Statistical model for the analysis of temperature: case study the 1895 - 2014 serie for Florida state

Abstract

This study applied experimental design to mean annual, mean maximum and mean minimum temperatures of Florida State, U. S. A. Considerations are: 1. Testing various continuous probability distributions, to identify the best one, to avoid experimental errors using the statistics Anderson-Darling (A-D) and P-value. The results showed the normal distribution was the best. 2. Calculations of descriptive statistical for the mean annual, mean maximum and mean minimum temperatures. The results showed very little experimental errors. 3. Constructing normal probability plotting positions to calculate return periods and probabilities of occurrence. 4. Construction of time-series analysis and its subjectivist validation, to assess annual temperature trends. The results showed upward trends for the mean annual, mean maximum and mean minimum temperatures. 5. Establishing a reliable database temperature framework for Florida State, to be used by researchers in meteorology, environmental engineering, hydrology, civil engineering, agriculture, etc.

Keywords

• Experimental design, normal probability plotting positions and time-series analysis.