Search

Accurate modeling of ash clouds from volcanic eruptions requires knowledge about the eruption source parameters including eruption onset, duration, mass eruption rates, particle size distribution, and vertical-emission profiles. However, most of these parameters are unknown and must be estimated somehow. Some are estimated based on observed correlations and known volcano parameters. However, a more accurate estimate is often needed to bring the model into closer agreement with observations. This paper describes the inversion procedure implemented at the Norwegian Meteorological Institute for estimating ash emission rates from retrieved satellite ash column amounts and a priori knowledge. The overall procedure consists of five stages: (1) generate a priori emission estimates, (2) run forward simulations with a set of unit emission profiles, (3) collocate/match observations with emission simulations, (4) build system of linear equations, and (5) solve overdetermined systems. We go through the mathematical foundations for the inversion procedure, performance for synthetic cases, and performance for real-world cases. The novelties of this paper include a memory efficient formulation of the inversion problem, a detailed description and illustrations of the mathematical formulations, evaluation of the inversion method using synthetic known-truth data as well as real data, and inclusion of observations of ash cloud-top height. The source code used in this work is freely available under an open-source license and is able to be used for other similar applications.

After the decrease of ozone-depleting substances (ODSs) as a consequence of the Montreal Protocol, it is still challenging to detect a recovery in the total column amount of ozone (total ozone) at northern high latitudes. To assess regional total ozone changes in the “ozone-recovery” period (2000–2020) at northern high latitudes, this study investigates trends from ground-based total ozone measurements at three stations in Norway (Oslo, Andøya, and Ny-Ålesund). For this purpose, we combine measurements from Brewer spectrophotometers, ground-based UV filter radiometers (GUVs), and a SAOZ (Système d'Analyse par Observation Zénithale) instrument. The Brewer measurements have been extended to work under cloudy conditions using the global irradiance (GI) technique, which is also presented in this study. We derive trends from the combined ground-based time series with the multiple linear regression model from the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) project. We evaluate various predictors in the regression model and found that tropopause pressure and lower-stratospheric temperature contribute most to ozone variability at the three stations. We report significantly positive annual trends at Andøya (0.9±0.7 % per decade) and Ny-Ålesund (1.5±0.1 % per decade) and no significant annual trend at Oslo (0.1±0.5 % per decade) but significantly positive trends in autumn at all stations. Finally we found positive but insignificant trends of around 3 % per decade in March at all three stations, which may be an indication of Arctic springtime ozone recovery. Our results contribute to a better understanding of regional total ozone trends at northern high latitudes, which is essential to assess how Arctic ozone responds to changes in ODSs and to climate change.

Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement a simple cloud model based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2–O2) absorption at 477 nm or on the oxygen A-band around 760 nm to determine an effective cloud height. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. Although clouds have significant effects on trace gas retrievals, the current cloud correction schemes are based on a simple cloud model, and the retrieved cloud parameters must be interpreted as effective values. Consequently, it is difficult to assess the accuracy of the cloud correction only based on analysis of the accuracy of the cloud retrievals, and this study focuses solely on the impact of the 3D cloud structures on the trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2–O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows measurements to be identified for which the standard NO2 retrieval produces a significant bias and therefore provides a way to improve the current data flagging approach.

Three-dimensional (3D) cloud structures may impact atmospheric trace gas products from ultraviolet–visible (UV–Vis) sounders. We used synthetic and observational data to identify and quantify possible cloud-related bias in NO2 tropospheric vertical column density (TVCD). The synthetic data were based on high-resolution large eddy simulations which were input to a 3D radiative transfer model. The simulated visible spectra for low-earth-orbiting and geostationary geometries were analysed with standard retrieval methods and cloud correction schemes that are employed in operational NO2 satellite products. For the observational data, the NO2 products from the TROPOspheric Monitoring Instrument (TROPOMI) were used, while the Visible Infrared Imaging Radiometer Suite (VIIRS) provided high-spatial-resolution cloud and radiance data. NO2 profile shape, cloud shadow fraction, cloud top height, cloud optical depth, and solar zenith and viewing angles were identified as the metrics being the most important in identifying 3D cloud impacts on NO2 TVCD retrievals. For a solar zenith angle less than about 40∘ the synthetic data show that the NO2 TVCD bias is typically below 10 %, while for larger solar zenith angles the NO2 TVCD is low-biased by tens of percent. The horizontal variability of NO2 and differences in TROPOMI and VIIRS overpass times make it challenging to identify a similar bias in the observational data. However, for optically thick clouds above 3000 m, a low bias appears to be present in the observational data.

Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data, and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering. In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC (Monte Carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres). The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMFs) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos. Two cloud setups are considered: the first includes simple box clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical of central Europe such as shallow cumulus, convective cloud cells, cirrus and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically. Along with the dataset, the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analysed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %. The dataset is available for the scientific community to assess the behaviour of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.

In early October 2020, northern Europe experienced an episode with poor air quality due to high concentrations of particulate matter (PM). At several sites in Norway, recorded weekly values exceeded historical maximum PM10 concentrations from the past 4 to 10 years. Daily mean PM10 values at Norwegian sites were up to 97 µg m−3 and had a median value of 59 µg m−3. We analysed this severe pollution episode caused by long-range atmospheric transport based on surface and remote sensing observations and transport model simulations to understand its causes. Samples from three sites in mainland Norway and the Arctic remote station Zeppelin (Svalbard) showed strong contributions from mineral dust to PM10 (23 %–36 % as a minimum and 31 %–45 % as a maximum) and biomass burning (8 %–16 % to 19 %–21 %). Atmospheric transport simulations indicate that Central Asia was the main source region for mineral dust observed in this episode. The biomass burning fraction can be attributed to forest fires in Ukraine and southern Russia, but we cannot exclude other sources contributing, like fires elsewhere, because the model underestimates observed concentrations. The combined use of remote sensing, surface measurements, and transport modelling proved effective in describing the episode and distinguishing its causes.

Measurements of total ozone column and effective cloud transmittance have been performed since 1995 at the three Norwegian sites Oslo/Kjeller, Andøya/Tromsø, and in Ny-Ålesund (Svalbard). These sites are a subset of nine stations included in the Norwegian UV monitoring network, which uses ground-based ultraviolet (GUV) multi-filter instruments and is operated by the Norwegian Radiation and Nuclear Safety Authority (DSA) and the Norwegian Institute for Air Research (NILU). The network includes unique data sets of high-time-resolution measurements that can be used for a broad range of atmospheric and biological exposure studies. Comparison of the 25-year records of GUV (global sky) total ozone measurements with Brewer direct sun (DS) measurements shows that the GUV instruments provide valuable supplements to the more standardized ground-based instruments. The GUV instruments can fill in missing data and extend the measuring season at sites with reduced staff and/or characterized by harsh environmental conditions, such as Ny-Ålesund. Also, a harmonized GUV can easily be moved to more remote/unmanned locations and provide independent total ozone column data sets. The GUV instrument in Ny-Ålesund captured well the exceptionally large Arctic ozone depletion in March/April 2020, whereas the GUV instrument in Oslo recorded a mini ozone hole in December 2019 with total ozone values below 200 DU. For all the three Norwegian stations there is a slight increase in total ozone from 1995 until today. Measurements of GUV effective cloud transmittance in Ny-Ålesund indicate that there has been a significant change in albedo during the past 25 years, most likely resulting from increased temperatures and Arctic ice melt in the area surrounding Svalbard.

Atmospheric turbulence and in particular its effect on tracer dispersion may be measured by cameras sensitive to the absorption of ultraviolet (UV) sunlight by sulfur dioxide (SO2), a gas that can be considered a passive tracer over short transport distances. We present a method to simulate UV camera measurements of SO2 with a 3D Monte Carlo radiative transfer model which takes input from a large eddy simulation (LES) of a SO2 plume released from a point source. From the simulated images the apparent absorbance and various plume density statistics (centre-line position, meandering, absolute and relative dispersion, and skewness) were calculated. These were compared with corresponding quantities obtained directly from the LES. Mean differences of centre-line position, absolute and relative dispersions, and skewness between the simulated images and the LES were generally found to be smaller than or about the voxel resolution of the LES. Furthermore, sensitivity studies were made to quantify how changes in solar azimuth and zenith angles, aerosol loading (background and in plume), and surface albedo impact the UV camera image plume statistics. Changing the values of these parameters within realistic limits has negligible effects on the centre-line position, meandering, absolute and relative dispersions, and skewness of the SO2 plume. Thus, we demonstrate that UV camera images of SO2 plumes may be used to derive plume statistics of relevance for the study of atmospheric turbulent dispersion.

The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm retrieves vertical dust concentration profiles from cloud-free Infrared Atmospheric Sounding Interferometer (IASI) thermal infrared (TIR) radiances using Rodgers' optimal estimation method (OEM). We describe the new version 4.1 and evaluation results. Main differences with respect to previous versions are the Levenberg–Marquardt modification of the OEM, the use of the logarithm of the concentration in the retrieval and the use of Radiative Transfer for TOVS (RTTOV) for in-line radiative transfer calculations. The dust aerosol concentrations are retrieved in seven 1 km thick layers centered at 0.5 to 6.5 km. A global data set of the daily dust distribution was generated with MAPIR v4.1 covering September 2007 to June 2018, with further extensions planned every 6 months. The post-retrieval quality filters reject about 16 % of the retrievals, a huge improvement with respect to the previous versions in which up to 40 % of the retrievals were of bad quality. The median difference between the observed and fitted spectra of the good-quality retrievals is 0.32 K, with lower values over oceans. The information content of the retrieved profiles shows a dependence on the total aerosol load due to the assumption of a lognormal state vector. The median degrees of freedom in dusty scenes (min 10 µm AOD of 0.5) is 1.4. An evaluation of the aerosol optical depth (AOD) obtained from the integrated MAPIR v4.1 profiles was performed against 72 AErosol RObotic NETwork (AERONET) stations. The MAPIR AOD correlates well with the ground-based data, with a mean correlation coefficient of 0.66 and values as high as 0.88. Overall, there is a mean AOD (550 nm) positive bias of only 0.04 with respect to AERONET, which is an extremely good result. The previous versions of MAPIR were known to largely overestimate AOD (about 0.28 for v3). A second evaluation exercise was performed comparing the mean aerosol layer altitude from MAPIR with the mean dust altitude from Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP). A small underestimation was found, with a mean difference of about 350 m (standard deviation of about 1 km) with respect to the CALIOP cumulative extinction altitude, which is again considered very good as the vertical resolution of MAPIR is 1 km. In the comparisons against AERONET and CALIOP, a dependence of MAPIR on the quality of the temperature profiles used in the retrieval is observed. Finally, a qualitative comparison of dust aerosol concentration profiles was done against lidar measurements from two ground-based stations (M'Bour and Al Dhaid) and from the Cloud–Aerosol Transport System (CATS) instrument on board the International Space Station (ISS). MAPIR v4.1 showed the ability to detect dust plumes at the same time and with a similar extent as the lidar instruments. This new MAPIR version shows a great improvement of the accuracy of the aerosol profile retrievals with respect to previous versions, especially so for the integrated AOD. It now offers a unique 3-D dust data set, which can be used to gain more insight into the transport and emission processes of mineral dust aerosols.

Highly unusual open fires burned in western Greenland between 31 July and 21 August 2017, after a period of warm, dry and sunny weather. The fires burned on peatlands that became vulnerable to fires by permafrost thawing. We used several satellite data sets to estimate that the total area burned was about 2345 ha. Based on assumptions of typical burn depths and emission factors for peat fires, we estimate that the fires consumed a fuel amount of about 117 kt C and emitted about 23.5 t of black carbon (BC) and 731 t of organic carbon (OC), including 141 t of brown carbon (BrC). We used a Lagrangian particle dispersion model to simulate the atmospheric transport and deposition of these species. We find that the smoke plumes were often pushed towards the Greenland ice sheet by westerly winds, and thus a large fraction of the emissions (30 %) was deposited on snow- or ice-covered surfaces. The calculated deposition was small compared to the deposition from global sources, but not entirely negligible. Analysis of aerosol optical depth data from three sites in western Greenland in August 2017 showed strong influence of forest fire plumes from Canada, but little impact of the Greenland fires. Nevertheless, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar data showed that our model captured the presence and structure of the plume from the Greenland fires. The albedo changes and instantaneous surface radiative forcing in Greenland due to the fire emissions were estimated with the SNICAR model and the uvspec model from the libRadtran radiative transfer software package. We estimate that the maximum albedo change due to the BC and BrC deposition was about 0.007, too small to be measured. The average instantaneous surface radiative forcing over Greenland at noon on 31 August was 0.03–0.04 W m−2, with locally occurring maxima of 0.63–0.77 W m−2 (depending on the studied scenario). The average value is up to an order of magnitude smaller than the radiative forcing from other sources. Overall, the fires burning in Greenland in the summer of 2017 had little impact on the Greenland ice sheet, causing a small extra radiative forcing. This was due to the – in a global context – still rather small size of the fires. However, the very large fraction of the emissions deposited on the Greenland ice sheet from these fires could contribute to accelerated melting of the Greenland ice sheet if these fires become several orders of magnitude larger under future climate.

In atmospheric tracer experiments, a substance is released into the turbulent atmospheric flow to study the dispersion parameters of the atmosphere. That can be done by observing the substance's concentration distribution downwind of the source. Past experiments have suffered from the fact that observations were only made at a few discrete locations and/or at low time resolution. The Comtessa project (Camera Observation and Modelling of 4-D Tracer Dispersion in the Atmosphere) is the first attempt at using ultraviolet (UV) camera observations to sample the three-dimensional (3-D) concentration distribution in the atmospheric boundary layer at high spatial and temporal resolution. For this, during a three-week campaign in Norway in July 2017, sulfur dioxide (SO2), a nearly passive tracer, was artificially released in continuous plumes and nearly instantaneous puffs from a 9 m high tower. Column-integrated SO2 concentrations were observed with six UV SO2 cameras with sampling rates of several hertz and a spatial resolution of a few centimetres. The atmospheric flow was characterised by eddy covariance measurements of heat and momentum fluxes at the release mast and two additional towers. By measuring simultaneously with six UV cameras positioned in a half circle around the release point, we could collect a data set of spatially and temporally resolved tracer column densities from six different directions, allowing a tomographic reconstruction of the 3-D concentration field. However, due to unfavourable cloudy conditions on all measurement days and their restrictive effect on the SO2 camera technique, the presented data set is limited to case studies. In this paper, we present a feasibility study demonstrating that the turbulent dispersion parameters can be retrieved from images of artificially released puffs, although the presented data set does not allow for an in-depth analysis of the obtained parameters. The 3-D trajectories of the centre of mass of the puffs were reconstructed enabling both a direct determination of the centre of mass meandering and a scaling of the image pixel dimension to the position of the puff. The latter made it possible to retrieve the temporal evolution of the puff spread projected to the image plane. The puff spread is a direct measure of the relative dispersion process. Combining meandering and relative dispersion, the absolute dispersion could be retrieved. The turbulent dispersion in the vertical is then used to estimate the effective source size, source timescale and the Lagrangian integral time. In principle, the Richardson–Obukhov constant of relative dispersion in the inertial subrange could be also obtained, but the observation time was not sufficiently long in comparison to the source timescale to allow an observation of this dispersion range. While the feasibility of the methodology to measure turbulent dispersion could be demonstrated, a larger data set with a larger number of cloud-free puff releases and longer observation times of each puff will be recorded in future studies to give a solid estimate for the turbulent dispersion under a variety of stability conditions.

Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5–0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO2 cameras is commonly used to monitor SO2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows the gas velocities in the plume to be retrieved directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constrained OF motion vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion fields. The new method is applied to two example data sets recorded at Mt Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO2 emission rates. We further show that our proposed correction can account for this and that it significantly improves the reliability of optical-flow-based gas velocity retrievals. In the case of Mt Etna, the SO2 emissions of the north-eastern crater are investigated. The corrected SO2 emission rates range between 4.8 and 10.7 kg s−1 (average of 7.1 ± 1.3 kg s−1) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO2 emission rates are between 0.5 and 2.9 kg s−1 (average of 1.3 ± 0.5 kg s−1) and provide the first report of SO2 emissions from this remotely located and inaccessible volcano.

Significant improvements in the way we can observe and model volcanic ash clouds have been obtained since the 2010 Eyjafjallajökull eruption. One major development has been the application of data assimilation techniques, which combine models and satellite observations such that an optimal understanding of ash clouds can be gained. Still, questions remain regarding the degree to which the forecasting capabilities are improved by inclusion of such techniques and how these improvements depend on the data input. This study explores how different satellite data and different uncertainty assumptions of the satellite and a priori emissions affect the calculated volcanic ash emission estimate, which is computed by an inversion method that couples the satellite retrievals and a priori emissions with dispersion model data. Two major ash episodes over 4 days in April and May of the 2010 Eyjafjallajökull eruption are studied. Specifically, inversion calculations are done for four different satellite data sets with different size distribution assumptions in the retrieval. A reference satellite data set is chosen, and the range between the minimum and maximum 4-day average load of hourly retrieved ash is 121 % in April and 148 % in May, compared to the reference. The corresponding a posteriori maximum and minimum emission sum found for these four satellite retrievals is 26 and 47 % of the a posteriori reference estimate for the same two periods, respectively. Varying the assumptions made in the satellite retrieval is seen to affect the a posteriori emissions and modelled ash column loads, and modelled column loads therefore have uncertainties connected to them depending on the uncertainty in the satellite retrieval. By further exploring our uncertainty estimates connected to a priori emissions and the mass load uncertainties in the satellite data, the uncertainty in the a priori estimate is found in this case to have an order-of-magnitude-greater impact on the a posteriori solution than the mass load uncertainties in the satellite. Part of this is explained by a too-high a priori estimate used in this study that is reduced by around half in the a posteriori reference estimate. Setting large uncertainties connected to both a priori and satellite mass load shows that they compensate each other, but the a priori uncertainty is found to be most sensitive. Because of this, an inversion-based emission estimate in a forecasting setting needs well-tested and well-considered assumptions on uncertainties for the a priori emission and satellite data. The quality of using the inversion in a forecasting environment is tested by adding gradually, with time, more observations to improve the estimated height versus time evolution of Eyjafjallajökull ash emissions. We show that the initially too-high a priori emissions are reduced effectively when using just 12 h of satellite observations. More satellite observations (> 12 h), in the Eyjafjallajökull case, place the volcanic injection at higher altitudes. Adding additional satellite observations (> 36 h) changes the a posteriori emissions to only a small extent for May and minimal for the April period, because the ash is dispersed and transported effectively out of the domain after 1–2 days. A best-guess emission estimate for the forecasting period was constructed by averaging the last 12 h of the a posteriori emission. Using this emission for a forecast simulation leads to better performance, especially compared to model simulations with no further emissions over the forecast period in the case of a continued volcanic eruption activity. Because of undetected ash in the satellite retrieval and diffusion in the model, the forecast simulations generally contain more ash than the observed fields, and the model ash is more spread out. Overall, using the a posteriori emissions in our model reduces the uncertainties in the ash plume forecast, because it corrects effectively for false-positive satellite retrievals, temporary gaps in observations, and false a priori emissions in the window of observation.

Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300–920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.

On 16–17 September 2013 strong surface winds over tephra deposits in southern Iceland led to the resuspension and subsequent advection of significant quantities of volcanic ash. The resulting resuspended ash cloud was transported to the south-east over the North Atlantic Ocean and, due to clear skies at the time, was exceptionally well observed in satellite imagery. We use satellite-based measurements in combination with radiative transfer and dispersion modelling to quantify the total mass of ash resuspended during this event. Typically ash clouds from explosive eruptions are identified in satellite measurements from a negative brightness temperature difference (BTD) signal; however this technique assumes that the ash resides at high levels in the atmosphere. Due to a temperature inversion in the troposphere over southern Iceland during 16 September 2013, the resuspended ash cloud was constrained to altitudes of

libRadtran is a widely used software package for radiative transfer calculations. It allows one to compute (polarized) radiances, irradiance, and actinic fluxes in the solar and thermal spectral regions. libRadtran has been used for various applications, including remote sensing of clouds, aerosols and trace gases in the Earth's atmosphere, climate studies, e.g., for the calculation of radiative forcing due to different atmospheric components, for UV forecasting, the calculation of photolysis frequencies, and for remote sensing of other planets in our solar system. The package has been described in Mayer and Kylling (2005). Since then several new features have been included, for example polarization, Raman scattering, a new molecular gas absorption parameterization, and several new parameterizations of cloud and aerosol optical properties. Furthermore, a graphical user interface is now available, which greatly simplifies the usage of the model, especially for new users. This paper gives an overview of libRadtran version 2.0.1 with a focus on new features. Applications including these new features are provided as examples of use. A complete description of libRadtran and all its input options is given in the user manual included in the libRadtran software package, which is freely available at http://www.libradtran.org.

During the Mt Kelud February 2014 eruption the ash cloud was detectable on 13–14 February in the infrared with the reverse absorption technique by, for example, the Advanced Very High Resolution Radiometer (AVHRR/3). The Infrared Atmospheric Sounding Interferometer (IASI) observed the ash cloud also on 15 February when AVHRR did not detect any ash signal. The differences between ash detection with AVHRR/3 and IASI are discussed along with the reasons for the differences, supported by radiative transfer modelling. The effect of concurrent ice clouds on the ash detection and the ash signal in the IASI measurements is demonstrated. Specifically, a radiative transfer model is used to simulate IASI spectra with ash-only, with ice cloud only and with both ash and ice clouds. It is shown that modelled IASI spectra with ash and ice clouds reproduce the measured IASI spectra better than ash-only- or ice-only-modelled spectra. The ash and ice modelled spectra that best reproduce the IASI spectra contain about a factor of 12 less ash than the ash-only spectra that come closest to reproducing the measured spectra.

We have evaluated the magnitude and makeup of error in cryospheric radiation observations due to small sensor misalignment in in situ measurements of solar irradiance. This error is examined through simulation of diffuse and direct irradiance arriving at a detector with a cosine-response fore optic. Emphasis is placed on assessing total error over the solar shortwave spectrum from 250 to 4500 nm, as well as supporting investigation over other relevant shortwave spectral ranges. The total measurement error introduced by sensor tilt is dominated by the direct component. For a typical high-latitude albedo measurement with a solar zenith angle of 60°, a sensor tilted by 1, 3, and 5° can, respectively introduce up to 2.7, 8.1, and 13.5 % error into the measured irradiance and similar errors in the derived albedo. Depending on the daily range of solar azimuth and zenith angles, significant measurement error can persist also in integrated daily irradiance and albedo. Simulations including a cloud layer demonstrate decreasing tilt error with increasing cloud optical depth.

Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6–12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m−2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones within scenes. The impact of ice and liquid-water clouds on the detection and retrieval of volcanic ash, implies that to fully appreciate the location and amount of ash, hyperspectral and spectral band measurements by satellite instruments should be combined with ash dispersion modelling.

The reverse absorption technique is often used to detect volcanic ash clouds from thermal infrared satellite measurements. From these measurements effective particle radius and mass loading may be estimated using radiative transfer modelling. The radiative transfer modelling usually assumes that the ash particles are spherical. We calculated thermal infrared optical properties of highly irregular and porous ash particles and compared these with mass- and volume-equivalent spherical models. Furthermore, brightness temperatures pertinent to satellite observing geometry were calculated for the different ash particle shapes. Non-spherical shapes and volume-equivalent spheres were found to produce a detectable ash signal for larger particle sizes than mass-equivalent spheres. The assumption of mass-equivalent spheres for ash mass loading estimates was found to underestimate mass loading compared to morphologically complex inhomogeneous ash particles. The underestimate increases with the mass loading. For an ash cloud recorded during the Eyjafjallajökull 2010 eruption, the mass-equivalent spheres underestimate the total mass of the ash cloud by approximately 30% compared to the morphologically complex inhomogeneous particles.

Infrared satellite images are widely and successfully used to detect and follow atmospheric ash from erupting volcanoes. We describe a new radiative transfer model framework for the simulation of infrared radiances, which can be compared directly with satellite images. This can be helpful to get insight into the processes that affect the satellite retrievals. As input to the radiative transfer model, the distribution of ash is provided by simulations with the FLEXPART Lagrangian particle dispersion model, meteorological cloud information is adopted from the ECMWF analysis and the radiative transfer modelling is performed with the MYSTIC 3-D radiative transfer model. The model framework is used to study an episode during the Eyjafjallajökull eruption in 2010. It is found that to detect ash by the reverse absorption retrieval technique, accurate representation of the ash particle size distribution is required. Detailed investigation of individual pixels displays the radiative effects of various combinations of ash, liquid water and ice clouds. In order to be clearly detectable, the ash clouds need to be located at some distance above other clouds. If ash clouds are mixed with water clouds or are located only slightly above water clouds, detection of the ash becomes difficult. Simulations were also made using the so-called independent pixel approximation (IPA) instead of the fully 3-D radiative transfer modelling. In the two simulations, different clouds (or different parts of the clouds) or the ground are effectively emitting radiation towards the instrument, thus causing differences in the brightness temperature of up to ± 25 K. The presented model framework is useful for further studies of the processes that affect satellite imagery and may be used to test both new and existing ash retrieval algorithms.

Rotational Raman scattering in the Earth's atmosphere explains the filling-in of Fraunhofer lines in the solar spectrum. A new model including first-order rotational Raman scattering has been developed, based on a reimplementation of the versatile discrete ordinate radiative transfer (DISORT) solver in the C computer language. The solver is fully integrated in the freely available libRadtran radiative transfer package. A detailed description is given of the model including the spectral resolution and a spectral interpolation scheme that considerably speeds up the calculations. The model is used to demonstrate the effect of clouds on top and bottom of the atmosphere filling-in factors and differential optical depths. Cloud effects on vertical profiles of the filling-in factor are also presented. The spectral behaviour of the model is compared against measurements under thunderstorm and aerosol loaded conditions.

A multi-platform field measurement campaign involving aircraft and balloons took place over West Africa between 26 July and 25 August 2006, in the frame of the concomitant AMMA Special Observing Period and SCOUT-O3 African tropical activities. Specifically aiming at sampling the upper troposphere and lower stratosphere, the high-altitude research aircraft M55 Geophysica was deployed in Ouagadougou (12.3° N, 1.7° W), Burkina Faso, in conjunction with the German D-20 Falcon, while a series of stratospheric balloons and sonde flights were conducted from Niamey (13.5° N, 2.0° E), Niger. Altogether, these measurements were intended to provide experimental evidence for a better understanding of large scale transport, assessing the effect of lightning on NOx production, and studying the impact of intense mesoscale convective systems on water, aerosol, dust and chemical species in the upper troposphere and lower stratosphere. The M55 Geophysica carried out five local and four transfer flights between southern Europe and the Sahel and back, while eight stratospheric balloons and twenty-nine sondes were flown from Niamey. These experiments allowed a characterization of the tropopause and lower stratosphere of the region. The paper provides an overview of SCOUT-AMMA campaign activities together with a description of the meteorology of the African monsoon and the situation prevailing during the flights and a brief summary of the observations accomplished.

Ultraviolet radiation is the key factor driving tropospheric photochemistry. It is strongly modulated by clouds and aerosols. A quantitative understanding of the radiation field and its effect on photochemistry is thus only possible with a detailed knowledge of the interaction between clouds and radiation. The overall objective of the project INSPECTRO was the characterization of the three-dimensional actinic radiation field under cloudy conditions. This was achieved during two measurement campaigns in Norfolk (East Anglia, UK) and Lower Bavaria (Germany) combining space-based, aircraft and ground-based measurements as well as simulations with the one-dimensional radiation transfer model UVSPEC and the three-dimensional radiation transfer model MYSTIC. During both campaigns the spectral actinic flux density was measured at several locations at ground level and in the air by up to four different aircraft. This allows the comparison of measured and simulated actinic radiation profiles. In addition satellite data were used to complete the information of the three dimensional input data set for the simulation. A three-dimensional simulation of actinic flux density data under cloudy sky conditions requires a realistic simulation of the cloud field to be used as an input for the 3-D radiation transfer model calculations. Two different approaches were applied, to derive high- and low-resolution data sets, with a grid resolution of about 100 m and 1 km, respectively. The results of the measured and simulated radiation profiles as well as the results of the ground based measurements are presented in terms of photolysis rate profiles for ozone and nitrogen dioxide. During both campaigns all spectroradiometer systems agreed within ±10% if mandatory corrections e.g. stray light correction were applied. Stability changes of the systems were below 5% over the 4 week campaign periods and negligible over a few days. The J(O1D) data of the single monochromator systems can be evaluated for zenith angles less than 70°, which was satisfied by nearly all airborne measurements during both campaigns. The comparison of the airborne measurements with corresponding simulations is presented for the total, downward and upward flux during selected clear sky periods of both campaigns. The compliance between the measured (from three aircraft) and simulated downward and total flux profiles lies in the range of ±15%.

We present the results of an intercomparison exercise between six different radiative transfer (RT) models carried out in the framework of QUILT, an EU funded project based on the exploitation of the Network for the Detection of Stratospheric Change (NDSC). RT modelling is an important step in the interpretation of Differential Optical Absorption Spectroscopy (DOAS) observations. It allows the conversion of slant column densities (SCDs) into vertical column densities (VCDs) using calculated air mass factors (AMFs). The originality of our study resides in comparing SCD simulations in multi-axis (MAX) geometry (trace gases: NO2 and HCHO) and in taking into account photochemical enhancement for calculating SCDs of rapidly photolysing species (BrO, NO2, and OClO) in zenith-sky geometry. Concerning the zenith-sky simulations, the different models agree generally well, especially below 90° SZA. At higher SZA, larger discrepancies are obtained with relative differences ranging between 2% and 14% in some cases. In MAX geometry, good agreement is found between the models with the calculated NO2 and HCHO SCDs differing by no more than 5% in the elevation and solar zenith angle (SZA) ranges investigated (5°–20° and 35°–85°, respectively). The impacts of aerosol scattering, ground albedo, and relative azimuth on MAX simulations have also been tested. Significant discrepancies appear for the aerosol effect, suggesting differences between models in the treatment of aerosol scattering. A better agreement is found in case of the ground albedo and relative azimuth effects. The complete set of initialization data and results have been made publicly available through the QUILT project web site (http://nadir.nilu.no/quilt/), enabling the testing of other RT codes designed for the calculation of SCDs/AMFs.

In September 2002, the first INSPECTRO campaign to study the influence of clouds on the spectral actinic flux in the lower troposphere was carried out in East Anglia, England. Measurements of the actinic flux, the irradiance and aerosol and cloud properties were made from four ground stations and by aircraft. The radiation measurements were modelled using the uvspec model and ancillary data. For cloudless conditions, the measurements of the actinic flux were reproduced by 1-D radiative transfer modelling within the measurement and model uncertainties of about ±10%. For overcast days, the ground-based and aircraft radiation measurements and the cloud microphysical property measurements are consistent within the framework of 1-D radiative transfer and within experimental uncertainties. Furthermore, the actinic flux is increased by between 60-100% above the cloud when compared to a cloudless sky, with the largest increase for the optically thickest cloud. Correspondingly, the below cloud actinic flux is decreased by about 55-65%. Just below the cloud top, the downwelling actinic flux has a maximum that is seen in both the measurements and the model results. For broken clouds the traditional cloud fraction approximation is not able to simultaneously reproduce the measured above-cloud enhancement and below-cloud reduction in the actinic flux.

The libRadtran software package is a suite of tools for radiative transfer calculations in the Earth's atmosphere. Its main tool is the uvspec program. It may be used to compute radiances, irradiances and actinic fluxes in the solar and terrestrial part of the spectrum. The design of uvspec allows simple problems to be easily solved using defaults and included data, hence making it suitable for educational purposes. At the same time the flexibility in how and what input may be specified makes it a powerful and versatile tool for research tasks. The uvspec tool and additional tools included with libRadtran are described and realistic examples of their use are given. The libRadtran software package is available from http://www.libradtran.org.

A new ligthweight multichannel moderate bandwidth filter instrument designed to be flown on balloons, is described. The instrument measures the radiation field within the short UV (center wavelength at 312 nm) and long UV (center wavelength at 340 nm). The angular and spectral characteristics of the instrument are discussed and the calibration procedure outlined. Measurements made during a stratospheric balloon flight at twilight conditions from Gap-Tallard, France, are presented and compared with state-of-the-art radiative transfer model simulations. The model simulations and the measurements agree within ±10% (±20%) for solar zenith angles smaller than 93° (90°) for the 340 (312) nm channel. Based on the model simulations of the measured radiation, actinic flux spectra are reconstructed. These are used to calculate various photodissociation rates.