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Gauging the Tides of Climate Change

February 11, 2020

When scientists or politicians begin to talk about climate change, most people become scared by the severity of the issue at hand, thinking there’s not a lot left for us to do. This fear-mongering tactic typically discourages individual actions like recycling or moving away from meat-focused diets. Scientists surely don’t want to scare the public with the truth, but the fact of the matter is that if we don’t do something now, our generation and all generations to follow will not have a safe or even comfortable planet to live on. This leads us to the question: what exactly can we do to prepare for and mitigate the coming decades of destruction and chaos? 

The first step to approaching the threat of climate change is to understand the impact we’re facing. To do so, we consider contributing factors in their current capacity that are predicted to change; by observing these patterns early on, it will be easier to assess the risk to infrastructure and communities. Variables that have the capability to become dangerous in the future include global sea level, atmospheric temperatures, ocean acidification, and glacial stability [4, 6]. The severity of predicted impact depends on the response of all of these variables to atmospheric carbon dioxide and other pollutant levels that have already increased global temperature. Scientists anticipate a 68% likelihood of 1-4 feet of sea level rise as a result, with 10 feet being the worst case scenario [1, 4]. With these predictions come the growing probability of worse hurricane seasons due to increased storm surge and extreme precipitation [4]. Even now we see worsening severity of weather events compared to 20 years prior and flooding during high tides in areas below sea level [1].

GMSL vs time
Global mean sea level since 1880 using tide gauge data from global PSMSL data base.

Conveniently, scientists have been monitoring sea level globally for nearly 200 years. However, gauging sea level is a bit more difficult than sticking a ruler somewhere on the coast and guessing the relative position over time. In 1807, Thomas Jefferson ordered a systematic survey utilizing “tide staffs”, or long poles that researchers used to compare sea level with a fixed point on nearby land [2]. It wasn’t until 1851 that the US coast guard implemented self recording tide gauges, but the device was still difficult to maintain and expensive to install [2]. Today’s advanced technology records the sea surface height via radar, or microwaves, with respect to the position of the gauge above the water. These gauges are a step up from acoustic gauges that must be protected from inclement weather, and cost upwards of $1300 [1, 2]. Although we have about 200 years of global sea level data, moving onto more reliable and cost efficient methods of measuring current and future sea level change is necessary for any chance of adaptation.

 

Dr. Kim Cobb and Dr. Russ Clark of Georgia Tech have spearheaded a project as a key initiative of the Global Change Program to provide low-cost tide gauges for Georgia coastlines. The Smart Sea Level venture is focused on particularly high risk regions, such as Chatham county. These $300 devices currently measure the relative sea level, air temperature, and barometric pressure, with planned capabilities to observe ocean properties, air quality, and inland flooding [5]. The smart sea level sensors use the roundtrip travel time of ultrasonic waves to measure the distance from the sensor to the water level. They log measurements every ten minutes, enabling their batteries to last one year or longer [5]. Already Georgia Tech scientists and collaborators can simulate tides, hurricanes, and extreme weather events via 43 strategically placed sensors [1, 5]. With this data, we’re moving towards predicting the flood patterns linked to severe weather events as atmospheric temperatures and sea levels continue to rise.  

tide gauge kim cobb
Smart Sea Level tide gauge adapted from Russ Clark of Georgia Tech.

As storm surge severity increases, so does the compounded risk of damaging communities beyond repair, which is the true threat of forthcoming extreme weather events. Many low income areas don’t have the resources to assist with evacuation or the infrastructure resilient enough to survive mass flooding. The smart sea level sensor project has led to close collaboration with these communities to provide information on the regions they’re most concerned with: air quality, temperature changes, and the future safety of family neighborhoods and K-12 school grounds [1]. Already the team has joined up with H. V. Jenkins School and Oglethorpe Charter Middle School [7] to recruit volunteers for engineering and installation, and test a climate literacy curriculum, respectively.

Now the question is to ask, what’s left to do? My personal answer would be to riot and do all we can to support this initiative, but that seems a little drastic. Increasing educational partnerships with high schools and elementary programs would improve awareness amongst the younger generations who are bound to be affected more by climate related concerns. Furthermore, getting into contact with legislators, particularly within the Georgia General Assembly would provide useful in terms of allocating funds towards this cause. With legislators on board, it’s possible legal action could be taken to prevent further damage towards vulnerable communities in areas like Chatham County. Programs such as incentivizing corporate relocation or the mitigation of current industrial hazards, could go a long way in establishing baselines for future climate change strategy. While most legislation to be passed will need to be from within the county, or even at the state level , it wouldn’t hurt to reach national recognition. By promoting climate literacy across the United States, we can increase the number of volunteers assisting with future adaptation, and motivate Congress to aid in the process of protecting these at risk communities [8].  

If you’re interested in supporting this cause, check out the following volunteer and educational opportunities:

References:

  1. Cobb, K. (2019, January 24). Smart Sea Level Sensors – Chatham County. Retrieved from http://smartcities.gatech.edu/sites/default/files/GA-Smart-Webinar_Smart-Sea-Level-Sensors_1-24-2019.pdf
  2. Dusto, A. (2014, August 4). Reading between the tides: 200 years of measuring global sea level: NOAA Climate.gov. Retrieved from https://www.climate.gov/news-features/climate-tech/reading-between-tides-200-years-measuring-global-sea-level
  3. Georgia, S. (n.d.). Office of Sustainability. Retrieved from https://www.savannahga.gov/507/Office-of-Sustainability
  4. Lindsey, R. (2019, November 19). Climate Change: Global Sea Level: NOAA Climate.gov. Retrieved from https://www.climate.gov/news-features/understanding-climate/climate-change-global-sea-level
  5. Matthews, R., Cobb, K., & Clark, R. (2019). FAQ. Retrieved from https://www.sealevelsensors.org/faq/
  6. Ocean Acidification. (n.d.). Retrieved from https://www.noaa.gov/education/resource-collections/ocean-coasts-education-resources/ocean-acidification
  7. Jarvis, K. (2019, May 16). Smart Sea Sensors Expo Highlights Accomplishments and Shares Future Plans. Retrieved from https://www.news.gatech.edu/2019/05/16/smart-sea-sensors-expo-highlights-accomplishments-and-shares-future-plans
  8. US Department of Commerce, & National Oceanic and Atmospheric Administration. (2005, December 19). NOS Education Offering. Retrieved from https://oceanservice.noaa.gov/education/literacy.html
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About Author

Vivian is a 4th year AstroPhysics major at Georgia Tech. They draw landscapes and cartoons in their free time, in addition to playing with environmental data and critiquing the scientific legitimacy of science fiction movies.

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.