scholarly journals Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data

2016 ◽  
Author(s):  
M. Inoue ◽  
I. Morino ◽  
O. Uchino ◽  
T. Nakatsuru ◽  
Y. Yoshida ◽  
...  
Keyword(s):  
Measurement Data ◽  
Correction Method ◽  
Temporal Variations ◽  
Department Of Energy ◽  
Total Carbon ◽  
Japan Meteorological Agency ◽  
Aircraft Measurement ◽  
Observation Network ◽  
Systematic Biases ◽  
Aircraft Data

Abstract. We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously-retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the U.S. Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole- to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically-derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present latitudinal distributions and temporal variations of the derived GOSAT biases.

scholarly journals Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data

2016 ◽  
Vol 9 (8) ◽  
pp. 3491-3512 ◽  
Author(s):  
Makoto Inoue ◽  
Isamu Morino ◽  
Osamu Uchino ◽  
Takahiro Nakatsuru ◽  
Yukio Yoshida ◽  
...  
Keyword(s):  
Measurement Data ◽  
Correction Method ◽  
Temporal Variations ◽  
Department Of Energy ◽  
Total Carbon ◽  
Japan Meteorological Agency ◽  
Aircraft Measurement ◽  
Observation Network ◽  
The Us ◽  
Systematic Biases

Abstract. We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

scholarly journals Validation of XCO<sub>2</sub> derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data

2013 ◽  
Vol 13 (19) ◽  
pp. 9771-9788 ◽  
Author(s):  
M. Inoue ◽  
I. Morino ◽  
O. Uchino ◽  
Y. Miyamoto ◽  
Y. Yoshida ◽  
...  
Keyword(s):  
Standard Deviation ◽  
A Priori ◽  
Measurement Data ◽  
Department Of Energy ◽  
Minor Effect ◽  
Aircraft Measurements ◽  
Aircraft Measurement ◽  
Additional Information ◽  
Observation Network ◽  
A Minor

Abstract. Column-averaged dry air mole fractions of carbon dioxide (XCO2) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were validated with aircraft measurements by the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. To calculate XCO2 based on aircraft measurements (aircraft-based XCO2), tower measurements and model outputs were used for additional information near the surface and above the tropopause, respectively. Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAKs) and the shape of a priori profiles on the aircraft-based XCO2 calculation. The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than ±0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2. We compared GOSAT data retrieved within ±2 or ±5° latitude/longitude boxes centered at each aircraft measurement site to aircraft-based data measured on a GOSAT overpass day. The results indicated that GOSAT XCO2 over land regions agreed with aircraft-based XCO2, except that the former is biased by −0.68 ppm (−0.99 ppm) with a standard deviation of 2.56 ppm (2.51 ppm), whereas the averages of the differences between the GOSAT XCO2 over ocean and the aircraft-based XCO2 were −1.82 ppm (−2.27 ppm) with a standard deviation of 1.04 ppm (1.79 ppm) for ±2° (±5°) boxes.

scholarly journals Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data

2019 ◽  
Vol 11 (3) ◽  
pp. 290 ◽  
Author(s):  
Tran Thi Ngoc Trieu ◽  
Isamu Morino ◽  
Hirofumi Ohyama ◽  
Osamu Uchino ◽  
Ralf Sussmann ◽  
...  
Keyword(s):  
Bias Correction ◽  
Correction Method ◽  
Regression Method ◽  
Total Carbon ◽  
Multilinear Regression ◽  
Bias Correction Method ◽  
Empirical Correction ◽  
Systematic Biases ◽  
Temporal And Spatial ◽  
Global Bias

This study evaluated three bias correction methods of systematic biases in column-averaged dry-air mole fraction of water vapor (XH2O) data retrieved from Greenhouse Gases Observing Satellite (GOSAT) Short-Wavelength Infrared (SWIR) observations compared with ground-based data from the Total Carbon Column Observing Network (TCCON). They included an empirically multilinear regression method, altitude bias correction method, and combination of altitude and empirical correction for three cases defined by the temporal and spatial collocation around TCCON site. The results showed that large altitude differences between GOSAT observation points and TCCON instruments are the main cause of bias, and the altitude bias correction method is the most effective bias correction method. The lowest biases result from GOSAT SWIR XH2O data within a 0.5° 0.5° latitude longitude box centered at each TCCON site matched with TCCON XH2O data averaged over ±15 min of the GOSAT overpass time. Considering land data, the global bias changed from −1.3 ± 9.3% to −2.2 ± 8.5%, and station bias from −2.3 ± 9.0% to −1.7 ± 8.4%. In mixed land and ocean data, global bias and station bias changed from −0.3 ± 7.6% and −1.9 ± 7.1% to −0.8 ± 7.2% and −2.3 ± 6.8%, respectively, after bias correction. The results also confirmed that the fine spatial and temporal collocation criteria are necessary in bias correction methods.

scholarly journals Calibration of column-averaged CH<sub>4</sub> over European TCCON FTS sites with airborne in-situ measurements

2012 ◽  
Vol 12 (1) ◽  
pp. 1517-1551 ◽  
Author(s):  
M. C. Geibel ◽  
J. Messerschmidt ◽  
C. Gerbig ◽  
T. Blumenstock ◽  
F. Hase ◽  
...  
Keyword(s):  
Careful Analysis ◽  
Calibration Method ◽  
In Situ Measurements ◽  
Calibration Factor ◽  
Total Carbon ◽  
Improved Method ◽  
Observation Network ◽  
First Time ◽  
Aircraft Data

Abstract. In September/October 2009, six ground-based Fourier Transform Spectrometers (FTS) of the Total Carbon Column Observation Network (TCCON) in Europe were calibrated with aircraft in-situ measurements for the first time. The campaign was part of the Infrastructure for Measurement of the European Carbon Cycle (IMECC) project. During this campaign aircraft in-situ profiles of CO2, CH4, CO and H2O (from continuous measurements) as well as N2O, H2, and SF6 (from flasks) were taken close to the FTS sites. The aircraft data had a vertical coverage ranging from approximately 300 to 13 000 m, corresponding to ~80% of the total atmospheric column seen by the FTS. This study summarizes the calibration results for CH4. Using similar methods, the resulting calibration factor of 0.978 ± 0.002 (±1 σ) from the IMECC campaign agreed very well with the results that Wunch et al. (2010) had derived for TCCON instruments in North America, Australia, New Zealand, and Japan. By adding the data of the previous calibration of Wunch et al. (2010), the uncertainty of the calibration factor could be reduced by a factor of three. A careful analysis of the calibration method used by Wunch et al. (2010) revealed that the incomplete vertical coverage of the aircraft profiles can lead to a bias in the calibration factor. This bias can be compensated with a new iterative approach that we developed. Using this improved method, we derived a significantly lower calibration factor of 0.974 ± 0.002 (±1 σ). This corresponds to a correction of all TCCON CH4 measurements by roughly −7 ppb.

scholarly journals Validation of XCO<sub>2</sub> derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data

2013 ◽  
Vol 13 (2) ◽  
pp. 3203-3246 ◽  
Author(s):  
M. Inoue ◽  
I. Morino ◽  
O. Uchino ◽  
Y. Miyamoto ◽  
Y. Yoshida ◽  
...  
Keyword(s):  
A Priori ◽  
Measurement Data ◽  
Minor Effect ◽  
Aircraft Measurements ◽  
Gap Filling ◽  
Aircraft Measurement ◽  
Mixing Ratios ◽  
Observation Network ◽  
Matched Data ◽  
A Minor

Abstract. Column-averaged volume mixing ratios of carbon dioxide (XCO2) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were compared with aircraft measurements by the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), and the National Institute for Environmental Studies (NIES). Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAK) and the shape of a priori profiles on the calculation of XCO2 based on aircraft measurements (aircraft-based XCO2). The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than 0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2. In this study, two approaches were used to validate GOSAT products (Ver. 02.00). First, we performed a comparison of GOSAT data retrieved within ±2-degree or ±5-degree latitude/longitude boxes centered at each aircraft measurement site and aircraft-based data measured on a GOSAT overpass day (i.e. extraction of temporally matched cases). As this method resulted in no matched data for observation sites where no aircraft measurement was made on the GOSAT overpass day, we also attempted to validate GOSAT products by gap-filling the aircraft-based XCO2 time series through curve fitting. Both methods indicated that GOSAT XCO2 agreed well with aircraft-based XCO2, except that the former is negatively biased by 1–2 ppm with a standard deviation of 1–3 ppm.

scholarly journals Validation of XCH<sub>4</sub> derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data

2014 ◽  
Vol 7 (5) ◽  
pp. 4729-4774
Author(s):  
M. Inoue ◽  
I. Morino ◽  
O. Uchino ◽  
Y. Miyamoto ◽  
T. Saeki ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Measurement Data ◽  
Department Of Energy ◽  
Aircraft Measurement ◽  
The Us ◽  
Temporal Interpolation ◽  
The Difference ◽  
The Impact ◽  
Data Screening ◽  
Good Agreement

Abstract. Column-averaged dry-air mole fractions of methane (XCH4), retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) spectra, were validated by using aircraft measurement data from the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. In the calculation of XCH4 from aircraft measurements (aircraft-based XCH4), other satellite data were used for the CH4 profiles above the tropopause. We proposed a data-screening scheme for aircraft-based XCH4 for reliable validation of GOSAT XCH4. Further, we examined the impact of GOSAT SWIR column averaging kernels (CAK) on the aircraft-based XCH4 calculation and found that the difference between aircraft-based XCH4 with and without the application of the GOSAT CAK was less than ±9 ppb at maximum, with an average difference of −0.5 ppb. We compared GOSAT XCH4 Ver. 02.00 data retrieved within ±2° or ±5° latitude/longitude boxes centered at each aircraft measurement site with aircraft-based XCH4 measured on a GOSAT overpass day. In general, GOSAT XCH4 was in good agreement with aircraft-based XCH4. However, over land, the GOSAT data showed a positive bias of 1.5 ppb (2.0 ppb) with a standard deviation of 14.9 ppb (16.0 ppb) within the ±2° (±5°) boxes, and over ocean, the average bias was 4.1 ppb (6.5 ppb) with a standard deviation of 9.4 ppb (8.8 ppb) within the ±2° (±5°) boxes. In addition, we obtained similar results when we used an aircraft-based XCH4 time series obtained by curve fitting with temporal interpolation for comparison with GOSAT data.

scholarly journals Validation of XCH<sub>4</sub> derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data

2014 ◽  
Vol 7 (9) ◽  
pp. 2987-3005 ◽  
Author(s):  
M. Inoue ◽  
I. Morino ◽  
O. Uchino ◽  
Y. Miyamoto ◽  
T. Saeki ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Measurement Data ◽  
Department Of Energy ◽  
Aircraft Measurement ◽  
The Us ◽  
Temporal Interpolation ◽  
The Difference ◽  
The Impact ◽  
Data Screening ◽  
Good Agreement

Abstract. Column-averaged dry-air mole fractions of methane (XCH4), retrieved from Greenhouse gases Observing SATellite (GOSAT) short-wavelength infrared (SWIR) spectra, were validated by using aircraft measurement data from the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. In the calculation of XCH4 from aircraft measurements (aircraft-based XCH4), other satellite data were used for the CH4 profiles above the tropopause. We proposed a data-screening scheme for aircraft-based XCH4 for reliable validation of GOSAT XCH4. Further, we examined the impact of GOSAT SWIR column averaging kernels (CAK) on the aircraft-based XCH4 calculation and found that the difference between aircraft-based XCH4 with and without the application of the GOSAT CAK was less than ±9 ppb at maximum, with an average difference of −0.5 ppb. We compared GOSAT XCH4 Ver. 02.00 data retrieved within ±2° or ±5° latitude–longitude boxes centered at each aircraft measurement site with aircraft-based XCH4 measured on a GOSAT overpass day. In general, GOSAT XCH4 was in good agreement with aircraft-based XCH4. However, over land, the GOSAT data showed a positive bias of 1.5 ppb (2.0 ppb) with a standard deviation of 14.9 ppb (16.0 ppb) within the ±2° (±5°) boxes, and over ocean, the average bias was 4.1 ppb (6.5 ppb) with a standard deviation of 9.4 ppb (8.8 ppb) within the ±2° (±5°) boxes. In addition, we obtained similar results when we used an aircraft-based XCH4 time series obtained by curve fitting with temporal interpolation for comparison with GOSAT data.

scholarly journals Calibration of column-averaged CH<sub>4</sub> over European TCCON FTS sites with airborne in-situ measurements

2012 ◽  
Vol 12 (18) ◽  
pp. 8763-8775 ◽  
Author(s):  
M. C. Geibel ◽  
J. Messerschmidt ◽  
C. Gerbig ◽  
T. Blumenstock ◽  
H. Chen ◽  
...  
Keyword(s):  
Meteorological Parameters ◽  
Careful Analysis ◽  
Calibration Method ◽  
Calibration Factor ◽  
Total Carbon ◽  
Aircraft Measurements ◽  
Observation Network ◽  
First Time ◽  
Aircraft Data

Abstract. In September/October 2009, six European ground-based Fourier Transform Spectrometers (FTS) of the Total Carbon Column Observation Network (TCCON) were calibrated for the first time using aircraft measurements. The campaign was part of the Infrastructure for Measurement of the European Carbon Cycle (IMECC) project. During this campaign, altitude profiles of several trace gases and meteorological parameters were taken close to the FTS sites (typically within 1–2 km distance for flight altitudes below 5000 m). Profiles of CO2, CH4, CO and H2O were measured continuously. N2O, H2, and SF6 were later derived from flask measurements. The aircraft data had a vertical coverage ranging from approximately 300 to 13 000 m, corresponding to ~80% of the total atmospheric column seen by the FTS. This study summarizes the calibration results for CH4. The resulting calibration factor of 0.978 ± 0.002 (±1 σ) from the IMECC campaign agreed very well with the results that Wunch et al. (2010) had derived for TCCON instruments in North America, Australia, New Zealand, and Japan using similar methods. By combining our results with the data of Wunch et al. (2010), the uncertainty of the calibration factor could be reduced by a factor of three (compared to using only IMECC or only Wunch et al. (2010) data). A careful analysis of the calibration method used by Wunch et al. (2010) revealed that the incomplete vertical coverage of the aircraft profiles can lead to a bias in the calibration factor. This bias can be compensated with a new iterative approach that we developed. Using this improved method, we derived a significantly lower calibration factor of 0.974 ± 0.002 (±1 σ). This corresponds to a correction of all TCCON CH4 measurements by roughly −7 ppb.

scholarly journals A newly identified calculation discrepancy of the Sunset semi-continuous carbon analyzer

2014 ◽  
Vol 7 (7) ◽  
pp. 1969-1977 ◽  
Author(s):  
G. J. Zheng ◽  
Y. Cheng ◽  
K. B. He ◽  
F. K. Duan ◽  
Y. L. Ma
Keyword(s):  
Occupational Safety ◽  
Single Point ◽  
Correction Method ◽  
Total Carbon ◽  
Carbonaceous Aerosol ◽  
Optical Data ◽  
Baseline Correction ◽  
Safety And Health ◽  
Corrected Data ◽  
Carbon Load

Abstract. The Sunset semi-continuous carbon analyzer (SCCA) is an instrument widely used for carbonaceous aerosol measurement. Despite previous validation work, in this study we identified a new type of SCCA calculation discrepancy caused by the default multipoint baseline correction method. When exceeding a certain threshold carbon load, multipoint correction could cause significant total carbon (TC) underestimation. This calculation discrepancy was characterized for both sucrose and ambient samples, with two protocols based on IMPROVE (Interagency Monitoring of PROtected Visual Environments) (i.e., IMPshort and IMPlong) and one NIOSH (National Institute for Occupational Safety and Health)-like protocol (rtNIOSH). For ambient samples, the IMPshort, IMPlong and rtNIOSH protocol underestimated 22, 36 and 12% of TC, respectively, with the corresponding threshold being ~ 0, 20 and 25 μgC. For sucrose, however, such discrepancy was observed only with the IMPshort protocol, indicating the need of more refractory SCCA calibration substance. Although the calculation discrepancy could be largely reduced by the single-point baseline correction method, the instrumental blanks of single-point method were higher. The correction method proposed was to use multipoint-corrected data when below the determined threshold, and use single-point results when beyond that threshold. The effectiveness of this correction method was supported by correlation with optical data.

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