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Time Series Analysis and Projection of Climate Variables of Piracicaba, SP

Overview: In this task, we used the long timeseries of climatic attributes, from Piracicaba Weather Station. This timeseries data started to be recorded in 1905, gathering more than a century of climate information. The spreadsheet with these data contains attributes such as Temperature (maximum, minimum and average), Air Relative Humidity, Precipitation and Global Radiation.

Questions: Using these climate data, we formulated the following scientific questions: 1-Is Piracicaba climate getting warmer, dryer and more rainless? 2-The tendency of increasing temperatures and decreasing relative humidities and precipitation will continue 100 years ahead?

Procedures Description: From Piracicaba Climate Spreadsheet, we extracted Mean, Minimum and Maximum Temperature, Relative Humidity and Precipitation data. Using dynamic tables in the Spreadsheet, we organized these daily data, turning them into average annual data and then into average decade data. With these decade data, we performed a polinomial quadractic modelling, aiming to predict these climate attributes (response variables), using the decade as the predictor variable. Thereafter, we used the fitted equations to perform a projection of the climate variables 100 years ahead (until 2120) to assess the tendency of these attributes over a century.

Outcomes Interpretation: .

Raw Data and Code used

Plots Generated

Figure 1. Modelling of Minimum Temperature using 1920-2025 data and its projection to 2120.

Figure 2. Modelling of Average Temperature using 1920-2025 data and its projection to 2120.

Figure 3. Modelling of Maximum Temperature using 1920-2025 data and its projection to 2120.

Figure 4. Modelling of Annual Average Precipitation using 1920-2025 data and its projection to 2120.

Figure 5. Modelling of Air Relative Humidity using 1920-2025 data and its projection to 2120.