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Initial products of Akatsuki 1-μm camera
- Naomoto Iwagami1Email authorView ORCID ID profile,
- Takeshi Sakanoi2,
- George L. Hashimoto3,
- Kenta Sawai3,
- Shoko Ohtsuki4,
- Seiko Takagi5,
- Kazunori Uemizu6,
- Munetaka Ueno7,
- Shingo Kameda8,
- Shin-ya Murakami9,
- Masato Nakamura9,
- Nobuaki Ishii9,
- Takumi Abe9,
- Takehiko Satoh9,
- Takeshi Imamura10,
- Chikako Hirose9,
- Makoto Suzuki9,
- Naru Hirata11,
- Atsushi Yamazaki9,
- Takao M. Sato9,
- Manabu Yamada12,
- Yukio Yamamoto9,
- Tetsuya Fukuhara8,
- Kazunori Ogohara13,
- Hiroki Ando14,
- Ko-ichiro Sugiyama15,
- Hiroki Kashimura16 and
- Toru Kouyama17
© The Author(s) 2018
- Received: 9 July 2017
- Accepted: 25 December 2017
- Published: 11 January 2018
- Dayside cloud
- Nightside surface
The Akatsuki mission to Venus, also called “Venus Climate Orbiter,” was planned to investigate the Venus meteorology and to solve the long-standing riddle of the atmospheric Super-Rotation. The strategy of Akatsuki to understand the mechanism of the Super-Rotation is to combine information from five nadir-viewing cameras and a horizon-viewing radio occultation instrument, to obtain various meteorological parameters at various heights. The overview of the mission is described in Nakamura et al. (2011), and its successful revival 5 years after the failure is in Nakamura et al. (2016). The Venus orbit insertion failure occurred in 2010; however, the insertion was successful in 2015 achieving a different orbit than initially planned.
Before the Akatsuki 1-μm camera, dayside imaging of Venus to retrieve wind field in the cloud region by using the 1-μm imaging has been performed by SSI (solid-state imaging) of the Galileo spacecraft at 986 nm (Belton et al. 1991) and by VIRTIS (Visible and Infrared Thermal Imaging Spectrometer) of Venus Express at 980 nm (Hueso et al. 2012). Both of them report mostly uniform westward zonal wind and slow meridional wind in the low and middle latitudes. The magnitude of the net meridional winds in Hueso et al. (2012) is below the measurement error and discards strong Hadley cell circulation at this atmospheric altitude in contrast to results in the UV (which sample higher altitudes) where the meridional winds are stronger and the Hadley cell circulation is evident. Hueso et al. (2015) with much better statistics and analysis of the data arrived at the same conclusion. Data from the Galileo spacecraft (Belton et al. 1991) have been reanalyzed by Peralta et al. (2007) who also found slow meridional winds below the measurement error. The westward wind speeds found in the 1-μm region are 65–75 m/s. This is slower than the nominal Super-Rotation speed of 100 m/s usually found in the UV imaging of the cloud top at around 65–72 km (Kawabata et al. 1980; Limaye and Suomi 1981; Belton et al. 1991; Peralta et al. 2007; Sanchez-Lavega et al. 2008; Ignatiev et al. 2009; Hueso et al. 2015). Some of the above concluded that the slower wind speed comes from the lower altitude sampled by the 1-µm images than in the UV region. Such estimation may be expected from the vertical wind shear of about + 1.5 m/s/km found by the Venera and the Pioneer Venus descent probes (summarized by Schubert 1983) between the surface and the cloud top.
On the nightside, there are several known IR windows that allow radiation to penetrate the clouds in the Venus atmosphere including 1.0–1.3-, 1.7- and 2.3-μm regions (Carlson et al. 1991). The 1.0–1.3-μm window has mostly been used for investigating surface properties. Lecacheux et al. (1993) and Meadows and Crisp (1996) found many topographic signatures from ground-based imaging. There are several discussions about the relationships among emissivity, topography, gravity and the possibility of active volcanos based on infrared observational data from the Venus Express (e.g., Mueller et al. 2008; Smrekar et al. 2010; Basilevsky et al. 2012), Galileo spacecraft (Hashimoto et al. 2008) and radar data from the Magellan spacecraft (Bondarenko et al. 2010). Meadows and Crisp (1996) also retrieved H2O abundance in the near-surface atmosphere to be 45 ppmv with this 1.0–1.3-μm window.
The 1.7- and 2.3-μm windows have mainly been used for quantification of gas abundances such as CO, H2O and HCl (e.g., Bezard and de Bergh 2007; Tsang et al. 2008; Iwagami et al. 2008, 2010; Marcq et al. 2008; Barstow et al. 2012; Arney et al. 2014) below the cloud (not exactly at the surface). They found an average H2O abundance of 25–35 ppmv with nearly uniform hemispherical distribution.
Cloud tracking on dayside images to obtain the wind field to investigate the generation mechanism of the Super-Rotation by combining information from other cameras and from radio occultation.
Nightside 1.01-μm imaging to discover active volcanos. If an active volcano is found and is consistently monitored, it will provide various insights into the interior of Venus as well as the origin and evolution of this next-door Earth-type planet. It will also be precious information to think about the past and future evolution of our planet Earth.
Quantification of the emissivity of the planetary surface and H2O abundance in the lower atmosphere by the combination of 0.90–0.97–1.01-μm images. The goal is to characterize the chemistry of the surface materials and the lower atmosphere to understand their current state and past evolution.
The present paper provides convenient and overall information about the Akatsuki 1-μm image data showing preliminary examples of data and analysis procedures.
The data used in this study are archived in PDS3 format. The archives have DATA_SET_IDs of VCO-V-IR1-2-EDR-V1.0, VCO-V-IR1-3-CDR-V1.0 and VCO-V-IR1-3-SEDR-V1.0. The first one includes raw data, and the second one includes calibrated data and information for calibration, and the third one includes geometry information calculated by the SPICE toolkit provided by NAIF/NASA, using the VCO SPICE kernels dataset, VCO-V-SPICE-6-V1.0. These data are available from the Akatsuki science data archive site at DARTS/JAXA, http://darts.isas.jaxa.jp/planet/project/akatsuki/. The data will also be available from the Atmospheres node and the NAIF node of the Planetary Data System of NASA, https://pds.nasa.gov.
The camera is described in Iwagami et al. (2011); however, some brief explanations and additional information are presented here.
Characteristics of the four channels of the 1-μm camera
Central wavelength (nm)
Peak transmission (%)
Typical exposure (s)
Typical S/N ratio
Nightside filters have a higher transmission around 75% at the ranges of interest. Figure 1c shows nightside 0.90-, 0.97- and 1.01-μm filter transmissions with expected Venus’ thermal emission spectra. The spectra are for various H2O surface abundances of 15, 30 and 60 ppmv. The 0.97- and 1.01-μm pair may be used to find out the H2O abundance in the near-surface atmosphere. The 0.97-μm output changes by a factor of two if the H2O mixing ratio changes from 15 to 60 ppmv (Iwagami et al. 2011). Also the pair of 0.90- and 1.01-μm radiances may give information of other surface properties such as emissivity distribution. The contribution functions for those nightside channels are found in Iwagami et al. (2011). The contribution for 1.01-μm radiance is mostly (89%) from the surface.
The 5-year cruise on space from the failure in orbit insertion in 2010 and the successful Venus orbit insertion in 2015 could have degraded the quality of the camera causing instrumental problems like a greater number of dead pixels. Fortunately, such degradation has been found to be minimal and well-contrasted images were obtained with the instrument. The reason for such healthy survival may be due to extremely quiet solar activity in the last 5 years. Although many dark spots have been found in recent images by deep inspection, fortunately, they may be removed by the flattening procedure. Such dark spots may be noticed in the flat image (e.g., Figs. 9, 10) as several negative spikes.
Sagittarius stars for alignment check and radiometric calibration
m v (mag)
T e (K)
K1 + IIIb
K1 + IIIb
A2III + A4 IV
Alignment check by stars on three days
C x Pixel**
C y Pixel
October 08, 2010
3.7W ± 2.8
3.4S ± 2.8
0.260cw ± 0.154
99.30 ± 0.27
February 24, 2016
3.0E ± 3.0
10.2S ± 3.0
0.250cw ± 0.152
99.30 ± 0.29
September 09, 2016
3.7E ± 3.1
10.8S ± 3.1
0.264cw ± 0.150
99.25 ± 0.30
After the successful insertion on December 07, 2015, and the start of regular data acquisition in Apr. 2016, dayside 0.90-μm images were obtained regularly showing good contrast, but all nightside 0.90-, 0.97- and 1.01-μm images present signal contamination from the dayside, and their acquisition requires specific planning pushing the dayside out of the field of view to avoid electric charge overflowed from the bright dayside part of the image into the nightside. This kind of observation has been performed regularly after July 21, 2016. However, such operation causes another kind of contamination. It causes a bias superposed on the nightside image; such bias seems to be due to instrumental internal reflections of the dayside image.
Unfortunately, data acquisition has been stopped since December 07, 2016, due to malfunction of the electronics and has not been resumed since then.
Smear noise correction
In Fig. 4a, a bright horizontal line is seen at the 513th line (brighter than the 514th line by about 20%) of the image. The cause of such a brightening is unknown, and it did not appear during the ground-based test operations. However, it is approximately corrected by the flattening procedure, fortunately, as shown in Fig. 4b. After all of this processing, the dayside images have a noise level of 0.3% which is suitable for the cloud-tracking procedure; this is demonstrated by the cloud-tracking tests in a latter section.
Quadrant brightness adjustment
When RAB is less than 0.5 or more than 2.0, which frequently occurs when the disk of Venus is not on the boundary, we set RAB = 1. RCD, RAC and RBD are estimated in the same way. If the center of Venus is in A or B region, we set R′ (the correction coefficient of top (AB)–bottom (CD) boundary) = RAC, and if it is in C or D region, we set R′ = RBD. The signals in B, C and D regions were multiplied by RAB, R′ and R′RCD, respectively.
Sensitivity coefficients for the four channels of the 1-μm camera
0.90 µm (day)
61.7 ± 4.7
0.90 µm (night)
0.0756 ± 0.0058
0.608 ± 0.070
1.35 ± 0.91
The values in the table differ from those in Iwagami et al. (2011) because of the difference in the method; the latter method utilized laboratory measurements (without considering the smear correction), whereas the present one relies on the star measurements. Because of uncertainty in the smear correction for the laboratory measurements, we use the star measurements for the radiometric calibration. The radiometric calibration here may include error due to difference between the actual spectral shape and the black body due to absorption structure; this is not included in the error in Table 4.
The standard exposure is 7.8 s for the dayside to have usual output of around 3000 ADU (full well is 10,000 ADU), and the fluctuation in noise level for dayside image is 5 ADU which seems to be mostly due to readout noise because the overall fluctuation in noise level for the nightside does not scale with exposure time. That is, it does not differ by a factor of four from that of dayside although the exposure duration differs by four times. The S/N (signal to noise) ratio of 600 is enough for the cloud tracking because the expected contrast is 3% as shown later. The standard exposure time for the nightside is 30.8 s. The fluctuation in thermal noise level seems to be much less than 5 ADU per 30.8 s when the detector is cooled to 260 K. The measured thermal noise level (not fluctuation) is around 40 ADU (2800 electrons)/30.8 s; this suggests a thermal noise fluctuation of 0.75 ADU (= 40 ADU/28001/2) which is much smaller than 5 ADU. The usual output of the 1.01-μm channel is around 500 ADU and satisfies a S/N ratio higher than 100, which is generally considered enough for a search of active volcanism (Iwagami et al. 2011); however, those of the 0.90- and 0.97-μm channels are around 150 ADU, which are less than expected, and may affect the quantification of H2O values and the spatial resolution of H2O abundance maps. The cause of this problem seems to be due to the readout noise which is higher than initially expected.
The reason why the representative height of the 0.90-μm dayside image is located at the cloud bottom comes from the fact “the source of 0.90 μm dayside contrast is inhomogeneous cloud thickness” as discussed by Takagi and Iwagami (2011). They checked three candidates (cloud thickness, cloud height and temperature) as the contrast source and performed simulations with radiative transfer calculation. They found that only inhomogeneous cloud thickness can be the source. This is due to the fact that the cloud particles show almost no absorption at 0.90 μm. However, the main source of such inhomogeneity seems to be due to inhomogeneity in the lower cloud, or in other words, the mode 3 particles. Descriptions of the modes of the Venus aerosols may be found in Knollenberg and Hunten (1980).
The representative height depends on the cloud model used. In the present paper, the center of mass of the population of the mode 3 particles was calculated by using an empirical cloud model of Takagi and Iwagami (2011) (in their Table 2 and Fig. 3). This cloud model is an average of cloud optical thickness measurements by six Venera and one Pioneer Venus descent probes modified to have nearly constant particle mixing ratios within each assumed layer (lower, middle and upper). Description of the layers may be found in James et al. (1997). The center of mass of the population of the mode 3 particles is found to be 51.3 km and that of all three modes is at 55.1 km. The most significant variation in the cloud thickness is expected to occur in the lower cloud layer (mostly with mode 3 particles); this is certainly seen as the largest spread of optical thickness measured by the descending probes in the lower cloud layer in Table 1 of Takagi and Iwagami (2011). The main information source for the images in Fig. 12a, b should locate at least between 51 and 55 km and probably is close to 51 km.
Figure 17b shows a simulated radiance of surface thermal emission based on the Magellan global topography data (Ford and Pettengill 1992). Vertical temperature profile of VIRA 1985 (Seiff et al. 1985) and uniform surface emissivity are assumed. Although a blurring effect due to scattering by cloud particles is taken into account with an averaging diameter of 100 km (Hashimoto and Imamura 2001), the attenuation by scattering of clouds is not calculated. Limb darkening observed in Fig. 17a is not reproduced in Fig. 17b.
Similarity between Fig. 17a, b clearly demonstrates that we sense the surface by using 1.01-μm window. Since the 1-μm region is located short-ward of the Planck function peak of the Venus surface emission at 4 μm (at 740 K), a small temperature difference results in a large radiance difference; in this case, 30 K difference in temperature causes 100% difference in radiance. Even though spatial inhomogeneity in cloud opacity affects the observation, we may be able to increase the accuracy of the measurement of the surface thermal emission by using cloud opacity estimated from 1.7- and/or 2.3-μm images taken by Akatsuki’s 2-µm camera. If an active volcano is found and is monitored with repeat observations, further information inside the planet Venus may be obtained; such information on the interior of the planet may help to understand the origin and evolution of the planet.
High-quality 0.90-μm dayside images were recorded regularly. Two examples show results similar to those reported by Galileo and Venus Express 1-μm imaging (e.g., Peralta et al. 2007 for the Galileo data; Sanchez-Lavega et al. 2008; and Hueso et al. 2015 for the VIRTIS data), i.e., an almost uniform westward zonal wind and weak meridional wind at low and middle latitudes are observed. It shows enough possibility to access the final goal “the generation mechanism of the Super-Rotation.”
The 1.01-μm nightside image shows topographic structures without large interference from cloud inhomogeneity and is suitable for the search of active volcanoes. The final goal of the nightside surface imaging is to investigate the origin and evolution of the planet Venus. The quantification of H2O mixing ratio in the near-surface atmosphere may have less spatial resolution than originally planned, but is expected to provide usable data to understand the amount and distribution of H2O near the surface.
NI has made contributions to conception and design. TS has made contributions to the design, data analysis and plotted Figs. 5, 6, 7, 8 and 10. GLH has made contributions to conception, design and data archiving. KS has made contributions to data analysis and interpretation. SO has made contributions to calibration data acquisition. ST has made contributions to data acquisition. KU and MU have made contributions to conception and design. SK performed data analysis, noise reduction and intensity calibration and wrote a part of the manuscript (“Image corrections and calibration” section and Appendix A). SM wrote a part of data pipeline processing program, archiving datasets, performed cloud tracking and wrote a data archiving part of the manuscript. MN has made contributions to conception and design. NI and TA have been involved in data acquisition. TS and TI have been involved in data analysis and interpretation. CH has made contributions to data analysis and interpretation. MS has been involved in data analysis and interpretation. NH has been involved in data acquisition and archiving. AY has been involved in data acquisition and data pipeline processing. TMS has been involved in data acquisition. MY has been involved in data acquisition and data pipeline processing. YY has been involved in data acquisition and archiving. TF has been involved in data acquisition. KO has made contributions to data analysis, interpretation and data pipeline processing. HA has been involved in data acquisition. KS, HK and TK have made contributions to data analysis and interpretation. All authors read and approved the final manuscript.
The authors thank all the people of ISAS and also of other institutions working for the Akatsuki project. The authors thank the people of manufactures designed, manufactured and operated the Akatsuki system. The authors thank two anonymous reviewers for many constructive comments including English usage. The authors thank Dr. Kevin McGouldrick for English grammar assistance. Also appreciated are very many people all over Japan and also over the world encouraging and supporting Akatsuki.
The authors declare that they have no competing interests.
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