The research performed in the framework of the completion of the Ph.D.
dissertation, is focused on the analysis of Florina’s meteorological data and climate
parameters that have an influence on agriculture.
In the prefecture of Flonina were operating seven meteorological stations which are
replaced with nine automatic ones. The data that are recorded is temperature, relative
humidity, solar radiation, wind speed and precipitation. The area is homogenous and the
data recorded between all stations have high correlation.
Double mass analysis for the temperature for the stations, between two each time, is
performed. Comparison of hourly recorded maximum and minimum values to the
maximum and minimum values of the day is performed for temperature and relative
humidity. Also, are compared the mean daily temperature to the average of the maximum
and the minimum temperature. The lapse rate is computed, using the mean temperature of
all the meteorological stations. The Weibull distribution is used, on monthly basis, for the
extreme values analysis of temperature. The Köppen Climate Classification System is
used to classify the climate of each one meteorological station.
A new function, based on the weighted least squares method, is developed for the
computation of b factor of the FAO 24 Blaney-Criddle evapotranspiration method.
New non linear functions are developed to estimate solar radiation from temperature
range.
A methodology is developed to estimate solar radiation, taking in account the daily
distribution of sunshine.
ANalysis Of VAriance (ANOVA) is performed to estimate the meteorological,
topographical and time parameters that are statistically important for the Clearness Index.
Spectral analysis is implemented to the hourly values of clearness index. The Lomb –
Scargle periodogram is calculated to find the periodicity of the clearness index. A
sinusoidal function is used to express clearness index as a function of time.
Clear sky solar radiation is calculated with the proposed sinusoidal function and the
existing exponent equations.
Comparative evaluation of five methods (FAO24 Blaney – Criddle, FAO24
Makkink, FAO24 Penman, FAO56 Penman – Monteith, Hargreaves) for the calculation of reference evapotranspiration is performed.
Is investigated the influence of:
• Sunshine to FAO24 Blaney – Criddle method,
• The factor b to FAO24 Blaney – Criddle method,
• Solar radiation to Makkink, Penman, Penman – Monteith and Hargreaves
methods,
• Clear sky solar radiation to Penman and Penman – Monteith methods,
• The factor c to Penman method.
A new sensitivity coefficient, based on standard deviation, is developed for the
sensitivity analysis to compare the relative importance of parameters. The new sensitivity
coefficient is implemented for the estimation of the relative importance of the
meteorological parameters to evapotranspiration, which is calculated with all the
mentioned 5 methods.
National Documentation Centre (EKT)
