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| Titel |
Estimation of volcanic ash emissions with satellite data: The inclusion of mass loading and plume height information in modified 4D-Var |
| VerfasserIn |
Sha Lu, Hai Xiang Lin, Arnold Heemink, Arjo Segers, Guangliang Fu |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250106578
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| Publikation (Nr.) |
 EGU/EGU2015-6255.pdf |
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| Zusammenfassung |
| Volcanic ash forecasting is a critical tool in hazard assessment and operational volcano
monitoring. Emission parameters such as injection height, total emission mass and
vertical distribution of the emission plume rate are essential and important in the
implementation of volcanic ash models. Satellite instrument is a powerful tool to monitor
volcanic aerosol evolution and satellite total-column data has been integrated in the
modeling process to achieve a better initial condition for the forecasting. However,
the use of total-column data,which has no vertical resolution, usually leads to an
ill-conditioned problem and ineffective estimation of emission parameters. Fortunately,
techniques to retrieve the information of total ash mass loading and injection height
from satellite data has been developed recently. It provides a new possibility to
increase the accuracy of estimation results by integrating them into data assimilation
systems.
In this work we propose a modified 4D-Var approach which seek the vertical emission
distribution by observing ash cloud transport patterns from satellite total-ash-columns data,
and two ways of including the information of mass loading and plume height in the
assimilation process. The modified 4D-Var based on trajectory statistics forms a reformulated
cost function which computes the total difference between observed ash columns and a linear
combination of simulated ensemble columns coupled with a priori emission knowledge
(‘background’ term). The ensembles are generated by a volcanic ash transport model with the
tracer released form different layers. Experiment shows such straightforward method does not
always guarantee the identification of injection height with a short assimilation time
window, and additional information of injection height is needed to correct the
solution.
We propose two tricks to incorporate the information: 1. add extra terms containing the
information to the cost function as restriction term; 2. generate a new emission
based on the information and substitute it for the ‘background’ term in the cost
function. The results of twin experiments show that with the inclusion of emission
parameter information both methods have great correction impact to recognize
the injection height and produce more accurate emission estimation and reliable
initial field of volcanic ash loading. Details of the correction effects of the two
methods are discussed and different sets of weighting factors for the restriction term
or ‘background’ term can be chosen according to specific situation. Furthermore,
comparison is made with other methods such as inverse modeling and satellite
image matching and analysis is given about the reliability and applicability of these
methods. |
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