TREND ANALYSIS OF TEMPERATURE AND RAINFALL OF
KOMBOLCHA TOWN, NORTH EASTERN ETHIOPIA
M.Sc PROJECT
MOHAMMED AHMED OUMER
AUGEST 2015
HARAMAYA UNIVERSITY, HARAMAYA
Trend Analysis of Temperature and Rainfall of Kombolcha
Town, North Eastern Ethiopia
A Project Submitted To Department of Physics,
Post Graduate Program Directorate
HARAMAYA UNIVERSITY
In partial Fulfilment of the Requirements for the Degree of
Master of Science in Physics (Environmental Physics)
Mohammed Ahmed Oumer
Augest 2015
Haramaya University, Haramaya
HARAMAYA UNIVERSITY
POST GRADUATE PROGRAM DIRECTORATE
I hear by certify that I have read and evaluated this Project entitled Trend Analysis of Temperature and Rainfall of Kombolcha Town, North Eastern Ethiopia prepared under my
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As a member of the board of Examiners of MSc project open defence examination I certify
that I read and evaluated the Project prepared by Mohammed Ahmed and examined the
candidate .I recommend that the project be accepted as fulfilling the Project requirement
for the degree of Master of Science in Environmental physics
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Final approval and acceptance of the project is contingent upon the submission of its final
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STATEMENT OF THE AUTHOR
By my signature below I declare and affirm that this Project is my own work. I have followed all ethical and technical principles of scholarship on the preparation, data collection,
data analysis and compilation of this Project. Any scholarly matter that is included in the
Project has been given recognition through citation.
This Project is submitted in partial fulfilment of the requirements for M.Sc degree at Haramaya University. The Project is deposited in the Haramaya University Library and is
made available to borrowers under the rules of the Library. I solemnly declare that this Project has not been submitted to any other institution anywhere for award of any academic
degree, diploma or certificate.
Brief quotations from this Project may be made without special permission provided that
accurate and complete acknowledgement of the source is made. Requests for permission
for extended quotations from or reproduction of this Project in whole or in part may be
granted by the Head of the physics Department when in his or her judgment the proposed
use of the material is in the interest of scholarship. In all other instances, however, permission must be obtained from the author of the Project.
Name:Mohammed Ahmed
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Department : Physics
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iii
BIOGRAPHICAL SKETCH
The author was born on September 30, 1983 in Dichiotto town of Awsiresu zone, Afar National Regional state. He attended his primary education in Hayu primary school located at
his birth place and attended his junior and secondary school in Kombolcha ,Wollo. Then he
joined Jimma University in 2003 and graduated with a Bachelor of Education in Physics on
July 8, 2006. After graduation, he has been working in Afar Regional state at Assita College of Teachers Education serving as a physics teacher until he joined the school of Graduate studies of Haramaya University to pursue his M.Sc degree in 2010.
iv
ACKNOWLEDGMENT
Above all, I praise the almighty God, the most gracious, the most beneficence and the most
merciful for giving me health, strength and endurance so as to successfully undertake the
courses, research work, and to compile this project manuscript.
I would like to express my deep heartfelt gratitude to my advisor Dr. Gelana Amente, who
helped me a lot from the beginning up to the end of this project work. During all this time
his swift and valuable guidance, interesting discussions to bring solution to problems, advices and constructive comments made me able to conduct the research confidently. Without his continuous follow-up, correcting the manuscripts and constructive comments the
research would not have taken the current form.
I would like to express my sincere thanks to Mr. Nigusse Zeray Ph.D candidate for his ideas on how to use the MS-Excell. His constructive comments and encouragements cannot
be underestimated.
My sincere thanks go to Kombolcha Meteorology station, who gave me the available climate data free of charge.
I would like to express my gratitude to my families whose patience encouraged me to pursue the postgraduate program.
I would like to express my heartfelt gratitude to my friends Nuredin Teshome, Sema Abrar,
Tamru Mesfin and to all other friends who helped me one way or the other. Their encouragement was inestimable.
Last but not least, I would like to express my deepest gratitude to my part sponsor Assaita
College of Teachers Education (A.C.T.E) for covering my educational expenses.
v
ABBREVIATIONS AND ACRONYMS
CSA
Central Statistical Agency
CV
Coefficient of Variation
FEWSNET
Famine Early Warning System Network
GHG
Green House Gases
FDRE
Federal Democratic Republic of Ethiopia
IPCC
Intergovernmental Panel on Climate Change
JJAS
June, July, August and September
MAM
March, April and May
NAPA
National Adaptation Programme of Action
NMA
National Meteorological Agency
ENMSA
Ethiopia National Meteorological Service Agency
ONDJF
October, November, December, January and February
UNDP
United Nations Development of Program
vi
TABLE OF CONTENTS
POST GRADUATE PROGRAM DIRECTORATE
ii
STATEMENT OF THE AUTHOR
iii
BIOGRAPHICAL SKETCH
iv
ACKNOWLEDGMENT
v
ABBREVIATIONS AND ACRONYMS
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
ix
LIST OF FIGURES
x
LIST OF TABLES IN THE APPENDIX
xi
ABSTRACT
xii
1. INTRODUCTION
1
2. LITERATURE REVIEW
3
2.1. Definitions and Concepts
2.2. Climate Change.
2.2.1. Reasons for Climate Trend Change
2.2.2. Observed Trend Changes in Temperature
2.3. Climate Change in Ethiopia
2.3.1. Topography and Seasons of Ethiopia
2.3.2. Annual and Seasonal Rainfall Trends
2.3.3. Annual and Seasonal Temperature Rends
3. MATERIALS AND METHODS
3
4
4
5
6
6
8
9
11
3.1. Description of the Study Area
3.2. Data
3.3. Methods of Data Analysis
4. RESULTS AND DISCUSSION
11
11
11
12
4.1 Rainfall Statistics
4.1.1. Monthly Rainfall Statistics
4.1.2. Seasonal Rainfall Statistics
4.1.3. Annual Rainfall Statistics
4.2. Annual and Seasonal Rainfall Trend
4.3. Maximum Temperature Statistics
4.3.1. Monthly Maximum Temperature Statistics
4.3.2. Seasonal and Annual Maximum Temperature Statistics
4.4. Seasonal and Annual Maximum Temperature Trend
4.5. Minimum Temperature Statistics
4.5.1. Monthly Minimum Temperature Statistics
4.5.2. Seasonal and Annual Minimum Temperature Statistics
4.6. Seasonal Minimum Temperature Trend
vii
12
12
12
13
14
18
18
19
19
22
22
23
23
4.7. Seasonal and Annual Minimum Temperature Statics
4.7. Seasonal and Annual Mean Temperature Trend
5. SUMMARY AND CONCLUSION
26
27
31
5.1. Summary
5.2 Conclusion
6. REFERENCES
31
33
34
7. APPENDIX
37
viii
LIST OF TABLES
Table
Page
1. Summary of statistical properties of monthly rainfall of Kombolcha from 1975- 2013. 12
2. Summary of Statistical Properties of Annual and Seasonal rainfall of Kobolcha town
from 1975-2013
12
3. Summary of regression statistics for annual and seasonal rainfall trends from 1975-2013
evaluated for α=0.05.
14
4. Summary of monthly average maximum temperature statistics of Kombolcha from
1985-2012
18
5. Summary of descriptive statistics of annual and seasonal maximum temperature of
Kombolcha town from 1985-2012
19
6. Summary of regression statistics for annual and seasonal maximum temperature trends
Kombolcha town from 1985-2012 evaluated for α=0.05
19
7. Summary of monthly minimum temperature statistics of Kombolcha town from 19852012.
22
8. Summary of descriptive statistics of annual and seasonal minimum temperature in
Kombolcha from 1985-2012
23
9. Summary of trends of annual and seasonal minimum temperature of Kombolcha from
1985-2012
23
10. Summary of descriptive statistics of annual and seasonal mean temperature in
Kombolcha from 1985-2012
26
11. Summary of annual and seasonal mean temperature trends of Kombolcha from 19852012
27
ix
LIST OF FIGURES
Figure
Page
1. Global mean temperature trend from 1860-2000.
6
2. Topography of Ethiopia and rainfall pattern
8
3. Normalized kiremt rainfall trends over South-West Ethiopia
9
4. Year to year variability of annual rainfall trend over Ethiopia. (Source NMA, 2007)
9
5. Year to year variability and annual minimum anomaly temperature trend over Ethiopia
(Source NMA,2007)
10
6. Average annual rainfall in Kombolcha from 1975-2013
14
7. Kiremt season rainfall trend from 1975-2013
16
8. Short rainy season (MAM) rainfall trend of from 1975-2013
16
9. Dry season (ONDJF) rainfall trend of Kombolcha from 1975-2013
17
10. Annual rainfall trend of Kombolcha from 1975-2013.
17
11. Kiremt and Belg seasons rainfall trend pattern of Kombolcha from 1975-2013
18
12. Kiremt maximum temperature trend from 1985-2012
20
13. Belg season maximum temperature trend of Kombolcha from 1985-2012
21
14. Bega season maximum temperature trend of Kombolcha from 1985-2012.
21
15. Annual maximum temperature trend of Kombolcha from 1985-2012
22
16. Kiremt season minimum temperature trend of Kombolcha from 1985-2012
24
17. Belg season minimum temperature trend of Kombolcha from 1985-2012
25
18. Bega season minimum temperature trend of Kombolcha from 1985-2012.
25
19. Annual minimum temperature trend of Kombolcha from 1985-2012
26
20. Kiremt season mean temperature trend of Kombolcha from 1985-2012
28
21. Belg season mean temperature trend of Kombolcha from 1985-2012
28
22. Bega season mean temperature trend of Kombolcha from 1985-2012.
29
23. Annual mean temperature trend of Kombolcha from 1985-2012
30
x
LIST OF TABLES IN THE APPENDIX
Appendix Table
Page
1. Monthly and Annually rainfall (in mm) data of Kombolcha town (1975-2013).
37
2. Monthly Average Maximum Temperature data (in 0C ) of Kombolcha town (1985-2012)
38
3. Monthly average minimum Temperature (in oC ) data of Kombolcha town (1985-2012)
39
xi
TREND ANALYSIS OF TEMPERATURE AND RAINFALL OF
KOMBOLCHA TOWN, NORTH EASTERN ETHIOPIA
ABSTRACT
Among the many factors of climate change anthropogenic factor is more likely to aggravate it particularly in many parts of Eastern Africa, including Ethiopia. In this study the
overall trend of both annual and seasonal (dry and rainy seasons) rainfall and temperature
data were examined in relation to the country’s dry and rainy season rainfall and temperature pattern using linear regression analysis where the values in the series were regressed
on time. The main statistical parameter, the slope, resulting from the regression analysis
indicated the mean temporal change of rainfall and temperature. The trend were also tested for significance. The result on trends of rainfall of Kombolcha town showed that the annual rainfall amount contribution of each season were 65% (Kiremt), 22% (Belg) and 13%
(Bega). Generally, the seasonal rainfall variability was variable. The CV was highest during Bega season (0.55), followed by Belg season (0.40). The CV for annual rainfall was
observed to be 0.15. The result shows that over the past 39 years (1975-2013) annual rainfall, Belg and Bega seasons rainfall showed decreasing trends while Kiremt season showed
an increasing trend, but all trends were not significant. The annual and all seasons maximum temperature trend for the past 28 years (1985-2012) were significant. The annual
maximum temperature trend showed the temperature increment at an average rate of 0.055
o
C per year or 0.55 oC per decade. The kiremt season maximum temperature trend showed
an average increase of 0.039 oC per year or 0.39 oC per decade. The temperature of Belg
season increased at average rate of 0.086 oC per year. The trend of annual and seasonal
minimum temperature trend showed no significant diferrences.
Key Words:- Kombolcha, Rainfall trend, Seasonal variability of Rainfall, Seasonal
variability of temperature, Temperature trend
xii
1. INTRODUCTION
Precipitation and temperature trend analyses, on different spatial and temporal scales, have
been of great concern during the past century because of the attention given to global climate change. Climate is important for development but natural climate fluctuations from
autonomous climate cycles disrupt ecological, economic and social systems. However,
human factors have impact on local and global climate patterns. Continued rates of high
population growth, increasing reliance on fossil fuel-driven growth technologies, and land
use effects, (particularly urbanization, agriculture and deforestation) cause global climate
change, largely due to increases in concentrations of atmospheric green house gases and
aerosols (Seth, 2007).
Climate of the Earth varies across temporal and spatial scales throughout the planet. Large
areas of the earth represent variability as part of their normal climate over both short and
long time periods. Climatic variability can be described as the annual difference in values
of specific climatic variables within averaging periods such as a 30-year period. These climatic variations will have unexpected consequences with respect to frequency and intensity of precipitation and temperature variability for many regions of the Earth (Melillo et al.,
1990).
The issue of climate change and variability has become more threatening to food security,
sustainable development of any nation, and also to the totality of human existence (Gadgil
et al., 1998). There is a substantial concern over the global problem of climate change and
it is described as the most universal and irreversible environmental problem facing the
planet Earth (IPCC, 2001). The effects of climate variability such as rising temperature and
changes in precipitation are undeniably clear with impacts already affecting ecosystems,
biodiversity and people. These conditions determine the carrying capacity of the biosphere
(IPCC, 2001).
There are a number of factors that contribute to changes in the Earth's climate over various
time scales. These include natural factors (such as changes in solar output, changes in the
earth's orbit and the natural greenhouse effect) and anthropogenic factors. It is the climate
2
change which is due to anthropogenic reason that is likely to be aggravating the climate
change impacts particularly in many parts of Eastern Africa (IPCC, 2007).
Climate change is a global problem, but it has national, regional and local manifestations
which need to be addressed. Ethiopia is one of the most vulnerable countries to the impacts
of climate change. Climate change threat is greater in Ethiopia because of the country’s
less adaptive capacity and deepened poverty (Michael, 2006). The negative impacts associated with climate change are also confounded by many factors, including widespread poverty, human diseases, and high population density, which is estimated to double the demand for food, water and livestock forage within the next 30 years (Davidson et al., 2003).
In South-Wollo zone in general and in Kombolcha town in particular, the risks of variability in climate patterns that smallholders face is believed to be due to the lack of zone and
local climatic information, low adaptive capacity and limited adaptation options. To that
end, analyzing and characterizing trends of rainfall and temperature through scientific investigations is crucial in order to help researchers, policymakers and developers to make
more informed decisions, at zone and local levels.
Therefore, the main objective of this study will be to evaluate the trend of rainfall (19752013) and temperature (1985-2012) of Kombolcha town and to compare them with the
country’s trend during the same period.
The specific objectives of the study included: To compare rainfall trend during the dry and rainy seasons and to compare
it with the country’s trend
 To assess minimum temperature of the dry and rainy seasons and to compare them with the country’s trend
 To assess maximum temperature of the dry and rainy seasons and to compare them with the country’s trend
3
2. LITERATURE REVIEW
2.1. Definitions and Concepts
Climate: Climate is usually defined as the “average weather” or more rigorously as the statistical
description in terms of the mean and variability of relevant quantities over a period of time ranging
from months to thousands or millions of years. The classical period is 30 years, as defined by the
World Meteorological Organization (WMO, 2007).
Weather: Is a short-term phenomenon, describing atmosphere, daily air temperature, pressure, humidity, solar radiation, wind speed, and precipitation (IPCC, 2007).
Climate variability: Variations in the mean state and other statistics (such as standard deviations,
the occurrence of extremes, etc.) of the climate on all temporal and spatial scales beyond that of
individual weather events. The differences are usually termed as anomalies (Manyatsi et al., 2010).
Climate change: A change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcing or to persistent anthropogenic changes in the composition of the atmosphere
or in land us (IPCC, 2007).
Trend: A trend is a significant change over time exhibited by a random variable (like temperature and rainfall data), detectable by statistical parametric and non-parametric procedures ( Onoz and Bayazit , 2003).
Greenhouse Gases: They are those gaseous constituents of the atmosphere, both natural
and anthropogenic, that absorb and emit radiation at specific wavelengths within the spectrum of thermal infrared radiation emitted by the Earth’s surface, the atmosphere itself, and
by clouds. This property causes the greenhouse effect. Water vapour (H2O), carbon dioxide
(CO2), nitrous oxide (N2O), methane (CH4) and ozone (O3) are the primary greenhouse
gases in the Earth’s atmosphere.
4
2.2. Climate Change.
2.2.1. Reasons for Climate Trend Change
Climate refers to long-term weather patterns, over periods of 30 years or more, that are
typical of a region. When changes occur in the climate that a region experiences over a
long period of time, it is called “Climate Change”. Scientific research has documented that
the earth’s atmosphere has been warming since the pre-industrial period of the mid-18th
century due to increasing concentrations of GHGs in the atmosphere.
Naturally, the earth absorbs a portion of the sunlight it receives, which then heats the planet, and reflects some of the sunlight back into space. As the earth is heated by the sunlight,
it also radiates a portion of this heat back into the atmosphere in the form of infrared radiation. Greenhouse gases warm the earth system by absorbing a portion of the outgoing radiation from the planet and re-radiating some of the absorbed radiation back towards the
Earth’s surface. As the overall energy of the system increases, the Earth surface and lower
atmospheric temperatures increase, as well. Many greenhouse gases occur naturally, and
without them the earth surface would be on average 60 degrees Fahrenheit colder (Wallace
and Hobbs, 2006).
The major greenhouse gases are carbon dioxide (CO2), methane (CH4), nitrous oxide
(N2O), ozone (O3), and various halocarbons. Water vapour also acts as a greenhouse gas,
but since human activities contribute inconsequentially to its atmospheric concentration, it
is neglected as a greenhouse gas and instead considered as part of the climate system feedbacks. Aerosols (also called particulate matter, PM, or particles) are another anthropogenic
influence. In contrast to greenhouse gases which warm the planet, most aerosols reflect
incoming solar radiation and act as a cooling agent. Black carbon (for our purposes, equal
to “elemental carbon” and “light absorbing carbon”) efficiently absorbs solar radiation and
warms the atmosphere (IPCC, 2007).
Individual greenhouse gases and aerosols differ in their effectiveness. For example, each
methane molecule is 20 times more effective at warming the atmosphere than each carbon
dioxide molecule. However, since carbon dioxide is present in higher concentrations and
lasts longer in the atmosphere, it is a more important greenhouse gas than methane. Current
5
emissions of carbon dioxide will be influencing our climate long after current methane
emissions (IPCC, 2007).
In addition to average temperatures, recent work shows that human activities have also
likely influenced extremes in temperature. Many indicators of climate extremes, including
the annual numbers of frost days, warm and cold days, and warm and cold nights, show
changes that are consistent with warming. For example, there is evidence that humaninduced warming may have substantially increased the risk of extremely warm summer
conditions in some regions. Discernible human influences extend to additional aspects of
climate, including the recent decreases in Arctic sea ice extent, patterns of sea level pressure and winds, and the global-scale pattern of land precipitation (IPCC, 2007).
2.2.2. Observed Trend Changes in Temperature
Temperature changes are one of the more obvious and easily measured changes in climate,
but atmospheric moisture, precipitation and atmospheric circulation also change, as the
whole system is affected. Global mean surface temperatures have raised by 0.74°C ±
0.18°C when estimated by a linear trend over the past 100 year (1906–2005) (IPCC, 2007).
The rate of warming over the last 50 years is almost double that over the last 100 years
(0.13°C ± 0.03°C vs. 0.07°C ± 0.02°C per decade). Global mean temperatures averaged
over land and ocean surfaces, from three different estimates, each of which has been independently adjusted for various homogeneity issues, are consistent within uncertainty estimates over the period 1901 to 2005 and show similar rates of increase. In recent decades
the trend is not linear, and the warming from the first 50 years of instrumental record
(1850–1899) to the last 5 years (2001–2005) is 0.76°C ± 0.19°C (IPCC, 2007) as shown in
Figure 2. 1
6
Figure 1 Global mean temperature trend from 1860-2000. (SOURCE IPCC, 2007)
2.3. Climate Change in Ethiopia
2.3.1. Topography and Seasons of Ethiopia
Ethiopia is a land locked country in eastern Africa located between 3015’ to 180N and 330
to 480E above the equator located within the tropics, Ethiopia has great geographical diversity with high and rugged mountainous, flat-topped plateaus, deep gorges, etc. The Great
Rift Valley divides the country into two parts forming the eastern and western highlands.
Its altitudinal range lies between 120 m below sea level and 4600 m above sea level
(Workneh, 1987).
The differences in altitude and relief create a large variation in climate in various regions
of the country. In places that are characterized as semi-arid zones, climate shows wide fluctuation from year to year and even within seasons in the year. Semi arid regions receive
very small, irregular, and unreliable rainfall (Workneh, 1987).
There are three generally altitude influenced distinguished environments, Dega (cool),
Weynadega (temprate) and Kola (hot).The Dega covers the central parts of the western and
eastern sections of the north-western plateau, and a small area in Harar, and generally
above 2,400 meters in elevation. The surrounding low lands between 1500 to 2400 meters
constitute the temperate zone. The hot zone which encompasses the Denakil depression ,
the eastern Ogaden, the deep tropical valleys of the Blue Nile and Tekezé rivers, and the
7
peripheral areas along the Sudanese and Kenyan borders has an elevation lower than 1500
meters. Forty percent (40%) of the country’s Population is estimated to live above 1500
meters Mean-annual temperature is around 15-20 oC in these high altitude regions, whilst
25‐30˚C in the lowlands (FDRE, 2008).
Rainfall during a year occurs in different seasons. Unlike most of the tropics where two
seasons are common (one wet season and one dry season), there are three seasons in Ethiopia due to the country’s geographical location, topography and large-scale circulations
dominating the climate in the horn of Africa. Bega is the dry season from October to February (ONDJF); Belg is the short rainy season from March to May (MAM); and Kiremt is
the long rainy season from June to September (JJAS). The central, eastern and northern
parts of the country experience a bimodal pattern receiving rains from June to September
and spring rains from March to May. The southern and south western parts of the country,
experience mono-modal pattern where precipitation falls from March to November. The
highlands generally receive more precipitation than the lowlands (FDRE, 2008).
The Belg (small) rainy season usually occurs in bimodal regimes of the country. These are
the north eastern, eastern, central, southern and south western parts of the country. However, the northern and north western parts of the country start getting rainfall towards the end
of the season. The Belg rainfall is highly variable in time and space. Moreover, the maximum temperature reaches its peak during this season. Kiremt (long rainfall) begins in June
and continues to September though its onset and cessation varies over space. Segele and
Lamb (2005) figured out, the mean onset of the main rainy season as June 21. It covers
much of the country except the southern and the south eastern lowlands which remain
cloudy during this season. The maximum temperature goes down during this season in association with cloud coverage. The enhancement of weather system leads to flash flood
and over bank flow of rivers during this season. This rainy season contributes 65-95% of
the total annual rainfall (Segele and Lamb, 2005).
Bega (dry season) is a dry for much of the country, however, the southern and the south
eastern lowlands receive their second rainy season. Towards the end of this season the minimum temperature goes down during this season in various parts of the country. Especially,
over highland areas the minimum temperature sometimes goes down to -8 0C (NMA,
8
2007). Areas of the country which experience such low minimum temperature are shown in
Fig 2.2.
Figure 2. Topography of Ethiopia and Rainfall Pattern
A=One rainy season Kiremt B= Belg and Kiremt (March-May and July-September) C=
September-November and March-May two wet seasons (Source: NMA 2007)
2.3.2. Annual and Seasonal Rainfall Trends
Since strong inter-annual and inter-decadal variability in Ethiopia’s rainfall makes it difficult to detect long-term trends, inconsistency is observed among different studies. One of
the studies that comprise a lot of station is the study of Wing et al. (2008) on trends and
spatial distribution of annual and seasonal rainfall in Ethiopia using data from 134 stations
from 1960 to 2002. This study showed that there are no significant changes or trends in
annual rainfall, belg rainfall and bega rainfall at the national level in Ethiopia. But, the
kiremt rain trend is decreasing in southern, south western and central parts of Ethiopia.
According to the study of FEWS NET (2012), belg and kiremt rainfall decreased by 15-20
% across parts of southern, south western (Fig 3), and south eastern Ethiopia between the
mid 1970s and 2000s. According to the study of Yilma Seleshi and Ulrich Zanke (2004)
there is no trend in the annual, kiremt , belg and bega rainfall totals and rainy days over
9
central, northern and north western Ethiopia in the period 1965–2002. In contrast, the annual and the kiremt total rainfall in eastern and southern Ethiopia showed a significant decline since 1982. The kiremt rainy days in eastern Ethiopia showed a significant decline (at
the 5% level) since about 1982, compared with the period 1965–1981.
Figure 3. Normalized Kiremt rainfall trends over Southwest Ethiopia.
(Source: FDRE, 2008)
Figure 4. Year to year variability of annual rainfall trend over Ethiopia.
(Source NMA, 2007)
2.3.3. Annual and Seasonal Temperature Trends
Unlike the study of rainfall trend, all studies on temperature trend shows an increasing
trend both for minimum and maximum temperatures in all seasons of the country. Recent
climate trends based on UNDP climate data indicate there is a clear and observable positive trend in temperature both in dry and rainy seasons. Ethiopia shows a broadly warming
10
trend, with observations of increasing minimum and maximum temperatures over the past
fifty years (McSweeney, 2008).
The NAPA reported mean annual temperature has increased by 1.3°C between 1960 and
2006, at an average rate of 0.28°C per decade. Average annual minimum temperature
trends rising by 0.2-0.4 oC per decade and average annual maximum temperature by 0.1 oC
per decade in both rainy and dry seasons (FDRE, 2008). According to NMA (2007), the
average maximum temperature in the country has been increasing by 0.1 oC per decade and
the annual minimum temperature over the past 54 years (1951-2005) increased by about
0.37 0C every ten years. as shown in Figure 5.
Figure 5. Year to year variability and annual minimum anomaly temperature over
Ethiopia expressed in temperature. (Source: NMA, 2007)
11
3. MATERIALS AND METHODS
3.1. Description of the Study Area
The town of Kombolcha is located in north-eastern part of Ethiopia, 375 kms North of Addis Ababa and 24 kms south - east of Dessie, the capital of South Wollo Zone. It is situated
at 11o 44' North and 39o 45' East, at an altitude of 1903 ms above mean seal level. Climatically, Kombolcha falls within the Weina-Dega zone. The average temperature varies from a
minimum of 11.9oC to a maximum of 26.8oC. The Kiremt season starts from July and lasts
for about three to four months. This season contributes more than 74.3% for the mean annual rainfall of the town. The mean annual rainfall of kiremt season in the town is 866.27
mm. Belg (short rainy season, MAM) rainfall makes a considerable contribution of 21.4 %
(CSA, 2001)
3.2. Data
For the analysis of past trends of rainfall and temperatures, data were obtained from Kombolcha meteorology district located near the air port of the town. The station was started
with recording of rainfall data’s in 1975 ten years before it launches recording of temperature data’s in 1985. The data set includes daily rainfall data from 1975 to 2013 and maximum and minimum daily temperature data from 1985 to 2012.
3.3. Methods of Data Analysis
Daily rainfall data has been summed into monthly and yearly totals. For further analysis,
the monthly rainfall data was categorized according to three seasons, kiremt (JJAS-long
rainy season), Belg (MAM-short rainy season) and Bega (ONDJF –dry season). The overall trend in a time series was examined in this study by the use of linear regression analysis
where the values in the series are regressed on time (year). The main statistical parameter,
the slope, resulting from the regression analysis indicates the mean temporal change of
rainfall and temperature. The parameter estimate of the slope was then tested for statistical
significance using the one-sample T -test at a 0.05 level of significance or at a confidence
level of 95 %.Microsoft office Excel was used to analyse the data.
12
4. RESULTS AND DISCUSSION
4.1 Rainfall Statistics
4.1.1. Monthly Rainfall Statistics
As shown in Table 1 below, July is the month when the town gets the highest mean rainfall
(267.3 mm) and December is the month when the town received the lowest mean rainfall
amount (17.6 mm). Coefficient of variation (ratio of standard deviation to mean) is suitable
measure of variability of rainfall. The monthly coefficient of variation (CV) for this town
lies between 0.31-1.35.
The average monthly rainfall was very variable. The variability of rainfall was highest in
December with CV (1.35) followed by February (1.14) and the least variability of rainfall
was recorded in August with CV (0.31) followed by July (0.36).
Table 1. Summary of statistical properties of monthly rainfall of Kombolcha from
1975- 2013.
Max.Rf Min.Rf
Range
Mean
Std.Dev
Month Season (mm)
(mm)
(mm)
(mm)
(mm)
Coeff.Variation
Jan
Bega
92.5
0
92.5
23.8
25.6
1.08
Feb
Bega
107.6
0
107.6
29.1
33.1
1.14
Mar
Belg
166.2
0
166.2
72.8
42.9
0.59
Apr
Belg
239.9
13.4
226.5
94.6
60.4
0.64
May
Belg
181
2.2
178.8
60.1
47.9
0.8
June
Kiremt
118.2
0
118.2
30
29.4
0.99
Jul
Kiremt
522.6
50.1
472.5
267.3
97
0.36
Aug
Kiremt
524.8
46.6
478.2
262.2
81
0.31
Sep
Kiremt
226.6
37.3
189.3
109.6
47.2
0.43
Oct
Bega
154.6
0
154.6
41.8
41.3
0.99
Nov
Bega
87
0
87
20.9
27.2
1.3
Dec
Bega
104.4
0
104.1
17.6
23.8
1.35
4.1.2. Seasonal Rainfall Statistics
In this section the summary of the statistical values of seasonal rainfall and annual rainfall
is discussed. The statistical values that will be discussed include mean value, standard deviation and coefficient of variation.
Table 2 below shows the seasonal and annual statistical analysis of rainfall and stated as
follows. The kiremt contribution to annual rainfall was 65%, 22% (belg) and 13% (bega).
13
Generally, the seasonal rainfall variability in Kombolcha town is higher. The CV is highest
during bega season (0.55), followed by belg season (0.40). The CV for annual rainfall is
observed to be 0.15. In better agreement with study of Daniel (2011) showed mean value
of rainfall and CV for Kombolcha town for annual, kiremt, belg and bega seasons to be
1021mm and 0.15, 653 mm and 0.2, 234 mm and 0.36 and 133 mm 0.56, respectively
from 1981-2006. Rainfall variability as expressed in terms of coefficient of variation
showed moderate inter-annual and seasonal variability. Belg and bega are much more variable than Kiremt. Similar conclusions that belg and bega rainfalls are more variable than
kiremt have been made by Bewket and Conway( 2007) and; Mersha (1999).
Table 2. Summary of Statistical Properties of Annual and Seasonal rainfall of
Kobolcha town from 1975-2013
Statistics/Seasons
Maximum(mm)
Minimum (mm)
Range (mm)
Mean (mm)
St.Dev (mm)
CV
Contribution to
annual RF
(in %)
Kiremt(JJAS)
962.5
273.6
688.9
669.1
149.1
0.22
65
Belg(MAM)
458
36.8
421.2
227.1
92.8
0.4
22
Bega(ONDJF)
Annual
335.4
1361.1
1
598.5
334.4
763.1
133.2
1029.7
73.8
152.3
0.55
0.15
13
100
4.1.3. Annual Rainfall Statistics
Figure 6 shows the long term average pattern of the annual rainfall of Kombolcha town.
The annual mean rainfall is 1029.7 mm. The annual maximum rainfall recorded for the
wettest years were 1361.6 mm in 1998, 1313.6 mm in 2010 and 1280 mm in 1993.
14
Rainfall (mm)
Kombolcha annual rainfall
y = 0.3673x + 1022.4
R² = 0.0008
1600
1400
1200
1000
800
600
400
200
0
Figure 6. Average annual rainfall in Kombolcha from 1975-2013
The annual minimum rainfall (driest year) in the study period was 598.5 mm in 1984. Both
Woldeamlak (2009) and Daniel (2011), have also found out the year 1984 as the year in
which the lowest rainfall was recorded in the region and the worst drought had happen in
the years 1987 and 1991 in which 799.5 and 767.7 mm of rainfall were recorded, respectively. The decadal mean values of rainfall 1975-1984, 1985-1994, 1995-2004 and 20042013 were almost similar and were 996.9 mm, 1040.9 mm, 1061 mm and 1007 mm, respectively.
4.2. Annual and Seasonal Rainfall Trend
This section describes about the summary of regression statistics such as regression equation, coefficient of determination (R2), P-value and level of significance
Table 3. Summary of regression statistics for annual and seasonal rainfall trends
from 1975-2013 evaluated for α=0.05.
Season
Regression
Equation
Kiremt
Y=3.99X+589
Belg
Y= -2.21X + 272
Bega
Y= -1.4X + 161
Annual
Y=0.38X + 1022
Y=Seasonal/annual rainfall X=year
RainfallChange
perdecade
(mm)
+39.9
-22.1
-14.0
3.8
PValue
R2
Significance
Trend
0.09
0.08 increase
None
0.07
0.09 decrease
None
0.05
0.18 decrease
None
0.0008
0.87 increase
None
15
Table 3 is the summary of Figure 7 to Figure 10 , that shows the annual and seasonal rainfall linear trends. From Table 3 onwards the positive (negative) slope of the regression
equation shows the increasing (decreasing) trend and. The P-value is a test for the significance level of the slope at α =0.05 (95 % confidence level), for the null hypothesis (H0=
there is no trend in the series). The R2 value (a fraction b/n 0.0-1.0) of regression analysis
of the trend line shows strong relationship between rainfall (temperature) and time (in
years) as it moves from zero to one.
As shown in Table 3, annual rainfall and seasonal rainfall for both belg and bega season
showed decreasing trends. There was an increasing trend for kiremt season. Though, the
seasonal rainfall pattern showed a significant episodic decadal trend, generally there is no
significant decreasing or increasing rainfall trends for the past 39 years (1975-2013).That
means the null hypothesis cannot be rejected since a P-value for all periods is equal or
greater than 0.05. This is in agreement with the study of Wing et al. (2008) that showed
there is no significant trend or changes in annual rainfall, belg rainfall and bega rainfall at
the national level in Ethiopia. Conway (2000) also agreed that there is no significant and
clear trend in the seasonal and the annual rainfall pattern in north-eastern Ethiopian highlands.
Kiremt season has shown least and episodic variability in comparison to the other seasons.
For instance the slight uniform increment from 1980-1983 (993 mm, 1067 mm, 1111 mm
and 1041 mm respectively) was followed by uniform decrement from 1988-1991(1188
mm, 1169 mm 893 mm and 767 mm respectively). Positive and negative trends were continuously interchanged, but generally long term kiremt rainfall trends during the period
1988-2000 were dominantly positive, while during a period 2001-2013 they were dominantly negative. A value of R2 0.0932, which is to mean that only 9.32% of the total variation in the data exist above the average (mean).This certainly showed that the correlation
between kiremt rainfall and the year during the study period was very weak.
As shown in Figure 7, kiremt season rainfall change from the mean average was to be +
589 mm as per the trend line. However, this value has been changed by a factor of +3.99.
Positive sign of the slop of the trend line indicates that rainfall is increasing from 1975 to
2013. A significant decline was observed in 1980 s and a significant increment from 1994
onwards.
16
y = 3.9924x + 589.27
R² = 0.0932
Rainfall (mm)
Kiremt season rainfall trend
850
650
450
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
250
Figure 7. Kiremt season rainfall trend of Kombolcha from 1975-2013
As shown in Figure 8, Belg season rainfall change from the mean average was to 272 mm
as per the trend line. However, this value changed by the factor of -2.21. Negative sign of
the slop of the trend line indicates that rainfall declined from 1975 to 2013. A significant
decline was observed from 1997-2009.
Rainfall (mm)
Belg season rainfall trend
500
450
400
350
300
250
200
150
100
50
0
y = -2.2145x + 271.68
R² = 0.074
Figure 8. Short rainy season (MAM) rainfall trend of Kombolcha from 1975-2013
As shown in Figure 9 the change in the bega season average rainfall amount of the study
area has been analyzed and stated as follows. Bega season rainfall change from the mean
average was161 mm as per the trend line. However, this value changed by the factor of 1.4. Negative sign of the slop of the trend line indicates that bega rainfall declining from
1975 to 2013. A significant decline was observed during 1983-1991 and 2001-2012.
17
Bega season rainfall trend
y = -1.41x + 161
R² = 0.0475
350
Rainfall (mm)
300
250
200
150
100
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
0
1975
50
Figure 9. Dry season (ONDJF) rainfall trend of Kombolcha from 1975-2013
From what is observed in figure 10, the town did not experience a significant increment or
decrement of annual rainfall between 1975-2013. The R2 value 0.0008 shows that only
0.08% variation rainfall is explained by time. The P-value (0.79) explains that the positive
trend displayed in the figure is not significant.
2013
2011
2009
2007
2005
2003
2001
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1999
y = 0.3673x + 1022.4
R² = 0.0008
1400
1300
1200
1100
1000
900
800
700
600
500
1975
Rainfall (mm)
Annual rainfall trend
Figure 10. Annual rainfall trend of Kombolcha from 1975-2013.
Figure 11 shows that the rainfall was cyclic and erratic for most years of the study period.
The rainfall was variable from year to year, season to season which has similar fashion
with the countries rainfall pattern as studied by Mc Scsweeney (2008).
18
kiremt season
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
300
200
100
0
-100
-200
-300
-400
1975
Rainfall Anomaly (mm)
Seasonal rainfall
Belg season
Figure 11. Kiremt and Belg seasons anomaly rainfall variability of Kombolcha from 19752013
4.3. Maximum Temperature Statistics
Under this section extreme temperatures (maximum and minimum) are analyzed before
mean temperature. Maximum temperature which occurs at day time of an area is indicative
of how hot it gets and warm trends, whereas minimum temperature that occurs at night is
indicative of cold trends.
4.3.1. Monthly Maximum Temperature Statistics
As shown in Table 4 below the range of monthly mean maximum temperature lies between
24.6 oC (January and December) to 30.5 oC (June). The range of monthly maximum value
of maximum temperature lies between 26.1 oC (December) to 32.1 oC (June),while the .
Table 4. Summary of monthly average maximum temperature statistic of Kombolcha
from 1985-2012
Month
January
February
March
April
May
June
July
August
September
October
November
December
Season
Bega
Bega
Belg
Belg
Belg
Kiremt
Kiremt
Kiremt
Kiremt
Bega
Bega
Bega
Min.
Mean
Max.
valRange St.Dev
o
o
o
( C)
value( C) ue( C)
(oC)
(oC)
C.V(%)
24.6
26.4
22.4
4
1.13
4.59
26
28.2
22.5
5.7
1.42
5.46
26.9
29.3
25
4.3
1.13
4.2
27.2
29.5
24
5.5
1.48
5.44
28.8
30.6
25.8
4.8
1.35
4.69
30.5
32.1
28.8
3.3
0.88
2.89
28
30.4
26.5
3.9
0.88
3.14
26.8
28
25.3
2.7
0.65
2.43
26.4
28
24.6
3.4
0.82
3.11
25.9
32
23.4
8.6
1.45
5.49
25.2
27
22.9
4.1
0.84
3.33
24.6
26.1
22.3
3.8
0.76
3.09
19
monthly minimum value of maximum temperature lies between 22.3 0C (December) to
28.8 0C (June).The monthly coefficient of variation (CV) for the study area lies between
2.43-5.49%. The CV is highest in October (5.49%), followed by February (5.46%) and the
least CV occurred during August (2.43%) and June (2.89%).
4.3.2. Seasonal and Annual Maximum Temperature Statistics
Table 5 shows statistical properties of annual and seasonal maximum temperatures of
Kombolcha town. The long rain season (kiremt) was also the season that experiences the
highest seasonal maximum temperature (27.9oC) and the dry season (bega) experience the
lowest seasonal maximum temperature (25.3oC ). Annual maximum temperature lies between 25.5-27.9 oC, and the mean value was 26.7oC during the past 28 years (1985-2012).
Table 5. Summary of descriptive statistic of annual and seasonal maximum tempera
ture of Kombolcha town from 1985-2012
Statistics
Max.T (0C)
Min.T (0C)
Range (0C)
Mean (0C)
St.Dev (0C)
C.V(%)
Kiremt
Belg
29
27
2
27.9
0.55
1.97
Bega
29.5
25.5
4
27.6
1.06
3.84
Annual
26.7
23
3.7
25.3
0.77
3.04
27.9
25.5
2.4
26.7
0.61
2.28
4.4. Seasonal and Annual Maximum Temperature Trend
Table 6 shows the summary of the annual and seasonal maximum temperature trend shown
in the Figure 12-15. As shown in Table 6 the annual and all seasons maximum temperature
Table 6. Summery of regression statistic for annual and seasonal maximum temperature trends Kombolcha town from 1985-2012 evaluated for α=0.05
Regression
Change per
Season
Equation
decade(oC)
Kiremt
Y=0.039X +27
0.34*
Belg
Y=0.085X +26
Bega
Y=0.05X +24
Annual
Y= 0.06X +26
SignifiR2
P-Value
Trend
cance
0.35 0.0009
increase
yes
0.89*
0.44 0.0001
increase
yes
0.5*
0.33 0.0013
increase
yes
0.58 2.3E-06
increase
0.6*
*significant at 5% probability Y=Seasonal/annual average temperature X=year
yes
20
trends significantly increased with the P-value very less than from α- Value(0.05), since
the null hypothesis H0 (there is no trend in the series) is rejected or the scientific hypothesis
H1(there is trend change in the series) will be accepted. This result is in agreement with
different studies of temperature trend analysis over the country, like studies by the
McSweeney (2008) and studies by FDRE (2008).
In Figure 12 the kiremt season maximum temperature trend showed that the temperature
increased by 0.039 oC per year or 0.39 oC per decade. As the computed P – value (0.001),
which is computed using exact method, is lower than the significance levelof (0.05), which
indicates that the null hypothesis should be rejected. The risk of rejecting the null hypothesis while it is true is lower than 0.1%. Therefore, it is true that kiremt season maximum
temperature change was significant for the last 28 years in the study area.
Max.Temperature
(Deg.C)
30.0
Kiremt maximum temperature trend
29.0
y = 0.0394x + 27.374
R² = 0.3501
28.0
27.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
26.0
Figure 12. Kiremt maximum temperature trend from 1985-2012
In Figure 13 the belg season maximum temperature trend showed the highest temperature
change than kiremt and bega seasons. The temperature was increasing by 0.086 oC per year
or 0.86 oC per decade. As the computed P – value (0.0001) is lower than the significance
level (0.05), the null hypothesis is rejected. The risk to rejecting the null hypothesis while
it is true is lower than 0.01%. Therefore, it is true that belg season maximum temperature
change was significant for the last 28 years over the study area. The R2 value 0.45 means
that only 45 % variation in belg season maximum temperature is explained by time.
21
Max.Temperature(Deg.C)
30.0
Belg max.Temp trend
29.0
28.0
27.0
y = 0.0853x + 26.371
R² = 0.4388
26.0
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
25.0
Figure 13. Belg season maximum temperature trend of Kombolcha from 1985-2013
In Figure 14 the bega season maximum temperature trend showed higher temperature
change than kiremt season. The temperature was increasing by 0.05 oC per year or 0.5 oC
per decade. As the computed P – value (0.002) is lower than the significance level (0.05),
the null hypothesis is rejected. The risk to rejecting the null hypothesis while it is true is
lower than 0.2%. Therefore, it is true that bega season maximum temperature change was
significant for the last 28 years in the study area. The R2 value 0.32 means that only 32
percent variation in bega season maximum temperature is explained by time.
Max.Temperature
(Deg.C)
27.0
Bega season max.Temperature trend
26.0
25.0
24.0
y
=
23.0
R² =
0.0541x
-
82.929
0.3335
22.0
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
Figure 14. Bega season maximum temperature trend of Kombolcha from 1985-2012.
In Figure 15 the annual maximum temperature a trend showed the temperature was increasing by 0.057 oC per year or 0.57 oC per decade. This result is far greater than (5.5
times) the national level annual maximum temperature change (0.1 oC per decade) between
1960-2006 studies by FDRE (2008). The reason for this could be urban island heat effect
such as population density, deforestation, construction of roads and buildings due to their
emissivity potential as it can be shown easily in Stefan-Boltzmann radiation law (since a
22
black body like roads have an emissivity of 1. Soil, Asphalt and human skin have emissivity of about 0.95).Beyond to this, the emission from industries could have its own effect due
to the town is serving as an industry zone for the country. As the computed p – value (2.4E06) is lower than the significance level (0.05), the null hypothesis is rejected. The risk to
rejecting the null hypothesis while it is true is lower than 0.00024 percent. Therefore, it is
true that annual maximum temperature change was significant for the last 28 years in the
study area. The R2 value 0.58 means that, 58 percent variation in annual maximum temper-
28.0
Annual max.Temperature trend
27.5
27.0
26.5
26.0
y = 0.057x + 25.911
R² = 0.5831
25.5
25.0
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Max.Temperature (De.C)
ature is explained by time.
Figure 15. Annual maximum temperature trend of Kombolcha from 1985-2012
4.5. Minimum Temperature Statistics
4.5.1. Monthly Minimum Temperature Statistics
As shown in Table 7 the range of monthly minimum temperature lies between -0.3 oC (November) to 19.5oC (August) and the range of mean monthly minimum temperature lies
Table 7. Summary of monthly minimum temperature statistic of Kombolcha town
from 1985-2012.
Month
Mean(oC) Maximum(oC) Minimum(oC) Range(oC) Stand.dev C.V(%)
January
10.3
13.6
3.8
9.8
2
19
February
11.1
14.4
4.8
9.6
2.4
22
March
12.6
14.9
6.4
8.5
1.8
14
April
13.9
14.6
7.3
7.3
1.3
09
May
14
15.5
7
8.5
1.5
11
June
15
16.5
7.2
9.3
1.7
11
July
14.9
16.2
6.2
10
1.8
12
August
14.8
19.5
5.8
13.7
2
14
September
13.7
17.9
4.8
13.1
2
15
October
10.4
12.3
1.7
10.6
2
19
November
8.5
11.9
-0.3
12.2
2
24
December
9
13
5.7
7.3
1.9
21
23
between 8.5oC (November) to 14.9 oC (July). The monthly coefficient of variation (CV) for
the study area lay between 0.09- 0.24. The CV was highest in November (24%), followed
by February (22%) and was least during April (9%) followed by both May and June (11%).
4.5.2. Seasonal and Annual Minimum Temperature Statistics
Table 8 shows analysis of statistical properties of annual and seasonal minimum temperatures of Kombolcha and stated as follows. The range of seasonal minimum temperature lay
between 3.8oC – 15.9oC. The long rainy season (kiremt) was also the season that experiences the highest seasonal minimum temperature (14.6oC) and the dry season (bega) experience the lowest seasonal minimum temperature (9.9 0C). Annual minimum temperature
lay between 5.3-13.7oC, and the mean value of minimum temperature was 12.3 oC during
the past 28 years (1985-2012).
Table 8. Summary of descriptive statistic of annual and seasonal minimum temperature in Kombolcha from 1985-2012
Statistics/Season
Maximum(oC)
Minimum(oC)
Range(0C)
Mean(0C)
St.Deviation (0C)
C.V(%)
Kiremt
Belg
15.9
6
9.9
14.6
1.74
12
Bega
14.4
6.9
7.5
13.5
1.35
10
Annual
11.8
3.8
8
9.9
1.41
14
13.7
5.3
8.4
12.3
1.5
12
4.6. Seasonal Minimum Temperature Trend
As shown in Table 9 the annual and all seasons’ minimum temperature trends have not significantly increased by the reason that their P-value was greater than α- Values (0.05).
Since the null hypothesis H0 (there is no trend in the series) is accepted or the scientific
hypothesis H1(there is trend change in the series) will be rejected.
Table 9.Summary of trends of annual and seasonal minimum temperature of
Kombolcha from 1985-2012 evaluated for α=0.05.
Season
Regression equation
R-square
P-value
Kiremt
Y=0.071X +13.6
0.114
0.079
Belg
Y=0.028X+13
0.029
0.384
Bega
Y=0.025X+9.5
0.021
0.466
Annual Y=0.039X+11.8
0.051
0.249
Y=Average seasonal/annual minimum temperatre. X=year
Trend
increase
increase
increase
increase
Significance
None
None
None
No ne
24
This result is not in agreement with different studies of temperature trend analysis over the
country, like studies by the McSweeney (2008) and studies by FDRE (2008).The reason
for this disagreement could be night radiative cooling effect due to the lack of down welling cloud radiation when the cloud remains clear and calm, which results greater radiative
cooling in the night such that greater surface radiation losses on clear nights results in
greater and faster temperature drops than cloudy nights as it is known in a modified Swinbank model of night time down ward thermal radiation of sky. Many studies about minimum temperature trend over Ethiopia showed that the minimum temperature trend over the
country is significantly increased faster than the maximum temperature trend. For example,
according to FDRE (2008) NAPA (National Adaptation Program of Action) reported that
average annual minimum temperature trends rising by 0.2-0.4 oC per decade and average
annual maximum temperature by 0.1 oC per decade during 1960-2006.
In Figure 16 the kiremt season minimum temperature trend shows non-significant temperature change. As the computed P – value (0.077) is greater than the significance level (0.05),
the null hypothesis should not rejected. The risk to accept the scientific hypothesis while it
is false is greater than 5% (7.7%). The R2 value 0.114 means that only 11.4 % variation in
kiremt season minimum temperature were explained by time.
20.0
15.0
10.0
Y = 0.0712X + 13.59
R² = 0.114
5.0
0.0
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Minimum T( Deg.C)
Long Rain Season Minimum Temperature Trend
Figure 16. Kiremt season minimum temperature trend of Kombolcha from 1985-2012
In Figure 17 the belg season minimum temperature trend showed non-significant temperature change. As the computed P – value (0.384) is greater than the significance level alpha
=0.05, we should not reject the null hypothesis. The risk to accept the scientific hypothesis
while it is not true is 38.4%. The R2 value 0.029 means that only 2.9 % variation in belg
season minimum temperature were explained by time.
25
Y = 0.0281X + 13.07
R² = 0.0292
20.0
15.0
10.0
5.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
0.0
1985
Minimum Temperature
(Deg.C)
Short rainy season minimum temperature trend
Figure 17. Belg season minimum temperature trend of Kombolcha from 1985-2012
In Figure 18 the bega season minimum temperature trend shows non-significant temperature change. As the computed p – value (0.47) is greater than the significance level alpha
=0.05, we should not reject the null hypothesis. The risk to accept the scientific hypothesis
while it is not true is 47%. The R2 value 0.0206 means that only 2.06% variation in belg
season minimum temperature were explained by time.
15.0
Y = 0.0246X + 9.53
R² = 0.0206
10.0
5.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
0.0
1985
Minimum Temperature
(Deg.C)
Dry Season Minimum Temperature Trend
Figure 18. Bega season minimum temperature trend of Kombolcha from 1985-2012.
In Figure 19 the annual minimum temperature trend shows non-significant temperature
change. As the computed p – value (0.25) is greater than the significance level alpha =0.05,
we should not reject the null hypothesis. The risk to accept the scientific hypothesis while
it is false is 25%. The R2 value 0.051 means that only 5.1 % variation in annual minimum
temperature is explained by time.
26
Y = 0.0398X + 11.77
R² = 0.0506
15.0
10.0
5.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
0.0
1985
Minimum Temperature
(Deg.C)
Annual minimum temperature trend
Figure 19. Annual minimum temperature trend of Kombolcha from 1985-2012
4.7. Seasonal and Annual Mean Temperature Statistics
Under this section the descriptive statistical analysis of annual mean temperature and seasonal mean temperature values, such as mean value, standard deviation and coefficient of
variation are analyzed.
Table 10 below shows statistical properties of annual and seasonal minimum temperatures
of Kombolcha town, and stated as follows. The coefficient of variation showed almost similar values for all seasons. The least standard deviation was recorded for Bega season
(0.78). The annual mean temperature lay between 15.7 -20.40C and the mean value recorded for the study period is 19.50C.
Table 10. Summary of descriptive statistics of annual and seasonal mean temperature
in Kombolcha from 1985-2012
Statistics/season
Mean Tempe
Max.T(0C)
Min.T (0C)
Range (0C)
St.Deviatio (0C)
CV(%)
Kiremt
21.3
22.1
16.6
5.5
0.99
4.6
Belg
20.5
21.5
16.7
4.8
0.90
4.4
Bega
17.6
18.5
14.3
4.2
0.78
4.4
Annual
19.5
20.4
15.7
4.7
0.83
4.3
27
4.7. Seasonal and Annual Mean Temperature Trend
Under this section annual and seasonal mean temperature (average of the maximum and
minimum temperature) trends are analyzed.
From Table 11, unlike the minimum temperature trend that showed a non-significant increment, the mean temperature (average of maximum and minimum temperature) trend
showed a significant increment in all seasons, where the belg season showed the highest
increment and the bega season showed the least increment. The annual and all seasons
mean temperature trends significantly increased, since the P-value is very less than from αValue (0.05). In reference to the limit of accepting significancy in this study, the null hypothesis H0 (there is no trend in the series) is rejected or the scientific hypothesis H1 (there
is trend change in the series) will be accepted. This result is in agreement with different
studies of temperature trend analysis over the country, like studies by the McSweeney
(2008) and studies by FDRE (2008).
Table 11. Summary of annual and seasonal mean temperature trends of Kombolcha
from 1985-2012
Change.
Regression
PR2
Value
Trend
Signi
perdecade
ficance
(oC)
Season
equation
Kiremt
Y=0.0553X + 20.5
0.21
0.014* Increase
Yes
Belg
Y=0.0567X +19.7
0.266
0.005* Increase
Yes
0.56
Bega
Y=0.039X+17
0.175
0.03* Increase
Yes
0.30
Annual
Y=0.048X+18.9
0.23
0.009* Increase
Yes
0.45
0.55
*significant at 5% probability Y= Average annual/seasonal mean temperature X=time in
years
In Figure 20 the kiremt season mean temperature trend shows higher temperature change
than bega season. The temperature increased by 0.055 oC per year or 0.55 oC per decade.
As the computed P – value (0.014) is lower than the significance level alpha (0.05), we
should reject the null hypothesis (there is no trend in the mean temperature series). The risk
to rejecting the null hypothesis while it is true is lower than 1.4%. Therefore, it is true that
28
kiremt season mean temperature change was significant for the last 28 years in the study
area. The R2 value 0.21 means that only 21 percent variation in kiremt season mean temperature is explained by time.
y = 0.0553x + 20.481
R² = 0.2097
22.0
20.0
18.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
16.0
1985
Mean Temperature
(Deg.C)
Kiremt mean monthly temperature trend
Figure 20. Kiremt season mean temperature trend of Kombolcha from 1985-2012
From Figure 21 the belg season mean temperature trend shows the highest temperature
change than kiremt and bega seasons. The temperature was increasing by 0.057 oC per year
or 0.57 oC per decade. As the computed P – value (0.005) is lower than the significance
level alpha (0.05), we should reject the null hypothesis (there is no trend in the mean temperature series). The risk to rejecting the null hypothesis while it is true is lower than
0.56%. Therefore, it is true that belg season mean temperature change was significant for
the last 28 years in the study area. The R2 value 0.27 means that only 27 percent variation
in belg season mean temperature is explained by time.
25.0
y = 0.0567x + 19.723
R² = 0.2656
20.0
15.0
10.0
5.0
0.0
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Mean Temperature (Deg.C)
Belg season mean temperature trend
Figure 21. Belg season mean temperature trend of Kombolcha from 1985-2012
29
Figure 22 clearly showed that the bega season mean temperature trend shows the least
temperature change than kiremt and belg seasons.
y = 0.0394x + 16.997
R² = 0.1742
20.0
15.0
10.0
5.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
0.0
1985
Mean Temperature (Deg.C)
Bega season mean temperature trend
Figure 22. Bega season mean temperature trend of Kombolcha from 1985-2012.
The temperature was increasing by 0.03 oC per year or 0.3 oC per decade. As the computed
P – value (0.027) is lower than the significance level alpha (0.05), we should reject the null
hypothesis (there is no trend in the mean temperature series). The risk to rejecting the null
hypothesis while it is true is lower than 2.7% or the risk to reject the scientific hypothesis
while it is true is greater than 97.3 %. Therefore, it is true that bega season mean temperature change was significant for the last 28 years in the study area. The R2 value 0.175
means that only 17.5 percent variation in bega season mean temperature is explained by
time.
From Figure 23 the annual mean temperature was increasing by 0.048 oC per year or 0.48
C per decade. As the computed P – value (0.009) is lower than the significance level alpha
o
(0.05), we should reject the null hypothesis (there is no trend in the annual mean temperature series). The risk to rejecting the null hypothesis while it is true is lower than 0.9% or
the risk to reject the scientific hypothesis while it is true is greater than 99 %. Therefore, it
is true that annual mean temperature change was significant for the last 28 years in the
study area. The annual mean temperature trend change (0.48 oC per decade) of Kombolcha
town is greater than from the annual mean temperature trend change of the country 0.2-0.4
o
C per decade based on the study of FDRE (2008) and from similar studies by the UNDP
Climate Change Profile for Ethiopia McSweeney (2008) that shows that the mean annual
temperature increased by 1.3°C between 1960 and 2006, at an average rate of 0.28°C per
30
decade. The R2 value 0.23 means that only 23 percent variation in annual mean temperature is explained by time.
Annual mean temperature trend
y = 0.0484x + 18.839
R² = 0.2302
Mean Temperature (Deg.C)
25.0
20.0
15.0
10.0
5.0
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
0.0
Figure 23. Annual mean temperature trend of Kombolcha from 1985-2012
31
5. SUMMARY AND CONCLUSION
5.1. Summary
This project is aimed to evaluate the trend of rainfall (1975-2013) and temperature (19852012) of Kombolcha town, south wollo, north eastern Ethiopia and to compare them with
the country’s trend during the same period.
In this study, daily data on temperature and rainfall were collected from Kombolcha Meteorological station. Daily rainfall data was summed into monthly and annual totals. For further analysis, the monthly rainfall data was categorized according to three seasons, kiremt
(JJAS), Belg (MAM) and Bega (ONDJF). The overall trend in a time series was examined
in this study by the use of linear regression analysis where the values in the series were regressed on time. The main statistical parameter, the slope, resulting from the regression
analysis indicated the mean temporal change of rainfall and temperature. The trend was
then tested for significance. For no trend to exist in the data series the P- value should exceed 5% significance level (P- value 0.05).
The annual mean rainfall of the town during the study period is 1029.7 mm, the annual
maximum rainfall (wettest year) during the study period was 1361.6 mm in 1998, 1313.6
mm in 2010 and 1280 mm in 1993 and the annual minimum rainfall (driest year) in the
study period was 598.5 mm in 1984. The decadal mean values of rainfall from 1975-1984,
1985-1994, 1995-2004 and 2004-2013 were almost similar and showed no significant difference.
The annual rainfall amount contribution of each season was 65% (kiremt), 22% (belg) and
13% (bega). Generally, the seasonal rainfall variability in Kombolcha town was high. The
CV was highest during bega season (0.55), followed by belg season (0.40). The CV for annual rainfall is observed to be 15%.
The assessment of the project showed that July is the month when the town gets the highest
rainfall (267.3 mm) and December is the month when the town received the lowest rainfall
amount (17.6 mm). The monthly coefficient of variation (CV) for this town lay between
0.31-1.35. The variability of rainfall was highest in December with CV (1.35) followed by
32
February (1.14) and the least variability of rainfall was recorded in August with CV (0.31)
followed by July (0.36).
During the past 39 years (1975-2013) annual rainfall trend , belg and bega seasons rainfall
trend showed decreasing pattern but Kiremt season rainfall trend showed an increasing pattern, but all trends were not significant at 95% confidence level.
The range of mean average monthly maximum temperature lies between 24.6 oC (January
and December) to 30.5 oC (Jun), the range of mean average monthly minimum temperature
lies between -0.3 oC (November) to 19.5 oC (Augest).
The annual and all seasons maximum temperature trends was significantly increased at
95% confidence level. The annual maximum temperature trend showed temperature increment at an average rate of 0.055 oC per year, 0.55 oC per decade or 1.49 oC during the
study period. The kiremt season maximum temperature trend shows that the temperature
increased by at an average rate of 0.039 oC per year or 0.39 oC per decade. The belg season
maximum temperature trend shows the highest temperature change than kiremt and bega
seasons. The temperature of belg season increased at average rate of 0.086 oC per year or
0.86 oC per decade and a total increase of 2.32 during the study period. The bega season
maximum temperature trend shows the higher temperature change than kiremt. The temperature increased by at an average rate of 0.05 oC per year or 0.5 oC per decade atotal increase of 1.35 0C.
The trend of annual and seasonal minimum temperature trend shows an increasing pattern
but the increment was not significant at 95% confidence level.
The mean temperature trend shows a significant increment in all seasons, where the belg
season showed the highest increment and the bega season showed the least increment. The
kiremt season mean temperature trend shows the higher temperature change than bega season. The temperature was increasing at an average rate of 0.055 oC per year or 0.55 oC per
decade a total increase of by 1.46 0C. The belg season mean temperature trend shows the
highest temperature change than kiremt and bega seasons. The temperature was increasing
at an average rate 0.056 oC per year or 0.56 oC per decade a total of 1.51 0C. The temperature of dry season was increased at an average rate of 0.03 oC per year or 0.30 oC per dec-
33
ade a total of 0.81 0C .The annual mean temperature increased at an average rate of 0.045
o
C per year or 0.45 oC per decade a total of increased 1.21 0C during the study period.
For P- value of 0.1(i.e.at 90% confidence interval) only Kiremt and Belg rainfall trend and
Kiremt minimum temperature trend can be considered significant.
5.2 Conclusion
Based on the above findings the following conclusions can be made.
 There is no significant annual and seasonal decreasing or increasing rainfall trends
at 95% confidence level for the past 39 years (1975-2013) which is similar to the
countries annual and seasonal rainfall trends according to similar studies.
 There was significant annual and seasonal maximum temperature increasing trend
at 95% confidence level for the past 28 years (1985-2012), which is similar with
the country’s trend.

There was no significant increasing trend of annual and seasonal minimum temperature at 95% confidence level for the past 28 years (1985-2012) unlike that of
the country’s trend.
 There was significant annual and seasonal mean temperature increasing trend at
95% confidence level. The Belg season (short rainy season) showed the highest increment and the Bega season (dry season) showed the least increment.
34
6. REFERENCES
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in the drought-prone Amhara Region of Ethiopia. International Journal of Climatology,
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Daniel Yirgaw.2011. Climate variability in the drought prone regions of Afar and Amhara
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Conway, D. 2000. The climate and hydrology of the Upper Blue Nile River. The Geographical
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Davidson, O., Halsnaes, K., Huq, S., Kok, M., Metz, B., Sokona, Y. and Verhag, J. 2003. The
development and climate nexus: The case of sub Saharan Africa. Climate policy, 31:97113.
FDRE (Federal Democratic Republic of Ethiopia ). 2008. Environmental policy, environmental
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FEWS NET (Famine Early Warning System Net work). 2012. A climate trend analysis of
Ethiopia.
Gadgil, S., Seshagiri, P. and Sridhar, S. 1998. Modelling impacts of climate variability on rainfed groundnut. Indian institute of Science, Bangalore, India. 11p. 70.
IPCC (Intergovernmental Panel on Climate Change). 2001. Climate change impacts, adaptation
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IPCC (Intergovernmental Panel Climate Change). 2007: The physical science basis: Contribution
of working group I to the fourth assessment. Cambridge University Press, Cambridge,
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Manyatsi, A., Mhazo,N. and Majorirambi, M. 2010. Climate variability and change as
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McSweeney, N. 2008. UNDP Climate Change Country Profiles, Ethiopia. UNDP, School of
Geography and Environment, University of Oxford and Tyndall Centre for Climate Change
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Melillo, M., Callaghan, V., Woodward, I., Salati, E. and Sinha, K.1990. Climate Change effects
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Michael, C. 2006. WWF (Worldwide Fund) for nature climate change scientist. Gland, Switzerland.
NMA (National Meteorology Agency).2007. Final Report on Synergy between Adaptation and
Multi-lateral Environmental Agreements prepared by B and M Development Consultants
for NMA. Addis Ababa, Ethiopia.
NMSA (National Meteorological Services Agency). 2001. Initial national communication of
Ethiopia to the United Nations frame work convention on climate change (UNFCCC).
Addis Ababa, Ethiopia.
Onoz, B. and Bayazit, M. 2003. The power of statistical tests for trend detection. Turkish Journal
of Engineering and Environmental Sciences, 27: 247–251.
Segele, Z . and Lamb, P. 2005. Characterization and variability of kiremt rainy season over
Ethiopia. Meteorology and atmospheric physics, 89: 153-180.
Seth, D.2007. Climate change and risk management in Africa. World economic forum on Africa ,
Cape Town.
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Yilma Seleshi and Ulrich, Z. 2004. Recent changes in rainfall and rainy days in Ethiopia.
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June 17, 2014.
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Academic Press, London, UK.
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Accessed on June 25, 2014.
Wolde Amlak Bewket. 2009. Enviromental rehabilation in response to climate change in
Ethiopia.WFP, MERET Project Evaluation Report, Ethiopia
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Hunger in Africa denying famine a future, Cambridge University Press.
WMO (World Meteorological Organization). 2007. The role of world metreological organization in the implementation of the Nairobi Work Programme.
37
7. APPENDIX
Table 1. Monthly and Annual rainfall (in mm) data of Kombolcha town (1975-2013)
Month
Jan
1975
47.9
1976
11.6
1977
24.7
1978
0
1979
86.5
1980
11.4
1981
0
1982 36.91
1983
16
1984
0.9
1985
22
1986
0
1987
0
1988
7.3
1989
11.8
1990
20.9
1991
4
1992
82.8
1993
46.2
1994
0
1995
0
1996
49
1997
33.6
1998
92.5
1999
54.4
2000
0
2001
4.4
2002
18.1
2003
64.7
2004
12.6
2005
19
2006
8.8
2007
40.5
2008
25.5
2009
20.6
2010
0
2011
15
2012
0.3
2013
36.8
Feb
Mar
33.7
50.5
47 102.01
7.7
98.7
33.42
50.31
83.5
81.2
30.1
37
1.6
166.2
107.6
131.1
39.91
162.3
9.6
55.4
0
42.4
32.7
40.5
74.8
114.7
96.8
32.4
43.7
116.3
99
123.4
35.1
112.6
18.4
49.3
83
37.1
0
53.9
29.5
48
3.4
139.7
0
64
94.2
36.4
3.8
22.7
0
6.2
2.7
134.9
5.8
58.9
26
75
11.7
39.7
4.5
76.1
0
121.8
34
52.3
0
0
11.4
17
31.6
70.7
0
50.4
0
109
0.3
54.2
Apr
May June July
Aug
Sept
Oct
Nov
Dec
Annual
102.7
32.6
72.7 185.2
397.2
188.3
10.6
0
13.9
1135.3
156 103.2
30.2 150.6
197.1
120.9
7.7
74.1
51
1051.41
65.21 129.8
13.1 319.5
252.2
102.1
61.3
10
7.3
1091.61
41
36.5
6.8
259
219.1
125.9
32.3 10.01 43.21
857.55
29
77.1
76.4 209.8
209.3
109.8
8
50.3
0.7
1021.6
62.6
41.6
31.8 305.6 278.41 104.23
75.6
15.4
0
993.74
76.5
19.4
0.42
264
291
118.5 120.42
0
9.8
1067.84
104.3
79.5
0
93.7
266.4
101.1
100
70.7 20.22
1111.53
89.51 113.3
75.6 173.8
182.6 120.42
48 19.01
0
1040.45
18.5 164.4
9 113.1
46.6
104.9
0
49.6
26.5
598.5
234.4
41.4
4.8
242
292.8 113.92
1.81
0
9.8
1005.33
138.7
49.5 118.2 254.3
336.1
73.5
6.9
0
20.2
1070.6
39.5 144.7
0
50.1
289.8
39.3
36.2
0
10.4
799.5
100.6
37.7
45.1
397
271.3
170.5
29.7
0
0
1188.4
175.2
2.2
18.5 239.9
259.5
174.1
20.4
3.4 104.1
1169.1
116.4
5.1
0 193.3
115.7
211.6
7.9
0
0
893.3
15.4
33.4
10 175.2
204.7
116
26.7
0
34.6
767.7
137.5
23.2
6.1 174.6
208.2
149.3
87.6
60.1
51.6
1048.7
239.9
181
4.7 256.8
155.3
226.6
41.8
0
7.6
1280
51
86.1
30.5 437.7
331.7
154.4
2.2
36.8
1.9
1186.2
212.8
87.4
30
284
254.5
73.3
30.3
0
44.6
1094.4
133.4 121.2
61.8 163.5
347.1
37.3
2.3
57.2
1.9
1117.8
69
13.6 110.2 233.5
192.9
52
154.6
87
0
1010.4
124.6
49.2
2.9 522.6
248.2
114.5
76.5
0
0
1361.6
19
5.4
10.8 374.3
318.4
109.1
121.8
0
2
1041.7
132.8
70.8
42.3 323.6
349.3
119.3
57.4
58.5
38.3
1198.5
39.2
42.9
46.8 350.4
235.4
115.3
7.1
0.8
8.9
988.8
82.1
20.7
10.6 278.5
254.8
86.8
7.1
0
62.2
885.6
80.9
5.8
48.1 214.9
269.3
149.3
0.2
12.9
60.2
1007.3
142.3
14.8
28 220.3
239.4
82.5
66.8
40.1
5.5
903.7
67
86.4
20.9 356.9
321.6
40.8
25.7
6.7
0
1025.6
87.1
44.3
14.7 365.8
277.2
183.3
62
1.2
6.4
1172.6
115
14.9
37.1 320.7
175.5
90.3
21.6
6.6
0
908.5
18.1
44.7
29.4 286.9
208.2
68.7
47.1
75.6
0
804.2
13.4
6.4
34.6 370.1
320.3
58.4
63.2
11.5
32.4
959.3
102.7 107.6
15.9 363.9
524.8
57.9
11.7
15.2
11.6
1313.6
25.5 130.9
20.4
278
338.6
90.5
16.6
41.4
0
1007.3
177.1
34
50.1
284
261.6
52.9
0.5
0
0.2
969.7
55.2
40
1.8 336.3
284.9
67.2
132.7
0.6
0
1010
38
Table 2. Monthly Average Maximum Temperature data (in 0C ) of Kombolcha town
(1985-2012).
y Aver.max.temp.
Year
Jan
1985
24.7
1986
25.1
1987
24.2
1988
25.3
1989
23.2
1990
23.5
1991
25.9
1992
22.4
1993
22.6
1994
25.4
1995
25.0
1996
23.2
1997
23.8
1998
23.7
1999
24.4
2000
25.5
2001
23.2
2002
24.0
2003
24.1
2004
26.1
2005
25.0
2006
25.5
2007
23.6
2008
26.2
2009
25.1
2010
25.6
2011
24.8
2012
26.4
Feb
25.2
25.5
26.1
25.2
24.2
23.1
25.3
23.1
22.4
26.6
25.7
26.7
25.9
24.5
27.6
26.9
26.1
26.5
27.1
25.5
28.1
27.2
26.1
29.5
27.2
26.6
27.1
27.6
Mar
27.8
26.6
25.0
28.1
25.3
25.3
25.8
26.1
26.4
26.7
26.0
25.8
27.1
26.1
26.7
28.1
25.4
27.2
27.5
27.2
28.1
27.1
28.2
31.4
28.6
26.6
26.4
28.3
Apr
25.2
25.3
25.8
27.4
24.0
25.8
27.8
27.1
24.4
28.6
25.7
26.5
26.8
28.5
29.3
28.0
27.8
27.8
27.7
26.5
28.1
26.3
27.6
31.7
29.3
28.5
29.4
26.9
May
26.5
28.5
26.0
29.7
27.9
29.8
29.2
28.4
25.8
28.9
27.8
26.7
29.0
28.4
30.6
28.5
29.3
30.5
30.2
30.1
27.8
29.0
30.4
32.3
30.8
29.2
28.4
28.6
Jun
29.6
28.8
29.9
30.3
30.4
31.4
31.8
30.6
29.2
30.7
30.2
28.8
29.0
31.7
31.4
31.0
30.3
31.3
30.7
29.9
30.7
31.4
30.4
33.0
32.0
31.5
30.0
30.1
Jul
27.2
27.5
30.4
26.9
28.7
28.0
27.7
28.3
28.2
26.5
27.3
28.1
28.0
27.4
26.9
28.2
27.6
30.0
28.1
28.7
27.8
27.9
27.2
33.5
28.2
28.6
28.6
28.3
Aug
26.6
26.3
27.3
25.6
26.9
28.0
26.7
25.3
27.1
25.6
26.6
26.6
27.0
26.4
26.6
26.6
26.5
27.8
26.4
27.5
27.3
27.1
27.3
27.3
27.6
27.1
26.7
27.5
Sep
25.4
25.4
27.5
25.0
25.2
26.1
26.4
24.6
26.1
25.9
26.3
26.7
27.4
26.6
26.0
26.0
26.2
26.0
26.3
26.4
26.9
26.4
27.3
27.2
28.0
27.0
27.2
27.6
Oct
25.2
25.4
26.1
24.3
24.8
25.7
32.0
23.4
25.2
25.3
25.9
26.4
25.9
25.8
24.2
25.1
26.2
26.7
26.1
25.2
26.0
26.7
26.2
26.3
26.2
26.9
26.3
26.7
Nov
25.0
25.5
26.2
24.1
25.1
25.7
24.9
22.9
25.1
24.5
25.7
24.3
24.8
25.2
24.3
24.3
25.0
26.1
25.8
25.5
25.8
25.2
25.3
24.8
26.7
25.9
24.7
26.9
Dec
24.2
24.0
25.5
24.3
22.3
25.2
24.2
23.4
24.9
24.3
24.7
24.1
24.7
25.1
23.8
23.8
25.4
24.2
24.5
24.9
25.3
24.6
25.5
25.1
25.0
24.3
25.0
26.1
Annual
26.1
26.2
26.7
26.4
25.7
26.5
27.3
25.5
25.6
26.6
26.4
26.2
26.6
26.6
26.8
26.8
26.6
27.3
27.0
26.9
27.2
27.0
27.1
29.0
27.9
27.3
27.1
27.6
39
Table 3. Monthly average minimum Temperature (in oC ) data of Kombolcha town
(1985-2012).
Month Jan
3.8
1985
8.6
1986
9.9
1987
12.5
1988
8.4
1989
10.8
1990
11.5
1991
12.7
1992
11.5
1993
8.6
1994
8.8
1995
12.4
1996
11.1
1997
13.1
1998
9.1
1999
8.5
2000
8.6
2001
11.4
2002
10.7
2003
14.5
2004
13.6
2005
9.6
2006
11.3
2007
9.2
2008
10.0
2009
10.4
2010
11.0
2011
8.8
2012
Feb
4.8
13.9
11.3
14.3
11.8
14.4
13.3
14.2
12.3
10.9
12.5
10.9
8.6
13.8
8.2
8.1
9.0
10.8
11.9
10.5
10.0
12.5
12.4
9.0
11.1
13.6
9.8
7.6
Mar
6.4
12.6
14.9
12.8
13.1
13.7
14.2
13.9
11.5
14.4
13.4
13.5
13.4
14.1
12.8
11.3
13.1
13.2
13.3
11.2
13.3
12.8
12.0
8.9
12.3
13.2
11.7
10.5
Apr
7.3
14.4
13.8
14.6
13.9
13.9
14.0
13.9
14.1
13.9
14.9
13.7
13.5
14.5
12.2
13.5
12.8
13.5
14.1
14.4
13.8
13.9
14.0
12.9
13.5
15.1
13.8
13.7
May
7.0
14.8
14.7
14.5
13.6
14.7
14.4
14.0
14.2
14.1
14.1
13.9
13.3
14.0
14.3
14.4
14.3
14.3
14.2
13.0
15.1
13.9
14.5
15.4
14.0
15.5
15.1
13.9
Jun
7.2
15.7
15.6
15.8
14.9
15.6
16.6
15.3
14.3
16.4
15.2
14.8
14.6
15.1
15.0
14.6
15.7
15.3
15.0
13.5
15.1
14.8
16.4
14.0
16.2
16.0
15.4
15.2
Jul
6.2
15.0
16.2
15.5
15.6
15.5
15.8
15.4
14.8
14.9
15.4
15.2
14.9
15.1
15.0
14.5
14.4
15.9
15.0
14.8
15.2
15.3
15.4
13.6
15.4
15.7
15.7
15.4
Aug
5.8
14.7
15.3
14.7
14.8
15.3
15.3
19.5
14.6
14.1
15.2
14.9
14.1
15.1
14.6
14.0
15.0
15.2
15.4
14.6
15.2
15.2
15.1
15.1
15.4
15.1
15.3
15.2
Sep
4.8
13.5
14.4
14.4
14.2
14.3
13.7
13.5
13.7
12.2
13.6
14.3
13.0
13.6
14.1
13.3
12.7
14.4
14.6
17.9
14.4
14.0
14.4
14.3
14.0
14.5
13.7
14.5
Oct
1.7
10.6
12.3
11.8
11.6
10.4
10.3
10.8
11.6
8.2
9.6
9.5
11.5
11.7
12.0
11.8
11.4
10.4
9.4
9.5
9.8
11.8
9.7
11.4
11.5
11.6
10.9
9.8
Nov Dec
-0.4
8.9
9.1
9.8
9.5
10.2
7.8
8.3
8.4
13.1
9.4
7.6
7.9
9.6
9.9
11.4
8.4
7.0
8.5
7.3
8.3
10.3
8.8
8.3
11.0
8.4
7.1
5.9
6.8
8.0
8.9
8.5
8.2
8.1
8.2
12.6
8.5
8.1
8.6
10.3
8.1
5.7
10.1 11.8
9.8
6.5
9.4
8.0
8.7
12.2
9.3
9.5
11.9
8.4
9.6
9.4
Annual
5.3
12.7
13.2
13.1
12.8
13.0
13.0
13.7
12.3
12.0
12.6
12.5
12.3
12.8
11.9
11.8
12.0
12.9
12.5
12.8
12.4
13.0
12.6
11.8
12.9
13.3
12.7
12.0