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Nat. Hazards Earth Syst. Sci., 10, 2169–2178, 2010
www.nat-hazards-earth-syst-sci.net/10/2169/2010/
doi:10.5194/nhess-10-2169-2010
© Author(s) 2010. CC Attribution 3.0 License.
Natural Hazards
and Earth
System Sciences
Study of outgoing longwave radiation anomalies associated
with Haiti earthquake
P. Xiong
1
, X. H. Shen
1
, Y. X. Bi
2
, C. L. Kang
3
, L. Z. Chen
1
, F. Jing
1
, and Y. Chen
1
1
Institute of Earthquake Science, China Earthquake Administration, Beijing, China
2
School of Computing and Mathematics, University of Ulster, Newtownabbey, Co. Antrim, UK
3
China Earthquake Networks Center, China Earthquake Administration, Beijing, China
Received: 27 May 2010 – Revised: 17 August 2010 – Accepted: 20 September 2010 – Published: 15 October 2010
Abstract. The paper presents an analysis by using the meth-
ods of Eddy field calculation mean and wavelet maxima to
detect seismic anomalies within the outgoing longwave radi-
ation (OLR) data based on time and space. The distinguish-
ing feature of the method of Eddy field calculation mean
is that we can calculate “the total sum of the difference
value” of “the measured value” between adjacent points,
which could highlight the singularity within data. The iden-
tified singularities are further validated by wavelet maxima,
which using wavelet transformations as data mining tools by
computing the maxima that can be used to identify obvious
anomalies within OLR data. The two methods has been ap-
plied to carry out a comparative analysis of OLR data as-
sociated with the earthquake recently occurred in Haiti on
12 January 2010. Combining with the tectonic explanation
of spatial and temporal continuity of the abnormal phenom-
ena, the analyzed results have indicated a number of singu-
larities associated with the possible seismic anomalies of the
earthquake and from the comparative experiments and anal-
yses by using the two methods, which follow the same time
and space, we conclude that the singularities observed from
19 to 24 December 2009 could be the earthquake precursor
of Haiti earthquake.
1 Introduction
Outgoing longwave radiation (OLR) of the Earth is a ma-
jor driver of the Earth system climate. The reflection, ab-
sorption, and emission of this energy occur through a com-
plex system of clouds, aerosols, atmospheric constituents,
oceans and land surfaces (Ouzounov et al., 2007). OLR esti-
mates have been obtained since June 1974 from the window
Correspondence to: P. Xiong
(xiong.pan@gmail.com)
channel measurements of the operational National Oceano-
graphic and Atmospheric Administration (NOAA) polar-
orbiting satellites (Gruber and Krueger, 1984; Gruber and
Winston, 1978). These estimates have been used extensively
to study natural disasters, both as one component of the radi-
ation balance of the atmosphere (Ohring and Gruber, 1982)
and to infer changes before natural disasters, like earthquakes
(Liu et al., 1997).
The techniques to use the OLR estimates have been devel-
oped to detect seismic precursors within OLR data prior to
earthquakes, which is vitally important to sufficiently make
use of OLR resources to monitor stable conditions of active
faults beneath the earth and to identify the potential earth-
quake zones. Liu and Kang have studied the spatial and tem-
poral variability of outgoing long wave radiation before and
during major earthquakes using the method of Eddy field cal-
culation mean (Liu et al., 1999), and found that the radia-
tion intension around epicenter district is much more inten-
sive, especially in a short term (one or two month) before
earthquakes (Kang and Liu, 2001; Liu, 2000). A analysis
based on mathematical statistics and spatial features shows
that there are strongly seasonal and regional variations in
China using 30 years (1979–2008) OLR data, that is, lower
value in Qinghai-Tibet Plateau and higher in northwest and
east of China, the variability of OLR in these regions are
dramatic in the spring and autumn and relatively smooth
in the summer and winter (Feng et al., 2009). More re-
cently, Xiong et al. (2009a, b) have conducted a study to
detect OLR anomalous using the method of wavelet max-
ima, which is introduced by Cervone et al. (2004, 2005) as a
new data mining methodology based on wavelet transforma-
tions and statistical analysis to detect precursory signals as-
sociated with earthquakes. The prominent OLR singularities
could be found prior to the earthquakes in the wavelet max-
ima curves, which follow continuity both in space and time
based on numerous comparative experiments and analyses of
the earthquakes occurred in China (Xiong et al., 2009a, b).
Published by Copernicus Publications on behalf of the European Geosciences Union.
2170 P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake
In this paper, the presented methodology calculates Eddy
field, which could highlight the singularity within data, and
uses wavelet transformations as data mining tools by com-
puting the wavelet maxima, which could be used to identify
obvious anomalies within OLR data. The two methods has
been applied to carry out a comparative analysis of OLR data
associated with the earthquake recently occurred in Haiti on
12 January 2010. Combining with the tectonic explanation of
spatial and temporal continuity of the abnormal phenomena,
the analyzed results have indicated a number of singularities
associated with the possible seismic anomalies of the earth-
quake.
2 Earthquake and data
In this study, Haiti earthquake of magnitude 7.0 is selected
for evaluating the proposed methods. It occurred on 12 Jan-
uary 2010, the location of the epicenter is at 18.457
◦
N,
72.533
◦
W (Fig. 1a), and the depth is 13km (8.1miles). The
main earthquake was followed by a series of smaller after-
shocks.
The OLR energy flux is characterized by a number of
parameters, such as the emission from the ground, atmo-
sphere and clouds formation, which have been being ob-
served on the top of the atmosphere by National Oceanic
and Atmosphere Administration (NOAA) satellites (NCAR
and NOAA, 2008). These OLR data have been recorded
twice-daily by the several polar-orbiting satellites for more
than eight years, forming time series data across the differ-
ent periods of time along with the spatial coverage of the
entire earth. The original OLR data are processed by the
interpolation technique to minimize the distance in space
or time over which the value is interpolated. The detail of
the interpolation technique has been given by Liebmann and
Smith (1996).
The NOAA Climate Prediction Center web site (
http://
www.cdc.noaa.gov/) provides the daily and monthly OLR
data. The OLR algorithm for analyzing the Advanced Very
High Resolution Radiometer (AVHRR) data is from Gruber
and Krueger (1984), and integrates infrared radiation data be-
tween 10µm and 13 µm. These data are mainly sensitive to
near surface and/or cloud temperatures. Our study includes
analysis of OLR data used measurements from four AVHRR
polar orbiters NOAA-18. The data used for this study are
twice-daily means from the NOAA-18 satellite. Their spatial
coverage is 1× 1degree of latitude by longitude covering the
area of 90
◦
N–90
◦
S and 0
◦
E–360
◦
E, and the time range is
from 1 February 2009 to 31 February 2010, forming time
series data over the specified region.
3 Methodology
There are several methods to choose in the analysis of OLR
data, mainly including the method of difference value (Kang
et al., 2006), the method of the Eddy field calculation mean
(Kang and Liu, 2001; Liu, 2000; Liu et al., 1999), thewavelet
time-frequency analysis method (Wang et al., 2008; Xiong
et al., 2009a, b; Feng et al., 2009) and the method of std
threshold (Feng et al., 2010). In previous study by using
these methods, the method of the Eddy field calculation mean
calculates Eddy field, which could highlight the singularity
within OLR data between adjacent points, and the wavelet
time-frequency analysis method is capable of providing the
time and frequency information simultaneously, hence giving
a time-frequency representation of the signal, that could de-
tect the prominent OLR singularities follow continuity both
in space and time. These two methods are more effective
and obvious to detect anomalies within OLR data related to
earthquake, which is in good accordance with previous study.
In this paper, we have undertaken a comparative analysis
using the two methods for our study. The method of Eddy
field calculation mean, and the method of wavelet maxima,
with the wavelet method of the Daubechies Wavelets, called
a db1. We use these two methods to detect singularities
within the OLR data in time and space covering the selected
earthquake.
3.1 The method of Eddy field calculation mean
The Eddy field calculation mean (Kang and Liu, 2001; Liu,
2000; Liu et al., 1999) refers to “the total sum of the differ-
ence value” of “the measured value” of OLR data between
adjacent points in the current day (month), its expression is
S
∗
d
x
i,j
,y
i,j
= 4· S
x
i,j
,y
i,j
−
S
x
i−1,j
,y
i,j
+ S
x
i,j
,y
i,j −1
+ S
x
i+1
,y
i,j
+ S
x
i,j
,y
i,j +1
. (1)
Where S
∗
d
(x
i,j
,y
i,j
) – daily Eddy field; S(x
i,j
,y
i,j
) – daily
mean; x – latitude, y – longitude; i, j – any number of grid
points.
The following describes the experimental procedure and
analysis method through an example of the Haiti earthquake
using OLR daily data.
First, based on historical seismic activities and tectonic
characteristics (Fig. 1a), we define an experimental area in
the 10× 10 degree of latitude by longitude area over the epi-
center (Fig. 1b). The duration of the OLR data used here
is from 1 to 24 January 2010. By calculating daily Eddy
field using expression (1) within the selected OLR daily
data, and using the method of mesh grid to transform vectors
x(latitude) and y(longitude) into arrays X and Y. The rows of
the output array X are copies of the vector x; columns of the
output array Y are copies of the vector y, using the method
of 2-D data (arrays X and Y) interpolation returns matrix C
(interpolated Eddy field) containing elements corresponding
to the elements of X and Y and determined by interpolation
within the 2-D function specified by matrices X, Y, and Z
(Eddy field), the interpolation method we used here is Cubic
interpolation, as long as data is uniformly-spaced.
Nat. Hazards Earth Syst. Sci., 10, 2169–2178, 2010 www.nat-hazards-earth-syst-sci.net/10/2169/2010/
P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake 2171
Fig. 1. (a) Historic seismicity (1990 to Present) of Haiti region. The epicenter of Haiti earthquake is marked with a star. The major tectonic
boundaries (Subduction Zones – purple, Ridges – red and Transform Faults – green) are also indicated (source: USGS). (b) Map of the
region of the earthquake. The epicenter is marked with a red star. The grids used in the experiment are indicated in gray.
With shading interpolation function (varies the color in
each line segment and face by interpolating the color map
index or true color value across the line or face), each cell
in matrix C (interpolated Eddy field) is colored by bilinear
interpolation of the colors at its four vertices. The minimum
and maximum elements of C are assigned the first and last
colors in the color map. Colors for the remaining elements
in C are determined by a linear mapping from value to color
map element, and we can get the daily Eddy field map by
drawing a pseudo color plot of the elements of C at the loca-
tions specified by X and Y.
Second, we rearrange every Eddy daily field curve onto
one diagram to form Eddy OLR curves of January 2010 as
shown in Fig. 2. In the figure the x-axis of each Eddy OLR
curve represents longitude, and the y-axis of each Eddy OLR
curve represents latitude. The magnitudes of color map rep-
resent the degrees of intensity where the larger the magni-
tude, the higher the degree of intensity. The figure heading
lists date of the used OLR daily data, epicenter is marked
with red star, tectonic plate boundaries with white line.
Final stage is to identify variability from the Eddy field
curves. The key feature of variability is that they appear
near epicenter with a large magnitude. In Fig. 2, we can find
several variability, which can be grouped into three types –
pre- and post-earthquake and when the earthquake occurred,
corresponding to (1) variability prior to the earthquake, sev-
eral high value variability appears around the epicenter, such
as Eddy daily field of 4, 8 and 11 January 2010 in Fig. 2a,
which may be caused by the large energy flux before the Haiti
earthquake; (2) variability in the time when the earthquake
occurred, such as Eddy daily field of 12 January 2010 in
Fig. 2a, whichmay be caused by the release of a largeamount
of energy; (3) variability after the earthquake, such as Eddy
daily field from 13 to 16 January 2010 in Fig. 2b, perhaps
caused by many aftershocks after the earthquake.
3.2 The method of wavelet maxima
The basic theory of wavelet transformation and singulari-
ties calculation based on wavelet maxima has been described
in the references (Grossman and Morlet, 1984; Mallat and
Hwang, 1992), and the detail description of the experimental
procedure of the method of wavelet maxima has been given
in the references (Xiong et al., 2009a, b). In this paper, for
studying seismic impact on spatial extent, we carried out a
new experiment by enlarging spatial extent of experimental
area.
First, we define an experimental area. By taking into ac-
count the tectonic background, continental boundaries and
active faults (Fig. 1a), we define an experimental area and
divide it into a set of grids of 3 × 3 degree of latitude by
longitude area over the epicenter, use the method of wavelet
maxima (Xiong et al., 2009a, b), we can get wavelet maxima
curves.
By enlarging spatial extent of experimental area, we divide
the experimental area into a set of grids from 5× 5degree of
latitude by longitude area over the epicenter to 9 × 9degree
of latitude by longitude area over the epicenter.
Second, based on the defined grids, OLR daily data, from
1 February 2009 to 31 February 2010, are downloaded from
the NOAA Climate Prediction Center. After pre-processing,
we employ the wavelet method db1 to analyze the data
and generate wavelet maxima curves. The scale of wavelet
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2172 P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake
Fig. 2. Eddy field OLR (day data) curves (a) from 1 to 12 January 2010, before Haiti earthquake, (b) from 13 to 24 January 2010, after Haiti
earthquake. Epicenter is marked with red star, tectonic plate boundaries with white line, Longitude from 282.5
◦
to 292.5
◦
, Latitude from
13.5
◦
N to 23.5
◦
N.
method here we used is 16, so the corresponding maxima
columns are 16 each time. To get maxima more effectively
and easy for visualize, we calculate the mean value of max-
ima each time/row, so the maxima column become 1 each
time. In the same spirit, we use the same method to cal-
culate the corresponding maxima of the experimental area
with a set of grids from 5 × 5degree of latitude by longitude
area over the epicenter to 9× 9degree of latitude by longi-
tude area over the epicenter.
Third, analyze the result using the method of wavelet max-
ima. The result of the new experiment indicated that the time
when singularity appeared is consistency in different spatial
scales, which will be discussed in next section.
4 Results and discussion
1. Using the method of Eddy field calculation mean, with
the OLR data from 1 to 24 January 2010. We get Eddy
field OLR (day data) curves(Fig. 2) and Eddy field OLR
(night data) curves (Fig. 3) from 1 to 24 January 2010,
the Epicenter is marked with red star, tectonic plate
boundaries with white line, Longitude is from 282.5
◦
to 292.5
◦
and Latitude is from 13.5
◦
N to 23.5
◦
N.
From Fig. 3a several singularities are identified before
Haiti earthquake, all of them are around the Haiti earth-
quake epicenter. These singularities may be caused by
the large amount of energy generated by the Haiti earth-
quake, and singularities in the day when the earthquake
occurred, which may be caused by the release of a large
amount of energy; after the earthquake (Fig. 3b), in
Eddy daily field of 20 and 21 January 2010, obvious
singularities could be observed, which perhaps caused
by many aftershocks after Haiti earthquake.
Compared with Fig. 2, the distribution of the singular-
ities before earthquake in Fig. 3a is similar to that in
Fig. 2a, but the Eddy OLR curves before earthquake
in Fig. 3a are more disorder with larger magnitudes,
and singularity in the day when the earthquake occurred
(12 January 2010) could be clearly observed, we con-
clude the cause could be due to that the time that earth-
quakes occurred is at night.
2. In order to examine the result by the method of Eddy
field calculation mean above, byenlarging spatial extent
from 3× 3degree of latitude by longitude area over the
epicenter to 9× 9degree of latitude by longitude area
over the epicenter, we get wavelet maxima curves of a
set of grids of 3× 3degree of latitude by longitude area
over the epicenter (Fig. 4), wavelet maxima curves of a
set of grids of 5× 5degree of latitude by longitude area
over the epicenter (Fig. 5), wavelet maxima curves of a
set of grids of 7× 7degree of latitude by longitude area
Nat. Hazards Earth Syst. Sci., 10, 2169–2178, 2010 www.nat-hazards-earth-syst-sci.net/10/2169/2010/
P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake 2173
Fig. 3. Eddy field OLR (night data) curves (a) from 1 to 12 January 2010, before Haiti earthquake, (b) from 13 to 24 January 2010, after
Haiti earthquake. Epicenter is marked with red star, tectonic plate boundaries with white line, Longitude from 282.5
◦
to 292.5
◦
, Latitude
from 13.5
◦
N to 23.5
◦
N.
over the epicenter (Fig. 6) and wavelet maxima curves
of a set of grids of 9 × 9 degree of latitude by longitude
area over the epicenter (Fig. 7).
From Fig. 4, the location of study girds is from 17
◦
N,
286
◦
E to 20
◦
N, 289
◦
E, it can be seen that the distri-
bution of singularities is discontinuous and disorder, all
of the singularities are not obvious except one before
earthquake, which is around December 2009, about one
month before Haiti earthquake. Around the earthquake,
no obvioussingularities could be observed, which is dif-
fer from the results using the method of Eddy field cal-
culation mean.
In order to examine the reliability of the result of
wavelet maxima analysis curves of a set of grids of
3× 3 degree of latitude by longitude area over the epi-
center and study seismic impact on spatial extent, we get
wavelet maxima curves of a set of grids of 5× 5degree
of latitude by longitude area over the epicenter (Fig. 5)
by enlarging spatial extent of experimental area, which
is wavelet maxima curves from Grid1 to Grid25, the lo-
cation which is from 16
◦
N, 285
◦
E to 21
◦
N, 290
◦
E.
The singularities in Fig. 5 are not obvious but one con-
tinuous and obvious singularity could be also observed
around December 2009, which is the same as in Fig. 4.
Comparing Fig. 5 with Fig. 4, the distribution of the sin-
gularities is similar, but singularities in Fig. 5 are more
disorder with smaller magnitudes, a possible reason for
this is the spatial extent in Fig.5 is larger, resulting in a
smaller distribution of average energy in experimental
areas.
To get more persuasive experimental results, we con-
tinue to enlarge spatial extent of experimental area to
7× 7 degree of latitude by longitude area over the epi-
center (Fig. 6) and 9× 9 degree of latitude by longitude
area over the epicenter (Fig. 7), the location of which are
from 15
◦
N, 284
◦
E to 22
◦
N, 291
◦
E and 14
◦
N, 283
◦
E
to 23
◦
N, 292
◦
E, respectively.
Compared with Fig. 4 and Fig. 5, the feature of the sin-
gularities in the wavelet maxima curves from 7 × 7degree of
latitude by longitude area over the epicenter (Fig. 6) and the
wavelet maxima curves 9× 9 degree of latitude by longitude
area over the epicenter (Fig. 7) is similar, which could be
summarized as follows:
1. The singularities in Figs. 6 and 7 are not obvious butone
continuous and obvious singularity is around December
2009, which is the same as Figs. 4 and 5.
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2174 P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake
Fig. 4. Wavelet maxima analysis curves from Grid1 to Grid9, with a set of grids of 3× 3degree of latitude by longitude area over the
epicenter, the dashed line indicates the day when the earthquake occurred.
Fig. 5. Wavelet maxima analysis curves from Grid1 to Grid25, with a set of grids of 5× 5 degree of latitude by longitude area over the
epicenter, the dashed line indicates the day when the earthquake occurred.
Nat. Hazards Earth Syst. Sci., 10, 2169–2178, 2010 www.nat-hazards-earth-syst-sci.net/10/2169/2010/
P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake 2175
Fig. 6. Wavelet maxima analysis curves from Grid1 to Grid49, with a set of grids of 7× 7 degree of latitude by longitude area over the
epicenter, the dashed line indicates the day when the earthquake occurred.
Fig. 7. Wavelet maxima analysis curves from Grid1 to Grid81, with a set of grids of 9× 9 degree of latitude by longitude area over the
epicenter, the dashed line indicates the day when the earthquake occurred.
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2176 P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake
Fig. 8. Wavelet maxima curves based on spatial continuity analysis of December 2009. Epicenter is marked with red star, tectonic plate
boundaries with white line.
2. Comparing Figs. 4 and 5, the distribution of the singu-
larities from Figs. 6 and 7 is similar, but more disorder
with smaller magnitudes.
From above discussion, one similar result from Fig. 4 to
Fig. 7 could be extracted is that one continuous and obvious
singularity around December 2009. To get more visual re-
sult, we used the OLR day data of December 2009 to draw
wavelet maxima curves based on spatial continuity analysis
(Fig. 8).
From Fig. 8, singularities form 19 to 24 December 2009
could be obviously observed, the largest magnitude of singu-
larities appear on 20 December 2009 and gradually weaken
after 20 December, thus we postulated that such effect would
result from the large energy flux before the Haiti earthquake.
In order to validate the postulate above, we get Eddy field
OLR (day data) curves of December 2009 (Fig. 9), and
several singularities can identified form 19 to 24 Decem-
ber 2009 in Eddy field OLR (day data) curves of December
2009 (Fig. 9), all of them are around the Haiti earthquake
epicenter, the distribution of the singularities is similar as in
Fig. 8.
5 Conclusions
This paper presents an analysis on the selected OLR data as-
sociated with the Haitiearthquake and explains how the OLR
singularities discovered which could be related to the earth-
quakes.
The methodology of wavelet maxima discussed in the
present paper uses data mining techniques, including wavelet
transformations and spatial/temporal continuity analysis of
the wavelet maxima to identify singularities before the earth-
quakes. Compared with the method of wavelet maxima,
the method of Eddy field calculation mean appears also be
effective in detecting seismic anomalies in the OLR data,
which is more visual to detect OLR anomalies before earth-
quake.
The conclusion using the two methods is similar, which
could be summarized as follows: several singularities may
be caused by the large amount of energy generated are iden-
tified before Haiti earthquake, and singularities in the day
when the earthquake occurred also could be detected, which
may be caused by the release of a large amount of energy;
after the earthquake obvious singularities could be observed,
which perhaps caused by many aftershocks after the earth-
quake. And from the comparative experiments and anal-
yses using the two methods, which follow the same time
Nat. Hazards Earth Syst. Sci., 10, 2169–2178, 2010 www.nat-hazards-earth-syst-sci.net/10/2169/2010/
P. Xiong et al.: Outgoing longwave radiation anomalies associated with Haiti earthquake 2177
Fig. 9. Eddy field OLR (day data) curves of December 2009, for Haiti earthquake, epicenter is marked with red star, tectonic plate boundaries
with white line.
and space, we conclude that the singularities observed from
19 to 24 December 2009 could be the earthquake precursor
of Haiti earthquakes.
Therefore our studies provide a finding that singularities
discovered within OLR data could be regarded as an effective
indicator to detect seismic anomalies. This finding will be
further validated by using more earthquake data in the future.
Acknowledgements. This work is supported by the project of
“Study of earthquake integrated identified index and method
based on multiple parameters of satellite infrared remote sensing
(founded by the Ministry of Science and Technology of China,
Grant No.: 2008BAC35B03-05)” and the project of “Data Mining
with Multiple Parameters Constraint for Earthquake Prediction
(founded by the Ministry of Science and Technology of China,
Grant No.: 2008BAC35B05)”. The authors would like to acknowl-
edge NOAA for making OLR data available for various research
communities, and thank Daya Shanker and another referee for
assisting in evaluating this paper.
Edited by: M. E. Contadakis
Reviewed by: D. Shanker and another anonymous referee
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