scholarly journals A full-mission data set of H<sub>2</sub>O and HDO columns from SCIAMACHY 2.3 µm reflectance measurements

2018 ◽  
Vol 11 (6) ◽  
pp. 3339-3350 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Haili Hu ◽  
Jochen Landgraf
Keyword(s):  
Light Scattering ◽  
A Posteriori ◽  
Vertical Column ◽  
Data Set ◽  
Average Bias ◽  
Cloud Parameters ◽  
Infrared Measurements ◽  
Mission Period ◽  
Scanning Imaging ◽  
Reflectance Measurements

Abstract. A new data set of vertical column densities of the water vapour isotopologues H2O and HDO from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument for the whole of the mission period from January 2003 to April 2012 is presented. The data are retrieved from reflectance measurements in the spectral range 2339 to 2383 nm with the Shortwave Infrared CO Retrieval (SICOR) algorithm, ignoring atmospheric light scattering in the measurement simulation. The retrievals are validated with ground-based Fourier transform infrared measurements obtained within the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project. A good agreement for low-altitude stations is found with an average bias of −3.6×1021 for H2O and −1.0×1018 molec cm−2 for HDO. The a posteriori computed δD shows an average bias of −8 ‰, even though polar stations have a larger negative bias. The latter is due to the large amount of sensor noise in SCIAMACHY in combination with low albedo and high solar zenith angles. To demonstrate the benefit of accounting for light scattering in the retrieval, the quality of the data product fitting effective cloud parameters simultaneously with trace gas columns is evaluated in a dedicated case study for measurements round high-altitude stations. Due to a large altitude difference between the satellite ground pixel and the mountain station, clear-sky scenes yield a large bias, resulting in a δD bias of 125 ‰. When selecting scenes with optically thick clouds within 1000 m above or below the station altitude, the bias in a posteriori δD is reduced from 125 to 44 ‰. The insights from the present study will also benefit the analysis of the data from the new Sentinel-5 Precursor mission.

scholarly journals A full-mission data set of H<sub>2</sub>O and HDO columns from SCIAMACHY 2.3 μm reflectance measurements

2018 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Haili Hu ◽  
Jochen Landgraf
Keyword(s):  
Light Scattering ◽  
A Posteriori ◽  
Vertical Column ◽  
Data Set ◽  
Average Bias ◽  
Cloud Parameters ◽  
Infrared Measurements ◽  
Mission Period ◽  
Scanning Imaging ◽  
Reflectance Measurements

Abstract. A new data set of vertical column densities of the water vapour isotopologues H₂O and HDO from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument for the whole mission period from January 2003 to April 2012 is presented. The data are retrieved from reflectance measurements in the spectral range 2339 nm to 2383 nm with the Shortwave Infrared CO Retrieval (SICOR) algorithm, ignoring atmospheric light scattering in the measurement simulation. The retrievals are validated with ground-based Fourier transform infrared measurements obtained within the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project. A good agreement for low-altitude stations is found with an average bias of −3.6·1021 molec cm−2 for HO and −1.0·1018molec cm−2 for HDO. The a posteriori computed δD shows an average bias of −8 ‰, even though polar stations have a larger negative bias. The latter is due to large sensor noise of SCIAMACHY in combination with low albedo and high solar zenith angles. To demonstrate the benefit of accounting for light scattering in the retrieval, the quality of the data product fitting effective cloud parameters simultaneously with trace gas columns is evaluated in a dedicated case study for measurements round high altitude stations. Due to a large altitude difference between the satellite ground pixel and the mountain station, clear sky scenes yield a large bias, resulting in a δD bias of 125 ‰. When selecting scenes with optically thick clouds within 1000 m above or below the station altitude, the bias in a posteriori δD is reduced from 125 ‰ to 44 ‰. The insights from the present study will also benefit the analysis of the data from the new Sentinel 5 Precursor mission.

scholarly journals First data set of H<sub>2</sub>O/HDO columns from TROPOMI

2019 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Franziska Aemisegger ◽  
Dietrich G. Feist ◽  
...  
Keyword(s):  
Water Vapour ◽  
Short Wave ◽  
Total Carbon ◽  
A Posteriori ◽  
Vertical Column ◽  
Data Set ◽  
Blocking Anticyclone ◽  
Global Coverage ◽  
Reflectance Measurements

Abstract. This paper presents a new data set of vertical column densities of the water vapour isotopologues H2O and HDO retrieved from short-wave infrared (2.3 μm) reflectance measurements by the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite. TROPOMI features daily global coverage with a spatial resolution of up to 7 km × 7 km. The retrieval utilises a profile-scaling approach. The forward model neglects scattering, thus strict cloud filtering is necessary. For validation, recent ground-based water vapour isotopologue measurements by the Total Carbon Column Observing Network (TCCON) are employed. A comparison of TCCON δD with measurements by the project Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) for data prior to 2014 (where MUSICA data is available) shows a bias in TCCON δD estimates. As TCCON HDO is currently not validated, an overall correction of recent TCCON HDO data is derived based on this finding. The agreement between the corrected TCCON measurements and collocated TROPOMI observations is good with an average bias of (0.02 ± 2) · 1021 molec cm−2 in H2O and (−0.3 ± 7) · 1017 molec cm−2 in HDO, which corresponds to a bias of (−12 ± 17) ‰ in a posteriori δD. The use of the data set is demonstrated with a case study of a blocking anticyclone in northwestern Europe in July 2018 using single overpass data.

scholarly journals Advanced NO<sub>2</sub> retrieval technique for the Brewer spectrophotometer applied to the 20-year record in Rome, Italy

2021 ◽  
Author(s):  
Henri Diémoz ◽  
Anna Maria Siani ◽  
Stefano Casadio ◽  
Anna Maria Iannarelli ◽  
Giuseppe Rocco Casale ◽  
...  
Keyword(s):  
Optical Depth ◽  
Cross Sections ◽  
Rayleigh Scattering ◽  
Economic Recession ◽  
Atmospheric Composition ◽  
Vertical Column ◽  
Data Set ◽  
Average Bias ◽  
Brewer Spectrophotometer

Abstract. A re-evaluated data set of nitrogen dioxide (NO2) column densities over Rome for the years 1996 to 2017 is here presented. This long-term record is obtained from ground-based direct sun measurements with a MkIV Brewer spectrophotometer (#067), further reprocessed using a novel algorithm. Compared to the original Brewer algorithm, the new method includes updated NO2 absorption cross sections and Rayleigh scattering coefficients, and accounts for additional atmospheric compounds and instrumental artefacts, such as the spectral transmittance of the filters, the alignment of the wavelength scale and internal temperature. Moreover, long-term changes in the Brewer radiometric sensitivity are tracked using statistical methods for in-field calibration. The resulting series presents only few (about 30) periods with missing data longer than one week and features NO2 retrievals in more than 6100 days, covering nearly 80 % of the considered 20-year period. The high quality of the data is demonstrated by two independent comparisons. In a first intensive campaign, Brewer #067 is compared against another Brewer (#066), recently calibrated at the Izaña Atmospheric Observatory through the Langley method and there compared to reference instrumentation from the Network for the Detection of Atmospheric Composition Change (NDACC). Data from this campaign show a highly significant Pearson's correlation coefficient of 0.90 between the two series of slant column densities, slope 0.98 and offset 0.05 DU (1.3 × 1015 molec cm−2). The average bias between the vertical column densities is 0.03 DU (8.1 ×1014 molec cm−2), well within the combined uncertainty of both instruments. Brewer #067 is also independently compared with new-generation instrumentation, a co-located Pandora spectrometer (#117), over a 1-year long period (2016–2017) at Sapienza University of Rome, showing linear correlation indices above 0.96 between slant column densities, slope of 0.97 and offset of 0.02 DU (5.4 × 1014 molec cm−2). The average bias between vertical column densities is negligible (−0.002 DU or −5.4 × 1013 molec cm−2). This, incidentally, represents the first intercomparison of NO2 retrievals between a MkIV Brewer and a Pandora instrument. Owing to its accuracy and length, the Brewer data set collected in Rome can be useful for satellite cal/val exercises, comparison with photochemical models, and for better aerosol optical depth estimates (NO2 optical depth climatology). In addition, it can be employed to identify long-term trends in NO2 column densities over a metropolitan environment, during two decades witnessing important changes in environmental policies, emission loads and composition, and the effect of a worldwide economic recession, to offer just a few examples. The method can be replicated on the more than 80 MkIV spectrophotometers operating worldwide in the frame of the international Brewer network. The NO2 data set described in this manuscript can be freely accessed at https://doi.org/10.5281/zenodo.4715219 (Diémoz and Siani, 2021).

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.

scholarly journals Retrieving H<sub>2</sub>O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI)

2021 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Alba Lorente ◽  
Franziska Aemisegger ◽  
...  
Keyword(s):  
Added Value ◽  
Total Carbon ◽  
A Posteriori ◽  
Data Set ◽  
Monitoring Instrument ◽  
Clear Sky ◽  
Cloud Parameters ◽  
Cold Air Outbreak ◽  
Low Sensitivity ◽  
Isotope System

Abstract. This paper presents an extension of the scientific HDO/H2O column data product from the Tropospheric Monitoring Instrument (TROPOMI) including clear-sky and cloudy scenes. The retrieval employs a forward model which accounts for scattering, and the algorithm infers the trace gas column information, surface properties and effective cloud parameters from the observations. The extension to cloudy scenes greatly enhances coverage, particularly enabling data over oceans. The data set is validated against co-located ground-based Fourier transform infrared (FTIR) observations by the Total Carbon Column Observing Network (TCCON). The median bias for clear-sky scenes is 1.4 × 1021 molec cm−2 (2.9 %) in H2O columns and 1.1 × 1017 molec cm−2 (−0.3 %) in HDO columns, which corresponds to −17 ‰ (9.9 %) in a posteriori δD. The bias for cloudy scenes is 4.9 × 1021 molec cm−2 (11 %) in H2O, 1.1 × 1017 molec cm−2 (7.9 %) in HDO, and −20 ‰ (9.7 %) in a posteriori δD. At low-altitude stations in low and middle latitudes the bias is small, and has a larger value at high latitude stations. At high altitude stations, an altitude correction is required to compensate for different partial columns seen by the station and the satellite. The bias in a posteriori δD after altitude correction depends on sensitivity due to shielding by clouds, and on realistic prior profile shapes for both isotopologues. Cloudy scenes generally involve low sensitivity below the clouds, and since the information is filled up by the prior, it plays an important role in these cases. Over oceans, aircraft measurements with the Water Isotope System for Precipitation and Entrainment Research (WISPER) instrument from a field campaign in 2018 are used for validation, yielding a bias of −3.9 % in H2O and −3 ‰ in δD over clouds. To demonstrate the added value of the new data set, a short case study of a cold air outbreak over the Atlantic Ocean in January 2020 is presented, showing the daily evolution of the event with single overpass results.

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 ◽  
Vol 10 (5) ◽  
pp. 1769-1782 ◽  
Author(s):  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Haili Hu ◽  
Philippe Nédélec ◽  
Ilse Aben ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Data Processing ◽  
Pearson Correlation ◽  
Short Wave ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
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 were 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. The situation 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 and the SCIAMACHY results 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. For example, at the cities Tehran 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. For cloudy-sky retrievals, the validation improves significantly. Here the retrieved column is mainly sensitive to CO above the cloud and so not affected by the strong local surface emissions. Adjusting the MOZAIC/IAGOS measurements to the vertical sensitivity of the retrieval, the mean bias adds up to b = 52. 3 ppb and 5.0 ppb for Tehran and Beijing. At the less urbanised region around the airport Windhoek, 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 for cloudy SCIAMACHY observations with a mean bias of b = 0. 2 ppb. Overall the cloudy-sky CO retrievals from SCIAMACHY short-wave infrared measurements present a major extension of the clear-sky-only data set, which more than triples the amount of data and adds unique observations over the oceans. 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.

scholarly journals MERIS albedo climatology for FRESCO+ O<sub>2</sub> A-band cloud retrieval

2011 ◽  
Vol 4 (3) ◽  
pp. 463-483 ◽  
Author(s):  
C. Popp ◽  
P. Wang ◽  
D. Brunner ◽  
P. Stammes ◽  
Y. Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Regional Scale ◽  
Trace Gas ◽  
Vertical Column ◽  
Cloud Parameters ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Scanning Imaging ◽  
Small Cloud

Abstract. A new global albedo climatology for Oxygen A-band cloud retrievals is presented. The climatology is based on MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data and its favourable impact on the derivation of cloud fraction is demonstrated for the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm. To date, a relatively coarse resolution (1° × 1°) surface reflectance dataset from GOME (Global Ozone Monitoring Experiment) Lambert-equivalent reflectivity (LER) is used in FRESCO+. The GOME LER climatology does not account for the usually higher spatial resolution of UV/VIS instruments designed for trace gas remote sensing which introduces several artefacts, e.g. in regions with sharp spectral contrasts like coastlines or over bright surface targets. Therefore, MERIS black-sky albedo (BSA) data from the period October 2002 to October 2006 were aggregated to a grid of 0.25° × 0.25° for each month of the year and for different spectral channels. In contrary to other available surface reflectivity datasets, MERIS includes channels at 754 nm and 775 nm which are located close to the spectral windows required for O2 A-band cloud retrievals. The MERIS BSA in the near-infrared compares well to Moderate Resolution Imaging Spectroradiometer (MODIS) derived BSA with an average difference lower than 1% and a correlation coefficient of 0.98. However, when relating MERIS BSA to GOME LER a distinctly lower correlation (0.80) and enhanced scatter is found. Effective cloud fractions from two exemplary months (January and July 2006) of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) data were subsequently derived with FRESCO+ and compared to those from the Heidelberg Iterative Cloud Retrieval Utilities (HICRU) algorithm. The MERIS climatology generally improves FRESCO+ effective cloud fractions. In particular small cloud fractions are in better agreement with HICRU. This is of importance for atmospheric trace gas retrieval which relies on accurate cloud information at small cloud fractions. In addition, overestimates along coastlines and underestimates in the Intertropical Convergence Zone introduced by the GOME LER were eliminated. While effective cloud fractions over the Saharan desert and the Arabian peninsula are successfully reduced in January, they are still too high in July relative to HICRU due to FRESCO+'s large sensitivity to albedo inaccuracies of highly reflecting targets and inappropriate aerosol information which hampers an accurate albedo retrieval. Finally, NO2 tropospheric vertical column densities and O3 total columns were derived with the FRESCO+ cloud parameters from the new dataset and it is found that the MERIS BSA climatology has a pronounced and beneficial effect on regional scale. Apart from FRESCO+, the new MERIS albedo dataset is applicable to any cloud retrieval algorithms using the O2 A-band or the O2-O2 absorption band around 477 nm. Moreover, the by-product of BSA at 442 nm can be used in NO2 remote sensing and the BSA at 620 nm, 665 nm, and 681 nm could be integrated in current H2O retrievals.

scholarly journals Advanced NO<sub>2</sub> retrieval technique for the Brewer spectrophotometer applied to the 20-year record in Rome, Italy

2021 ◽  
Vol 13 (10) ◽  
pp. 4929-4950
Author(s):  
Henri Diémoz ◽  
Anna Maria Siani ◽  
Stefano Casadio ◽  
Anna Maria Iannarelli ◽  
Giuseppe Rocco Casale ◽  
...  
Keyword(s):  
Optical Depth ◽  
Cross Sections ◽  
Rayleigh Scattering ◽  
Economic Recession ◽  
Atmospheric Composition ◽  
Vertical Column ◽  
Data Set ◽  
Average Bias ◽  
Brewer Spectrophotometer

Abstract. A re-evaluated data set of nitrogen dioxide (NO2) column densities over Rome for the years 1996 to 2017 is here presented. This long-term record is obtained from ground-based direct sun measurements with a MkIV Brewer spectrophotometer (serial number #067) and further reprocessed using a novel algorithm. Compared to the original Brewer algorithm, the new method includes updated NO2 absorption cross sections and Rayleigh scattering coefficients, and it accounts for additional atmospheric compounds and instrumental artefacts, such as the spectral transmittance of the filters, the alignment of the wavelength scale, and internal temperature. Moreover, long-term changes in the Brewer radiometric sensitivity are tracked using statistical methods for in-field calibration. The resulting series presents only a few (about 30) periods with missing data longer than 1 week and features NO2 retrievals for more than 6100 d, covering nearly 80 % of the considered 20-year period. The high quality of the data is demonstrated by two independent comparisons. In the first intensive campaign, Brewer #067 is compared against another Brewer (#066), recently calibrated at the Izaña Atmospheric Observatory through the Langley method and there compared to reference instrumentation from the Network for the Detection of Atmospheric Composition Change (NDACC). Data from this campaign show a highly significant Pearson's correlation coefficient of 0.90 between the two series of slant column densities (SCDs), slope 0.98 and offset 0.05 DU (Dobson units; 1.3×1015 molec.cm-2). The average bias between the vertical column densities is 0.03 DU (8.1×1014 molec.cm-2), well within the combined uncertainty of both instruments. Brewer #067 is also independently compared with new-generation instrumentation, a co-located Pandora spectrometer (#117), over a 1-year-long period (2016–2017) at Sapienza University of Rome, showing linear correlation indices above 0.96 between slant column densities, slope of 0.97, and offset of 0.02 DU (5.4×1014 molec.cm-2). The average bias between vertical column densities is negligible (−0.002 DU or -5.4×1013 molec.cm-2). This, incidentally, represents the first intercomparison of NO2 retrievals between a MkIV Brewer and a Pandora instrument. Owing to its accuracy and length, the Brewer data set collected in Rome can be useful for satellite calibration/validation exercises, comparison with photochemical models, and better aerosol optical depth estimates (NO2 optical depth climatology). In addition, it can be employed to identify long-term trends in NO2 column densities in a metropolitan environment, over two decades witnessing important changes in environmental policies, emission loads and composition, and the effect of a worldwide economic recession, to offer just a few examples. The method can be replicated on the more than 80 MkIV spectrophotometers operating worldwide in the frame of the international Brewer network. The NO2 data set described in this paper can be freely accessed at https://doi.org/10.5281/zenodo.4715219 (Diémoz and Siani, 2021).

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2014 ◽  
Vol 7 (3) ◽  
pp. 3021-3073 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Data Processor ◽  
Climate Analysis ◽  
Total Column

Abstract. The knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors and perform an extensive inter-comparison and validation in order to estimate their absolute accuracy and long-term stability. We use the recently reprocessed data sets retrieved by the GOME-2 instruments aboard EUMETSAT's MetOp-A and MetOp-B satellites and generated by DLR in the framework of the O3M-SAF using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines H2O/O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. We evaluate the overall consistency between about 8 months measurements from the newer GOME-2 instrument on the MetOp-B platform with the GOME-2/MetOp-A data in the overlap period. Furthermore, we compare GOME-2 results with independent TCWV data from ECMWF and with SSMIS satellite measurements during the full period January 2007–August 2013 and we perform a validation against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project. We find global mean biases as small as ± 0.03 g cm−2 between GOME-2A and all other data sets. The combined SSM/I-MERIS sample is typically drier than the GOME-2 retrievals (−0.005 g cm−2), while on average GOME-2 data overestimate the SSMIS measurements by only 0.028 g cm−2. However, the size of some of these biases are seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, but are not as evident in the validation with the ECMWF and the SSM/I + MERIS data. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three independent data sets, especially for land areas, although some discrepancies over ocean and over land areas with high humidity and a relatively large surface albedo are also present.

scholarly journals VALIDATION OF LIDAR SURVEY DATA BY COMPARISON OF SEVERAL UNCERTAINTY MODELS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1385-1390
Author(s):  
N. Seube
Keyword(s):  
Point Cloud ◽  
A Priori ◽  
A Posteriori ◽  
Data Set ◽  
Timing Errors ◽  
Beam Incidence ◽  
A Priori Uncertainty ◽  
Uncertainty Models ◽  
Attitude Uncertainty ◽  
The Relationship

Abstract. This paper introduce a new method for validating the precision of an airborne or a mobile LiDAR data set. The proposed method is based on the knowledge of an a Combined Standard Measurement Uncertainty (CSMU) model which describes LiDAR point covariance matrix and thus uncertainty ellipsoid. The model we consider includes timing errors and most importantly the incidence of the LiDAR beam. After describing the relationship between the beam incidence and other variable uncertainty (especially attitude uncertainty), we show that we can construct a CSMU model giving the covariance of each oint as a function of the relative geometry between the LiDAR beam and the point normal. The validation method we propose consist in comparing the CSMU model (predictive a priori uncertainty) t the Standard Deviation Alog the Surface Normal (SDASN), for all set of quasi planr segments of the point cloud. Whenever the a posteriori (i.e; observed by the SDASN) level of uncertainty is greater than a priori (i.e; expected) level of uncertainty, the point fails the validation test. We illustrate this approach on a dataset acquired by a Microdrones mdLiDAR1000 system.

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