Essa é uma revisão anterior do documento!
Tabela de conteúdos
DRAFT
== Data and Results of Climate Analysis ==
Data Source
The climate analysis is based on data from FigShare, which includes historical records of carbon dioxide (CO2) concentration and temperature measurements. The dataset spans multiple years and provides key insights into the relationship between CO2 levels and temperature variations. For more information, refer to: [https://climatechange.chicago.gov/climate-change-science/future-climate-change](https://climatechange.chicago.gov/climate-change-science/future-climate-change).
Data Processing
The dataset was processed using R, employing the following steps: - Loading the dataset: The data was imported from an Excel file. - Data transformation: Conversion of year, CO2 concentration (ppm), and temperature (K) values into numeric format. - Summary statistics: Calculation of mean CO2 levels, mean temperature, and correlation between CO2 and temperature.
Results
Summary Statistics
- Mean CO2 Concentration: The average CO2 level across the dataset. - Mean Temperature: The average temperature measured in Kelvin. - Correlation Analysis: A correlation coefficient was computed to assess the relationship between CO2 levels and temperature changes.
Visualizations
To better understand trends, the following visualizations were created: - CO2 Concentration Over Time: A line graph showing how CO2 levels have evolved over the years. - Temperature Change Over Time: A time series plot illustrating temperature variations. - CO2 vs Temperature Scatter Plot: A scatter plot with a fitted regression line demonstrating the correlation between CO2 concentration and temperature.
Correlation and Regression Analysis
- The correlation coefficient calculated between CO2 and temperature suggests a strong relationship. - A linear regression model was applied to examine the trend:
- Regression Equation: Temperature = *Intercept* + *Slope* × CO2 Concentration
- The model summary provides insights into the significance of CO2 as a predictor of temperature variations.
Conclusion
The analysis confirms a strong correlation between rising CO2 levels and increasing temperature. The regression analysis further suggests that CO2 concentration significantly impacts temperature changes. These findings reinforce the scientific understanding of climate change and the role of greenhouse gases in global warming.
Files and Graphs
- Temperature_Change_Over_Time.png: Visualization of temperature trends. - CO2_vs_Temp.png: Scatter plot of CO2 vs Temperature with regression line.
This analysis provides critical evidence supporting climate change research and helps understand long-term environmental trends.