Vertical‐Wind‐Induced Cloud Opacity Variation in Low Latitudes Simulated by a Venus GCM

Karyu, Hiroki; Kuroda, Takeshi; Itoh, Kunihiro; Nitta, Akira; Ikeda, Kohei; Yamamoto, Masaru; Sugimoto, Norihiko; Terada, Naoki; Kasaba, Yasumasa; Takahashi, Masaaki; Hartogh, P.

doi:10.1029/2022je007595

Cited by 2 publications

(6 citation statements)

References 91 publications

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“…Consequently, clouds form at the ascending motion of meridional circulation at low latitudes and are transported to mid-high latitudes by the circulation. Different from previous models (Ando, Takagi, et al, 2020;Imamura & Hashimoto, 1998;Karyu et al, 2023;Stolzenbach et al, 2023), our simulation also produces a weak Ferrel-like circulation in this region (Figure 4f). This circulation and Hadley-like circulation contributes to the transport of cloud mass to mid-high latitudes.…”

Section: Zonal-mean Meridional Distribution Of the Venus Cloudscontrasting

confidence: 99%

“…Similar mechanisms are also discussed by Imamura and Hashimoto (1998) and Karyu et al. (2023). Consequently, a meridionally decreasing cloud top structure is produced.…”

Section: Resultssupporting

confidence: 77%

“…This pattern is inconsistent with observations by Venus Express (Haus et al, 2014), where column cloud mass peaks at low and high latitudes. Some previous models (Ando, Takagi, et al, 2020;Imamura & Hashimoto, 1998;Karyu et al, 2023) have reproduced this feature but with small differences. The discrepancy of column cloud mass latitudinal variation between our model and the previous models should be related to different meridional circulation patterns simulated in the cloud deck.…”

Section: Zonal-mean Meridional Distribution Of the Venus Cloudsmentioning

confidence: 78%

“…Karyu et al. (2023) incorporated a simple cloud parameterization into a Venus GCM and studied the effects of gravity and Kelvin waves on cloud opacity variations. Due to the computational cost of accurately simulating cloud physics in 3D, all the above 3D Venus cloud models use a rather simple cloud representation, which is also the case in this work.…”

Section: Motivationmentioning

confidence: 99%

“…Stolzenbach et al (2023) presented the Venus GCM that first includes both photochemistry and clouds, and investigated the importance of the Hadley-type circulation to long-lived species. Karyu et al (2023) incorporated a simple cloud parameterization into a Venus GCM and studied the effects of gravity and Kelvin waves on cloud opacity variations. Due to the computational cost of accurately simulating cloud physics in 3D, all the above 3D Venus cloud models use a rather simple cloud representation, which is also the case in this work.…”

Section: Motivationmentioning

confidence: 99%

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Three‐Dimensional Venus Cloud Structure Simulated by a General Circulation Model

Shao,

Mendonça,

Dai

2024

JGR Planets

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The clouds have a great impact on Venus's energy budget and climate evolution, but its three‐dimensional structure is still not well understood. Here we incorporate a simple Venus cloud physics scheme into a flexible GCM to investigate the three‐dimensional cloud spatial variability. Our simulations show good agreement with observations in terms of the vertical profiles of clouds and H2SO4 vapor. H2O vapor is overestimated above the clouds due to efficient transport in the cloud region. The cloud top decreases as latitude increases, qualitatively consistent with Venus Express observations. The underlying mechanism is the combination of H2SO4 chemical production and meridional circulation. The mixing ratios of H2SO4 at 50–60 km and H2O vapors in the main cloud deck basically exhibit maxima around the equator, due to the effect of temperature's control on the saturation vapor mixing ratios of the two species. The cloud mass distribution is subject to both H2SO4 chemical production and dynamical transport and shows a pattern that peaks around the equator in the upper cloud while peaks at mid‐high latitudes in the middle cloud. At low latitudes, H2SO4 and H2O vapors, cloud mass loading and acidity show semidiurnal variations at different altitude ranges, which can be validated against future missions. Our model emphasizes the complexity of the Venus climate system and the great need for more observations and simulations to unravel its spatial variability and underlying atmospheric and/or geological processes.

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Section: Zonal-mean Meridional Distribution Of the Venus Cloudscontrasting

confidence: 99%

“…Similar mechanisms are also discussed by Imamura and Hashimoto (1998) and Karyu et al. (2023). Consequently, a meridionally decreasing cloud top structure is produced.…”

Section: Resultssupporting

confidence: 77%

Section: Zonal-mean Meridional Distribution Of the Venus Cloudsmentioning

confidence: 78%

Section: Motivationmentioning

confidence: 99%

Section: Motivationmentioning

confidence: 99%

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Three‐Dimensional Venus Cloud Structure Simulated by a General Circulation Model

Shao,

Mendonça,

Dai

2024

JGR Planets

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One-dimensional Microphysics Model of Venusian Clouds from 40 to 100 km: Impact of the Middle-atmosphere Eddy Transport and SOIR Temperature Profile on the Cloud Structure

Karyu,

Kuroda,

Imamura

et al. 2024

Planet. Sci. J.

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We conducted a simulation of H2SO4 vapor, H2O vapor, and H2SO4–H2O liquid aerosols from 40 to 100 km, using a 1D Venus cloud microphysics model based on the one detailed in Imamura & Hashimoto. The cloud distribution obtained is in good agreement with in situ observations by Pioneer Venus and remote-sensing observations from Venus Express (VEx). Case studies were conducted to investigate sensitivities to atmospheric parameters, including eddy diffusion and temperature profiles. We find that efficient eddy transport is important for determining upper haze population and its microphysical properties. Using the recently updated eddy diffusion coefficient profile by Mahieux et al., our model replicates the observed upper haze distribution. The H2O vapor distribution is highly sensitive to the eddy diffusion coefficient in the 60–70 km region. This indicates that updating the eddy diffusion coefficient is crucial for understanding the H2O vapor transport through the cloud layer. The H2SO4 vapor abundance varies by several orders of magnitude above 85 km, depending on the temperature profile. However, its maximum value aligns well with observational upper limits found by Sandor et al., pointing to potential sources other than H2SO4 aerosols in the upper haze layer that contribute to the SO2 inversion layer. The best-fit eddy diffusion profile is determined to be ∼2 m2 s−1 between 60 and 70 km and ∼360 m2 s−1 above 85 km. Furthermore, the observed increase of H2O vapor concentration above 85 km is reproduced by using the temperature profile from the VEx/SOIR instrument.

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Vertical‐Wind‐Induced Cloud Opacity Variation in Low Latitudes Simulated by a Venus GCM

Cited by 2 publications

References 91 publications

Three‐Dimensional Venus Cloud Structure Simulated by a General Circulation Model

Three‐Dimensional Venus Cloud Structure Simulated by a General Circulation Model

One-dimensional Microphysics Model of Venusian Clouds from 40 to 100 km: Impact of the Middle-atmosphere Eddy Transport and SOIR Temperature Profile on the Cloud Structure

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