scholarly journals Error analysis for CO and CH<sub>4</sub> total column retrievals from SCIAMACHY 2.3 μm spectra

2008 ◽  
Vol 8 (14) ◽  
pp. 3999-4017 ◽  
Author(s):  
A. M. S. Gloudemans ◽  
H. Schrijver ◽  
O. P. Hasekamp ◽  
I. Aben
Keyword(s):  
Sensitivity Analysis ◽  
Likelihood Method ◽  
Retrieval Algorithm ◽  
Polarization Sensitivity ◽  
Line Intensities ◽  
Aerosol Scattering ◽  
Detailed Assessment ◽  
Instrument Noise ◽  
Iterative Maximum Likelihood ◽  
The Impact

Abstract. A detailed sensitivity analysis of the Iterative Maximum Likelihood Method (IMLM) algorithm and its application to the SCIAMACHY 2.3 μm spectra is presented. The sensitivity analysis includes a detailed assessment of the impact of aerosols in the 2.3 μm range. Results show that near strong aerosol sources mineral dust and biomass aerosols can have an effect of ~7–10% on the CH4 total columns retrieved from this wavelength range if aerosol scattering is neglected in the retrieval algorithm. Similar but somewhat larger effects are found for CO, but due to the larger variability of CO these errors are less important. Away from strong sources much smaller effects of a few percent are found. Using CH4 as a proxy for CO and/or including aerosol information in the retrieval algorithm significantly reduces these errors for both CO and CH4. Spectroscopic uncertainties are mostly negligible except for uncertainties in the CH4 intrinsic line intensities, which can be important. Application of the IMLM algorithm to the SCIAMACHY 2.3 μm spectra shows that the quality of the retrieved CO and CH4 total columns is good, except for a bias for large instrument-noise errors which is partly due to remaining calibration issues. Polarization sensitivity of the SCIAMACHY instrument has a negligible effect on the retrieved CO and CH4 total columns. The H2O total columns, which have to be retrieved simultaneously with CO and CH4 due to overlapping absorption lines, agree well with H2O total columns from ECMWF data. This ensures that the fit to the H2O absorptions is of sufficient quality not to hamper the retrieved CO and CH4 total columns from SCIAMACHY spectra.

scholarly journals Error analysis for CO and CH<sub>4</sub> total column retrievals from SCIAMACHY 2.3 μm spectra

2008 ◽  
Vol 8 (2) ◽  
pp. 5183-5233
Author(s):  
A. M. S. Gloudemans ◽  
H. Schrijver ◽  
O. P. Hasekamp ◽  
I. Aben
Keyword(s):  
Sensitivity Analysis ◽  
Likelihood Method ◽  
Polarization Sensitivity ◽  
Line Intensities ◽  
Detailed Assessment ◽  
Instrument Noise ◽  
Aerosol Sources ◽  
Iterative Maximum Likelihood ◽  
The Impact

Abstract. A detailed sensitivity analysis of the Iterative Maximum Likelihood Method (IMLM) algorithm and its application to the SCIAMACHY 2.3 μm spectra is presented. The sensitivity analysis includes a detailed assessment of the impact of aerosols in the 2.3 μm range. Results show that near strong aerosol sources mineral dust and biomass aerosols can have an effect of ~7–10% on the CH4 total columns retrieved from this wavelength range. Similar but somewhat larger effects are found for CO, but due to the larger variability of CO these errors are less important. Away from strong sources much smaller effects of a few percent are found. Spectroscopic uncertainties are mostly negligible except for uncertainties in the CH4 intrinsic line intensities, which can be important. Application of the IMLM algorithm to the SCIAMACHY 2.3 μm spectra shows that the quality of the retrieved CO and CH4 total columns is good, except for a bias for large instrument-noise errors which is partly due to remaining calibration issues. Polarization sensitivity of the SCIAMACHY instrument has a negligible effect on the retrieved CO and CH4 total columns. The H2O total columns, which have to be retrieved simultaneously with CO and CH4 due to overlapping absorption lines, agree well with H2O total columns from ECMWF data. This ensures that the fit to the H2O absorptions is of sufficient quality not to hamper the retrieved CO and CH4 total columns from SCIAMACHY spectra.

scholarly journals GFIT3: a full physics retrieval algorithm for remote sensing of greenhouse gases in the presence of aerosols

2021 ◽  
Vol 14 (10) ◽  
pp. 6483-6507
Author(s):  
Zhao-Cheng Zeng ◽  
Vijay Natraj ◽  
Feng Xu ◽  
Sihe Chen ◽  
Fang-Ying Gong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Los Angeles ◽  
Greenhouse Gases ◽  
High Spectral Resolution ◽  
Ratio Method ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Atmospheric Scattering ◽  
Aerosol Scattering ◽  
The Impact

Abstract. Remote sensing of greenhouse gases (GHGs) in cities, where high GHG emissions are typically associated with heavy aerosol loading, is challenging due to retrieval uncertainties caused by the imperfect characterization of scattering by aerosols. We investigate this problem by developing GFIT3, a full physics algorithm to retrieve GHGs (CO2 and CH4) by accounting for aerosol scattering effects in polluted urban atmospheres. In particular, the algorithm includes coarse- (including sea salt and dust) and fine- (including organic carbon, black carbon, and sulfate) mode aerosols in the radiative transfer model. The performance of GFIT3 is assessed using high-spectral-resolution observations over the Los Angeles (LA) megacity made by the California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS-FTS). CLARS-FTS is located on Mt. Wilson, California, at 1.67 km a.s.l. overlooking the LA Basin, and it makes observations of reflected sunlight in the near-infrared spectral range. The first set of evaluations are performed by conducting retrieval experiments using synthetic spectra. We find that errors in the retrievals of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) due to uncertainties in the aerosol optical properties and atmospheric a priori profiles are less than 1 % on average. This indicates that atmospheric scattering does not induce a large bias in the retrievals when the aerosols are properly characterized. The methodology is then further evaluated by comparing GHG retrievals using GFIT3 with those obtained from the CLARS-GFIT algorithm (used for currently operational CLARS retrievals) that does not account for aerosol scattering. We find a significant correlation between retrieval bias and aerosol optical depth (AOD). A comparison of GFIT3 AOD retrievals with collocated ground-based observations from AErosol RObotic NETwork (AERONET) shows that the developed algorithm produces very accurate results, with biases in AOD estimates of about 0.02. Finally, we assess the uncertainty in the widely used tracer–tracer ratio method to obtain CH4 emissions based on CO2 emissions and find that using the CH4/CO2 ratio effectively cancels out biases due to aerosol scattering. Overall, this study of applying GFIT3 to CLARS-FTS observations improves our understanding of the impact of aerosol scattering on the remote sensing of GHGs in polluted urban atmospheric environments. GHG retrievals from CLARS-FTS are potentially complementary to existing ground-based and spaceborne observations to monitor anthropogenic GHG fluxes in megacities.

scholarly journals SCIAMACHY CO over land and oceans: 2003–2007 interannual variability

2009 ◽  
Vol 9 (11) ◽  
pp. 3799-3813 ◽  
Author(s):  
A. M. S. Gloudemans ◽  
A. T. J. de Laat ◽  
H. Schrijver ◽  
I. Aben ◽  
J. F. Meirink ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Biomass Burning ◽  
Accurate Determination ◽  
Likelihood Method ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Noise Error ◽  
A Minor ◽  
Iterative Maximum Likelihood ◽  
Good Agreement

Abstract. We present a new method to obtain accurate SCIAMACHY CO columns over clouded ocean scenes. Based on an improved version of the Iterative Maximum Likelihood Method (IMLM) retrieval algorithm, we now have retrieved five years of data over both land and clouded ocean scenes between 2003 and 2007. The ocean-cloud method uses the CH4 columns retrieved simultaneously with the CO columns to determine the cloud top height. The CH4 cloud top height is in good agreement with the FRESCO+ cloud top height determined from UV-VIS oxygen-A band measurements, providing confidence that the CH4 cloud top height is a good diagnostic of the cloud top height over (partially) clouded ocean scenes. The CO measurements over clouded ocean scenes have been compared with collocated modeled CO columns over the same clouds and agree well. Using clouded ocean scenes quadruples the number of useful CO measurements compared to land-only measurements. The five-year CO data set over land and clouded ocean scenes presented here is based on an improved version of the IMLM algorithm which includes a more accurate determination of the random instrument-noise error for CO. This leads to a smaller spread in the differences between single CO measurements and the corresponding model values. The new version, IMLM version 7.4, also uses updated spectroscopic parameters for H2O and CH4 but this has only a minor impact on the retrieved CO columns. The five-year data set shows significant interannual variability over land and over clouded ocean scenes. Three examples are highlighted: the Asian outflow of pollution over the northern Pacific, the biomass-burning outflow over the Indian Ocean originating from Indonesia, and biomass burning in Brazil. In general there is good agreement between observed and modeled seasonal cycles and interannual variability.

scholarly journals Impact of aerosol size distribution on extinction and spectral dependence of radiances measured by the OMPS Limb profiler instrument

2018 ◽  
Author(s):  
Zhong Chen ◽  
Pawan K. Bhartia ◽  
Robert Loughman ◽  
Peter Colarco
Keyword(s):  
Size Distribution ◽  
Spectral Dependence ◽  
Aerosol Size Distribution ◽  
Retrieval Algorithm ◽  
In Situ Data ◽  
Aerosol Scattering ◽  
Scattering Phase ◽  
Scattering Phase Function ◽  
Scattering Index ◽  
The Impact

Abstract. The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) has been flying on the Suomi NPP satellite since Oct 2011. It is designed to produce ozone and aerosol vertical profiles at ~ 2 km vertical resolution over the entire sunlit globe. The current operational (V1) aerosol extinction retrieval algorithm assumes a bimodal lognormal aerosol size distribution (ASD) whose parameters were derived from in situ data taken from an aircraft. In this paper we discuss the impact on the retrieval of using an ASD derived by the Community Aerosol and Radiation Model for Atmospheres (CARMA). We find that the impact of ASD on the retrieved extinctions varies strongly with the underlying reflectivity of the scene, and the functional form of this variation is very different at different scattering angles. We also evaluate how well the two ASDs perform in explaining the spectral dependence of Aerosol Scattering Index (ASI); a dimensionless quantity that we derive from the measured radiances by subtracting out the Rayleigh contribution. ASI is easier to interpret than radiances themselves and serves as our measurement vector. The results show that even though the two ASDs produce very different aerosol scattering phase function values at small and large scattering angles, the effect of the ASD on the spectral dependence of ASI is significant only at small angles. This implies that while OMPS/LP measurements have some information to evaluate the ASDs, they are most effective only at small scattering angles, which for LP measurement geometry occur only in the northern hemisphere. Our analysis suggests that overall CARMA ASD does a better job in explaining the spectral dependence of measured ASI than the ASD used in the operational V1 algorithm.

scholarly journals GFIT3: A full physics retrieval algorithm for remote sensing of greenhouse gases in the presence of aerosols

2021 ◽  
Author(s):  
Zhao-Cheng Zeng ◽  
Vijay Natraj ◽  
Feng Xu ◽  
Sihe Chen ◽  
Fang-Ying Gong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Los Angeles ◽  
Greenhouse Gases ◽  
High Spectral Resolution ◽  
Ratio Method ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Atmospheric Scattering ◽  
Aerosol Scattering ◽  
The Impact

Abstract. Remote sensing of greenhouse gases (GHGs) in cities, where high GHG emissions are typically associated with heavy aerosol loading, is challenging due to retrieval uncertainties caused by imperfect characterization of scattering by aerosols. We investigate this problem by developing GFIT3, a full physics algorithm to retrieve GHGs (CO2 and CH4) by accounting for aerosol scattering effects in polluted urban atmospheres. In particular, the algorithm includes coarse (including sea salt and dust) and fine (including organic carbon, black carbon, and sulfate) mode aerosols in the radiative transfer model. The performance of GFIT3 is assessed using high spectral resolution observations over the Los Angeles (LA) megacity made by the California Laboratory for Atmospheric Remote Sensing–Fourier Transform Spectrometer (CLARS–FTS). CLARS–FTS is located on Mt. Wilson, California, at 1.67 km a.s.l. overlooking the LA basin, and makes observations of reflected sunlight in the near-infrared spectral range. The first set of evaluations are performed by conducting retrieval experiments using synthetic spectra. We find that errors in the retrievals of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) due to uncertainties in the aerosol optical properties and atmospheric a priori profiles are less than 1 % on average. This indicates that atmospheric scattering does not induce a large bias in the retrievals when the aerosols are properly characterised. The methodology is then further evaluated by comparing GHG retrievals using GFIT3 with those obtained from the CLARS-GFIT algorithm (used for currently operational CLARS retrievals) that does not account for aerosol scattering. We find a significant correlation between retrieval bias and aerosol optical depth (AOD). Comparison of GFIT3 AOD retrievals with collocated ground-based observations from AERONET shows that the developed algorithm produces very accurate results, with biases in AOD estimates of about 0.02. Finally, we assess the uncertainty in the widely used tracer-tracer ratio method to obtain CH4 emissions based on CO2 emissions, and find that using the CH4 / CO2 ratio effectively cancels out biases due to aerosol scattering. Overall, this study of applying GFIT3 to CLARS-FTS observations improves our understanding of the impact of aerosol scattering on the remote sensing of GHGs in polluted urban atmospheric environments. GHG retrievals from CLARS-FTS are potentially complementary to existing ground-based and space-borne observations to monitor anthropogenic GHG fluxes in megacities.

scholarly journals Validation of two independent retrievals of SCIAMACHY water vapour columns using radiosonde data

2013 ◽  
Vol 6 (1) ◽  
pp. 665-702 ◽  
Author(s):  
A. du Piesanie ◽  
A. J. M. Piters ◽  
I. Aben ◽  
H. Schrijver ◽  
P. Wang ◽  
...  
Keyword(s):  
Water Vapour ◽  
Correction Method ◽  
Short Wave ◽  
Mean Difference ◽  
Likelihood Method ◽  
Radiosonde Data ◽  
Retrieval Algorithm ◽  
Infrared Wavelength ◽  
Integrated Water Vapour ◽  
Iterative Maximum Likelihood

Abstract. Two independently derived SCIAMACHY total water vapour column (WVC) products are compared with integrated water vapour data calculated from radiosonde measurements, and with each other. The two SCIAMACHY WVC products are retrieved with two different retrieval algorithms applied in the visible and short wave infrared wavelength regions respectively. The first SCIAMACHY WVC product used in the comparison is ESA's level 2 version 5.01 WVC product derived with the Air Mass Corrected Differential Absorption Spectroscopy (AMC-DOAS) retrieval algorithm (SCIAMACHY-ESA). The second SCIAMACHY WVC product is derived using the Iterative Maximum Likelihood Method (IMLM) developed by Netherlands Institute for Space Research (SCIAMACHY-IMLM). Both SCIAMACHY WVC products are compared with collocated water vapour amounts determined from daily relative humidity radiosonde measurements obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) radiosonde network, over an 18 month and 2 yr period respectively. Results indicate a good agreement between the WVC amounts of SCIAMACHY-ESA and the radiosonde, and a mean difference of 0.03 g cm−2 is found for cloud free conditions. Overall the SCIAMACHY-ESA WVC amounts are smaller than the radiosonde WVC amounts, especially over oceans. For cloudy conditions the WVC bias has a clear dependence on the cloud top height and increases with increasing cloud top heights larger than approximately 2 km. A likely cause for this could be the different vertical profile shapes of water vapour and O2 leading to different relative changes in their optical thickness, which makes the AMF correction method used in the algorithm less suitable for high clouds. The SCIAMACHY-IMLM WVC amounts compare well to the radiosonde WVC amounts during cloud free conditions over land. A mean difference of 0.08 g cm−2 is found which is consistent with previous results when comparing daily averaged SCIAMACHY-IMLM WVC amounts with ECMWF model data globally. Furthermore, we show that the measurements for cloudy conditions (cloud fraction ≥ 0.5) with low clouds (cloud pressure ≥ 930 hPa) above the ocean and land compare quite well with radiosonde data.

scholarly journals SCIAMACHY CO over the oceans: 2003–2007 interannual variability

2009 ◽  
Vol 9 (2) ◽  
pp. 5583-5621
Author(s):  
A. M. S. Gloudemans ◽  
A. T. J. de Laat ◽  
H. Schrijver ◽  
I. Aben ◽  
J. F. Meirink ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Biomass Burning ◽  
Accurate Determination ◽  
Likelihood Method ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Noise Error ◽  
A Minor ◽  
Iterative Maximum Likelihood ◽  
Good Agreement

Abstract. We present a new method to obtain accurate SCIAMACHY CO columns over clouded ocean scenes. Based on an improved version of the Iterative Maximum Likelihood Method (IMLM) retrieval algorithm, we now have retrieved five years of data over both land and clouded ocean scenes between 2003 and 2007. The ocean-cloud method uses the CH4 columns retrieved simultaneously with the CO columns to determine the cloud top height. The CH4 cloud top height is in good agreement with the FRESCO+ cloud top height determined from UV-VIS oxygen-A band measurements, providing confidence that the CH4 cloud top height is a good diagnostic of the cloud top height over (partially) clouded ocean scenes. The CO measurements over clouded ocean scenes have been compared with collocated modeled CO columns over the same clouds and agree well. Using clouded ocean scenes quadruples the number of useful CO measurements compared to land-only measurements. The five-year CO data set over land and clouded ocean scenes presented here is based on an improved version of the IMLM algorithm which includes a more accurate determination of the random instrument-noise error for CO. This leads to a smaller spread in the differences between single CO measurements and the corresponding model values. The new version, IMLM version 7.4, also uses updated spectroscopic parameters for H2O and CH4 but this has only a minor impact on the retrieved CO columns. The five-year data set shows significant interannual variability over land and over clouded ocean scenes. Three examples are highlighted: the Asian outflow of pollution over the northern Pacific, the biomass-burning outflow over the Indian Ocean originating from Indonesia, and biomass burning in Brazil. In general there is good agreement between observed and modeled seasonal cycles and interannual variability.

scholarly journals Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups

2013 ◽  
Vol 1 (2) ◽  
pp. 209-234 ◽  
Author(s):  
Pengyuan Wang ◽  
Mikhail Traskin ◽  
Dylan S. Small
Keyword(s):  
Sensitivity Analysis ◽  
Control Groups ◽  
Two Stage ◽  
Time Effects ◽  
Unaffected Control ◽  
Group Time ◽  
Before And After ◽  
Group Variation ◽  
The Impact ◽  
Before And After Study

AbstractThe before-and-after study with multiple unaffected control groups is widely applied to study treatment effects. The current methods usually assume that the control groups’ differences between the before and after periods, i.e. the group time effects, follow a normal distribution. However, there is usually no strong a priori evidence for the normality assumption, and there are not enough control groups to check the assumption. We propose to use a flexible skew-t distribution family to model group time effects, and consider a range of plausible skew-t distributions. Based on the skew-t distribution assumption, we propose a robust-t method to guarantee nominal significance level under a wide range of skew-t distributions, and hence make the inference robust to misspecification of the distribution of group time effects. We also propose a two-stage approach, which has lower power compared to the robust-t method, but provides an opportunity to conduct sensitivity analysis. Hence, the overall method of analysis is to use the robust-t method to test for the overall hypothesized range of shapes of group variation; if the test fails to reject, use the two-stage method to conduct a sensitivity analysis to see if there is a subset of group variation parameters for which we can be confident that there is a treatment effect. We apply the proposed methods to two datasets. One dataset is from the Current Population Survey (CPS) to study the impact of the Mariel Boatlift on Miami unemployment rates between 1979 and 1982.The other dataset contains the student enrollment and grade repeating data in West Germany in the 1960s with which we study the impact of the short school year in 1966–1967 on grade repeating rates.

scholarly journals A Model for the Thermal Behaviour of an Offshore Cable Installed in a J-Tube

Proceedings ◽  
2020 ◽  
Vol 58 (1) ◽  
pp. 31
Author(s):  
Jeremy Arancio ◽  
Ahmed Ould El Moctar ◽  
Minh Nguyen Tuan ◽  
Faradj Tayat ◽  
Jean-Philippe Roques
Keyword(s):  
Sensitivity Analysis ◽  
Numerical Model ◽  
Thermal Behaviour ◽  
Energy Production ◽  
Power Transmission ◽  
Temperature Fields ◽  
Sobol Indices ◽  
Lumped Element ◽  
Thermal Phenomena ◽  
The Impact

In the race for energy production, supplier companies are concerned by the thermal rating of offshore cables installed in a J-tube, not covered by IEC 60287 standards, and are now looking for solutions to optimize this type of system. This paper presents a numerical model capable of calculating temperature fields of a power transmission cable installed in a J-tube, based on the lumped element method. This model is validated against the existing literature. A sensitivity analysis performed using Sobol indices is then presented in order to understand the impact of the different parameters involved in the heating of the cable. This analysis provides an understanding of the thermal phenomena in the J-tube and paves the way for potential technical and economic solutions to increase the ampacity of offshore cables installed in a J-tube.

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