Professor Roy Grainger

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:

<p>Satellite remote sensing has been widely used to make measurements of sulphur dioxide (SO<sub>2</sub>) 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.  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.  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 ‘fast’ 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’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<sub>2 </sub>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.  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).</p>

Abstract:

<p>Precise knowledge of the location and height of the volcanic sulfur dioxide (SO<sub>2</sub>) plume is essential for accurate determination of SO<sub>2</sub> emitted by volcanic eruptions. So far, UV based SO<sub>2</sub> 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<sub>2</sub> layer heights based on the UV satellite instruments Sentinel-5 Precursor/TROPOMI and MetOp/GOME-2.</p><p>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<sub>2</sub>, which could be detected  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<sub>2</sub> plume into the upper atmosphere, with plume heights of up to 20km. </p><p>The algorithm is developed in the framework of ESA's  "Sentinel-5p+ Innovation: SO<sub>2</sub> Layer Height project" (S5P+I: SO2 LH),  dedicated to the generation of an SO<sub>2</sub> LH product and its extensive verification with collocated ground- and space-born measurements.</p><p>The high-resolution UV spectrometer GOME-2 aboard the three EPS MetOp-A, -B, and –C satellites perform global daily atmospheric trace-gas measurements with a spatial resolution of  40x40km<sup>2</sup> 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<sup>2</sup> 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.</p>

Abstract:

Ash clouds are a geographically far-reaching hazard associated with volcanic eruptions. To minimise the risk that these pose to aircraft and to limit disruption to the aviation industry, it is important to closely monitor the emission and atmospheric dispersion of these plumes. The altitude of the plume is an important consideration and is an essential input into many models of ash cloud propagation. CO2 slicing is an established technique for obtaining the top height of aqueous clouds, and previous studies have demonstrated that there is potential for this method to be used for volcanic ash. In this study, the CO2 slicing technique has been adapted for volcanic ash and applied to spectra obtained from the Infrared Atmospheric Sounding Interferometer (IASI). Simulated ash spectra are first used to select the most appropriate channels and then demonstrate that the technique has merit for determining the altitude of the ash. These results indicate a strong match between the true heights and CO2 slicing output with a root mean square error (RMSE) of less than 800 m. Following this, the technique was applied to spectra obtained with IASI during the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 respectively, both of which emitted ash clouds into the troposphere, and which have been extensively studied with satellite imagery. The CO2 slicing results were compared against those from an optimal estimation scheme, also developed for IASI, and a satellite-borne lidar is used for validation. The CO2 slicing heights returned an RMSE value of 2.2 km when compared against the lidar. This is lower than the RMSE for the optimal estimation scheme (2.8 km). The CO2 slicing technique is a relatively fast tool and the results suggest that this method could be used to get a first approximation of the ash cloud height, potentially for use for hazard mitigation, or as an input for other retrieval techniques or models of ash cloud propagation.