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The Greenhouse gases Observing SATellite-2 (GOSAT-2, launched on October 29, 2018) has shown immense potential in CO2 and CH4 research, as a successor of GOSAT; however, the retrieval of tropospheric ozone is yet to be analyzed. Meanwhile, metropolitan areas are regarded as tropospheric ozone source for emission of ozone precursors (NOx and VOC) by anthropogenic activities. The extreme surface temperature due to urban heat island effect can potentially modify the averaging kernel (AK) of satellite retrieval; this effect, "thermal contrast", is expected to favor the analysis of ozone in urban areas. In the paper, we aim at providing the first results of 3-year tropospheric ozone retrieval using thermal infrared (TIR) band from the nadir-looking instrument Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer-2 (TANSO-FTS-2), which is onboard GOSAT-2. The retrieval is focused on the urban area of Tokyo, Japan by the targeting mode of FTS-2 with around 40×40 km2 domain. In the retrieval process, we basically apply the optimal estimation and the Line-By-Line Radiative Transfer Model (LBLRTM) as the forward model, with the spectroscopic line parameters from HITRAN 2016 database. The climatological mean of the tropospheric ozone in Tokyo is applied as the a priori profile. For validation, we use ozonesonde data in Tsukuba, Japan (36.06° N, 140.13° E) with averaging kernel smoothing method. The results are also compared with ground measurements obtained from Atmospheric Environmental Regional Observation System (AEROS) of Japan. The performance of retrieval is evaluated by the degree of freedom of signal (DOFS), root-mean square error (RMSE) and mean bias (BIAS), in comparison with previous satellite missions such as TES and IASI. Our results present day-to-day and seasonal variation of tropospheric ozone in metropolitan area, while elucidating the urban heat island effect on the sensitivity of satellite retrieval and the characteristics of retrieved ozone episodes in view of meteorological conditions. Our results facilitate the assessment of urban tropospheric ozone trend and lead to better understanding of ozone chemistry using new satellite observations. Global validation and analysis of GOSAT-2 retrieval will be presented in a subsequent paper.

An original method is suggested for solving the inverse problem of hyperspectral satellite sounding of the atmosphere for retrieving the HDO/H2O ratio vertical profile in the atmosphere with simultaneous inversion of thermal and near-IR spectra. A computational experiment was performed to retrieve the vertical profile of the relative content of the HDO isotopologue in atmospheric water vapor from high-resolution spectra simulated with parameters of the TANSO-FTS spectrometer onboard the GOSAT-2 satellite. The inverse problem was solved by the optimal estimation method with simultaneous inversion of thermal and near-IR spectra. The output data of the isotopic version of the ECHAM6-wiso atmospheric general circulation model were used as an a priori statistical set of water vapor isotopologue vertical profiles.

A novel, practical observation system for measuring tropospheric carbon dioxide (CO2) concentrations using a non-dispersive infrared analyzer carried by a small helium-filled balloon (CO2 sonde) has been developed for the first time. Vertical profiles of atmospheric CO2 can be measured with a 240–400 m altitude resolution through regular onboard calibrations using two different CO2 standard gases. The standard deviations (1σ) of the measured mole fractions in the laboratory experiments using a vacuum chamber at a temperature of 298 K were approximately 0.6 ppm at 1010 hPa and 1.2 ppm at 250 hPa. Two CO2 vertical profile data obtained using the CO2 sondes, which were launched on 31 January and 3 February 2011 at Moriya, were compared with the chartered aircraft data on the same days and the commercial aircraft data obtained by the Comprehensive Observation Network for TRace gases by Airliner (COTRAIL) program on the same day (31 January) and 1 d before (2 February). The difference between the CO2 sonde data and these four sets of in situ aircraft data (over the range of each balloon altitude ±100 m) up to the altitude of 7 km was 0.6±1.2 ppm (average ±1σ). In field experiments, the CO2 sonde detected an increase in CO2 concentration in an urban area and a decrease in a forested area near the surface. The CO2 sonde was shown to be a useful instrument for observing and monitoring the vertical profiles of CO2 concentration in the troposphere.

We investigate surface-layer characteristics over a mountainous ridge in the Central Himalayas, utilizing tower-based fast-response micrometeorological observations (at 12 and 27 m above ground level) for the winter months November 2013–January 2014. During this period, the site generally experienced clear skies and weak synoptic flow (wind speed

We present a method and algorithm for inverse problem solution in satellite sounding of the atmosphere for retrieval of vertical profiles of optically active gases by joint use of high-resolution thermal and near-infrared atmospheric spectra. To show the capabilities of the method, a computational experiment was performed on retrieving the vertical profile of the main methane isotopologue with simultaneous use of the simulated thermal and near-infrared spectra. The spectra simulated are similar to those measured by TANSO-FTS/GOSAT IR spectrometer. The signal-to-noise ratio in the simulated spectra was set to 350. The model experiments show higher accuracy of retrieval of the methane vertical profile and its total column in the case when both spectral bands (thermal and near-IR) are used in comparison with the case when each band is used separately.

COVID-19 induced restrictions resulted in a lowered fine aerosol particle and trace gas concentration across several urban places around the world, providing a natural opportunity to study effects of anthropogenic activities on emissions of air pollutants. Impact of sudden suspension of human activities on air pollution was analyzed by studying the change in satellite retrieved NO2 concentrations and top-down NOx emission over the urban and rural areas around Delhi. NO2 was chosen for being the most indicative of emission intensity due to its short lifetime of the order of a few hours in the planetary boundary layer. We present a robust temporal comparison of Ozone Monitoring Instrument (OMI) retrieved NO2 column density during the lockdown with the counterfactual baseline concentrations, extrapolated from the long-term trend and seasonal cycle components of NO2 using observations during 2015 to 2019. NO2 columns in the urban area of Delhi experienced an anomalous relative change ranging from 60.0% decline during the Phase 1 of lockdown (March 25-April 13, 2020) to 3.4% during the post-lockdown Phase 5. In contrast, we find no substantial reduction in NO2 concentrations over the rural areas. To clarify the quantitative impact of the lockdown measures, weekly top-down NOx emissions were estimated from TROPOspheric Monitoring Instrument (TROPOMI) retrieved NO2 by accounting for horizontal advection derived from the steady state continuity equation. NOx emissions from urban areas and power plants exhibited a mean decline of 72.19% and 53.4% respectively in Phase 1 compared to the pre-lockdown business-as-usual phase. Due to absence of confounding emission source activity during lockdown, emission estimates over urban areas and power-plants were validated with respective electricity generation reports and Google’s mobility reports. A higher anomaly in emission estimates suggests that comparison of only concentration change, without accounting for the dynamical and photochemical conditions, may mislead evaluation of lockdown impact. Our results are also useful for optimizing bottom-up emission inventories.

Japan is now operating a series of two earth observation satellites for greenhouse gas measurement from space: GOSAT launched in 2009 and GOSAT-2 launched in 2018. In this presentation, products and latest science achievements of GOSAT Satellite Series will be introduced.

CO2 observations in the free troposphere can be useful for constraining CO2 source and sink estimates at the surface since they represent CO2 concentrations away from point source emissions. The thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO) Fourier transform spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO2 concentrations in the free troposphere for about 8 years and thus could provide a dataset with which to evaluate the vertical transport of CO2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO2 product in the lower troposphere (LT) and the middle troposphere (MT) (736–287 hPa), on the basis of comparisons with CO2 profiles obtained over airports using Continuous CO2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40–20° S, 20° S–20° N, 20–40° N, and 40–60° N. TIR V1 CO2 data had consistent negative biases of 1–1.5 % compared with CME CO2 data in the LT and MT regions, with the largest negative biases at 541–398 hPa, partly due to the use of 10 µm CO2 absorption band in conjunction with 15 and 9 µm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by a transport model based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM-TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398–287 hPa), however, TIR CO2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in Southeast Asia, where CO2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.

FIRE-ARMS software was supplemented with the vector radiative transfer model VLIDORT. The new version of the software allows simulating outgoing thermal infrared radiation (TIR) from the Earth and solar shortwave infrared radiation (SWIR) reflected from the surface taking into account multiple scattering for the same atmospheric model and sensing geometry. We performed simulations of the spectra of outgoing TIR and SWIR radiation with multiple scattering in a cloudless atmosphere and compared them with the spectra measured by GOSAT satellite spectrometers in the cloudless atmosphere over Western Siberia. Analysis of calculated weighting functions shows that simultaneous use of the TIR and SWIR spectral regions will improve the height resolution in vertical profiling of methane concentrations in the atmosphere.

A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

The relative 13С content in atmospheric carbon dioxide contains information about sources and sinks of this gas and their impact on Earth’s carbon cycle. This paper represents the study on feasibility of 13CO2 atmospheric vertical profile retrieval from satellite thermal infrared spectra measured with high spectral resolution. In IASI/METOP spectra, the spectral interval is determined, in which molecular absorption is mainly bound by the given isotopologue. A comparison was made of variations in the magnitude of spectral radiance due to variations in air temperature and in relative content of 13CO2 within the limits of known from studies on the direct measurement of the isotopic composition of atmospheric carbon dioxide. Prospects for building a robust algorithm is discussed.

This study examines contribution of brick kiln (BK) industry to PM 2.5 emission over northern part of India. We analyze NASA’s MODIS and JAXA’s GCOM-C/SGLI land-atmospheric products with 3887 BK locations over the region in the period of the highest PM 2.5 concentration during December 2016 to February 2017. Our preliminary results show that more than 60% of BK occupied silt-rich areas, with more than 80% of them were located over croplands on the outskirts of urban areas, indicating proxies for PM 2.5 emission over Northern India. Initial WRF-Chem model simulations showed prominent diurnal variation of the pollutant with averaged peak concentration exceeding 1μg/m3 over the capital city of New Delhi. Future works will introduce the use of Google Earth Engine (GEE) cloud platform for identifying BK locations and incorporate them into the model to improve the simulation results.

Remote sensing data from GOSAT (Greenhouse gases Observing SATellite) and GOSAT-2 in the future ameliorate inversion analysis of greenhouse gas (GHG) emissions[1],[2]. Meso-scale atmospheric transport model AIST-MM (National Institute of Advanced Industrial Science and Technology-Mesoscale Model)[3],[4] and global-scale transport model NICAM-TM (Nonhydrostatic ICosahedral Atmospheric Model-Transport Model)[5] have been coupled for data assimilation in order to estimate CO 2 emission from mega-city Tokyo. However, forests west and north of Tokyo Metropolis in the Kantō plain generate significant biogenic CO 2 fluxes and such atmosphere-biosphere gas exchange remains to be properly calculated during the modeling processes. In this study, we use MODIS products[6],[7] to simulate regional gross primary production (GPP), vegetational and soil respirations based on Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data (BEAMS) algorithms[8],[9]. By integrating this atmosphere-terrestrial ecosystem carbon balance module to our regional inversion analysis, we aim at more precise estimation of CO 2 emission from Tokyo.

The present study shows spatio-temporal variability in carbon dioxide $$(\hbox {CO}_{2})$$ in the mid-tropospheric region over India (0–32 $$^{\mathrm{o}}\hbox {N}$$ , 60–100 $$^{\mathrm{o}}\hbox {E}$$ ) during 2003–2011. The $$\hbox {CO}_{2}$$ data used in the study is retrieved from Atmospheric Infra-Red Sounder (AIRS). Analysis of 9 yrs of data shows that the $$\hbox {CO}_{{2}}$$ exhibits a linear increasing trend of 2.01 ppm/year. Besides displaying the linear increasing trend, data show strong seasonal and annual variability. Concentration of $$\hbox {CO}_{{2}}$$ is observed to be highest around April–May (summer months), which decreases by 4–5 ppm during the monsoon months. Seasonal decrease in $$\hbox {CO}_{2}$$ concentration appeared to be influenced by the monsoonal activity. Low OLR (proxy of convection) associated with high rainfall during summer monsoon via increasing vegetation index (NDVI) appears to be the primary cause for the seasonal decrease in $$\hbox {CO}_{{2}}$$ through photosynthesis. Correlation coefficient between $$\hbox {CO}_{{2}}$$ and NDVI is of the order of –0.90 suggesting vegetation as a seasonal sink of $$\hbox {CO}_{{2}}$$ . Decrease in $$\hbox {CO}_{{2}}$$ concentration takes place at a delay of 2–3 months of rainfall. However, convection seems to be another component, which causes uplifting of $$\hbox {CO}_{{2}}$$ during dry summer (April and May) making high concentration in the mid-troposphere as shown by increase in the planetary boundary layer (PBL) height in this period. Eastward propagating intra-seasonal oscillations with period 30–40 days in OLR anomalies are found to modulate (with a fluctuation of 1–2 ppm) mid-tropospheric $$\hbox {CO}_{{2}}$$ . Analysis of seasonal anomalies in $$\hbox {CO}_{{2}}$$ over four different regions (northern, southern, western and eastern) of India is also being investigated. The regional variability of $$\hbox {CO}_{2}$$ in northern region show marginal larger values suggesting more anthropogenic activities especially during late winter.

The Thermal and Near Infrared Sensor for Carbon Observation (TANSO)–Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing carbon dioxide (CO2) concentrations in several atmospheric layers in the thermal infrared (TIR) band since its launch. This study compared TANSO-FTS TIR version 1 (V1) CO2 data and CO2 data obtained in the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project in the upper troposphere and lower stratosphere (UTLS), where the TIR band of TANSO-FTS is most sensitive to CO2 concentrations, to validate the quality of the TIR V1 UTLS CO2 data from 287 to 162 hPa. We first evaluated the impact of considering TIR CO2 averaging kernel functions on CO2 concentrations using CO2 profile data obtained by the CONTRAIL Continuous CO2 Measuring Equipment (CME), and found that the impact at around the CME level flight altitudes (∼ 11 km) was on average less than 0.5 ppm at low latitudes and less than 1 ppm at middle and high latitudes. From a comparison made during flights between Tokyo and Sydney, the averages of the TIR upper-atmospheric CO2 data were within 0.1 % of the averages of the CONTRAIL CME CO2 data with and without TIR CO2 averaging kernels for all seasons in the Southern Hemisphere. The results of comparisons for all of the eight airline routes showed that the agreements of TIR and CME CO2 data were worse in spring and summer than in fall and winter in the Northern Hemisphere in the upper troposphere. While the differences between TIR and CME CO2 data were on average within 1 ppm in fall and winter, TIR CO2 data had a negative bias up to 2.4 ppm against CME CO2 data with TIR CO2 averaging kernels at the northern low and middle latitudes in spring and summer. The negative bias at the northern middle latitudes resulted in the maximum of TIR CO2 concentrations being lower than that of CME CO2 concentrations, which led to an underestimate of the amplitude of CO2 seasonal variation.

A novel, practical observation system for measuring tropospheric carbon dioxide (CO2) concentrations using a non-dispersive infrared analyzer carried by a small helium-filled balloon (CO2 sonde), has been developed for the first time. Onboard calibrations, using CO2 standard gases, is possible to measure the vertical profiles of atmospheric CO2 accurately with a 240–400 m altitude resolution. The standard deviations (1σ) of the measured mixing ratios in the laboratory experiments using a vacuum chamber at a temperature of 298 K were approximately 0.6 ppm at 1010 hPa and 1.2 ppm at 250 hPa. Compared with in situ aircraft data, although the difference up to the altitude of 7 km was 0.6 ± 1.2 ppm, this bias and difference were within the precision of the CO2 sonde. In field experiments, the CO2 sonde detected an increase in CO2 concentration in an urban area and a decrease in a forested area near the surface. The CO2 sonde was shown to be a useful instrument for observing and monitoring the vertical profiles of CO2 concentration in the troposphere.

The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO2 retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO2 concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO2 adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO2. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO2 from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO2 was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO2 analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified.

Site environments and instrumental characteristics of carbon dioxide (CO2) measurements operated by local governments in the Kanto Plain, the center of which is Tokyo were summarized for this study. The observation sites were classified into environments of three types: urban, suburban, and woodland. Based on a few decades of accumulated hourly data, the diurnal and seasonal variations of CO2 concentrations were analyzed as a composite of anomalies from annual means recorded for each site. In urban areas, the highest concentrations appear before midnight in winter. The second peak corresponds to the morning rush hour and strengthening of the inversion layer. Suburban areas can be characterized as having the highest concentration before dawn and the lowest concentration during the daytime in summer in association with the activation of respiration and photosynthesis of vegetation. In these areas, concentration peaks also appear during the morning rush hour. Woodland areas show background features, with the highest concentration in early spring: higher than the global background by about 5 ppmv.

We have validated CO2 and CH4 data retrieved from TIR band of GOSAT/TANSO-FTS based on comparisons with aircraft observations. The accuracy of GHG measurements by TIR bands of GOSAT-2/TANSO-FTS-2 are expected to be much improved.

Greenhouse gases Observing SATellite (GOSAT) and its successor, GOSAT-2, are Japanese earth observation satellites for greenhouse gas measurement from space using Fourier transform spectrometers. Instrument specifications, together with GOSAT achievements and GOSAT-2 expectations, will be introduced.

This chapter reviews the cloud screening and cloud property retrieval techniques used in the operational processing of five space-borne thermal infrared hyper-spectral sounders, AIRS, IASI, TES, TANSO-FTS, and CrIS. In the primary sections, the sounder specifications and the concepts of the widely used three basic cloud detection techniques, the threshold method which is based on the brightness temperature difference in the atmospheric window region, the CO2 slicing method, and the split window method are described. After that, the strategy of cloud screening and property retrieval techniques developed to utilize their large number of channels and geometries of footprints for each sounder are reviewed, respectively.

A series of ground-based high-resolution Fourier-transform measurements of atmospheric transmittance in the near infrared region (4000–10000 cm−1) recorded at the Ural Atmospheric Station in 2012–2013 was processed in order to retrieve relative concentrations of CO2 and CH4 in the atmospheric column. Retrieved values of methane concentration do not show a noticeable seasonal cycle, while retrieved CO2 concentrations show clear seasonal variations with high amplitude, which are also observed in GOSAT measurements over the Ural region. The estimated amplitude of CO2 seasonal variations is 14–15 ppm. The comparison between CO2 ground-based and GOSAT measurements shows a good agreement, while satellite values are overestimated by approximately 3 ppm. There is no noticeable correlation between CH4 values, which could be explained by the presence of local methane sources in the area of GOSAT observations.

The algorithm for atmospheric methane distribution retrieval in atmosphere from IASI spectra has been developed. The feasibility of Levenberg-Marquardt method for atmospheric methane total column amount retrieval from the spectra measured by IASI/METOP modified for the case of lack of a priori covariance matrices for methane vertical profiles is studied in this paper. Method and algorithm were implemented into software package together with iterative estimation of a posteriori covariance matrices and averaging kernels for each individual retrieval. This allows retrieval quality selection using the properties of both types of matrices. Methane (XCH4) retrieval by Levenberg-Marquardt method from IASI/METOP spectra is presented in this work. NCEP/NCAR reanalysis data provided by ESRL (NOAA, Boulder, USA) were taken as initial guess. Surface temperature, air temperature and humidity vertical profiles are retrieved before methane vertical profile retrieval. The data retrieved from ground-based measurements at the Ural Atmospheric Station and data of L2/IASI standard product were used for the verification of the method and results of methane retrieval from IASI/METOP spectra.

In this paper we present a method, using methane as example, which allows more accurate greenhouse gases retrieval in the Earth's atmosphere. Using the new version of the FIRE-ARMS software, supplemented with the VLIDORT vector radiation transfer model, we carried out joint methane retrieval from TIR (Thermal Infrared Range) and SWIR (ShortWavelength Infrared Range) GOSAT spectra using optimal estimation method. MACC reanalysis data from the European Center for Medium-Range Forecasts (ECMWF), supplemented by data from aircraft measurements of the HIPPO experiment were used as a statistical ensemble.

CO2 observations in the free troposphere can be useful for constraining CO2 source and sink estimates at the surface due to their representativeness being away from local point sources of CO2. The thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO)−Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO2 concentrations in the free troposphere for about 8 years, and thus could provide a dataset with which to evaluate the vertical transport of CO2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO2 product in the lower troposphere (LT) and the middle troposphere (MT) (736–287 hPa), on the basis of comparisons with CO2 profiles obtained over airports using Continuous CO2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40°S–20°S, 20° S–20° N, 20° N–40° N, and 40° N–60° N. TIR V1 CO2 data had consistent negative biases of 1–1.5 % compared with CME CO2 data in the LT and MT regions, with the largest negative biases at 541–398 hPa, partly due to the use of 10-μm CO2 absorption band in conjunction with 15-μm and 9-μm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by Nonhydrostatic ICosahedral Atmospheric Model (NICAM)-based transport model (TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398–287 hPa), however, TIR CO2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in East Asia where CO2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.

This paper investigates the scientific value of retrieving H218O and HDO columns in addition to H216O columns from high-resolution ground-based near-infrared spectra. We present a set of refined H216O, H218O, and HDO spectral windows. The retrieved H216O, H218O, and HDO columns are used for an a posteriori calculation of columnar δD and δ18O. We estimate the uncertainties for the so-calculated columnar δD and δ18O values. These estimations include uncertainties due to the measurement noise, errors in the a priori data, and uncertainties in spectroscopic parameters. Time series of δ18O obtained from ground-based FTIR (Fourier transform infrared) spectra are presented for the first time. For our study we use a full physics isotopic general circulation model (ECHAM5-wiso). We show that the full physics simulation of HDO and H218O can already be reasonably predicted from the H216O columns by a simple linear regression model (scatter values between full physics and linear regression simulations are 35 and 4‰ for HDO and H218O, respectively). We document that the columnar δD and δ18O values as calculated a posteriori from the retrievals of H216O, H218O, and HDO show a better agreement with the ECHAM5-wiso simulation than the δD and δ18O values as calculated from the H216O retrievals and the simple linear regression model. This suggests that the H218O and HDO column retrievals add complementary information to the H216O retrievals. However, these data have to be used carefully, because of the different vertical sensitivity of the H216O, H218O, and HDO columnar retrievals. Furthermore, we have to note that the retrievals use reanalysis humidity profiles as a priori input and the results are thus not independent of the reanalysis data.

The metropolitan area of Tokyo, the capital of Japan, emits a large amount of carbon dioxide (CO2), an anthropogenic greenhouse gas. We measured the day-time column-averaged dry-air molar mixing ratios of atmospheric CO2, XCO2, in the central area of Tokyo during September 2014 – August 2016 using a desktop optical spectrum analyzer. The observed seasonal cycle is compared with the seasonal cycle that is observed at the Total Carbon Column Observing Network (TCCON) site in Tsukuba, which is located 60 km to the northeastern direction of Tokyo. The differences in XCO2 between the two sites are high (∼5 ppm) during December – February and low (∼0.5 ppm) during June – September. The characteristic variations of XCO2 in Tokyo are interpreted in terms of local emission sources and surface meteorological data, by referring to the variations in the concentrations of surface CO2. The sharp peaks in XCO2 at both the Tokyo and Tsukuba sites in July are interpreted in terms of local air retention in the areas, as indicated by the aircraft profiles and wind-flow forward trajectory calculations. Finally, we compare the ground-based column measurements with the top-down satellite column observations. Keywords: Emission, Megacity, Urban area, Seasonal cycle, Power plant

In this paper we used VLIDORT procedures as a forward model in FIRE-ARMS code for modeling the spectra and Jacobian calculation in both thermal infrared (TIR) and short wavelength infrared spectral bands (SWIR). Simulated spectra are compared with spectra measured under clear sky conditions over Western Siberia by the Fourier spectrometer TANSO-FTS, on board of the GOSAT satellite. With the new software, operating simultaneously in both bands, Jacobians were calculated in order to retrieve vertical profiles of carbon dioxide and methane in TIR and SWIR. Data from NCEP/NCAR reanalysis were used as initial guess model atmosphere.

The algorithm for atmospheric methane distribution retrieval in atmosphere from IASI spectra has been developed. Wellknown Levenberg-Marquardt algorithm is expanded for the case of absence of a priori statistics for methane vertical profiles. A modified technique for iterative calculation of averaging kernels and a posteriori errors for every spectrum is suggested. Levenberg-Marquardt method parameter selection for methane (XCH4) retrieval from IASI/METOP spectra is presented in this work. NCEP/NCAR reanalysis data provided by ESRL (NOAA, Boulder, USA) were taken as initial guess. Surface temperature, air temperature and humidity vertical profiles are retrieved before methane vertical profile retrieval. The data of Monitoring Atmospheric Composition and Climate reanalysis of the European Centre for Medium- Range Weather Forecasts (МАСС/ECMWF) were used for the validation of the method and results of methane retrieval from IASI/METOP.

A 4-dimensional variational method (4D-Var) is a popular technique for inverse modeling of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines off-line forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. It is found that a system of forward and adjoint models that has less model errors but with non-linearity performs better than another system that conserves linearity with exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is confirmed; the global error is reduced by about 15 % by adding prior error correlations that are simply designed. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to a global scale. The optimization algorithm introduced in the new system does not require difficult decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

A 4-dimensional variational (4D-Var) method is a popular algorithm for inverting atmospheric greenhouse gas (GHG) measurements. In order to meet the computationally intense 4D-Var iterative calculation, off-line forward and adjoint transport models are developed based on the Nonhydorstatic ICosahedral Atmospheric Model (NICAM). By introducing flexibility into the temporal resolution of the input meteorological data, the forward model developed in this study is not only computationally efficient but is also found to nearly match the transport performance of the on-line model. In a transport simulation of atmospheric carbon dioxide (CO2), the data-thinning error (error resulting from reduction in the time resolution of the meteorological data used to drive the off-line transport model) is minimized by employing high temporal resolution data of the vertical diffusion coefficient; with a lower temporal resolution, significant concentration biases near the surface are introduced. The new adjoint model can be run in discrete or continuous adjoint mode for the advection process. The discrete adjoint is characterized by perfect adjoint relationship with the forward model that switches off the flux limiter, while the continuous adjoint is characterized by imperfect but reasonable adjoint relationship with its corresponding forward model. In the latter case, both the forward and adjoint models use the flux limiter to ensure the monotonicity of tracer concentrations and sensitivities. Trajectory analysis for high-CO2 concentration events are performed to test adjoint sensitivities; we also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport. Both the off-line forward and adjoint models have computational efficiency about ten times more than that of the on-line model. A description of our new 4D-Var system that includes an optimization method, along with its application in an atmospheric CO2 inversion and the effects of using either the discrete or continuous adjoint method, is presented in an accompanying paper (Niwa et al., 2016).

Numerical simulation and validation of three-dimensional structure of atmospheric carbon dioxide (CO2) is necessary for quantification of transport model uncertainty and its role on surface flux estimation by inverse modeling. Simulations of atmospheric CO2 were performed using four transport models and two sets of surface fluxes compared with an aircraft measurement dataset of Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL), covering various latitudes, longitudes, and heights. Under this transport model intercomparison project, spatiotemporal variations of CO2 concentration for 2006–2007 were analyzed with a three-dimensional perspective. Results show that the models reasonably simulated vertical profiles and seasonal variations not only over northern latitude areas but also over the tropics and southern latitudes. From CONTRAIL measurements and model simulations, intrusion of northern CO2 in to the Southern Hemisphere, through the upper troposphere, was confirmed. Furthermore, models well simulated the vertical propagation of seasonal variation in the northern free troposphere. However, significant model-observation discrepancies were found in Asian regions, which are attributable to uncertainty of the surface CO2 flux data. In summer season, differences in latitudinal gradients by the fluxes are comparable to or greater than model-model differences even in the free troposphere. This result suggests that active summer vertical transport sufficiently ventilates flux signals up to the free troposphere and the models could use those for inferring surface CO2 fluxes.

The Ural Atmospheric Fourier Station (UAFS) based on a Bruker IFS-125M Fourier spectrometer conjugated with an A547N automated solar tracker is described. The UAFS is located in the forest area (57.038°N; 59.545°E) and is intended for trace gas monitoring in the background atmosphere. The examples of solar-radiation near-IR atmospheric transmittance spectra measured with a high spectral resolution are presented, as well as the first results of retrieval of the heavy water fraction in the Ural atmosphere.

A tracer advection scheme for a three-dimensional icosahedral grid model is developed. Then, its tracer transport performance is evaluated using realistic flow fields. The consistency with continuity (CWC) scheme is newly introduced to a three-dimensionally monotonic scheme using existing techniques of an upwind-biased scheme and the intermediate density method. The CWC guarantees mass conservation and Lagrangian conservation, both of which are important properties for tracer transport. In addition, the scheme is positive definite. This transport scheme is implemented with the nonhydrostatic icosahedral atmospheric model and transport simulations are performed. A comparison with radon observations reveals that the proposed method reproduces high-concentration events more realistically than the original method does. Furthermore, results show that the proposed method has less numerical diffusion and is superior to the original method in terms of a sharper gradient.

We present further development of the empirical orthogonal functions (EOF)-based retrieval algorithm. The algorithm output is a regression formula that relates principal components of the reflected sunlight spectra with CO2 total column amount. The algorithm was implemented and tested for the observations from the Japanese satellite Greenhouse gases Observing Satellite (GOSAT). Training of the EOF-based algorithm with the collocated ground-based and space-borne data (e.g., Total Carbon Column Observing Network and GOSAT observations, respectively) was shown to impose some errors that were interpreted as a result of implicit averaging over the collocation area. Alternative training with the small subset (∼5 % to 10%) of the full-physics algorithm is free of such errors; however, this option requires additional filtering of the space-borne observations that are strongly affected by atmospheric light scattering. This filtering was implemented by the comparison of the EOF-regression estimates of surface pressure with corresponding meteorological data.

The thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO)–Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing carbon dioxide (CO2) concentrations in several atmospheric layers since its launch. This study compared TANSO-FTS TIR V1.0 CO2 data and CO2 data obtained in the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project in the upper troposphere and lower stratosphere (UTLS), where the TIR band of TANSO-FTS is most sensitive to CO2 concentrations, to validate the quality of the TIR V1.0 UTLS CO2 data from 287 to 162 hPa. From a comparison made during flights between Tokyo and Sydney, the averages of the TIR upper atmospheric CO2 data agreed well with the averages of the data obtained by the CONTRAIL Continuous CO2 Measuring Experiment (CME) within 0.1 % for all of the seasons in the Southern Hemisphere. The results of a comparison for all of the eight airline routes showed that the agreement between the TIR and CONTRAIL CO2 data was within 0.5 % on average in the Northern Hemisphere, which was better than the agreement between a priori and CONTRAIL CO2 data. The quality of TIR lower stratospheric CO2 data depends largely on the information content, and therefore has a seasonal dependence. In high latitudes, TIR V1.0 lower stratospheric CO2 data are only valid in the summer. The magnitude of bias in the TIR upper atmospheric CO2 data did not have a clear longitudinal dependence. The comparison results for flights in northern low and middle latitudes showed that the agreement between TIR and CONTRAIL CO2 data in the upper troposphere was worse in the spring and summer than in the fall and winter. This could be attributed to a larger negative bias in the upper atmospheric a priori CO2 data in the spring and summer and a seasonal dependence of spectral bias in TANSO-FTS TIR Level 1B (L1B) radiance data. The negative bias in northern middle latitudes made the maximum of TIR CO2 concentrations lower than that of CONTRAIL CO2 concentrations, which leads to underestimate the amplitude of CO2 seasonal variation.

Remote sensing of the atmospheric greenhouse gases, methane (CH4) and carbon dioxide (CO2), contributes to the understanding of global warming and climate change. A portable ground-based instrument consisting of a commercially available desktop optical spectrum analyzer and a small sun tracker has been applied to measure the column densities of atmospheric CH4 and CO2 at Yanting observation station in a mountainous paddy field of the Sichuan Basin from September to November 2013. The column-averaged dry-air molar mixing ratios, XCH4/XCO2, are compared with those retrieved by satellite observations in the Sichuan Basin and by ground-based network observations in the same latitude zone as the Yanting observation station.

The space and time variabilities of methane (CH4) total column and upper tropospheric mixing ratios are analyzed above the Mediterranean Basin (MB) as part of the Chemical and Aerosol Mediterranean Experiment (ChArMEx) programme. Spaceborne measurements from the Thermal And Near infrared Sensor for carbon Observations-Fourier Transform Spectrometer (TANSO-FTS) instrument on the Greenhouse gases Observing SATellite (GOSAT) satellite, the Atmospheric InfraRed Spectrometer (AIRS) on the AURA platform and the Infrared Atmospheric Sounder Interferometer (IASI) instrument aboard the MetOp-A platform are used in conjunction with model results from the Chemical Transport Model (CTM) MOCAGE, and the Chemical Climate Models (CCMs) CNRM-AOCCM and LMDz-OR-INCA (according to different emission scenarios). In order to minimize systematic errors in the spaceborne measurements, we have only considered maritime pixels over the MB. The period under interest spans from 2008 to 2011 considering satellite and MOCAGE data and, regarding the CCMs, from 2001 to 2010. An East-West gradient in CH4 is observed and modelled whatever the season considered. In winter, air masses mainly originating from Atlantic Ocean and Europe tend to favour an elevated amount of mid-to-upper tropospheric CH4 in the West vs. the East of the MB, with a general upward transport above the MB. In summer, the meteorological state of the MB is changed, favouring air from Northern Africa and Middle East together with Atlantic Ocean and Europe, with a general downward motion above the MB. The Asian Monsoon traps and uplifts high amounts of CH4 that are transported towards North Africa and Middle East by the Asian Monsoon Anticyclone to finally reach and descent in the East of the MB. Consequently, the mid-to-upper tropospheric CH4 is much greater in the East than in the West of the MB. The seasonal variation of the difference in CH4 between the East and the West MB does show a maximum in summer for pressures from 500 to 100 hPa considering both spaceborne measurements and model results whatever the emission scenarios used. From this study, we can conclude that CH4 in the mid-to-upper troposphere over the MB is mainly affected by long-range transport, particularly intense in summer from Asia. In the low-to-mid troposphere, the local sources of emission in the vicinity of the MB mainly affect the CH4 variability.