Hirofumi Ohyama

Long-Term Vicarious Calibration of GOSAT Short-Wave Sensors: Techniques for Error Reduction and New Estimates of Radiometric Degradation Factors

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.

Retrievals of Total and Tropospheric Ozone From GOSAT Thermal Infrared Spectral Radiances

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.

Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics

ABSTRACT This study presents an approach for generating a global land mapping dataset of the satellite measurements of CO2 total column (XCO2) using spatio-temporal geostatistics, which makes full use of the joint spatial and temporal dependencies between observations. The mapping approach considers the latitude-zonal seasonal cycles and spatio-temporal correlation structure of XCO2, and obtains global land maps of XCO2, with a spatial grid resolution of 1° latitude by 1° longitude and temporal resolution of 3 days. We evaluate the accuracy and uncertainty of the mapping dataset in the following three ways: (1) in cross-validation, the mapping approach results in a high correlation coefficient of 0.94 between the predictions and observations, (2) in comparison with ground truth provided by the Total Carbon Column Observing Network (TCCON), the predicted XCO2 time series and those from TCCON sites are in good agreement, with an overall bias of 0.01 ppm and a standard deviation of the difference of 1.22 ppm and (3) in comparison with model simulations, the spatio-temporal variability of XCO2 between the mapping dataset and simulations from the CT2013 and GEOS-Chem are generally consistent. The generated mapping XCO2 data in this study provides a new global geospatial dataset in global understanding of greenhouse gases dynamics and global warming.

Intercomparison of XH2O Data from the GOSAT TANSO-FTS (TIR and SWIR) and Ground-Based FTS Measurements: Impact of the Spatial Variability of XH2O on the Intercomparison

Spatial and temporal variability of atmospheric water vapor (H2O) is extremely high, and therefore it is difficult to accurately evaluate the measurement precision of H2O data by a simple comparison between the data derived from two different instruments. We determined the measurement precisions of column-averaged dry-air mole fractions of H2O (XH2O) retrieved independently from spectral radiances in the thermal infrared (TIR) and the short-wavelength infrared (SWIR) regions measured using a Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT), by an intercomparison between the two TANSO-FTS XH2O data products and the ground-based FTS XH2O data. Furthermore, the spatial variability of XH2O was also estimated in the intercomparison process. Mutually coincident XH2O data above land for the period ranging from April 2009 to May 2014 were intercompared with different spatial coincidence criteria. We found that the precisions of the TANSO-FTS TIR and TANSO-FTS SWIR XH2O were 7.3%–7.7% and 3.5%–4.5%, respectively, and that the spatial variability of XH2O was 6.7% within a radius of 50 km and 18.5% within a radius of 200 km. These results demonstrate that, in order to accurately evaluate the measurement precision of XH2O, it is necessary to set more rigorous spatial coincidence criteria or to take into account the spatial variability of XH2O as derived in the present study.

SUBMILLIMETER OBSERVATION OF JUPITER’S STRATOSPHERIC COMPOSITION: DETECTION OF CARBON MONOSULFIDE (J = 7 − 6) 19 YEARS AFTER THE COMETARY IMPACT

In Jupiters stratosphere, gaseous carbon monosulfide (CS) was first discovered in 1994 by millimeter and ultraviolet observations as a product induced by the collision of comet Shoemaker–Levy 9 (SL9). To constrain sulfur chemistry, in 2013, 19 years after the SL9 event, we observed Jupiters stratospheric CS J = 7 − 6 rotational transition at 0.8 mm wavelength by using the Atacama Submillimeter Telescope Experiment 10 m single-dish telescope. The CS molecular line was successfully detected with 120 mK intensity in the antenna temperature scale. The obtained CS total mass shows ~90% decrease relative to that observed in 1998. From the line shape analysis, CS is suggested to be present above the mbar pressure level, which is comparable to that determined in 1998.

Sensitivity Analysis of Fourier Transformation Spectrometer: FTS Against Observation Noise on Retrievals of Carbon Dioxide and Methane

Sensitivity analysis of Fourier Transformation Spectrometer: FTS against observation noise on retrievals of carbon dioxide and methane is conducted. Through experiments with real observed data and additive noise, it is found that the allowable noise on FTS observation data is less than 2.1x10-5 if estimation accuracy of total column carbon dioxide and methane is better than 1(%).

Building the COllaborative Carbon Column Observing Network(COCCON): Long term stability and ensemble performance of theEM27/SUN Fourier transform spectrometer

In a 3.5-year long study, the long-term performance of a mobile, solar absorption Bruker EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference Bruker IFS 125HR spectrometer, which is part of the Total Carbon Column Observing Network (TCCON). We find that the EM27/SUN is stable on timescales of several years; the drift per year between the EM27/SUN and the official TCCON product is 0.02 ppmv for XCO2 and 0.9 ppbv for XCH4, which is within the 1σ precision of the comparison, 0.6 ppmv for XCO2 and 4.3 ppbv for XCH4. The bias between the two data sets is 3.9 ppmv for XCO2 and 13.0 ppbv for XCH4. In order to avoid sensitivity-dependent artifacts, the EM27/SUN is also compared to a truncated IFS 125HR data set derived from full-resolution TCCON interferograms. The drift is 0.02 ppmv for XCO2 and 0.2 ppbv for XCH4 per year, with 1σ precisions of 0.4 ppmv for XCO2 and 1.4 ppbv for XCH4, respectively. The bias between the two data sets is 0.6 ppmv for XCO2 and 0.5 ppbv for XCH4. With the presented long-term stability, the EM27/SUN qualifies as an useful supplement to the existing TCCON network in remote areas. To achieve consistent performance, such an extension requires careful testing of any spectrometers involved by application of common quality assurance measures. One major aim of the COllaborative Carbon Column Observing Network (COCCON) infrastructure is to provide these services to all EM27/SUN operators. In the framework of COCCON development, the performance of an ensemble of 30 EM27/SUN spectrometers was tested and found to be very uniform, enhanced by the centralized inspection performed at the Karlsruhe Institute of Technology prior to deployment. Taking into account measured instrumental line shape parameters for each spectrometer, the resulting average bias across the ensemble with respect to the reference EM27/SUN used in the long-term study in XCO2 is 0.20 ppmv, while it is 0.8 ppbv for XCH4. The average standard deviation of the ensemble is 0.13 ppmv for XCO2 and 0.6 ppbv for XCH4. In addition to the robust metric based on absolute differences, we calculate the standard deviation among the empirical calibration factors. The resulting 2σ uncertainty is 0.6 ppmv for XCO2 and 2.2 ppbv for XCH4. As indicated by the executed long-term study on one device presented here, the remaining empirical calibration factor deduced for each individual instrument can be assumed constant over time. Therefore the application of these empirical factors is expected to further improve the EM27/SUN network conformity beyond the scatter among the empirical calibration factors reported above.

Comparison of ozone profiles from DIAL, MLS, and chemical transport model simulations over Río Gallegos, Argentina during the spring Antarctic vortex breakup, 2009

This study evaluates the agreement between ozone profiles derived from the ground-based differential absorption lidar (DIAL), satellite-borne Aura Microwave Limb Sounder (MLS), and 3-D chemical transport model (CTM) simulations such as the Model for Interdisciplinary Research on Climate (MIROC-CTM) over the Atmospheric Observatory of Southern Patagonia (Observatorio Atmosférico de la Patagonia Austral, OAPA; 51.6 S, 69.3W) in Río Gallegos, Argentina, from September to November 2009. In this austral spring, measurements were performed in the vicinity of the polar vortex and inside it on some occasions; they revealed the variability in the potential vorticity (PV) of measured air masses. Comparisons between DIAL and MLS were performed between 6 and 100 hPa with 500 km and 24 h coincidence criteria. The results show a good agreement between DIAL and MLS with mean differences of ±0.1 ppmv (MLS−DIAL, n= 180) between 6 and 56 hPa. MIROC-CTM also agrees with DIAL, with mean differences of ±0.3 ppmv (MIROC-CTM−DIAL, n= 23) between 10 and 56 hPa. Both comparisons provide mean differences of 0.5 ppmv (MLS) to 0.8–0.9 ppmv (MIROC-CTM) at the 83– 100 hPa levels. DIAL tends to underestimate ozone values at this lower altitude region. Between 6 and 8 hPa, the MIROCCTM ozone value is 0.4–0.6 ppmv (5–8 %) smaller than those from DIAL. Applying the scaled PV (sPV) criterion for matching pairs in the DIAL–MLS comparison, the variability in the difference decreases 21–47 % between 10 and 56 hPa. However, the mean differences are small for all pressure levels, except 6 hPa. Because ground measurement sites in the Southern Hemisphere (SH) are very sparse at midto high latitudes, i.e., 35–60 S, the OAPA site is important for evaluating the bias and long-term stability of satellite instruments. The good performance of this DIAL system will be useful for such purposes in the future.

Comparative Study on Cloud Parameter Estimation Among GOSAT/CAI, MODIS, CALIPSO/CALIOP and Landsat-8/OLI with Laser Radar: Lidar as Truth Data

A comparative study on cloud parameter estimation among GOSAT/CAI, MODIS, CALIPSO/CALIOP and Landsat-8/OLI is carried out using Laser Radar: Lidar as a truth data. Optical depth, size distribution, as well as cirrus type of clouds are cloud parameters. In particular, cirrus cloud detection is tough issue. 1.38 µm channel is required for its detection. Although MODIS and Landsat-8/OLI have such channel, the other mission instruments, CAI and CALIPSO/CALIOP do not have such channel. As a truth data of cloud parameter, ground based Lidar is used in this comparative study. From the Lidar, backscattered echo signal and depolarization coefficient are obtained as a function of altitude. Therefore, cloud type, vertical profile can be derived from the Lidar data. CALIPSO/CALIOP is satellite based Lidar which allows observation of clouds from space. Although the directions of laser light emissions between CALIPSO/CALIOP and the ground based Lidar are different, their principles are same. Therefore, it is expected that CALIPSO/CALIOP data derived cloud parameters are similar to the ground based Lidar data derived cloud parameters. The experimental results show the aforementioned facts and are useful for improvement of cloud parameter estimation accuracy with several sensor data combinations.

Numerical Deviation Based Optimization Method for Estimation of Total Column CO2 Measured with Ground Based Fourier Transformation Sepectormeter: FTS Data

Numerical deviation based optimization method for estimation of total column CO2 measured with ground based Fourier Transformation Spectormeter: FTS data is proposed. Through experiments with aircraft based sample return data and the ground based FTS data, it is found that the proposed method is superior to the conventional method of Levenberg Marquads based nonlinear least square method with analytic deviation of Jacobian and Hessean around the current solution. Moreover, the proposed method shows better accuracy and required computer resources in comparison to the internationally used method (TCCON method) for estimation of total column CO2 with FTS data. It is also found that total column CO2 depends on weather conditions, in particular, wind speed.