Shin-Ya Murakami

The Near-Infrared Spectrometer (NIRS3) onboard Hayabusa2 observed asteroid (162173) Ryugu, searching especially for signatures of water-bearing minerals. However, during the mission, absolute reflectance measured by the Telescopic Optical Navigation Camera (ONC-T) and NIRS3 showed a systematic offset. Additionally, touchdown operations have modified the instrumental response, which has made post-second-touchdown data less reliable. Correction of these issues is crucial to interpret the subtle spectroscopic differences across the surface, better understand the origin and evolution of carbonaceous asteroids, and support the Hayabusa2 ♯ mission’s future observations of the asteroids (98943) Torifune and 1998 KY26. We used Ryugu observations at different mission phases for relative calibrations and lunar observations for the absolute calibration. Moon spectra acquired during the first Earth swing-by were compared to simulated ones from photometric models based on lunar orbiter and ground-based data. We then applied the updated calibration to the full Hayabusa2 proximity phase data set, enabling disk-resolved global and regional photometric analyses. We showed that the data obtained following the first and second touchdowns required downscaled corrections of 5.4% ± 1.8% and 10.3% ± 0.4% at 2 μ m, respectively, while the absolute calibration revealed that NIRS3 reflectance was underestimated by about 8% compared with the original calibration. Our new photometric parameters are consistent with previous studies and indicate a weak east–west dichotomy in phase ratio and phase reddening, pointing to higher surface roughness and higher abundance of fine-grained regolith in Ryugu's eastern hemisphere.

Asteroid (162173) Ryugu, visited by the JAXA Hayabusa2 mission, was extensively observed during the proximity phase with the NIRS3 near-infrared spectrometer (1.8 – 3.2 mm) [1,2]. The radiometric calibration of NIRS3 was initially obtained from ground-based measurements of a commercial blackbody. After the two touchdown (TD) maneuvers of the Hayabusa2 spacecraft, the instrumental response of the NIRS3 instrument was altered likely due to contamination by dust particles. Thorough analysis of all the Ryugu data obtained during the proximity phase showed systematic residual variations between data obtained during mission phases, indicating the need for further refinement of the radiometric calibration. The data obtained after TD1 were found to be about 5% brighter than the data before TD1, and the data after TD2 about 10% brighter. After improving the relative calibration of the NIRS3 dataset at the different mission phases, we also check and improve the absolute calibration of the instrument using the Moon observations acquired in December 2015 during the Hayabusa2 Earth gravity assist. Calibration method is as follows: (i) we used the photometrically-corrected radiance (i0=30 deg, e0=0 deg, α0=30 deg) lunar map derived from Kaguya/SP and Chandrayaan-1/M3 observations [4,5]; (ii) we applied the ROLO correction factor [3], which we updated to apply it to the SP data up to 2053 nm; (iii) from the NIRS3 footprint position on the Moon, we computed the average SP and M3 spectra and projected them to the NIRS3 observation geometries using their respective photometric model [4,5]; (iv) we finally derived a scale factor to match the two lunar models and the NIRS3 data in the wavelength range 1820 – 2053 nm. NIRS3 reflectance was underestimated by about 8% compared with the original calibration [1]. The updated calibration will support the future observations of the asteroids (98943) Torifune and 1998 KY26, the two targets of the Hayabusa2# extended mission.These new radiometrically corrected data enabled us to derive updated global near-infrared photometric properties of Ryugu, using all data from the proximity phase acquired between June 2018 to November 2019. After removing observations acquired with extreme illumination/observation geometries (i, e > 70 deg) and performing a 3D averaging binning (i, e, α), we derived the global disk-resolved phase curves and fitted these phase curves with the Hapke IMSA model for all wavelength channels, hence obtaining the variations of the Hapke parameters with the wavelength. The obtained parameters with this full dataset are consistent with previous studies [6,7]. An east-west dichotomy of the phase ratio and phase reddening is observed, likely consistent with a higher surface roughness in Ryugu eastern hemisphere.The photometric parameters are used to produce photometrically corrected (i0=30 deg, e0=0 deg, α0=30 deg) data. These radiometric and photometrically corrected NIRS3 data will be released through NASA PDS and JAXA DARTS.Acknowledgments: This work is supported by the JAXA Hayabusa2# International Visibility Enhancement Project.References: [1] Kitazato et al. (2019), Science, 364, 6437 [2] Iwata et al. (2017), SSR, 208 [3] Kouyama et al. (2016), PSS, 124 [4] Yokota et al. (2011), Icarus, 215, 2 [5] Besse et al. (2013), Icarus, 222 [6] Domingue et al. (2021), PSJ, 2:178 [7] Pilorget et al. (2021), Icarus, 355

The Hayabusa2 International Visibility Enhancement Project is engaged in activities to ensure that the scientific data returned by JAXA's Hayabusa2 mission are openly disclosed and accessible to both professional researchers and the general public. The observation data of the near-Earth asteroid (162173) Ryugu acquired by the Hayabusa2 onboard instruments are publicly available through JAXA's Data Archives and Transmission System (DARTS) and NASA's Planetary Data System (PDS). To facilitate intuitive access to these archives, we have developed the JAXA Asteroid Data Explorer 2 (JADE2; https://jade2.darts.isas.jaxa.jp/), a web-based platform that allows users to search and visualize data from the Hayabusa2 instruments without prior expertise in mission data formats. The first version of JADE2 was publicly released in 2025. Here we present the major updates introduced in the January 2026 release.The initial JADE2 release incorporated data from the Optical Navigation Camera (ONC), the Near-Infrared Spectrometer (NIRS3), the Thermal Infrared Imager (TIR), the Light Detection and Ranging instrument (LIDAR), and the Mobile Asteroid Surface Scout (MASCOT) lander. Detailed descriptions of each instrument and product level are provided in the corresponding Software Interface Specifications (SIS) documents and references therein. In the January 2026 update, we have added several higher-level products: the ONC I/F and reflectance Mosaic Maps (L3dm, L3drm, L3em, L3erm), and the NIRS3 thermal-removed reflectance spectra (L2D). New datasets are also provided in GIS-compatible formats (GeoTIFF, GeoPackage) that can be readily ingested into applications such as QGIS and ArcGIS. Additional content includes new global basemap datasets covering a range of illumination conditions and spatial resolutions, new color maps designed to enhance spectral and topographic features, and high-resolution 3D models of the touchdown site and of the Small Carry-on Impactor (SCI) crater before and after its formation.The January 2026 update also introduces new viewing functions for LIDAR 3D data, interactive adjustment of colormap hues, and improved rendering of 3D models. For the Hayabusa2 trajectory display, we have added a spacecraft-perspective view frame and a blinking-light indicator synchronized with the observation timing of each instrument, allowing users to intuitively follow the mission's operations along the timeline.JADE2 enables users to search and visualize data from multiple Hayabusa2 instruments through a single interface. In the near future, we plan to incorporate data from additional instruments such as DCAM3 and the MINERVA-II rovers, as well as further higher-level products. We are also exploring the extension of JADE2 to the upcoming targets of the Hayabusa2 extended mission and to other planetary missions, with the long-term goal of providing a unified data-exploration platform for small-body science.Acknowledgements. This work is supported by the JAXA Hayabusa2 International Visibility Enhancement Project. The data served by JADE2 are available from DARTS (https://darts.isas.jaxa.jp/).

An objective analysis dataset of the Venus atmosphere, ALERA‐V version 1.0, has been released. This objective analysis provides the best estimate of the state of the Venus atmosphere produced by combining observations and a forecast model weighted according to their respective levels of uncertainty. The accumulation of frequent observations by the Venus Climate Orbiter ‘Akatsuki’ has, for the first time, enabled an objective analysis of the Venus atmosphere. ALERA‐V stands for AFES‐LETKF experimental ensemble objective (re)analysis of the Venus atmosphere, and is generated by ALEDAS‐V, the AFES‐LETKF data assimilation system for the Venus atmosphere. ALEDAS‐V uses AFES‐Venus (Atmospheric General Circulation Model for the Earth Simulator for Venus) as a forecast model and the LETKF (Local Ensemble Transform Kalman Filter) for data assimilation. The observations of the zonal and meridional winds obtained by a cloud tracking technique from images taken by Akatsuki's UVI (Ultraviolet Imager) are assimilated to produce ALERA‐V version 1.0. The dataset consists of atmospheric variables defined on a grid of 128 longitude and 64 latitude points, and 60 vertical levels, with output every 6 Earth hours from September to December 2018, including the intensive observation period of November. ALERA‐V is expected to be useful for both scientific and engineering research, such as understanding the dynamical mechanisms of various atmospheric phenomena and planning for future satellite missions, with appropriate consideration of its quality and limitations.

In Fujisawa et al. (2022) [1], we previously produced an objective analysis of the Venusian atmosphere by assimilating horizontal winds derived from cloud tracking of the UVI camera onboard the Venus orbiter Akatsuki. To produce objective analysis, we used the Venus atmospheric data assimilation system ALEDAS-V (Sugimoto et al., 2017) [2], which is based on the Venus general circulation model AFES-Venus (Sugimoto et al., 2014) [3]. This dataset appropriately corrects both the phase bias of thermal tides and the super-rotation speed in AFES-Venus to be closer to those observed in the real Venusian atmosphere. The dataset was produced by assimilating observations from September to December 2018, a period that includes an intensive observation period of Akatsuki.Akatsuki has accumulated observational data over a long period from 2015 to 2024, and it has been revealed that the super-rotation speed exhibits both faster and slower periods (Horinouchi et al., 2024) [4]. In this study, we selected five epochs during the Akatsuki observation period that exhibit characteristic super-rotation speeds and performed data assimilation for each epoch. As a result, we confirmed that distinct super-rotation speeds corresponding to each epoch, including their meridional asymmetry, are reproduced. In the presentation, we will show the relationship between the reproduced super-rotation speeds and the structure of the atmospheric circulation.[1] Fujisawa, Y., et al. (2022) Sci. Rep. 12, 14577.[2] Sugimoto, N., et al. (2017) Sci. Rep. 7(1), 9321.[3] Sugimoto, N., et al. (2014) J. Geophys. Res. Planets 119, 1950–1968.[4] Horinouchi, T., et al. (2024) J. Geophys. Res. Planets 129, e2023JE008221.

. IntroductionHayabusa2 is equipped with a variety of scientific instruments and landers. The observational data obtained from them are available via Planetary Data System (PDS) by NASA and Data Archives and Transmission System (DARTS) by JAXA. However, the status of higher-level, analysis-ready product development and the data formats are different across instruments, making multi-instrument analysis challenging and often requiring specialized knowledge. To address this, the JAXA Hayabusa2# [1] International Visibility Enhancement Project (https://hayabusa2visibility.jaxa.jp) is developing Geographic Information System (GIS)-format data products to promote the usability of Hayabusa2 observational data. By formatting the data for use in GIS software, this approach is expected to enable multi-instrument analysis while lowering the barrier to data utilization and analysis.This presentation introduces GIS products and an experimental QGIS plugin designed for data analysis.2. Development of the GIS productsThis study developed two GIS-compatible data formats: raster (GeoTIFF) and vector (GeoPackage). These formats are broadly supported by standard GIS software, such as QGIS and ArcGIS, and can be easily viewed and edited. As both formats contain geographic coordinate information, geospatial analyses through comparisons between different observation dates and instruments at the same location are possible. In addition, users can analyze the data quickly and easily by utilizing built-in GIS tools, such as raster calculators and spatial statistics, without the need for additional coding. A raster data (GeoTIFF) has a regular digital picture like a JPEG or a normal TIFF file. Besides the pixel data, it includes the georeferenced information such as location, scale, projection, and coordinate system. Vector data consist of geometries (lines, polygons, etc.) and attribute information. We employ this format to NIRS3[2,3]: Attribute table can store various types of information—such as observation conditions and reflectance values at each wavelength —associated with corresponding footprint. This structure enables users to examine detailed information for each observation footprint and extract data subsets based on specific observation conditions. Figure 1 illustrates how a NIRS3 footprint outlined in red corresponds to the records selected in the attribute table, demonstrating the linkage between spatial features and tabular data. The NIRS3 GIS product was generated using geometry information calculated with SPICE kernels and L2 products stored in FITS format. For the data conversion process, Python libraries such as Shapely, GeoPandas, and Rasterio[4] were used.Figure 1. Vector product examples of NIRS3 footprints. 3. Development of plugin for data analysisQGIS [5] is a widely used open-source GIS application that offers many powerful features. It is particularly used for the visualization and analysis of Earth satellite data. In this study, we apply QGIS to the analysis of small body data, thereby making it easier for a broad range of researchers to work with spacecraft observation data. We present the experimental development of a QGIS plugin based on GIS-formatted NIRS3 data which has three functions, spectral profile visualization, spectral slope calculation, and map data generation. Providing the tool as QGIS plugin enables users to easily analyze observation data, without specialized knowledge of QGIS or Python programming.4. GIS Analysis ExampleExpected use cases for the GIS product and plugin functions are presented below.・Filtering and Extraction of Observational DataObservation data that meet specific conditions can be extracted. This function enables users to extract the specific condition data and examine the distribution and correlation of these data with terrain features. This can be performed using existing GIS software.・Visualization of spectral profileWe developed a plugin function to visualize the spectral profile at specific locations and compare profiles across multiple user-selected points (Fig. 2).・Calculate spectral slope and map data generationWe developed plugin functions to calculate spectral slope and generate global maps by averaging values such as spectral slope and reflectance, derived from overlapping footprints, helping users visually assess overall trends across the surface. As an example, Figure 3 shows the resulting spectral slope map calculated from 2.1 µm to 2.5 µm using the least squares method.Figure 2. Plugin example of spectral profile visualizationFigure 3. Plugin example for spectral slope calculation and map generation5. Future workWe are preparing for the release of the GIS-format data and the distribution of the plugin, as well as developing GIS-format data for other instruments and exploring enhancements to the plugin’s functionality. Furthermore, we hold Hayabusa2 data analysis workshops for further reaching out to users. These ongoing efforts aim to promote broader and more effective use of the Hayabusa2 observation data.Acknowledgements: This work is supported by the JAXA Hayabusa2# International Visibility Enhancement Project.References: [1] Hirabayashi, M. et al., 2021, Advances in Space Research 68, 1533-1555. [2] Iwata, T. et al., 2017, Space Science Reviews 208, 317. [3] Kitazato, K. et al., 2019, Science 364(6437), 272. [4] Python libraries such as GeoPandas (Jordahl et al., 2023), Shapely (Gillies et al., 2023), and Rasterio (Gillies et al., 2023) were used in the data conversion process. [5] QGIS Development Team. (2024). QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.org

The Venus orbiter Akatsuki started its observation in December 2015, and it provided valuable data on the atmosphere of Venus until its signal was lost in April 2024. We published a paper with the same title as this presentation by using the winds obtained by tracking clouds obtained at two ultraviolet wavelengths by Akatsuki/UVI until March 2023 (Horinouchi et al., 2024). In this presentation, we will present its findings and further updates by adding observations that were not used in the paper. The zonal winds associated with the superrotation are found to vary in many ways. There exists hemispheric asymmetry across the equator, and it varies with time. On average, the superrotation in the southern hemisphere was faster over the observational period, but it reverted sometimes. Earlier studies sought periodic variabilities on the order of hundred days or decades (e.g., Kouyama et al. 2013, Khatuntsev et al. 2013, 2022), which can result from periodical forcings. However, mean zonal winds representing the superrotation exhibited broad low-frequency variability with spectra resembling the red noise spectra (Fig. 1). This is indicative of the presence of internal variability rather than responses to periodical external forcing, indicating needs for paradigm shift. Long-term variability over the Venus Express and Akatsuki periods until 2020 appears that the superrotation was accelerated gradually and maximized during the Venus Express period and was then decelerated during the Akatsuki period. However, in 2021, it appears that the superrotation started fluctuating more rapidly and abruptly (Fig. 2). Earlier studies found planetary-scale wave with zonal-wavenumber 1 at periods around 4 and 5 days, which were interpreted as equatorial Kelvin and Rossby waves, respectively. We found that the two waves coexist. While the ~5-day waves have nearly constant frequencies, the ~4-day waves have variable phase speeds that follow the superrotation speed. This finding provides insight on their origins, that the ~5-day waves are likely to extend over a large depth below the cloud top and that the ~4-day waves are likely to be confined near the cloud top. It further provides implications on their excitation mechanism. The presence of wind variability at periods of 10 to 15 days is suggested for the first time. Wind distribution of the thermal tides at around the cloud top was quantified better than in previous studies. The variability in winds obtained in this study and the variability in constituents in previous studies are compared. The Horinouchi et al. (2024) paper includes methodological development regarding the co-use of the discrete Fourier transform (DFT by FFT) and the Lomb-Scargle (LS) periodogram for better spectral estimation from data with observation pauses. Reference: Horinouchi et al. (2024) https://doi.org/10.1029/2023JE008221Khatuntsev et al. (2013) https://doi.org/ 10.1016/j.icarus.2013.05.018Khatuntsev et al. (2022) https://doi.org/10.3390/atmos13122023Kouyama et al. (2013) https://doi.org/10.1029/2011JE004013 Fig. 1: Figure 8 of Horinouchi et al. (2024). Power spectral density averaged between 20degS and 20degN for (a, c) zonal and (b, d) meridional winds obtained from (a, b) 283-nm and (c, d) 365-nm images computed by (blue) the DFT and (black) the LS methods from by using nearly the whole analysis period (Type A). For spectral stability, the 1-2-1 three-point smoothing filter is applied with frequency once for f≥1×10^(-2) day^(-1), twice for f≥2×10^(-2) day^(-1), and three times for f≥4×10^(-2) day^(-1). The red lines indicate spectral slopes of -1 and -2. The dotted curves in (a, c) show subjectively fit red noise spectra (see the text). Also shown on the abscissas is the period defined by f^(-1), which is equal to the ground-based period if fluctuations represented by the spectra are zonally uniform. Fig. 2: Updated Figure 7a of Horinouchi et al. (2024). Black dots are the zonal winds obtained in this study from the 365-nm images, which are averaged over 11-13 LT and 24degS-18degS and binned over 5 days only when valid data are available for 3 or more days in each bin. Blue dots are the same but for zonal winds obtained from VEx/VMC, which were derived by Kouyama et al. (2013).

Introduction:Following the successful completion of its primary mission to (162173) Ryugu, Hayabusa2 has transitioned into its extended mission phase, referred to as Hayabusa2# [1]. Concurrently, as samples from the nominal mission are disseminated globally for laboratory analyses, our focus shifts towards amplifying the visibility of Hayabusa2 mission data. The in-situ observations of asteroids by spacecraft are an unique opportunity, and thus it is important to utilize the data properly and exploit the scientific information as much as possible. As the instruments are more and more matured and sophisticated, the dataset has various potential to be analyzed. Our objectives are threefold: 1) to open access to the data, 2) to promote its utilization, and 3) to optimize the scientific yield from the mission. In this presentation, we report our current activities and future plans. The framework can serve as a model case for future missions.Opening Access to Data:We are actively working on archiving data in both the Data Archives and Transmission System (DARTS; https://darts.isas.jaxa.jp/) by JAXA and the PDS (Planetary Data System) Small Bodies Node (https://sbn.psi.edu/pds/) by NASA. Currently, data from the main remote-sensing instruments and the MASCOT lander from the nominal mission are accessible. We are working on archiving data from additional instruments such as DCAM3, MINERVA II, and CAM-H.Promoting Data Utilization:Given that the available data are primarily at a low level, and sometimes the profound knowledges of the instruments and/or the mission are required to look for and decode the data, especially when the data is separated from the geographic information. we are implementing two strategies to encourage their utilization. Firstly, we are developing a user-friendly searching and downloading system designed for intuitive access to desired data, exemplified by the JAXA Asteroid Data Explorer (JADE; https://jade.darts.isas.jaxa.jp/) [2]. Second, we are creating high-level products, including global and local basemaps derived from Optical Navigation Camera (ONC) images [3], formatted in GeoTIFF for seamless integration with GIS softwares, such as QGIS and ArcGIS. These basemaps can be served not only for mapping geomorphological features, but also for comparison between different observation dates or illumination conditions. We are currenly generating GeoTIFF-based spectral maps using data from the near-infrared spectrometer NIRS3, facilitating easy analysis in tandem with the ONC data.Future products will encompass laser altimeter LIDAR and thermal infrared imager TIR data, ensuring compatibility with QGIS/ArcGIS for enhanced interdisciplinary research. These products will be open for public after the appropriate reviews under PDS or scientific journals.Figure: Example of Hayabusa2 high-level products on QGIS. The NIRS3 footprints (pink circles) on top of the ONC basemaps (single and multi-band maps).Maximizing Scientific Outcomes:To foster broader engagement within the Planetary Science community, we propose organizing an international workshop dedicated to introducing the Hayabusa2 dataset. This workshop will feature presentations on the dataset and hands-on sessions for dataset analysis. References:[1] Hirabayashi et al. (2021) ASR, 1533-1555.[2] Kikuchi et al. (2023) LPSC, #2806.[3] Honda et al. (2024) LPSC, #1428.Acknowledgement:This work is supported by the JAXA Hayabusa2# International Visibility Enhancement Project.

Data assimilation of the Venus atmosphere has become more feasible due to the long-term observations by the Venus climate orbiter “Akatsuki”. We have produced the first objective analysis for the Venus atmosphere by assimilating horizontal winds derived by the cloud tracking of the Akatsuki Ultraviolet Imager (UVI) [1]. Here, we assimilate the temperature derived by the Akatsuki Longwave Infrared Camera (LIR), using the AFES-LETKF data assimilation system for Venus "ALEDAS-V" [2], which is based on the atmospheric general circulation model for Venus "AFES-Venus" [3] and local ensemble transform Kalman filter “LETKF”. In this experiment the altitude for the assimilation is set to 65 km regardless of the emission angle for simplicity, though the altitude observed by LIR depends on the emission angle (the angle between the zenith and observer directions as seen from the observation point). The influence of the emission angle is investigated for two cases; the one is the emission angle limited to 40 degrees or less and the other one is that limited to 75 degrees or less. [1] Fujisawa, Y., Sy. Murakami, N. Sugimoto, M. Takagi, T. Imamura, T. Horinouchi, G. L. Hashimoto, M. Ishiwatari, T. Enomoto, T. Miyoshi, H. Kashimura and Y.-Y. Hayashi, Y.-Y. (2022), Sci. Rep. 12, 14577.[2] Sugimoto, N., A. Yamazaki, T. Kouyama, H. Kashimura, T. Enomoto, and M. Takagi (2017), Sci. Rep., 7(1), 9321.[3] Sugimoto, N., M. Takagi, and Y. Matsuda (2014a), J. Geophys. Res. Planets, 119, 1950–1968.