NOTES AND CORRESPONDENCE
An Observing System Simulation Experiment (OSSE) for Aerosol Optical
Depth from Satellites
RENSKE M. A. TIMMERMANS,* MARTIJN SCHAAP,* HENDRIK ELBERN,1 RICHARD SIDDANS,#
STEPHEN TJEMKES,@ ROBERT VAUTARD,& AND PETER BUILTJES*
* TNO Built Environment and Geosciences, Utrecht, Netherlands
1 Rhenish Institute for Environmental Research at the University of Cologne, Cologne, Germany
# Rutherford Appleton Laboratory, Chilton, Oxfordshire, United Kingdom
@ EUMETSAT, Darmstadt, Germany
& Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France
(Manuscript received 1 December 2008, in final form 22 June 2009)
ABSTRACT
Monitoring aerosols over wide areas is a scientific challenge with important applications for human health
and the understanding of climate. Aerosol optical depth (AOD) measurements from satellites can improve
the highly needed analyzed and forecasted distributions of ground-level aerosols in combination with models
and ground-based measurements. To assess the benefit of future satellite AOD measurements, an observing
system simulation experiment (OSSE) is developed. In this pilot study, the OSSE is applied to total AOD
measurements from a flexible combined imager (FCI) proposed to fly on a geostationary satellite. OSSEs are
widely used in the meteorological research community, but their use for air quality applications and specif-
ically for aerosols is new. In this paper, the functionality and potential of the developed OSSE for evaluation
of aerosol data from future satellite missions are demonstrated. The results show a positive impact of adding
AOD observations next to in situ observations for the analysis of PM2.5 (particles smaller than 2.5 mm in
median diameter) distributions. However, the development of an OSSE for aerosols presents a number of
further challenges, as discussed in this paper, which prohibits a detailed quantitative analysis of the results of
this pilot study.
1. Introduction
Aerosols play an important role in the earth’s radia-
tion budget and the climate system through their in-
teraction with clouds and solar radiation (Kiehl and
Briegleb 1993). Also, health studies have shown that
short- and long-term exposure to aerosols has a negative
effect on human health and can lead to premature death
(Brunekreef and Holgate 2002). To protect against the
negative health effects, the European Union (EU) and
the United States (US) have set limit values for partic-
ulate matter loadings. Furthermore, the EU member
states have an obligation to inform the public on the
actual air quality situation. Hence, there is a need for
accurate analyzed and forecasted distributions of aero-
sol concentrations.
Traditionally, in situ ground-based measurements are
used to provide information on aerosol concentrations.
However, these have the disadvantage of a low spatial
coverage and measurement methods and correction
factors are sometimes not consistent between different
countries. Spaceborne observations of aerosol optical
depth (AOD) have the advantage of providing full
spatial coverage (although only during daylight and
cloud-free conditions) and—in principle—consistent data
for the whole European region. Thus, synergetic use of
satellite measurements, models, and ground-based
measurements may be useful to improve the insight into
aerosol distributions in Europe. Assimilation experi-
ments, in which satellite data have been combined with
models, have shown that current satellite data have
Corresponding author address: R. M. A. Timmermans, TNO
Built Environment and Geosciences, P.O. Box 80015, 3508 TA
Utrecht, Netherlands.
E-mail: renske.timmermans@tno.nl
DECEMBER 2009 N O T E S A N D C O R R E S P O N D E N C E 2673
DOI: 10.1175/2009JTECHA1263.1
 2009 American Meteorological Society

a positive influence on the determination of the aerosol
distribution, but the capability of the assimilation sys-
tems to track the evolution of the aerosol distributions is
still limited because of the large time intervals (one day
or longer) between valid retrievals (Schaap et al. 2006).
Hence, a higher temporal resolution of the AOD data
may be highly beneficial.
User consultations (Lelieveld 2003; EUMETSAT
2006) as well as the projects Protocol Monitoring for
the Global Monitoring for Environment and Security
(GMES) Service Element (PROMOTE) and Compo-
sition of the Atmosphere: Progress to Applications in
the User Community (CAPACITY; Goede 2005) have
led to resolution requirements for future AOD derived
from spaceborne observations intended to be used for
air quality applications. The required high temporal re-
solution and quality present a challenge for instrument
design. To consolidate these requirements with respect
to spatial and temporal resolution, an observing system
simulation experiment (OSSE) is developed, a concept
that has commonly been used in meteorology for testing
the impact of future spaceborne measurements (Masutani
et al. 2006) but never in atmospheric chemistry for aerosol
measurements. In this paper, the setup of the OSSE
directed at aerosols and its application to a proposed
future instrument [the flexible combined imager (FCI)]
that will measure total AOD columns from a geosta-
tionary satellite are presented. The issues encountered
during this first application of the OSSE principle to
aerosol retrievals are discussed. Some results are shown
demonstrating the potential of the OSSE system for
such applications. However, the encountered issues do
not allow an extensive quantitative evaluation of results
and consolidation of the requirements.
2. Observing system simulation experiments
Generally, observing system experiments (OSEs) are
used to assess the impact of existing operational observ-
ing systems on, for example, weather forecasts. These
experiments contain the following elements:
d a state-of-the-art model,
d active data assimilation of the observations in the
model, and
d assessment of the added value of assimilation of the
measurements (on, e.g., analyzed fields or forecasts).
In OSSEs, which are used to anticipate the effect of
future instruments, the existing observations are replaced
by synthetic observations. The synthetic measurements
are generated through a so-called nature run, which is
supposed to simulate the ‘‘true’’ state of the atmosphere.
Synthetic observations are created corresponding to in-
strument characteristics.
An OSSE thus consists of the following elements:
1) production of synthetic observations through
(i) a nature run performed by a state-of-the-art
model (referred to as the nature run model)
providing the true state of the atmosphere and
(ii) conversion of nature run output to synthetic
observations corresponding to instrument stud-
ied by OSSE;
2) a state-of-the-art model different from the one in the
nature run (referred to as the assimilation model);
3) active data assimilation of the synthetic observations
in the assimilation model; and
4) assessment of the added value of assimilation of the
measurements (on, e.g., analyzed fields or forecasts)
through comparison of resulting fields with the true
state of the atmosphere (i.e., the nature run output).
The nature run model used to generate the synthetic
observations should differ from the assimilation model
in which the observations are assimilated. The differ-
ences should ideally approximate the differences be-
tween a state-of-the-art model and the real atmosphere.
In an OSSE, analyzed fields and forecasts are evaluated
by comparing with the ‘‘truth’’ represented by the na-
ture run.
3. Model system
The model used in this study is the Long Term Ozone
Simulation–European Operational Smog (LOTOS-
EUROS) model, a three-dimensional Eulerian chemis-
try transport model of intermediate complexity (Schaap
et al. 2008). The model covers the European region and
is aimed to describe air pollution in the lower tropo-
sphere (up to 3.5–5 km above sea level). Because during
90% of the time, 90% of all aerosols are below about
3 km, the limited vertical extension of this model ver-
sion is adequate for the current study. In the vertical, the
system has four layers that use the dynamic mixing layer
approach. The first layer is a fixed surface layer of 25 m,
the second layer follows the mixing layer height, and
layers three and four are equally thick, covering the al-
titudes between the mixing layer height and the top of
the model at 3.5 km. The standard horizontal resolution
is 0.258 latitude3 0.58 longitude, approximately 30 km3
25 km (depending on the latitude), with the possibility
to increase the resolution up to a factor of 8. The model
contains all relevant processes, although mostly in pa-
rameterized forms to avoid exceedingly long comput-
ing times. Prior applications of the model to aerosols
have been documented in literature (e.g., Schaap et al.
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