IVATF/4-WP/11 Revision 1 07/06/12. International WORKING PAPER IVATF TASK. (Presented SUMMARY 1.1. (5 pages)

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1 International Civil Aviation Organization WORKING PAPER Revision 1 07/06/12 INTERNATIONAL VOLCANIC ASH TASK FORCE (IVATF) FOURTH MEETING Montréal, 13 to 15 June 2012 Agenda Item 2: Report of the science sub-group (SCI SG) 2.3: Additional scientific guidance material on visible ash IVATF TASK TF-SCI03. 1 REPORT (PART I) DETECTION THRESHOLDS OF SATELITE-BASED INFRARED SENSORS (Presented by the Rapporteur of the IVATF Science Sub-Group, in collaboration with the WMO-IUGG Volcanic Ash Scientific Advisory Group) SUMMARY This paper considerss the current status of satellite-based infrared sensor methods for determining ash cloud microphysics. Scientificc interest in recent volcanic eruptions has led to the provision of new validation data from ground-based lidars, from aircraft measurements, and from satellite-based estimatess of ash cloud-top heights. These new data suggest that ash mass loadings from infrared satellite sensors have a lower detection threshold of 0.2 g/m 2 and a standard error of ±0.150 g/m 2 under the most favourable conditions. It is noted that for an ash cloud of 1 km mean thickness, the lower detection threshold for ash concentration estimation from satellites is 200 µg/m 3. This report is in support of IVATF Task TF-SCI INTRODUCTION 1.1 As a result of discussions about what constitutes visible ash in terms of both human observation and satellite detection (see for example IVATF/2-WP/08), the IVATF has recognized the need to quantify ash detection thresholds of space-based sensors throughh IVATF Recommendationn 2/5. Such thresholds, or lower limits, are usually expressed in units of mass of ash per area and are a constraint on defining cloud edges in terms of physical properties, for both observed and forecast (modelled) clouds. When combined with cloud-thickness data, detection thresholds also set a lower limit for ashconcentration values. (5 pages) IVATF.4.WP Rev.1.en.docx

2 Research into utilising satellite-based measurements of volcanic ash in the atmosphere has been steadily improving since the pioneering work of Sawada (e.g. Sawada, 1996) and his co-workers who used Geostationary Meteorological Satellite data to track and identify ash clouds. The National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometers (AVHHRs), first launched in 1979 and continuing today, have allowed scientists to develop robust retrieval schemes based on multi-spectral infrared measurements. The focus has remained on using infrared measurements because of the sensitivity of these data to ash (specifically its silicate content) and the capability to obtain these measurements during the day and night. With the advent of multi-spectral instruments in geostationary orbit, greater effort has been placed on improving discrimination of ash from meteorological clouds and on developing optimal estimations schemes with proper error characterisation. 1.3 This report is in support of IVATF Task TF-SCI03.1 accordingly. 2. DISCUSSION 2.1 Satellite sensors Polar-orbiting satellite instruments can provide infrared measurements globally, but with limited temporal resolution. Geostationary instruments are generally preferred for volcanic ash measurements because of the near continuous coverage of large parts of the globe. Table 1 shows the current and future capabilities of infrared sensors on board geostationary satellites. Table 1 (below): An overview of the geostationary satellite capabilities is shown as a function of Volcanic Ash Advisory Center (VAAC). The table summarizes the temporal and spectral capabilities (those relevant to volcanic ash remote sensing) of each instrument that covers each VAAC area of responsibility. In addition, future geostationary satellite capabilities are summarized. Next generation satellites that include a hyperspectral sounding capability for greater vertical resolution are shown in bold. VAAC GEO Satellite(s) Temporal Refresh Spectral Capabilities Next Generation GEO Satellite Anchorage GOES minutes GOES-R (2015) Buenos Aires Darwin GOES-13 MSG 180 minutes 1 15 minutes 2 Advanced GOES-R (2015) and MTG (~2018) FY4A from China (2014) London MSG 15 minutes Advanced MTG (~2018) Montreal Tokyo GOES-13 GOES minutes 30 minutes GOES-R (2015) FY4A from China (2014) 1 Partial coverage (up to 45 degrees South) every 30 minutes and no coverage when severe meteorological conditions occur in North America and the Caribbean. 2 Partial coverage only the north-east of VAAC Buenos Aires area of responsibility. No access to Channel 5.

3 - 3 - Toulouse MSG 5 or 15 minutes Advanced MTG (~2018) Washington Wellington GOES-12 GOES-13 (E) GOES-15 (W) MSG GOES-15 Call-up if needed ~15 minutes or less Call-up if needed 60 minute Call-up if needed 60 minute 180 minutes GOES-R (2015) and MTG (~2018) Himawari-8 (2014) FY4A (2014) GOES-R (2015) A priori knowledge of ash properties. Utilisation of infrared measurements to determine mass loadings or the vertically integrated mass concentration relies on knowledge of some basic properties of dispersing fine-grained (radii less than 16 µm or so) ash. Most important of these are: the spectral complex refractive index of volcanic ash, and its variability; the particle size distribution within the radius interval of 1 < r < 32 µm; the typical shape and angularity of ash; the composition and density of ash. There are concerted efforts to provide reliable estimates of these parameters Optimal estimation of ash microphysics. Methods and algorithms to retrieve ash microphysics have greatly improved over the years. Researchers have converged on using optimal estimation methods (e.g. Pavolonis and Sieglaff, 2010; Francis et al., 2011) that are capable of estimating effective particle radius, spectral infrared optical depth, ash cloud-top height and mass loading, with error estimates of the retrieved parameters. Without a measurement of ash cloud thickness it is problematic to determine ash concentrations Assimilation and inversion. Satellite infrared measurements provide some of the information needed to help make better quantitative forecasts of volcanic ash concentrations, but some data are lacking. Additional information is sometimes available from other data sources, such as groundbased and space-borne lidars or aircraft measurements. Information from atmospheric dispersion models is available in most cases and may also be utilised with satellite measurements in an assimilation scheme or by using inverse methods to improve forecasts and estimate ash cloud thickness. Optimal estimation techniques are well-suited to incorporate different sources of data and properly handle the error characteristics of the data and the model estimates Validation is a vital part of the estimation process. Satellite retrievals must be validated against independent measurements, and model forecasts of ash must be corroborated in a consistent and meaningful manner. Ash cloud-top height can be independently measured by space-borne lidar (Caliop), by ground-based radar (and lidar when available) and by a variety of alternate satellite-based algorithms including cloud stereoscopy, carbon dioxide slicing/absorption methods, A-band absorption, and through a combination of cloud-top temperature and radiosonde measurements. Ash concentrations are much more difficult to validate because of the lack of independent data and because the satellite retrieval scheme still requires an estimate of cloud thickness before concentrations can be determined. Other validation data on ash microphysics, such as the effective particle radius, shape and angularity, composition and density are almost non-existent The Eyjafjallajökull validation data-set. During the eruptions of Eyjafjallajökull in April and May 2010, a series of airborne measurements were made by the Met Office (UK), and by DLR

4 - 4 - (Germany) using well-equipped scientific research aircraft. These measurements have been carefully scrutinised and reported in the peer-reviewed literature (Johnson et al., 2012; Schumann et al., 2011). A validation exercise has been performed by Prata and Prata (2012), who found that under favourable conditions (e.g. no cloud interference) ash mass loadings as low as 0.2 g/m 2 with standard errors of ±0.15 g/m 2 could be determined. Independent validation using a data-set composed of space-borne lidar data (Caliop) by Pavolonis (2011) gives very similar results. These data could form the basis for an on-going validation data-set, to be used for benchmarking satellite-based ash retrieval schemes. 3. RECOMMENDATION 3.1 The need in some parts of the world for quantitative ash retrievals and the requirements to validate and corroborate model forecasts imply the need to establish minimum thresholds and error bounds on satellite retrievals. Accordingly, the task force is invited to formulate the following recommendation: Recommendation 4/xx That, the International Airways Volcano Watch Operations Group (IAVWOPSG) be invited to task the WMO-IUGG Volcanic Ash Scientific Advisory Group (VASAG) to: a) support the establishment of a validation data-set for benchmarking current and future satellite-based retrieval schemes; b) note that the current best estimate of the minimum detection threshold for ash mass loading is 0.2 g/m 2, with a standard error of ±0.15 g/m 2 under favourable conditions using the most advanced retrieval methodologies; and c) note the current and future global coverage at infrared wavelengths and to encourage national and international spacebased earth observation programs to maintain and improve this level of coverage. 4. ACTION BY THE IVATF 4.1 The IVATF is invited to: a) note the information contained in this paper; and b) decide on a recommendation for the task force s consideration.

5 - 5 - References Francis, P. N., M. C. Cooke, and R. W. Saunders (2011), Retrieval of physical properties of volcanic ash using Meteosat: A case study from the 2010 Eyjafjallajökull eruption, J. Geophys. Res., 117, D00U09, doi: /2011jd Johnson, B., et al. (2012), In-situ observations of volcanic ash clouds from the FAAM aircraft during the eruption of Eyjafjallajökull in 2010, J. Geophys. Res., 117, D00U24, doi: /2011jd Pavolonis, M. J. and J. Sieglaff, 2010: GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for Volcanic Ash: Detection and Height, Version 2.0., 72 pp. Pavolonis, M. J. (2011), Using infrared satellite measurements to identify and track volcanic ash clouds that exceed aircraft exposure thresholds: Capabilities and limitations, paper presented at European Geosciences Union General Assembly 2011, Vienna. Prata, A.J. and A. T. Prata (2012), Eyjafjallajökull volcanic ash concentrations determined using Spin Enhanced Visible and Infrared Imager measurements, J. Geophys. Res. 117, D00U23, doi: /2011jd Sawada Y. (1996) Detection of explosive eruptions and regional tracking of volcanic ash clouds with geostationary meteorological satellites (GMS). In: Scarpa R, Tilling RI (eds) Monitoring and miti- gation of volcano hazards. Springer-Verlag, Berlin, Heidelberg, pp Schumann, U., et al. (2011), Airborne observations of the Eyjafjalla volcano ash cloud over Europe during air space closure in April and May 2010, Atmos. Chem. Phys., 11, , doi: /acp END