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Volcanoes often erupt explosively and generate a variety of hazards including volcanic ash clouds and gaseous plumes. These clouds and plumes are a significant hazard to the aviation industry and the ground features can be a major hazard to local communities. Here, we provide a chronology of the 2009 Redoubt Volcano eruption using frequent, low spatial resolution thermal infrared (TIR), mid-infrared (MIR) and ultraviolet (UV) satellite remote sensing data. The first explosion of the 2009 eruption of Redoubt Volcano occurred on March 15, 2009 (UTC) and was followed by a series of magmatic explosive events starting on March 23 (UTC). From March 23–April 4 2009, satellites imaged at least 19 separate explosive events that sent ash clouds up to 18 km above sea level (ASL) that dispersed ash across the Cook Inlet region. In this manuscript, we provide an overview of the ash clouds and plumes from the 19 explosive events, detailing their cloud-top heights and discussing the variations in infrared absorption signals. We show that the timing of the TIR data relative to the event end time was critical for inferring the TIR derived height and true cloud top height. The ash clouds were high in water content, likely in the form of ice, which masked the negative TIR brightness temperature difference (BTD) signal typically used for volcanic ash detection. The analysis shown here illustrates the utility of remote sensing data during volcanic crises to measure critical real-time parameters, such as cloud-top heights, changes in ground-based thermal activity, and plume/cloud location.

During an explosive volcanic eruption, accurately determining the height of a volcanic plume or cloud is essential to accurately forecast its motion because volcanic ash transport and dispersion models require the initial plume height as an input parameter. The direct use of satellite infrared temperatures for height determination, one of the most commonly employed methods at the Alaska Volcano Observatory, often does not yield unique solutions for height. This result is documented here for the 2009 eruption of Redoubt Volcano. Satellite temperature heights consistently underestimated the height of ash plumes in comparison to other methods such as ground-based radar and Multi-angle Imaging SpectroRadiometer (MISR) stereo heights. For ash plumes below the tropopause, increasing transparency of a plume begins to affect the accuracy of simple temperature height retrievals soon after eruption. With decreasing opacity, plume temperature heights become increasingly inaccurate. Comparison with dispersion models and aircraft gas flight data confirms that radar and MISR stereo heights are more accurate than basic satellite temperature heights. Even in the cases in which satellite temperature results appeared to be relatively accurate (e.g., for plumes below the tropopause), a mixed signal of plume and ground radiation still presented an issue for almost every event studied. This was true regardless of the fact that a band differencing method was used to remove presumably translucent pixels. The data presented here make a strong case for the use of data fusion in volcano monitoring, as there is a need to confirm satellite temperature heights with other height data. If only basic satellite temperature heights are available for a given eruption, then these heights must be considered with a significant margin of error.

Over the last 40 years, there have been numerous volcanic eruptions across the North Pacific (NOPAC) region that posed a potential threat to both local communities and transcontinental aircraft. The ability to detect these volcanic clouds using satellite remote sensing and predict their movement by dispersion modeling is a major component of hazard mitigation. The Puff volcanic ash transport and dispersion model, used by the Alaska Volcano Observatory, was used to illustrate the impact that these volcanic ash clouds have made across the NOPAC and entire Polar region over the past 40 years. Nearly, 400 separate ash clouds were analyzed that were either reported or detected to have reached above 6 km (20,000 ft) above sea level, an average of one ash cloud every 1.25 months. Particular events showed that ash clouds can be tracked from Alaska to Greenland (Crater Peak, Mount Spurr in 1992), from Kamchatka to Alaska (Kluvicheskoi Volcano in 1994), from Alaska to California (Mount Cleveland Volcano in 2001) and from multiple events within 1 day (Mount Augustine Volcano in 2006). This study showed the vast number of events that have impacted this Polar region and how tracking them is useful for hazard mitigation.

Ash clouds are one of the major hazards that result from volcanic eruptions. Once an eruption is reported, volcanic ash transport and dispersion (VATD) models are used to forecast the location of the ash cloud. These models require source parameters to describe the ash column for initialization. These parameters include: eruption cloud height and vertical distribution, particle size distribution, and start and end time of the eruption. Further, if downwind concentrations are needed, the eruption mass rate and/or volume of ash need to be known. Upon notification of an eruption, few constraints are typically available on many of these source parameters. Recently, scientists have defined classes of eruption types, each with a set of pre-defined eruption source parameters (ESP). We analyze the August 18, 1992 eruption of the Crater Peak vent at Mount Spurr, Alaska, which is the example case for the Medium Silicic eruption type. We have evaluated the sensitivity of two of the ESP – the grain size distribution (GSD) and the vertical distribution of ash – on the modeled ash cloud. HYSPLIT and Puff VATD models are used to simulate the ash clouds from the different sets of source parameters. We use satellite data, processed through the reverse absorption method, as reference for computing statistics that describe the modeled-to-observed comparison. With the grain size distribution, the three options chosen, (1) an estimated distribution based on past eruption studies, (2) a distribution with finer particles and (3) the National Oceanic and Atmospheric Administration HYSPLIT GSD, have little effect on the modeled ash cloud. For the initial vertical distribution, both linear (uniform concentration throughout the vertical column) and umbrella shapes were chosen. For HYSPLIT, the defined umbrella distribution (no ash below the umbrella), apparently underestimates the lower altitude portions of the ash cloud and as a result has a worse agreement with the satellite detected ash cloud compared to that with the linear vertical distribution for this particular eruption. The Puff model, with a Poisson function to represent the umbrella cloud, gave similar results as for a linear distribution, both having reasonable agreement with the satellite detected cloud. Further sensitivity studies of this eruption, as well as studies using the other source parameters, are needed.

During volcanic eruptions, volcanic ash transport and dispersion models (VATDs) are used to forecast the location and movement of ash clouds over hours to days in order to define hazards to aircraft and to communities downwind. Those models use input parameters, called “eruption source parameters”, such as plume height H, mass eruption rate Ṁ, duration D, and the mass fraction m63 of erupted debris finer than about 4ϕ or 63 μm, which can remain in the cloud for many hours or days. Observational constraints on the value of such parameters are frequently unavailable in the first minutes or hours after an eruption is detected. Moreover, observed plume height may change during an eruption, requiring rapid assignment of new parameters. This paper reports on a group effort to improve the accuracy of source parameters used by VATDs in the early hours of an eruption. We do so by first compiling a list of eruptions for which these parameters are well constrained, and then using these data to review and update previously studied parameter relationships. We find that the existing scatter in plots of H versus Ṁ yields an uncertainty within the 50% confidence interval of plus or minus a factor of four in eruption rate for a given plume height. This scatter is not clearly attributable to biases in measurement techniques or to well-recognized processes such as elutriation from pyroclastic flows. Sparse data on total grain-size distribution suggest that the mass fraction of fine debris m63 could vary by nearly two orders of magnitude between small basaltic eruptions (∼ 0.01) and large silicic ones (> 0.5). We classify eleven eruption types; four types each for different sizes of silicic and mafic eruptions; submarine eruptions; “brief” or Vulcanian eruptions; and eruptions that generate co-ignimbrite or co-pyroclastic flow plumes. For each eruption type we assign source parameters. We then assign a characteristic eruption type to each of the world's ∼ 1500 Holocene volcanoes. These eruption types and associated parameters can be used for ash-cloud modeling in the event of an eruption, when no observational constraints on these parameters are available.

Volcanic eruptions produce ash clouds, which are a major hazard to population centers and the aviation community. Within the North Pacific (NOPAC) region, there have been numerous volcanic ash clouds that have reached aviation routes. Others have closed airports and traveled for thousands of kilometers. Being able to detect these ash clouds and then provide an assessment of their potential movement is essential for hazard assessment and mitigation. Remote sensing satellite data, through the reverse absorption or split window method, is used to detect these volcanic ash clouds, with a negative signal produced from spectrally semi-transparent ash clouds. Single channel satellite is used to detect the early eruption spectrally opaque ash clouds. Volcanic Ash Transport and Dispersion (VATD) models are used to provide a forecast of the ash clouds' future location. The Alaska Volcano Observatory (AVO) remote sensing ash detection system automatically analyzes satellite data of volcanic ash clouds, detecting new ash clouds and also providing alerts, both email and text, to those with AVO. However, there are also non-volcanic related features across the NOPAC region that can produce a negative signal. These can complicate alerts and warning of impending ash clouds. Discussions and examples are shown of these non-volcanic features and some analysis is provided on how these features can be discriminated from volcanic ash clouds. Finally, there is discussion on how information of the ash cloud such as location, particle size and concentrations, could be used as VATD model initialization. These model forecasts could then provide an improved assessment of the clouds' future movement.

On 11 January 2006, Mount Augustine volcano in southern Alaska began erupting after 20-year repose. The Anchorage Forecast Office of the National Weather Service (NWS) issued an advisory on 28 January for Kodiak City. On 31 January, Alaska Airlines cancelled all flights to and from Anchorage after multiple advisories from the NWS for Anchorage and the surrounding region. The Alaska Volcano Observatory (AVO) had reported the onset of the continuous eruption. AVO monitors the approximately 100 active volcanoes in the Northern Pacific. Ash clouds from these volcanoes can cause serious damage to an aircraft and pose a serious threat to the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. Within AVO, a dispersion model has been developed to track the dispersion of volcanic ash clouds. The model, Puff, was used operational by AVO during the Augustine eruptive period. Here, we examine the dispersion of a volcanic ash cloud from Mount Augustine across Alaska from 29 January through the 2 February 2006. We present the synoptic meteorology, the Puff predictions, and measurements from aerosol samplers, laser radar (or lidar) systems, and satellites. UAF aerosol samplers revealed the presence of volcanic aerosols at the surface at sitesmore » where Puff predicted the ash clouds movement. Remote sensing satellite data showed the development of the ash cloud in close proximity to the volcano and a sulfur-dioxide cloud further from the volcano consistent with the Puff predictions. Lidars showed the presence of volcanic aerosol with consistent characteristics aloft over Alaska and were capable of detecting the aerosol, even in the presence of scattered clouds and where the cloud is too thin/disperse to be detected by remote sensing satellite data. The lidar measurements revealed the different trajectories of ash consistent with the Puff predictions. Dispersion models provide a forecast of volcanic ash cloud movement that might be undetectable by any other means but are still a significant hazard. Validation is the key to assessing the accuracy of any future predictions. The study highlights the use of multiple and complementary observations used in detecting the trajectory ash cloud, both at the surface and aloft within the atmosphere.« less

Bezymianny volcano, Kamchatka Peninsula, Russia, is one of the most active volcanoes in the North Pacific (NOPAC) region and erupts violently on average every 6 months. We report the SO2 cloud mass, emission and transport rates for the eruption of Bezymianny on 13-14 January 2004, and discuss the issues associated with determining SO2 production and transfer to the atmosphere from NOPAC volcanoes. During the 13-14 January 2004 eruption, Bezymianny was observed twice by the MODerate Resolution Imaging Spectroradiometer (MODIS) at 0025 and 0210 UTC on 14 January. Using a retrieval based on the 8.6 µm SO2 infrared absorption feature, MODIS yielded a total cloud mass of 34.6±5.19 kt of SO2, an SO2 emission rate of ∼(4.9×103)±(9.12×102) kg s-1, and a transport rate of ∼16.5 m s-1. We tested the sensitivity of the SO2 algorithm to the following input parameters: cloud top height, atmospheric profile, spectral emissivity of the ground and maximum SO2 threshold. The retrieval is sensitive to the atmospheric profile and is particularly dependent on the choice of background emissivity. Multiple background emissivity spectra, obtained over homogeneous backgrounds, reduce errors in the retrieval, when compared to single, less homogeneous emissivity regions.

There are over 100 active volcanoes in the North Pacific (NOPAC) region, most of which are located in sparsely populated areas. Dispersion models play an important role in forecasting the movement of volcanic ash clouds by complementing both remote sensing data and visual observations from the ground and aircraft. Puff is a three-dimensional dispersion model, primarily designed for forecasting volcanic ash dispersion, used by the Alaska Volcano Observatory and other agencies. Since early 2007, the model is in an automated mode to predict the movement of airborne volcanic ash at multiple elevated alert status volcanoes worldwide to provide immediate information when an eruption occurs. Twelve of the predictions are within the NOPAC region, nine more within the southern section of the Pacific ring of fire and the others are in Europe and the Caribbean. Model forecasts are made for initial ash plumes ranging from 4 to 20 km altitude above sea level and for a 24-h forecast period. This information is made available via the Puff model website. Model results can be displayed in Virtual Globes for three-dimensional visualization. Here, we show operational Puff predictions in two and three-dimensions in Google Earth®, both as iso-surfaces and particles, and study past eruptions to illustrate the capabilities that the Virtual Globes can provide. In addition, we show the opportunity that Google Maps® provides in displaying Puff operational predictions via an application programming web interface and how radiosonde data (vertical soundings) and numerical weather prediction vertical profiles can be displayed in Virtual Globes for assisting in estimating ash cloud heights.

The focus of this book is to highlight applications and analysis of data from satellite-borne instruments for monitoring and interpreting volcanic activity. In this introductory chapter, we abbreviate ‘‘data from satellite-borne instruments’’ to satellite data. The techniques and procedures are described in detail to demonstrate the utility of satellite data. Our region of primary interest is the North Pacific, where many of the techniques were developed or first applied in near-real time. For this region, both monitoring and emergency response applications have been pioneered at the Alaska Volcano Observatory (AVO).

The North Pacific region is remote and vast (5,000 by 2,000 km), and includes several hundred volcanoes in Kamchatka, the Kurile Islands, Alaska, and the northwestern U.S.A. (Figure 9.1).

Airborne ash probability distribution (AAPD) maps have been generated to show the distribution of airborne volcanic ash in the North Pacific (NOPAC) region by simulating volcanic eruption clouds from 22 of the 100 most historically active volcanoes in the region. The PUFF ash-dispersion model was run daily using archived wind field data between 1994–1995 and 1997–2001 for low and high aircraft flight levels. Subsequent statistics are generated representing the distribution of simulated airborne ash at 6- and 24-h intervals, defining the regions most likely to contain airborne ash and the direction and distance a volcanic ash cloud may propagate from a given volcano. The AAPD maps show the extent of ash from a given volcano can encompass all of Alaska, most of the North Pacific Ocean, portions of northwestern North America, regions as far south as 35°N, regions over the western Arctic Ocean, and portions of eastern Russia. In general, low-altitude atmospheric regions (3–8 km ASL) are more susceptible to airborne volcanic ash when compared to regions above 8 km ASL due to the eruption characteristics of volcanoes in the North Pacific and the region's atmospheric profile. The results indicate that the paths of many NOPAC air traffic routes coincide with airborne ash distribution probability maxima. The upper atmospheric region most likely to contain airborne ash is located off the eastern coast of the Kamchatkan Peninsula, and is generally centered over the heavy air traffic flight corridor of the NOPAC. Although this paper focuses on the NOPAC region, the technique can be directly applied to other regions characterized by active volcanism.

Satellite data were the primary source of information for the eruption of Mt. Cleveland, Alaska on 19 February, and 11 and 19 March 2001. Multiple data sets were used pre-, syn- and post-eruption to mitigate the hazard and determine an eruption chronology. The 19 February eruption was the largest of the three, resulting in a volcanic cloud that formed an arc over 1000 km long, moved to the NE across Alaska and was tracked using satellite data over more than a 50-h period. The volcanic cloud was “concurrently” detected on the GOES, AVHRR and MODIS data at various times and their respective signals compared. All three sensors detected a cloud that had a very similar shape and position but there were differences in their areal extent and internal structural detail. GOES data showed the largest volcanic cloud in terms of area, probably due to its oblique geometry. MODIS bands 31 and 32, which are comparable to GOES and AVHRR thermal infrared wavelengths, were the least effective single channels at detecting the volcanic cloud of those investigated (MODIS bands 28, 29, 31 and 32). MODIS bands 28 and 29 detected the largest volcanic clouds that could easily be distinguished from weather clouds. Of the split-window data, MODIS bands 29 minus band 32 detected the largest cloud, but the band 31 minus band 32 data showed the volcanic cloud with the most internal structural detail. The Puff tracking model accurately tracked the movement, and predicted the extent and shape of this complex cloud even into areas beyond satellite detection. Numerous thermal anomalies were also observed during the eruption on the twice-daily AVHRR data and the high spatial-resolution Landsat data. The high-resolution Radarsat data showed that the AVHRR thermal anomalies were due to lava and debris flow features and a newly formed fan along the west coast of the island. Field observations and images from a hand-held Forward Looking Infrared Radiometer (FLIR) showed that the flow features were ′a′a lava, debris flows and a warm debris fan along the west coast. Real-time satellite data were the primary tool used to monitor the eruption, track changes and to mitigate hazards. High-resolution data, even though coverage is infrequent, were critical in helping to identify volcanic processes and to compile an eruption chronology.

Field mapping of young lava flows at Aleutian volcanoes is logistically difficult, and the utility of optical images from aircraft or satellites for this purpose is greatly reduced by persistent cloud cover. These factors have hampered earlier estimates of the areas and volumes of three young lava flows at Westdahl Volcano, including its most recent (1991–1992) flow. We combined information from synthetic aperture radar (SAR) images with multispectral Landsat-7 data to differentiate the 1991–1992 flow from the 1964 flow and a pre-1964 flow, and to calculate the flow areas (8.4, 9.2, and 7.3 km 2 , respectively). By differencing a digital elevation model (DEM) from the 1970–1980s with a DEM from the Shuttle Radar Topography Mission (SRTM) in February 2000, we estimated the average thickness of the 1991–1992 flow to be 13 m, which reasonably agrees with field observations (5–10 m). Lava-flow maps produced in this way can be used to facilitate field mapping and flow-hazards assessment, and to study magma-supply dynamics and thus to anticipate future eruptive activity. Based on the recurrence interval of recent eruptions and the results of this study, the next eruption at Westdahl may occur before the end of this decade.

Mud volcanoes are relatively small spatter cones that erupt water-laden mud and gases, and occur throughout the world. For many mud volcanoes, the eruption of warm mud (10–40°C) can be detected with high-resolution thermal satellite imagery. We demonstrate the utility of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery for thermal monitoring of active mud volcanism. We constrain the temperature and area of active mud discharge and estimate surface heat flux for two isolated mud volcanoes in the Copper River Basin, Alaska using Band 6 (10.4–12.5 μm). The heat flux results span a wide range due to uncertainties in the environmental conditions at the time of image acquisition, but can be constrained to be less than 0.24 MW for each of the two mud volcanoes considering previously published field measurements. With this higher-resolution Band 6 on the ETM+ sensor, as well as the high-resolution thermal bands on the ASTER sensor, reliable monitoring of mud volcanism on this scale is possible for the first time.

Okmok Volcano, in the eastern Aleutian Islands, erupted in February and March of 1997 producing a 6-km-long lava flow and low-level ash plumes. This caldera is one of the most active in the Aleutian Arc, and is now the focus of international multidisciplinary studies. A synthesis of remotely sensed data (AirSAR, derived DEMs, Landsat MSS and ETM+ data, AVHRR, ERS, JERS, Radarsat) has given a sequence of events for the virtually unobserved 1997 eruption. Elevation data from the AirSAR sensor acquired in October 2000 over Okmok were used to create a 5-m resolution DEM mosaic of Okmok Volcano. AVHRR nighttime imagery has been analyzed between February 13 and April 11, 1997. Landsat imagery and SAR data recorded prior to and after the eruption allowed us to accurately determine the extent of the new flow. The flow was first observed on February 13 without precursory thermal anomalies. At this time, the flow was a large single lobe flowing north. According to AVHRR Band 3 and 4 radiance data and ground observations, the first lobe continued growing until mid to late March, while a second, smaller lobe began to form sometime between March 11 and 12. This is based on a jump in the thermal and volumetric flux determined from the imagery, and the physical size of the thermal anomalies. Total radiance values waned after March 26, indicating lava effusion had ended and a cooling crust was growing. The total area (8.9 km 2 ), thickness (up to 50 m) and volume (1.54×10 8 m 3 ) of the new lava flow were determined by combining observations from SAR, Landsat ETM+, and AirSAR DEM data. While the first lobe of the flow ponded in a pre-eruption depression, our data suggest the second lobe was volume-limited. Remote sensing has become an integral part of the Alaska Volcano Observatory’s monitoring and hazard mitigation efforts. Studies like this allow access to remote volcanoes, and provide methods to monitor potentially dangerous ones.

Shishaldin Volcano, Unimak Island Alaska, began showing signs of thermal unrest in satellite images on 9 February 1999. A thermal anomaly and small steam plume were detected at the summit of the volcano in short-wave thermal infrared AVHRR (advanced very high resolution radiometer) satellite data. This was followed by over 2 months of changes in the observed thermal character of the volcano. Initially, the thermal anomaly was only visible when the satellite passed nearly directly over the volcano, suggesting a hot source deep in the central crater obscured from more oblique satellite passes. The "zenith angle" needed to see the anomaly increased with time, presumably as the thermal source rose within the conduit. Based on this change, an ascent rate of ca. 14 m per day for the thermal source was estimated, until it reached the summit on around 21 March. It is thought that Strombolian activity began around this time. The precursory activity culminated in a sub-Plinian eruption on 19 April, ejecting ash to over 45,000 ft. (13,700 m). The thermal energy output through the precursory period was calculated based on geometric constraints unique to Shishaldin. These calculations show fluctuations that can be tied to changes in the eruptive character inferred from seismic records and later geologic studies. The remote location of this volcano made satellite images a necessary observation tool for this eruption. To date, this is the longest thermal precursory activity preceding a sub-Plinian eruption recorded by satellite images in the region. This type of thermal monitoring of remote volcanoes is central in the efforts of the Alaska Volcano Observatory to provide timely warnings of volcanic eruption, and mitigate their associated hazards to air-traffic and local residents.

Seasat, Earth Resource Satellite (ERS-1) and Japan Earth Resource Satellite (JERS-1) Synthetic Aperture Radar (SAR) data were used to investigate surface geomorphic and topographic changes caused by volcanic eruptions of Westdahl Volcano, Alaska. This volcano is located at the west end of Unimak Island, Alaska, approximately 1200 km southwest of Anchorage. This remote, ice-capped volcano has erupted three times in the last 34 years. The eruptions have melted portions of the ice-cap which have been replenished by winter snow. Changes in terrain were studied by comparing seasonal and inter-annual SAR data acquired over a 17 year period prior to, during and after two eruptions. The SAR data provided a record of geological and environmental processes between 1978 and 1995. Time sequential data recorded the formation of landforms and subsequent burial by snow. A series of winter images showed that changing environmental conditions, thought to be predominantly snow moisture, influence the detection and ability ...

The 1996 eruption of Pavlof volcano provided a unique opportunity for the combined use of satellite and seismic monitoring techniques. Advanced Very High Resolution Radiometer (AVHRR) satellite data provided observations of both thermal anomalies and eruption plumes. A thermal anomaly appeared in AVHRR data 3 days prior to the eruption and continued to grow until shortly before the height of eruptive activity. Eruption plumes observed in AVHRR images ranged from tens to hundreds of kilometers in length; ground observations indicate that they reached elevations between 2,750 m and 9,150 m above sea level. The largest, ash-rich plumes reached great lengths (>200 km) due to increased wind velocity at altitude; small, steam-rich plumes were less predictable. Seismic data were received from a newly installed network around the volcano. Stations at intermediate distances (from 8 to 12 km) from the volcano provided the most useful information for monitoring the eruption. As is typical for Pavlof, the eruption produced no A-type events, and monitoring was based exclusively on tremor and explosion events. Broad increases in tremor amplitude occurred before the appearance of the largest eruption plumes. The combination of satellite and seismic data revealed several interesting correlations. The sizes of thermal anomalies increased concurrently with the number of explosions for small plumes and with plume height for the largest plumes. Further, a general relationship between plume height and tremor amplitude was observed for the largest eruption plumes. Finally, the combination of monitoring methods revealed the general course of the eruption sequence; steady increases in the size of the thermal anomaly and seismicity presaged the eruption of several large plumes.

It has been observed that arctic coastal regions which receive river discharge show significant ice regression in advance of other coastal areas without this source of sensible heat. This phenomena has been particularly apparent on satellite imagery. The work reported here attempts (1) to quantify and assess the influence of springtime river discharge on the removal of nearshore ice and (2) to demonstrate the utility of satellite imagery as a source of data to “drive” a model assessing the influence of springtime river discharge on the removal of nearshore ice. Central to this work is a sequence of advanced very high resolution radiometer images of the Mackenzie Delta region, Northwest Territories, Canada. These images constitute a database establishing the temporal sequence of observable breakup events from which a thermodynamic model for the ice decay can be parameterized. The emphases of this model are the influence of the riverine sensible heat on the melting of sea ice and the ability of satellite imagery to monitor this process. For simplicity, climatological values rather than meteorological values for atmospheric and solar influences have been used. The results suggest that the river discharge supplies a significant amount of sensible heat to the base of the nearshore ice, accounting for nearly half of the energy required to melt the ice cover. As a result, the coastal ice is removed 7–14 days in advance of areas without significant river discharge.

[1] Throughout February and March 1997, Okmok Volcano, in the eastern Aleutian Islands of Alaska, erupted a 6-km-long lava flow of basaltic ′a′a within its caldera. In the first part of the study a numerical model for lava flow cooling was developed by Patrick et al. and applied to the flow to better understand the nature of its cooling. In this second part of the study, the model predictions for lava surface temperature over a 200-day cooling period were compared to advanced very high resolution radiometer (AVHRR) thermal imagery. Various methods were used to extract the subpixel lava temperature from the AVHRR pixel-integrated values, including the dual-band method and pixel merging. Inherent to these approaches is the multicomponent modeling of the lava surface temperature. Whereas active flows have been shown to have several thermal components, so, too, do flows undergoing extended cooling. Because of the dependence of the methods on the AVHRR instantaneous field of view (IFOV), the scan-dependent IFOV dimensions and overlap values were considered. Results from Patrick et al. indicate that convective heat loss from the surface largely controls surface temperature during extended cooling, but the functions governing this heat loss mechanism are poorly understood. AVHRR-derived temperatures from this part of the study suggest that values for the convective heat transfer coefficient for this flow were most commonly between 50 and 100 W m−2 K−1 and generally above 25 W m−2 K−1. These results are in agreement with previously measured values from the field but are significantly higher than those assumed in other remote sensing studies of cooling lava. Also, the AVHRR data corroborate the modeled prediction of seasonal warming of the lava surface.

Multi-temporal satellite images, field observations and field measurements were used to investigate the mechanisms by which sea ice melts offshore from the Mackenzie River Delta. Satellite data recorded between April and August 1986 were corrected to a map projection and calibrated such that albedo and temperature values could be compared. Three stages in the melting of sea ice were identified: flooding (overflows), insolation and melting by warm river water. The albedo values of overflows were as much as 1/7 that of ice values while the albedo of ice decreased by 1/3 over the summer. Approximately two weeks after the overflows develop, sea surface temperatures rise as the river-discharge peaks and becomes the dominant source of energy. By this process, ice removal in the delta regime is initiated two months earlier than adjacent coasts with minimal runoff. However, the net result is only a two-week acceleration of ice removal in the delta region.

Erratum to ‘A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions’ by Mastin et al. [J. Volcanol. Geotherm. Res. 188(2009)1–21] L.G. Mastin ⁎, M. Guffanti , R. Servranckx , P. Webley , S. Barsotti , K. Dean , A. Durant , J.W. Ewert , A. Neri , W.I. Rose , D. Schneider , L. Siebert , B. Stunder , G. Swanson , A. Tupper , A. Volentik , C.F. Waythomas h

[1] We applied the PUFF algorithm [Searcy et al., 1998] to simulate the space-time evolution of the eruptive cloud generated by one of the main paroxysms to have occurred this past century at Etna volcano, namely the 22 July 1998 explosive event at the Voragine summit crater. The comparison of PUFF simulations to satellite images of the ash cloud at different times allowed us to estimate several parameters of the eruptive event, such as onset time, duration, ash cloud height and shape, and pyroclast size. Based on this analysis, we concluded that the paroxysm started around 1645 GMT, lasted between 20 and 40 min, and generated a Poissonian-shaped ash column nearly 13 km high and composed of particles with a mean diameter (MD) of 10−3 m and size logarithmic standard deviation (LSD) equal to 1.5. The PUFF simulations using horizontal and vertical diffusivity values of 5000 and 10 m2 s−1, respectively, provided the best agreement to the eruption clouds observed on satellite images. The results were compared to the information available in the literature concerning the eruption, e.g., volcanological, video camera, and volcanic tremor data. The analysis showed that the method of simulating the eruptive clouds and comparing simulations to satellite images can give a contribution to the study of paroxysmal events generated by the Etna volcano. Also, the degree of accuracy of the cloud simulation leads us to be optimistic about the potential of using this method as a tool for hazard mitigation in the Etna region, with particular applications to air traffic.

Mt. Cleveland is one of more than 40 active volcanoes in Alaska that is monitored by the Alaska Volcano Observatory (AVO). It is located on the western half of Chuginadak, a remote and uninhabited island in the east central Aleutians that lies 1526 km southwest of Anchorage. The closest inhabited community, Nikolski, is 75 km to the east on Umnak Island (Figure 1). Mt. Cleveland erupted explosively on 19 February and on 11 and 19 March 2001. Because the volcano is not yet monitored with seismic, deformation, or other geophysical instruments, satellite imagery was the only effective tool for detecting and monitoring this activity. Eruption clouds and elevated surface temperatures were detected on multiple satellite data sets. The largest eruption was in February. This first eruption cloud and the subsequent wave of ash (Figure 1) that drifted across Alaska extended up to flight levels and prompted cancellation and re-routing of air traffic throughout the North Pacific region on 19 and 20 February.

Satellite monitoring of remote volcanoes is greatly benefitting the Alaska Volcano Observatory (AVO), and last year's eruption of the Okmok Volcano in the Aleutian Islands is a good case in point. The facility was able to issue and refine warnings of the eruption and related activity quickly, something that could not have been done using conventional seismic surveillance techniques, since seismometers have not been installed at these locations. AVO monitors about 100 active volcanoes in the North Pacific (NOPAC) region, but only a handful are observed by costly and logistically complex conventional means. The region is remote and vast, about 5000 × 2500 km, extending from Alaska west to the Kamchatka Peninsula in Russia (Figure 1). Warnings are transmitted to local communities and airlines that might be endangered by eruptions. More than 70,000 passenger and cargo flights fly over the region annually, and airborne volcanic ash is a threat to them. Many remote eruptions have been detected shortly after the initial magmatic activity using satellite data, and eruption clouds have been tracked across air traffic routes. Within minutes after eruptions are detected, information is relayed to government agencies, private companies, and the general public using telephone, fax, and e-mail. Monitoring of volcanoes using satellite image data involves direct reception, real-time monitoring, and data analysis. Two satellite data receiving stations, located at the Geophysical Institute, University of Alaska Fairbanks (UAF), are capable of receiving data from the advanced very high resolution radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites and from synthetic aperture radar (SAR) equipped satellites.

The early phreatomagmatic and magmatic explosive activity of Redoubt Volcano, December 14–16, 1989, produced several ashladen eruption columns that caused significant damage to jet aircraft. The major aircraft-ash incident occurred December 15 at 1150 AST, when a KLM Boeing 747 jet aircraft, enroute from Amsterdam to Anchorage with 231 passengers and 14 crew members, flew through an ash plume east of Talkeetna, Alaska, at an altitude of 7.5 km and experienced sudden shutdown of all four engines. For 12 minutes the jet glided steeply from 7.5 km to 3.5 km before the crew managed to restart the engines after seven or eight tries. The plane came within about 1500 m of the mountain tops before landing safely at Anchorage International Airport.

The photographic processing of color Landsat imagery was evaluated to determine the optimal enhancement techniques. Twenty-six images were examined to explore the effects of gamma values upon image interpretation in a subarctic environment. Gamma values were varied on the images of bands 4 through 7 prior to the creation of the color composites. This yielded color-composited images with various color balances. These images were evaluated in terms of visible geological features (drainage, lineaments, landforms, etc.) and landcover features (exposed rock and ground, coniferous forest, etc.). The results indicate that the most informative images are created by using gamma values of 2.0 for band 4, 1.0 for band 5, and 2.0 for band 6 or 7. Other photographic enhancements tend to enhance some features at the expense of others.

The ecosystem of the northern Bering-Sea shelf was studied using data from the NOAA Very High Resolution Radiometer and AVHRR and the Landsat MSS and Thematic Mapper (TM) in conjunction with shipboard measurements. Emphasis was placed on the influence of the Yukon River on this inner shelf environment and on the evaluation of the utility of the new Landsat TM data for oceanography. It was found that the patterns of water mass distribution obtained from satellite images agreed reasonably well with the areal patterns of temperature, salinity, and phytoplankton distributions. The AVHRR, MSS, and TM data show that the Yukon-River discharge is warmer and more turbid than the surrounding coastal water that originates to the south; thus, the Yukon water contributes to the higher temperatures and lower transmissivity of the coastal water. The high resolution of the TM thermal IR band made it possible to observe complex patterns and structures in the surface water that could not be resolved on previous data sets.

High-altitude radar and thermal imagery collected by the NASA research aircraft WB57F were used to examine the structural setting and distribution of radiant temperatures of geothermal anomalies in the Pilgrim Springs, Alaska area. Like-polarized radar imagery with perpendicular look directions provides the best structural data for lineament analysis, although more than half the mapped lineaments are easily detectable on conventional aerial photography. Radiometer data and imagery from a thermal scanner were used to evaluate radiant surface temperatures, which ranged from 3 to 17 C. The evening imagery, which utilized density-slicing techniques, detected thermal anomalies associated with geothermal heat sources. The study indicates that high-altitude predawn thermal imagery may be able to locate relatively large areas of hot ground in site-specific studies in the vegetated Alaskan terrain. This imagery will probably not detect gentle lateral gradients.