The Socioeconomic Impacts of Natural Disasters on the United States
Kelci Gilot
2019-03-14
Data Collection and Tidying
I used a variety of packages including tidyverse, dplyr, and plotly. Initially I loaded in as many as I thought I might need, then narrowed it down to only the ones I ended up using.
## -- Attaching packages --------------------------------------- tidyverse 1.2.1 --## v ggplot2 3.1.0 v purrr 0.2.5
## v tibble 2.0.1 v dplyr 0.8.0.1
## v tidyr 0.8.2 v stringr 1.3.1
## v readr 1.3.1 v forcats 0.3.0## Warning: package 'tibble' was built under R version 3.5.3## Warning: package 'dplyr' was built under R version 3.5.3## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
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## layoutThese are the four data sets I used for my project. Two of them I created myself in excel and the other two were downloaded directly from the NOAA website. I then put them into excel to be able to manipulate them the way I wanted in R.
disaster_data <- read_csv("./Data/Billion_Dollar_Disasters_Data - Sheet1.csv", skip = 1) #NOAA website## Parsed with column specification:
## cols(
## Year = col_double(),
## `Drought Count` = col_double(),
## `Drought Cost` = col_double(),
## `Flooding Count` = col_double(),
## `Flooding Cost` = col_double(),
## `Freeze Count` = col_double(),
## `Freeze Cost` = col_double(),
## `Severe Storm Count` = col_double(),
## `Severe Storm Cost` = col_double(),
## `Tropical Cyclone Count` = col_double(),
## `Tropical Cyclone Cost` = col_double(),
## `Wildfire Count` = col_double(),
## `Wildfire Cost` = col_double(),
## `Winter Storm Count` = col_double(),
## `Winter Storm Cost` = col_double()
## )costliest_cyclones <- read_csv("./Data/Costliest_US_Tropical_Cyclones - Sheet1.csv") # NOAA data compiled by me## Parsed with column specification:
## cols(
## Rank = col_double(),
## `Tropical Cyclone` = col_character(),
## Year = col_double(),
## Category = col_double(),
## `Damage in Billions (U.S.)` = col_double(),
## `Regions Impacted` = col_character()
## )wildfire_data <- read_csv("./Data/Wildfire_data - Sheet1.csv", skip = 1) # NOAA website## Parsed with column specification:
## cols(
## Date = col_double(),
## `Number of Fires` = col_number(),
## `Acres Burned` = col_number(),
## `Acres Burned per Fire` = col_double()
## )Year_count <- read.csv("./Data/Year_count - Sheet1.csv") # NOAA data compiled by me
The wildfire data from NOAA had the date set up so the year and month were squished together as one long 6 character number. I used the apply function to separate them into two different columns.
wildfire_data$Year <- sapply(wildfire_data$Date, substr, start = 1, stop =4) # extracting the first four digits which represented the yearwildfire_data$Month <- sapply(wildfire_data$Date, substr, start = 5, stop = 6) # extracting the last two digits which reresented the month
I made the original date column NULL so it wouldn’t be identifiable and interfere with the data I actually wanted from the data frame.
wildfire_data$Date <- NULL
Originally my data had a column for each individual disaster count and cost. I wanted to be able to group my data by disaster so I made two new data frames with the data fro cost and event in one and count per event in another.
col_index <- seq(2, 14, by = 2)
col_to_gather <- colnames(disaster_data)[col_index] # pulling out the event counts
col_index2 <- seq(3, 15, by = 2)
col_to_gather2 <- colnames(disaster_data)[col_index2] # pulling out the event costsevent_time_series <- gather(disaster_data, key = Event_type, value = Event_count, col_to_gather) %>%
select(Year,Event_type, Event_count) # creating a new data frame with just year, event type, and countcost_series <- gather(disaster_data, key = Event_type, value = Event_cost, col_to_gather2) %>%
select(Year, Event_type, Event_cost) # creating a new data frame with just year, event type, and cost
Within these two data frames the terms “cost” and “count” were sill attached to the event type which meant I couldn’t join them.
event_time_series %>% separate(Event_type, c("Event_Name", "Extra")) # separating the event from the extra term, in this case count## Warning: Expected 2 pieces. Additional pieces discarded in 117 rows [118,
## 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133,
## 134, 135, 136, 137, ...].cost_series %>% separate(Event_type, c("Event_type", "Extra")) # separating the event from the extra term, cost## Warning: Expected 2 pieces. Additional pieces discarded in 117 rows [118,
## 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133,
## 134, 135, 136, 137, ...].
I replaced the words count and cost with blank space.
event_time_series$Event_type <- str_replace(event_time_series$Event_type, "Count", "") # replacing the term countcost_series$Event_type <- str_replace(cost_series$Event_type, "Cost", "") # replacing the term cost
I used left_join to merge the data frames and create what was my main data frame.
disaster_data_merged <- left_join(event_time_series, cost_series) # joining the two data frames ## Joining, by = c("Year", "Event_type")
Climate Change and Natural Disasters
Natural disasters have been ravaging the planet for as long as it has been around. They have become part of the natural order of ecosystems and in some cases are necessary for organisms survival. But for humans they can be devastating. While plants and animals may be accustomed to change, when change strikes humans we panic as our lives are thrown out of balance. These natural disasters can destroy homes and lives, but they are simply a part of the balance of the Earth. We are the ones causing change in the first place, who then end up suffering and not taking responsibility for our actions. The looming threat of climate change is not as far off as people believe. It is here and now, sweeping away cars in the storm surge and burning up forests in wildfires. Some say it may be too late, but it is never too late to change our ways. The United States has spent $500 billion dollars on disaster damage clean up in the last five years (NOAA). We can continue to pay exuberant amounts of money to clean up messes we could have attempted to mitigate in the first place, or we can do something about climate change before whole communities and valuable infrastructure are lost to flooding or wildfires.
As our climate has changed the natural disasters we experience have changed too. Some have become more frequent and many have become more intense. Fewer tropical cyclones are doing more damage than a series of smaller storms would. While there are not necessarily more fires burning, more acres of land are being burned. We can see that both the number of natural disaster events has risen along with the cost due to damage. Since 2000 tropical cyclones have become more abundant in the Atlantic ocean and with them come big clean up bills. The disaster with the greatest increase in abundance are severe storms, which NOAA describes as a storm that has wind gusts of 85 mph or above and/or hail that is at least one inch in diameter or one that involves a tornado.
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
Billions Upon Billions
The average natural disaster costs $6.9 billion. In 2018 alone there were 14 billion-dollar disaster events which cost $91 billion in total (NOAA). From 1980 to 2017 topical cyclones have cost the most in damages at $919.7 billion. They also have the highest average event cost at $21.9 billion. All costs are CPI adjusted.
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
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## parametric, : zero-width neighborhood. make span bigger## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
The United States spends billions of dollars on natural disasters and if we continue to do nothing about climate change we will only be spending more in the future. In the long run if we put a stop to anthropocentric means of increasing climate change through things like control of CO2 emissions we will save money. We won’t have to pay for as many repairs if people didn’t build in certain places in the first place. Their homes would be up to code with hurricane standards. That means houses raised on stilts and hurricane proof windows, and also the knowledge that beachfront property isn’t entirely safe. People want to live on the beach but strong storms also bring erosion which can destroy their homes foundations. The very ground they live on is being taken out from under them. Homes need to be lifted and moved back, but around 40% of Americans live on the coast and there isn’t necessarily much room to spare. People can’t simply move their homes back in most cases, they would run out of property as the decades go by.
Frequency
From 1980 when NOAA first started keeping track of these billion-dollar disasters to present day the US has seen 215 disasters in total and an average of 6.2 a year. In the last five years that average jumped up to 12.6 events. 2017 and 2011 are tied with the most events at 16. Severe storms are the most frequent, occurring 103 times in the past four decades. Tropical cyclones and flooding are the next most frequent disasters.
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
Overall there is an increase in the number of disasters across the country, a steady one that doesn’t appear to be leveling out anytime soon. We need to take caution after observing this pattern and realize that these events are not going to be stopping. People need to learn to take them seriously and be better prepared. There is certainly no lack of warning to the public when an event is anticipated, but the public needs to step up and be ready to take action themselves and not wait for others to do so for them. After a while these things will become more and more common place and people will have no one to blame but themselves for not being informed and prepared.
Tropical Cyclones
NOAA describes tropical cyclones as “rotating, organized system of clouds and thunderstorms that originates over tropical or subtropical waters and has closed, low-level circulation.” Hurricanes and typhoons fall under this umbrella term.
Of the past 10 most costly tropical cyclones, 9 have happened in the 21st century and 3 in the past two years. Atlantic hurricane activity has grow in both intensity and frequency. Some of the most destructive storms are not even those that are high categories. None of the top five costliest storms were category fives, the highest possible category on the Saffir-Simpson scale based on wind speeds. Number four is even a category one. These storms wreak their havoc in the form of powerful storm surges and copious amount of precipitation which both cause immense flooding. Sea level rise due to climate change ensures that storm surges will reach even further inland.
From this figure we see tropical cyclones do not need to be high categories to cause severe damage. They just need the right conditions, which are made possible with the help of rising sea surface temperatures. Tropical cyclones are fuel by warm waters and moist air so our warming oceans act as an energy source to further fuel storms.
One of the most destructive aspects of storms are the storm surges, which do not depend on wind speed. They are why storms like Katrina and Sandy were so devastating. Flooding wipes out infrastructure and kills more people than wind does.
Wildfires
With the warmer temperatures brought on by climate change, parts of the country have had warmer winters. Warmer winters means less snow pack accumulates in the mountains and less water is available in the spring and summer to places like California. As summer droughts get worse, potential for wildfires to start and spread highten (Popovich and Pierre-Louis 2018). The environment of states like California becomes more flammable when it is dry. Four out of five wildfires are start by humans (Barron and Gajana 2018).
The number of fires can be seen to vary month to month due to seasonal trends. Wildfire occurrences start increasing in June and remain high until September. For some years they have remained high all year round. 
While there haven’t necessarily been a greater number of wildfires in the United States, the ones we have had have been consistently more destructive. More acres of land are being burned in these less frequent fires. 
Just as wildfires are being impacted by climate change they are also contributing to it. When the forest are burned they are releasing carbon dioxide into the atmosphere, contributing to the Green House Effect. If forests continue to burn like they are they will be emitting more carbon into the atmosphere than they are taking in. The number of forests rebounding after wildfires in California has declined as well (Popovich and Pierre-Louis 2018).
Conclusion
The National Climate Assessment wrote “Some extreme weather and climate events have increased in recent decades, and new and stronger evidence confirms that some of these increases are related to human activities.” Anthropocentric climate change is providing fuel to make natural disasters more destructive than ever before. The frequency of specific events may not change as drastically as others, but overall we are and will be experiencing more natural disasters. The cost of disasters is likely to go up in the coming decades. The destruction behind these incidents is likely to increase as well. Which means more homes lost, people displaced, and lives ruined.
If we want to mitigate damage at local levels information such as this needs to be better conveyed to the public. It is not as if it is poorly done now, but the public themselves need to step up and understand that this is a problem that affects everyone in the country. No matter where a person lives they are susceptible to at east one of these disasters. Wildfires are not just a problem for the southwest, if trends continue then they could move east. Those that are inland may not worry about flooding during a severe storm or tropical cyclone, but as there is more erosion and sea level rise it can creep on on them. Those on the coast will have property under water and their infrastructure will lose value. Building infrastructure up to code with hurricane standards and not directly on the coast can help to mitigate losses. If we take action now then we will end up paying less later on. The country won’t keep having to spend billions and billions of dollars each year to clean up if we do things to slow climate change now.
References
NOAA National Centers for Environmental Information (NCEI) U.S. Billion-Dollar Weather and Climate Disasters 2019. https://www.ncdc.noaa.gov/billions/
NOAA National Hurricane Center. “Costliest U.S. Tropical Cyclones.” 2018. https://www.nhc.noaa.gov/news/UpdatedCostliest.pdf
Pierre-Louis, Kendra and Popovich, Nadja. “Climate Change Is Fueling Wildfires Nationwide, New Report Warns.” The New York Times. 2018. https://www.nytimes.com/interactive/2018/11/27/climate/wildfire-global-warming.html
Mooney, Chris and Dennis, Brady. “Extreme hurricanes and wildfires made 2017 the most costly U.S. disaster year on record.” The Washington Post. 2018. https://www.washingtonpost.com/news/energy-environment/wp/2018/01/08/hurricanes-wildfires-made-2017-the-most-costly-u-s-disaster-year-on-record/?noredirect=on&utm_term=.09562659624b
U.S. Global Chnage Research Program. “Extreme Weather.” National Climate Assessment. 2018. https://nca2014.globalchange.gov/highlights/report-findings/extreme-weather#tab2-images