Revealing climatic fluctuations with emphasis on minimum temperature parameters and freezing days

Number of pages: 131 File Format: word File Code: 30116
Year: 2014 University Degree: Master's degree Category: Geography - Urban Planning
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  • Summary of Revealing climatic fluctuations with emphasis on minimum temperature parameters and freezing days

    Dissertation to receive a master's degree

    in the field of urban meteorology

    Abstract:

    Researches conducted in the world mainly indicate a gradual increase in the average temperature. Today, the temperature trend of Frein is one of the most important climate parameters that are evaluated to prove climate change in a region. Analyzing the trend of the time series of the temperature limit indicators gives us a better understanding of the past and present behavior of climate change. In this research, in order to identify the climatic fluctuations of minimum temperature parameters and freezing days, the observations of Khorramabad synoptic station in the statistical period of 1984-2013 were used. The aim of this study was to reveal the minimum temperature trend on a monthly basis. On the other hand, seasonal time series were chosen for trend analysis. The methods used in this research to analyze the minimum temperature trend were using the absolute standard normal homogeneity test. To draw trend analysis charts, Mann-Kendall statistical test was used at 95% and 99% levels. In order to predict the temperature trend in the coming years, two methods of the Holt-Winters smoothing test and ARIMA were used. The results obtained from the statistical methods used in this research showed that the temperature series had no significant heterogeneity and the metadata of the station confirmed the homogeneity of these series. The most and least significant trend of minimum temperature occurred in spring and autumn, respectively. Kendall's T-statistic for the studied time period showed a significant increase in minimum temperature in most months. The results of temperature forecasting with two methods, Halt-Winters and ARIMA, show that the temperature will increase at least in the coming years, but the temperature trend in the autumn season is less significant than in other seasons. Based on this, the results of the study of the severity of frost in the winter season during the statistical period studied showed that the severity of the frost has decreased.

    Introduction:

    Geography[1] is the interrelationship between man, technique and the environment or the interrelationship of man, technique, management and the environment (Papli Yazdi 1369). and the analysis of factors, the difference between climates and the use of climatic information in solving society's problems (Hascheck[3] 1980).

    In other words, the goal of climatology is to discover and explain the natural behavior of the atmosphere and exploit it for human benefits. Climate as the main subject of climatology has been known to man and the scientific community for a long time (Dorst[4] 1951).

    Although the behavior of the atmosphere can be explained and explained by certain physical laws, for example, the movement of water vapor or air in the atmosphere is controlled by certain laws and principles, but the appearance of the atmosphere, in addition to being controlled by the behavior of the atmosphere, is also influenced by the low and high altitudes of the earth's surface, and as a result, the appearance of the atmosphere, which is Continuous changes in temperature, humidity, cloudiness, pressure, etc. cannot be expressed and explained by fixed physical principles and laws. In general, atmospheric states are a reality that can be understood through repeated observations in the dimension of time and space. For this reason, the daily changes in the state of the atmosphere are assumed to be semi-random variables and therefore can be explained and justified using statistical distributions of probabilities (Landsberg[5] 1987).

    The most important factor of any statistical distribution is its average, which was considered the most important statistic for defining climate until the end of the 19th century. Today, many common people and even climatologists use it, but at the end of the 19th century K?ppen announced that the climate of a region cannot be explained and described only by calculating the long-term average of its meteorological elements (Stringer [6] 1982). Rather, in describing the climate of a place, one should also pay attention to frequencies and frequencies. Therefore, climate today is determined by examining the frequency of occurrence of climatic elements of a place such as temperature, precipitation, relative humidity, freezing days, etc. The process of determining the climate is either based on the frequency of different momentary weather and the amount of time, or based on the set of long-term conditions of climatic elements and using multivariate statistical methods. Roughness, latitude and distance and proximity to large bodies of water are considered to be the most important factors affecting the spatial distribution of temperature. In the cold and hot seasons, the difference in the average temperature of the coldest and hottest parts of Iran is so great that different parts of the country experience different seasons at the same time.. In the cold and hot seasons, the difference between the average temperature of the coldest and hottest parts of Iran is so great that different parts of the country experience different seasons at the same time (Montazari 2012).

    In recent years, scientists have paid special attention to temperature series in order to analyze climatic patterns, temperature is one of the most important climatic elements and is also effective in determining the role and distribution of other climatic elements. Temperature is also one of the main and fundamental factors in climatic zoning and classification, and therefore the basis of fluctuations and variability of temperature is very important, and due to the prediction of future temperatures, it has great scientific and practical importance. Time series methods to study climate, especially temperature, have been used and cited in countless writings (Quaidel Rahimi 2013).

    Temperature is a thermodynamic and important atmospheric variable whose change is the source of many physical, chemical and environmental changes, and its measurement in the atmosphere has a longer history compared to other atmospheric elements (Masoudian and Darende 2013). In recent years, climate change, especially global warming, has received much attention. The climate of the earth has always been changing, but its warming has attracted more attention from climatologists. Since temperature is one of the basic elements of climate formation, its changes can change the climate structure of any place. For this reason, examining the temperature trend in temporal and spatial scales has occupied a large part of climatology research (Esadi and Heydari 2019). Despite the evidence of temperature changes and the warning of several scientists in 1948 and 1947 about global warming, the belief based on climate stagnation continued until the 1970s. The results of extensive studies carried out at the national, regional and global levels indicate an increase in temperature in many parts of the globe and an overall increase in the average temperature of the earth's air. During the last few decades, the minimum and maximum temperatures have shown different behaviors and the minimum temperature has obviously increased in many places; Although the maximum temperature shows an increasing rate in many places. But due to its lower rate compared to the minimum temperature, it has caused a decrease in the day and night range[7] of temperature (Rahimzadeh and Asgari 2013).

    The speed and nature of changes in climate parameters in the second half of the 20th century have been different and have gained more momentum and the process has become somewhat different from the past. The issue of climate change has always faced many doubts, and for this reason, various researchers and scientists have done a lot of research on its nature and causes, and have announced hypotheses that sometimes contradict each other. Climate change is one of the most complex problems that humanity will face now and in the future. This phenomenon is caused by the changes that have occurred in the atmospheric processes that have caused the warming of the earth's air and have had important effects and consequences in the hydrological cycle. Many scientists and researchers believe that there are signs of gradual warming on the planet. One of the most basic reasons is that most of the energy received from the sun and received from the air surrounding the earth is stored in the atmosphere and its exit from the earth's atmosphere is slow. Although the real causes of climate variability are not fully known, hypotheses have been proposed as effective factors in climate change, and the result of all these hypotheses is the change in temperature and precipitation parameters (Nasiri Mahalati et al. 2015). The average air temperature on the surface of the earth and its changes are indicators of climate change, which are mentioned in almost all climate change theories. Estimates show that the average temperature in 2030 will be 0.7 to 2 degrees Celsius warmer than today. Also, based on climate models, it is predicted that the average temperature of the earth will increase by 2 to 3.5 degrees Celsius in the year 2100 (Ebrahimi et al. 2014). 

        

    1-2 - Statement of the problem:

    Since the climate plays an important role in all aspects of life, paying attention to its changes and fluctuations in the last 150 years and especially in recent decades has become one of the concerns of humans. Climate change refers to changes in the climatic behavior of a region compared to the expected behavior during a long period of time from recorded and observed information (Azarakhshi et al. 2012).

  • Contents & References of Revealing climatic fluctuations with emphasis on minimum temperature parameters and freezing days

    List:

    Title

    Chapter 1

    Research overview

    1-1 - Introduction.. 2

    1-2 - Statement of the problem.. 5

    1-3 - Importance and research necessity.. 7

    1- 4 - Research objectives.. 7

    1-5 - Research questions.. 9

    1-6 - Research assumptions.. 9

    Chapter II

    Theoretical foundations and research background

    1-2- Theoretical foundations of research.. 12

    2-1-1- Metadata.. 12

    2- 1 - 2 - Homogeneity of data.. 12

    2 - 2 - Temperature.. 14

    2 - 2 - 1 - Minimum temperature.. 14

    2 - 2 - 2 - Frein temperature.. 14

    2 - 3 - Frost.. 14

    2 - 3 - 1 - Types of frost.. 14

    2-4 – Time series.. 15

    2-4-1 – Types of time series.. 15

    2-5 – Random processes.. 15

    2-6 – Review of sources.. 16

    2-6-1- Internal sources.. 16

    2-6-2- Sources Foreign.. 31

    2-7 - Conclusion.. 36

    Chapter 3

    3 - Study area.. 38

    3-1 - Geographical location of Lorestan province. 38

    3-2- Geographical location of Khorramabad city. 38

    3-3- The relative position of Khorramabad city. 38

    3 - 4 - The climate of Khorram Abad city. 39

    3 - 4 - 1 - Local factors.. 39

    3 - 4 - 2 - Latitude.. 40

    3 - 4 - 3 - Access to moisture sources.. 40

    3 - 5 - The climatic condition of Khorramabad city. 40

    3-5-1 - Temperature.. 41

    3-5-2 - Precipitation.. 42

    3-6 - Prevailing winds of Khorramabad city.. 42

    Chapter 4

    4 - Materials and methods.. 44

    4-1 - Meteorological station of the studied area. 44

    4-2 – required variables.. 44

    4-2-1 – minimum temperature.. 44

    4-2-2 – frost days.. 44

    4-3 – materials and methods.. 44

    4-3-1 – collection of used data. 44

    4-4- Data homogeneity.. 45

    4-4-1- Homogeneity test method for temperature time series. 46

    4 - 4 - 2 - Absolute standard normal homogeneity method. 46

    4 - 5 - Run test - test.. 47

    4 - 6 - Test for the existence of a trend.. 47

    4 - 6 - 1 - My - Kendall test. 48

    4 - 6 - 3 - My diagram test - Kendall. 49

    4-7 – Holt-Winters smoothing method.. 50

    4-8 – Box-Jenkins models.. 52

    4-8-1 – Stationary check in variance.. 52

    4-8-2 – Stationary check in mean.. 53

    4-8-3 - Draw ACF and PACF diagrams. 54

     

    4-8-4 - checking the appropriateness of the model.. 54

    4-8-5 - forecasting.. 55

    4-8-6 - autoregressive process.. 55

    4-8-7 - moving average process.. 56

    4-8-8 - compound process Autoregressive – moving average. 57

    4 - 8 - 9 - Periodicity in the seasonal model.. 57

    Chapter 5

    5 - Research findings.. 61

    1 - 5 - Descriptive research findings.. 61

    5 - 2 - Diagrams extracted from the standard normal homogeneity test. 62

    5-3- Findings from the Run-test. 63

    5-4 - Findings from my test - Kendall for the minimum temperature. 63

    5 - 4 - 1 - The results of my statistical test (T) - Kendall. 63

    5 - 4 - 2 - My chart test results - Kendall. 65

    5-5 - Findings from my test - Kendall for frosty days. 69

    5-5-1- The results of my statistical test (T) - Kendall. 68

    5-5-2 - Results of my chart test - Kendall. 68

    5-6 - The results of estimating the linear trend of temperature in MINITAB software. 70

    5-7- The results of the Holt-Winters smoothing test. 72

    5-7-1 - Winter season.. 72

    5-7-2 - Spring season.. 74

    5-7-3 - Summer season.. 76

    5-7-4 - Autumn season.. 78

    5-8 - Results of ARIMA model application. 80

    5-8-1 - winter season.. 83

    5-8-2 - spring season.. 85

    5-8-3 - summer season.. 87

    5-8-4 - autumn season..91

    5-9- Conclusion. 92

     

    Sixth chapter

    6-1- Summary. 95

     

    6-2- Results. 96

    6-3- Hypothesis analysis. 97

    6-3-1- Research questions. 97

    6-3-2- research assumptions. 97

    4-6 - suggestions. 100

    Sources and sources. 102

    Appendixes. 113

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Revealing climatic fluctuations with emphasis on minimum temperature parameters and freezing days