Carbon monoxide from shortwave infrared reflectance measurements: A new retrieval approach for clear sky and partially cloudy atmospheres

2012 ◽  
Vol 120 ◽  
pp. 255-266 ◽  
Author(s):  
J. Vidot ◽  
J. Landgraf ◽  
O.P. Hasekamp ◽  
A. Butz ◽  
A. Galli ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Infrared Reflectance ◽  
Clear Sky ◽  
Shortwave Infrared ◽  
Reflectance Measurements

scholarly journals Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements

2016 ◽  
Vol 9 (10) ◽  
pp. 4955-4975 ◽  
Author(s):  
Jochen Landgraf ◽  
Joost aan de Brugh ◽  
Remco Scheepmaker ◽  
Tobias Borsdorff ◽  
Haili Hu ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Carbon Monoxide ◽  
Transport Model ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Scattering ◽  
Clear Sky ◽  
Infrared Measurements ◽  
Shortwave Infrared ◽  
Total Column

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) spectrometer is the single payload of the Copernicus Sentinel 5 Precursor (S5P) mission. It measures Earth radiance spectra in the shortwave infrared spectral range around 2.3 µm with a dedicated instrument module. These measurements provide carbon monoxide (CO) total column densities over land, which for clear sky conditions are highly sensitive to the tropospheric boundary layer. For cloudy atmospheres over land and ocean, the column sensitivity changes according to the light path through the atmosphere. In this study, we present the physics-based operational S5P algorithm to infer atmospheric CO columns satisfying the envisaged accuracy ( <  15 %) and precision ( <  10 %) both for clear sky and cloudy observations with low cloud height. Here, methane absorption in the 2.3 µm range is combined with methane abundances from a global chemical transport model to infer information on atmospheric scattering. For efficient processing, we deploy a linearized two-stream radiative transfer model as forward model and a profile scaling approach to adjust the CO abundance in the inversion. Based on generic measurement ensembles, including clear sky and cloudy observations, we estimated the CO retrieval precision to be  ≤  11 % for surface albedo  ≥  0.03 and solar zenith angle  ≤  70°. CO biases of  ≤  3 % are introduced by inaccuracies in the methane a priori knowledge. For strongly enhanced CO concentrations in the tropospheric boundary layer and for cloudy conditions, CO errors in the order of 8 % can be introduced by the retrieval of cloud parameters of our algorithm. Moreover, we estimated the effect of a distorted spectral instrument response due to the inhomogeneous illumination of the instrument entrance slit in the flight direction to be  <  2 % with pseudo-random characteristics when averaging over space and time. Finally, the CO data exploitation is demonstrated for a TROPOMI orbit of simulated shortwave infrared measurements. Overall, the study demonstrates that for an instrument that performs in compliance with the pre-flight specifications, the CO product will meet the required product performance well.

scholarly journals Carbon monoxide total columns from SCIAMACHY 2.3  µm atmospheric reflectance measurements: towards a full-mission data product (2003–2012)

2016 ◽  
Vol 9 (1) ◽  
pp. 227-248 ◽  
Author(s):  
T. Borsdorff ◽  
P. Tol ◽  
J. E. Williams ◽  
J. de Laat ◽  
J. aan de Brugh ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
Spectral Response ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial And Temporal Variability ◽  
Data Set ◽  
Clear Sky ◽  
Data Product ◽  
Reflectance Measurements

Abstract. We present a full-mission data product of carbon monoxide (CO) vertical column densities using the 2310–2338 nm SCIAMACHY reflectance measurements over clear-sky land scenes for the period January 2003–April 2012. The retrieval employs the SICOR algorithm, which will be used for operational data processing of the Sentinel-5 Precursor mission. The retrieval approach infers simultaneously carbon monoxide, methane and water vapour column densities together with a Lambertian surface albedo from individual SCIAMACHY measurements employing a non-scattering radiative transfer model. To account for the radiometric instrument degradation including the formation of an ice-layer on the 2.3 µm detector array, we consider clear-sky measurements over the Sahara as a natural calibration target. For these specific measurements, we spectrally calibrate the SCIAMACHY measurements and determine a spectral radiometric offset and the width of the instrument spectral response function as a function of time for the entire operational phase of the mission. We show that the smoothing error of individual clear-sky CO retrievals is less than ±1 ppb and thus this error contribution does not need to be accounted for in the validation considering the much higher retrieval noise. The CO data product is validated against measurements of ground-based Fourier transform infrared spectrometers at 27 stations of the NDACC-IRWG and TCCON network and MOZAIC/IAGOS aircraft measurements at 26 airports worldwide. Overall, we find a good agreement with TCCON measurements with a mean bias b  = −1.2 ppb and a station-to-station bias with σ   = 7.2 ppb. The negative sign of the bias means a low bias of SCIAMACHY CO with respect to TCCON. For the NDACC-IRWG network, we obtain a larger mean station bias of b  = −9.2 ppb with σ  = 8.1 ppb and for the MOZAIC/IAGOS measurements we find b  = −6.4 ppb with σ  = 5.6 ppb. The SCIAMACHY data set is subject to a small but significant bias trend of 1.47 ± 0.25 ppb yr−1. After trend correction, the bias with respect to MOZAIC/IAGOS observation is 2.5 ppb, with respect to TCCON measurements it is −4.6 ppb and with respect to NDACC-IRWG measurements −8.4 ppb. Hence, a discrepancy of 3.8 ppb remains between the global biases with NDACC-IRWG and TCCON, which is confirmed by directly comparing NDACC-IRWG and TCCON measurements. Generally, the scatter of the individual SCIAMACHY CO retrievals is high and dominated by large measurement noise. Hence, for practical usage of the data set, averaging of individual retrievals is required. As an example, we show that monthly mean SCIAMACHY CO retrievals, averaged separately over Northern and Southern Africa, reflect the spatial and temporal variability of biomass burning events in agreement with the global chemical transport model TM5.

scholarly journals Carbon monoxide total columns from SCIAMACHY 2.3 μm atmospheric reflectance measurements: towards a full-mission data product (2003–2012)

2015 ◽  
Vol 8 (9) ◽  
pp. 9731-9783
Author(s):  
T. Borsdorff ◽  
P. Tol ◽  
J. E. Williams ◽  
J. de Laat ◽  
J. aan de Brugh ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
Spectral Response ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial And Temporal Variability ◽  
Data Set ◽  
Clear Sky ◽  
Data Product ◽  
Reflectance Measurements

Abstract. We present a full-mission data product of carbon monoxide (CO) vertical column densities using the 2310–2338 nm SCIAMACHY reflectance measurements over clear sky land scenes for the period January 2003–April 2012. The retrieval employs the SICOR algorithm, which will be used for operational data processing of the Sentinel-5 Precursor mission, combined with a SCIAMACHY specific radiometric soft-calibration to mitigate instrumental issues. The retrieval approach infers simultaneously carbon monoxide, methane and water vapour column densities together with a Lambertian surface albedo from individual SCIAMACHY measurements employing a non-scattering radiative transfer model. To account for the radiometric instrument degradation including the formation of an ice-layer on the 2.3 μm detector-array, we consider clear sky measurements over the Sahara as a natural calibration target. For these specific measurements, we spectrally calibrate the SCIAMACHY measurements and determine a spectral radiometric offset and the width of the instrument spectral response function as a function of time for the entire operational phase of the mission. We show that the smoothing error of individual clear sky CO retrievals is less than ±1 ppb and thus this error contribution has not to be accounted for in the validation considering the much higher retrieval noise. The CO data product is validated against measurements of ground-based Fourier transform infrared spectrometers at 27 stations of the NDACC-IRWG and TCCON network and MOZAIC/IAGOS aircraft measurements at 26 airports worldwide. Overall, we find a good agreement with TCCON measurements with a mean bias b = −1.2 ppb and a station-to-station bias with σ = 7.2 ppb. For the NDACC-IRWG network, we obtain a larger mean station bias of b = −9.2 ppb with σ = 8.1 ppb and for the MOZAIC/IAGOS measurements we find b = −6.4 ppb with σ = 5.6 ppb. The SCIAMACHY data set is subject to a small but significant trend of 1.47 ± 0.25 ppb yr−1. After trend correction, the bias with respect to MOZAIC/IAGOS observation is 2.5 ppb, with respect to TCCON measurements it is −4.6 ppb and with respect to NDACC-IRWG measurements −8.4 ppb. Hence, a discrepancy of 3.8 ppb remains between the global biases with NDACC-IRWG and TCCON, which is confirmed by directly comparing NDACC-IRWG and TCCON measurements. Generally, the scatter of the individual SCIAMACHY CO retrievals is high and dominated by large measurement noise. Hence, for practical usage of the dataset, averaging of individual retrievals is required. As an example, we show that monthly mean SCIAMACHY CO retrievals, averaged separately over Northern and Southern Africa, reflect the spatial and temporal variability of biomass burning events in agreement with the global chemical transport model TM5.

Satellite Detection of Water Stress Effects on Terrestrial Latent Heat Flux With MODIS Shortwave Infrared Reflectance Data

2018 ◽  
Vol 123 (20) ◽  
pp. 11,410-11,430 ◽  
Author(s):  
Yunjun Yao ◽  
Shunlin Liang ◽  
Bao Cao ◽  
Shaomin Liu ◽  
Guirui Yu ◽  
...  
Keyword(s):  
Heat Flux ◽  
Water Stress ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Infrared Reflectance ◽  
Stress Effects ◽  
Shortwave Infrared ◽  
Reflectance Data

Angle-dependent infrared reflectance measurements in support of VIIRS

2008 ◽  
Author(s):  
Simon G. Kaplan ◽  
Enrique J. Iglesias ◽  
Leonard M. Hanssen
Keyword(s):  
Infrared Reflectance ◽  
Reflectance Measurements

scholarly journals Carbon monoxide column retrieval for clear-sky and cloudy atmospheres: a full-mission data set from SCIAMACHY 2.3 μm reflectance measurements

2017 ◽  
Author(s):  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Haili Hu ◽  
Philippe Nédélec ◽  
Ilse Aben ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Data Processing ◽  
Pearson Correlation ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Validation Data ◽  
Data Set ◽  
Airborne Measurements ◽  
Clear Sky ◽  
Infrared Measurements

Abstract. We discuss the retrieval of carbon monoxide (CO) vertical column densities from clear-sky and cloud contaminated 2311–2338 nm reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) from January 2003 until the end of the mission in April 2012. These data was processed with the Shortwave Infrared CO Retrieval algorithm SICOR that we developed for the operational data processing of the Tropospheric Monitoring Instrument (TROPOMI) that will be launched on ESA’s Sentinel-5 Precursor (S5P) mission. This study complements previous work that was limited to clear-sky observations over land. Over the oceans, CO is estimated from cloudy-sky measurements only, which is an important addition to the SCIAMACHY clear-sky CO data set as shown by NDACC and TCCON measurements at coastal sites. For Ny-Ålesund, Lauder, Mauna Loa, and Reunion, a validation of SCIAMACHY clear-sky retrievals is not meaningful because of the high retrieval noise and the few collocations at these sites. This improves significantly when considering cloudy-sky observations, where we find a low mean bias b = ±6.0 ppb and a strong correlation between the validation data set and the SCIAMACHY data sets with a mean Pearson correlation coefficient r = 0.7. Also for land observations, cloudy-sky CO retrievals present an interesting complement to the clear-sky data set, which is less sensitive to the spatial representativeness of the satellite and validation measurement. For example, at the cities Teheran and Beijing the agreement of SCIAMACHY clear-sky CO observations with MOZAIC/IAGOS airborne measurements is poor with a mean bias of b = 171.2 ppb and 57.9 ppb because of local CO pollution, which cannot be captured by SCIAMACHY. The validation improves significantly for cloudy sky retrievals with b = 52.3 ppb and 5.0 ppb, respectively. This is due to a reduced retrieval sensitivity to CO below the cloud and so to the altitude range, which is mostly affected by strong local surface emissions. At the less urbanized region around the airportWindhoek, local CO pollution is less prominent and so MOZAIC/IAGOS measurements agree well with SCIAMACHY clear-sky retrievals with a mean bias of b = 15.5 ppb, but can be even further improved considering cloudy SCIAMACHY observations with a mean CO bias of b = 0.2 ppb. Overall the cloudy-sky CO retrievals from SCIAMACHY short wave infrared measurements present a valuable addition to the clear-sky only data set. Moreover, the study represents the first application of the S5P algorithm for operational CO data processing on cloudy observations prior to the launch of the S5P mission.

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