Advances in Space Research 37 (2006) 671–680
www.elsevier.com/locate/asr
Anomalous increase of chlorophyll concentrations associated
with earthquakes
Ramesh P. Singh
b
a,b,*
, Sagnik Dey a, Sanjeeb Bhoi b, Donglian Sun b,
Guido Cervone b, Menas Kafatos b
a
Department of Civil Engineering, Indian Institute of Technology, Kanpur 208 016, India
School of Computational Sciences, George Mason University, 4400 University Drive MS 5C3, Fairfax, VA 22030, USA
Received 28 September 2004; received in revised form 11 July 2005; accepted 16 July 2005
Abstract
Recent studies have shown land, ocean, atmosphere and ionospheric anomalies prior to earthquakes. The optical and microwave
sensors onboard satellites are now capable of monitoring land, ocean, atmosphere and ionosphere which provide changes associated
with natural hazards. In this paper, we have analyzed remote sensing data of the ocean coasts lying near the epicenters of recent four
major earthquakes (Gujarat of January 26, 2001, Andaman of September 13, 2002, Algeria of May 21, 2002 and Bam, Iran earthquake of December 26, 2003), our detailed analysis shows increase of Chlorophyll-a (Chl-a) concentration associated with these
recent earthquakes. The increase of Chl-a concentration is due to the change in sea surface temperature (SST) associated with
the changes in stress regime in the epicentral region which is responsible for modifying the in situ thermal structure of the water
and enhancing the upwelling of nutrient-rich water. The increase of Chl-a concentration also shows one to one relation with the
increase of surface latent heat flux (SLHF) which is found to increase significantly prior to the earthquake events. Due to cloud
cover, it has not been possible to quantify the effect of the chlorophyll concentrations associated with the earthquake events for each
successive day during an event. However, the limited data from the adjacent oceanic regions provide strong evidence of the increase
in Chl-a concentration. The monitoring of chlorophyll concentrations with higher spatial and temporal resolutions may provide
early information about impending coastal earthquakes.
2005 COSPAR. Published by Elsevier Ltd. All rights reserved.
Keywords: Earthquake; Chlorophyll; Remote sensing; Early warning; Upwelling
1. Introduction
Ocean optics and physical processes are fundamentally linked through the radiative heating component
of the solar radiation absorbed by the ocean water primarily due to the phytoplankton pigments (Bissett
et al., 2001). Chlorophyll-a (Chl-a) is the indicator of
the primary productivity of phytoplankton biomass in
*
Corresponding author. Tel.: +91 512 2597295; fax: +1 703 993
1993.
E-mail addresses: [email protected], [email protected] (Ramesh
P. Singh).
the ocean, which can be monitored from space accurately by ocean color sensors (Sathyendranath et al.,
1991; Yoder et al., 1993; Tang et al., 2002; Dey and
Singh, 2003a). Pigment retrievals from ocean color sensors in case 1 water, where optical properties are dominated by Chl-a and associated detrital colored dissolved
organic matter (CDOM) have achieved reasonable results (Carder et al., 1999). The spatial and temporal distributions of the Chl-a in the ocean are intimately linked
with the sea surface temperature (Sathyendranath et al.,
1991) and the vertical and horizontal mixing within the
mixed layer (Nakamoto et al., 2000) in the ocean induced by the physical forcing (Kumar et al., 2000).
0273-1177/$30 2005 COSPAR. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.asr.2005.07.053
672
R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
Spatial and temporal variability of the Chl-a may occur
due to the large scale disturbances in the oceanic circulation patterns, arising from sudden changes of thermal
structure (Chaturvedi and Narain, 2003) of the water.
The thermal structure of the ocean is maintained by
the numerous controlling parameters, including sea surface temperature (SST), incoming solar radiation, precipitation and winds, which modulates the SLHF of
the ocean (Bissett et al., 2001; Wang et al., 2002). The
sudden change in one of parameters will result in changing the thermal structure of the ocean water, which will
induce upwelling and ocean water mixing.
In the present paper, we have investigated impact of
earthquakes on the Chl-a concentration in ocean water.
Initial stage of stress increase in the focal region of
earthquakes gives rise to the strong coupling between
the land–ocean–atmosphere as a result anomalous
behavior in the land, ocean, atmospheric and ionospheric parameters are being observed prior to the
earthquakes (Dey and Singh, 2003b; Dey et al., 2004;
Ouzounov and Freund, 2004). We have carried out analysis of ocean parameters of about 10 coastal earthquakes, here we present the analysis of chlorophyll
concentrations of four major coastal earthquakes (details are shown in Table 1 and the locations are shown
in Fig. 1) occurred in the last 5 years. The four earthquakes chosen for the present study differ in proximity
of the epicenters to the ocean, tectonic settings and
bathymetry. The epicenters of the Andaman and Algeria
earthquakes are located on the coastlines, whereas the
epicenters of Gujarat and Iran earthquakes are near
the coasts. The ocean near the epicenters of Gujarat
and Iran earthquakes is very shallow compared to those
near the Andaman and Algeria earthquakes (Fig. 1).
The regional tectonics of these earthquakes are discussed in detail by many (Negishi et al., 2002; Rajendran
et al., 2003; Eshghi and Zare, 2003; Semmane et al.,
2005).
Earlier Singh et al. (2002) have shown an increase in
Chl-a concentration immediately after the Gujarat
earthquake, but due to non-availability of continuous
data it was not assured if the anomalous increase was
associated with earthquake or a regional phenomenon.
In this paper, we have looked for the possible reasons,
on the basis of the associated oceanic parameters. The
detailed analysis of Chl-a concentration along the Gujarat coasts near the epicenter of the Gujarat earthquake
show increase prior to the Gujarat earthquake, similar
results were also found to be associated with three other
recent coastal earthquakes.
2. Data and methodology
For Chl-a concentration and SST, Moderate Resolution Imaging Spectroradiometer (MODIS) level 3 products have been used in the present study. The algorithm
is valid for case 2 coastal water. Case 2 Chl-a algorithm
Table 1
Details of the earthquakes (source: www.usgs.gov)
No.
Place
Date
Longitude
Latitude
Magnitude
Focal depth (km)
1
2
3
4
Gujarat, India
Andaman, India
Algeria
Bam, Iran
January 26, 2001
September 13, 2002
May 21, 2003
December 26, 2003
70.32E
93.07E
3.63E
58.32E
23.4N
13.04N
36.96N
28.99N
7.7
6.5
6.8
6.6
17
21
12
10
Fig. 1. Locations of the epicenters of the four earthquakes shown in a bathymetry map of world.
R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
is based on a semi-analytical bio-optical remote sensing
algorithm and is calculated by dividing the water leaving
radiance by the downwelling irradiance. The use of a
semi-analytic algorithm reduces the errors from 40%
to 20% when compared to the estimates using an empirical algorithm (Carder et al., 2004). We have used
MODIS version 4 data for the present study.
673
We have also analyzed surface latent heat flux
(SLHF) data available from the National Center for
Environmental Prediction (NCEP) to study the characteristics of SLHF prior and after the earthquake. The
SLHF data is downloaded from the Scientific Computing Division of the National Center for Atmospheric
Research (NCAR) (http://ingrid.ldeo.columbia.edu/
Fig. 2a. Time series of images of Chl-a concentration retrieved from MODIS in the Arabian Sea during the Gujarat earthquake of January 26, 2001.
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R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
Fig. 2a (continued).
SOURCES/NOAA/NCEP-NCAR/). The data set is
projected into 2-latitude by 2-longitude grid. The
reanalysis and upgrading of the database at NCEP have
been discussed by Kalnay et al. (1996). The SLHF
anomaly has been derived by applying wavelet transformations (Cervone et al., 2004) on the daily SLHF data.
The Ekman transport can be taken as a quantitative
characteristic for the upwelling intensity, the integral
Ekman transport in the surface layer U can be computed
using following equation
sy
U¼
;
ð1Þ
q0 f
R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
675
Fig. 2b. Daily averaged upwelling index for Gujarat earthquake showing maximum rise three days prior to the main event.
where sy is the coastline parallel wind stress on the water
surface, q0 is the density of water and is equal to
1000 kg/m3, f is the coriolis parameter and f = 2Xsinh,
X is the angular velocity of the earth rotation
(7.29 · 105), and h is the latitude. U is actually the offshore Ekman transport, which is additionally modified
by local parameters, such as coastline, bottom topography, and stratification. Wind stress s = kqaW2, where qa
is the density of air, k is the empirical drag coefficient
and is a function of wind velocity W (Trenberth et al.,
1990).
The spatial distributions of Chl-a concentration near
the epicenters of these earthquakes are analyzed for onemonth period together with the variations of SST and
SLHF. The upwelling index has been averaged over
the surrounding oceanic regions to understand the
blooming of Chl-a.
3. Results and discussion
Chl-a concentration and SST in the Gulf of
Kutchchh and Cambay (Fig. 2a) near the epicenter
and the entire Arabian Sea during January 1–31,
2001 are shown in Figs. 2a and 2c, respectively. In general, during the northeast monsoon, the northeastern
part of the Arabian Sea has been found to be very productive (Tang et al., 2002; Dey and Singh, 2003a) due
to strong upwelling of nutrient-rich water. The Chl-a
concentration in the Gulfs during January has been
found consistently greater than 2 mg m3 and is higher
than the corresponding open ocean values. Chl-a concentration is found to be more than 5 mg m3 on 4
occasions, on January 8, 12, 15–17 and 25–27. The
daily averaged upwelling index in this region
(Fig. 2b) shows 4 peaks, on January 7, 11, 17 and
24, one day prior to the each bloom event confirming
that Chl-a concentration increases due to upwelling
of nutrient-rich water. The upwelling in the Arabian
Sea shows enhanced productivity during winter season
due to faster convection in high saline Arabian Sea
water (Kumar et al., 2001). The upwelling is enhanced
just prior to the earthquake, when it reaches its maximum value. Similarly, highest Chl-a concentration in
region during the same time period are shown in
Fig. 2a. SST higher than 25 C has been found in most
parts of the Arabian Sea except the Gulf of Kutchchh
and Cambay. In these Gulfs, SST increases by 2 C
on January 25, one day prior to the earthquake. The
sudden increase in SST is attributed to the increased
SLHF, which has been observed to show anomalous
increase three days prior to the main event on January
26, 2001 and found to continue until the next day
(Fig. 2d).
Similar response of Chl-a concentration has been
found to be associated with the Andaman earthquake,
where Chl-a concentration increases by 2–3 mg/m3
on September 14 as compared to September 6, 2002 (figure not shown here) around the Andaman and Nicobar
Islands. Due to thick cloud covers in the region it was
not possible to get continuous cloud free satellite data
to ascertain the start of blooming of Chl-a during the
week of the earthquake. Increase in Chl-a concentration
has also been found to be associated with the Algeria
and the Iran earthquakes. Instead of showing continuous Chl-a concentration images for the these earthquakes, we show the variations of upwelling index
during the month in which these three earthquakes have
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R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
occurred (Fig. 3). In each case, the maximum upwelling
has been found few days prior to the main events. Only
for the Andaman earthquake, another high upwelling
has been observed on September 21, 2002 (Fig. 3a).
All four earthquakes were found to be accompanied
by series of aftershocks, the effect of the aftershocks
on the upwelling is observed to be the strongest in case
of the Andaman earthquake. The epicenter of the Andaman earthquake is lying in the open ocean, whereas for
the other three, the epicenters are lying on the land,
although they are close to the ocean. As the SLHF of
the ocean is larger than that of the land, the magnitude
of the increase in SST is highest for the Andaman
earthquake.
Fig. 2c. Time series of images of SST retrieved from MODIS in the Arabian Sea during the Gujarat earthquake of January 26, 2001.
R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
677
Fig. 2c (continued).
With the building of stress in the focal regime of
earthquakes prior to the earthquake event, it is now confirmed that the SST increases prior to the earthquake
(Gujarat earthquake, http://www.nasa.gov/centers/
ames/images). It is likely that with the increase of SST
of the land, the coastal upwelling may enhance which
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R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
Fig. 2d. Spatio-temporal variation in SLHF prior to the main event of Gujarat earthquake.
may be responsible to bring the nutrients near the ocean
surface. The efficiency of the upwelling will be maximum
where the difference in temperature is maximum. The
overall impact of the released thermal energy associated
with an earthquake also depends on the distance of its
epicenter from the ocean. This is because the transport
of the heat energy to the surface is more efficient in
the oceans compared to land, as the average continental
crustal thickness (33 km) is much more compared to
an average oceanic crustal thickness (8 km). Ouzounov and Freund (2004) have found increase in thermal
infrared emission from the rock mass prior to an earthquake. Release of thermal energy prior to the earthquake is reflected in terms of increase in SLHF and
SST of the region. Dey and Singh (2003b), Cervone
et al. (2004) and Singh et al. (2004) have recently found
consistent SLHF anomaly prior to coastal earthquakes,
which can be used as precursory signals. SLHF has been
found to migrate from the high-stress regions to lowstress zones prior to the main event and eventually appears in the low-stress zones on the surface. Tectonically, the gulf areas in the south and west of the
epicenter of Gujarat earthquake are the low-stress
zones, where maximum SLHF anomaly has been observed. Despite of the difference in bathymetry and tectonics, the pre-earthquake thermal energy affects the
thermal stratification of the ocean water, but the magnitude of its effect depends on several factors, such as, distance of the epicenter from the ocean, magnitude of the
impending earthquake (directly proportional to the
amount of energy released) and the focal depth. Maximum upwelling has been found 9 days prior to the Iran
earthquake, 6 days prior to the Algeria earthquake, 3
days prior to the Gujarat earthquake and 5 days prior
to the Andaman earthquake, whereas the shallow focal
depth is observed for the Iran earthquake, followed by
the Algeria, the Gujarat and the Andaman earthquakes.
This relation indicates that shallower is the focal depth,
more advance is the upwelling with respect to the main
event, considering the distance of the epicenter from
ocean is almost similar. As the epicenter of the Andaman earthquake is closer to ocean compared to the
Gujarat earthquake, the maximum upwelling occurs 2
days faster.
On the basis of all the observed changes in the oceanic parameters linked sequentially in response to an
earthquake, we propose a hypothesis to explain the
phenomenon. The thermal energy released prior to
the earthquake is transported to the surface altering
the ambient thermal structure of the water. This results in increase in SST and SLHF and enhances
upwelling, which in turns brings nutrient-rich water
near the ocean surface giving rise to the Chl-a blooming. During non-productive period, an impending
earthquake will cause primary production, but the increase in Chl-a concentration will be spatially limited.
However, during the productive period, such as during
the winter monsoon in the North Arabian Sea, the
earthquake will enhance the normal production. The
whole sequence will begin much earlier and occur
much faster in case of higher magnitude of earthquake
and hence it may give valuable information about an
impending earthquake.
4. Conclusions
Increase in Chl-a concentration associated with the
coastal earthquakes is attributed to the upwelling of
nutrient-rich water due to the redistribution of thermal
structure of ocean water. Anomalous increase in SLHF
simultaneously associated with the increase in SST are
found due to the build up of stress in the epicentral regime of an earthquake. The most dominant controlling
factors of the overall impact of the earthquakes in this
process are the distance of epicenter from the ocean
and focal depth. Also the zones of the Chl-a bloom
are the low-stress zones, whereas the epicenter lies in
R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
679
Fig. 3. Daily averaged upwelling index for: (a) Andaman; (b) Algeria; (c) Iran earthquakes.
the corresponding high-stress zones in that particular
tectonic regime. Detailed analysis of Chl-a concentration depending upon the cloud free data from the future
earthquakes are required to ascertain the time lag between the blooming of Chl-a with an impending
earthquake.
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R.P. Singh et al. / Advances in Space Research 37 (2006) 671–680
Acknowledgements
This research was partially supported by NASAÕs office of Earth Science Enterprise under grant NAG1201009, NAG13-02054 and NAG13-03019, VAccess/
MAGIC projects. We are grateful to the two anonymous reviewers of their useful comments and suggestions which helped us to improve the original version
of the manuscript.
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