scholarly journals Near-real time retrieval of tropospheric NO<sub>2</sub> from OMI

2006 ◽  
Vol 6 (6) ◽  
pp. 12301-12345 ◽  
Author(s):  
K. F. Boersma ◽  
H. J. Eskes ◽  
J. P. Veefkind ◽  
E. J. Brinksma ◽  
R. J. van der A ◽  
...  
Keyword(s):  
Real Time ◽  
Local Time ◽  
Cloud Fraction ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Satellite Measurement ◽  
Similar Frequency ◽  
Line System ◽  
Cloud Parameters ◽  
Tropospheric No2

Abstract. We present a new algorithm for the near-real time retrieval – within 3 h of the actual satellite measurement – of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). The retrieval system is based on the combined retrieval-assimilation-modelling approach developed at KNMI for off-line tropospheric NO2 from the GOME and SCIAMACHY satellite instruments. We have adapted the off-line system such that the required a priori information ndash; profile shapes and stratospheric background NO2 ndash; is now immediately available upon arrival of the OMI NO2 slant columns and cloud data at KNMI. Slant column NO2 and cloud information arrives at KNMI typically within 80 min of actual OMI observations. Slant columns for NO2 are retrieved using differential optical absorption spectroscopy (DOAS) in the 405–465 nm range. Cloud fraction and cloud pressure are provided by a new cloud retrieval algorithm that uses the absorption of the O2–O2 collision complex near 477 nm. On-line availability of stratospheric slant columns and NO2 profiles is achieved by running the TM4 chemistry transport model (CTM) forward in time based on forecast ECMWF meteo and assimilated NO2 information from all previously observed orbits. OMI NO2 slant columns, after correction for spurious across-track variability, show a random error for individual pixels of approximately 0.7×1015molec.cm–2. As NO2 retrievals are very sensitive to clouds, we evaluated the consistency of cloud fraction and cloud pressure from the new O2–O2 (OMI) algorithm and from the Fast Retrieval Scheme for Cloud Observables (FRESCO). Cloud parameters from the O2–O2 (OMI) algorithm have similar frequency distributions as cloud parameters retrieved from FRESCO (SCIAMACHY) for August 2006. On average, OMI cloud fractions are higher by 0.011, and OMI cloud pressures exceed FRESCO cloud pressures by 60 hPa. As a consistency check, we intercompared OMI near-real time NO2 columns measured at 13:45 h local time to SCIAMACHY off-line NO2 columns measured at 10:00 h local time. In August 2006, both instruments observe very similar spatial patterns of tropospheric NO2 columns, and small differences for most locations on Earth where tropospheric NO2 columns are small. For regions that are strongly polluted, SCIAMACHY observes higher tropospheric NO2 columns than OMI.

scholarly journals Near-real time retrieval of tropospheric NO<sub>2</sub> from OMI

2007 ◽  
Vol 7 (8) ◽  
pp. 2103-2118 ◽  
Author(s):  
K. F. Boersma ◽  
H. J. Eskes ◽  
J. P. Veefkind ◽  
E. J. Brinksma ◽  
R. J. van der A ◽  
...  
Keyword(s):  
Real Time ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Satellite Measurement ◽  
Ozone Monitoring Instrument ◽  
Similar Frequency ◽  
Line System ◽  
Cloud Data ◽  
Tropospheric No2

Abstract. We present a new algorithm for the near-real time retrieval – within 3 h of the actual satellite measurement – of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). The retrieval is based on the combined retrieval-assimilation-modelling approach developed at KNMI for off-line tropospheric NO2 from the GOME and SCIAMACHY satellite instruments. We have adapted the off-line system such that the required a priori information – profile shapes and stratospheric background NO2 – is now immediately available upon arrival (within 80 min of observation) of the OMI NO2 slant columns and cloud data at KNMI. Slant columns for NO2 are retrieved using differential optical absorption spectroscopy (DOAS) in the 405–465 nm range. Cloud fraction and cloud pressure are provided by a new cloud retrieval algorithm that uses the absorption of the O2-O2 collision complex near 477 nm. On-line availability of stratospheric slant columns and NO2 profiles is achieved by running the TM4 chemistry transport model (CTM) forward in time based on forecast ECMWF meteo and assimilated NO2 information from all previously observed orbits. OMI NO2 slant columns, after correction for spurious across-track variability, show a random error for individual pixels of approximately 0.7×1015 molec cm−2. Cloud parameters from OMI's O2-O2 algorithm have similar frequency distributions as retrieved from SCIAMACHY's Fast Retrieval Scheme for Cloud Observables (FRESCO) for August 2006. On average, OMI cloud fractions are higher by 0.011, and OMI cloud pressures exceed FRESCO cloud pressures by 60 hPa. A sequence of OMI observations over Europe in October 2005 shows OMI's capability to track changeable NOx air pollution from day to day in cloud-free situations.

scholarly journals FRESCO+: an improved O<sub>2</sub> A-band cloud retrieval algorithm for tropospheric trace gas retrievals

2008 ◽  
Vol 8 (3) ◽  
pp. 9697-9729 ◽  
Author(s):  
P. Wang ◽  
P. Stammes ◽  
R. van der A ◽  
G. Pinardi ◽  
M. van Roozendael
Keyword(s):  
Rayleigh Scattering ◽  
Cloud Fraction ◽  
Retrieval Algorithm ◽  
Minor Effect ◽  
Vertical Column ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Retrieval Scheme ◽  
The Difference ◽  
A Minor

Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds shows that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column densities (VCD) is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1) are lower than the tropospheric NO2 VCDs which used FRESCO cloud parameters (v1.04), in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014 molec cm−2.

scholarly journals FRESCO+: an improved O<sub>2</sub> A-band cloud retrieval algorithm for tropospheric trace gas retrievals

2008 ◽  
Vol 8 (21) ◽  
pp. 6565-6576 ◽  
Author(s):  
P. Wang ◽  
P. Stammes ◽  
R. van der A ◽  
G. Pinardi ◽  
M. van Roozendael
Keyword(s):  
Rayleigh Scattering ◽  
Cloud Fraction ◽  
Retrieval Algorithm ◽  
Minor Effect ◽  
Vertical Column ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
The Difference ◽  
A Minor

Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds show that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column density (VCD) retrievals is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1) are lower than the tropospheric NO2VCDs which used FRESCO cloud parameters (v1.04), in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014molec cm−2.

scholarly journals Development and Application of HECORA Cloud Retrieval Algorithm Based On the O2-O2 477 nm Absorption Band

2020 ◽  
Vol 12 (18) ◽  
pp. 3039
Author(s):  
Shuntian Wang ◽  
Cheng Liu ◽  
Wenqiang Zhang ◽  
Nan Hao ◽  
Sebastián Gimeno García ◽  
...  
Keyword(s):  
Absorption Band ◽  
Cloud Model ◽  
Cloud Fraction ◽  
Trace Gas ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Tropospheric No2 ◽  
Low Cloud ◽  
The One

In this paper, we present the Hefei EMI Cloud Retrieval Algorithm (HECORA), which uses information from the O2-O2 absorption band around 477 nm to retrieve effective cloud fraction and effective cloud pressure from satellite observations. The retrieved cloud information intends to improve the atmospheric trace gas products based on the Environment Monitoring Instrument (EMI) spectrometer. The HECORA method builds on OMCLDO2 and presents some evolutions. The Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model has been used to produce the Top of the Atmosphere (TOA) reflectance Look-up Tables (LUT) as a function of the cloud fraction and cloud pressure. Applying the Differential Optical Absorption Spectroscopy (DOAS) technique to the synthetic reflectance LUT, the reflectance spectra can be associated with O2-O2 geometrical vertical column densities (VCDgeo) and continuum reflectance. This is the core of the retrieval method, since there is a one-to-one relationship between O2-O2 VCDgeo and continuum reflectance, on the one hand, and effective cloud fraction and effective cloud pressure, on the other hand, for a given illumination and observing geometry and given surface height and surface albedo. We first used the VLIDORT synthetic spectra to verify the HECORA algorithm and obtained good results in both the Lambertian cloud model and the scattering cloud model. Secondly, HECORA is applied to OMI and TROPOMI and compared with OMCLDO2, FRESCO+, and OCRA/ROCINN cloud products. Later, the cloud pressure results from TROPOMI observations obtained using HECORA and FRESCO+ are compared with the CALIOP Cloud Layer product. HECORA is closer to the CALIOP results under low cloud conditions, while FRESCO+ is closer to high clouds due to the higher sensitivity of the O2 A-band to cloud vertical information. Finally, HECORA is applied to the TROPOMI NO2 retrieval. Validation of the tropospheric NO2 VCD with ground-based MAX-DOAS measurements shows that choosing HECORA cloud products to correct for photon path variations on the TROPOMI tropospheric NO2 VCD retrievals has better performance than using FRESCO+ under low cloud conditions. In conclusion, this paper shows that the HECORA cloud products are in good agreement with the well-established cloud products and that they are suitable for correcting the effect of cloud in trace gas retrievals. Therefore, HECORA has the potential to be applied to EMI.

scholarly journals An improved air mass factor calculation for NO<sub>2</sub> measurements from GOME-2

2019 ◽  
Author(s):  
Song Liu ◽  
Pieter Valks ◽  
Gaia Pinardi ◽  
Jian Xu ◽  
Athina Argyrouli ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Model Parameters ◽  
Air Mass ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Mass Factor ◽  
The Impact

Abstract. An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle-dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parametrization over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS(CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a Cloud-As-Layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current Clouds-as-Reflecting-Boundaries (CRB) model, which assumes the clouds as Lambertian reflectors. Improvements in the AMF calculation affect the tropospheric NO2 columns on average within ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and aerosol-induced cloud parameters (implicit aerosol correction). Compared to the implicit aerosol correction through the CRB cloud parameters, the use of CAL reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAXDOAS) measurements at the BIRA-IASB Xianghe station. The improved tropospheric NO2 dataset shows good agreement with coincident ground-based measurements with a correlation coefficient of 0.94 and a relative difference of −9.9 % on average.

scholarly journals Impact of aerosols on the OMI tropospheric NO<sub>2</sub> retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

2016 ◽  
Vol 9 (2) ◽  
pp. 359-382 ◽  
Author(s):  
J. Chimot ◽  
T. Vlemmix ◽  
J. P. Veefkind ◽  
J. F. de Haan ◽  
P. F. Levelt
Keyword(s):  
Fine Particles ◽  
Cloud Model ◽  
Satellite Observation ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Complex Behaviour ◽  
Cloud Parameters ◽  
Aerosol Pollution ◽  
Tropospheric No2 ◽  
The Impact

Abstract. The Ozone Monitoring Instrument (OMI) has provided daily global measurements of tropospheric NO2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current operational OMI tropospheric NO2 retrieval chain (DOMINO – Derivation of OMI tropospheric NO2) product. Instead, the operational OMI O2 − O2 cloud retrieval algorithm is applied both to cloudy and to cloud-free scenes (i.e. clear sky) dominated by the presence of aerosols. This paper describes in detail the complex interplay between the spectral effects of aerosols in the satellite observation and the associated response of the OMI O2 − O2 cloud retrieval algorithm. Then, it evaluates the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) with a focus on cloud-free scenes. For that purpose, collocated OMI NO2 and MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua aerosol products are analysed over the strongly industrialized East China area. In addition, aerosol effects on the tropospheric NO2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based and the simulation-based approach demonstrate that the retrieved cloud fraction increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT primarily represents the shielding effects of the O2 − O2 column located below the aerosol layers. The study cases show that the aerosol correction based on the implemented OMI cloud model results in biases between −20 and −40 % for the DOMINO tropospheric NO2 product in cases of high aerosol pollution (AOT  ≥ 0.6) at elevated altitude. These biases result from a combination of the cloud model error, used in the presence of aerosols, and the limitations of the current OMI cloud Look-Up-Table (LUT). A new LUT with a higher sampling must be designed to remove the complex behaviour between these biases and AOT. In contrast, when aerosols are relatively close to the surface or mixed with NO2, aerosol correction based on the cloud model results in an overestimation of the DOMINO tropospheric NO2 column, between 10 and 20 %. These numbers are in line with comparison studies between ground-based and OMI tropospheric NO2 measurements in the presence of high aerosol pollution and particles located at higher altitudes. This highlights the need to implement an improved aerosol correction in the computation of tropospheric NO2 AMFs.

scholarly journals Impact of aerosols on the OMI tropospheric NO<sub>2</sub> retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

2015 ◽  
Vol 8 (8) ◽  
pp. 8385-8437 ◽  
Author(s):  
J. Chimot ◽  
T. Vlemmix ◽  
J. P. Veefkind ◽  
J. F. de Haan ◽  
P. F. Levelt
Keyword(s):  
Fine Particles ◽  
Cloud Model ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Cloud Parameters ◽  
Scattering Effects ◽  
Aerosol Pollution ◽  
Tropospheric No2 ◽  
Aerosol Effects ◽  
The Impact

Abstract. The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current OMI tropospheric NO2 retrieval chain. Instead, the operational OMI O2-O2 cloud retrieval algorithm is applied both to cloudy scenes and to cloud free scenes with aerosols present. This paper describes in detail the complex interplay between the spectral effects of aerosols, the OMI O2-O2 cloud retrieval algorithm and the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) over cloud-free scenes. Collocated OMI NO2 and MODIS Aqua aerosol products are analysed over East China, in industrialized area. In addition, aerosol effects on the tropospheric NO2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based and the simulation-based approach demonstrate that the retrieved cloud fraction linearly increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT represents primarily the absorbing effects of aerosols. The study cases show that the actual aerosol correction based on the implemented OMI cloud model results in biases between −20 and −40 % for the DOMINO tropospheric NO2 product in cases of high aerosol pollution (AOT ≥ 0.6) and elevated particles. On the contrary, when aerosols are relatively close to the surface or mixed with NO2, aerosol correction based on the cloud model results in overestimation of the DOMINO tropospheric NO2 product, between 10 and 20 %. These numbers are in line with comparison studies between ground-based and OMI tropospheric NO2 measurements under conditions with high aerosol pollution and elevated particles. This highlights the need to implement an improved aerosol correction in the computation of tropospheric NO2 AMFs.

scholarly journals Potential and limitations of the MAX-DOAS method to retrieve the vertical distribution of tropospheric nitrogen dioxide

2011 ◽  
Vol 4 (3) ◽  
pp. 4013-4072 ◽  
Author(s):  
T. Vlemmix ◽  
A. J. M. Piters ◽  
A. J. C. Berkhout ◽  
L. F. L. Gast ◽  
P. Wang ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Nitrogen Dioxide ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Mixing Ratio ◽  
Average Difference ◽  
Retrieval Models ◽  
Ensemble Technique ◽  
Tropospheric No2 ◽  
The Vertical Distribution

Abstract. Muliple Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments can measure from the ground the absorption by nitrogen dioxide (NO2) of scattered sunlight seen in multiple viewing directions. This paper studies the potential of this technique to derive the vertical distribution of NO2 in the troposphere. Such profile information is essential in validation studies in which MAX-DOAS retrievals play a role. The retrieval algorithm used is based on a pre-calculated look-up table and assumes homogeneous mixing of aerosols and NO2 in layers extending from the surface to a variable height. Two retrieval models are compared: one including and one excluding an elevated NO2 layer at a fixed altitude in the free troposphere. An ensemble technique is applied to derive retrieved model uncertainties. Sensitivity studies demonstrate that MAX-DOAS based retrievals can make a distinction between an NO2 layer that extends from the surface to a certain height (having a constant mixing ratio, or a mixing ratio that decreases with altitude) and an elevated NO2 layer. The height of the elevated NO2 layer can only be retrieved accurately when the aerosol extinction profile is known and the measurement noise is low. The uncertainty in this elevated NO2 layer height provides the main source of uncertainty in the retrieval of the free tropospheric contribution to the tropospheric NO2 column. A comparison was performed with independent data, based on observations done at the CINDI campaign, held in the Netherlands in 2009. Comparison with lidar partial tropospheric NO2 columns showed a correlation of 0.78, and an average difference of 0.1× 1015 molec cm−2. The diurnal evolution of the NO2 volume mixing ratio measured by in-situ monitors at the surface and averaged over five days with cloud-free mornings, compares quite well to the MAX-DOAS retrieval: a correlation was found of 0.8, and an average difference of 0.2 ppb.

scholarly journals An Improved Total and Tropospheric NO<sub>2</sub> Column Retrieval for GOME-2

2018 ◽  
Author(s):  
Song Liu ◽  
Pieter Valks ◽  
Gaia Pinardi ◽  
Isabelle De Smedt ◽  
Huan Yu ◽  
...  
Keyword(s):  
Cross Sections ◽  
Column Density ◽  
Transport Model ◽  
A Priori ◽  
Estimation Algorithm ◽  
Reference Points ◽  
Atmospheric Composition ◽  
Optical Absorption Spectroscopy ◽  
Cloud Parameters ◽  
Tropospheric No2

Abstract. An improved algorithm for the retrieval of total and tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment-2 (GOME-2) is presented. The refined retrieval will be implemented in a future version of the GOME Data Processor (GDP) as used by the EUMETSAT Satellite Application Facility on Atmospheric Composition and UV Radiation (AC-SAF). The first main improvement is the application of an extended 425–497 nm wavelength fitting window in the differential optical absorption spectroscopy (DOAS) retrieval of the NO2 slant column density. Updated absorption cross-sections and a linear offset correction are used for the large fitting window. An improved slit function treatment is applied to compensate for both long-term and in-orbit drift of the GOME-2 slit function. Compared to the current operational (GDP 4.8) dataset, the use of these new features increases the NO2 columns by  1–3 × 1014 molec/cm2 and reduces the slant column error by ∼ 24 %. In addition, the bias between GOME-2A and GOME-2B measurements is largely reduced by adopting a new level 1b data version in the DOAS retrieval. The retrieved NO2 slant columns show good consistency with the Quality Assurance for Essential Climate Variables (QA4ECV) retrieval with a good overall quality. Second, the STRatospheric Estimation Algorithm from Mainz (STREAM), which was originally developed for the TROPOspheric Monitoring Instrument (TROPOMI) instrument, was optimized for GOME-2 measurements to determine the stratospheric NO2 column density. Applied to synthetic GOME-2 data, the estimated stratospheric NO2 columns from STREAM shows a good agreement with the a priori truth. An improved latitudinal correction is introduced in STREAM to reduce the biases over the subtropics. Applied to GOME-2 measurements, STREAM largely reduces the overestimation of stratospheric NO2 columns over polluted regions in the GDP 4.8 dataset. Third, the calculation of AMF applies an updated box-air mass factor (box-AMF) look-up table (LUT) calculated using the latest version of VLIDORT model with an increased number of reference points and vertical layers, a new GOME-2 surface albedo climatology, improved a priori NO2 profiles obtained from the TM5-MP chemistry transport model, and improved GOME-2 cloud parameters. A large effect on the retrieved tropospheric NO2 columns (more than 10 %) is found over polluted regions. To evaluate the GOME-2 tropospheric NO2 columns, an end-to-end validation is performed using ground-based multiple-axis DOAS (MAXDOAS) measurements. The validation is illustrated for 6 stations covering urban, suburban, and background situations. Compared to the GDP 4.8 product, the new dataset presents an improved agreement with the MAXDOAS measurements for all the stations.

scholarly journals An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

2020 ◽  
Vol 13 (2) ◽  
pp. 755-787 ◽  
Author(s):  
Song Liu ◽  
Pieter Valks ◽  
Gaia Pinardi ◽  
Jian Xu ◽  
Athina Argyrouli ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Surface Albedo ◽  
Optical Absorption Spectroscopy ◽  
Model Parameters ◽  
Air Mass ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Mass Factor ◽  
Ozone Monitoring ◽  
The Impact

Abstract. An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94.

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