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Bromine monoxide (BrO) is a key radical in the atmosphere, influencing the chemical state of the atmosphere, most notably the abundance of ozone (O3). O3 depletion caused by the release of bromine has been observed and modeled in polar regions, salt pans, and in particular inside volcanic plumes. Furthermore, the molar ratio of BrO and SO2 – which can be detected simultaneously via spectroscopic measurements using the differential optical absorption spectroscopy (DOAS) method – is a proxy for the magmatic composition of a volcano and potentially an eruption forecast parameter. The detection of BrO in volcanic plumes from satellite spectroscopic observations is limited by the precision and sensitivity of the retrieval, which so far only allowed for the detection of BrO during major eruptions. The unprecedented spatial resolution of up to 3.5km×5.5km and the high signal-to-noise ratio of the TROPOspheric Monitoring Instrument (TROPOMI) on board Sentinel-5 Precursor (S-5P) enable observing and monitoring volcanic bromine release globally even for minor eruptions or even quiescent degassing. In this study, we investigate how far the BrO retrieval can be improved using TROPOMI data and how well BrO can be detected, even in small eruptions and during quiescent volcanic degassing. There are two steps for which improvements in accuracy are investigated and applied: the improvement and quantitative determination of (1) the detection limit of the DOAS BrO column retrieval and (2) the correction of the non-volcanic background BrO signal. First, the DOAS retrieval settings are varied, and their influence on accuracy and precision is investigated with respect to the detection limit and potential systematic influences. Based on these results, we propose a dedicated DOAS evaluation scheme optimized for the detection of BrO in volcanic plumes. For the DOAS retrieval, we propose the use of a large fit window from 323–360 nm , yielding a statistical uncertainty lower by a factor of 1.8 compared to previous BrO DOAS algorithms while not enhancing systematic influences. Second, the effect of the background BrO is reduced by a latitude-dependent empirical correction scheme correlated to cloud information as well as information on the O3 column. Via these improvements, the combined statistical and systematic uncertainties in the resulting BrO vertical column density is on the order of 7×1012moleculescm-2. We present a new and accurate retrieval algorithm of BrO columns from TROPOMI observations which allows for the detection of even slightly enhanced BrO amounts inside minor eruptive plumes of bromine-rich volcanoes. While designed specifically for TROPOMI observations, the retrieval algorithm is in general also applicable to other hyperspectral satellite observations. However, some parts might require adaptation. [ABSTRACT FROM AUTHOR]

Bromine monoxide (BrO) is a key radical in the atmosphere, influencing the chemical state of the atmosphere, most notably the abundance of ozone. The main effect of BrO onto tropospheric ozone concentrations occurs in bromine release events in polar regions, salt pans and volcanic plumes. Ozone depletion caused by halogen release has been observed and modeled for such conditions, in particular inside volcanic plumes. Furthermore, the molar bromine to sulphur ratio in volcanic plumes is a proxy for the magmatic composition of a volcano and potentially an eruption forecast parameter. The integrated column of BrO in the atmosphere, which in turn serves as an estimate for the bromine content, can be detected simultaneously with SO2 via spectroscopic measurements using the Differential Optical Absorption Spectroscopy (DOAS). Thus, a direct derivation of the BrO/SO2 ratio can be performed from a single measurement. Satellite spectroscopic observations offer the potential to observe and monitor volcanic bromine release globally. The detection of BrO in volcanic plumes is limited by the precision and sensitivity of the retrieval, which so far only allowed for the detection of BrO during major eruptions, leading to a potential sampling bias when looking at the BrO/SO2 ratio. The The TROPospheric Monitoring Instrument (TROPOMI) onboard Sentinel-5 Precursor (S-5P) however, with its unprecedented spatial resolution of up to 3.5 × 5.5 km2 and high signal-to-noise ratio, enables the detection of BrO in minor eruptions or even quiescent degassing. In this study, we investigate, how far the BrO retrieval can be improved using TROPOMI data and how well BrO can be detected, even in small eruptions and during quiescent volcanic degassing. There are two steps, for which improvements in accuracy are investigated and applied: the improvement and quantitative determination of (1) the detection limit of the DOAS BrO column retrieval and (2) the correction of non-volcanic background BrO signal. First, the DOAS retrieval settings are varied and their influence on accuracy and precision is investigated with respect to the detection limit and potential systematic influences. Based on these results, we propose a dedicated DOAS evaluation scheme optimized for the detection of BrO in volcanic plumes. For the DOAS retrieval, we propose the use of a large fit window from 323–360 nm, yielding a factor of 1.8 lower statistical uncertainty compared to previous BrO DOAS algorithms, while not enhancing systematic influences. Second, the effect of the background BrO is reduced by a latitude dependent empirical correction scheme correlated to cloud information as well as information on the ozone column. Via these improvements, the combined statistical and systematic uncertainties of the resulting BrO vertical column density is in the order of 7 × 1012 molecules cm−2, which allows for the detection of even slightly enhanced BrO amounts inside minor eruptive plumes of bromine-rich volcanoes. [ABSTRACT FROM AUTHOR]

Clouds have a strong impact on satellite measurements of tropospheric trace gases in the ultraviolet, visible, and near-infrared spectral ranges from space. Therefore, trace gas retrievals rely on information on cloud fraction, cloud albedo, and cloud height from cloud products. In this study, the cloud parameters from different cloud retrieval algorithms for the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) are compared: the Optical Cloud Recognition Algorithm (OCRA) a priori cloud fraction, the Retrieval Of Cloud Information using Neural Networks (ROCINN) CAL (Clouds-As-Layers) cloud fraction and cloud top and base height, the ROCINN CRB (Clouds-as-Reflecting-Boundaries) cloud fraction and cloud height, the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) cloud fraction, the interpolated FRESCO cloud height from the TROPOMI NO 2 product, the cloud fraction from the NO 2 fitting window, the O 2 –O 2 cloud fraction and cloud height, the Mainz Iterative Cloud Retrieval Utilities (MICRU) cloud fraction, and the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud fraction. Two different versions of the TROPOMI cloud products OCRA/ROCINN, FRESCO, and the TROPOMI NO 2 product are included in the comparisons (processor version 1.x and 2.x). Overall, the cloud parameters retrieved by the different algorithms show qualitative consistency in version 1.x and good agreement in version 2.x with the exception of the VIIRS cloud fraction, which cannot be directly compared to the other data. Differences between the cloud retrievals are found especially for small cloud heights with a cloud fraction threshold of 0.2, i.e. clouds that are particularly relevant for tropospheric trace gas retrievals. The cloud fractions of the different version 2 cloud products primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters show some systematic problems related to the across-track dependence, where larger values are found at the edges of the satellite view. The consistency between the cloud parameters from different algorithms depends strongly on how the data are filtered for the comparison, for example, what quality value is used or whether snow- and ice-covered pixels are excluded from the analysis. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data. [ABSTRACT FROM AUTHOR]

Clouds have a strong impact on satellite measurements of tropospheric trace gases in the ultraviolet, visible, and near-infrared spectral ranges from space. Therefore, trace gas retrievals rely on information on cloud fraction, cloud albedo, and cloud height from cloud products. In this study, the cloud parameters from different cloud retrieval algorithms for Sentinel-5 Precursor (S5P) TROPOMI are compared: the OCRA a priori cloud fraction, the ROCINN CAL cloud fraction and cloud top and base height, the ROCINN CRB cloud fraction and cloud height, the FRESCO cloud fraction, the interpolated FRESCO cloud height from the TROPOMI NO2 product, the cloud fraction from the NO2 fitting window, the O2-O2 cloud fraction and cloud height, the MICRU cloud fraction, and the VIIRS cloud fraction. Two different versions of the TROPOMI cloud products OCRA/ROCINN, FRESCO, and the TROPOMI NO2 product are included in the comparisons (processor version 1.x and 2.x). Overall, the cloud parameters retrieved by the different algorithms show qualitative consistency in version 1.x and good agreement in version 2.x with the exception of the VIIRS cloud fraction, which cannot be directly compared to the other data. Differences between the cloud retrievals are found especially for small cloud heights with a cloud fraction threshold of 0.2, i.e., clouds that are particularly relevant for tropospheric trace gas retrievals. The cloud fractions of the different version 2 cloud products primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters show some systematic problems related to the across-track dependence, where larger values are found at the edges of the satellite view. The consistency between the cloud parameters from different algorithms depends strongly on how the data is filtered for the comparison, e.g., what quality value is used or whether snow and ice-covered pixels are excluded from the analysis. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data. [ABSTRACT FROM AUTHOR]

Clouds impact the radiative transfer of the Earth's atmosphere and strongly influence satellite measurements in the ultraviolet–visible (UV–vis) and infrared (IR) spectral ranges. For satellite measurements of trace gases absorbing in the UV–vis spectral range, particularly clouds ultimately determine the vertical sensitivity profile, mainly by reducing the sensitivity for trace-gas columns below the cloud. The Mainz iterative cloud retrieval utilities (MICRU) algorithm is specifically designed to reduce the error budget of trace-gas retrievals, such as those for nitrogen dioxide (NO2), which strongly depends on the accuracy of small cloud fractions (CFs) in particular. The accuracy of MICRU is governed by an empirical parameterisation of the viewing-geometry-dependent background surface reflectivity taking instrumental and physical effects into account. Instrumental effects are mainly degradation and polarisation effects; physical effects are due to the anisotropy of the surface reflectivity, e.g. shadowing of plants and sun glitter. MICRU is applied to main science channel (MSC) and polarisation measurement device (PMD) data collected between April 2007 and June 2013 by the Global Ozone Monitoring Experiment 2A (GOME-2A) instrument aboard the MetOp-A satellite. CFs are retrieved at different spectral bands between 374 and 758 nm. The MICRU results for MSC and PMD at different wavelengths are intercompared to study CF precision and accuracy, which depend on wavelength and spatial correlation. Furthermore, MICRU results are compared to FRESCO (fast retrieval scheme for clouds from the oxygen A band) and OCRA (optical cloud recognition algorithm) operational cloud products. We show that MICRU retrieves small CFs with an accuracy of 0.04 or better for the entire 1920 km wide swath with a potential bias between - 0.01 and - 0.03. CFs retrieved at shorter wavelengths are less affected by adverse surface heterogeneities. The comparison to the operational CF algorithms shows that MICRU significantly reduces the dependence on viewing angle, time, and sun glitter. Systematic effects along coasts are particularly small for MICRU due to its dedicated treatment of land and ocean surfaces. The MICRU algorithm is designed for spectroscopic instruments ranging from the GOME to Sentinel-5P/Tropospheric Monitoring Instrument (TROPOMI) but is also applicable to UV–vis imagers like the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and Sentinel-2. [ABSTRACT FROM AUTHOR]

Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on the open-source software package Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For this purpose, the MOZART (Model for Ozone and Related chemical Tracers)–MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) chemical reaction mechanism is extended by bromine and chlorine reactions as well as an emission mechanism for reactive bromine via heterogeneous reactions on snow surfaces. The simulation domain covers an area of 5040km×4960km , centered north of Utqiaġvik (formerly Barrow), Alaska, and the time interval from February through May 2009. Several simulations for different strengths of the bromine emission are conducted and evaluated by comparison with in situ and ozone sonde measurements of ozone mixing ratios as well as by comparison with tropospheric BrO vertical column densities (VCDs) from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instrument. The base bromine emission scheme includes the direct emission of bromine due to bromide oxidation by ozone. Results of simulations with the base emission rate agree well with the observations; however, a simulation with 50 % faster emissions performs somewhat better. The bromine emission due to bromide oxidation by ozone is found to be important to provide an initial seed for the bromine explosion. Bromine release due to N2O5 was found to be important from February to mid March but irrelevant thereafter. A comparison of modeled BrO with in situ and multi-axis differential optical absorption spectroscopy (MAX-DOAS) data hints at missing bromine release and recycling mechanisms on land or near coasts. A consideration of halogen chemistry substantially improves the prediction of the ozone mixing ratio with respect to the observations. Meteorological nudging is essential for a good prediction of ODEs over the 3-month period. [ABSTRACT FROM AUTHOR]

Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using the regional software WRF-Chem. For this purpose, the MOZART-MOSAIC chemical reaction mechanism is extended by bromine and chlorine reactions as well as an emission mechanism for reactive bromine via heterogeneous reactions on ice and snow surfaces. The simulation domain covers an area of 5,040 km x 4,960 km, centered north of Utqiagvik (formerly Barrow), Alaska, and the time interval from February through May, 2009. Several simulations for different strengths of the bromine emission are conducted and evaluated by comparison with in-situ and ozone-sonde measurements of ozone mixing ratios as well as by comparison with tropospheric BrO vertical column densities (VCDs) from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instrument. The base bromine emission scheme includes the direct emission of bromine due to bromide oxidation by ozone through the reactive surface ratio β of the ice/snow surface relative to a flat surface. 10 Results of simulations with β = 1.0 agree well with the observations, however, a value of 1.5 performs somewhat better. The bromine emission due to bromide oxidation by ozone is found to be important to provide an initial seed for the bromine explosion. Consideration of halogen chemistry substantially improves the prediction of the ozone mixing ratio with respect to the observations. Meteorological nudging is found to be essential for a good prediction of ODEs over the three months period. [ABSTRACT FROM AUTHOR]

Clouds impact the radiative transfer of the Earth's atmosphere and strongly influence satellite measurements in the UV visible and IR spectral ranges. For satellite measurements of trace gases absorbing in the UV/vis spectral range, particularly clouds ultimately determine the vertical sensitivity profile, mainly by reducing the sensitivity for trace gas columns below the cloud. The Mainz Iterative Cloud Retrieval Utilities (MICRU) algorithm is specifically designed to reduce the error budget of trace gas retrievals, such as those for nitrogen dioxide (NO2), which strongly depends on the accuracy of small cloud fractions (CF) in particular. The accuracy of MICRU is governed by an empirical parametrisation of the viewing geometry dependent background surface reflectivity taking instrumental and physical effects into account. Instrumental effects are mainly degradation and polarisation effects, physical effects are due to the anisotropy of the surface reflectivity, e.g. shadowing of plants and sun glitter. MICRU is applied to main science channel (MSC) and polarisation measuring device (PMD) data collected between April 2007 and June 2013 by the GOME-2A instrument onboard the MetOp-A satellite. CF are retrieved at different spectral bands between 374 and 758 nm. The MICRU results for MSC and PMD at different wavelengths are inter-compared to study CF precision and accuracy, which depend on wavelength and spatial correlation. Furthermore, MICRU results are compared to FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A band) and OCRA (Optical Cloud Recognition Algorithm) operational cloud products. We show that MICRU retrieves small CF with an accuracy of 0.04 or better for the entire 1920 km wide swath with a potential bias between -0.01 and -0.03. CF retrieved at shorter wavelengths are less affected by adverse surface heterogeneities. The comparison to the operational CF algorithms shows that MICRU significantly reduces the dependence on viewing angle, time, and sun glitter. Systematic effects along coasts are particularly small for MICRU due to its dedicated treatment of land and ocean surfaces. The MICRU algorithm is designed for spectroscopic instruments ranging from the GOME to TROPOMI/Sentinel-5P, but is also applicable to UV/vis imagers like, for example, AVHRR, MODIS, VIIRS, and Sentinel-2. [ABSTRACT FROM AUTHOR]

Total column water vapour has been retrieved from TROPOMI measurements in the visible blue spectral range and compared to a variety of different reference data sets for clear-sky conditions during boreal summer and winter. The retrieval consists of the common two-step DOAS approach: first the spectral analysis is performed within a linearized scheme and then the retrieved slant column densities are converted to vertical columns using an iterative scheme for the water vapour a priori profile shape, which is based on an empirical parameterization of the water vapour scale height. Moreover, a modified albedo map was used combining the OMI LER albedo and scaled MODIS albedo map. The use of the alternative albedo is especially important over regions with very low albedo and high probability of clouds like the Amazon region. The errors of the total column water vapour (TCWV) retrieval have been theoretically estimated considering the contribution of a variety of different uncertainty sources. For observations during clear-sky conditions, over ocean surface, and at low solar zenith angles the error typically is around values of 10 %–20 %, and during cloudy-sky conditions, over land surface, and at high solar zenith angles it reaches values around 20 %–50 %. In the framework of a validation study the retrieval demonstrates that it can well capture the global water vapour distribution: the retrieved H2O vertical column densities (VCDs) show very good agreement with the reference data sets over ocean for boreal summer and winter whereby the modified albedo map substantially improves the retrieval's consistency to the reference data sets, in particular over tropical land masses. However, over land the retrieval underestimates the VCD by about 10 %, particularly during summertime. Our investigations show that this underestimation is likely caused by uncertainties within the surface albedo and the cloud input data: low-level clouds cause an underestimation, but for mid- to high-level clouds good agreement is found. In addition, our investigations indicate that these biases can probably be further reduced by the use of improved cloud input data. For the general purpose we recommend only using VCDs with cloud fraction <20% and AMF >0.1 , which represents a good compromise between spatial coverage and retrieval accuracy. The TCWV retrieval can be easily applied to further satellite sensors (e.g. GOME-2 or OMI) for creating uniform, long-term measurement data sets, which is particularly interesting for climate and trend studies of water vapour. [ABSTRACT FROM AUTHOR]

Total column water vapour has been retrieved from TROPOMI measurements in the visible blue spectral range and compared to a variety of different reference data sets for clear-sky conditions during boreal summer and winter. The retrieval consists of the common two-step DOAS approach: first the spectral analysis is performed within a linearized scheme and then the retrieved slant column densities are converted to vertical columns using an iterative scheme for the water vapour a priori profile shape which is based on an empirical parameterization of the water vapour scale height. Moreover, a modified albedo map was used combining the OMI LER albedo and scaled MODIS albedo map. The use of the alternative albedo is especially important over regions with very low albedo and high probability of clouds like the Amazon region. The errors of the TCWV retrieval have been theoretically estimated considering the contribution of a variety of different uncertainty sources. For observations during clear-sky conditions, over ocean surface, and at low solar zenith angles the error typically is around values of 10-20 % and during cloudy-sky conditions, over land surface, and at high solar zenith angles it reaches values around 20-50 %. In the framework of a validation study the retrieval demonstrates that it can well capture the global water vapour distribution: the retrieved H2O VCDs show very good agreement to the reference data sets over ocean for boreal summer and winter whereby the modified albedo map substantially improves the retrieval's consistency to the reference data sets in particular over tropical landmasses. However over land the retrieval underestimates the VCD by about 10 %, particularly during summertime. Our investigations show that this underestimation is likely caused by uncertainties within the surface albedo and the cloud input data: Low level clouds cause an underestimation but for mid to high level clouds good agreement is found. In addition, our investigations indicate that these biases can probably be further reduced by the use of updated cloud input data. The TCWV retrieval can be easily applied to further satellite sensors (e.g. GOME-2 or OMI) for creating uniform measurement data sets on longterm which is particularly interesting for climate and trend studies of water vapour. [ABSTRACT FROM AUTHOR]

This paper presents a numerical study of the oscillations (or recurrences) of tropospheric ozone depletion events (ODEs) using the further-developed one-dimensional KInetic aNALysis of reaction mechanics with Transport (KINAL-T) chemistry transport model. Reactive bromine is the major contributor to the occurrence of ODEs. After the termination of an ODE, the reactive bromine in the air is deposited onto aerosols or on the snow surface, and the ozone may regenerate via NOx -catalyzed photochemistry or by turbulent transport from the free troposphere into the boundary layer. The replenished ozone then is available for the next cycle of autocatalytic bromine release (bromine explosion) leading to another ODE. The oscillation periods are found to be as short as 5 d for the purely chemically NOx -driven oscillation and 30 d for a diffusion-driven oscillation. An important requirement for oscillation of ODEs to occur is found to be a sufficiently strong inversion layer. In a parameter study, the dependence of the oscillation period on the nitrogen oxides' concentration, the inversion layer strength, the ambient temperature, the aerosol density, and the solar radiation is investigated. Parameters controlling the oscillation of ODEs are discussed. [ABSTRACT FROM AUTHOR]

Abstract. This paper presents a numerical study of the recurrences (or oscillations) of tropospheric ozone depletion events, ODEs, using the further developed one-dimensional chemistry transport model KINAL-T. Reactive bromine is the major contributor to the occurrence of ODEs. After the termination of an ODE, the reactive bromine in the air is deposited onto aerosols or on the snow surface, and the ozone may regenerate via NOx-catalyzed photochemistry or by turbulent transport from the free troposphere into the boundary layer. The replenished ozone then is available for the next cycle of autocatalytic bromine release (bromine explosion) leading to another ODE. The recurrence periods are found to be as low as five days for the purely chemically NOx-driven oscillation and 30 days for a diffusion-driven recurrence. An important requirement for recurrences of ODEs to occur is found to be a sufficiently strong inversion layer. In a parameter study, the dependence of the recurrence period on the nitrogen oxides concentration, the inversion layer strength, the ambient temperature, the aerosol density, and the solar radiation is investigated. Parameters controlling the recurrence of ODEs are discussed. [ABSTRACT FROM AUTHOR]

Experience of differential atmospheric absorption spectroscopy (DOAS) shows that a spectral shift between measurement spectra and reference spectra is frequently required in order to achieve optimal fit results, while the straightforward calculation of the optical density proves inferior. The shift is often attributed to temporal instabilities of the instrument but implicitly solved the problem of the tilt effect discussed/explained in this paper. Spectral positions of Fraunhofer and molecular absorption lines are systematically shifted for different measurement geometries due to an overall slope - or tilt - of the intensity spectrum. The phenomenon has become known as the tilt effect for limb satellite observations, where it is corrected for in a first-order approximation, whereas the remaining community is less aware of its cause and consequences. It is caused by the measurement process, because atmospheric absorption and convolution in the spectrometer do not commute. Highly resolved spectral structures in the spectrum will first be modified by absorption and scattering processes in the atmosphere before they are recorded with a spectrometer, which convolves them with a specific instrument function. In the DOAS spectral evaluation process, however, the polynomial (or other function used for this purpose) accounting for broadband absorption is applied after the convolution is performed. In this paper, we derive that changing the order of the two modifications of the spectra leads to different results. Assuming typical geometries for the observations of scattered sunlight and a spectral resolution of 0.6 nm, this effect can be interpreted as a spectral shift of up to 1.5 pm, which is confirmed in the actual analysis of the ground-based measurements of scattered sunlight as well as in numerical radiative transfer simulations. If no spectral shift is allowed by the fitting routine, residual structures of up to 2.5×10-3 peak-topeak are observed. Thus, this effect needs to be considered for DOAS applications aiming at an rms of the residual of 100-3 and below. [ABSTRACT FROM AUTHOR]

Ultraviolet (UV) SO2 cameras have become a common tool to measure and monitor SO2 emission rates, mostly from volcanoes but also from anthropogenic sources (e.g., power plants or ships). Over the past decade, the analysis of UV SO2 camera data has seen many improvements. As a result, for many of the required analysis steps, several alternatives exist today (e.g., cell vs. DOAS based camera calibration; optical flow vs. cross-correlation based gas-velocity retrieval). This inspired the development of Pyplis (Python plume imaging software), an open-source software toolbox written in Python 2.7, which unifies the most prevalent methods from literature within a single, cross-platform analysis framework. Pyplis comprises a vast collection of algorithms relevant for the analysis of UV SO2 camera data. These include several routines to retrieve plume background radiances as well as routines for cell and DOAS based camera calibration. The latter includes two independent methods to identify the DOAS field-of-view (FOV) within the camera images (based on (1) Pearson correlation and (2) IFR inversion method). Plume velocities can be retrieved using an optical flow algorithm as well as signal cross-correlation. Furthermore, Pyplis includes a routine to perform a first order correction of the signal dilution effect (also referred to as light dilution). All required geometrical calculations are performed within a 3D model environment allowing for distance retrievals to plume and local terrain features on a pixel basis. SO2 emission rates can be retrieved simultaneously for an arbitrary number of plume intersections. Hence, Pyplis provides a state-of-the-art framework for more efficient and flexible analyses of UV SO2 camera data and, therefore, marks an important step forward towards more transparency, reliability and inter-comparability of the results. Pyplis has been extensively and successfully tested using data from several field campaigns. Here, the main features are introduced using a dataset obtained at Mt. Etna, Italy on 16 September 2015. [ABSTRACT FROM AUTHOR]

Heterogeneous photochemistry converts bromide (Br-) to reactive bromine species (Br atoms and bromine monoxide, BrO) that dominate Arctic springtime chemistry. This phenomenon has many impacts such as boundary-layer ozone depletion, mercury oxidation and deposition, and modification of the fate of hydrocarbon species. To study environmental controls on reactive bromine events, the B Romine, Ozone, and Mercury EXperiment (BROMEX) was carried out from early March to mid-April 2012 near Barrow (Utqiaġvik), Alaska. We measured horizontal and vertical gradients in BrO with multiple-axis differential optical absorption spectroscopy (MAX-DOAS) instrumentation at three sites, two mobile and one fixed. During the campaign, a large crack in the sea ice (an open lead) formed pushing one instrument package ~250 km downwind from Barrow (Utqiaġvik). Convection associated with the open lead converted the BrO vertical structure from a surface-based event to a lofted event downwind of the lead in?uence. The column abundance of BrO downwind of the refreezing lead was comparable to upwind amounts, indicating direct reactions on frost ?owers or open seawater was not a major reactive bromine source. When these three sites were separated by ~30 km length scales of unbroken sea ice, the BrO amount and vertical distributions were highly correlated for most of the time, indicating the horizontal length scales of BrO events were typically larger than ~30 km in the absence of sea ice features. Although BrO amount and vertical distribution were similar between sites most of the time, rapid changes in BrO with edges significantly smaller than this 30 km length scale episodically transported between the sites, indicating BrO events were large but with sharp edge contrasts. BrO was often found in shallow layers that recycled reactive bromine via heterogeneous reactions on snowpack. Episodically, these surface-based events propagated aloft when aerosol extinction was higher (> 0.1 km-1/; however, the presence of aerosol particles aloft was not sufficient to produce BrO aloft. Highly depleted ozone (< 1 nmol mol-1/ repartitioned reactive bromine away from BrO and drove BrO events aloft in cases. This work demonstrates the interplay between atmospheric mixing and heterogeneous chemistry that affects the vertical structure and horizontal extent of reactive bromine events. [ABSTRACT FROM AUTHOR]

Experience of differential atmospheric absorption spectroscopy (DOAS) shows that a spectral shift between measurement and reference spectrum is frequently required in order to achieve optimal fit results, while the straight forward calculation of the optical density proves inferior. The shift is often attributed to temporal instabilities of the instrument, but implicitly solved the problem of the "tilt-effect" discussed/explained in this paper. Spectral positions of Fraunhofer and molecular absorption lines are systematically shifted for different measurement geometries due to an overall slope - or "tilt" - of the intensity spectrum. The phenomenon has become known as "tilt effect" for limb satellite observations, where it is corrected for in a first order approximation, whereas the remaining community is less aware of its cause and consequences. It is caused by the measurement process because atmospheric absorption and convolution in the spectrometer do not commute. Highly resolved spectral structures in the spectrum first will be modified by absorption and scattering processes in the atmosphere. before they are recorded with a spectrometer, which convolves it with a specific instrument function. In the DOAS spectral evaluation process, however, the polynomial (or other function used for this purpose) accounting for broadband absorption is applied after the convolution is performed. In this paper, we derive that changing the order of the two modifications of the spectra leads to different results. Assuming typical geometries for the observations of scattered sunlight and a spectral resolution of 0.6 nm, this effect can be interpreted as a spectral shift of up to 1.5 pm, which is confirmed in actual the analysis of the ground based measurements of scattered sunlight as well as in numerical radiative transfer simulations. If no spectral shift is allowed by the fitting routine, residual structures of up to 2.5 × 10-3 peak-to-peak are observed. Thus, this effect needs to be considered for DOAS application aiming at RMS of the residual of 10-3 and below. [ABSTRACT FROM AUTHOR]

The return of sunlight in the polar spring leads to the production of reactive halogen species from the surface snowpack, significantly altering the chemical composition of the Arctic near-surface atmosphere and the fate of long-range transported pollutants, including mercury. Recent work has shown the initial production of reactive bromine at the Arctic surface snowpack; however, we have limited knowledge of the vertical extent of this chemistry, as well as the lifetime and possible transport of reactive bromine aloft. Here, we present bromine monoxide (BrO) and aerosol particle measurements obtained during the March 2012 BRomine Ozone Mercury EXperiment (BROMEX) near Utqiaġvik (Barrow), AK. The airborne differential optical absorption spectroscopy (DOAS) measurements provided an unprecedented level of spatial resolution, over 2 orders of magnitude greater than satellite observations and with vertical resolution unable to be achieved by satellite methods, for BrO in the Arctic. This novel method provided quantitative identification of a BrO plume, between 500m and 1 km aloft, moving at the speed of the air mass. Concurrent aerosol particle measurements suggest that this lofted reactive bromine plume was transported and maintained at elevated levels through heterogeneous reactions on colocated supermicron aerosol particles, independent of surface snowpack bromine chemistry. This chemical transport mechanism explains the large spatial extents often observed for reactive bromine chemistry, which impacts atmospheric composition and pollutant fate across the Arctic region, beyond areas of initial snowpack halogen production. The possibility of BrO enhancements disconnected from the surface potentially contributes to sustaining BrO in the free troposphere and must also be considered in the interpretation of satellite BrO column observations, particularly in the context of the rapidly changing Arctic sea ice and snowpack. [ABSTRACT FROM AUTHOR]

Heterogeneous photochemistry converts bromide (Br-) to reactive bromine species (Br atoms and bromine monoxide, BrO) that dominate Arctic springtime chemistry. This phenomenon has many impacts such as boundary-layer ozone depletion, mercury oxidation and deposition, and modification of the fate of hydrocarbon species. To study environmental controls on reactive bromine events, the BRomine, Ozone, and Mercury EXperiment (BROMEX) was carried out from early March to mid April 2012 near Barrow (Utqiaġvik), Alaska. We measured horizontal and vertical gradients in BrO with Multiple-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrumentation at three sites, two mobile and one fixed. During the campaign, a large crack in the sea ice (an open lead) formed pushing one instrument package ~ 250 km downwind from Barrow (Utqiaġvik). Convection associated with the open lead converted the BrO vertical structure from a surface-based event to a lofted event downwind of the lead influence. The column abundance of BrO downwind of the re-freezing lead was comparable to upwind amounts indicating direct reactions on frost flowers or open seawater was not a major reactive bromine source. When these three sites were separated by ~ 30 km length scales of unbroken sea ice, the BrO amount and vertical distributions were highly correlated for most of the time, indicating the horizontal length scales of BrO events were typically larger than ~ 30 km in the absence of sea-ice features. Although correlation dominated most of the time, rapid changes in BrO with edges significantly sharper than this ~ 30 km length scale episodically transported between the sites, indicating BrO events were large but with sharp edge contrasts. BrO was often found in shallow layers that recycled reactive bromine via heterogeneous reactions on snowpack. Episodically, these surface-based events propagated aloft, which required enhanced aerosol extinction aloft; however, the presence of aerosol particles aloft was not sufficient to produce BrO aloft. Highly depleted ozone (< 1 nmol mol-1) repartitioned reactive bromine away from BrO and drove BrO events aloft in cases. This work demonstrates the interplay between atmospheric mixing and heterogeneous chemistry that affects the vertical structure and horizontal extent of reactive bromine events. [ABSTRACT FROM AUTHOR]

Knowledge of the field of view (FOV) of a remote sensing instrument is particularly important when interpreting their data and merging them with other spatially referenced data. Especially for instruments in space, information on the actual FOV, which may change during operation, may be difficult to obtain. Also, the FOV of ground-based devices may change during transportation to the field site, where appropriate equipment for the FOV determination may be unavailable. This paper presents an independent, simple and robust method to retrieve the FOV of an instrument during operation, i.e. the two-dimensional sensitivity distribution, sampled on a discrete grid. The method relies on correlated measurements featuring a significantly higher spatial resolution, e.g. by an imaging instrument accompanying a spectrometer. The method was applied to two satellite instruments, GOME-2 and OMI, and a ground-based differential optical absorption spectroscopy (DOAS) instrument integrated in an SO2 camera. For GOME-2, quadrangular FOVs could be retrieved, which almost perfectly match the provided FOV edges after applying a correction for spatial aliasing inherent to GOME-type instruments. More complex sensitivity distributions were found at certain scanner angles, which are probably caused by degradation of the moving parts within the instrument. For OMI, which does not feature any moving parts, retrieved sensitivity distributions were much smoother compared to GOME-2. A 2-D super-Gaussian with six parameters was found to be an appropriate model to describe the retrieved OMI FOV. The comparison with operationally provided FOV dimensions revealed small differences, which could be mostly explained by the limitations of our IFR implementation. For the ground-based DOAS instrument, the FOV retrieved using SO2-camera data was slightly smaller than the flat-disc distribution, which is assumed by the state-of-the-art correlation technique. Differences between both methods may be attributed to spatial inhomogeneities. In general, our results confirm the already deduced FOV distributions of OMI, GOME-2, and the ground-based DOAS. It is certainly applicable for degradation monitoring and verification exercises. For satellite instruments, the gained information is expected to increase the accuracy of combined products, where measurements of different instruments are integrated, e.g. mapping of high-resolution cloud information, incorporation of surface climatologies. For the SO2-camera community, the method presents a new and efficient tool to monitor the DOAS FOV in the field. [ABSTRACT FROM AUTHOR]

The return of sunlight in the polar spring leads to production of reactive halogen species from the surface snowpack, significantly altering the chemical composition of the Arctic near-surface atmosphere and the fate of long-range transported pollutants, including mercury. Recent work has shown the initial production of reactive bromine at the Arctic surface snowpack; however, we have limited knowledge of the vertical extent of this chemistry, as well as the lifetime and possible transport of reactive bromine aloft. Here, we present bromine monoxide (BrO) and aerosol particle measurements obtained during the March 2012 BRomine Ozone Mercury EXperiment (BROMEX) near Utqiagvik (Barrow), AK. The airborne differential optical absorption spectroscopy (DOAS) measurements provided an unprecedented level of spatial resolution, over two orders of magnitude greater than satellite observations and with vertical resolution unable to be achieved by satellite methods, for BrO in the Arctic. This novel method provided quantitative identification of a BrO plume, disconnected from the surface, moving at the speed of the air mass. This lofted reactive bromine plume was transported and maintained at elevated levels through heterogeneous reactions on co-located supermicron aerosol particles, independently of surface snowpack bromine chemistry. This chemical transport mechanism significantly increases the spatial extent of this reactive bromine chemistry, impacting atmospheric composition and pollutant fate across the region, beyond the area of initial snowpack halogen production. This process must be considered in the interpretation of satellite BrO observations and examined in the context of the rapidly changing Arctic sea ice and snowpack. [ABSTRACT FROM AUTHOR]

The instrumental spectral response function (ISRF) is a key quantity in DOAS analysis, as it is needed for wavelength calibration and for the convolution of trace gas cross sections to instrumental resolution. While it can generally be measured using monochromatic stimuli, it is often parameterized in order to merge different calibration measurements and to plainly account for its wavelength dependency. For some instruments, the ISRF can be described appropriately by a Gaussian function, while for others, dedicated, complex parameterizations with several parameters have been developed. Here we propose to parameterize the ISRF as a "super- Gaussian", which can reproduce a variety of shapes, from point-hat to boxcar shape, by just adding one parameter to the "classical" Gaussian. The super-Gaussian turned out to describe the ISRF of various DOAS instruments well, including the satellite instruments GOME-2, OMI, and TROPOMI. In addition, the super-Gaussian allows for a straightforward parameterization of the effect of ISRF changes, which can occur on long-term scales as well as, for example, during one satellite orbit and impair the spectral analysis if ignored. In order to account for such changes, spectral structures are derived from the derivatives of the super-Gaussian, which are afterwards just scaled during spectral calibration or DOAS analysis. This approach significantly improves the fit quality compared to setups with fixed ISRF, without drawbacks on computation time due to the applied linearization. In addition, the wavelength dependency of the ISRF can be accounted for by accordingly derived spectral structures in an easy, fast, and robust way. [ABSTRACT FROM AUTHOR]

The Rann of Kutch (India and Pakistan) is one of the largest salt deserts in the world. Being a so-called "seasonal salt marsh", it is regularly flooded during the Indian summer monsoon.We present 10 years of bromine monoxide (BrO) satellite observations by the Ozone Monitoring Instrument (OMI) over the Great and Little Rann of Kutch. OMI spectra were analysed using Differential Optical Absorption Spectroscopy (DOAS) and revealed recurring high BrO vertical column densities (VCDs) of up to 1.4 x 1014 molec cm-2 during April/May, but no significantly enhanced column densities during the monsoon season (June-September). In the following winter months, the BrO VCDs are again slightly enhanced while the salty surface dries up. We investigate a possible correlation of enhanced reactive bromine concentrations with different meteorological parameters and find a strong relationship between incident UV radiation and the total BrO abundance. In contrast, the second Global Ozone Monitoring Instrument (GOME-2) shows about 4 times lower BrO VCDs over the Rann of Kutch than found by OMI and no clear seasonal cycle is observed. One reason for this finding might be the earlier local overpass time of GOME-2 compared to OMI (around 09:30 vs. 13:30 LT), as the ambient conditions significantly differ for both satellite instruments at the time of the measurements. Further possible reasons are discussed and mainly attributed to instrumental issues. OMI additionally confirms the presence of enhanced BrO concentrations over the Dead Sea valley (Israel/Jordan), as suggested by former ground-based observations. The measurements indicate that the Rann of Kutch salt marsh is probably one of the strongest natural point sources of reactive bromine compounds outside the polar regions and is therefore supposed to have a significant impact on local and regional ozone chemistry [ABSTRACT FROM AUTHOR]

The instrumental spectral response function (ISRF) is a key quantity in DOAS analysis, as it is needed for wavelength calibration and for the convolution of trace gas cross-sections to instrumental resolution. While it can generally be measured using monochromatic stimuli, it is often parameterized in order to merge different calibration measurements and to plainly account for its wavelength dependency. For some instruments, the ISRF can be described appropriately by a Gaussian function, while for others, dedicated, complex parameterizations with several parameters have been developed. Here we propose to parameterize the ISRF as a "Super Gaussian", which can reproduce a variety of shapes, from point-hat to boxcar shape, by just adding one parameter to the "classical" Gaussian. The Super Gaussian turned out to describe the ISRF of various DOAS instruments well, including the satellite instruments GOME-2, OMI, and TROPOMI. In addition, the Super Gaussian allows for a straightforward parametrization of the effect of ISRF changes, which can occur on long-term scales as well as e.g. during one satellite orbit, and impair the spectral analysis if ignored. In order to account for such changes, spectral structures are derived from the derivatives of the Super Gaussian, which are afterwards just scaled during spectral calibration or DOAS analysis. This approach significantly improves the fit quality compared to setups with fixed ISRF, without drawbacks on computation time due to the applied linearization. In addition, the wavelength dependency of the ISRF can be accounted for by accordingly derived spectral structures in an easy, fast, and robust way. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Instrument (OMI) is a push-broom imaging spectrometer, observing solar radiation backscattered by the Earth's atmosphere and surface. The incoming radiation is detected using a static imaging CCD (charge-coupled device) detector array with no moving parts, as opposed to most of the previous satellite spectrometers, which used a moving mirror to scan the Earth in the acrosstrack direction. The field of view (FoV) of detector pixels is the solid angle from which radiation is observed, averaged over the integration time of a measurement. The OMI FoV is not quadrangular, which is common for scanning instruments, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels. This has consequences for pixel-area-dependent applications, like cloud fraction products, and visualisation. The shapes and sizes of OMI FoVs were determined preflight by theoretical and experimental tests but never verified after launch. In this paper the OMI FoV is characterised using collocated MODerate resolution Imaging Spectroradiometer (MODIS) reflectance measurements. MODIS measurements have a much higher spatial resolution than OMI measurements and spectrally overlap at 469 nm. The OMI FoV was verified by finding the highest correlation between MODIS and OMI reflectances in cloud-free scenes, assuming a 2-D super-Gaussian function with varying size and shape to represent the OMI FoV. Our results show that the OMPIXCOR product 75FoV corner coordinates are accurate as the full width at half maximum (FWHM) of a super-Gaussian FoV model when this function is assumed. The softness of the function edges, modelled by the super-Gaussian exponents, is different in both directions and is view angle dependent. The optimal overlap function between OMI and MODIS reflectances is scene dependent and highly dependent on time differences between overpasses, especially with clouds in the scene. For partially clouded scenes, the optimal overlap function was represented by super-Gaussian exponents around 1 or smaller, which indicates that this function is unsuitable to represent the overlap sensitivity function in these cases. This was especially true for scenes before 2008, when the time differences between Aqua and Aura overpasses was about 15 min, instead of 8 min after 2008. During the time between overpasses, clouds change the scene reflectance, reducing the correlation and influencing the shape of the optimal overlap function. [ABSTRACT FROM AUTHOR]

Knowledge of the field of view (FOV) of a remote sensing instrument is particularly important when interpreting their data and merging them with other spatially referenced data. Especially for instruments in space, information on the actual FOV, which may change during operation, may be difficult to obtain. Also, the FOV of ground-based devices may change during transportation to the field site, where appropriate equipment is absent.

This paper presents an independent, simple and robust method to retrieve FOV of an instrument during operation, i. e. the two-dimensional sensitivity distribution, sampled on a discrete grid. The method relies on correlated measurements featuring a significantly higher spatial resolution, e. g. by an imaging instrument accompanying a spectrometer. The method was applied to two satellite instruments, GOME-2 and OMI, and a ground-based differential optical absorption spectroscopy (DOAS) instrument integrated in an SO2-camera. For GOME-2, quadrangular FOVs could be retrieved, which almost perfectly match the provided FOV edges after applying a correction for spatial aliasing inherent to GOME-type instruments. More complex sensitivity distributions were found at certain scanner angles, which are probably caused by degradation of the moving parts within the instrument. For OMI, which does not feature any moving parts, retrieved sensitivity distributions were much smoother compared to GOME-2. A 2D super-Gaussian with six parameters was found to be an appropriate model to describe the retrieved OMI FOV. The comparison with operationally provided FOV dimensions revealed small differences, which could be mostly explained by the limitations of our retrieval. For the ground-based DOAS instrument, the FOV retrieved using SO2-camera data was slightly smaller than the flat-disc distribution, which is assumed by commonly used correlation technique. Differences between both methods may be attributed to spatial inhomogeneities.

In general, our results confirm the already deduced FOV distributions of OMI, GOME-2 and the ground-based DOAS. It is certainly applicable for degradation monitoring and verification exercises. For satellite instruments, the gained information is expected to increase the accuracy of combined products, where measurements of different instruments are integrated, e. g. mapping of high-resolution cloud information, incorporation of surface climatologies. For the SO2-camera community, the method presents a new and efficient tool to monitor the DOAS FOV in the field. [ABSTRACT FROM AUTHOR]

We present a top-down approach to infer and quantify rain-induced emission pulses of NOx (≡NO+NO2), stemming from biotic emissions of NO from soils, from satellite-borne measurements of NO2. This is achieved by synchronizing time series at single grid pixels according to the first day of rain after a dry spell of prescribed duration. The full track of the temporal evolution several weeks before and after a rain pulse is retained with daily resolution. These are needed for a sophisticated background correction, which accounts for seasonal variations in the time series and allows for improved quantification of rain-induced soil emissions. The method is applied globally and provides constraints on pulsed soil emissions of NOx in regions where the NOx budget is seasonally dominated by soil emissions. We find strong peaks of enhanced NO2 vertical column densities (VCDs) induced by the first intense precipitation after prolonged droughts in many semi-arid regions of the world, in particular in the Sahel. Detailed investigations show that the rain-induced NO2 pulse detected by the OMI (Ozone Monitoring Instrument), GOME-2 and SCIAMACHY satellite instruments could not be explained by other sources, such as biomass burning or lightning, or by retrieval artefacts (e.g. due to clouds). For the Sahel region, absolute enhancements of the NO2 VCDs on the first day of rain based on OMI measurements 2007-2010 are on average 4×1014 moleccm-2 and exceed 1×1015 moleccm-2 for individual grid cells. Assuming a NOx lifetime of 4 h, this corresponds to soil NOx emissions in the range of 6 up to 65 ngNm-2 s-1, which is in good agreement with literature values. Apart from the clear first-day peak, NO2 VCDs are moderately enhanced (2×1014 moleccm-2) compared to the background over the following 2 weeks, suggesting potential further emissions during that period of about 3.3 ngNm-2 s-1. The pulsed emissions contribute about 21-44% to total soil NOx emissions over the Sahel. [ABSTRACT FROM AUTHOR]

The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2  which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1–0.2 × 1015 molecules cm−2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study. [ABSTRACT FROM AUTHOR]