Weak-constraint inverse modeling using HYSPLIT-4 Lagrangian dispersion model and Cross-Appalachian Tracer Experiment (CAPTEX) observations – effect of including model uncertainties on source term estimation
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Published:2018-12-14
Issue:12
Volume:11
Page:5135-5148
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Chai TianfengORCID, Stein Ariel, Ngan Fong
Abstract
Abstract. A Hybrid Single-Particle Lagrangian Integrated Trajectory version 4
(HYSPLIT-4) inverse system that is based on variational data
assimilation and a Lagrangian dispersion transfer coefficient matrix (TCM) is
evaluated using the Cross-Appalachian Tracer Experiment (CAPTEX) data
collected from six controlled releases. For simplicity, the initial tests are
applied to release 2, for which the HYSPLIT has the best performance. Before
introducing model uncertainty terms that will change with source estimates,
the tests using concentration differences in the cost function result in
severe underestimation, while those using logarithm concentration differences
result in overestimation of the release rate. Adding model uncertainty terms
improves results for both choices of the metric variables in the cost
function. A cost function normalization scheme is later introduced to avoid
spurious minimal source term solutions when using logarithm concentration
differences. The scheme is effective in eliminating the spurious solutions
and it also helps to improve the release estimates for both choices of the
metric variables. The tests also show that calculating logarithm
concentration differences generally yields better results than calculating
concentration differences, and the estimates are more robust for a reasonable
range of model uncertainty parameters. This is further confirmed with nine
ensemble HYSPLIT runs in which meteorological fields were generated with
varying planetary boundary layer (PBL) schemes. In addition, it is found that
the emission estimate using a combined TCM by taking the average or median
values of the nine TCMs is similar to the median of the nine estimates using
each of the TCMs individually. The inverse system is then applied to the
other CAPTEX releases with a fixed set of observational and model uncertainty
parameters, and the largest relative error among the six releases is 53.3 %.
At last, the system is tested for its capability to find a single source
location as well as its source strength. In these tests, the location and
strength that yield the best match between the predicted and the observed
concentrations are considered as the inverse modeling results. The estimated
release rates are mostly not as good as the cases in which the exact release
locations are assumed known, but they are all within a factor of 3 for all
six releases. However, the estimated location may have large errors.
Funder
National Oceanic and Atmospheric Administration
Publisher
Copernicus GmbH
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