Self-consistent retrieval of temperature profiles and cloud structure in the northern hemisphere of Venus using VIRTIS/VEX and PMV/VENERA-15 radiation measurements

Haus, Rainer; Kappel, David; Arnold, Gabriele

doi:10.1016/j.pss.2013.09.020

Cited by 45 publications

(134 citation statements)

References 65 publications

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“…Systematic difference with the cloud top altitudes reported by Ignatiev et al (2009) are discussed in details in Cottini et al (2012) and attributed to imperfect quality of the VIRTIS-M spectrum fitting. At longer wavelengths in the thermal IR spectral range at 4.5 mm (Lee et al, 2012;Haus et al, 2013) and 8 mm (e.g. Zasova et al, 2007) cloud tops are located deeper by several kilometers but demonstrate a similar latitudinal trend.…”

Section: Resultsmentioning

confidence: 90%

Water vapor near Venus cloud tops from VIRTIS-H/Venus express observations 2006–2011

Cottini

Ignatiev

Piccioni

et al. 2015

Planetary and Space Science

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Section: Resultsmentioning

confidence: 90%

Water vapor near Venus cloud tops from VIRTIS-H/Venus express observations 2006–2011

Cottini

Ignatiev

Piccioni

et al. 2015

Planetary and Space Science

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“…The night side data detected only the thermal emission from the atmosphere, whereas the day side measurements contained contributions from the scattered sunlight and solar-induced fluorescence. Different groups have analyzed the day and night side observations separately - Grassi et al ( , 2010Grassi et al ( , 2014; Migliorini et al (2012); Haus et al (2013Haus et al ( , 2014 and by Garate-Lopez et al (2015) using only the night-time data acquired at moderate emission angles (> 30°, solar zenith angles < 95°). The variability of total opacity inside the CO 2 band allowed retrieval of air temperatures from the cloud top level (about 100 mb, or ∼ 65 km at intermediate latitudes) up to 1 mb (∼ 85 km), with an effective resolution in the order of 5-7 km .…”

Section: Virtis Experiments On Venus Expressmentioning

confidence: 99%

“…Results of Grassi et al (2010) are essentially confirmed: more stringent acceptance criteria resulted in a wider cold collar region (polar dipole demonstrated it is particularly difficult to model with the new retrieval algorithm), while improved confidence allowed the authors to discuss an average field at the 1.4 bar level, that turned out to be roughly symmetric around midnight. Haus et al (2013) also analyzed VIRTIS-M data independently and presented an improved treatment of the VIRTIS-M data, using a more complete treatment of aerosols, made possible by including the 2.3 and 1.74 μm radiation measured by VIRTIS-M in the retrieval process. Moreover, the authors developed a sophisticated pre-processing pipeline that allowed Haus et al to improve radiometric accuracy of the measurements prior to retrieval.…”

Section: Figmentioning

confidence: 99%

Venus Atmospheric Thermal Structure and Radiative Balance

et al. 2018

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From the discovery that Venus has an atmosphere during the 1761 transit by M. Lomonosov to the current exploration of the planet by the Akatsuki orbiter, we continue to learn about the planet's extreme climate and weather. This chapter attempts to provide a comprehensive but by no means exhaustive review of the results of the atmospheric thermal structure and radiative balance since the earlier works published in Venus and Venus II books from recent spacecraft and Earth based investigations and summarizes the gaps in [1411][1412][1413][1414] 1986). Thus, most of the new information about the atmospheric thermal structure has come from different remote sensing (Earth based and spacecraft) techniques using occultations (solar infrared, stellar ultraviolet and orbiter radio occultations), spectroscopy and microwave, short wave and thermal infrared emissions. The results are restricted to altitudes higher than about 40 km, except for one investigation of the near surface static stability inferred by Meadows and Crisp (J. Geophys. Res. 101:4595-4622, 1996) from 1 μm observations from Earth. Little information about the lower atmospheric structure is possible below about 40 km altitude from radio occultations due to large bending angles. The gaps in our knowledge include spectral albedo variations over time, vertical variation of the bulk composition of the atmosphere (mean molecular weight), the identity, properties and abundances of absorbers of incident solar radiation in the clouds. The causes of opacity variations in the nightside cloud cover and vertical gradients in the deep atmosphere bulk composition and its impact on static stability are also in need of critical studies. The knowledge gaps and questions about Venus and its atmosphere provide the incentive for obtaining the necessary measurements to understand the planet, which can provide some clues to learn about terrestrial exoplanets.

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“…Extinction coefficient distributions in the [15–40] μ m range for the two different cloud models used,

\log (k_{cld})

in m −1 : (a) for the Haus et al [, ] (low latitudes) cloud model and (b) for the Zasova et al [] (below 70 km) and Wilquet et al [] (above) cloud model.…”

Section: Net Exchange Rate Analysismentioning

confidence: 99%

“…However, understanding in detail the temperature profile is still a challenge. Above and within the clouds, data sets and modeling have helped to constrain the cloud characteristics [ Zasova et al , , ; Haus et al , ; Wilquet et al , ], though their latitudinal variations still need additional investigations [ Wilson et al , ]. Many uncertainties remain in the opacity of the gas below the clouds, where the pressure and temperature conditions make it difficult to get experimental constraints.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the radiative budget of the Venusian atmosphere based on infrared Net Exchange Rate formalism

Lebonnois

Eymet²,

Lee

et al. 2015

JGR Planets

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A detailed one-dimensional analysis of the energy balance in Venus atmosphere is proposed in this work, based on the Net Exchange Rate formalism that allows the identification in each altitude region of the dominant energy exchanges controlling the temperature. Well-known parameters that control the temperature profile are the solar flux deposition and the cloud particle distribution. Balance between solar heating and infrared energy exchanges is analyzed for each region: upper atmosphere (from cloud top to 100 km), upper cloud, middle cloud, cloud base, and deep atmosphere (cloud base to surface). The energy accumulated below the clouds is transferred to the cloud base through infrared windows, mostly at 3-4 μm and 5-7 μm. The continuum opacity in these spectral regions is not well known for the hot temperatures and large pressures of Venus's deep atmosphere but strongly affects the temperature profile from cloud base to surface. From cloud base, upward transport of energy goes through convection and short-range radiative exchanges up to the middle cloud where the atmosphere is thin enough in the 20-30 μm window to cool directly to space. Total opacity in this spectral window between the 15 μm CO 2 band and the CO 2 collision-induced absorption has a strong impact on the temperature in the cloud convective layer. Improving our knowledge of the gas opacities in these different windows through new laboratory measurements or ab initio computations, as well as improving the constraints on cloud opacities would help to separate gas and cloud contributions and secure a better understanding of Venus's atmosphere energy balance.

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Self-consistent retrieval of temperature profiles and cloud structure in the northern hemisphere of Venus using VIRTIS/VEX and PMV/VENERA-15 radiation measurements

Cited by 45 publications

References 65 publications

Water vapor near Venus cloud tops from VIRTIS-H/Venus express observations 2006–2011

Water vapor near Venus cloud tops from VIRTIS-H/Venus express observations 2006–2011

Venus Atmospheric Thermal Structure and Radiative Balance

Analysis of the radiative budget of the Venusian atmosphere based on infrared Net Exchange Rate formalism

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