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Using an Empirical Climate Model
| Climate Forcing Component | How Much of the ‘Best Fit’ Can Be Explained | Other Observations Based on Manipulation of the Model |
| El Nino | 1.1% | The 2nd graph (red line) reduces with the changes |
| Volcanic | 10.1% | The temperature returns to equilibrium around 1995 following fluctuations during 1992 |
| Solar Cycles | 1.2% | No noticeable changes to the temperature |
| Anthropogenic | 51% | It appears the temperature is gradually declining with minimal deviations. |
Question One
When the anthropogenic and volcanic settings are change to 0 and 1, there is a change in both observations. The temperature experiences a sharp decline in 1992 and instead of returning to equilibrium, there is equally another sharp decline in the anthropogenic.
El-Nino and volcanoes seem to balance each other due to their extreme temperature differences. The best fit is drawn when they are both at zero.
Question Two
While all four effects have considerable implications on global temperatures, it is evident that anthropogenic and volcanic variables have the greatest effect on climate change. The consequences are more drastic and long-lasting compared to the other two variables.
Question Three
According to research, empirical models depend on past events and observations to draw inferences or conclusions (Pierce et al. 8442; Skelton et al. 18). On the other hand, global climate models (GCM) use equations and data to make climate predictions. The data-based approach is GSM greatest strength as it negates human errors. On the other hand, it is complex and relies on vast amounts of data (Zhu et al. 8729). The empirical model is useful because it factors in El-Nino and other natural disasters. However, observations are prone to human error.
Question Four
Empirical models are best applied to scientists in the comparison of global climate patterns that span years. Some weather occurrences cannot be tracked on a daily basis as they take many years to occur (McCrystall et al. 6765). Empirical models provide leeway to consider the longitudinal changes and their effects on global weather.
Works Cited
McCrystall, Michelle R et al. “New Climate Models Reveal Faster and Larger Increases in Arctic Precipitation Than Previously Projected.” Nature Communications, vol. 12, no. 1, 2021, pp. 6765., doi:10.1038/s41467-021-27031-y
Pierce, David W et al. “Selecting Global Climate Models for Regional Climate Change Studies.” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 21, 2009, pp. 8441-6. doi:10.1073/pnas.0900094106
Skelton, Maurice et al. “Customising Global Climate Science for National Adaptation: A case Study of Climate Projections in UNFCCC’s National Communications.” Environmental Science & Policy, vol. 101, 2019, pp. 16-23. doi: 10.1016/j.envsci.2019.07.015
Zhu, Feng et al. “Climate Models Can Correctly Simulate the Continuum of Global-Average Temperature Variability.” Proceedings of the National Academy of Sciences of the United States of America, vol. 116, no. 18, 2019, pp. 8728-8733. doi:10.1073/pnas.1809959116