In this study, we proposed a new method for flat-flied calibration of a sensor in space, which is basically difficult to conduct in space. In this method, an observation of the Moon with cross-track scan and its simulation are keys to achieve conducting the calibration. By applying the proposed method to GOSAT-2/CAI-2’s Moon observations with cross-track scan, we successfully obtained sensitivity difference among pixels in a sensor quantitatively, and it is consistent with that in a ground test before launch. In addition, by comparing results from different observations, it is possible to assess temporal variations of sensitivities in various positions in a sensor, which is a new information.

The Japan's greenhouse gases observing satellite (GOSAT) observes the atmospheric CO2change for a decade. JAXA EORC provides the GOSAT tropospheric partial column product V2 from 2009 up to 2021 by using both SWIR and TIR spectra. The CO2enhancement derived from the tropospheric partial column product has demonstrated the change detection over urban cities by the COVID-19 effect. The CO2partial column product has a potential for better quantifying urban CO2flux.

To track atmospheric CO2changes resulting from the lockdowns, observations collected by the NASA Orbiting Carbon Observatory-2 (OCO-2) satellite and Japan's Greenhouse gases Observing SATellite (GOSAT) in 2020 were compared to results collected in previous years. The OCO-2 results were used to search for changes on regional scales over the globe. Targeted observations from GOSAT were used to track changes in large urban areas, such as Beijing and Tokyo. Both types of observations yielded key insights into the CO2changes accompanying the economic disruptions caused by the COVID-19 lockdowns. ESA, NASA and JAXA developed the dashboard jointly to monitor the climate impacts of COVID-19.

In this study, we developed a fast yet flexible remote sensing algorithm to estimate the aerosol optical properties over water for the Cloud and Aerosol Imager-2 (CAI-2) onboard the Greenhouse gases Observing SATellite-2 (GOSAT-2) launched in October 2018. The CAI-2 is the successor of GOSAT/CAI by providing more spectral and finer spatial data. The algorithm uses the optimal estimation approach to simultaneously retrieve aerosol and water substances (SIRAW), combined with an artificial neural network (ANN) solver to perform the radiative transfer (RT) calculation. The ANN was well constructed based on an improved learning scheme and educated from a coupled atmosphere-ocean vector RT model over both open and coastal water. To investigate the availability of SIRAW, the retrieval was conducted using the real CAI-2 data and preliminarily validated via the ground-based observation of aerosol robotic network and maritime aerosol network over different ocean regions from March to November in 2019. Results demonstrated that the retrieved aerosol optical thickness (AOT) at 550 nm from CAI-2 had a good consistency to thein situmeasurement, of which about 70.37% of CAI-2 AOT fell within a ±(0.05+10%) envelope. The algorithm developed by this study performed generally well for the AOTs and oceanic suspended particles over the global ocean through the intercomparison to those of MODIS products. Moreover, the ultraviolet channel of CAI-2, which produces the first application with 500-m spatial resolution, shows a promising skill in the monitoring of the smoke plume.

Vicarious calibration methods use well-characterized surface sites to complement other on-orbit radiometric calibration techniques. Since 2009, NASA's Orbiting Carbon Observatory-2 (OCO-2) and Japan's Greenhouse gasses Observing SATellite teams have conducted annual campaigns at Railroad Valley, NV, USA, for this purpose. These sensors pose special challenges due to their large footprint sizes and view angles. OCO-2 sweeps the playa surface during a targeted overpass of the test site, and records data at a number of viewing angles. The smallest of these is selected for processing, thereby minimizing the off-nadir correction. Surface reflectances at nadir are recorded by the field team, and the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product is used to provide the small, off-nadir correction. Another MODIS product, the Level 1B top-of-atmosphere radiance product, is used to validate the results and to provide input into the OCO-2 calibration uncertainty estimate. From 11 experiments, the ratio of radiances reported by the OCO-2 Level 1B data product to those from the field campaigns is 1.01, 1.04, and 1.01 for the three OCO-2 spectral bands. These analyses validate the data product absolute calibration, to within the 5% requirement. The need for executing these experiments will be of continued importance to OCO-3. This sensor has an on-board calibrator that provides a dark signal and lamps for response trends but does not have the on-board solar-diffuser present on OCO-2, and thus cannot track degradations relative to the Sun.

The Greenhouse gases Observing SATellite (GOSAT) carries the Thermal and Near-Infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS). TANSO-FTS covers a wide spectral range from the shortwave infrared to the thermal infrared (TIR). This paper describes the updated calibration algorithm of the TANSO-FTS Level 1B TIR spectra and the radiometric validation of the new V210.210 products by comparison with the previous version of V201.202. The revised nonlinearity correction for V210.210 product creates a decade-long, well-calibrated radiance set while minimizing the effect of two major anomalies: rotation stop of the one of the solar paddles in 2014 and a cryocooler shutdown in 2015, which caused abrupt changes in the thermal environment of the TANSO-FTS sensor. To check the improved nonlinearity correction and onboard calibration in TANSO-FTS V210.210 processing, we validated the entire spectral range by comparing with aircraft-based Scanning High-resolution Interferometer Sounder coincident in time with the GOSAT overpass. Also selected CO2and CH4channels are validated with the Atmospheric infrared sounder and the window channel with the in situ SST Quality Monitor data at temporally coincident and spatially collocated points. We have confirmed that the new V210.210 products exhibit no significant time trend in the window channel and a reduced spectral bias in the CO2and CH4channels. There remains some spectral bias, especially in the CO2ν2channel and CH4channel, which are attributed to the uncertainty of orbital and seasonal variations in the average direct current level of TANSO-FTS without photon input.

The thermal infrared (TIR) band of Thermal and Near-Infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse gases Observing SATellite (GOSAT) measures a wide range of scene temperatures using a single detector band with broad spectral coverage. This work describes the vicarious radiometric calibration over a large footprint (10.5 km) and high temperature surface using well-calibrated ground-based and airborne FTS sensors. The vicarious calibration campaign of GOSAT was conducted at Railroad Valley, NV in June 2011. During the campaign, the Scanning High-resolution Interferometer Sounder (S-HIS) mounted on the high-altitude NASA ER-2 aircraft observed upwelling radiation and the ground-based Surface-Atmospheric Emitted Radiance Interferometer (S-AERI) observed infrared thermal emission from the atmosphere and the surface at the same location and time as the GOSAT TANSO-FTS. We validated TANSO-FTS TIR radiance with S-HIS radiance using double difference method, which reduces the effect of differences in the observation geometry. In this paper, we estimated the TANSO-FTS Instantaneous Field of View average temperature and emissivity by the coincident S-AERI and S-HIS observed radiance. The double difference between TANSO-FTS and S-HIS result in a difference of 0.5 K at atmospheric window channels (800 ~ 900 cm-1) and CO2warm brightness temperature channels (700 ~ 750 cm-1), 0.1 K at ozone channels (980 ~ 1080 cm-1), and more than 2 K at CO2cool brightness temperature channels (650 ~ 700 cm-1). The main reason of remaining errors is attributed to a calibration error in the TANSO-FTS Level 1B product version under evaluation.

This work describes the radiometric calibration of the short-wave infrared (SWIR) bands of two instruments aboard the Greenhouse gases Observing SATellite (GOSAT), the Thermal And Near infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) and the Cloud and Aerosol Imager (TANSO-CAI). Four vicarious calibration campaigns (VCCs) have been performed annually since June 2009 at Railroad Valley, NV, USA, to estimate changes in the radiometric response of both sensors. While the 2009 campaign ( VCC2009) indicated significant initial degradation in the sensors compared to the prelaunch values, the results presented here show that the stability of the sensors has improved with time. The largest changes were seen in the 0.76 μm oxygen A-band for TANSO-FTS and in the 0.380 and 0.674 μm bands for TANSO-CAI. This paper describes techniques used to optimize the vicarious calibration of the GOSAT SWIR sensors. We discuss error reductions, relative to previous work, achieved by using higher quality and more comprehensive in situ measurements and proper selection of reference remote sensing products from the Moderate Resolution Imaging Spectroradiometer used in radiative transfer calculations to model top-of-the-atmosphere radiances. In addition, we present new estimates of TANSO-FTS radiometric degradation factors derived by combining the new vicarious calibration results with the time-dependent model provided by Yoshida (2012), which is based on analysis of on-board solar diffuser data. We conclude that this combined model provides a robust correction for TANSO-FTS Level 1B spectra. A detailed error budget for TANSO-FTS vicarious calibration is also provided.

Total and tropospheric ozone columns have been retrieved from thermal infrared spectral radiances recorded with the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS), which is onboard the Greenhouse gases Observing SATellite launched on January 23, 2009. We present ozone retrievals that were performed over about two years of observations (during the period from April 2009 to December 2010) over four climatically distinct regions (the Sapporo, Tsukuba, Naha, and Syowa sites). Annual variations of the total and tropospheric ozone columns over the four sites were derived. We compare TANSO-FTS total ozone columns with ground-based data from the Dobson spectrophotometer, and the seasonal trends and patterns of the retrieved total ozone are consistent with those of Dobson measurements. The TANSO-FTS total ozone columns are in good agreement with the Dobson data, with a correlation coefficient of about 0.98. On average, TANSO-FTS total ozone retrievals exhibit a positive bias of 8.8 DU (3.0%) with a root-mean-square difference of 10.9 DU (4.1%) compared to the Dobson measurements. Comparisons of the TANSO-FTS tropospheric ozone columns to ozonesondes available from the four sites have been performed. The TANSO-FTS tropospheric ozone columns compare well with the ozonesonde measurements, with correlation coefficients of 0.96 and 0.92 for the surface-tropopause and surface-6 km partial columns, respectively. Average differences of 0.7 ± 4.2 DU (2.5% ± 12.8%) and -0.7 ±2.2 DU (-3.0% ±12.2%) are found for the surface-tropopause and surface-6 km partial columns, respectively.

Japan's Greenhouse Gases Observing Satellite (GOSAT) was successfully launched into a sun-synchronous orbit on January 23, 2009 to monitor global distributions of carbon dioxide$( \hbox{CO}_{2})$and methane$(\hbox{CH}_{4})$. GOSAT carries two instruments. The Thermal And Near-infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) measures reflected radiances in the 0.76$\mu\hbox{m}$oxygen band and in the weak and strong$\hbox{CO}_{2}$bands at 1.6 and 2.0$\mu\hbox{m}$. The TANSO Cloud and Aerosol Imager (TANSO-CAI) uses four spectral bands at 0.380, 0.674, 0.870, and 1.60$\mu\hbox{m}$to identify clear soundings and to provide cloud and aerosol optical properties. Vicarious calibration was performed at Railroad Valley, Nevada, in the summer of 2009. The site was chosen for its flat surface and high spectral reflectance. In situ measurements of geophysical parameters, such as surface reflectance, aerosol optical thickness, and profiles of temperature, pressure, and humidity, were acquired at the overpass times. Because the instantaneous field of view of TANSO-FTS is large (10.5 km at nadir), the spatially limited reflectance measurements at the field sites were extrapolated to the entire footprint using independent satellite data. During the campaign, six days of measurements were acquired from two different orbit paths. Spectral radiances at the top of the atmosphere were calculated using vector radiative transfer models coupled with ground in situ data. The agreement of the modeled radiance spectra with those measured by the TANSO-FTS is within 7%. Significant degradations in responsivity since launch have been detected in the short-wavelength bands of both TANSO-FTS and TANSO-CAI.

Greenhouse gases observation by space-borne FTS, such as GOSAT, is a challenging project. The FTS enables to obtain the high spectral resolution data, although the high SNR depends on the scanning speed during an interferometric scan time. The FTS measurement is based upon no-changeable target radiance, however it depends on the mechanical pointing accuracy and stability as well as the target natural stability during an interferometric scan time. The FTS onboard GOSAT satellite primarily aims at observing CO2over the land and oceanic sun glint in shortwave infrared. We study the sun glint radiance level and the stability during an interferometric scan time using Aqua satellite data, such as MODIS radiance and AMSR-E sea surface wind over the same oceanic sun glint region.

The Advanced Microwave Scanning Radiometer (AMSR) on board the Advanced Earth Observing Satellite-II (ADEOS-II, or Midori-II) has two channels in the oxygen absorption bands. This is the first attempt to obtain brightness temperatures at the channels by a conically scanning microwave radiometer with high spatial resolution. Potential applications of the channels include the air temperature monitoring, improving geophysical parameter retrieval by incorporating the information of air temperature, and sensing hydrometeor information by utilizing the different penetration depth compared to other window-frequency channels. Since one of the future trends of passive microwave instruments is to integrate the imaging and sounding capabilities into single conical scanning instrument, AMSR data will provide some insights to those future plans. We introduce some potential uses of the channels in conjunction with the preliminary examples of actual AMSR data

The Advanced Microwave Scanning Radiometer for EOS (AMSR-E) was developed and provided to NASA's EOS Aqua satellite by the National Space Development Agency of Japan (NASDA). AMSR-E is the modified version of AMSR onboard the Advanced Earth Orbiting Satellite-II (ADEOS-II, currently called the Midori-II). AMSR-E has been in operation since June 2002 and providing continuous data record. This paper presents the status of post-launch calibration and data evaluation of the instrument.