The feasibility of using TRMM satellite data for missing terrestrial stations in Iraq for mapping the rainfall contour lines

Abstract

Rainfall data are considered an important and critical element of many environmental and hydrological studies such as drought, desertification, climate change and other strategic studies. These studies are mainly based on the rainfall data archive for previous years. During the last two decades, a large number of meteorological stations have been destroyed as a result of wars and internal conflicts, reducing the stations to 16 after the number was more than 30 stations, resulting in a significant lack of meteorological data archive. In addition to the spatial distribution of these stations does not adequately cover Iraq. The research aim to evaluate the feasibility of the TRMM satellite data (3B42 V7 product) to complete the rainfall data archive of the missing terrestrial stations. Several rainfall contour maps of the season 2017-2018 were drawn from data of 16 terrestrial stations, 16 and 30 stations derived from TRMM satellite data, and a hybrid map derived from the TRMM satellite data and available terrestrial stations, afterwards there were compared with the general rainfall contour map. The correlation was made between the satellite data and terrestrial stations data, and the results showed a positive correlation with a strong correlation coefficient reach to 0.91. The results showed that TRMM data could be used as a good alternative to terrestrial station data for its accuracy, wide coverage and ease of availability.

Full text

*Corresponding Author: zaidoon.taha@live.co m
(Z.T. Abdulrazzaq Orcid: 0000-0002-0234-0872)
Received 16 April 2020 Revised 07 May 2020 Accepted 07 May 2020
Civil Enginering Beyond L imits 3 (2020) 15-19
2687-5756 © 2019 ACA Publishing. All rights reserved.
https://doi.org/10 .36937/cebe l.2020.003.003
15
Civil Engineering Beyond Limits 3 (2020) 15-19
Civil Engineering Beyond Limits
www.acapublishing.com
Research Article
The feasibility of using TRMM satellite data for missing terrestrial stations in Iraq for
mapping the rainfall contour lines
Zaidoon T. Abdulrazzaq
Directorate of Space and Communication, Ministry of Science and Technology, Baghdad 10070, Iraq.
Corresponding author, e_mail: zaidoon.taha@live.com
Abstract
Rainfall data are considered an important and critical element of many environmental and hydrological studies
such as drought, desertification, climate change and other strategic studies. These studies are mainly based on
the rainfall data archive for previous years. During the last two decades, a large number of meteorological
stations have been destroyed as a result of wars and internal conflicts, reducing the stations to 16 after the
number was more than 30 stations, resulting in a significant lack of meteorological data archive. In addition to
the spatial distribution of these stations does not adequately cover Iraq. The research aim to evaluate the
feasibility of the TRMM satellite data (3B42 V7 product) to complete the rainfall data archive of the missing
terrestrial stations. Several rainfall contour maps of the season 2017-2018 were drawn from data of 16 terrestrial
stations, 16 and 30 stations derived from TRMM satellite data, and a hybrid map derived from the TRMM satellite
data and available terrestrial stations, afterwards there were compared with the general rainfall contour map.
The correlation was made between the satellite data and terrestrial stations data, and the results showed a
positive correlation with a strong correlation coefficient reach to 0.91. The results showed that TRMM data could
be used as a good alternative to terrestrial station data for its accuracy, wide coverage and ease of availability.
Keywords: Terrestrial stations, TRMM, Rainfall contour map, Drought, Precipitation radar
1. Introduction
The precipitation plays an important role in the hydrological cycle
and has obvious repercussions on human life (agriculture, water
resources). From a climatic point of view, the intensity and
distribution of precipitation are undoubtedly modified in the context
of global climate change, known mainly by its aspect of warming
temperatures. However, we do not know which way and which regions
are likely to be the most affected. Precipitation measurements are
essential to improve our understanding of the mechanisms of climate
change [1]. To do that, climate-related studies need extensive data to
cover events and arrive at the best conclusions. In addition, updating
the rainfall contour map is an important pillar in strategic studies.
Satellite measurements began in the 1970s, with equipment
measuring in the infrared domain. Infrared imagers measure the
temperature at the top of the clouds to relate it indirectly to the
precipitation they generate. A second frequency domain useful in
measuring precipitation is the microwave domain. Microwave
measurements are direct measurements of the absorption and
emission or diffusion of radiation by water drops and ice crystals
contained in clouds [2].
The meteorological data obtained from the terrestrial stations are no
longer sufficient for conducting regional studies, especially in
developing countries, but are restricted to local studies with small
areas. Therefore, many researchers e.g. [3-6] turned to the use of data
that obtaining from the meteorological space radar of Airborne via
satellite. Iraq is one of these countries that owns a few earth stations.
Moreover, several stations have been destroyed as a result of the
military operations against ISIS gangs that have occurred since 2014
and until now. Where it became the number of terrestrial stations at
the present time is 16 after the number was more than 30 stations.
Thus, it was necessary to use an alternative resource that provides a
solution to the problem of the lack of the meteorological data, and the
most prominent of these data are from the TRMM (Tropical Rainfall
Measuring Mission) satellite [7]. The study aims to produce an updated
the rainfall contour map by integration the meteorological data of the
terrestrial stations and TRMM satellite as one of the meteorological
and agricultural droughts indicators.
2. Materials and Methods
2.1. TRMM Overview
The TRMM satellite constitutes the first space mission dedicated to
the measurement of precipitation in the tropics and sub-tropics. It is
a joint mission of the American agency NASA (National Aeronautics
and Space Administration) and the Japanese agency NASDA (National
Space Development Agency of Japan) now called JAXA (Japan
Aerospace and Exploration Agency), whose objectives are to measure
precipitation as well as energy exchanges (latent heat) in tropical
regions [8]. The satellite was launched on November 27, 1997 for an
expected duration of three years. In August 2001, the satellite’s
altitude was increased from 350 to 403 km to extend its lifespan by a
few years. In 2010, the satellite was still active [9].
The idea of measuring precipitation using a combination of passive
and active microwave space instruments was introduced in the early
1980s. The start of the reflection on the TRMM mission took place in
1984. After preliminary studies, the inclined orbit between 35° N and
35° S at an altitude of 350 km was chosen. The orbit chosen is such
that the satellite flies over a place at a different time each day with a

Abdulrazzaq
Civil Engineering Beyond Limits 3 (2020) 15-19
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cycle of about 42 days. This non-helio-synchronous orbit makes it
possible to document the large daily variation in tropical
precipitation. The low altitude of 350 km is chosen according to the
needs of the radar measurement (backscattered radiation strong
enough to be measured by the radar receiver).
The TRMM satellite carries five instruments (Fig. 1), three of which are
specifically dedicated to the observation and estimation of
precipitation:
1- The VIRS (Visible and Infrared Scanner). It is a Visible-Infrared
radiometer with 5 channels at wavelengths 0.63 μm, 1.6 μm, 3.75 μm,
10.8 μm and 12 μm.
2- The TMI instrument (TRMM Microwave Imager) is a multi-
frequency microwave radiometer comprising 8 channels polarized
horizontally and vertically at frequencies 10.7 GHz, 19.3 GHz, 37 GHz
and 85.5 GHz, and a vertically polarized 21.3 GHz channel.
3- PR radar (Precipitation Radar). It is a radar operating at a frequency
of 13.8 GHz and allowing the measurement of vertical rain profiles.
4- The CERES instrument (Cloud and Earth’s Radiant Energy System)
is a wide-band VISIR radiometer dedicated to the study of the
radiation balance. It comprises three radiometric sensors, which
measure the solar radiation reflected by the Earth in the interval 0.3
- 0.5 μm, the radiation reflected and emitted by the Earth in the
interval 0.3 -100 μm, and the wave radiation long emitted by the Earth
in the interval 8 - 12 μm with a spatial resolution of 10 km at nadir.
Coupled with latent heat estimates derived from precipitation
estimates, the radiation budget estimates obtained from CERES
measurements describe the entire energy balance of the Earth's
atmosphere. However, the instrument onl y worked during the months
of January to August 1998 and during the month of March 2000.
5- The LIS (Lightning Imaging Sensor) is an imager dedicated to the
observation of lightning [9].
Figure 1. Schematic view of the scanning geometries of the TMI,
VIRS and PR instruments of TRMM [10]
2.2. TRMM TMPA 3B42 RT and V7 products
The TRMM-TMPA 3B42 (TRMM Multi-satellite Precipitation Analysis)
algorithm, developed by NASA, is a precipitation estimation product
from the TRMM which combines satellite data and data on the ground
[11-13]. The infrared sources for TRMM-TMPA 3B42 V7 come from the
operational geostationary environmental study satellites (GOES) West
and East, the geostationary meteorological satellite (GMS), the
METEOSAT-5 and METEOSAT-7 satellites and the NOAA-12 polar orbit
(National Oceanic and Atmospheric Administration). PMW sources
come from radiometers present in low-orbiting satellites TMI, SSMI
(Special Sensor Microwave Imager), AMSU (Advanced Microwave
Sounding Unit), and AMSR (Advanced Microwave Scanning
Radiometer).
There are two datasets from the TRMM-TMPA 3B42 algorithm: the first
is TRMM-TMPA 3B42 V7, which is the research version, available
approximately two months after the observation. The second is
TRMM-TMPA 3B42 RT which is the real-time version, available
approximately 6 to 9 hours after the observation, but which does not
take into account the data on the ground. Over the past 10 years, the
TRMM-TMPA 3B42 algorithm has undergone three major updates due
to the new sensors used by the algorithm [12].
The data output from the TRMM-TMPA 3B42 algorithm has a time
resolution of 3 hours with precipitation rate values in mm / h. The
geographic area covered extends from latitude 50 ° S to 50 ° N for 3B42
V7 (Fig. 2) and from 60 ° S to 60 ° N for 3BR42 RT for a spatial resolution
grid of 0.25 ° x 0.25 °. Product data is available from January 1, 1998
to date for 3B42 V7 and from March 1, 2000 to today for 3B42 RT [14].
Figure 2. The coverage area of TRMM-TMPA 3B42 V7 [15]
2.3. Data collection
In this study, data from terrestrial stations and satellite-derived were
used for the period 2017–2018. The period starts from 1 September
and ends on April 31, which is considered the rainy season in Iraq. 16
terrestrial stations data (Table 1) were available out of 30 stations (Fig.
3). On the other hand, 16 and 30 stations data were derived from
TRMM satellite data as a terrestrial station equal to ground stations.
These stations were chosen on the basis of their proximity to the
missing terrestrial stations with a distance of no more than 50 km. In
order to represent it as much as possible. TRMM-TMPA 3B42 V7
product is used in this study, with a spatial resolution of 0.25° × 0.25°
which downloading from TOVAS system. Firstly, the area of interest is
defined, and selecting the time interval, then the data are visualized.
Four format data types can download it, including HDF, NetCDF, ASCII,
and Google Earth KMZ [16]. The TRMM data were downloaded as a
NetCDF format to operate it in ArcGIS software for mapping the
rainfall contour lines using Kriging interpolation method to estimate
the rainfall distribution in Iraq.

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Table 1. The available and missing data of the terrestrial stations [17]
and TRMM data [18] for the season of 2017–2018.
No
Terrestrial stations data TRMM data
Station
Name Lat. Long. Rainfall
(mm) Lat. Long. Rainfall
(mm)
1
Mosul
36.375
43.125
290
36.125
43.125
304.751
2
Kirkuk
35.375
44.375
253
35.375
44.125
338.3469
3
Tuz
34.875
44.625
252
34.875
44.375
295.3835
4
Khanaqin
34.375
45.375
295
34.375
45.125
371.6543
5
Khales
33.833
43.533
203
33.875
43.625
199.0592
6
Baghdad
33.375
44.375
183
33.375
44.125
198.9865
7
Kerbela
32.625
44.125
111
32.375
44.125
184.3744
8
Hilla
32.45
44.45
118
32.125
44.375
140.4296
9
Aziziyah
32.91
45.066
155
32.875
45.125
242.9573
10
Kut
32.5
45.816
126
32.375
45.875
164.6396
11
Najaf
31.875
44.375
91
31.875
44.375
106.034
12
Diwaniya
31.875
44.875
82
31.625
45.125
96.83266
13
Samawa
31.375
45.375
72
31.375
45.375
80.27095
14
Nasiriya
31.125
46.125
58
31.125
46.125
71.5834
15
Amara
31.875
47.125
103
31.875
46.875
114.5546
16
Basra
30.625
47.875
66
30.625
47.875
103.7755
17
Tel-Afar
36.375
42.375
-
36.375
42.375
332.5606
18
Sulamaniy
a
35.375 45.375 - 35.375 45.375 756.343
19
Arbil
36.125
43.875
-
36.125
43.875
463.1895
20
Samarra
34.125
43.875
-
34.125
43.875
208.8148
21
Hai
32.125
45.875
-
32.125
45.875
124.4244
22
Ana
34.375
41.875
-
34.625
41.875
73.91969
23
Rutba
32.875
40.375
-
32.875
40.375
56.17239
24
Baiji
34.875
43.375
-
34.875
43.125
194.5393
25
Ain Al
Tamur
32.58 43.46 - 32.625 43.125 117.9774
26
Al Misiab
32.71
44.12
-
32.875
44.125
187.0971
27
Al Qa'im
34.30
41.09
-
34.375
41.375
70.52767
28
Ar Ramadi
33.32
43.34
-
33.375
43.125
142.7511
29
Shamiya
31.89
44.49
-
31.875
44.625
122.5724
30
Hit
33.59
42.78
-
33.375
42.625
114.0135
Figure 3. The distribution of the available and missing terrestrial
stations in Iraq
3. Results and Discussion
The knowing of the trend of changes in rainfall and temperature rates
is extremely important in knowing possible future environmental
changes, and their impact on the national economy, and constitute
one of the most important factors guiding the planning of the national
economy, and the stability of agricultural production in Iraq depends
on securing irrigation water on schedule.
The rainfall in Iraq was characterized in general by its irregular
distribution in terms of place and time, as the amount of rain recorded
in the terrestrial stations varies from place to another according to
the height of the sea surface and the geographical location of the
station, as it increases in high places in general. The main source that
supplies Earth with water is the rainfall that can be studied in two
terms: the spatial distribution and the temporal distribution.
Figure 4a shows clearly deformed rainfall lines due to the few number
of terrestrial stations and their poor geographical distribution.
Likewise, in Figure 4b for the same reasons, compared to the last
rainfall contour map (Fig. 5) produced by Jassim et al (2012) [19]. On
the other hand, Figure 6 shows a good distribution of rainfall lines,
due to the increase in the number of TRMM stations. While the hybrid
map derived from the TRMM satellite data and terrestrial stations (Fig.
7) showed a very good matching.
Rainfall contour maps have a great importance for production the
areas suitable for permaculture and the most area vulnerable to
drought. Through observing the 100 mm contour line (which is the
critical line for drought), we notice that the southern and
southwestern part of Iraq is the most vulnerable to drought. However,
this is difficult to guess from the maps drawn from 16 stations.
In Figure 4a and b, the data is not uniformly distributed along the
study-area. This is of course very usual for hydrological studies under
the current circumstances. The problem is that the extend the area of
interest to cover the whole country, and disregarding the fact that the
estimations in areas where the data network is dense are much more
accurate than in areas where the observation network is less dense or
does not even exist. In this case, the results would be is not accurate
and not applicable.
Figure 4. The rainfall contour map for the season of 2017–2018, a-
based on 16 terrestrial stations, b- based on 16 stations derived from
TRMM data

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Figure 5. The rainfall contour map for the season of 2010–2011
based on 23 terrestrial stations [18]
Figure 6. The rainfall contour map for the season of 2017–2018
based on 30 stations derived from TRMM data
Regression analysis was made between terrestrial stations and TRMM
data (Fig. 8) to validate the TRMM data, where the relationship was
normal and linear with 0.91 R-squared (the correlation coefficient).
Where the correlation coefficient gives evidence of the
appropriateness of the data when it approaches the value of 1 [20].
Figure 7. Hybrid rainfall contour map for the season of 2017–2018
based on 16 terrestrial stations and 14 stations derived from TRMM
data
Figure 8. Regression analysis between terrestrial and TRMM rainfall
data.
TRMM data have some limitations, as some systematic errors can
result in them. One of these limitations is the presence of land water‐
bodies (e.g. lake and marsh) [21], where measurements are inaccurate
over or near these water bodies. This is due to the fact that the radar
sensor will calculate the evaporated water vapor from the water
bodies as a rain precipitation. Another limitation is the existence of
topography that may cause terrain-induced errors on remote sensing
retrievals [22, 23].
As indicated in Figure 8 the correlation is higher for the rainfall
values less than 150-200 mm. According to this data and the positions
of the missing stations, those are generally located in this range.
While the data with less correlation are more likely to be near water
bodies or areas with high topography. This can be seen clearly when
we used the whole accumulated rainfall grid values as shown in
Figure 9. The closed areas are associated with water bodies (see Fig. 3),
whereas irregular contour lines are noticed in the northern region,
which is associated with topographic areas. Therefore, the data that
generates systematic errors must be reduced or ignored when need to
using the whole TRMM grid data.

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Figure 9. The rainfall contour map for the season of 2017–2018
based on the whole TRMM grid data
4. Conclusions
TRMM is a research satellite designed to improve knowledge of the
distribution and variability of precipitation, as part of the water cycle
in the climate system. In the present study, the accuracy of TRMM
satellite precipitation data for the season of 2017–2018 was evaluated.
The results indicate that there is a high correlation between satellite
precipitation data and terrestrial data and, it has a correlation
coefficient 0.91, which is a high accuracy. Therefore, it is suitable to
use it in meteorological and hydrological studies, and rainfall contour
maps. In addition, TRMM data can be used to compensate for the lack
of archival data for previous years due to its good and realistic results.
Besides, the choose of TRMM stations should considering the
existence of the topography and water bodies that may cause errors
on remote sensing retrievals. Finally, the large number of stations
may not produce good results in contour mapping if they are not well
distributed.
Declaration of Conflict of Interests
The author declares that there is no conflict of interest.
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