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Abstract:

<jats:p>Volcanic ash can interact with the earth system on many temporal and spatial scales and is a significant hazard to aircraft. In the event of a volcanic eruption, fast and robust decisions need to be made by aviation authorities about which routes are safe to operate. Such decisions take into account forecasts of ash location issued by Volcanic Ash Advisory Centers (VAACs) which are informed by simulations from Volcanic Ash Transport and Dispersion (VATD) models. The estimation of the time-evolving vertical distribution of ash emissions for use in VATD simulations in real time is difficult which can lead to large uncertainty in these forecasts. This study presents a method for constraining the ash emission estimates by combining an inversion modeling technique with an ensemble of meteorological forecasts, resulting in an ensemble of ash emission estimates. These estimates of ash emissions can be used to produce a robust ash forecast consistent with observations. This new ensemble approach is applied to the 2011 eruption of the Icelandic volcano Grímsvötn. The resulting emission profiles each have a similar temporal evolution but there are differences in the magnitude of ash emitted at different heights. For this eruption, the impact of precipitation uncertainty (and the associated wet deposition of ash) on the estimate of the total amount of ash emitted is larger than the impact of the uncertainty in the wind fields. Despite the differences that are dominated by wet deposition uncertainty, the ensemble inversion provides confidence that the reduction of the unconstrained emissions (a priori), particularly above 4 km, is robust across all members. In this case, the use of posterior emission profiles greatly reduces the magnitude and extent of the forecast ash cloud. The ensemble of posterior emission profiles gives a range of ash column loadings much closer in agreement with a set of independent satellite retrievals in comparison to the a priori emissions. Furthermore, airspace containing volcanic ash concentrations deemed to be associated with the highest risk (likelihood of exceeding a high concentration threshold) to aviation are reduced by over 85%. Such improvements could have large implications in emergency response situations. Future research will focus on quantifying the impact of uncertainty in precipitation forecasts on wet deposition in other eruptions and developing an inversion system that makes use of the state-of-the-art meteorological ensembles which has the potential to be used in an operational setting.</jats:p>

Abstract:

We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products.

Abstract:

Abstract. We present version 3 (V3) of the Cloud_cci ATSR-2/AATSR dataset. The dataset was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) program. The cloud properties were retrieved from the second Along- Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the Advanced ATSR (AATSR) on board Envisat, which spanned 2002–2012. The data comprises a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius and optical thickness alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top and bottom-of-atmosphere short- and long-wave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with collocated CALIPSO data. The cloud masking has improved significantly, particularly the ability to detect clear pixels The Kuiper Skill score has increased from .49 to .66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulous cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments, the Correlation with MAC-LWP increase from .4 to over .8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth’s Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new dataset is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol-cloud interactions, and providing contextual information for collocated ATSR-2/AATSR surface temperature and aerosol products. For the Cloud_cci ATSR-2/AATSRv3 dataset a new digital identifier has been issued: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 Poulsen et al. (2019).

Abstract:

&lt;p&gt;Satellite remote sensing has been widely used to make measurements of sulphur dioxide (SO&lt;sub&gt;2&lt;/sub&gt;) emissions from volcanoes. The Infrared Atmospheric Sounding Interferometer (IASI) is one such instrument that has been used to examine the emissions from large explosive eruptions.&amp;#160; Much less work has been done using IASI to study the emissions from smaller eruptions, non-eruptive degassing or anthropogenic sources, and similarly it is rarely used for examining long term trends in activity.&amp;#160; Now, when there are three IASI instruments in orbit and with over ten years of data, is the perfect opportunity to explore these topics. This study applied a &amp;#8216;fast&amp;#8217; linear retrieval developed for IASI in Oxford, across the globe for a ten-year period. Global annual averages were dominated by the emissions from large eruptions (e.g. Nabro in 2011) but elevated signals could also be identified from smaller volcanic sources and industrial centres, suggesting the technique has promise for detecting lower level emissions. A systematic approach was then taken, rotating the linear retrieval output for each orbit at over 100 volcanoes worldwide, with the wind direction at the volcano&amp;#8217;s vent, or in cases where the plume was emitted at a greater height, using the observed plume direction. This isolates the elevated signal downwind of the volcano. The rotated outputs were then averaged over monthly, annual and multi-annual time periods. Analysis of the upwind and downwind values establishes whether there is an elevated signal and its intensity. An inventory was then constructed from these observations which show how these emissions varied over a ten-year period. Trends in SO&lt;sub&gt;2 &lt;/sub&gt;emission were compared against fluxes generated for the Ozone Monitoring Instrument (OMI) and the number of thermal anomalies detected by the MODVOLC algorithm developed for MODIS.&amp;#160; It was identified for example, that long term trends are more easily identified at high altitude volcanoes such as Popocatepetl, Sabancaya and Nevado del Ruiz. This is consistent with the idea that the instrument performs better in regions with lower levels of water vapour (e.g. above the boundary layer).&lt;/p&gt;

Abstract:

&lt;p&gt;Precise knowledge of the location and height of the volcanic sulfur dioxide (SO&lt;sub&gt;2&lt;/sub&gt;) plume is essential for accurate determination of SO&lt;sub&gt;2&lt;/sub&gt; emitted by volcanic eruptions. So far, UV based SO&lt;sub&gt;2&lt;/sub&gt; plume height retrieval algorithms are very time-consuming and therefore not suitable for near-real-time applications like aviation control. We have therefore developed the Full-Physics Inverse Learning Machine (FP_ILM) algorithm for extremely fast and accurate retrieval of volcanic SO&lt;sub&gt;2&lt;/sub&gt; layer heights based on the UV satellite instruments Sentinel-5 Precursor/TROPOMI and MetOp/GOME-2.&lt;/p&gt;&lt;p&gt;In this presentation, we will present the FP-ILM algorithm and show results of the 2019 Raikoke eruption; a strong volcanic eruption which has emitted a huge ash cloud accompanied by more than 1300 DU of SO&lt;sub&gt;2&lt;/sub&gt;, which could be detected &amp;#160;even two months after the end of eruptive event. We will also present first results of the recent Taal volcanic eruption on 13 January 2020 in Indonesia, which has injected a huge ash and SO&lt;sub&gt;2&lt;/sub&gt; plume into the upper atmosphere, with plume heights of up to 20km.&amp;#160;&lt;/p&gt;&lt;p&gt;The algorithm is developed in the framework of ESA's&amp;#160; &quot;Sentinel-5p+ Innovation: SO&lt;sub&gt;2&lt;/sub&gt; Layer Height project&quot; (S5P+I: SO2 LH),&amp;#160; dedicated to the generation of an SO&lt;sub&gt;2&lt;/sub&gt; LH product and its extensive verification with collocated ground- and space-born measurements.&lt;/p&gt;&lt;p&gt;The high-resolution UV spectrometer GOME-2 aboard the three EPS MetOp-A, -B, and &amp;#8211;C satellites perform global daily atmospheric trace-gas measurements with a spatial resolution of &amp;#160;40x40km&lt;sup&gt;2&lt;/sup&gt; at an overpass time of 8:30h local time. The UV spectrometer TROPOMI aboard the ESA Sentinel-5P satellite provides a much higher spatial resolution of currently 5.6x3.6km&lt;sup&gt;2&lt;/sup&gt; per ground pixel, at an overpass time of 13:30h. In the future, also UV instruments aboard the Sentinel-4 (geostationary) and Sentinel-5 will complement the satellite-based global monitoring of atmospheric trace gases.&lt;/p&gt;