glyoxal retrievals from tropomi (glyretro) sentinel-5p

GLYoxal REtrievals from TROPOMI GLYRETRO

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Ref: S5p+I_CHOCHO_BIRA_PUM

Issue 1.1

GLYoxal Retrievals from TROPOMI (GLYRETRO)

Sentinel-5p + Innovation - Theme 1: CHOCHO

Product User Manual

document number : S5p+I_CHOCHO_BIRA_PUM

authors : Christophe Lerot

Distributed to : Christian Retscher, Marie-Helene Rio, Stefano Casadio, Daniele Gasbarra

issue : 1.1

date : 2021-12-22

status : Final


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Contents

List of Figures ........................................................................................................................ 2

List of Tables ......................................................................................................................... 2

1 Introduction .................................................................................................................... 3

Purpose and objective ...................................................................................................... 3

Document overview ......................................................................................................... 3

2 Applicable and Reference Documents .............................................................................. 4

Applicable Documents ...................................................................................................... 4

Reference Documents ...................................................................................................... 4

3 Acronyms, Terms and Definitions .................................................................................... 5

4 Introduction to the TROPOMI/S5p Glyoxal product. ........................................................ 6

5 Product description ......................................................................................................... 7

Product L2 File ................................................................................................................ 7

General structure of the L2 file content .............................................................................. 7

Detailed description of the variables contained in the L2 product. .......................................... 8

Recommendations for using the L2 CHOCHO product ......................................................... 13

Description of the L3 CHOCHO product............................................................................. 14

6 List of known issues ...................................................................................................... 16

7 References .................................................................................................................... 17

List of Figures

Figure 1: Mean glyoxal tropospheric vertical columns retrieved from three years of TROPOMI observations

(2018-2020). ................................................................................................................................. 6 Figure 2 : L2 glyoxal file structure .................................................................................................... 8

List of Tables

Table 1: Possible attributes associated to variables contained in the L2 CHOCHO files. ............................ 8 Table 2: List of variables stored in the group PRODUCT of TROPOMI glyoxal L2 files. .............................. 9 Table 3: List of variables stored in the group PRODUCT/DETAILED_RESULTS of TROPOMI glyoxal L2 files. .................................................................................................................................................. 10 Table 4: List of variables stored in the group PRODUCT/GEOLOCATIONS of TROPOMI glyoxal L2 files. .... 11 Table 5: List of variables stored in the group PRODUCT/INPUT_DATA and its subgroup BACKGROUND_CORRECTION of TROPOMI glyoxal L2 files.................................................................. 12 Table 6: List of variables stored in the TROPOMI glyoxal L3 daily grid files. .......................................... 15 Table 7: List of variables stored in the TROPOMI glyoxal L3 monthly grid files. ..................................... 15


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1 Introduction

Purpose and objective

The present document is the Product User Manual (PUM) describing the scientific S5p/TROPOMI glyoxal tropospheric vertical column product v4.0 generated at BIRA-IASB. Both L2 and L3 files are described in this document. Those products may be requested and accessed via the project website https://glyretro.aeronomie.be/.

The purpose of the document is to give a detailed description of the content of the product files. It also aims at giving recommendations to users on how to use the product.

Document overview

Sections 1 and 2 provide the introduction and references. Section 3 lists the acronyms, terms and definitions

used in this document. Section 4 gives a general introduction of the TROPOMI glyoxal product. Section 5 is the core of the document. It describes the L2 product, the general structure of the files and details all contained variables. It also gives recommendations on how to use the data. In addition, a L3 gridded product based on the L2 data is also generated and described in this section. Finally, Section 6 lists known issues.


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2 Applicable and Reference Documents

Applicable Documents

[AD01] Sentinel-5p Innovation (S5p+I) - Statement of Work - EOP-SD-SOW-2018-049, source: ESA, issue: 2, date: 20/08/2018.

[AD02] Sentinel-5p+Innovation: Theme 1; Glyoxal Retrievals from TROPOMI (GLYRETRO): Requirement

Baseline Document,

source: BIRA-IASB, issue: 2.0, ref: S5p+I_CHOCHO_BIRA_RB, date: 2019-11-01.

[AD03] Sentinel-5p+Innovation: Theme 1; Glyoxal Retrievals from TROPOMI (GLYRETRO): Auxiliary User Manual, Source: BIRA-IASB, issue: 2.0, ref: S5p+I_CHOCHO_BIRA_AUM, date: 2021-10-19.

[AD04] Sentinel-5p+Innovation: Theme 1; Glyoxal Retrievals from TROPOMI (GLYRETRO): Algorithm Theoretical Baseline Document,

Source: BIRA-IASB, issue: 3.1, ref: S5p+I_CHOCHO_BIRA_ATBD, date: 2021-12-22.

[AD05] Sentinel-5p+Innovation: Theme 1; Glyoxal Retrievals from TROPOMI (GLYRETRO): Product Validation Report,

Source: IUP-Bremen, issue: 2.1, ref: S5p+I_CHOCHO_BIRA_VR, date: 2021-12-22.

Reference Documents

[RD01] Terms, and symbols in the TROPOMI Algorithm Team; source: KNMI; ref: SN-TROPOMI-KNMI-L2-049-MA; issue: 1.0.0; date: 2015-07-16

[RD02] TROPOMI Instrument and Performance Overview. source:KNMI;ref:S5P-KNMI-L2-0010-RP; issue:0.10.0; date:2014-03-15.

[RD03] S5P/TROPOMI ATBD of the total and tropospheric NO2 data products; source: KNMI; ref: S5P-KNMI-L2-0005-RP; issue: 2.2.0; date: 2021-06-16.

[RD04] S5P/TROPOMI Level 2 Product User Manual Nitrogen dioxide;

source: KNMI, ref: S5P-KNMI-L2-0021-MA; issue: 4.0.1; date: 2021-07-06.


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3 Acronyms, Terms and Definitions

Terms, definitions and abbreviated terms that are used in development program for the TROPOMI L2 data processors are listed in [RD01].

The most important symbols and acronyms related to the data product described in this document are the following:

A averaging kernel

m altitude-resolved air mass factor or weighting function

M air-mass factor

Ns slant column density

Nv vertical column density

x vertical profile

Acronym Explanation

AAI Absorbing Aerosol Index

AMF Air Mass Factor

ATBD Algorithm Theoretical Basis Document

BIRA-IASB Royal Belgian Institute for Space Aeronomy

CF Climate and Forecast metadata conventions

CHOCHO Glyoxal

DOAS Differential Optical Absorption Spectroscopy

ESA European Space Agency

GOME Global Ozone Monitoring Experiment

GLYRETRO GLYoxal REtrievals from TROPOMI

MAX-DOAS Multi-Axis DOAS

NMVOC Non-Methane Volatile Organic Compound

OMI Ozone Monitoring Instrument

SCD Slant Column Density

SCIAMACHY SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY

SZA Solar Zenith Angle

TROPOMI Tropospheric Monitoring Instrument

VAA Viewing Azimuth Angle

VCD Vertical Column Density

VOC Volatile Organic Compound

VZA Viewing Zenith Angle


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4 Introduction to the TROPOMI/S5p Glyoxal product.

Glyoxal is mostly produced in the atmosphere as an intermediate product in the oxidation of other Non-Methane Volatile Organic Compounds (NMVOCs). It is also directly emitted from fire events and combustion processes. Several attempts to establish a glyoxal global budget using chemistry transport models (Cao et al., 2018; Fu et al., 2008; Li et al., 2016; Myriokefalitakis et al., 2008; Stavrakou et al., 2009) have estimated the production from natural sources and fires to about 70% and from human activities to about 30%. Owing to its short lifetime (a few hours), elevated glyoxal concentrations are observed near emission

sources (Figure 1). Satellite observations of glyoxal contribute therefore to provide information on NMVOC

emissions in support to air quality and chemistry-climate related studies. In addition, glyoxal is also known to significantly contribute to the total budget of secondary organic aerosols (Washenfelder et al., 2011), which impact both air quality and climate forcing.

Figure 1: Mean glyoxal tropospheric vertical columns retrieved from three years of TROPOMI observations (2018-2020).

Glyoxal has three absorption bands in the visible spectral range that have been exploited to remotely retrieve information on its atmospheric abundance using the Differential Optical Absorption Spectroscopy method (DOAS, Platt and Stutz, 2008) applied to ground-based (e.g. Benavent et al., 2019; Hoque et al., 2018;

Javed et al., 2019; Schreier et al., 2020), air-borne (e.g. Kluge et al., 2020; Volkamer et al., 2015), ship-borne (e.g. Behrens et al., 2019; Sinreich et al., 2010) and space-based instruments. The first global glyoxal tropospheric column observations from space have been realized by Wittrock et al. (2006) using nadir measurements from the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) instrument. Based on this pioneering work, different glyoxal data products were derived from the Global Ozone Monitoring Experiment-2 (GOME-2) (Lerot et al., 2010; Vrekoussis et al., 2009) and from

the Ozone Monitoring Instrument (OMI) (Alvarado et al., 2014; Chan Miller et al., 2014). All those different

products rely on a similar DOAS approach, but generally differ from each other by the choice of the fit settings and of the auxiliary input data.

As part of the S5p+Innovation program, the BIRA-IASB scientific glyoxal retrieval algorithm has been further developed and applied to the TROPOMI L1 data. The product has been extensively compared with other satellite data products as well as with a few MAX-DOAS glyoxal data sets from stations in Asia and Europe. A detailed description of the algorithm and of the validation results can be found in the GLYRETRO ATBD

[AD04] and Validation Report [AD05] as well as in Lerot et al. (2021). The scientific requirements currently defined for glyoxal retrievals have been discussed in the requirement baseline document [AD02] and the satellite inter-comparison and validation exercises have shown that those requirements are generally met (for clear-sky scenes).


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5 Product description

Product L2 File

The current output format of the L2 CHOCHO files produced by this scientific algorithm follows closely the current conventions of the operational products, in terms of filename and content structure as well as variable name nomenclature and units. The output files are in NetCDF-4, with the convention CF.

A typical L2 glyoxal filename is structured as:

S5P_OFFL_L2__CHOCHO___20180904T054104_20180904T072234_04623_01_010000_20190315.nc

where the two first time stamps in yellow correspond to start and end of the orbit, the orbit number is in

green, the grey substrings inherit from the collection and product versions of the L1 data, and the creation date is in cyan.

Every individual L2 file corresponds to one S5p orbit and include for each ground pixel a comprehensive list of variables, covering:

glyoxal vertical column, slant column and air mass factor measurement time and geolocation (center and corner), taken from the L1b product

retrieval diagnostics including error estimates, averaging kernel and a priori information. quality flags. input parameters Various flags useful for using the product.

General structure of the L2 file content

The general structure of the L2 files is illustrated in Figure 2. The primary group within the file is PRODUCT,

which contains main output variables and a subgroup SUPPORT_DATA providing additional information:

PRODUCT: This group stores the main data fields of the product, including the precision of the main parameter, latitude, longitude and variables to determine the observation time. The “qa_value” parameter provides an estimate of the reliability of the measurement and range from 100 (high quality) to 0 (poor quality).

SUPPORT_DATA: This group stores additional data needed for advanced use of the product. This group is

split into different subgroups:

DETAILED_RESULTS: Additional output, including full state-vectors, error estimates, a priori information, intermediate results…

GEOLOCATIONS: Additional geolocation and geometry related fields, including the pixel corner

coordinates, viewing and solar zenith angles, azimuth angles.

INPUT_DATA: Additional input data, such as surface albedo and altitude, cloud information, additional flags…


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Figure 2 : L2 glyoxal file structure

The primary group PRODUCT also includes a set of dimensioning variables:

- time : A time dimension. The length of this dimension is 1. The reason this dimension is used is compatibility with the CF convention. It contains the number of seconds since 2010-01-01, UTC midnight.

- scanline: the dimension along the flight direction. - ground_pixel: The dimension perpendicular to the flight direction. - corner: The length of this dimension is 4 and represents the number of corners for every

measurement footprint. - layer: the vertical dimension of the atmosphere.

Detailed description of the variables contained in the L2 product.

In this section, we provide a detailed description of all variables contained in the different groups of the L2 CHOCHO files. Each of those variables have a series of attributes providing complementary information to

the user. The full list of possible variable attributes and their description is given in Table 1. Table 2-Table 5

list all variables contained in the different groups of the L2 files, describe them and provide their dimension and units.

Table 1: Possible attributes associated to variables contained in the L2 CHOCHO files.

attribute description

comment Miscellaneous information about the data or methods used to produce it.

coordinates Identifies auxiliary coordinate variables, providing a connection between data and geolocation, time.

_FillValue Value to represent missing or undefined data.

flag_meanings Use in conjunction with flag_values to provide descriptive words or phrases for each flag value.

flag_values Provides a list of the flag values. Use in conjunction with flag_meanings.


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long_name A descriptive name that indicates a variable’s content. This name is not standardized.

multiplication_factor_ to_convert_to_DU

Multiply the contents of the variable with this scale factor to obtain columns in DU.

multiplication_factor_ to_convert_to_molecules_percm2

Multiply the contents of the variable with this scale factor to obtain columns in molecules/cm²

scale_factor Scale Factor to be applied to the content of the variable

source Method of production of the original data.

standard_name A standard name that references a description of a variable’s content in the standard name table.

units Units of a variable’s content.

valid_min Smallest valid value of a variable.

valid_max Largest valid value of a variable

Table 2: List of variables stored in the group PRODUCT of TROPOMI glyoxal L2 files.

Name Unit Dimension Description / long name

time s 1 Reference time since 2010-01-01 00:00:00

delta_time ms time x scanline x ground_pixel

Time difference with respect to the reference time variable for each scanline.

time_utc - time x scanline

String array with each observation time stored as an ISO date string

glyoxal_tropospheric_vertical_column

mol.m-

2

time x scanline x ground_pixel

Glyoxal tropospheric vertical column

glyoxal_tropospheric_vertical _column_precision

mol.m-

2


Glyoxal tropospheric vertical column random error

qa_value 1 time x scanline x ground_pixel

Quality assurance value describing the quality of the measurement. It is recommended to reject all pixels with a qa_value less than 50% (0.5)

latitude degree north


Latitude of the center of each ground pixel

longitude degree

east


Longitude of the center of each ground pixel


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Table 3: List of variables stored in the group PRODUCT/DETAILED_RESULTS of TROPOMI glyoxal L2 files.


averaging_kernel 1

time x scanline x ground_pixel x layer

Column averaging kernel

fitted_radiance_shift

nm time x scanline x ground_pixel

Radiance wavelength shift from the DOAS fit

fitted_radiance_squeeze

1 time x scanline x ground_pixel

Radiance wavelength stretch from the DOAS fit

fitted_root_mean_square


DOAS fit residual root mean square

fitted_slant_columns

mol.m-2 mol.m-2 mol.m-2 mol.m-2 mol.m-2 mol.m-2

1 m 1 1 1 1 1 1

time x scanline x ground_pixel x number_of_slant_columns

Slant column density from all absorbers/cross-sections in the fitting window: glyoxal O3 NO2 (220K) NO2 (296K) H2O O4 Ring Liquid Water Offset (0th order) Offset (1st order) resolution_delta common residual scene_heterogeneity1 scene_heterogeneity2

fitted_slant_columns_precision

mol.m-2 mol.m-2 mol.m-2 mol.m-2 mol.m-2 mol.m-2

1 m 1 1 1 1 1 1

time x scanline x ground_pixel x number_of_slant_columns

Slant column density random errors from all absorbers in the fitting window: glyoxal O3 NO2 (220K) NO2 (296K) H2O O4 Ring Liquid Water Offset (0th order) Offset (1st order) resolution_delta common residual scene_heterogeneity1 scene_heterogeneity2.

glyoxal_profile_apriori

1 (vmr)


a priori profile used for AMF computation


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glyoxal_profile_apriori_pressure

Pa


Vertical pressure grid of a priori profile

glyoxal_slant_column_corrected

mol.m-2 time x scanline x ground_pixel

Background-corrected glyoxal slant column

glyoxal_slant_column_corrected_trueness


Systematic error on the glyoxal slant column

glyoxal_tropospheric_air_mass_factor


Glyoxal clear air mass factor

glyoxal_ tropospheric _air_mass_factor_trueness

1


Systematic error on the air mass factor

glyoxal_tropospheric _air_mass_factor_kernel_trueness

1


Systematic error on the air mass factor without smoothing error

glyoxal_ tropospheric _air_mass_factor_precision

1


Random error on the air mass factor

glyoxal_tropospheric_vertical _column_trueness


Glyoxal tropospheric column systematic error

glyoxal_tropospheric_vertical_column_kernel_trueness


Glyoxal tropospheric column systematic error without smoothing error

number_of_slant_columns

1 1 Dimension Variable : number of elements in the DOAS state vector

scene_inhomogeneity_factor


Degree of the scene brightness heterogeneity (0 : homogeneous ; -1/+1 maximum heterogeneity).

Table 4: List of variables stored in the group PRODUCT/GEOLOCATIONS of TROPOMI glyoxal L2 files.


solar_zenith_angle degree time x scanline x ground_pixel

Zenith angle of the sun measured from the ground pixel location

solar_azimuth_angle

degree time x scanline x ground_pixel

Azimuth angle of the sun measured from the ground pixel location

viewing_zenith_angle


Zenith angle of the satellite measured from the ground pixel location

viewing_azimuth_angle


Azimuth angle of the satellite measured from the ground pixel location


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latitude_bounds degree north

time x scanline x ground_pixel x corner

The four latitude boundaries of each ground pixel.

longitude_bounds degree east

time x scanline x ground_pixel x corner

The four longitude boundaries of each ground pixel.

Table 5: List of variables stored in the group PRODUCT/INPUT_DATA and its subgroup BACKGROUND_CORRECTION of TROPOMI glyoxal L2 files.


aerosol_index_354_388


Aerosol absorbing index from the 354/388 nm wavelength pair

cloud_fraction_crb 1 time x scanline x ground_pixel

Effective cloud fraction derived in the NO2 fitting window. Extracted from the S5p NO2 operational product [RD04].

cloud_pressure_crb

Pa time x scanline x ground_pixel

Cloud optical centroid pressure. Extracted from the S5p NO2 operational product [RD04]. For information only (not used in the algorithm)

land_ocean_flag 1 time x scanline x ground_pixel

Indicates whether the gorund_pixel is located over land or ocean. 0 : land ; 1 : ocean. Extracted from the surface classification variable in the operational NO2 product [RD04].

snow_ice_flag 1 time x scanline x ground_pixel

Indicates percentage of snow/ice cover over the pixel footprint : 0-100 percent sea ice; 101 permanent ice ; 103 snow ; 252 mixed pixels at coastlines ; 253 suspect ice value ; 254 corners ; 255 ocean. Extracted from the operational NO2 product [RD04].

surface_albedo 1 time x scanline x ground_pixel

Surface albedo extracted from the OMI LER climatology (Kleipool et al., 2008).

surface_altitude m time x scanline x ground_pixel

Effective surface altitude of the pixel footprint. Extracted from the operational NO2 product [RD04].

surface_classification


Surface classification extracted from the operational NO2 product [RD04].

surface_pressure Pa time x scanline x ground_pixel

Surface pressure of the pixel footprint.

BACKGROUND_CORRECTION

detector_rows 1 1 Dimension variable for background correction variables. Dimension perpendicular to the flight direction

lat_nbins 1 1 Dimension variable for background correction variables. Dimension of the binning of the reference sector along the latitudinal dimension.

glyoxal_reference_sector_days_used

1 - String variable listing dates of observations considered for computing slant column correction terms.


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glyoxal_reference_sector_mean_air_mass_factor Ɨ

1 lat_nbins x detector_rows

Latitude/ground_pixel-binned glyoxal AMF of the pixels falling into the reference sector

glyoxal_reference_sector_mean_air_mass_factor_trueness Ɨ


Latitude/ground_pixel-binned glyoxal AMF systematic errors of the pixels falling into the reference sector

glyoxal_reference_sector_mean_model_scd Ɨ

mol.m-2 lat_nbins x detector_rows

Latitude/ground_pixel-binned modelled glyoxal slant columns of the pixels falling into the reference sector

glyoxal_reference_sector_mean_scd Ɨ

mol.m-2 lat_nbins x detector_rows

Latitude/ground_pixel-binned glyoxal slant columns of the pixels falling into the reference sector

glyoxal_tropospheric_column_reference

mol.m-2 1 Reference glyoxal tropospheric vertical column for the background correction.

glyoxal_tropospheric_column_reference_trueness

mol.m-2 1 Systematic error on the reference glyoxal tropospheric vertical column for the background correction.

number_of_reference_sector_mean_obs Ɨ


Number of pixels considered for the latitude/ground_pixel binning of the reference sector.

Ɨ Depending on the configuration of the background correction in the algorithm, those variables are not

necessarily completely filled in. The content of the variable lat_nbins indicates how the binning of reference

sector along the latitude dimension has been set up.

Recommendations for using the L2 CHOCHO product

As mentioned before, the file format is netCDF-4, which is now a standard for Earth Observation missions. This format is versatile, flexible and permits the user to use netCDF-4 or HDF-5 APIs written in many data-analysis packages (e.g. IDL, MatLab, Python, C, C++,…) in order to read the data. This format also facilitates the visualization of the Geo-2D variables contained in the file with visualization tools such as Panoply (http://www.giss.nasa.gov/tools/panoply/). All variables contained in the L2 files are provided for all TROPOMI observations with a solar zenith angle less than 70°. No filter is applied by default for degraded fit quality, cloud or aerosol contamination, snow/ice cover… Instead, the user is recommended to use the qa_value variable to filter out the data. Keeping data with a qa_value equal or higher than 0.5 guarantees that only clear sky observations (cloud fraction less than or equal to 20%), not covered by snow/ice and with good fit quality are considered. This approach allows advanced users to implement their own filtering approach by making use of the different variables contained in the files. It is however reminded that no cloud correction is applied for the AMF computation. It is therefore essential to reject cloud-contaminated pixels, even if there is some flexibility on the cloud fraction thresholds to be used for this.

Advanced users may also exploit the column averaging kernels A and the a priori information provided in

the L2 files when ingesting them in their own application. In DOAS, the column averaging kernel is computed as the altitude-dependent AMF (or Box-AMF) divided by the total AMF (Boersma et al., 2004). Averaging kernels can be used in the following ways:

When comparing TROPOMI column data with independent profile data from other instruments or models, discrepancies due to the assumptions made in the TROPOMI retrievals can be minimized by

recomputing a column 𝑁𝑣𝑖𝑛𝑑𝑒𝑝

by multiplying the partial column profile from the independent source

𝑥𝑖𝑛𝑑𝑒𝑝 with the averaging kernel as

𝑁𝑣𝑖𝑛𝑑𝑒𝑝

= ∑ 𝐴𝑙𝑥𝑖𝑛𝑑𝑒𝑝,𝑙

𝑙

http://www.giss.nasa.gov/tools/panoply/


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Alternatively, TROPOMI AMFs can also be recomputed with any available a priori profile using the averaging kernels as

𝑀′ = 𝑀 ∑ 𝐴𝑙𝑥′𝑙

𝑙

∑ 𝑥′𝑙

𝑙

⁄

where M is the AMF provided in the L2 file based on the a priori profile used in the retrieval algorithm, and M’ is the new AMF corresponding to the new a priori profile.

The L2 product includes estimates for the random and systematic errors of the retrieved glyoxal tropospheric vertical column, namely the glyoxal_tropospheric_vertical_column_precision and the

glyoxal_tropospheric_vertical_column_trueness. The first term is estimated by propagation of the instrumental noise through the algorithm. The second term results from all systematic errors in the different steps of the algorithm due to input data uncertainty, forward model and assumption errors… Please refer to [AD04] or Lerot et al. (2021) for a comprehensive description of those errors. Among the systematic errors,

a significant component is the smoothing error, i.e. the error caused by the use of inexact a priori profile information in the AMF computation. As described above, this a priori profile can be replaced by any other external information by making use of the averaging kernels. If this new information can be considered as accurate, the smoothing error should become small. This motivates the provision of a total systematic error computed without this smoothing error (glyoxal_tropospheric_vertical_column_kernel_trueness). The total error 𝜎𝑁𝑣

combining both the random and systematic errors can be computed for single observations

as:

𝜎𝑁𝑣= √𝜎𝑁𝑣,𝑟𝑎𝑛𝑑

2 + 𝜎𝑁𝑣,𝑠𝑦𝑠𝑡2

Glyoxal being a weak absorber, the random component is large and dominates for single observations. The

product noise generally requires averaging of multiple observations in time and/or space to unambiguously detect real glyoxal signal. Only in case of extreme fire events, the measured glyoxal columns may occasionally exceed the detection limit for single observations. When combining N observations, the random

component of the error is reduced and the total error may be computed as:

𝜎𝑁𝑣= √

𝜎𝑁𝑣,𝑟𝑎𝑛𝑑2

𝑁+ 𝜎𝑁𝑣,𝑠𝑦𝑠𝑡

2

Because of this averaging need and because L2 product files are heavy and contain a lot of information useful for experts only, it is very convenient for many users to have directly gridded L3 data. Such glyoxal grids are described in the next section.

Description of the L3 CHOCHO product.

The gridding capability available within the HARP toolkit of the atmospheric toolbox (https://atmospherictoolbox.org/harp/) has been used to generate L3 data grids on a daily basis and with a spatial resolution of 0.05°x0.05°. The L3 product consists in one NetCDF file per day containing a series of key variables gridded using all L2 orbit files of the same day as input. Note that all L2 retrievals with a qa_value less than 0.5 have been rejected before the gridding process. The coverage of those daily grids is therefore incomplete and in particular cloud-covered area are missing. In addition, monthly grids of

the glyoxal tropospheric vertical columns are also computed by averaging the daily grids.

The L3 daily and monthly grid filenames are structured as CHOCHO_S5P_V4_BIRA_YYYYMMDD.nc and CHOCHO_S5P_V4_BIRA_YYYYMM_Monthly.nc where the yellow substring indicates the product version while the green substrings indicate the date of the grid. Table 6 and Table 7 lists and describes all variables contained in the L3 daily and monthly gridded data files.

https://atmospherictoolbox.org/harp/


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Table 6: List of variables stored in the TROPOMI glyoxal L3 daily grid files.


latitude degree north 3600 Dimension variable along the latitude dimension. Latitude of the center of each bin.

longitude degree east 7200 Dimension variable along the longitude dimension. Longitude of the center of each bin.

doas_fit_rms 1 latitude x longitude

Binned DOAS fit residual root mean square. Equivalent variable name in L2 product: fitted_root_mean_square

glyoxal_amf 1 latitude x longitude

Binned glyoxal clear air mass factor. Equivalent variable name in L2 product: glyoxal_tropospheric_air_mass_factor

glyoxal_corrected_scd

molecules.cm-2 latitude x longitude

Binned glyoxal background-corrected slant column. Equivalent variable name in L2 product: glyoxal_slant_column_corrected

glyoxal_scd molecules.cm-2 latitude x longitude

Binned glyoxal slant column. Equivalent variable name in L2 product: fitted_slant_columns

glyoxal_vcd molecules.cm-2 latitude x longitude

Binned glyoxal tropospheric vertical column. Equivalent variable name in L2 product: glyoxal_tropospheric_vertical_column

glyoxal_vcd_kernel_trueness

molecules.cm-2

latitude x longitude

Binned glyoxal tropospheric vertical column systematic error without smoothing error. Equivalent variable name in L2 product: glyoxal_tropospheric_vertical_column_kernel_trueness

glyoxal_vcd_precision


Binned glyoxal tropospheric vertical column random error. Equivalent variable name in L2 product: glyoxal_tropospheric_vertical _column_precision

glyoxal_vcd_trueness


Binned glyoxal tropospheric vertical column systematic error. Equivalent variable name in L2 product: glyoxal_tropospheric_vertical _column_trueness

surface_albedo 1 latitude x longitude

Binned surface albedo. Equivalent variable name in L2 product: surface_albedo

Table 7: List of variables stored in the TROPOMI glyoxal L3 monthly grid files.


latitude degree north 3600 Dimension variable along the latitude dimension.

longitude degree east 7200 Dimension variable along the longitude dimension.

monthly_glyoxal_vcd


Binned glyoxal tropospheric vertical column. Equivalent variable name in L2 product: glyoxal_tropospheric_vertical_column

count 1 latitude x longitude

Number of days of the month contributing to this cell.


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6 List of known issues

- The group PRODUCT/DETAILED_RESULTS in the CHOCHO L2 output files includes a subgroup WAVELENGTH_CALIBRATIONS with variables foreseen to report results from the DOAS wavelength calibration fits. Those variables are currently filled in with fill values only.

- Failure of the background correction is not properly traced in the qa_value computation. In this case, qa_values are acceptable while the main output variables are fill values. To circumvent this, we

recommend adding a filter to reject pixels with the main variable

glyoxal_tropospheric_vertical_column > 1e30.


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7 References

Alvarado, L. M. A., Richter, A., Vrekoussis, M., Wittrock, F., Hilboll, A., Schreier, S. F. and Burrows, J. P.: An improved glyoxal retrieval from OMI measurements, Atmos. Meas. Tech., 7(12), 4133–4150, doi:10.5194/amt-7-4133-2014, 2014.

Behrens, L. K., Hilboll, A., Richter, A., Peters, E., Alvarado, L. M. A., Kalisz Hedegaard, A. B., Wittrock, F., Burrows, J. P. and Vrekoussis, M.: Detection of outflow of formaldehyde and glyoxal from the African continent to the Atlantic Ocean with a MAX-DOAS instrument, Atmos. Chem. Phys., 19(15), 10257–10278,

doi:10.5194/acp-19-10257-2019, 2019.

Benavent, N., Garcia-Nieto, D., Wang, S. and Saiz-Lopez, A.: MAX-DOAS measurements and vertical profiles of glyoxal and formaldehyde in Madrid, Spain, Atmos. Environ., 199, 357–367, doi:10.1016/j.atmosenv.2018.11.047, 2019.

Boersma, K. F., Eskes, H. J. and Brinksma, E. J.: Error analysis for tropospheric NO 2 retrieval from space, J. Geophys. Res. Atmos., 109(D4), n/a-n/a, doi:10.1029/2003JD003962, 2004.

Cao, H., Fu, T. M., Zhang, L., Henze, D. K., Miller, C. C., Lerot, C., Abad, G. G., De Smedt, I., Zhang, Q.,

Van Roozendael, M., Hendrick, F., Chance, K., Li, J., Zheng, J. and Zhao, Y.: Adjoint inversion of Chinese non-methane volatile organic compound emissions using space-based observations of formaldehyde and glyoxal, Atmos. Chem. Phys., 18(20), 15017–15046, doi:10.5194/acp-18-15017-2018, 2018.

Chan Miller, C., Gonzalez Abad, G., Wang, H., Liu, X., Kurosu, T., Jacob, D. J. and Chance, K.: Glyoxal retrieval from the Ozone Monitoring Instrument, Atmos. Meas. Tech., 7(11), 3891–3907, doi:10.5194/amt-7-3891-2014, 2014.

Fu, T.-M. T.-M., Jacob, D. J., Wittrock, F., Burrows, J. P., Vrekoussis, M. and Henze, D. K.: Global budgets of atmospheric glyoxal and methylglyoxal, and implications for formation of secondary organic aerosols, J. Geophys. Res., 113(D15), D15303, doi:10.1029/2007JD009505, 2008.

Hoque, H. M. S., Irie, H. and Damiani, A.: First MAX-DOAS Observations of Formaldehyde and Glyoxal in Phimai, Thailand, J. Geophys. Res. Atmos., 123(17), 9957–9975, doi:10.1029/2018JD028480, 2018.

Javed, Z., Liu, C., Khokhar, M., Tan, W., Liu, H., Xing, C., Ji, X., Tanvir, A., Hong, Q., Sandhu, O., Rehman, A., Javed, Z., Liu, C., Khokhar, M. F., Tan, W., Liu, H., Xing, C., Ji, X., Tanvir, A., Hong, Q., Sandhu, O. and

Rehman, A.: Ground-Based MAX-DOAS Observations of CHOCHO and HCHO in Beijing and Baoding, China, Remote Sens., 11(13), 1524, doi:10.3390/rs11131524, 2019.

Kleipool, Q. L., Dobber, M. R., de Haan, J. F. and Levelt, P. F.: Earth surface reflectance climatology from 3 years of OMI data, J. Geophys. Res., 113(D18), D18308, doi:10.1029/2008JD010290, 2008.

Kluge, F., Hüneke, T., Knecht, M., Lichtenstern, M., Rotermund, M., Schlager, H., Schreiner, B. and Pfeilsticker, K.: Profiling of formaldehyde, glyoxal, methylglyoxal, and CO over the Amazon: normalized

excess mixing ratios and related emission factors in biomass burning plumes, Atmos. Chem. Phys., 20(20),

12363–12389, doi:10.5194/acp-20-12363-2020, 2020.

Lerot, C., Stavrakou, T., De Smedt, I., Müller, J. F., Van Roozendael, M., M̈uller, J. F. and Van Roozendael, M.: Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model, Atmos. Chem. Phys., 10(24), 12059–12072, doi:10.5194/acp-10-12059-2010, 2010.

Lerot, C., Hendrick, F., Van Roozendael, M., Alvarado, L. M., Richter, A., De Smedt, I., Theys, N., Vlietinck, J., Yu, H., Van, J., Stavrakou, T., Müller, J.-F., Valks, P., Loyola, D., Kumar, V., Wagner, T., Schreier, S. F.,

Sinha, V., Wang, T., Wang, P. and Retscher, C.: Glyoxal tropospheric column retrievals from TROPOMI, multi-satellite intercomparison and ground-based validation 2 3, , doi:10.5194/amt-2021-158, n.d.

Li, J., Mao, J., Min, K.-E., Washenfelder, R. A., Brown, S. S., Kaiser, J., Keutsch, F. N., Volkamer, R., Wolfe, G. M., Hanisco, T. F., Pollack, I. B., Ryerson, T. B., Graus, M., Gilman, J. B., Lerner, B. M., Warneke, C., de Gouw, J. A., Middlebrook, A. M., Liao, J., Welti, A., Henderson, B. H., McNeill, V. F., Hall, S. R., Ullmann, K., Donner, L. J., Paulot, F. and Horowitz, L. W.: Observational constraints on glyoxal production from isoprene oxidation and its contribution to organic aerosol over the Southeast United States, J. Geophys. Res. Atmos.,

121(16), 9849–9861, doi:10.1002/2016JD025331, 2016.

Myriokefalitakis, S., Vrekoussis, M., Tsigaridis, K., Wittrock, F., Richter, A., Brühl, C., Volkamer, R., Burrows, J. P. and Kanakidou, M.: The influence of natural and anthropogenic secondary sources on the glyoxal global


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distribution, Atmos. Chem. Phys., 8(16), 4965―4981 [online] Available from: http://www.atmos-chem-phys.net/8/4965/2008/, 2008.

Platt, U. and Stutz, J.: Differential Optical Absorption Spectroscopy: Principles and Applications, Springer-Verlag., 2008.

Schreier, S. F., Richter, A., Peters, E., Ostendorf, M., Schmalwieser, A. W., Weihs, P. and Burrows, J. P.: Dual ground-based MAX-DOAS observations in Vienna, Austria: Evaluation of horizontal and temporal NO2,

HCHO, and CHOCHO distributions and comparison with independent data sets, Atmos. Environ. X, 5, 100059, doi:10.1016/J.AEAOA.2019.100059, 2020.

Sinreich, R., Coburn, S., Dix, B. and Volkamer, R.: Ship-based detection of glyoxal over the remote tropical

Pacific Ocean, Atmos. Chem. Phys., 10(23), 11359–11371, doi:10.5194/acp-10-11359-2010, 2010.

Stavrakou, T., MÃ¼ller, J.-F., De Smedt, I., Van Roozendael, M., Kanakidou, M., Vrekoussis, M., Wittrock, F., Richter, A. and Burrows, J. P.: The continental source of glyoxal estimated by the synergistic use of

spaceborne measurements and inverse modelling, Atmos. Chem. Phys., 9(21), 8431–8446 [online] Available from: http://www.atmos-chem-phys.net/9/8431/2009/, 2009.

Volkamer, R., Baidar, S., Campos, T. L., Coburn, S., DiGangi, J. P., Dix, B., Eloranta, E. W., Koenig, T. K., Morley, B., Ortega, I., Pierce, B. R., Reeves, M., Sinreich, R., Wang, S., Zondlo, M. A. and Romashkin, P. A.: Aircraft measurements of BrO, IO, glyoxal, NO2, H2O, O2–O2 and aerosol extinction profiles in the t, Atmos. Meas. Tech., 8(5), 2121–2148, doi:10.5194/amt-8-2121-2015, 2015.

Vrekoussis, M., Wittrock, F., Richter, A. and Burrows, J. P.: Temporal and spatial variability of glyoxal as

observed from space, Atmos. Chem. Phys., 9(13), 4485–4504, doi:10.5194/acp-9-4485-2009, 2009.

Washenfelder, R. A., Young, C. J., Brown, S. S., Angevine, W. M., Atlas, E. L., Blake, D. R., Bon, D. M., Cubison, M. J., de Gouw, J. A., Dusanter, S., Flynn, J., Gilman, J. B., Graus, M., Griffith, S., Grossberg, N.,

Hayes, P. L., Jimenez, J. L., Kuster, W. C., Lefer, B. L., Pollack, I. B., Ryerson, T. B., Stark, H., Stevens, P. S. and Trainer, M. K.: The glyoxal budget and its contribution to organic aerosol for Los Angeles, California, during CalNex 2010, J. Geophys. Res., 116(D21), D00V02, doi:10.1029/2011JD016314, 2011.

Wittrock, F., Richter, A., Oetjen, H., Burrows, J. P., Kanakidou, M., Myriokefalitakis, S., Volkamer, R., Beirle,

S., Platt, U. and Wagner, T.: Simultaneous global observations of glyoxal and formaldehyde from space, Geophys. Res. Lett., 33(16), L16804, doi:10.1029/2006GL026310, 2006.