International Journal of Environmental Science and Technology
Improving the Persian Gulf sea surface temperature simulation
by assimilating the satellite data via the ensemble Kalman
M. R. Abbasi
· V. Chegini
· M. Sadrinasab
· S. M. Siadatmousavi
Received: 17 February 2017 / Revised: 4 March 2018 / Accepted: 15 May 2018
© Islamic Azad University (IAU) 2018
One of the indicators representing the permissible performance of a marine model is the capability of model in providing
an accurate spatiotemporal distribution of the thermal structure of domain. Data assimilation is taken into account as an
expedient platform in order to achieve this goal. In this paper, the ensemble Kalman ﬁlter (EnKF) was applied as a data
assimilation scheme to enhance the sea surface temperature (SST) simulation and whereupon the underwater temperature
of the Persian Gulf in the ﬁnite volume community ocean model (FVCOM). The daily satellite measured SST data that
obtained from advanced very high-resolution radiometer pathﬁnder were considered as observational assimilation data. The
comparisons between the results of both proposed models including FVCOM and SST measurements were carried out to
evaluate the eﬃciency of data assimilation. The comparisons revealed a meaningful improvement in the assimilated simula-
tion of the spatiotemporal SST variability in the whole domain, especially in the shallow parts and near the Hormuz Strait.
The root-mean-square error reduced signiﬁcantly in assimilation run. The statistical comparisons of the results bias denote
a positive impact of the data assimilation.
Keywords Data assimilation · Sea surface temperature · Ensemble Kalman ﬁlter · Persian Gulf
The sea surface temperature (SST) plays a sumptuous role in
studying the meteorological and oceanographic processes.
Due to its impact on ﬂuxing of energy (heat and momentum)
and mass (salt and gas) between the ocean and the atmos-
phere and the simplicity of its measurements, it has been one
of the ﬁrst considerations in environmental studies for those
who are connoisseurs of marine biology.
For instance, with getting inspiration from marine biol-
ogy researches, the rate of mangrove growth in the water and
SST is inextricably bound up with the chlorophyll concentra-
tion, coral reef and sea grass. (Podesta et al. 1998; Sheppard
and Rayner 2002; Paulson and Simpson 1977; Ghanea et al.
2016; Jones et al. 2002; Glibert et al. 2002).
Climatological processes such as monsoon (Kailasam and
Rao 2010; Kothawale et al. 2008; Castro 2001), El Nino, La
Nina, ENSO (Iskandar 2010) are in conjunction with SST.
This importance caused the using of various instruments
including direct or indirect methods and in situ or remote
equipment for measuring the SST. These varieties create
a great SST data records in diﬀerent spatial and temporal
resolutions. The combination of these measurements has
created thorough SST maps that can be employed in widely
oceanic and atmospheric studies. The daily regular global
gridded optimal interpolated SST (OISST) (Reynolds et al.
2007) is one of these maps that is a combination of various
measuring platforms (satellites, ships, buoys) data analyzed
by interpolating to ﬁll the gaps.
Since this parameter lies in the interface of the air and the
water, a multiplicity of coupled ocean–atmosphere models
have been built to provide a better studying of these phenom-
ena. There is some errors in both observational measure-
ments and mathematical models. In the numerical modeling
Editorial responsibility: M. Abbaspour.
* M. R. Abbasi
Iranian National Institute for Oceanography
and Atmospheric Science, No.3, Etemad Zadeh St., Fatemi
Ave., Tehran, Islamic Republic of Iran
Department of Environmental Design, University of Tehran,
Tehran, Islamic Republic of Iran
University of Science and Technology, Narmak, Tehran,
Islamic Republic of Iran