Contrast sources for the infrared images taken by the Venus mission AKATSUKI
© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences; TERRAPUB. 2011
Received: 18 September 2010
Accepted: 24 January 2011
Published: 21 June 2011
A feasibility study has been carried out to look for the source of contrast that will be seen in the infrared images of Venus taken by the cameras on board AKATSUKI. This procedure used a cloud model based on the measurements of previous entry probes and radiative transfer calculations. The source of the small contrast expected in the 0.90-/xm dayside image was found to be due to inhomogeneity in the cloud optical thickness, with the variations in cloud altitude and temperature having little effect. The source of the large contrast expected in the 2.26-μm nightside image was also found to be due to inhomogeneity in the cloud optical thickness. We attempted to determine the representative altitude of the cloud layers, but this could not be specified to one particular layer. The brightness expected in the 2.02-μm dayside image was found to be affected by the cloud altitude, as expected since the 2.02-μm is in a moderate CO2 absorption band; however, it is also affected by the cloud optical thickness. The brightness expected in the 10-μm image was found to be affected mostly by temperature; however, the effects due to cloud optical thickness and cloud altitude are also important. It is necessary to use all of the information obtained at various wavelengths to gain a correct understanding of the brightness distribution of the Venus images taken by AKATSUKI.
The superrotation of Venus atmosphere is one of the most remarkable and mysterious phenomena in the solar system. Although several theories on its generation have been proposed (e.g., Gierasch, 1975), to date, the exact mechanism has not been identified. The main aim of the Japanese mission AKATSUKI is to elucidate this mechanism, and to this end, five cameras and a radio occultation instrument are on board. Since each camera uses different wavelengths, they are able to observe targets at various altitudes at the same time. The strategy of the AKATSUKI mission is to understand the acceleration mechanism by measuring various meteorological parameters in the acceleration region using cloud tracking and radio occultation techniques at various altitudes. The AKATSUKI mission and the instruments on board have been described in detail by Nakamura et al. (2007). Here, we discuss the contrast sources for the 0.90±0.005-µm dayside image of the 1-µm camera (IR1), the 2.26±0.03-µm nightside image and the 2.02±0.02-µm dayside image of the 2-µm camera (IR2), the 10±2-µm image of the 10-µm camera (LIR) and their representative altitudes.
A Venus atmosphere model, molecular line databases, a cloud model, and a radiative transfer calculation are necessary to calculate the brightness distribution on the Venus disk.
2.1 Cloud model
Mean optical thickness of cloud layers at 920 nm based mainly on Venera entry probe data summarized by James et al. (1997). Upper haze layers based on Pioneer Venus data (Crisp, 1986) are added. The ratios among the particle modes are from Knollenberg and Hunten (1980). The maximum positive and negative deviations are also determined from the same data set; however, those for the upper haze layers are just assumed to be 50%.
Upper haze (80–90 km)
Upper haze (70–80 km)
Upper (57–70 km)
Middle (50–57 km)
Lower (47.5–50 km)
The cloud model used in this study for calculating radiative transfer. Optical thickness of each mode in each layer (2 km thick) at 920 nm is represented.
Layer center altitude (km)
Optical thickness per 2 km
2.2 Radiative transfer calculation
Synthetic spectra were calculated by means of line-by-line method using the HITRAN 2004 molecular database (Rothman et al, 2005) and the CO2 HITEMP database (Wattson and Rothman, 1992; Pollack et al., 1993), the VIRA1985 model atmosphere (Keating et al., 1985), and a solar line atlas (Livingston and Wallace, 1991). The sub-Lorentz line shape is applied for CO2 in the same way as in Pollack et al (1993), and the Voigt line shape (Humlicek, 1992) is applied for the other gases. Scattering by the cloud particles is taken into account by using a plane-parallel radiative transfer code RSTAR (Nakajima and Tanaka, 1986) modified for the Venus atmosphere (G. L. Hashimoto, private communication) with the cloud model noted in the previous section (Table 2, Fig. 3). Cloud parameters of three modes, namely, 1, 2, and 3, are calculated by assuming a 75% H2SO4 solution for the particles based on the Mie theory (e.g., Crisp, 1986). In the RSTAR code, the refractive index of H2SO4 is taken from WCP-55 (1983).
3.1 Source of the contrast in the 0.90-µm image
3.2 Source of the contrast in the 2.26-µm nightside image
3.3 Representative altitude for the 0.90-µmdayside contrast and the 2.26-µm nightside contrast
Maximum contrast expected for the 0.90-µm dayside and 2.26-µm nightside images calculated for the maximum positive and negative deviations in each layer shown in Table 1.
Maximum contrast at 0.90-µm (%)
Maximum contrast at 2.26-µm (%)
Upper haze (70-90 km)
Upper (57−70 km)
Middle (50−57 km)
Lower (48−50 km)
As seen in Table 3, all layers, with the exception of the upper haze layer, have the potential to cause a contrast of ≥3% in the 0.90-µm dayside image. The data in Table 3 also show that all cloud layers, again with the exception of the upper haze layer, may cause a contrast of ≥100% in the 2.26-µm image.
3.4 The contrast source for the 2.02-µm dayside image and the 10-µm image
Carlson et al. (1991) reported that the contrast source of the 2.3-µm nightside image is located at 50 km. These authors based their conclusion on data obtained by the Galileo NIMS. According to their discussion, the contrast found in the 2.3-µm image (20:1) requires a tenfold change in cloud optical thickness at 2.3 μm. However, the brightness temperature deviation at 3.71 μm exceeds the observed value of 0.13 K if such large change does actually occur in the upper or middle cloud layer. They concluded that only a change in the lower cloud layer at around 50 km may satisfy both conditions. However, our results show a possibility that the contrast source may also be located in the middle or upper cloud region.
The 2.02-µm brightness is found to provide information on both cloud altitude and cloud optical thickness. The 10-µm brightness is found to give information on temperature, cloud optical thickness, and cloud altitude. In order to separate such cloud parameters one by one, it seems necessary to introduce information obtained at other wavelength regions. The cloud altitude deviation is determined from 2.02-µm brightness by using information on cloud optical thickness from the 0.90-µm dayside image; the temperature information may be determined from the 10-µm brightness by using the cloud optical thickness and the altitude information obtained from the 0.90-µm and the 2.02-µm regions.
The error associated with this procedure may be estimated as follows only if the random error of 0.3% in the 0.90-µm dayside image is important. The error in brightness of the 0.90-µm dayside image is expected to be 0.3% (Iwagami et al, in press), which is statistical noise due to fluctuations in photon number. This error corresponds to about unity in the optical thickness in the 0.90-µm image according to Fig. 5. Since the reference value of the total cloud optical thickness is 34, as noted in Table 2, such uncertainties of unity in cloud optical thickness may be converted into an error of 0.03 km in the cloud altitude deviation according to Fig. 7. The error in temperature by the 10-µm data is estimated to be 0.09 K by using the above uncertainties and information shown in Figs. 8 and 9.
It should be noted that the above discussion is the simplest and the most optimistic estimation of errors. The estimate given here means that the error caused by the random noise in the 0.90-µm image is negligible. If possible, we should take into account all uncertainties, such as instrumental errors (calibration errors, nonlinearity, temperature dependences, among others) and model errors (cloud parameters, gas parameters, among others). Also, we should validate the whole procudure with real data and simulataneous measurements from the ground or other missions.
A procedure to determine the source and the representative altitude of the contrast seen in infrared images has been carried out. We show that the source of the small contrast expected in the 0.90-µm image is mostly caused by inhomogeneity in cloud optical thickness. We also show that the source of the large contrast expected in the 2.26-µm nightside image is also caused by inhomogeneity in the cloud optical thickness. Our attempt to determine the representative altitudes of these cloud layers revealed that this spectral band is sensitive to any cloud region (upper, middle and lower), but not sensitive to the upper haze region. This result is not always consistent with results reported by other researchers (e.g., Belton et al, 1991; Carlson et al, 1991). Cloud altitude deviation determined from the 2.02-μm brightness may be affected by inhomogeneity in the cloud optical thickness. The temperature deviation determined from the 10-µm brightness was found to be affected by the deviations in cloud optical thickness and cloud altitude. Cloud optical thickness, cloud altitude, and temperature information may be determined separately by introducing information obtained from other wavelength regions. Future studies should consider acidity as a parameter in addition to cloud thickness, height, and temperature, as indicated by Tsang et al. (2010).
The authors thank the OpenCLASTER project for the usage of the RSTAR (system for transfer of atmospheric radiation) package in this research. The authors also thank Dr. G. L. Hashimoto for modifying the RSTAR code for Venus. The authors also thank the two referees, Drs. C. C. C. Tsang and N. I. Ignatiev, for their constructive comments.
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