦ S(c). Error bars show standard error for a 99% confidence interval. Figure 6. Local time profiles of the zonal wind speed constrained in latitude bins of 5–20° S (a), 20– 40° SThe (b) meridionaland 40–60° Sspeed (c). Error is predominantlybars show standard northward error for (equatorward)a 99% confidence with interval. the values in the range 0–3 m s−1. There is a statistically significant westward (towards the morning terminator)The meridional acceleration speed across is predominantly all night side, nort morehward pronounced (equatorward) in the middle with the and values high in latitudesthe range than 0–3 in m the s−1 low. There (Figure is a 7statistically). After the significant evening terminator, westward at (towards 19–20 h LTthe inmorning high terminator) acceleration across all night side, more pronounced in the middle and high latitudes than in the low (Figure 7). After the evening terminator, at 19–20 h LT in high latitudes, the mean meridional speed changes direction and becomes southward (poleward). Additionally, the meridional speed has negative values in low latitudes between 19 and 1 h LT. This area coincides with one of the zonal speed maxima.

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latitudes, the mean meridional speed changes direction and becomes southward (poleward). Atmosphere 2021, 12, x FOR PEER REVIEWAdditionally, the meridional speed has negative values in low latitudes between 19 and8 1of h 16

LT. This area coincides with one of the zonal speed maxima.

◦ Figure 7. Local time profile of the meridional wind speed constrained in latitude bins of 5–20 S(a), 20–40◦ S(b) and 40–60◦ S(c). Error bars show standard error for a 99% confidence interval. Figure 7. Local time profile of the meridional wind speed constrained in latitude bins of 5–20° S (a), 3.2.20–40° Latitudinal S (b) and Dependence 40–60° S (c). Error bars show standard error for a 99% confidence interval. Mean latitudinal profiles of the zonal and meridional wind speed are shown in Figure3.2. Latitudinal8 . Zonal speed Dependence stays unchanging at −60 m s−1 between 20◦ S and 40◦ S. It gradually increasesMean both latitudinal northward profiles and of southward the zonal and of this meri latitudedional wind range. speed To theare shown south, in between Figure 8. 40Zonal◦ S and speed 60◦ S,stays a jet-like unchanging increase at by–60 2–4 m ms−1 sbetween−1 was revealed.20° S and Southward40° S. It gradually of 60◦ S increases mean zonalboth speed northward decreases and southward to zero at the of this South latitude Pole. range. To the south, between 40° S and 60° S, a jet-likeIn most increase of the by Southern 2–4 m s−1 Hemisphere, was revealed. meanSouthward meridional of 60° S speed mean haszonal a positivespeed decreases sign, indicatingto zero at that the theSouth flow Pole. is directed north, towards the equator. This is not the case, however, for latitudes north of 15–20◦ S, as the meridional wind likely changes its sign to negative and horizontal flow changes to south-poleward (until about 5◦ S). In the equatorial region, the sign of the meridional wind changes abruptly to be positive, and up to 10◦ N, the horizontal flow reverts to North-poleward. We found that the sign change of the meridional wind (from positive to negative) at 20◦ S coincides with the increase of the zonal speed (2–5 m s−1). From the fact that we detect two flows moving towards each other, we concluded that we could observe levels at different altitudes north and south of 20◦ S. Despite sparse data, these variations are significant enough to be contained within a 99% confidence interval.

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Figure 8. Mean proﬁles of the zonal (a) and meridional (b) winds in the lower clouds of Venus on the nightside from the full VIRTIS-M dataset. The average values were calculated for 2.5◦ latitude bins. Figure 8. Mean profiles of the zonal (a) and meridional (b) winds in the lower clouds of Venus on Error bars show standard errors for a 99% conﬁdence interval. the nightside from the full VIRTIS-M dataset. The average values were calculated for 2.5° latitude 3.3.bins. Longitudinal Error bars show Dependence standard errors for a 99% confidence interval.

RecentIn most works of the have Southern shown Hemisphere, how Venus topographymean meridional can influence speed has atmospheric a positive sign, motion onindicating different that levels, the at flow the cloud is directed top [16 –north,18,20 ,25towards] and at the 90–110 equator. km [19This]. To is explainnot the observed case, variations,however, for aforementioned latitudes north research of 15–20° suggested S, as the meridional that stationary wind gravitylikely changes waves its emerge sign to near thenegative surface and caused horizontal by the flow large changes highland to structures,south-poleward terrae (until and regii.about Topography-induced5° S). In the equa- influencetorial region, on the the lower sign of cloud the meridional motion was wind not changes investigated abruptly until to results be positive, of the and IR2 up camera to onboard10° N, the Akatsuki horizontal showed flow reverts no influence to North-poleward. of topography, coupled with the fact that they longitudeWe found variations that the cannot sign bechange separated of the frommeridi theonal local wind time (from effects positive [13]. to negative) at 20° ForS coincides VIRTIS-M with data the uncoupling, increase of the the zonal longitudinal speed (2–5 variations m s−1). fromFrom thethelocal fact that time we varia- tionsdetect poses two theflows same moving challenge. towards Mean each wind other, speed we concluded distribution that (Figure we could9) showsobserve variations levels acrossat different the Southern altitudes Hemisphere. north and south of 20° S. Despite sparse data, these variations are significant enough to be contained within a 99% confidence interval.

3.3. Longitudinal Dependence Recent works have shown how Venus topography can influence atmospheric motion on different levels, at the cloud top [16–18,20,25] and at 90–110 km [19]. To explain observed variations, aforementioned research suggested that stationary gravity waves emerge near the surface caused by the large highland structures, terrae and regii. To- pography-induced influence on the lower cloud motion was not investigated until results of the IR2 camera onboard Akatsuki showed no influence of topography, coupled with the fact that they longitude variations cannot be separated from the local time effects [13]. For VIRTIS-M data uncoupling, the longitudinal variations from the local time variations poses the same challenge. Mean wind speed distribution (Figure 9) shows variations across the Southern Hemisphere.

Figure 9. Longitudinal distribution of the zonal (a) and the meridional (b) wind velocities from

VIRTIS-M data, indicated by isolines. Figure 9. Longitudinal distribution of the zonal (a) and the meridional (b) wind velocities from VIRTIS-MStrong data, accelerationindicated by isolines. up to −70 m s−1 of the zonal wind above the plains south of Aphrodite Terra is the most prominent feature of the zonal wind distribution; however, the −1 dataStrong in this acceleration area consists up of to only –70 10–50m s of vectors the zonal per awind 10◦ ×above10◦ bin.the Theplains slowest south meanof zonal Aphrodite Terra is the most prominent feature of the zonal wind distribution; however, wind of up to −58 m s−1 is located in the middle latitudes between 210◦ and 260◦ longitude, the data in this area consists of only 10–50 vectors per a 10° × 10° bin. The slowest mean corresponding to the area surrounding−1 Imdr Regio on the surface. The meridional speed in zonal wind of up to –58 m s is located in the middle◦ ◦latitudes between 210° and 260°◦ ◦ longitude,the middle corresponding latitudes is to closer the area to zero surrounding at 220 –350 Imdr longitude,Regio on the whereas surface. atThe 40 me-–200 it can −1 ridionalreach up speed to 5–6 in the m smiddlein the latitudes equatorward is closer to direction. zero at 220°–350° longitude, whereas at 40°–200° it can reach up to 5–6 m s−1 in the equatorward direction. Figure 10 provides a more detailed look into the behavior of zonal wind in the middle latitudes. Here we consider the changes in wind speed in the 40°–50° S longitude bin. From 180° eastward, zonal speed decelerates from 62–63 m s−1 to 57 m s−1 at 220°– 240°, then further eastward accelerates back to 62–63 m s−1 at around 300° longitude. Importantly, average local time of the vectors in the aforementioned latitude and longitude range does not change sharply (no more than 0.5 h between any of the 10° × 10° bins); therefore, we rule out local time bias related to variations described in Section 3.1. Meridional wind speed does not manifest any significant change in this latitude bin.

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Figure 10 provides a more detailed look into the behavior of zonal wind in the middle latitudes. Here we consider the changes in wind speed in the 40◦–50◦ S longitude bin. From 180◦ eastward, zonal speed decelerates from 62–63 m s−1 to 57 m s−1 at 220◦–240◦, then further eastward accelerates back to 62–63 m s−1 at around 300◦ longitude. Importantly, average local time of the vectors in the aforementioned latitude and longitude range does not change sharply (no more than 0.5 h between any of the 10◦ × 10◦ bins); therefore, we rule out local time bias related to variations described in Section 3.1. Meridional wind Atmosphere 2021, 12, x FOR PEER REVIEW 11 of 16 speed does not manifest any signiﬁcant change in this latitude bin.

Figure 10. Longitudinal profiles (160–360◦) of the zonal (a) and the meridional (b) wind speed in the ◦ ◦ 40Figure–50 10.S latitude Longitudinal bin. Errorprofiles bars (160–360°) show standard of the zonal error (a) forand athe 99% meridional confidence (b) wind interval. speed in the 40°–50° S latitude bin. Error bars show standard error for a 99% confidence interval. 4. Discussion 4. DiscussionThe results of our research expand on the previous partial analysis of VIRTIS-M data. MainThe wind results speed of values our research correspond expand with on [5th,11e previous] within thepartial standard analysis error of VIRTIS-M limits. A similar east-to-westdata. Main wind increase speed of values the meridional correspond speedwith [5,11] was within reported, the standard as well as error the limits. acceleration A of thesimilar zonal east-to-west speed in middle increase latitudes. of the meridion However,al speed the was expansion reported, of as analyzed well as the data accel- allowed us toeration take a of more the zonal detailed speed look in middle at the lowerlatitude clouds. However, motion, the discerning expansion localof analyzed time, latitudedata and longitude-dependentallowed us to take a more trends detailed that look previously at the lower were cloud not detected.motion, discerning Comparison local time, with NIMS andlatitude ground-based and longitude-dependent observations trends [6–10] that also previously shows agreement were not detected. of the mean Comparison values within theirwith errorNIMS limits. and ground-based observations [6–10] also shows agreement of the mean values within their error limits. The meridional circulation is organized as Hadley cells. A theory suggests the exis- The meridional circulation is organized as Hadley cells. A theory suggests the ex- tenceistence of of several several direct direct and and backward backward cells [2]; [2]; however, however, experimentally experimentally only only one one direct direct cell wascell confirmed,was confirmed, in thein the upper upper clouds. clouds. Gene Generalral circulation circulation models models (GCM) (GCM) have shown have shownthat that severalseveral meridionalmeridional circulation circulation cells cells can can exist exist in the in thelower lower clouds clouds [26]. Detailed [26]. Detailed observations observations fromfrom UVUV VMC, Pioneer Pioneer Venus Venus and and ground-based ground-based observations observations showed showedthe South thepole South di- pole directedrected branch branch at the at theupper upper boundary boundary of clou ofds clouds (68–72 (68–72km), and km), the andbackward the backward branch di- branch directedrected toto the the equator equator from from IR VMC IR VMC near the near upper the boundary upper boundary of middle of clouds middle [18,27,28]. clouds [18,27,28]. AsAs waswas discusseddiscussed (in Section 3.2),3.2), the the fact fact that that we we see see two two flows flows moving moving towards towards each othereach northwardother northward and and southward southward from from 20 20°◦ S, S, signifies signifies thatthat we observe levels levels at atdif- different altitudesferent altitudes in the in clouds. the clouds. Additional Additional insight insight can can bebe achieved by by analyzing analyzing the thechange change in zonalin zonal wind wind speed speed when when the the meridional meridional speedspeed changes direction. direction. Based Based on on the the latitu- latitudinal dinal profile (Figure 8a) we selected two neighboring latitude ranges, where the mean profile (Figure8a) we selected two neighboring latitude ranges, where the mean meridional meridional speed is equatorward: 20° S–40° S and poleward: 3° S–20° S. We then calcu- speed is equatorward: 20◦ S–40◦ S and poleward: 3◦ S–20◦ S. We then calculated the mean lated the mean zonal speed for both ranges, which turned out to be −60.3 and −61.8 m s−1, − − −1 zonalrespectively, speedfor with both the ranges,standard which error of turned each value out to not be exceeding60.3 and 0.9 61.8m s−1 m. Taking s , respectively, into −1 withaccount the that standard the estimated error of vertical each value shear notin the exceeding lower clouds 0.9 is m <1 s m. s Taking−1 km−1 [5], into we account sug- that −1 −1 thegest estimated that the layer vertical in the shear equatorial in the region lower is located clouds about is <1 2 m km s higherkm (48–50[5], wekm) suggest than that the layer with the positive meridional speed (44–46 km). The higher level has a negative meridional speed and horizontal flow there moves towards the South Pole, whereas in the latitudes of 20° S–40° S, at the lower level, the meridional speed is positive and the horizontal flow moves towards the equator. We assume that we observed two fragments of the lower cloud direct Hadley cell: the South pole directed branch is located at 48–50

Atmosphere 2021, 12, 186 10 of 13

the layer in the equatorial region is located about 2 km higher (48–50 km) than the layer with the positive meridional speed (44–46 km). The higher level has a negative meridional Atmosphere 2021, 12, x FOR PEER REVIEW 12 of 16 speed and horizontal flow there moves towards the South Pole, whereas in the latitudes of 20◦ S–40◦ S, at the lower level, the meridional speed is positive and the horizontal flow moves towards the equator. We assume that we observed two fragments of the lower km, and thecloud equatorward direct Hadley return branch cell: the is Southat 44–46 pole km. directed Thus, these branch two isfragments located atcan 48–50 be km, and the considered equatorwardas the fragments return of the branch second is direct at 44–46 Hadley km. cell Thus, in the these lower two clouds fragments observed can at be considered as 1.74 µm. Thisthe proposition fragments is of also the supported second direct by the Hadley existence cell of in the the mid-latitude lower clouds jet observedat 40–60° S at 1.74 µm. This (Figure 8a), propositionwhich is most is likely also supported connected by to thethe existencelower cloud of thedirect mid-latitude Hadley cell. jet at 40–60◦ S (Figure8a) , We comparedwhich is our most results likely with connected previous to cloud the lower tracking cloud in other direct wavelengths Hadley cell. on the dayside from UVWe (VMC/VEX compared [22] our and results two Pion witheer previous Venus profiles cloud tracking for two different in other years wavelengths on the of observationdayside [29]) fromand IR UV (VMC/VEX (VMC/VEX [18]) [22 (F]igure and two11). Blue Pioneer arrows Venus in Figure profiles 11a for show two different years direction ofof the observation meridional [29 flow]) and in IRthe (VMC/VEX Southern (South-pole [18]) (Figure direction) 11). Blue and arrows Northern in Figure 11a show (North-poledirection direction) of Hemispheres the meridional on the flow upper in the boundary Southern of (South-poleclouds in the direction)poleward and Northern branch of the upper clouds Hadley cell (at 70 km). The backward flow to the equator is (North-pole direction) Hemispheres on the upper boundary of clouds in the poleward found at around 54–58 km in middle clouds and is shown by a red arrow. Result obtained branch of the upper clouds Hadley cell (at 70 km). The backward flow to the equator is in 1.74 µm is shown by green color and consists of 3 arrows: (1) an equatorward flow found at around 54–58 km in middle clouds and is shown by a red arrow. Result obtained south of 20° S, where the direction coincides with the red arrow; (2) a South-pole directed in 1.74 µm is shown by green color and consists of 3 arrows: (1) an equatorward flow south flow from 20° S to the equator, where the direction coincides with the blue arrow in the of 20◦ S, where the direction coincides with the red arrow; (2) a South-pole directed flow Southern Hemisphere; (3) a North-pole directed flow from the equator to 10° N, where from 20◦ S to the equator, where the direction coincides with the blue arrow in the Southern the direction coincides with the blue arrow in the Northern Hemisphere, e.g., ◦with the direction ofHemisphere; the zonal wind (3) aon North-pole the upper directedboundary flow of clouds from thein Northern equator to Hemisphere. 10 N, where the direction Thus, greencoincides arrows indicate with the fragments blue arrow of in the the lower-cloud Northern Hemisphere, direct Hadley e.g., cell, with and the a direction of the symmetricalzonal lower wind cloud on Hadley the upper cell boundaryin the Northern of clouds Hemisphere. in Northern From Hemisphere. the equator Thus,and green arrows up to 10° Nindicate (VIRTIS fragmentsdata on dynamics of the lower-cloudfor higher northern direct Hadleylatitudes cell, are not and available) a symmetrical the lower cloud ◦ meridional Hadleywind changes cell in theits sign Northern to positive Hemisphere.; the horizontal From the flow equator changes and its up direction to 10 N (VIRTIS data towards theon North dynamics Pole. At for these higher latitudes, northern th latitudese horizontal are flow not available)toward the the North meridional Pole is wind changes likely to correspondits sign to to positive; the Northern the horizontal hemisphere flow branch changes of the itsdirect direction Hadley towards cell. the North Pole. At these latitudes, the horizontal flow toward the North Pole is likely to correspond to the Northern hemisphere branch of the direct Hadley cell.

Figure 11. (a) Mean direction of the meridional wind at different altitudes (arrows) overlaid on the thermal structure of the atmosphere in latitude-altitude coordinates from combined Venus Express and Akatsuki radio occultation experiment results, averagedFigure over both11. (a hemispheres) Mean direction [30 ].of We the changedmeridional the wind latitude at different sign to altitudes negative (arrows) to adopt overlaid the figure on tothe the Southern thermal structure of the atmosphere in latitude-altitude coordinates from combined Venus Express hemisphere. Numbers at the contours indicate the temperature in Kelvin. Latitudes represent both hemispheres assuming and Akatsuki radio occultation experiment results, averaged over both hemispheres [30]. We north-south symmetry.changed The the thermal latitude structuresign to negative is used to for adopt illustration the figure to designate to the Southern different hemisphere. levels in the Numbers Southern at Hemisphere. Blue arrows representthe contours UV cloud indicate tracking the temperature results (PV andin Kelvin VMC/VEX),. Latitudes red represent arrow: IRboth cloud hemispheres tracking fromassuming VMC/VEX, green arrows: 1.74 µmnorth-south (1740 nm) IRsymmetry. cloud tracking The thermal from structure VIRTIS/VEX. is used Dashed for illustration green arrows to designate indicate different branches levels of in Hadley cells that are not observablethe Southern in the Hemisphere. experiment. Blue (b) Meanarrows latitudinal represent UV profiles cloud of tracking the meridional results (PV wind and from VMC/VEX), several experiments; line colors correspondred arrow: with IR those cloud in tracking (a), line from types VMC/VEX, correspond gr witheen arrows: the legend. 1.74 µm Two (1740 vertical nm) linesIR cloud located tracking at v = 0 axis limit from VIRTIS/VEX. Dashed green arrows indicate branches of Hadley cells that are not observable the latitude range of the 1.74 µm cloud tracking profile (green line) where the meridional wind becomes south-poleward. in the experiment. (b) Mean latitudinal profiles of the meridional wind from several experiments; line colors correspond with those in (a), line types correspond with the legend. Two vertical lines located at v = 0 axis limit the latitude range of the 1.74 µm cloud tracking profile (green line) where the meridional wind becomes south-poleward.

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Observed deceleration of the zonal speed from evening to morning terminator is the most notable feature of the local time-dependent variations. A similar deceleration has been suggested for the middle clouds based on near-IR cloud tracking [18], although it was less pronounced than in our case at only up to 2 m s−1, close to the error margins. Emergence of the mid-latitude jet observed at the cloud top can be connected to a Hadley circulation cell [31]. In the lower clouds the jet found between 40◦ S and 60◦ S can as well be driven by Hadley circulation. This can also indirectly indicate that we observe fragments of a direct Hadley cell. Therefore, features described above repeat those of the upper cloud cell. Discovered longitudinal variations are in many instances comparable to the diurnal variations (up to ±5 m s−1). Moreover, searching for the influence of topography is challenging because VIRTIS nadir data do not cover any prominent highlands, such as Aphrodite Terra, instead covering several smaller ones, the tallest of which is Lada Terra (tallest areas are up to ~3 km peak altitude, located at 65–75◦ S/320–30◦ E). The notable deceleration of zonal speed, roughly in the coordinates of Imdr Regio, is a volcanic area with young lava flows and excess heat radiation [32], which as shown in Section 3.3, is stronger than any possible local time bias; however, other highlands such as Lada Terra (center at 60◦ S/20◦E), Themis Regio (center at 40◦ S/280◦ E) and Alpha Regio (center at 22◦ S/5◦ E) do not show any coherent signs of influence on the circulation. We can compare our results to the general circulation models. The AFES-Venus model [33] produced the same deceleration of the zonal wind from evening to morning terminator at the altitude of 50 km, as in our results (Figure5). The local time dependency for the meridional speed also shows similarities, as the poleward motion is found before midnight, and equatorward—after midnight. Jet-like increases of zonal speed at the lower cloud level near equator and in middle latitudes has been shown by the T63 GCM [34]. Longitudinal variations have also been simulated by the GCM at ~54 km [35]. Although the general behavior of wind velocity does not coincide with our results (Figure9), model meridional speed was found to show more variability compared to the zonal speed.

5. Conclusions In this work, the full set of VIRTIS data was processed and analyzed. It allowed us to study four times more data than in the previous works and to obtain some new findings. An experimental indication for the existence of the lower cloud direct Hadley cell was found for the first time. Although GCMs allow the existence of one or more cells in the lower atmosphere, they were not experimentally found before. Dynamics of the Venusian atmosphere is very variable (if we compare VIRTIS and Akatsuki measurements), and we were lucky that during VIRTIS observations, a lower cloud layer was arranged in such a way that in the same wavelength (1.74 µm), we could observe the levels at different altitudes in the atmosphere depending on latitude. Parallel with the change in the value of the zonal speed, we also observed the change of the sign of the meridional speed, which leads to a conclusion that there most likely are different circulation cells in the considered altitude range of the atmosphere. It is known that in the upper cloud meridional circulation is organized as a direct Hadley cell, with the upper branch directed to the pole at the altitude of 68–70 km and the lower one directed to the equator more than 10 km below. The mid-latitude jet is considered as being connected to the Hadley cell. Meridional flow directions of the upper cloud Hadley cell branches and the observed lower cloud cell branches show a correlation. The mid-latitude jet observed at 40–60◦ S in the lower clouds, most likely connected to the lower cloud cell, also resembles the jet in the upper cloud layer. Thus, by analogy with the direct Hadley cell in the upper cloud layer, we came to a conclusion that in 1.74 µm, we observe fragments of the direct Hadley cell in the lower cloud layer. Atmosphere 2021, 12, 186 12 of 13

Supplementary Materials: The following are available online at https://www.mdpi.com/2073-443 3/12/2/186/s1, The supplemental material that accompanies this work consists of a compressed file that contains an ASCII data file of retrieved wind velocity vectors and a description file detailing the contents of the data file. Author Contributions: Conceptualization, D.A.G., L.V.Z. and I.V.K.; Data curation, D.A.G. and I.V.K.; Formal analysis, L.V.Z. and I.V.K.; Funding acquisition, L.V.Z.; Investigation, L.V.Z., I.V.K. and M.V.P.; Methodology, D.A.G., L.V.Z. and I.V.K.; Project administration, L.V.Z.; Software, D.A.G., I.V.K. and A.V.T.; Supervision, L.V.Z.; Validation, I.V.K. and M.V.P.; Visualization, D.A.G., L.V.Z. and A.V.T.; Writing—original draft, D.A.G.; Writing—review & editing, L.V.Z. and I.V.K. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the program #AAAA-A18-118052890092-7 of the Ministry of High Education and Science of the Russian Federation. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data is contained within the article or Supplementary Material. Acknowledgments: The authors are grateful to the ESA Mission and Operations teams for flawless operations of the VIRTIS instrument, as well as VIRTIS Principal Investigators P. Drossart (LESIA— Observatoire de Paris, CNRS, UPMC Univ., Paris 06, Univ. Paris. Diderot, Meudon, France) and G. Piccioni (INAF-IAPS) and the ESA Planetary Science Archive (ftp://psa.esac.esa.int/pub/mirror/ VENUS-EXPRESS/VIRTIS/). Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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