Brian E. Moroz,* Harold L. Beck,’ André Bouville,* and Steven L. Simon*
were used in a limited fashion to support the dose reconstruction described in companion papers within this volume.
Health Phys. 99(2):252-269; 2010

Abstract—The NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) was evaluated as a
research tool to simulate the dispersion and deposition of
radioactive fallout from nuclear tests. Model-based estimates
of fallout can be valuable for use in the reconstruction of past
exposures from nuclear testing, particularly where little historical fallout monitoring data are available. The ability to
makereliable predictions about fallout deposition could also
have significant importance for nuclear events in the future.
Weevaluated the accuracy of the HYSPLIT-predicted geographic patterns of deposition by comparing those predictions
against known deposition patterns following specific nuclear
tests with an emphasis on nuclear weaponstests conducted in
the Marshall Islands. We evaluated the ability of the computer
code to quantitatively predict the proportion of fallout particles of specific sizes deposited at specific locations as well as
their time of transport. In our simulations of fallout from past
nucleartests, historical meteorological data were used from a
reanalysis conducted jointly by the National Centers for
Environmental Prediction (NCEP) and the National Center for
Atmospheric Research (NCAR). We used a systematic approach in testing the HYSPLIT model by simulating the
release of a rangeof particle sizes from a rangeof altitudes and
evaluating the numberandlocation of particles deposited. Our
findings suggest that the quantity and quality of meteorological data are the most important factors for accurate fallout
predictions and that, when satisfactory meteorological input
data are used, HYSPLIT can produce relatively accurate
deposition patterns and fallout arrival times. Furthermore,
when no other measurement data are available, HYSPLIT can
be used to indicate whetheror not fallout might have occurred
at a given location and provide, at minimum, crude quantitative estimates of the magnitude of the deposited activity. A
variety of simulations of the deposition of fallout from
atmospheric nuclear tests conducted in the Marshall Islands
(mid-Pacific), at the Nevada Test Site (U.S.), and at the
Semipalatinsk Nuclear Test Site (Kazakhstan) were performed. The results of the Marshall Islands simulations

Key words: Marshall Islands; nuclear weapons; fallout; modeling, meteorological

CoMPUTER MODELS have been both influential and beneficial in predicting fallout dispersion and deposition. These
models have been usedhistorically for such diverse tasks
as producing quick fallout estimates necessary for immediate health assessments, extending exposure estimates
downwind beyond ground-based measurements in retrospective dose and risk assessments (Cederwall and Peterson 1990; Hoecker and Machta 1990), and projecting
potential physical damage, including atmospheric effects
such as smokeproduction from regional nuclear conflicts
and individual acts of nuclear terrorism (Toon et al.

2007). Computer codes used for such purposes were
developed and applied by the scientific and defense
communities as early as the 1960’s (Rowland 1994).

Modeling the transport and deposition of particles
released from a nuclear weaponstest is both a complex
and highly uncertain exercise. This is true even when the
meteorological data used in the simulation are accurate.
Furthermore, in order to simulate the deposition density
of specific radionuclides or total radioactivity, a modelis
required for the spatial distribution of radionuclides in
the initial debris cloud as well as the distribution of
activity as a function of particle size. The most computationally burdensome factors in performing the simulations are the large size of the debris cloud and,therefore,
the large numberof particles and particle sizes that are
needed to conducta realistic fallout simulation over long
distances. An additional difficulty is presented when
modeling wet removal processes. Both in-cloud and
below-cloud wet removal processes may be of great
importance to accurately simulating deposition when
precipitation occurred downwind. The data available

* Division of Cancer Epidemiology and Genetics, National Insti-

tutes of Health, National Cancer Institute, Bethesda, MD, 20892;

* New York, NY.

For correspondence contact: Steven L. Simon, National Cancer
Institute, National Institutes of Health, 6120 Executive Blvd., Bethesda, MD 20892, or email at

(Manuscript accepted 22 June 2009)

Copyright © 2010 Health Physics Society

DOI: 10.1097/HP.0b013e3 18 1b43697

Select target paragraph3