scholarly journals Plume propagation direction determination with SO<sub>2</sub> cameras

2017 ◽  
Vol 10 (3) ◽  
pp. 979-987 ◽  
Author(s):  
Angelika Klein ◽  
Peter Lübcke ◽  
Nicole Bobrowski ◽  
Jonas Kuhn ◽  
Ulrich Platt
Keyword(s):  
Time Series ◽  
Wind Direction ◽  
Column Density ◽  
Image Plane ◽  
Propagation Direction ◽  
Volcanic Plume ◽  
High Temporal Resolution ◽  
Good Precision ◽  
So2 Flux ◽  
Flux Measurements

Abstract. SO2 cameras are becoming an established tool for measuring sulfur dioxide (SO2) fluxes in volcanic plumes with good precision and high temporal resolution. The primary result of SO2 camera measurements are time series of two-dimensional SO2 column density distributions (i.e. SO2 column density images). However, it is frequently overlooked that, in order to determine the correct SO2 fluxes, not only the SO2 column density, but also the distance between the camera and the volcanic plume, has to be precisely known. This is because cameras only measure angular extents of objects while flux measurements require knowledge of the spatial plume extent. The distance to the plume may vary within the image array (i.e. the field of view of the SO2 camera) since the plume propagation direction (i.e. the wind direction) might not be parallel to the image plane of the SO2 camera. If the wind direction and thus the camera–plume distance are not well known, this error propagates into the determined SO2 fluxes and can cause errors exceeding 50 %. This is a source of error which is independent of the frequently quoted (approximate) compensation of apparently higher SO2 column densities and apparently lower plume propagation velocities at non-perpendicular plume observation angles.Here, we propose a new method to estimate the propagation direction of the volcanic plume directly from SO2 camera image time series by analysing apparent flux gradients along the image plane. From the plume propagation direction and the known location of the SO2 source (i.e. volcanic vent) and camera position, the camera–plume distance can be determined. Besides being able to determine the plume propagation direction and thus the wind direction in the plume region directly from SO2 camera images, we additionally found that it is possible to detect changes of the propagation direction at a time resolution of the order of minutes. In addition to theoretical studies we applied our method to SO2 flux measurements at Mt Etna and demonstrate that we obtain considerably more precise (up to a factor of 2 error reduction) SO2 fluxes. We conclude that studies on SO2 flux variability become more reliable by excluding the possible influences of propagation direction variations.

scholarly journals Plume Propagation Direction Determination with SO<sub>2</sub> Cameras

2016 ◽  
Author(s):  
Angelika Klein ◽  
Peter Lübcke ◽  
Nicole Bobrowski ◽  
Jonas Kuhn ◽  
Ulrich Platt
Keyword(s):  
Time Series ◽  
Wind Direction ◽  
Column Density ◽  
Image Plane ◽  
Propagation Direction ◽  
Volcanic Plume ◽  
High Temporal Resolution ◽  
Good Precision ◽  
So2 Flux ◽  
Flux Measurements

Abstract. SO2 cameras are becoming an established tool for measuring sulphur dioxide (SO2) fluxes in volcanic plumes with good precision and high temporal resolution. The primary result of SO2 camera measurements are time series of two-dimensional SO2 column density distributions (i.e. SO2 column density images). However it is frequently overlooked that in order to determine the correct SO2 fluxes, not only the SO2 column density, but also the distance between the camera and the volcanic plume have to be precisely known. This is because cameras only measure angular extensions of objects while flux measurements require knowledge of the spatial plume extension. The distance to the plume may vary within the image array (i.e. the field of view of the SO2 camera) since the plume propagation direction (i.e. the wind direction) might not be parallel to the image plane of the SO2 camera. If the wind direction and thus the camera-plume distance is not well known, this error propagates into the determined SO2 fluxes and can cause errors exceeding 50 %. This is a source of error which is independent of the frequently quoted (approximate) compensation of apparently higher SO2 column densities and apparently lower plume propagation velocities at non-perpendicular plume observation angles. Here, we propose a new method to estimate the propagation direction of the volcanic plume directly from SO2 camera image time series by analysing apparent flux gradients along the image plane. From the plume propagation direction and the known location of the SO2 source (i.e. volcanic vent) and camera position the camera-plume distance can be determined. Besides being able to determine the plume propagation direction, and thus the wind direction in the plume region, directly from SO2 camera images, we additionally found, that it is possible to detect changes of the propagation direction at a time resolution on the order of minutes. In addition to theoretical studies we applied our method to SO2 flux measurements at Mt. Etna and demonstrate that we obtain considerably more precise (up to a factor of 2 error reduction) SO2 fluxes. We conclude that studies on SO2 flux variability become more reliable by excluding the possible influences of propagation direction variations.

scholarly journals Satellite-derived SO<sub>2</sub> flux time-series and magmatic processes during the 2015 Calbuco eruptions

2017 ◽  
Author(s):  
Federica Pardini ◽  
Mike Burton ◽  
Fabio Arzilli ◽  
Giuseppe La Spina ◽  
Margherita Polacci
Keyword(s):  
Time Series ◽  
Melt Inclusion ◽  
Computational Cost ◽  
High Temporal Resolution ◽  
Climatic Impact ◽  
So2 Emissions ◽  
Plume Height ◽  
So2 Flux ◽  
Magmatic Processes ◽  
Average Flux

Abstract. Quantifying time-series of sulphur dioxide (SO2) emissions during explosive eruptions provides insight into volcanic processes, assists in volcanic hazard mitigation, and permits quantification of the climatic impact of major eruptions. While volcanic SO2 is routinely detected from space during eruptions, the retrieval of plume injection height and SO2 flux time-series remains challenging. Here we present a new numerical method based on forward- and backward-trajectory analyses which enable such time-series to be robustly determined. The method is applied to satellite images of volcanic eruption clouds through the integration of the HYSPLIT software with custom-designed Python routines in a fully automated manner. Plume injection height and SO2 flux time-series are computed with a period of ~ 10 minutes with low computational cost. Using this technique, we investigated the SO2 emissions from two sub-Plinian eruptions of Calbuco, Chile, produced in April 2015. We found a mean injection height above the vent of ~ 15 km for the two eruptions, with overshooting tops reaching ~ 20 km. We calculated a total of 300 ± 46 kt of SO2 released almost equally during both events, with 160 ± 30 kt produced by the first event and 140 ± 35 kt by the second. The retrieved SO2 flux time-series show an intense gas release during the first eruption (average flux of 2560 kt day−1), while a lower SO2 flux profile was seen for the second (average flux 560 kt day−1), suggesting that the first eruption was richer in SO2. This result is exemplified by plotting SO2 flux against retrieved plume height above the vent, revealing distinct trends for the two events. We propose that a pre-erupted exsolved volatile phase was present prior to the first event, which could have led to the necessary overpressure to trigger the eruption. The second eruption, instead, was mainly driven by syneruptive degassing. This hypothesis is supported by melt inclusion measurements of sulfur concentrations in plagioclase phenocrysts and groundmass glass of tephra samples through electron microprobe analysis. This work demonstrates that detailed interpretations of sub-surface magmatic processes during eruptions are possible using satellite SO2 data. Quantitative comparisons of high temporal resolution plume height and SO2 flux time-series offer a powerful tool to examine processes triggering and controlling eruptions. These novel tools open a new frontier in space-based volcanological research, and will be of great value when applied to remote, poorly monitored volcanoes, and to major eruptions that can have regional and global climate implications through, for example, influencing ozone depletion in the stratosphere and light scattering from stratospheric aerosols.

scholarly journals Inverting for volcanic SO2 flux at high temporal resolution using spaceborne plume imagery and chemistry-transport modelling: the 2010 Eyjafjallajökull eruption case study

2013 ◽  
Vol 13 (17) ◽  
pp. 8569-8584 ◽  
Author(s):  
M. Boichu ◽  
L. Menut ◽  
D. Khvorostyanov ◽  
L. Clarisse ◽  
C. Clerbaux ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Spatial Scales ◽  
Source Parameters ◽  
Volcanic Plume ◽  
High Temporal Resolution ◽  
Transport Modelling ◽  
Important Indicator ◽  
So2 Flux ◽  
Volcanic Source

Abstract. Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modelling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. We show that no a priori knowledge on the SO2 flux is required for this reconstruction. The initialisation of chemistry-transport modelling with this reconstructed source allows for reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a timescale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.

scholarly journals Inverting for volcanic SO<sub>2</sub> flux at high temporal resolution using spaceborne plume imagery and chemistry-transport modelling: the 2010 Eyjafjallajökull eruption case-study

2013 ◽  
Vol 13 (3) ◽  
pp. 6553-6588 ◽  
Author(s):  
M. Boichu ◽  
L. Menut ◽  
D. Khvorostyanov ◽  
L. Clarisse ◽  
C. Clerbaux ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Spatial Scales ◽  
Source Parameters ◽  
Volcanic Plume ◽  
High Temporal Resolution ◽  
Transport Modelling ◽  
Important Indicator ◽  
So2 Flux ◽  
Volcanic Source

Abstract. Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time-variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modeling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to better characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case-study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time-series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. The initialisation of chemistry-transport modelling with this reconstructed source allows for a reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a time scale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.

scholarly journals iFit: An intensity based retrieval for volcanic SO<sub>2</sub> from scattered sunlight UV spectra

2018 ◽  
Author(s):  
Ben Esse ◽  
Mike Burton ◽  
Matthew Varnam ◽  
Ryunosuke Kazahaya ◽  
Giuseppe Salerno
Keyword(s):  
Column Density ◽  
Uv Spectra ◽  
Optical Absorption Spectroscopy ◽  
Test Cases ◽  
Reference Spectrum ◽  
Monitoring Networks ◽  
Measured Intensity ◽  
So2 Flux ◽  
Flux Measurements ◽  
Novel Method

Abstract. Accurate quantification of the sulphur dioxide (SO2) flux from volcanoes provides both an insight into magmatic processes and a powerful monitoring tool for hazard mitigation, with miniature ultraviolet spectrometers becoming the go-to method for SO2 flux measurements globally. The most common analysis method for these spectrometers is Differential Optical Absorption Spectroscopy (DOAS), in which a reference spectrum taken outside the plume is used to quantify the SO2 column density inside the plume. This can lead to problems if the reference spectrum is contaminated with SO2 as this leads to systematic underestimates in the retrieved SO2 column density. We present a novel method, named “iFit”, which retrieves the SO2 column density from UV spectra by directly fitting the measured intensity spectrum using a high resolution solar reference spectrum. This has a number of advantages over the traditional DOAS method, primarily by eliminating the requirement for a measured reference spectrum. We show that iFit can accurately retrieve SO2 column densities in a series of test cases, finding excellent agreement with existing methods without the use of a reference spectrum. We propose that iFit is well suited to application to both traverse measurements and permanent scanning stations, and shows strong potential for integration into volcano monitoring networks at observatories.

scholarly journals High temporal resolution SO2 flux measurements at Erebus volcano, Antarctica

2010 ◽  
Vol 190 (3-4) ◽  
pp. 325-336 ◽  
Author(s):  
Marie Boichu ◽  
Clive Oppenheimer ◽  
Vitchko Tsanev ◽  
Philip R. Kyle
Keyword(s):  
Temporal Resolution ◽  
High Temporal Resolution ◽  
So2 Flux ◽  
Flux Measurements ◽  
Erebus Volcano

scholarly journals Assessment of Automatically Monitored Water Levels and Water Quality Indicators in Rivers with Different Hydromorphological Conditions and Pollution Levels in Greece

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 86
Author(s):  
Angeliki Mentzafou ◽  
George Varlas ◽  
Anastasios Papadopoulos ◽  
Georgios Poulis ◽  
Elias Dimitriou
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Quality Indicators ◽  
High Frequency ◽  
Automatic Monitoring ◽  
Water Levels ◽  
High Temporal Resolution ◽  
Water Quality Indicators ◽  
Pollution Levels ◽  
Riverine Ecosystems

Water resources, especially riverine ecosystems, are globally under qualitative and quantitative degradation due to human-imposed pressures. High-temporal-resolution data obtained from automatic stations can provide insights into the processes that link catchment hydrology and streamwater chemistry. The scope of this paper was to investigate the statistical behavior of high-frequency measurements at sites with known hydromorphological and pollution pressures. For this purpose, hourly time series of water levels and key water quality indicators (temperature, electric conductivity, and dissolved oxygen concentrations) collected from four automatic monitoring stations under different hydromorphological conditions and pollution pressures were statistically elaborated. Based on the results, the hydromorphological conditions and pollution pressures of each station were confirmed to be reflected in the results of the statistical analysis performed. It was proven that the comparative use of the statistics and patterns of the water level and quality high-frequency time series could be used in the interpretation of the current site status as well as allowing the detection of possible changes. This approach can be used as a tool for the definition of thresholds, and will contribute to the design of management and restoration measures for the most impacted areas.

LamaH: Large-sample Data for Hydrology in Central Europe

2021 ◽  
Author(s):  
Christoph Klingler ◽  
Mathew Herrnegger ◽  
Frederik Kratzert ◽  
Karsten Schulz
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Vegetation Indices ◽  
River Network ◽  
Series Data ◽  
High Temporal Resolution ◽  
Stream Length ◽  
Discharge Data ◽  
Large Sample ◽  
Access To Data

&lt;p&gt;Open large-sample datasets are important for various reasons: i) they enable large-sample analyses, ii) they democratize access to data, iii) they enable large-sample comparative studies and foster reproducibility, and iv) they are a key driver for recent developments of machine-learning based modelling approaches.&lt;/p&gt;&lt;p&gt;Recently, various large-sample datasets have been released (e.g. different country-specific CAMELS datasets), however, all of them contain only data of individual catchments distributed across entire countries and not connected river networks.&lt;/p&gt;&lt;p&gt;Here, we present LamaH, a new dataset covering all of Austria and the foreign upstream areas of the Danube, spanning a total of 170.000 km&amp;#178; in 9 different countries with discharge observations for 882 gauges. The dataset also includes 15 different meteorological time series, derived from ERA5-Land, for two different basin delineations: First, corresponding to the entire upstream area of a particular gauge, and second, corresponding only to the area between a particular gauge and its upstream gauges. The time series data for both, meteorological and discharge data, is included in hourly and daily resolution and covers a period of over 35 years (with some exceptions in discharge data for a couple of gauges).&lt;/p&gt;&lt;p&gt;Sticking closely to the CAMELS datasets, LamaH also contains more than 60 catchment attributes, derived for both types of basin delineations. The attributes include climatic, hydrological and vegetation indices, land cover information, as well as soil, geological and topographical properties. Additionally, the runoff gauges are classified by over 20 different attributes, including information about human impact and indicators for data quality and completeness. Lastly, LamaH also contains attributes for the river network itself, like gauge topology, stream length and the slope between two sequential gauges.&lt;/p&gt;&lt;p&gt;Given the scope of LamaH, we hope that this dataset will serve as a solid database for further investigations in various tasks of hydrology. The extent of data combined with the interconnected river network and the high temporal resolution of the time series might reveal deeper insights into water transfer and storage with appropriate methods of modelling.&lt;/p&gt;

scholarly journals A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

2013 ◽  
Vol 17 (6) ◽  
pp. 2121-2129 ◽  
Author(s):  
N. F. Liu ◽  
Q. Liu ◽  
L. Z. Wang ◽  
S. L. Liang ◽  
J. G. Wen ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
Critical Role ◽  
Radiant Energy ◽  
High Temporal Resolution ◽  
Land Surface Parameter ◽  
Temporal Filter ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

Sign in / Sign up

Export Citation Format

Share Document