This project consists of a months work, of data research, analysis and results. The project’s intent is to demonstrate how the increasing carbon dioxide concentrations in the atmosphere are effecting the global temperature. Then cross analyze the ocean temperature anomaly data against the wildfire data to find a correlation between increasing temperatures and drier conditions that facilitate wildfires.
The data was sifted through using a few labor saving devices, such as Matlab and Emacs. The usefulness in Emacs comes from its ability for the user to create macro keyboard commands that can be repeated thousands of times to remove columns of data, or adjust the set as a whole. The data used comes from several different locations from across the internet. The errors and uncertainties were evaluated to gain a better understanding of how accurate the results are. Plots of the data are shown in various figures throughout the document. A strong majority of the graphs include trend lines that show an obvious upward trend. The final results indicate a strong correlation between the increase of carbon dioxide concentration in the atmosphere, temperature anomaly data, and an increase of wildfire severity.
Talk of climate change is everywhere, it is on the news, in the papers, and in publishings by researchers with new findings or backing up old ones. Climate change was originally called global warming, but now we know that the climate is doing more than just getting warmer. Assertions heard most commonly about climate change include sea level rise, warming oceans, glacial retreat, more extreme event occurrences, and rising carbon dioxide(CO2) levels. This project focuses on three big aspects of climate change. A major cause, evidence of warming global temperatures, and a specific affect of the increasing temperatures.
Carbon dioxide has the largest effect on the Earth’s atmosphere. It is significantly larger than other molecules like hydrogen and oxygen. The amount of energy carbon dioxide holds is the standard for the greenhouse effect with a rating of 1. Other molecules, like methane, have a much higher greenhouse rating. Methane has a rating of 20 on the scale(1). However, the volume of them is considerably less than carbon dioxide. When heat radiates from the Earth’s surface CO2, and other large molecules, absorb the radiation and reflect it back towards the surface of Earth(1). This is the main contributor in the greenhouse effect. In 2013 the US produced 5,505 million metric tons of CO2(5), 70% of which was from transportation and producing electricity from burning coal and fossil fuels. The most effective way to reduce CO2 emissions is to reduce fossil fuel consumption(1).
An effective way to observe the warming effect from carbon dioxide is to analyze the ocean temperature anomalies. These temperature anomalies are a good indicator of global average temperatures because the water has a high heat index and does not change without a lot of heat input(2). Looking at the temperature anomalies through time is the best option because the records are more reliable than actual temperature records. A temperature anomaly is the difference between the expected average temperature and the actual temperature. Rising ocean temperatures lead to higher sea levels and have a strong effect on the climate and environment of certain areas. Higher ocean temperatures lead to stronger ocean storms and can destabilize marine habitats by aiding in the spread of invasive species and marine diseases(2). The ocean temperature anomalies combined with carbon dioxide data should show a significant correlation
A specific affect of increasing temperatures could be an increase of wildfire severity. It is not a direct cause and effect relationship, but there are many ways that the changing climate is affecting wildfires. Fire seasons are becoming longer, conditions are becoming drier making for more fuel for fires, and there is an increase in lightning(3). Wild fires have a very important role in nature. The fires return nutrients to the soil by burning dead or dying plants. Wildfires can troublesome when they infringe on populated areas. If this happens, the wildfires threaten the lives and property of the residents and firefighters. In the past, there has been an average of more than 100,000 wildfires which burn 4 to 5 million acres of U.S. land during a given year. Recently that average has peaked at 9 million acres(4). In addition, the overall area burned by fires per year in the United States is projected to double by late this century, if the average summertime temperature increases by a mere 2.9 degrees F(3).
Is there a strong correlation between the carbon dioxide levels in the atmosphere and the temperature anomalies in the ocean? If there is a significant correlation, how does it relate to the severity of wildfires within the US?
The main objective of this project is to prove that climate change does exist, and show that increased concentrations of carbon dioxide does increase the temperature of the Earth. The increase in temperatures will be proven using temperature anomaly data of the ocean. With these two data sets in mind, the actual effect on the climate change will be shown using wildfire data. The correlation between the increase in carbon dioxide and the ocean temperature anomalies will follow along the same trend line as the severity of wildfires. A secondary objective is to show this correlation using data from more recent sources. It is important for the purposes of this project to stick to data that is less than 150 years old. This is to show that the climate change is modern occurrence, rather than a long term trend.
The data used in this project is more modern compared to the scope of time that climate change occurs over. The oldest data set used dates back to the late 1800s. This is because the data used consists of modern recordings of the various data types. An alternative to this would be exploring data in ice-cores. Data in ice cores goes back thousands of years, and could possibly show a larger picture of the climate cycle. This approach was not used because one of the main objectives is to show the correlation is a modern trend.
This project also had a lot of options in terms of looking at data of the responding variables to the increase in carbon dioxide. Rather than use wildfires as the indication of climate change, the project could have been based around the melting of ice sheets, rising ocean levels, or even reduced snowfall in the mountains. Wildfire severity was chosen because it has a more abstract application, and it should increase as the climate gets warmer and drier, showing more correlation back to climate change.
This project covers a broad range of subjects, and finding data for all of the subjects can be difficult. This was the main restriction on the project. For example, there are only two data sets to use for the wildfire data. However, the carbon dioxide data was the easiest to access because it is kept by the EPA on their .gov site. This means that the data is free to use, and is open access. The other sets of data did not have the same advantages.
The other main restriction was the time that the group had to work. Climate change a very broad issue with many different datasets from around the world. Exploring every avenue was simply not possible, so the workload was fine-tuned and filed down to a reasonable level for a three week project. This was also the hardest boundary to deal with, because it is very easy to go over board when gathering information, and figuring out what is actually useful is difficult.
Finding and downloading all of the data necessary took a lot of time and effort. When the project was in its initial workings, it was required that possible locations for data were recorded. So, the research for data started with those websites and locations.
The carbon dioxide was found on the website originally recorded. NOAA holds data on carbon dioxide concentrations from around the world. The data was taken from locations like the Black Sea, Barrow, and Guam. By taking the data from such varied locations, it gives a better world perspective on how much the carbon dioxide concentrations are changing.
The data acquired for the carbon dioxide analysis came from flask data sets. Flask data is taken by scientists who know the volume of the flask, and then do certain tests on the volume of air to determine what the concentration is in parts per million. Collecting this type of data was consistent across all of the sets. There were multiple options to choose from that were not specifically flask data.
The last parameter used when gathering the carbon dioxide data was to make sure the data was up to date. This was not extremely difficult to do thanks to NOAA’s filtering options. When looking for data an option was chosen that the data sets had to have been updated within the last 365 days. This means that all of the data sets have measurements within the last year, or slightly longer. It appeared that updating the data did not always mean adding new points in. The worst data set, in terms of new data, had its newest data point as the end of 2012.