Indian Journal of Radio & Space Physics
Vol. 38, August 2009, pp. 215-219
Subsurface thermal mapping during contrast seasons over Central Kerala
Michael G Pious1, S Abraham Thambi Raja2,$,* & Oscar Dhas T Xavier2
1
Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu
Department of Physics, Lekshmipuram College of Arts and Science, Neyyoor 629 802, Tamil Nadu
$
E-mail: [email protected]
2
Received 19 June 2007; revised 20 June 2008; accepted 2 April 2009
Thermal mapping of seasonal variation of soil temperature at four locations of increasing altitudes in Central Kerala, India
during cold and hot weather is presented based on special observations carried out during 1998. Subsurface characteristics like
soil temperature, such as time lag, range of temperature; soil heat flux; and speed of the seasonal variation of annual soil
temperature are determined and it is seen that lower annual rainfall at Chinnar WLS has influenced temperature range and time
lag at different soil depths. The loss or gain of heat either in cold or hot weather periods are totally location based. The velocity
of annual wave during cold weather is lower than hot weather as the presence of soil moisture dampens the penetration of the
wave into downward layers of the soil except at Silent Valley. Non-linear behaviour of seasonal soil temperature characteristics
gives the impression that localized effect due to non-homogeneous soil pattern would have played a part, apart from soil
moisture.
Keywords: Thermal mapping, Seasonal variation, Soil temperature, Soil heat flux
PACS No.: 92.40.Lg
1 Introduction
Diurnal and annual variation of soil temperature
influences local climate change1. The behaviour of
annual variation of soil temperature is the cumulative
effect of seasonal variation of soil temperatures. At
the deeper soil layers, the highest and lowest
temperatures are delayed by month compared to those
at the surface and two waves may even be completely
out of phase. The soil heat flux estimation and soil
temperature measurement give better understanding
of the heat exchange between soil temperature and
atmosphere. The surface, being the site of net
radiation absorption during day, has the greatest
energy surplus and hence the highest temperature in
the soil atmosphere system. Conversely, the night
experiences the greatest energy deficit and hence low
temperature2. The diurnal variations of soil
temperature penetrates the subsoil layers consequent
to the surface solar heating, and its amplitude
decreases with soil depth3. The study of the vectorial
heat of the soil stratum is important to understand the
magnitude of heat exchange across the earth’s surface
leading to the influence of local climate during
various seasons. The present study is an attempt to
construct subsurface thermal mapping based on soil
temperature and soil heat flux at four locations of
increasing altitudes from 100 to 2000 m in Central
Kerala in contrast seasons (cold and hot).
2 Data and description of surface parameters
During 1998, special observations of soil and
subsoil surface were carried out at four locations of
different altitudes, ranging 100 – 2000 m in the
domain 10° 05’ to 10° 30’N and 76° 21’ to 77° 13’E in
Central Kerala. The locations Peechi Vazhani
(10°31.42’N, 76°21.06’E, 100 m), Chinnar WLS
(10°20.50’N, 77°13.15’E, 460 m), Silent Valley NP
(10°05.46’N, 76°27.05’E, 1040 m) and Eravikulam
NP (10°10.10’N, 77°00.39’E, 2000 m) are
abbreviated as P1, C4, S10 and E20, respectively. The
data consists of hourly means of air temperature, soil
temperature, subsurface soil temperature at 15 and
30 cm depths below the surface, wind speed, relative
humidity, rainfall and incoming solar radiation during
all the months at the four locations. The variation of
all these parameters is presented in the paper.
Weather data such as soil temperature and rainfall
are automatically sensed by temperature sensor
(housing thermistors of model SKTS 200/I encased
the Stevensen screen having an accuracy of + 0.10C)
and rainfall sensors (tipping bucket rain gauge model
ARG 100 with a pulse of 0.2 mm per tip) are
216
INDIAN J RADIO & SPACE PHYS, AUGUST 2009
collected by the data logger centered 8-bit
microprocessor. The prediction of onset of monsoon
through the interaction of boundary layer with soil
moisture was studied by Goankar & Manokar4.
Yaping Shao & Irannejad5 found that the soil
hydraulic parameters affect the performance of land
surface schemes used in climate and weather
prediction models.
3 Geographic details of the four weather stations
The latitudinal variation is minimum at the four
locations. The topographical features of the locations
mainly decide their microclimate. Most significant
among them is the position of Chinnar WLS, which
lies on the eastern slopes of Western Ghats and hence
a rain shadow region. The fall in temperature at P1
(although being at lowest elevation of 100 m) during
monsoon months shows the impact of rain on the
surface, the same is not seen at C4 (although being at
highest elevation of 460 m) because of its location in
a rain shadow zone. The relative humidity (RH) in all
the three locations on the western side of the Western
Ghats is nearly identical in all the months except
during pre-monsoon indicating variable dryness of the
locations and in March, the RH follows typical
altitudinal gradient from locations P1 to E20. The
lowest RH in C4 confirms the locations being rain
shadow one. In the seasonal distribution of solar
radiation (in MJm-2) at the surface highest values
corresponded to March only at all the four locations,
irrespective of their altitudes. However, the altitudinal
effect is seen in pre- and monsoon months. The rapid
reduction in solar radiation from C4 to E20 during
monsoon months is also an effect of increasing cloud
cover. In the surface wind speed variation, a typical
maximum is observed in the month of June at all
locations with respect to increasing altitude. A similar
but of lower magnitude is seen in September
indicating energy accumulation before and after
monsoon event. However, the wind at the surface
remained low between 1 and 3.5 ms-1 only. The soil
temperature measured at 15 and 30 cm below the
surface at all the four locations depict a similar trend
to the air temperature but with higher magnitudes.
The difference in soil temperature between 15 and
30 cm depths is observed to be in degree Celsius. The
annual rainfall variation (Fig. 1) shows that maximum
precipitation is from the southwest monsoon only
especially over locations in the western slopes of
Western Ghats. In C4, there is an overall reduction in
rainfall as it lies in a rain shadow zone. In June, there
is increasing rainfall with location’s altitude.
Orographic rainfall after the first out burst over
Kerala is not uncommon.
Further, the annual soil temperature trend follows a
wave like pattern which is analogous to that of the
diurnal temperature wave6. Intense solar radiation is
absorbed by the soil during the day time. It warms the
ground surface more than the layers beneath resulting
a time gradient between the surface and the subsoil on
one hand, surface and air layers near the ground on
the other. Within the soil, this causes heat to flow
downward as diurnal variation of soil temperature2.
Similar heating and cooling of soil during summer
and winter causes annual variation of soil
temperature.
4 Methodology
4.1 Determination of time lag of temperature wave
The time lag for the temperature wave crest and
trough to reach lower depths is given by Oke2:
(z1 -z 2 )
(P/πk s )1/2
… (1)
2
where, t1 and t2, are time at which the wave crest or
trough reaches the depths z1 and z2; P, period of the
annual wave; and ks, thermal diffusivity of the soil,
0.845x10-6 m2s-1 for the cold and 0.59x10-6 m2s-1 for
hot seasons7.
t 2 -t1 =
4.2 Determination of temperature range
The difference between maximum and minimum
occurrences of soil temperature in a soil layer, i.e.
range (Rz) at a depth z is given by Chang8
Rz =R0 exp {-z (π/ksP) 1/2}
… (2)
where, R0, is the temperature range at the ground; and
P, period of annual wave; and ks, thermal diffusivity
of the soil that depends on other soil parameters.
4.3 Determination of soil heat flux
The rate of flow of heat in soil depends on the
strength of mean temperature gradient and hence, the
soil heat flux (S) is given by Oke2
S= -λ ∂Ts/∂Zs
… (3)
where, Ts, is soil temperature; ∆Zs, soil layer
thickness; ∂Ts/∂Zs, vertical soil temperature gradient;
and λ, soil thermal conductivity assumed 2.5 Wm-1K-1
PIOUS et al.: SUB SURFACE THERMAL MAPPING OVER CENTRAL KERALA
for the cold and 1.05 Wm-1K-1 for the hot with respect
to soil depth where the type of soil is same7. The
negative sign signifies the flow of heat
perpendicularly down to the soil surface. If the soil
stratum of 0-30 cm or 15-30 cm is considered, the
solar radiation heats the soil surface right from the
morning and temperature of soil surfaces increases.
Schematic representation of estimation of soil heat
flux in the soil stratum 15-30 cm soil depth is shown
in Fig. 2. The vertical temperature gradient across
different soil depths drives the flow of heat to
downward layers.
217
4.4. Determination of speed of annual soil temperature variation
The speed with which the annual variation of the
soil temperature vertically penetrates down to the soil
is determined based on time lag of the wave.
5 Results
5.1 Time lag
The time lag of annual variation of soil temperature
is determined by perceiving the difference in time
between the period of occurrence of the maximum
soil temperature at 15 cm soil depth and the
succeeding occurrence of the maximum at 30 cm soil
Fig. 1—Monthly rainfall in the four sanctuaries during 1998: (a) Peechi-Vazhani WLS; (b) Chinnar WLS; (c) Silent Valley NP; and
(d) Eravikulam NP
Fig. 2—Schematic representation of estimation of soil heat flux in the soil stratum 15 – 30 cm soil depth
INDIAN J RADIO & SPACE PHYS, AUGUST 2009
218
Fig. 3—Seasonal observed values of time lag for the four
locations in Central Kerala during 1998
Fig. 4—Range of annual soil temperature for the four locations in
Central Kerala during 1998
Table 1 — Soil heat flux (Wm-2) for the seasonal variation of soil temperature at the four locations during 1998
No
Location
Soil heat flux (Wm-2)
Soil stratum
Cold weather
1
P1
2
C4
3
S10
4
E20
15 cm
30 cm
15 cm
30 cm
15 cm
30 cm
15 cm
30 cm
Morning
0.22
0.30
-0.13
0.20
0.08
0.18
0.23
-0.13
Noon
-0.53
-0.38
0.02
0.15
-0.20
-0.10
-0.03
0.12
depths (Fig. 3).The time lag in summer is exceeded by
a day as compared to winter at all locations except
S10.
5.2 Range of annual soil temperature during 1998
The range of temperature of annual variation of soil
temperature at 30 and 15 cm soil depths at the four
locations during cold and hot weather of 1998 are
shown in Fig. 4. Higher range of temperature at 30
cm over 15 cm at C4 (low altitude) and E20 (high
altitude) contrary to the other two locations, probably
in association with the available soil moisture due to
rainfall there. It is noted that the effect of location
altitude and their climate characteristics influence the
thermal property of the soil.
5.3 The soil heat flux
The soil heat fluxes (S) have been computed using
Eq. (3). Using the soil stratum between soil depths
Hot weather
Evening
0.03
-0.17
0.45
0.37
0
0.13
0.23
0.57
Morning
0.04
0.11
-0.01
-0.14
-0.06
0.06
-0.01
-0.07
Noon
-0.29
0.04
0.04
-0.09
-0.17
-0.04
-0.03
-0.03
Evening
0
0.10
0.26
0.12
-0.06
0.04
0.06
0.06
15 and 30 cm at the four locations during cold and hot
weather of 1998, the fluxes at 0-15 cm, 0-30 cm
stratum for morning, noon and evening times are
presented in Table 1. The magnitude of the soil heat
flux varies at random in the soil stratum without any
specific direction of heat flow. It is clear from Table 1
that the morning values of soil heat flux during cold
weather at 30 cm depth are generally high at all
locations except E20. During hot weather in S10, the
flow of heat during the day makes every soil stratum
heat reservoir to gain when seasonal temperature is
maximum and to loose when seasonal temperature is
minimum. Evening values in both the weathers of all
the locations infer that there is a loss of heat in all soil
strata. Loss or gain of heat either in cold or hot
weather is totally location based. It is clear from the
table that heat loss results during morning in the three
locations whereas P1 showed heat gain in the stratum.
PIOUS et al.: SUB SURFACE THERMAL MAPPING OVER CENTRAL KERALA
Table 2 — Velocity of annual variation of soil temperature
S No Place
1
Peechi Vazhani WLS
2
Chinnar WLS
3
Silent Valley NP
4
Eravikulam NP
-7
-1
Season
Observed x 10 ms
CWP
HWP
CWP
HWP
CWP
HWP
CWP
HWP
1.74
1.58
2.17
1.93
1.74
1.83
1.93
1.74
It is noted that the effect of altitude and their climate
characteristics influence the thermal property of the
soil.
3.
219
at C4 has fuelled high temperature range and
low time lag in the sub soil regions during hot
weather.
The velocity of the seasonal variation of soil
temperature during cold weather is lower than
hot weather in the presence of soil moisture
which in turn, dampens the penetration of the
variations into the downward layers of the soil
except at S10. Unusual behavior of the
characteristics of seasonal soil temperature
variations such us time lag and velocity at S10
gives the impression that localized effect due to
non-homogenous nature of soil played a major
role.
5.4 Velocity of annual variation of soil temperature
Velocity of annual variation of soil temperature
helps to understand the traveling effect of temperature
changes into the soil with respect to various seasons.
The observed and theoretical values are computed
using respective time lag values and are given in
Table 2. The theoretical value of speed of annual
variation of soil for cold weather (1.88×10-6 ms-1) is
higher than hot weather (1.47×10-6 ms-1) as it is
estimated from time lag corresponding to respective
seasons. It implies that the variation speed is higher
during high temperature weather.
6 Conclusions
Based on the present study, the following
conclusions are drawn:
1.
Loss or gain of heat either in cold or hot weather
is totally location based.
2.
Low annual rainfall and hence the soil moisture
References
1 Abraham Thambi Raja S & Renuka, Heat storage at sub
surface soil and microclimate at Thiruvananthapuram, India,
Indian J Radio Space Phys, 34 (2005) pp 274-280.
2 Oke T R, Boundary layer climate (John Wiley, New York),
1978.
3 Chowdhury A, Das H P & Pujari A D, Sub soil temperature
variation and estimation of soil heat flux at Pune, Mausam
(India), 42 (1991) 357.
4 Goankar S S K & Manohar G K, A study of the association
of surface potential gradient with the onset of monsoon at
Pune, Indian J Radio Space Phys, 22 (1993) 349.
5 Yaping Shao & Irannejad P, On the choice of soil hydraulic
models in land-surface schemes, Bound-Layer Meteorol
(Netherlands), 90 (1) (1999), pp 83-115.
6 Manjusha K & Shekh A M, Estimation of soil temperature
by harmonic analysis, Mausam (India), 52 (2001) pp 379384
7 Abraham Thambi Raja S, Thermal wave in soil, Ph D Thesis,
University of Kerala, Thiruvananthapuram, 2003, pp 120.
8 Chang J, Climate and agriculture (Alderic Publishers,
Chicago), 1968.