The data exists the same way as it was in the archive and it will first be edited. This includes the filling of the missing data using the estimation method and checking for the consistency through data quality control method.
The data from this station will be used to determine the mean daily air temperature using the maximum and minimum temperatures. Correlation analyses for mean air temperatures with amount of sunshine will also be conducted and also with that of maximum temperature. The relationship between the soil temperature and air temperature will also be conducted. Then, the lag between air temperature and that of soil temperature will be conducted and finally, the differences of the air temperatures will be investigated.
Data handling
There is the need for the careful checking of the data before processing to minimize errors. The process involves the following steps cleaning of the data thoroughly. Stop checking of the data to observe if there are any glaring errors. This is done by comparing the raw data and the card stage data. Checking of minor errors on a random sample for quality control is also necessary. Crop (2010 67).
DATA AND METHODOLOGY
This chapter focuses on the data sets used in this study, the data quality control and the methodology used for analysis.
The data is coverage for the years 2000-2002. The data was recorded on the daily basis for the maximum and minimum temperatures, sunshine and also the soil temperatures at the surface, 10cm and also 20cm depth on the ground.
The daily minimum and maximum temperature for this particular station in degrees Celsius is used in this study.
The daily soil temperatures for the surface, 10cm and 30 cm in degrees Celsius below the ground were also used. This was also averaged to obtain the monthly averages, and then used to determine the seasons.
The sunshine duration in the units of hours was also used.
Methodology
In order to achieve the objectives, several quality control measures were used. Also, the various methods for studying the relationship between soil temperature and the air temperature, the trend analysis in the region is also discussed. The methods included,
Estimation of the missing data
The purpose of estimation of the climate data is to fill the missing gaps in a series of measurements in this particular station. The measurements may be missing on account of malfunctioning of the instruments or even the power break down. During the estimation of the missing data it is advisable to separate the columns with the missing data from those that are full as I did in my case. Abas (2010 56).
In some cases, the data missing can be assumed if the available data is more than ninety five percent of the total samples considered.
Data Quality Control
Data quality control helps in the identification of missing figures, and also checking of the internal consistency of the data. The simultaneous maximum and minimum values of temperatures was conducted to check on the similarity. For example, one can find a case where the maximum temperature is lower than minimum thus the need for collection. Once the data are checked, they may be supplemented by the calculations of averages, the amount of scatter and the extreme data.
The method used to test the homogeneity of the data for detection of errors in the data is the Single Mass Curve, whereby, the data is cumulated in time. In this study, the single mass curve straight line would indicate a homogenous data whilst heterogeneity would be indicated by significant deviations of some of the plots from the straight line. The results of the mass curves are as shown in the results section.
Calculation of the mean air temperatures
The mean air temperature is the average between the maximum and minimum temperatures.
Estimation of missing temperature data
This was done by using the mean monthly temperature, annual mean temperatures and the seasonal means. However, the missing data was very minimal. This is by multiplying the monthly means with seasonal means and dividing by the annual means.
The daily data was averaged to obtain the monthly averages, and then used to determine the season. The average air temperature was determined by the use of the maximum and minimum air temperature. The mean temperature is the is the average of the two that is given by the formula
Where T mean is the mean temperature, T max is the maximum daily temperature and T min is the minimum daily temperature.
Results and discussion
To assist in drawing the daily mean temperature, the first day of January 2000 was taken as day 1 and I progressed to 1096th day as the 31st December 2002. The graph was as shown.
For the mean monthly temperatures, the January of 2000 was taken as month 1 and the December 2002 as the month 36.
It is clearly seen that the temperatures changes with the months with the highest temperatures in august and minimum in January.
Correlation of temperature with sunshine
The air temperatures depend on the amount of solar radiation that reaches the earths surface. Therefore, there is evident high correlation that exists between the mean daily air temperatures, maximum and also minimum temperatures. The temperatures also correlate with the daily hours of sunshine.
Correlation analysis
The correlation analysis was done to determine the degree of relationship between the air temperatures and the sunshine mixing ratio at the station.
The Pearsons correlation coefficient (r) was used to determine the magnitude of correlation between the two parameters.
The correlation coefficient is given by the formula below
EMBED Equation.3 ..................................................... (3)
Where
N Total number of observations
Mean monthly air temperature.
Mean monthly sunshine amount.
The amount of sunshine was estimated using the method below.
The amount and the degree of the cloud cover at a given location is determine by the differences in the maximum and minimum temperatures. During a clear sky conditions the temperatures (Tmax)) are relatively high during the day due to the transparency of the atmosphere that reduces the reflection and absorption of the incoming solar radiation. In the same case, the temperatures during the night (Tmin) are relatively cold due to the increased long wave radiation and the reduced reflection and absorption in the atmosphere.
However, during the overcast conditions, a lot of absorption of the direct solar radiation takes place. The clouds absorb the radiation and emit it back into space without reaching the ground surface. As a result, the maximum temperatures (Tmax) are relatively lower. The cloud cover acts as a blanket that absorbs and re emits the out going long wave radiation and reflects it back to the surface. As a result, the minimum temperatures (Tmin) are relatively warmer. The difference between the maximum and the minimum temperatures, (Tmax- Tmin) thus, can be used as a good indicator of the amount of terrestrial radiation that reaches the earths surface.
This principle has been utilized by Hargreaves and Samani to develop estimates of ETo using only air temperature data.
The Hargreaves radiation formula, adjusted and validated at several weather stations in a variety of climate conditions, becomes
Where
Rs is the solar radiation
Ra extraterrestrial radiation MJ m-2 d-1, which mostly depends on the earth sun distance.
Ra is given by the formula
Where Isc is the solar constant given as 1.3661kWm2 and n is the day of the year.
Tmax maximum air temperature C,Tmin minimum air temperature C,kRs adjustment coefficient (0.16.. 0.19) C-0.5.
The square root of the temperature difference is closely related to the existing daily solar radiation in a given location. The adjustment coefficient kRs is empirical and differs for interior or coastal regions
For interior locations like in our case, where land mass dominates and air masses are not strongly influenced by a large water body like in our case, kRs 0.16 Rick (2005 p34)
Results
The correlation between the mean temperatures and sunshine gave a weak positive correlation of 0.2.
For the correlation between the maximum daily temperatures and the sunshine, the results were a stronger positive correlation of 0.45. This shows that the amount of sunshine is related to the air temperatures and this depends with the intensity of sunshine reaching the surface.
Relationship between air temperature and soil temperature
Temperature is important in almost all chemical and physical processes. This even includes weathering and decomposition. To determine whether the soil temperatures are dependent on the atmospheric temperatures, the data was averaged to obtain monthly mean air and soil temperatures. The two follow the pattern of solar radiation.
The soil temperatures are also moderated by the vegetation cover and the floor of the surface, the canopy protect the soil from excessive high temperature in summer through intercepting solar radiation and it prevents the loss of heat from the soil during the winter season. Eleftheria (2002 p79).
To observe the relationship of the two, correlation between the two variables was done. The results displayed a very strong correlation between the mean air temperature and the mean soil temperature. The correlation value was 0.95, thus the temperature of the soil depends mainly on the air temperature.
Lag time between the temperature of the air and the soil temperature.
In this case, the averaged air and soil temperatures were used to determine the lag correlation. It was expected that the soil temperature is to exhibit a lagged reflection of a moving average on both monthly and daily basis. As a result, the air temperature affects the amount of water a given soil can hold.
Radiation load, transpiration rate, canopy conductance, and energy dissipation by conduction and convection determines the differences between the air temperature and the soil temperature. Fahkri ( 1996 p66).
This was examined by working on the lag correlation of the two variables.
However a lagged correlation was observed with a lag time of six months. The soil temperature lags behind the air temeprature and this changes with the depth of the soil. This however, is dependent with the type of the soil.
Annual variation analysis
These are identical patterns that a time series appears to follow during corresponding months of successive years. The mean seasonal air temperatures were determined by plotting the trend and the bar graphs.
There are very small differences in the mean monthly temperatures for the three years as shown by the graph. These are as a result of the global warming and the human activities.
Conclusion
The relative sunshine duration is another ratio that expresses the cloudiness of the atmosphere. It is the ratio of the actual duration of sunshine, n, to the maximum possible duration of sunshine or daylight hours N. In the absence of any clouds, the actual duration of sunshine is equal to the daylight hours (n N) and the ratio is one, while on cloudy days n and consequently the ratio may be zero. In the absence of a direct measurement of Rs, the relative sunshine duration, nN, is often used to derive solar radiation from extraterrestrial radiation. As with extraterrestrial radiation, the day length N depends on the position of the sun and is hence a function of latitude and date. The daily temperature was seen to consist of seasons.
The correlation between air temperature and sunshine showed that the level of inter relationship increase with the increase in temperature. This is evident with the strong correlation for the maximum temperature and sunshine.
Deeper in the soil, the lag time becomes longer and the influence of solar radiation is reduced. This is however, affected by the amount of soil cover and the vegetation. 4early in the season, the soil are bare, the surface receives maximum energy and experiences the largest fluctuation in temperature. With greater canopy development, energy exchanges occur further from the soil surface and the soil temperatures fluctuate less.
Categories:
0 comments:
Post a Comment