scholarly journals Estimation of the vertical profile of sulfur dioxide injection into the atmosphere by a volcanic eruption using satellite column measurements and inverse transport modeling

2008 ◽  
Vol 8 (14) ◽  
pp. 3881-3897 ◽  
Author(s):  
S. Eckhardt ◽  
A. J. Prata ◽  
P. Seibert ◽  
K. Stebel ◽  
A. Stohl
Keyword(s):  
Vertical Profile ◽  
Volcanic Ash ◽  
Transport Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
Inversion Method ◽  
Volcanic Plume ◽  
Operational Environment ◽  
Data Set ◽  
Emission Profile

Abstract. An analytical inversion method has been developed to estimate the vertical profile of SO2 emissions from volcanic eruptions. The method uses satellite-observed total SO2 columns and an atmospheric transport model (FLEXPART) to exploit the fact that winds change with altitude – thus, the position and shape of the volcanic plume bear information on its emission altitude. The method finds the vertical emission distribution which minimizes the total difference between simulated and observed SO2 columns while also considering a priori information. We have tested the method with the eruption of Jebel at Tair, Yemen, on 30 September 2007 for which a comprehensive observational data set from various satellite instruments (AIRS, OMI, SEVIRI, CALIPSO) is available. Using satellite data from the first 24 h after the eruption for the inversion, we found an emission maximum near 16 km above sea level (a.s.l.), and secondary maxima near 5, 9, 12 and 14 km a.s.l. 60% of the emission occurred above the tropopause. The emission profile obtained in the inversion was then used to simulate the transport of the plume over the following week. The modeled plume agrees very well with SO2 total columns observed by OMI, and its altitude agrees with CALIPSO aerosol observations to within 1–2 km. The inversion result is robust against various changes in both the a priori and the observations. Even when using only SEVIRI data from the first 15 h after the eruption, the emission profile was reasonably well estimated. The method is computationally very fast. It is therefore suitable for implementation within an operational environment, such as the Volcanic Ash Advisory Centers, to predict the threat posed by volcanic ash for air traffic. It could also be helpful for assessing the sulfur input into the stratosphere, be it in the context of volcanic processes or also for proposed geo-engineering techniques to counteract global warming.

scholarly journals Estimation of the vertical profile of sulfur dioxide injection into the atmosphere by a volcanic eruption using satellite column measurements and inverse transport modeling

2008 ◽  
Vol 8 (1) ◽  
pp. 3761-3805 ◽  
Author(s):  
S. Eckhardt ◽  
A. J. Prata ◽  
P. Seibert ◽  
K. Stebel ◽  
A. Stohl
Keyword(s):  
Vertical Profile ◽  
Volcanic Ash ◽  
Transport Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
Inversion Method ◽  
Volcanic Plume ◽  
Operational Environment ◽  
Data Set ◽  
Emission Profile

Abstract. An analytical inversion method has been developed to estimate the vertical profile of SO2 emissions from volcanic eruptions. The method uses satellite-observed total SO2 columns and an atmospheric transport model (FLEXPART) to exploit the fact that winds change with altitude – thus, the position and shape of the volcanic plume bear information on its emission altitude. The method finds the vertical emission distribution which minimizes the total difference between simulated and observed SO2 columns while also considering a priori information. We have tested the method with the eruption of Jebel at Tair on 30 September 2007 for which a comprehensive observational data set from various satellite instruments (AIRS, OMI, SEVIRI, CALIPSO) is available. Using satellite data from the first 24 h after the eruption for the inversion, we found an emission maximum near 16 km above sea level (asl), and secondary maxima near 5, 9, 12 and 14 km a.s.l. 60% of the emission occurred above the tropopause. The emission profile obtained in the inversion was then used to simulate the transport of the plume over the following week. The modeled plume agrees very well with SO2 total columns observed by OMI, and its altitude and width agree mostly within 1–2 km with CALIPSO observations of stratospheric aerosol produced from the SO2. The inversion result is robust against various changes in both the a priori and the observations. Even when using only SEVIRI data from the first 15 h after the eruption, the emission profile was reasonably well estimated. The method is computationally very fast. It is therefore suitable for implementation within an operational environment, such as the Volcanic Ash Advisory Centers, to predict the threat posed by volcanic ash for air traffic. It could also be helpful for assessing the sulfur input into the stratosphere, be it in the context of volcanic processes or also for proposed geo-engineering techniques to counteract global warming.

scholarly journals A Near-Real-Time Method for Estimating Volcanic Ash Emissions Using Satellite Retrievals

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1573
Author(s):  
Rachel Pelley ◽  
David Thomson ◽  
Helen Webster ◽  
Michael Cooke ◽  
Alistair Manning ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
A Priori ◽  
Atmospheric Dispersion ◽  
Posteriori Probability ◽  
Inversion Method ◽  
Volcanic Plume ◽  
A Posteriori Probability ◽  
Satellite Retrievals ◽  
Atmospheric Dispersion Model

We present a Bayesian inversion method for estimating volcanic ash emissions using satellite retrievals of ash column load and an atmospheric dispersion model. An a priori description of the emissions is used based on observations of the rise height of the volcanic plume and a stochastic model of the possible emissions. Satellite data are processed to give column loads where ash is detected and to give information on where we have high confidence that there is negligible ash. An atmospheric dispersion model is used to relate emissions and column loads. Gaussian distributions are assumed for the a priori emissions and for the errors in the satellite retrievals. The optimal emissions estimate is obtained by finding the peak of the a posteriori probability density under the constraint that the emissions are non-negative. We apply this inversion method within a framework designed for use during an eruption with the emission estimates (for any given emission time) being revised over time as more information becomes available. We demonstrate the approach for the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions. We apply the approach in two ways, using only the ash retrievals and using both the ash and clear sky retrievals. For Eyjafjallajökull we have compared with an independent dataset not used in the inversion and have found that the inversion-derived emissions lead to improved predictions.

scholarly journals Estimation of Volcanic Ash Emissions Using Trajectory-Based 4D-Var Data Assimilation

2016 ◽  
Vol 144 (2) ◽  
pp. 575-589 ◽  
Author(s):  
S. Lu ◽  
H. X. Lin ◽  
A. W. Heemink ◽  
G. Fu ◽  
A. J. Segers
Keyword(s):  
Data Assimilation ◽  
Vertical Distribution ◽  
Volcanic Ash ◽  
Transport Model ◽  
Volcanic Eruptions ◽  
Emission Rates ◽  
Plume Height ◽  
Ill Posed ◽  
Total Difference ◽  
The Vertical Distribution

Abstract Volcanic ash forecasting is a crucial tool in hazard assessment and operational volcano monitoring. Emission parameters such as plume height, total emission mass, and vertical distribution of the emission plume rate are essential and important in the implementation of volcanic ash models. Therefore, estimation of emission parameters using available observations through data assimilation could help to increase the accuracy of forecasts and provide reliable advisory information. This paper focuses on the use of satellite total-ash-column data in 4D-Var based assimilations. Experiments show that it is very difficult to estimate the vertical distribution of effective volcanic ash injection rates from satellite-observed ash columns using a standard 4D-Var assimilation approach. This paper addresses the ill-posed nature of the assimilation problem from the perspective of a spurious relationship. To reduce the influence of a spurious relationship created by a radiate observation operator, an adjoint-free trajectory-based 4D-Var assimilation method is proposed, which is more accurate to estimate the vertical profile of volcanic ash from volcanic eruptions. The method seeks the optimal vertical distribution of emission rates of a reformulated cost function that computes the total difference between simulated and observed ash columns. A 3D simplified aerosol transport model and synthetic satellite observations are used to compare the results of both the standard method and the new method.

scholarly journals Determination of time- and height-resolved volcanic ash emissions and their use for quantitative ash dispersion modeling: the 2010 Eyjafjallajökull eruption

2011 ◽  
Vol 11 (9) ◽  
pp. 4333-4351 ◽  
Author(s):  
A. Stohl ◽  
A. J. Prata ◽  
S. Eckhardt ◽  
L. Clarisse ◽  
A. Durant ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
General Nature ◽  
Aviation Industry ◽  
Dispersion Modeling ◽  
Source Information ◽  
European Area ◽  
Ash Dispersion

Abstract. The April–May, 2010 volcanic eruptions of Eyjafjallajökull, Iceland caused significant economic and social disruption in Europe whilst state of the art measurements and ash dispersion forecasts were heavily criticized by the aviation industry. Here we demonstrate for the first time that large improvements can be made in quantitative predictions of the fate of volcanic ash emissions, by using an inversion scheme that couples a priori source information and the output of a Lagrangian dispersion model with satellite data to estimate the volcanic ash source strength as a function of altitude and time. From the inversion, we obtain a total fine ash emission of the eruption of 8.3 ± 4.2 Tg for particles in the size range of 2.8–28 μm diameter. We evaluate the results of our model results with a posteriori ash emissions using independent ground-based, airborne and space-borne measurements both in case studies and statistically. Subsequently, we estimate the area over Europe affected by volcanic ash above certain concentration thresholds relevant for the aviation industry. We find that during three episodes in April and May, volcanic ash concentrations at some altitude in the atmosphere exceeded the limits for the "Normal" flying zone in up to 14 % (6–16 %), 2 % (1–3 %) and 7 % (4–11 %), respectively, of the European area. For a limit of 2 mg m−3 only two episodes with fractions of 1.5 % (0.2–2.8 %) and 0.9 % (0.1–1.6 %) occurred, while the current "No-Fly" zone criterion of 4 mg m−3 was rarely exceeded. Our results have important ramifications for determining air space closures and for real-time quantitative estimations of ash concentrations. Furthermore, the general nature of our method yields better constraints on the distribution and fate of volcanic ash in the Earth system.

Ensemble-based data assimilation of volcanic aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Andrew Prata ◽  
Federica Pardini
Keyword(s):  
Data Assimilation ◽  
Information Transfer ◽  
High Performance ◽  
Volcanic Ash ◽  
Numerical Models ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Eruption Column ◽  
Operational Environment ◽  
Assimilation System

<p>Modelling atmospheric dispersion and deposition of volcanic ash is becoming increasingly valuable for understanding the potential impacts of explosive volcanic eruptions on infrastructures, air quality and aviation. The generation of high-resolution forecasts depends on the accuracy and reliability of the input data for models. Uncertainties in key parameters such as eruption column height injection, physical properties of particles or meteorological fields, represent a major source of error in forecasting airborne volcanic ash. The availability of nearly real time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context. Data assimilation (DA) is one of the most effective ways to reduce the error associated with the forecasts through the incorporation of available observations into numerical models. Here we present a new implementation of an ensemble-based data assimilation system based on the coupling between the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The implementation is based on the last version release of FALL3D (versions 8.x) tailored to the extreme-scale computing requirements, which has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE). The proposed methodology can be efficiently implemented in an operational environment by exploiting high-performance computing (HPC) resources. The FALL3D+PDAF system can be run in parallel and supports online-coupled DA, which allows an efficient information transfer through parallel communication. Satellite-retrieved data from recent volcanic eruptions were considered as input observations for the assimilation system.</p>

scholarly journals Estimated regional CO<sub>2</sub> flux and uncertainty based on an ensemble of atmospheric CO<sub>2</sub> inversions

2021 ◽  
Author(s):  
Naveen Chandra ◽  
Prabir K. Patra ◽  
Yousuke Niwa ◽  
Akihiko Ito ◽  
Yosuke Iida ◽  
...  
Keyword(s):  
Atmospheric Carbon Dioxide ◽  
Transport Model ◽  
Carbon Sink ◽  
A Priori ◽  
Inversion Method ◽  
Co2 Fluxes ◽  
Emission Mitigation ◽  
Regional Sources ◽  
Carbon Dioxide Co2 ◽  
Riverine Export

Abstract. Global and regional sources and sinks of carbon across the earth’s surface have been studied extensively using atmospheric carbon dioxide (CO2) observations and chemistry-transport model (ACTM) simulations (top-down/inversion method). However, the uncertainties in the regional flux (+ve: source to the atmosphere; −ve: sink on land/ocean) distributions remain unconstrained mainly due to the lack of sufficient high-quality measurements covering the globe in all seasons and the uncertainties in model simulations. Here, we use a suite of 16 inversion cases, derived from a single transport model (MIROC4-ACTM) but different sets of a priori (bottom-up) terrestrial biosphere and oceanic fluxes, as well as prior flux and observational data uncertainties (50 sites) to estimate CO2 fluxes for 84 regions over the period 2000–2020. The ensemble inversions provide a mean flux field that is consistent with the global CO2 growth rate, land and ocean sink partitioning of −2.9 ± 0.3 (±1σ uncertainty on mean) and −1.6 ± 0.2 PgC yr−1, respectively, for the period 2011–2020 (without riverine export correction), offsetting about 22–33 % and 16–18 % of global fossil-fuel CO2 emissions. Aggregated fluxes for 15 land regions compare reasonably well with the best estimations for (approx. 2000–2009) given by the REgional Carbon Cycle Assessment and Processes (RECCAP), and all regions appeared as a carbon sink over 2011–2020. Interannual variability and seasonal cycle in CO2 fluxes are more consistently derived for different prior fluxes when a greater degree of freedom is given to the inversion system (greater prior flux uncertainty). We have evaluated the inversion fluxes using independent aircraft and surface measurements not used in the inversions, which raises our confidence in the ensemble mean flux rather than an individual inversion. Differences between 5-year mean fluxes show promises and capability to track flux changes under ongoing and future CO2 emission mitigation policies.

scholarly journals Interpretation of observed microwave signatures from ground dual polarization radar and space multi frequency radiometer for the 2011 Grímsvötn volcanic eruption

2013 ◽  
Vol 6 (4) ◽  
pp. 6215-6248 ◽  
Author(s):  
M. Montopoli ◽  
G. Vulpiani ◽  
D. Cimini ◽  
E. Picciotti ◽  
F. S. Marzano
Keyword(s):  
Spatial Resolution ◽  
Volcanic Ash ◽  
Volcanic Eruptions ◽  
Radar Data ◽  
Radar Signal ◽  
Volcanic Plume ◽  
Dual Polarization ◽  
X Band ◽  
Volcanic Vent ◽  
Ash Cloud

Abstract. The important role played by ground-based microwave weather radars for the monitoring of volcanic ash clouds has been recently demonstrated. The potential of microwaves from satellite passive and ground-based active sensors to estimate near-source volcanic ash cloud parameters has been also proposed, though with little investigation of their synergy and the role of the radar polarimetry. The goal of this work is to show the potentiality and drawbacks of the X-band Dual Polarization radar measurements (DPX) through the data acquired during the latest Grímsvötn volcanic eruptions that took place on May 2011 in Iceland. The analysis is enriched by the comparison between DPX data and the observations from the satellite Special Sensor Microwave Imager/Sounder (SSMIS) and a C-band Single Polarization (SPC) radar. SPC, DPX, and SSMIS instruments cover a large range of the microwaves spectrum, operating respectively at 5.4, 3.2, and 0.16–1.6 cm wavelengths. The multi-source comparison is made in terms of Total Columnar Concentration (TCC). The latter is estimated from radar observables using the "Volcanic Ash Radar Retrieval for dual-Polarization X band systems" (VARR-PX) algorithm and from SSMIS brightness temperature (BT) using a linear BT–TCC relationship. The BT–TCC relationship has been compared with the analogous relation derived from SSMIS and SPC radar data for the same case study. Differences between these two linear regression curves are mainly attributed to an incomplete observation of the vertical extension of the ash cloud, a coarser spatial resolution and a more pronounced non-uniform beam filling effect of SPC measurements (260 km far from the volcanic vent) with respect to the DPX (70 km from the volcanic vent). Results show that high-spatial-resolution DPX radar data identify an evident volcanic plume signature, even though the interpretation of the polarimetric variables and the related retrievals is not always straightforward, likely due to the possible formation of ash and ice particle aggregates and the radar signal depolarization induced by turbulence effects. The correlation of the estimated TCCs derived from DPX and SSMIS BTs reaches −0.73.

scholarly journals Total column water vapor retrieval for GOME-2 visible blue observations

2020 ◽  
Author(s):  
Ka Lok Chan ◽  
Pieter Valks ◽  
Sander Slijkhuis ◽  
Claas Köhler ◽  
Diego Loyola
Keyword(s):  
Water Vapor ◽  
Transport Model ◽  
A Priori ◽  
Spectral Band ◽  
Atmospheric Composition ◽  
Retrieval Algorithm ◽  
Blue Band ◽  
Data Set ◽  
Ozone Monitoring ◽  
Total Column

Abstract. We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the EUMETSAT MetOp satellites. The blue band algorithm allows retrieval of water vapor from sensors which do not cover longer wavelengths, such as Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical column using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing to the operational product retrieved in the red spectral band, sun-photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results, and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.

scholarly journals Total column water vapor retrieval for Global Ozone Monitoring Experience-2 (GOME-2) visible blue observations

2020 ◽  
Vol 13 (8) ◽  
pp. 4169-4193
Author(s):  
Ka Lok Chan ◽  
Pieter Valks ◽  
Sander Slijkhuis ◽  
Claas Köhler ◽  
Diego Loyola
Keyword(s):  
Water Vapor ◽  
Transport Model ◽  
A Priori ◽  
Spectral Band ◽  
Atmospheric Composition ◽  
Retrieval Algorithm ◽  
Blue Band ◽  
Data Set ◽  
Ozone Monitoring ◽  
Total Column

Abstract. We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.

scholarly journals Aerosol data assimilation in the chemical-transport model MOCAGE during the TRAQA/ChArMEx campaign: Aerosol optical depth

2016 ◽  
Author(s):  
Bojan Sič ◽  
Laaziz El Amraoui ◽  
Andrea Piacentini ◽  
Virginie Marécal ◽  
Emanuele Emili ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Vertical Profile ◽  
Transport Model ◽  
Control Variable ◽  
Concentration Data ◽  
Validation Data ◽  
Data Set ◽  
Direct Model

Abstract. In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry-transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the 2D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument and to estimate improvements in a 3D CTM assimilation run compared to a direct model run. Our assimilation system uses 3D-FGAT (First Guess at Appropriate Time) as an assimilation method and the total 3D aerosol concentration as a control variable. In order to have an extensive validation data set, we set our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l’Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2D and 3D) measured by in-situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation reduced the bias in the AOD (from 0.050 to 0.006) and increased the correlation (from 0.74 to 0.88). When compared to the 3D concentration data obtained by the in-situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We also examine how the assimilation can influence the modelled aerosol vertical distribution. The results show that a 2D continuous AOD assimilation can improve the 3D vertical profile, as a result of differential horizontal transport of aerosols in the model.

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