scholarly journals Rapid methods for inversion of MAXDOAS elevation profiles to surface-associated box concentrations, visibility, and heights: application to analysis of Arctic BrO events

2010 ◽  
Vol 3 (6) ◽  
pp. 4645-4674 ◽  
Author(s):  
D. Donohoue ◽  
D. Carlson ◽  
W. R. Simpson
Keyword(s):  
Column Density ◽  
Surface Concentration ◽  
Trace Gas ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Data Set ◽  
Profile Method ◽  
Remote Sensing Technique ◽  
Vertical Column Density ◽  
Gas Layer

Abstract. Multiple Axis Differential Optical Absorption Spectroscopy (MAXDOAS) is a remote sensing technique that measures surface-associated trace gas profiles using simple automated instrumentation that requires very low power and is deployable at remote sites. However, the analysis of MAXDOAS data is complex and often cannot be applied rapidly or consistently over long measurement periods. Here we present three transparent methods to analyze MAXDOAS data. The box profile method finds the best trace gas layer height and surface-associated vertical column density (VCD) to simultaneously fit oxygen collisional dimer (O4) and trace gas differential slant column density (dSCD) observations. The elevated viewing method estimates the surface-associated VCD from observations at high view elevations, such as 10° and 20°. The horizon viewing method estimates the surface concentration of a trace gas by using near-horizon view trace gas and O4 data. We apply these methods to a two-month data set and show that the methods retrieve information 80% of the time and provides a consistent time series. Surface-associated trace gas VCD observations by the elevated viewing method correlate (r2 > 0.93) with the box profile method with slopes within 15% of unity. Surface-associated concentration observations from the horizon viewing method correlate well (r2 > 0.90) with the box profile method and a slope within 4% of unity. Application of these retrieval methods to UV-absorbing trace gases other than BrO is straightforward, and application in other spectral regions is discussed. These methods provide rapid and comprehensive inversions of MAXDOAS spectral data that are useful during field campaigns, as well as, verification of more complex (e.g. optimal estimate inversion) methods.

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 Shipborne MAX-DOAS measurements for validation of TROPOMI NO<sub>2</sub> products

2020 ◽  
Vol 13 (3) ◽  
pp. 1413-1426 ◽  
Author(s):  
Ping Wang ◽  
Ankie Piters ◽  
Jos van Geffen ◽  
Olaf Tuinder ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Column Density ◽  
Transport Model ◽  
Massively Parallel ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Chemistry Transport Model ◽  
The Pacific ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Good Agreement

Abstract. Tropospheric NO2 and stratospheric NO2 vertical column densities are important TROPOspheric Monitoring Instrument (TROPOMI) data products. In order to validate the TROPOMI NO2 products, KNMI Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments have measured NO2 on ship cruises over the Atlantic and the Pacific oceans. The MAX-DOAS instruments have participated in five cruises on board RV Sonne (in 2017 and 2019) and RV Maria S. Merian (in 2018). The MAX-DOAS measurements were acquired over 7 months and spanned about 90∘ in latitude and 300∘ in longitude. During the cruises aerosol measurements from Microtops sun photometers were also taken. The MAX-DOAS measured stratospheric NO2 columns between 1.5×1015 and 3.5×1015 molec cm−2 and tropospheric NO2 up to 0.6×1015 molec cm−2. The MAX-DOAS stratospheric NO2 vertical column densities have been compared with TROPOMI stratospheric NO2 vertical column densities and the stratospheric NO2 vertical column densities simulated by the global chemistry Transport Model, version 5, Massively Parallel model (TM5-MP). Good correlation is found between the MAX-DOAS and TROPOMI and TM5 stratospheric NO2 vertical column densities, with a correlation coefficient of 0.93 or larger. The TROPOMI and TM5 stratospheric NO2 vertical column densities are about 0.4×1015 molec cm−2 (19 %) higher than the MAX-DOAS measurements. The TROPOMI tropospheric NO2 also has good agreement with the MAX-DOAS measurements. The tropospheric NO2 vertical column density is as low as 0.5×1015 molec cm−2 over remote oceans.

scholarly journals Long-Term Variation in the Tropospheric Nitrogen Dioxide Vertical Column Density over Korea and Japan from the MAX-DOAS Network, 2007–2017

2021 ◽  
Vol 13 (10) ◽  
pp. 1937
Author(s):  
Yongjoo Choi ◽  
Yugo Kanaya ◽  
Hisahiro Takashima ◽  
Hitoshi Irie ◽  
Kihong Park ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Column Density ◽  
Optical Absorption Spectroscopy ◽  
Industrial Complex ◽  
Vertical Column ◽  
Source Regions ◽  
Potential Source ◽  
Vertical Column Density ◽  
Good Agreement

We investigated long-term observations of the tropospheric nitrogen dioxide vertical column density (NO2 TropVCD) from the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) network in Russia and ASia (MADRAS) from 2007 to 2017 at urban (Yokosuka and Gwangju) and remote (Fukue and Cape Hedo) sites in East Asia. The monthly mean in the NO2 TropVCD from MAX-DOAS measured at ~13:30 local time, which is the Ozone Monitoring Instrument (OMI) overpass time, shows good agreement with OMI data during summer, but differences between the two datasets increase in winter. The Theil-Sen slope of the long-term trend indicate a relatively rapid and gradual reduction in NO2 at Yokosuka and two remote sites (Fukue and Cape Hedo), respectively, regardless of the season except for fall at Fukue, but significant changes in NO2 are not observed at Gwangju, Korea. In contrast, OMI satellite data reveal an increase in the NO2 TropVCD at all sites except for Yokosuka, where a decreasing trend common to MAX-DOAS is found, suggesting that the results from satellites need to be cautiously used for investigating long-term trends in less polluted or remote areas. Using backward trajectories, potential source regions are identified for the two urban sites. The spatial distribution from OMI data shows good agreement with the potential source regions at Yokosuka. The potential source regions in Gwangju are identified as the National Industrial Complex in Yeosu and Gwangyang, while the transport route is not clearly visible with OMI data because of their low sensitivity in less polluted areas. The proposed approach is suitable for identifying potential source areas that might not be recognized by satellite observations.

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

2015 ◽  
Vol 8 (3) ◽  
pp. 1111-1133 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Temporal Stability ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Climate Analysis ◽  
Total Column

Abstract. 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 aboard EUMETSAT's MetOp-A and MetOp-B satellites and perform an extensive inter-comparison in order to evaluate their consistency and temporal stability. For the analysis, the GOME-2 data sets are generated by DLR in the framework of the EUMETSAT O3M-SAF project 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 a H2O and O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O total column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. The overall consistency between measurements from the newer GOME-2 instrument on board of the MetOp-B platform and the GOME-2/MetOp-A data is evaluated in the overlap period (December 2012–June 2014). Furthermore, we compare GOME-2 results with independent TCWV data from the ECMWF ERA-Interim reanalysis, with SSMIS satellite measurements during the full period January 2007–June 2014 and against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project (January 2007–December 2008). Global mean biases as small as ±0.035 g cm−2 are found between GOME-2A and all other data sets. The combined SSM/I-MERIS sample and the ECMWF ERA-Interim data set are typically drier than the GOME-2 retrievals, while on average GOME-2 data overestimate the SSMIS measurements by only 0.006 g cm−2. However, the size of these biases is seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, which include only data over ocean. The seasonal behaviour is not as evident when comparing GOME-2 TCWV to the ECMWF ERA-Interim and the SSM/I+MERIS data sets, since the different biases over land and ocean surfaces partly compensate each other. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three data sets, especially for land areas, although some discrepancies (bias larger than ±0.5 g cm−2) over ocean and over land areas with high humidity or a relatively large surface albedo are observed.

scholarly journals Recommendations for HCHO and SO2 Retrieval Settings from MAX-DOAS Observations under Different Meteorological Conditions

2021 ◽  
Vol 13 (12) ◽  
pp. 2244
Author(s):  
Zeeshan Javed ◽  
Aimon Tanvir ◽  
Muhammad Bilal ◽  
Wenjing Su ◽  
Congzi Xia ◽  
...  
Keyword(s):  
Column Density ◽  
Trace Gases ◽  
Meteorological Conditions ◽  
Optical Absorption Spectroscopy ◽  
Chemical Production ◽  
Vertical Column ◽  
Phase Oxidation ◽  
Fog Days ◽  
Rms Errors ◽  
Optimal Settings

Recently, the occurrence of fog and haze over China has increased. The retrieval of trace gases from the multi-axis differential optical absorption spectroscopy (MAX-DOAS) is challenging under these conditions. In this study, various reported retrieval settings for formaldehyde (HCHO) and sulfur dioxide (SO2) are compared to evaluate the performance of these settings under different meteorological conditions (clear day, haze, and fog). The dataset from 1st December 2019 to 31st March 2020 over Nanjing, China, is used in this study. The results indicated that for HCHO, the optimal settings were in the 324.5–359 nm wavelength window with a polynomial order of five. At these settings, the fitting and root mean squared (RMS) errors for column density were considerably improved for haze and fog conditions, and the differential slant column densities (DSCDs) showed more accurate values compared to the DSCDs between 336.5 and 359 nm. For SO2, the optimal settings for retrieval were found to be at 307–328 nm with a polynomial order of five. Here, root mean square (RMS) and fitting errors were significantly lower under all conditions. The observed HCHO and SO2 vertical column densities were significantly lower on fog days compared to clear days, reflecting a decreased chemical production of HCHO and aqueous phase oxidation of SO2 in fog droplets.

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