Evaluation of the impact of severe weather events on population health and economy
Melanie
2024-05-03
1. Synopsis
The US National Oceanic and Atmospheric Administration (NOAA) has established a database recording storm events and the impact on population and infrastructures since 1950 in the United States. We can use this database to determine which events are the most harmful on population or have the greatest economic impact. Since the data collection methods have changed over the time, we have focused our analysis from January 2001 to end of 2011. We first evaluate the evolution of impact on population and economy consequences over the time by focusing on 6 variables (“injuries”, “fatalities”, “CROPDMG” and “CROPDMGEXP”, “PROPDMG” and “PROPDMGEXP”). To assess which events were the most harmful on population health, we calculated the total number of persons injured or killed since 2001 for each of the 48 events. We processed the same way to evaluate the economical consequences on properties and crops.
2. Data processing
We download the file using the link provided in the instructions page:
if(!file.exists("StormData.csv.bz2")){
download.file("https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2", "StormData.csv.bz2")}
data <- read.csv("StormData.csv.bz2")
## The following libraries are loaded
library(dplyr)
library(stringr)
library(stringdist)
library(lubridate)
library(ggplot2)
library(reshape2)
library(gridExtra)
library(forcats)We first evaluate the content of the dataset:
str(data)## 'data.frame': 902297 obs. of 37 variables:
## $ STATE__ : num 1 1 1 1 1 1 1 1 1 1 ...
## $ BGN_DATE : chr "4/18/1950 0:00:00" "4/18/1950 0:00:00" "2/20/1951 0:00:00" "6/8/1951 0:00:00" ...
## $ BGN_TIME : chr "0130" "0145" "1600" "0900" ...
## $ TIME_ZONE : chr "CST" "CST" "CST" "CST" ...
## $ COUNTY : num 97 3 57 89 43 77 9 123 125 57 ...
## $ COUNTYNAME: chr "MOBILE" "BALDWIN" "FAYETTE" "MADISON" ...
## $ STATE : chr "AL" "AL" "AL" "AL" ...
## $ EVTYPE : chr "TORNADO" "TORNADO" "TORNADO" "TORNADO" ...
## $ BGN_RANGE : num 0 0 0 0 0 0 0 0 0 0 ...
## $ BGN_AZI : chr "" "" "" "" ...
## $ BGN_LOCATI: chr "" "" "" "" ...
## $ END_DATE : chr "" "" "" "" ...
## $ END_TIME : chr "" "" "" "" ...
## $ COUNTY_END: num 0 0 0 0 0 0 0 0 0 0 ...
## $ COUNTYENDN: logi NA NA NA NA NA NA ...
## $ END_RANGE : num 0 0 0 0 0 0 0 0 0 0 ...
## $ END_AZI : chr "" "" "" "" ...
## $ END_LOCATI: chr "" "" "" "" ...
## $ LENGTH : num 14 2 0.1 0 0 1.5 1.5 0 3.3 2.3 ...
## $ WIDTH : num 100 150 123 100 150 177 33 33 100 100 ...
## $ F : int 3 2 2 2 2 2 2 1 3 3 ...
## $ MAG : num 0 0 0 0 0 0 0 0 0 0 ...
## $ FATALITIES: num 0 0 0 0 0 0 0 0 1 0 ...
## $ INJURIES : num 15 0 2 2 2 6 1 0 14 0 ...
## $ PROPDMG : num 25 2.5 25 2.5 2.5 2.5 2.5 2.5 25 25 ...
## $ PROPDMGEXP: chr "K" "K" "K" "K" ...
## $ CROPDMG : num 0 0 0 0 0 0 0 0 0 0 ...
## $ CROPDMGEXP: chr "" "" "" "" ...
## $ WFO : chr "" "" "" "" ...
## $ STATEOFFIC: chr "" "" "" "" ...
## $ ZONENAMES : chr "" "" "" "" ...
## $ LATITUDE : num 3040 3042 3340 3458 3412 ...
## $ LONGITUDE : num 8812 8755 8742 8626 8642 ...
## $ LATITUDE_E: num 3051 0 0 0 0 ...
## $ LONGITUDE_: num 8806 0 0 0 0 ...
## $ REMARKS : chr "" "" "" "" ...
## $ REFNUM : num 1 2 3 4 5 6 7 8 9 10 ...We will adopt a strategy in 3 parts to clean the dataset:
1. Select the columns and rows of interest
2. Clean the “EVTYPE” column
3. Handle the exponent values for crops and properties
2.1. Select the columns and rows of interest
For the purpose of the study, we only need a couple of variables: STATE (not particularly needed but nice to have), DATE (to select rows based on date), EVTYPE (the type of events), FATALITIES, INJURIES (fatalities and injuries to respond to the question about the harmfulness of the event), PROPDMG, PROPDMGEXP, CROPDMG, CROPDMGEXP (these additional variables to measure the damages on properties and crops).
data[c("DATE", "TIME")] <- str_split_fixed(data$BGN_DATE, " ", 2) # to split time and date into 2 columns
data_tidy <- data %>% # to select only certain column and create a new dataset
select(STATE, DATE, EVTYPE, FATALITIES, INJURIES, PROPDMG, PROPDMGEXP, CROPDMG, CROPDMGEXP)
data_tidy$DATE <- mdy(data_tidy$DATE)We got a new dataset called “data_tidy” with 9 variables only and data since 1950, when the first events are recorded. We can now check the number of events measured.
str(unique(data_tidy$EVTYPE))## chr [1:985] "TORNADO" "TSTM WIND" "HAIL" "FREEZING RAIN" "SNOW" ...We get a large list of events. According to the NOAA website https://www.ncdc.noaa.gov/stormevents/details.jsp all events were only recorded from 1996, but standardization of the events did not happen before 2000 when a drop-down selector for Event Type on the data entry interface was included https://www.ncdc.noaa.gov/stormevents/details.jsp?type=collection. Hence, it will be more advised to filter the events prior to 2000. We can start our selection from January 2001 to make sure this standardization has been properly implemented.
data_tidy <- with(data_tidy, data_tidy[(DATE >= "2001-01-01"), ]) # select data from January 2001
unique(data_tidy$EVTYPE) # to check the number of unique events recorded## [1] "TSTM WIND" "HAIL"
## [3] "TORNADO" "FLASH FLOOD"
## [5] "HIGH WIND" "FLOOD"
## [7] "WILD/FOREST FIRE" "WINTER STORM"
## [9] "EXCESSIVE HEAT" "LIGHTNING"
## [11] "FUNNEL CLOUD" "HEAVY SNOW"
## [13] "EXTREME COLD" "WATERSPOUT"
## [15] "COASTAL FLOODING" "TROPICAL STORM"
## [17] "TSTM WIND/HAIL" "HEAVY RAIN"
## [19] "RIP CURRENTS" "HEAVY SURF"
## [21] "AVALANCHE" "EXTREME WINDCHILL"
## [23] "BLIZZARD" "ICE STORM"
## [25] "VOLCANIC ASH" "LATE SEASON SNOW"
## [27] "FOG" "URBAN/SML STREAM FLD"
## [29] "DUST STORM" "WIND DAMAGE"
## [31] "DRY" "FROST"
## [33] "STORM SURGE" "SNOW"
## [35] "WIND" "FREEZE"
## [37] "WINTER WEATHER" "GUSTY LAKE WIND"
## [39] "ABNORMALLY DRY" "SMALL HAIL"
## [41] "WINTER WEATHER MIX" "THUNDERSTORM"
## [43] "DUST DEVIL" "RED FLAG CRITERIA"
## [45] "MUD SLIDE" "THUNDERSTORMS"
## [47] "RAIN" "WND"
## [49] "DRY MICROBURST" "FREEZING RAIN"
## [51] "STRONG WIND" "RECORD HEAT"
## [53] "RECORD COLD" "BLACK ICE"
## [55] "WINTRY MIX" "CSTL FLOODING/EROSION"
## [57] "UNSEASONABLY DRY" "UNSEASONABLY HOT"
## [59] "UNSEASONABLY COOL" "UNSEASONABLY WARM"
## [61] "DROUGHT" "SMOKE"
## [63] " WATERSPOUT" "HIGH SURF"
## [65] "SNOW ADVISORY" "WIND ADVISORY"
## [67] "HURRICANE" "LIGHT SNOW"
## [69] "EXTREMELY WET" "SNOW/SLEET"
## [71] "UNUSUALLY LATE SNOW" "UNSEASONABLY COLD"
## [73] "VERY DRY" "RECORD LOW RAINFALL"
## [75] "ROGUE WAVE" "SNOW/FREEZING RAIN"
## [77] "SNOW/BLOWING SNOW" "SNOWMELT FLOODING"
## [79] "GRADIENT WIND" "LANDSLIDE"
## [81] "RECORD WARMTH" "PROLONG COLD"
## [83] "MONTHLY PRECIPITATION" "COLD"
## [85] "PROLONG WARMTH" "STRONG WINDS"
## [87] "MODERATE SNOWFALL" "MIXED PRECIPITATION"
## [89] "EXTREME WINDCHILL TEMPERATURES" "ACCUMULATED SNOWFALL"
## [91] "FALLING SNOW/ICE" "DRY CONDITIONS"
## [93] "DUST DEVEL" "NON-TSTM WIND"
## [95] "NON TSTM WIND" "MUDSLIDE"
## [97] "OTHER" "LAKE EFFECT SNOW"
## [99] "DRY SPELL" "BRUSH FIRE"
## [101] "GUSTY WINDS" "GUSTY THUNDERSTORM WINDS"
## [103] "BEACH EROSION" "ROUGH SEAS"
## [105] "LIGHT FREEZING RAIN" "DENSE FOG"
## [107] "PATCHY ICE" "SNOW SHOWERS"
## [109] "HEAVY RAIN EFFECTS" "HEAT"
## [111] "BLOWING DUST" "SNOW DROUGHT"
## [113] "GUSTY WIND" "FUNNEL CLOUDS"
## [115] "SEVERE THUNDERSTORMS" "EXCESSIVE HEAT/DROUGHT"
## [117] "HIGH WATER" "NORTHERN LIGHTS"
## [119] "MARINE TSTM WIND" " HIGH SURF ADVISORY"
## [121] "HIGH SURF ADVISORY" "HIGH SEAS"
## [123] "WIND CHILL" "HAZARDOUS SURF"
## [125] "WILDFIRE" "FROST/FREEZE"
## [127] "WINTER WEATHER/MIX" "ASTRONOMICAL HIGH TIDE"
## [129] "COLD WEATHER" "HARD FREEZE"
## [131] "WHIRLWIND" "VERY WARM"
## [133] "ABNORMALLY WET" "UNUSUALLY COLD"
## [135] "COASTAL FLOOD" "TORNADO DEBRIS"
## [137] "EXTREME COLD/WIND CHILL" "ICE ON ROAD"
## [139] "EARLY SNOWFALL" "FREEZING DRIZZLE"
## [141] "FIRST SNOW" "SNOW SQUALLS"
## [143] "SEICHE" "ICY ROADS"
## [145] "ICE/SNOW" "DROWNING"
## [147] "GUSTY THUNDERSTORM WIND" "MARINE HAIL"
## [149] "HIGH SURF ADVISORIES" "RIP CURRENT"
## [151] "HURRICANE/TYPHOON" "HEAVY SURF/HIGH SURF"
## [153] "TROPICAL DEPRESSION" "SLEET STORM"
## [155] "COLD WIND CHILL TEMPERATURES" "STORM SURGE/TIDE"
## [157] "FREEZING FOG" "COLD/WIND CHILL"
## [159] "LAKE-EFFECT SNOW" "MARINE HIGH WIND"
## [161] "THUNDERSTORM WIND" "TSUNAMI"
## [163] "SLEET" "DENSE SMOKE"
## [165] "LAKESHORE FLOOD" "MARINE THUNDERSTORM WIND"
## [167] "MARINE STRONG WIND" "ASTRONOMICAL LOW TIDE"
## [169] "VOLCANIC ASHFALL"We can see that more than 48 events were recorded. So we need to clean the dataset and rename when necessary the events to narrow done to the 48 events.
2.2. Clean the “EVTYPE” column
To get the list of the 48 events, we generate a list based on the dataset from October 2006 when the NWS switched from Paradox to Windows SQL Server.
events <- c(unique(with(data_tidy, data_tidy[(DATE >= "2006-11-01"),3])))
print(events)## [1] "BLIZZARD" "HIGH WIND"
## [3] "HEAVY SNOW" "THUNDERSTORM WIND"
## [5] "TORNADO" "FLASH FLOOD"
## [7] "HAIL" "FUNNEL CLOUD"
## [9] "DENSE FOG" "WINTER WEATHER"
## [11] "FLOOD" "WINTER STORM"
## [13] "STRONG WIND" "HEAVY RAIN"
## [15] "TSUNAMI" "WILDFIRE"
## [17] "FROST/FREEZE" "HEAT"
## [19] "DUST STORM" "HIGH SURF"
## [21] "LIGHTNING" "DROUGHT"
## [23] "LANDSLIDE" "AVALANCHE"
## [25] "COASTAL FLOOD" "EXTREME COLD/WIND CHILL"
## [27] "RIP CURRENT" "SLEET"
## [29] "LAKE-EFFECT SNOW" "ICE STORM"
## [31] "FREEZING FOG" "SEICHE"
## [33] "COLD/WIND CHILL" "WATERSPOUT"
## [35] "MARINE THUNDERSTORM WIND" "MARINE HAIL"
## [37] "MARINE STRONG WIND" "DUST DEVIL"
## [39] "ASTRONOMICAL LOW TIDE" "STORM SURGE/TIDE"
## [41] "EXCESSIVE HEAT" "DENSE SMOKE"
## [43] "TROPICAL STORM" "TROPICAL DEPRESSION"
## [45] "HURRICANE" "LAKESHORE FLOOD"
## [47] "MARINE HIGH WIND" "VOLCANIC ASHFALL"We can split the “data_tidy” dataset in two, between the data matching the 48 events and the one where events are recorded differently. We will call this dataset “data_toclean”.
data_toclean <- data_tidy %>% filter(!EVTYPE %in% events) # create a new dataset with the data to clean
data_tidy <- data_tidy %>% filter(EVTYPE %in% events) # remove the data that need cleaningAmong the 488,692 initial observations, we have 83,968 observations to clean. Let’s have a look at the events to clean:
unique(data_toclean$EVTYPE)## [1] "TSTM WIND" "WILD/FOREST FIRE"
## [3] "EXTREME COLD" "COASTAL FLOODING"
## [5] "TSTM WIND/HAIL" "RIP CURRENTS"
## [7] "HEAVY SURF" "EXTREME WINDCHILL"
## [9] "VOLCANIC ASH" "LATE SEASON SNOW"
## [11] "FOG" "URBAN/SML STREAM FLD"
## [13] "WIND DAMAGE" "DRY"
## [15] "FROST" "STORM SURGE"
## [17] "SNOW" "WIND"
## [19] "FREEZE" "GUSTY LAKE WIND"
## [21] "ABNORMALLY DRY" "SMALL HAIL"
## [23] "WINTER WEATHER MIX" "THUNDERSTORM"
## [25] "RED FLAG CRITERIA" "MUD SLIDE"
## [27] "THUNDERSTORMS" "RAIN"
## [29] "WND" "DRY MICROBURST"
## [31] "FREEZING RAIN" "RECORD HEAT"
## [33] "RECORD COLD" "BLACK ICE"
## [35] "WINTRY MIX" "CSTL FLOODING/EROSION"
## [37] "UNSEASONABLY DRY" "UNSEASONABLY HOT"
## [39] "UNSEASONABLY COOL" "UNSEASONABLY WARM"
## [41] "SMOKE" " WATERSPOUT"
## [43] "SNOW ADVISORY" "WIND ADVISORY"
## [45] "LIGHT SNOW" "EXTREMELY WET"
## [47] "SNOW/SLEET" "UNUSUALLY LATE SNOW"
## [49] "UNSEASONABLY COLD" "VERY DRY"
## [51] "RECORD LOW RAINFALL" "ROGUE WAVE"
## [53] "SNOW/FREEZING RAIN" "SNOW/BLOWING SNOW"
## [55] "SNOWMELT FLOODING" "GRADIENT WIND"
## [57] "RECORD WARMTH" "PROLONG COLD"
## [59] "MONTHLY PRECIPITATION" "COLD"
## [61] "PROLONG WARMTH" "STRONG WINDS"
## [63] "MODERATE SNOWFALL" "MIXED PRECIPITATION"
## [65] "EXTREME WINDCHILL TEMPERATURES" "ACCUMULATED SNOWFALL"
## [67] "FALLING SNOW/ICE" "DRY CONDITIONS"
## [69] "DUST DEVEL" "NON-TSTM WIND"
## [71] "NON TSTM WIND" "MUDSLIDE"
## [73] "OTHER" "LAKE EFFECT SNOW"
## [75] "DRY SPELL" "BRUSH FIRE"
## [77] "GUSTY WINDS" "GUSTY THUNDERSTORM WINDS"
## [79] "BEACH EROSION" "ROUGH SEAS"
## [81] "LIGHT FREEZING RAIN" "PATCHY ICE"
## [83] "SNOW SHOWERS" "HEAVY RAIN EFFECTS"
## [85] "BLOWING DUST" "SNOW DROUGHT"
## [87] "GUSTY WIND" "FUNNEL CLOUDS"
## [89] "SEVERE THUNDERSTORMS" "EXCESSIVE HEAT/DROUGHT"
## [91] "HIGH WATER" "NORTHERN LIGHTS"
## [93] "MARINE TSTM WIND" " HIGH SURF ADVISORY"
## [95] "HIGH SURF ADVISORY" "HIGH SEAS"
## [97] "WIND CHILL" "HAZARDOUS SURF"
## [99] "WINTER WEATHER/MIX" "ASTRONOMICAL HIGH TIDE"
## [101] "COLD WEATHER" "HARD FREEZE"
## [103] "WHIRLWIND" "VERY WARM"
## [105] "ABNORMALLY WET" "UNUSUALLY COLD"
## [107] "TORNADO DEBRIS" "ICE ON ROAD"
## [109] "EARLY SNOWFALL" "FREEZING DRIZZLE"
## [111] "FIRST SNOW" "SNOW SQUALLS"
## [113] "ICY ROADS" "ICE/SNOW"
## [115] "DROWNING" "GUSTY THUNDERSTORM WIND"
## [117] "HIGH SURF ADVISORIES" "HURRICANE/TYPHOON"
## [119] "HEAVY SURF/HIGH SURF" "SLEET STORM"
## [121] "COLD WIND CHILL TEMPERATURES"We can see that 80 events are recorded differently from the standardized events. The next steps will be to replace these events by the standardized names. For this, we will apply a subjective judgment on defining the type of event. “OTHER” could not be classified and was left as it is.
data_toclean$EVTYPE[grepl("SURF",data_toclean$EVTYPE, ignore.case = TRUE)]<-"HIGH SURF"
data_toclean$EVTYPE[grepl("^TSTM|THUNDERSTORM",data_toclean$EVTYPE, ignore.case = TRUE)]<-"THUNDERSTORM WIND"
data_toclean$EVTYPE[grepl("WND|^WIND|^GUSTY|NON TSTM WIND|NON-TSTM WIND|GRADIENT WIND",data_toclean$EVTYPE, ignore.case = TRUE)]<-"HIGH WIND"
data_toclean$EVTYPE[grepl("SNOW",data_toclean$EVTYPE, ignore.case = TRUE)]<-"HIGH SNOW"
data_toclean$EVTYPE[grepl("HAIL",data_toclean$EVTYPE, ignore.case = TRUE)]<-"HAIL"
data_toclean$EVTYPE[grepl("COASTAL FLOOD",data_toclean$EVTYPE, ignore.case = TRUE)]<-"COASTAL FLOOD"
data_toclean$EVTYPE[grepl("freez|winter we",data_toclean$EVTYPE, ignore.case = TRUE)]<-"WINTER WEATHER"
data_toclean$EVTYPE[grepl("tornado|WHIRLWIND",data_toclean$EVTYPE, ignore.case = TRUE)]<-"TORNADO"
data_toclean$EVTYPE[grepl("fog",data_toclean$EVTYPE, ignore.case = TRUE)]<-"DENSE FOG"
data_toclean$EVTYPE[grepl("frost|ICE ON ROAD|BLACK ICE|ICY ROADS|UNSEASONABLY COOL|PATCHY ICE",data_toclean$EVTYPE, ignore.case = TRUE)]<-"FROST/FREEZE"
data_toclean$EVTYPE[grepl("fire",data_toclean$EVTYPE, ignore.case = TRUE)]<-"WILDFIRE"
data_toclean$EVTYPE[grepl("cold",data_toclean$EVTYPE, ignore.case = TRUE)]<-"EXTREME COLD/WIND CHILL"
data_toclean$EVTYPE[grepl("current|DROWNING",data_toclean$EVTYPE, ignore.case = TRUE)]<-"RIP CURRENT"
data_toclean$EVTYPE[grepl("^storm",data_toclean$EVTYPE, ignore.case = TRUE)]<-"STORM SURGE/TIDE"
data_toclean$EVTYPE[grepl("sleet",data_toclean$EVTYPE, ignore.case = TRUE)]<-"SLEET"
data_toclean$EVTYPE[grepl("marine tstm",data_toclean$EVTYPE, ignore.case = TRUE)]<-"MARINE THUNDERSTORM WIND"
data_toclean$EVTYPE[grepl("astronimical",data_toclean$EVTYPE, ignore.case = TRUE)]<-"ASTRONOMICAL LOW TIDE"
data_toclean$EVTYPE[grepl("smoke",data_toclean$EVTYPE, ignore.case = TRUE)]<-"DENSE SMOKE"
data_toclean$EVTYPE[grepl("HURRICANE",data_toclean$EVTYPE, ignore.case = TRUE)]<-"HURRICANE"
data_toclean$EVTYPE[grepl("marine",data_toclean$EVTYPE, ignore.case = TRUE)]<- "MARINE THUNDERSTORM WIND"
data_toclean$EVTYPE[grepl("volc",data_toclean$EVTYPE, ignore.case = TRUE)]<- "VOLCANIC ASHFALL"
data_toclean$EVTYPE[grepl("dry|RECORD LOW RAINFALL",data_toclean$EVTYPE, ignore.case = TRUE)]<- "DROUGHT"
data_toclean$EVTYPE[grepl("URBAN/SML STREAM FLD|ABNORMALLY WET|MONTHLY PRECIPITATION|MIXED PRECIPITATION",data_toclean$EVTYPE, ignore.case = TRUE)]<- "HEAVY RAIN"
data_toclean$EVTYPE[grepl("High snow",data_toclean$EVTYPE, ignore.case = TRUE)]<- "HEAVY SNOW"
data_toclean$EVTYPE[grepl("UNSEASONABLY WARM|VERY WARM|WARMTH",data_toclean$EVTYPE, ignore.case = TRUE)]<- "HEAT"
data_toclean$EVTYPE[grepl("WINTRY MIX|NORTHERN LIGHTS",data_toclean$EVTYPE, ignore.case = TRUE)]<- "WINTER WEATHER"
data_toclean$EVTYPE[grepl("EXTREME WINDCHILL",data_toclean$EVTYPE, ignore.case = TRUE)]<- "EXTREME COLD/WIND CHILL"
data_toclean$EVTYPE[grepl("MUDSLIDE|MUD SLIDE|BEACH EROSION",data_toclean$EVTYPE, ignore.case = TRUE)]<- "LANDSLIDE"
data_toclean$EVTYPE[grepl("STRONG WINDS",data_toclean$EVTYPE, ignore.case = TRUE)]<- "STRONG WIND"
data_toclean$EVTYPE[grepl("ROUGH SEAS|HIGH SEAS|ASTRONOMICAL HIGH TIDE|HIGH WATER|ROGUE WAVE",data_toclean$EVTYPE, ignore.case = TRUE)]<- "STORM SURGE/TIDE"
data_toclean$EVTYPE[grepl("RECORD HEAT|EXCESSIVE HEAT/DROUGHT",data_toclean$EVTYPE, ignore.case = TRUE)]<- "EXCESSIVE HEAT"
data_toclean$EVTYPE[grepl("UNSEASONABLY HOT",data_toclean$EVTYPE, ignore.case = TRUE)]<- "HEAT"
data_toclean$EVTYPE[grepl(" WATERSPOUT",data_toclean$EVTYPE, ignore.case = TRUE)]<- "WATERSPOUT"
data_toclean$EVTYPE[grepl("FUNNEL CLOUDS",data_toclean$EVTYPE, ignore.case = TRUE)]<- "FUNNEL CLOUD"
data_toclean$EVTYPE[grepl("CSTL FLOODING/EROSION",data_toclean$EVTYPE, ignore.case = TRUE)]<- "COASTAL FLOOD"
data_toclean$EVTYPE[grepl("RAIN|HEAVY RAIN EFFECTS|EXTREMELY WET",data_toclean$EVTYPE, ignore.case = TRUE)]<- "HEAVY RAIN"
data_toclean$EVTYPE[grepl("RED FLAG CRITERIA",data_toclean$EVTYPE, ignore.case = TRUE)]<- "WILDFIRE"
data_toclean$EVTYPE[grepl("BLOWING DUST|DUST DEVEL",data_toclean$EVTYPE, ignore.case = TRUE)]<- "DUST STORM"Finally, we will re-combine the two dataset into one “data_tidy”
data_tidy <- rbind(data_tidy, data_toclean)
unique(data_tidy$EVTYPE)## [1] "HAIL" "TORNADO"
## [3] "FLASH FLOOD" "HIGH WIND"
## [5] "FLOOD" "WINTER STORM"
## [7] "EXCESSIVE HEAT" "LIGHTNING"
## [9] "FUNNEL CLOUD" "HEAVY SNOW"
## [11] "WATERSPOUT" "TROPICAL STORM"
## [13] "HEAVY RAIN" "AVALANCHE"
## [15] "BLIZZARD" "ICE STORM"
## [17] "DUST STORM" "WINTER WEATHER"
## [19] "DUST DEVIL" "STRONG WIND"
## [21] "DROUGHT" "HIGH SURF"
## [23] "HURRICANE" "LANDSLIDE"
## [25] "DENSE FOG" "HEAT"
## [27] "WILDFIRE" "FROST/FREEZE"
## [29] "COASTAL FLOOD" "EXTREME COLD/WIND CHILL"
## [31] "SEICHE" "MARINE HAIL"
## [33] "RIP CURRENT" "TROPICAL DEPRESSION"
## [35] "STORM SURGE/TIDE" "FREEZING FOG"
## [37] "COLD/WIND CHILL" "LAKE-EFFECT SNOW"
## [39] "MARINE HIGH WIND" "THUNDERSTORM WIND"
## [41] "TSUNAMI" "SLEET"
## [43] "DENSE SMOKE" "LAKESHORE FLOOD"
## [45] "MARINE THUNDERSTORM WIND" "MARINE STRONG WIND"
## [47] "ASTRONOMICAL LOW TIDE" "VOLCANIC ASHFALL"
## [49] "OTHER"2.3. Handle the exponent values for crops and properties
The codebook gives information related to the definition of character in the propdmgexp and cropdmgexp columns https://github.com/lgreski/datasciencectacontent/blob/master/markdown/repdata-stormAnalysisCodebook.md
We first check the type of characters present in these columns
unique(data_tidy$PROPDMGEXP)## [1] "" "K" "M" "B" "0"unique(data_tidy$CROPDMGEXP)## [1] "" "K" "M" "B"Next, we multiply the values from propdmg or cropdmg variables whenever a “K”, “M”, or “B” is present.
# to handle the exponent values for properties
data_tidy <- data_tidy %>% mutate(PROPDMG = case_when(
PROPDMGEXP == "K" ~ PROPDMG*1000,
PROPDMGEXP == "M" ~ PROPDMG*1000000,
PROPDMGEXP == "B" ~ PROPDMG*1000000000,
TRUE ~ PROPDMG*1
))
# to handle the exponent values for properties
data_tidy <- data_tidy %>% mutate(CROPDMG = case_when(
CROPDMGEXP == "K" ~ CROPDMG*1000,
CROPDMGEXP == "M" ~ CROPDMG*1000000,
CROPDMGEXP == "B" ~ CROPDMG*1000000000,
TRUE ~ CROPDMG*1
))Finally, we can remove the cropdmgexp and propdmgexp variables from the table
data_tidy <- data_tidy %>%
select(-CROPDMGEXP, -PROPDMGEXP)For the rest of the analysis, only the year in the DATE column will be informative. We are now changing the format to display the year only:
data_tidy$DATE <- year(data_tidy$DATE) # keep only year3.Results
3.1. Evolution of the impact on population and economy since 2001
In order to evaluate which events have the most impact on population or economically, we first summarize the database by year and type of events (Table 1).
table1_melt <- melt(data_tidy, id = c("DATE", "EVTYPE"), measure.vars = c("FATALITIES", "INJURIES", "PROPDMG", "CROPDMG"))
table1 <- dcast(table1_melt, DATE+EVTYPE~variable, fun.aggregate = sum)
table1$TOTAL.POPULATION <- table1$FATALITIES + table1$INJURIES
table1$TOTAL.DAMAGE <- table1$PROPDMG + table1$CROPDMG
table1 <- table1 %>% select(DATE, EVTYPE, TOTAL.POPULATION, FATALITIES, INJURIES, TOTAL.DAMAGE, PROPDMG, CROPDMG)
knitr::kable(table1, caption = "Table 1: Summary of events and impact on population and economic since 2001")| DATE | EVTYPE | TOTAL.POPULATION | FATALITIES | INJURIES | TOTAL.DAMAGE | PROPDMG | CROPDMG |
|---|---|---|---|---|---|---|---|
| 2001 | AVALANCHE | 24 | 18 | 6 | 44000 | 44000 | 0 |
| 2001 | BLIZZARD | 9 | 4 | 5 | 8145000 | 8145000 | 0 |
| 2001 | COASTAL FLOOD | 1 | 1 | 0 | 16993000 | 16993000 | 0 |
| 2001 | DENSE FOG | 74 | 7 | 67 | 1283000 | 1283000 | 0 |
| 2001 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2001 | DROUGHT | 1 | 1 | 0 | 1274041500 | 169500 | 1273872000 |
| 2001 | DUST DEVIL | 1 | 0 | 1 | 3000 | 3000 | 0 |
| 2001 | DUST STORM | 5 | 0 | 5 | 180000 | 180000 | 0 |
| 2001 | EXCESSIVE HEAT | 610 | 165 | 445 | 0 | 0 | 0 |
| 2001 | EXTREME COLD/WIND CHILL | 4 | 4 | 0 | 84330000 | 0 | 84330000 |
| 2001 | FLASH FLOOD | 297 | 34 | 263 | 657393500 | 633851000 | 23542500 |
| 2001 | FLOOD | 21 | 13 | 8 | 604171000 | 584771000 | 19400000 |
| 2001 | FROST/FREEZE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2001 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2001 | HAIL | 32 | 0 | 32 | 2638727740 | 2368341440 | 270386300 |
| 2001 | HEAT | 1 | 1 | 0 | 0 | 0 | 0 |
| 2001 | HEAVY RAIN | 12 | 5 | 7 | 44263500 | 22662500 | 21601000 |
| 2001 | HEAVY SNOW | 23 | 3 | 20 | 65774000 | 65774000 | 0 |
| 2001 | HIGH SURF | 23 | 3 | 20 | 622500 | 622500 | 0 |
| 2001 | HIGH WIND | 104 | 13 | 91 | 69041570 | 66481570 | 2560000 |
| 2001 | HURRICANE | 1 | 1 | 0 | 1100000 | 650000 | 450000 |
| 2001 | ICE STORM | 12 | 5 | 7 | 10032000 | 10032000 | 0 |
| 2001 | LANDSLIDE | 0 | 0 | 0 | 1325000 | 1325000 | 0 |
| 2001 | LIGHTNING | 416 | 44 | 372 | 45610600 | 43602800 | 2007800 |
| 2001 | MARINE THUNDERSTORM WIND | 0 | 0 | 0 | 0 | 0 | 0 |
| 2001 | OTHER | 4 | 0 | 4 | 0 | 0 | 0 |
| 2001 | RIP CURRENT | 125 | 49 | 76 | 60000 | 60000 | 0 |
| 2001 | STORM SURGE/TIDE | 8 | 5 | 3 | 1460000 | 1460000 | 0 |
| 2001 | STRONG WIND | 9 | 1 | 8 | 322000 | 322000 | 0 |
| 2001 | THUNDERSTORM WIND | 359 | 17 | 342 | 379785660 | 318727660 | 61058000 |
| 2001 | TORNADO | 783 | 40 | 743 | 637497400 | 630086900 | 7410500 |
| 2001 | TROPICAL STORM | 29 | 23 | 6 | 5188110000 | 5185910000 | 2200000 |
| 2001 | VOLCANIC ASHFALL | 0 | 0 | 0 | 500000 | 500000 | 0 |
| 2001 | WATERSPOUT | 0 | 0 | 0 | 0 | 0 | 0 |
| 2001 | WILDFIRE | 53 | 5 | 48 | 45172800 | 45172800 | 0 |
| 2001 | WINTER STORM | 84 | 7 | 77 | 19868000 | 19808000 | 60000 |
| 2001 | WINTER WEATHER | 65 | 0 | 65 | 47915000 | 65000 | 47850000 |
| 2002 | AVALANCHE | 29 | 18 | 11 | 31500 | 31500 | 0 |
| 2002 | BLIZZARD | 11 | 4 | 7 | 185000 | 185000 | 0 |
| 2002 | COASTAL FLOOD | 0 | 0 | 0 | 100000 | 100000 | 0 |
| 2002 | DENSE FOG | 168 | 22 | 146 | 3975000 | 3975000 | 0 |
| 2002 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2002 | DROUGHT | 7 | 1 | 6 | 737718000 | 83000 | 737635000 |
| 2002 | DUST DEVIL | 1 | 0 | 1 | 13300 | 13300 | 0 |
| 2002 | DUST STORM | 47 | 2 | 45 | 427000 | 427000 | 0 |
| 2002 | EXCESSIVE HEAT | 545 | 167 | 378 | 0 | 0 | 0 |
| 2002 | EXTREME COLD/WIND CHILL | 11 | 11 | 0 | 70663000 | 303000 | 70360000 |
| 2002 | FLASH FLOOD | 103 | 32 | 71 | 267968500 | 258248500 | 9720000 |
| 2002 | FLOOD | 15 | 10 | 5 | 467419300 | 394639800 | 72779500 |
| 2002 | FROST/FREEZE | 1 | 1 | 0 | 0 | 0 | 0 |
| 2002 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2002 | HAIL | 125 | 0 | 125 | 479113590 | 325268840 | 153844750 |
| 2002 | HEAT | 0 | 0 | 0 | 0 | 0 | 0 |
| 2002 | HEAVY RAIN | 15 | 5 | 10 | 4628200 | 3566200 | 1062000 |
| 2002 | HEAVY SNOW | 41 | 2 | 39 | 11337400 | 11337400 | 0 |
| 2002 | HIGH SURF | 12 | 5 | 7 | 42000 | 42000 | 0 |
| 2002 | HIGH WIND | 152 | 26 | 126 | 116385900 | 82835900 | 33550000 |
| 2002 | HURRICANE | 321 | 2 | 319 | 1012255010 | 744255010 | 268000000 |
| 2002 | ICE STORM | 49 | 4 | 45 | 700860000 | 700860000 | 0 |
| 2002 | LANDSLIDE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2002 | LIGHTNING | 307 | 51 | 256 | 43556600 | 43537600 | 19000 |
| 2002 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2002 | MARINE THUNDERSTORM WIND | 0 | 0 | 0 | 158000 | 158000 | 0 |
| 2002 | RIP CURRENT | 104 | 44 | 60 | 100000 | 100000 | 0 |
| 2002 | SEICHE | 0 | 0 | 0 | 35000 | 35000 | 0 |
| 2002 | STORM SURGE/TIDE | 7 | 6 | 1 | 10558000 | 10558000 | 0 |
| 2002 | STRONG WIND | 5 | 2 | 3 | 172000 | 172000 | 0 |
| 2002 | THUNDERSTORM WIND | 298 | 17 | 281 | 344768750 | 290076500 | 54692250 |
| 2002 | TORNADO | 1023 | 55 | 968 | 802060210 | 801261200 | 799010 |
| 2002 | TROPICAL STORM | 5 | 1 | 4 | 193204000 | 187304000 | 5900000 |
| 2002 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2002 | WATERSPOUT | 1 | 0 | 1 | 0 | 0 | 0 |
| 2002 | WILDFIRE | 139 | 1 | 138 | 202833630 | 200827000 | 2006630 |
| 2002 | WINTER STORM | 108 | 9 | 99 | 40621700 | 40621700 | 0 |
| 2002 | WINTER WEATHER | 3 | 0 | 3 | 60000 | 60000 | 0 |
| 2003 | AVALANCHE | 17 | 10 | 7 | 15000 | 15000 | 0 |
| 2003 | BLIZZARD | 4 | 0 | 4 | 62135000 | 62135000 | 0 |
| 2003 | COASTAL FLOOD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2003 | DENSE FOG | 48 | 5 | 43 | 1675000 | 1675000 | 0 |
| 2003 | DROUGHT | 0 | 0 | 0 | 1217630000 | 645150000 | 572480000 |
| 2003 | DUST DEVIL | 4 | 1 | 3 | 130000 | 130000 | 0 |
| 2003 | DUST STORM | 93 | 2 | 91 | 284000 | 284000 | 0 |
| 2003 | EXCESSIVE HEAT | 210 | 36 | 174 | 2000 | 0 | 2000 |
| 2003 | EXTREME COLD/WIND CHILL | 34 | 20 | 14 | 17910000 | 860000 | 17050000 |
| 2003 | FLASH FLOOD | 130 | 69 | 61 | 2142321000 | 2124036500 | 18284500 |
| 2003 | FLOOD | 23 | 18 | 5 | 558468900 | 418678900 | 139790000 |
| 2003 | FROST/FREEZE | 0 | 0 | 0 | 11120000 | 0 | 11120000 |
| 2003 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2003 | HAIL | 121 | 0 | 121 | 615969520 | 505952470 | 110017050 |
| 2003 | HEAVY RAIN | 44 | 6 | 38 | 78697000 | 8884000 | 69813000 |
| 2003 | HEAVY SNOW | 15 | 2 | 13 | 64458080 | 64458080 | 0 |
| 2003 | HIGH SURF | 21 | 13 | 8 | 8180000 | 8180000 | 0 |
| 2003 | HIGH WIND | 142 | 15 | 127 | 198615520 | 157610520 | 41005000 |
| 2003 | HURRICANE | 8 | 6 | 2 | 1017140000 | 987770000 | 29370000 |
| 2003 | ICE STORM | 37 | 6 | 31 | 278166000 | 269616000 | 8550000 |
| 2003 | LANDSLIDE | 31 | 15 | 16 | 5591000 | 5591000 | 0 |
| 2003 | LIGHTNING | 282 | 44 | 238 | 25771750 | 25728750 | 43000 |
| 2003 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2003 | MARINE THUNDERSTORM WIND | 4 | 2 | 2 | 3215000 | 3215000 | 0 |
| 2003 | RIP CURRENT | 88 | 41 | 47 | 0 | 0 | 0 |
| 2003 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2003 | STORM SURGE/TIDE | 1 | 0 | 1 | 61892000 | 61892000 | 0 |
| 2003 | STRONG WIND | 38 | 9 | 29 | 9153600 | 9153600 | 0 |
| 2003 | THUNDERSTORM WIND | 241 | 17 | 224 | 422409120 | 355886320 | 66522800 |
| 2003 | TORNADO | 1141 | 54 | 1087 | 1281558270 | 1265650770 | 15907500 |
| 2003 | TROPICAL DEPRESSION | 0 | 0 | 0 | 50000 | 50000 | 0 |
| 2003 | TROPICAL STORM | 238 | 8 | 230 | 849038000 | 837088000 | 11950000 |
| 2003 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2003 | WATERSPOUT | 0 | 0 | 0 | 0 | 0 | 0 |
| 2003 | WILDFIRE | 275 | 24 | 251 | 2362777830 | 2331612330 | 31165500 |
| 2003 | WINTER STORM | 68 | 16 | 52 | 102714000 | 102714000 | 0 |
| 2003 | WINTER WEATHER | 16 | 4 | 12 | 531000 | 531000 | 0 |
| 2004 | AVALANCHE | 18 | 12 | 6 | 90000 | 90000 | 0 |
| 2004 | BLIZZARD | 5 | 1 | 4 | 242000 | 242000 | 0 |
| 2004 | DENSE FOG | 46 | 1 | 45 | 1590000 | 1590000 | 0 |
| 2004 | DROUGHT | 0 | 0 | 0 | 1190000 | 0 | 1190000 |
| 2004 | DUST DEVIL | 5 | 0 | 5 | 8800 | 8800 | 0 |
| 2004 | DUST STORM | 11 | 0 | 11 | 80000 | 80000 | 0 |
| 2004 | EXCESSIVE HEAT | 80 | 6 | 74 | 0 | 0 | 0 |
| 2004 | EXTREME COLD/WIND CHILL | 29 | 27 | 2 | 650000 | 650000 | 0 |
| 2004 | FLASH FLOOD | 87 | 58 | 29 | 868884250 | 856662250 | 12222000 |
| 2004 | FLOOD | 123 | 24 | 99 | 1173603400 | 844435500 | 329167900 |
| 2004 | FROST/FREEZE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2004 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2004 | HAIL | 4 | 0 | 4 | 535992480 | 463019380 | 72973100 |
| 2004 | HEAVY RAIN | 13 | 4 | 9 | 4069000 | 3619000 | 450000 |
| 2004 | HEAVY SNOW | 142 | 3 | 139 | 25812400 | 25612400 | 200000 |
| 2004 | HIGH SURF | 53 | 24 | 29 | 305000 | 305000 | 0 |
| 2004 | HIGH WIND | 62 | 13 | 49 | 3516832850 | 3224745850 | 292087000 |
| 2004 | HURRICANE | 862 | 23 | 839 | 18922255800 | 18356435000 | 565820800 |
| 2004 | ICE STORM | 10 | 0 | 10 | 46222000 | 46222000 | 0 |
| 2004 | LANDSLIDE | 15 | 4 | 11 | 32289000 | 32289000 | 0 |
| 2004 | LIGHTNING | 312 | 33 | 279 | 26047800 | 26006000 | 41800 |
| 2004 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2004 | MARINE THUNDERSTORM WIND | 6 | 6 | 0 | 243000 | 243000 | 0 |
| 2004 | RIP CURRENT | 55 | 32 | 23 | 0 | 0 | 0 |
| 2004 | SEICHE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2004 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2004 | STORM SURGE/TIDE | 0 | 0 | 0 | 45730000 | 45730000 | 0 |
| 2004 | STRONG WIND | 32 | 13 | 19 | 135494140 | 87044140 | 48450000 |
| 2004 | THUNDERSTORM WIND | 259 | 16 | 243 | 182297150 | 166653400 | 15643750 |
| 2004 | TORNADO | 431 | 35 | 396 | 548718950 | 536587450 | 12131500 |
| 2004 | TROPICAL DEPRESSION | 0 | 0 | 0 | 335000 | 335000 | 0 |
| 2004 | TROPICAL STORM | 12 | 11 | 1 | 601100000 | 499600000 | 101500000 |
| 2004 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2004 | WATERSPOUT | 0 | 0 | 0 | 2000 | 2000 | 0 |
| 2004 | WILDFIRE | 63 | 0 | 63 | 17232700 | 16932700 | 300000 |
| 2004 | WINTER STORM | 25 | 9 | 16 | 109454000 | 109454000 | 0 |
| 2004 | WINTER WEATHER | 36 | 15 | 21 | 2005000 | 2005000 | 0 |
| 2005 | AVALANCHE | 27 | 11 | 16 | 200000 | 200000 | 0 |
| 2005 | BLIZZARD | 3 | 1 | 2 | 15840000 | 15840000 | 0 |
| 2005 | COASTAL FLOOD | 1 | 0 | 1 | 450000 | 450000 | 0 |
| 2005 | COLD/WIND CHILL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2005 | DENSE FOG | 12 | 0 | 12 | 642000 | 642000 | 0 |
| 2005 | DROUGHT | 0 | 0 | 0 | 1388494000 | 77414000 | 1311080000 |
| 2005 | DUST DEVIL | 0 | 0 | 0 | 30800 | 30800 | 0 |
| 2005 | DUST STORM | 32 | 0 | 32 | 70000 | 70000 | 0 |
| 2005 | EXCESSIVE HEAT | 456 | 158 | 298 | 3000000 | 3000000 | 0 |
| 2005 | EXTREME COLD/WIND CHILL | 25 | 24 | 1 | 100000 | 100000 | 0 |
| 2005 | FLASH FLOOD | 50 | 28 | 22 | 328520700 | 293188200 | 35332500 |
| 2005 | FLOOD | 31 | 15 | 16 | 1313378090 | 1244483090 | 68895000 |
| 2005 | FREEZING FOG | 0 | 0 | 0 | 0 | 0 | 0 |
| 2005 | FROST/FREEZE | 0 | 0 | 0 | 139225000 | 0 | 139225000 |
| 2005 | FUNNEL CLOUD | 0 | 0 | 0 | 15000 | 15000 | 0 |
| 2005 | HAIL | 9 | 1 | 8 | 536592230 | 480469230 | 56123000 |
| 2005 | HEAVY RAIN | 47 | 8 | 39 | 492808500 | 264197500 | 228611000 |
| 2005 | HEAVY SNOW | 18 | 7 | 11 | 19188000 | 19078000 | 110000 |
| 2005 | HIGH SURF | 16 | 5 | 11 | 1400000 | 1400000 | 0 |
| 2005 | HIGH WIND | 16 | 2 | 14 | 65581500 | 44251500 | 21330000 |
| 2005 | HURRICANE | 152 | 34 | 118 | 51799317000 | 49786635000 | 2012682000 |
| 2005 | ICE STORM | 6 | 2 | 4 | 146084500 | 146049500 | 35000 |
| 2005 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 80000 | 80000 | 0 |
| 2005 | LANDSLIDE | 22 | 11 | 11 | 91515000 | 91515000 | 0 |
| 2005 | LIGHTNING | 347 | 38 | 309 | 52849100 | 52434100 | 415000 |
| 2005 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2005 | MARINE HIGH WIND | 0 | 0 | 0 | 21000 | 21000 | 0 |
| 2005 | MARINE THUNDERSTORM WIND | 1 | 1 | 0 | 305000 | 305000 | 0 |
| 2005 | RIP CURRENT | 44 | 35 | 9 | 0 | 0 | 0 |
| 2005 | SEICHE | 0 | 0 | 0 | 25000 | 25000 | 0 |
| 2005 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2005 | STORM SURGE/TIDE | 1 | 0 | 1 | 43059400000 | 43059400000 | 0 |
| 2005 | STRONG WIND | 34 | 5 | 29 | 14862650 | 14257650 | 605000 |
| 2005 | THUNDERSTORM WIND | 200 | 15 | 185 | 410655100 | 398724100 | 11931000 |
| 2005 | TORNADO | 575 | 38 | 537 | 503938400 | 421833500 | 82104900 |
| 2005 | TROPICAL DEPRESSION | 0 | 0 | 0 | 50000 | 50000 | 0 |
| 2005 | TROPICAL STORM | 11 | 0 | 11 | 286627000 | 220127000 | 66500000 |
| 2005 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2005 | WATERSPOUT | 0 | 0 | 0 | 0 | 0 | 0 |
| 2005 | WILDFIRE | 88 | 6 | 82 | 40877400 | 40654500 | 222900 |
| 2005 | WINTER STORM | 34 | 15 | 19 | 109573500 | 109573500 | 0 |
| 2005 | WINTER WEATHER | 45 | 9 | 36 | 3277000 | 3277000 | 0 |
| 2006 | AVALANCHE | 19 | 13 | 6 | 0 | 0 | 0 |
| 2006 | BLIZZARD | 1 | 1 | 0 | 4685000 | 4685000 | 0 |
| 2006 | COASTAL FLOOD | 0 | 0 | 0 | 51824000 | 51824000 | 0 |
| 2006 | COLD/WIND CHILL | 2 | 2 | 0 | 0 | 0 | 0 |
| 2006 | DENSE FOG | 43 | 3 | 40 | 650000 | 650000 | 0 |
| 2006 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2006 | DROUGHT | 4 | 0 | 4 | 2498130000 | 122305000 | 2375825000 |
| 2006 | DUST DEVIL | 1 | 0 | 1 | 37000 | 37000 | 0 |
| 2006 | DUST STORM | 24 | 2 | 22 | 2940000 | 690000 | 2250000 |
| 2006 | EXCESSIVE HEAT | 1198 | 205 | 993 | 492570000 | 170000 | 492400000 |
| 2006 | EXTREME COLD/WIND CHILL | 13 | 8 | 5 | 0 | 0 | 0 |
| 2006 | FLASH FLOOD | 77 | 59 | 18 | 2161608130 | 2136595130 | 25013000 |
| 2006 | FLOOD | 24 | 19 | 5 | 116611270440 | 116516105440 | 95165000 |
| 2006 | FREEZING FOG | 0 | 0 | 0 | 0 | 0 | 0 |
| 2006 | FROST/FREEZE | 0 | 0 | 0 | 11940000 | 0 | 11940000 |
| 2006 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2006 | HAIL | 18 | 0 | 18 | 1433507000 | 1300570000 | 132937000 |
| 2006 | HEAT | 567 | 47 | 520 | 86500 | 10000 | 76500 |
| 2006 | HEAVY RAIN | 5 | 1 | 4 | 102128010 | 52383010 | 49745000 |
| 2006 | HEAVY SNOW | 2 | 0 | 2 | 8136750 | 8136750 | 0 |
| 2006 | HIGH SURF | 22 | 13 | 9 | 360000 | 360000 | 0 |
| 2006 | HIGH WIND | 76 | 19 | 57 | 138173100 | 123144100 | 15029000 |
| 2006 | ICE STORM | 6 | 6 | 0 | 22002000 | 22002000 | 0 |
| 2006 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 23328000 | 23328000 | 0 |
| 2006 | LAKESHORE FLOOD | 0 | 0 | 0 | 10000 | 10000 | 0 |
| 2006 | LANDSLIDE | 5 | 3 | 2 | 78889500 | 58889500 | 20000000 |
| 2006 | LIGHTNING | 290 | 45 | 245 | 63772280 | 63758280 | 14000 |
| 2006 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2006 | MARINE HIGH WIND | 0 | 0 | 0 | 136000 | 136000 | 0 |
| 2006 | MARINE STRONG WIND | 2 | 2 | 0 | 16000 | 16000 | 0 |
| 2006 | MARINE THUNDERSTORM WIND | 7 | 1 | 6 | 1501000 | 1501000 | 0 |
| 2006 | RIP CURRENT | 50 | 26 | 24 | 0 | 0 | 0 |
| 2006 | SEICHE | 0 | 0 | 0 | 10000 | 10000 | 0 |
| 2006 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2006 | STORM SURGE/TIDE | 0 | 0 | 0 | 705000 | 705000 | 0 |
| 2006 | STRONG WIND | 42 | 17 | 25 | 17820000 | 17698500 | 121500 |
| 2006 | THUNDERSTORM WIND | 254 | 13 | 241 | 438881080 | 407825780 | 31055300 |
| 2006 | TORNADO | 1059 | 67 | 992 | 758960000 | 752273000 | 6687000 |
| 2006 | TROPICAL STORM | 1 | 0 | 1 | 44945200 | 1655200 | 43290000 |
| 2006 | TSUNAMI | 0 | 0 | 0 | 9203000 | 9203000 | 0 |
| 2006 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2006 | WATERSPOUT | 0 | 0 | 0 | 25000 | 25000 | 0 |
| 2006 | WILDFIRE | 107 | 15 | 92 | 411797400 | 179107000 | 232690400 |
| 2006 | WINTER STORM | 23 | 9 | 14 | 79398000 | 79398000 | 0 |
| 2006 | WINTER WEATHER | 25 | 3 | 22 | 2227500 | 2227500 | 0 |
| 2007 | ASTRONOMICAL LOW TIDE | 0 | 0 | 0 | 120000 | 120000 | 0 |
| 2007 | AVALANCHE | 30 | 18 | 12 | 2000 | 2000 | 0 |
| 2007 | BLIZZARD | 0 | 0 | 0 | 279000 | 279000 | 0 |
| 2007 | COASTAL FLOOD | 0 | 0 | 0 | 77470060 | 77470060 | 0 |
| 2007 | COLD/WIND CHILL | 14 | 4 | 10 | 591000 | 91000 | 500000 |
| 2007 | DENSE FOG | 3 | 0 | 3 | 440000 | 440000 | 0 |
| 2007 | DENSE SMOKE | 0 | 0 | 0 | 100000 | 100000 | 0 |
| 2007 | DROUGHT | 0 | 0 | 0 | 374677000 | 825000 | 373852000 |
| 2007 | DUST DEVIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | DUST STORM | 4 | 0 | 4 | 780000 | 780000 | 0 |
| 2007 | EXCESSIVE HEAT | 558 | 22 | 536 | 0 | 0 | 0 |
| 2007 | EXTREME COLD/WIND CHILL | 24 | 23 | 1 | 3000 | 3000 | 0 |
| 2007 | FLASH FLOOD | 121 | 70 | 51 | 1277552900 | 1227564900 | 49988000 |
| 2007 | FLOOD | 25 | 17 | 8 | 1030828500 | 512321500 | 518507000 |
| 2007 | FREEZING FOG | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | FROST/FREEZE | 0 | 0 | 0 | 379699000 | 640000 | 379059000 |
| 2007 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | HAIL | 25 | 0 | 25 | 530995250 | 375726250 | 155269000 |
| 2007 | HEAT | 52 | 22 | 30 | 0 | 0 | 0 |
| 2007 | HEAVY RAIN | 10 | 2 | 8 | 80472030 | 78570030 | 1902000 |
| 2007 | HEAVY SNOW | 0 | 0 | 0 | 1168000 | 1168000 | 0 |
| 2007 | HIGH SURF | 10 | 10 | 0 | 7355000 | 7355000 | 0 |
| 2007 | HIGH WIND | 31 | 3 | 28 | 197744500 | 197695500 | 49000 |
| 2007 | HURRICANE | 13 | 1 | 12 | 37700000 | 37700000 | 0 |
| 2007 | ICE STORM | 10 | 2 | 8 | 474170000 | 474170000 | 0 |
| 2007 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 4871000 | 4871000 | 0 |
| 2007 | LAKESHORE FLOOD | 0 | 0 | 0 | 30000 | 30000 | 0 |
| 2007 | LANDSLIDE | 6 | 3 | 3 | 50952500 | 50952500 | 0 |
| 2007 | LIGHTNING | 184 | 45 | 139 | 82058800 | 81996800 | 62000 |
| 2007 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | MARINE HIGH WIND | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | MARINE STRONG WIND | 18 | 3 | 15 | 3000 | 3000 | 0 |
| 2007 | MARINE THUNDERSTORM WIND | 4 | 2 | 2 | 102000 | 102000 | 0 |
| 2007 | RIP CURRENT | 60 | 46 | 14 | 0 | 0 | 0 |
| 2007 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | STORM SURGE/TIDE | 5 | 0 | 5 | 4000000 | 4000000 | 0 |
| 2007 | STRONG WIND | 28 | 7 | 21 | 3673820 | 3538820 | 135000 |
| 2007 | THUNDERSTORM WIND | 270 | 16 | 254 | 406490450 | 218065450 | 188425000 |
| 2007 | TORNADO | 740 | 81 | 659 | 1408022650 | 1400756650 | 7266000 |
| 2007 | TROPICAL DEPRESSION | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | TROPICAL STORM | 0 | 0 | 0 | 350000 | 345000 | 5000 |
| 2007 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2007 | WATERSPOUT | 0 | 0 | 0 | 70000 | 70000 | 0 |
| 2007 | WILDFIRE | 202 | 17 | 185 | 1020603700 | 1004493700 | 16110000 |
| 2007 | WINTER STORM | 5 | 3 | 2 | 24035000 | 24012000 | 23000 |
| 2007 | WINTER WEATHER | 160 | 4 | 156 | 2676000 | 2676000 | 0 |
| 2008 | ASTRONOMICAL LOW TIDE | 0 | 0 | 0 | 200000 | 200000 | 0 |
| 2008 | AVALANCHE | 39 | 25 | 14 | 1126000 | 1126000 | 0 |
| 2008 | BLIZZARD | 2 | 2 | 0 | 521000 | 521000 | 0 |
| 2008 | COASTAL FLOOD | 2 | 2 | 0 | 978000 | 978000 | 0 |
| 2008 | COLD/WIND CHILL | 31 | 31 | 0 | 0 | 0 | 0 |
| 2008 | DENSE FOG | 0 | 0 | 0 | 430000 | 430000 | 0 |
| 2008 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2008 | DROUGHT | 0 | 0 | 0 | 645000 | 100000 | 545000 |
| 2008 | DUST DEVIL | 15 | 1 | 14 | 60530 | 60530 | 0 |
| 2008 | DUST STORM | 0 | 0 | 0 | 0 | 0 | 0 |
| 2008 | EXCESSIVE HEAT | 146 | 15 | 131 | 0 | 0 | 0 |
| 2008 | EXTREME COLD/WIND CHILL | 8 | 8 | 0 | 0 | 0 | 0 |
| 2008 | FLASH FLOOD | 85 | 55 | 30 | 1559310660 | 1147531660 | 411779000 |
| 2008 | FLOOD | 38 | 22 | 16 | 3115787650 | 2037495650 | 1078292000 |
| 2008 | FREEZING FOG | 0 | 0 | 0 | 0 | 0 | 0 |
| 2008 | FROST/FREEZE | 0 | 0 | 0 | 120132000 | 40000 | 120092000 |
| 2008 | FUNNEL CLOUD | 0 | 0 | 0 | 25000 | 25000 | 0 |
| 2008 | HAIL | 14 | 2 | 12 | 606047300 | 427831300 | 178216000 |
| 2008 | HEAT | 35 | 27 | 8 | 0 | 0 | 0 |
| 2008 | HEAVY RAIN | 18 | 2 | 16 | 12402500 | 7902500 | 4500000 |
| 2008 | HEAVY SNOW | 22 | 4 | 18 | 5538000 | 5538000 | 0 |
| 2008 | HIGH SURF | 64 | 6 | 58 | 9824000 | 9824000 | 0 |
| 2008 | HIGH WIND | 67 | 11 | 56 | 833856470 | 786725470 | 47131000 |
| 2008 | HURRICANE | 1 | 1 | 0 | 2589380000 | 2419380000 | 170000000 |
| 2008 | ICE STORM | 0 | 0 | 0 | 87469000 | 87469000 | 0 |
| 2008 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 2911000 | 2911000 | 0 |
| 2008 | LANDSLIDE | 0 | 0 | 0 | 2421000 | 2421000 | 0 |
| 2008 | LIGHTNING | 232 | 25 | 207 | 58976660 | 58873660 | 103000 |
| 2008 | MARINE HAIL | 0 | 0 | 0 | 4000 | 4000 | 0 |
| 2008 | MARINE HIGH WIND | 2 | 1 | 1 | 110000 | 110000 | 0 |
| 2008 | MARINE STRONG WIND | 4 | 4 | 0 | 26100 | 26100 | 0 |
| 2008 | MARINE THUNDERSTORM WIND | 8 | 2 | 6 | 162000 | 162000 | 0 |
| 2008 | RIP CURRENT | 65 | 44 | 21 | 0 | 0 | 0 |
| 2008 | SEICHE | 0 | 0 | 0 | 75000 | 75000 | 0 |
| 2008 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2008 | STORM SURGE/TIDE | 11 | 11 | 0 | 4595885000 | 4595035000 | 850000 |
| 2008 | STRONG WIND | 43 | 17 | 26 | 8762540 | 8713540 | 49000 |
| 2008 | THUNDERSTORM WIND | 278 | 25 | 253 | 1185744580 | 1159133580 | 26611000 |
| 2008 | TORNADO | 1819 | 129 | 1690 | 1724441840 | 1706231840 | 18210000 |
| 2008 | TROPICAL DEPRESSION | 0 | 0 | 0 | 1300000 | 1300000 | 0 |
| 2008 | TROPICAL STORM | 15 | 2 | 13 | 261973750 | 110568750 | 151405000 |
| 2008 | VOLCANIC ASHFALL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2008 | WATERSPOUT | 0 | 0 | 0 | 10200 | 10200 | 0 |
| 2008 | WILDFIRE | 35 | 3 | 32 | 201948100 | 199938100 | 2010000 |
| 2008 | WINTER STORM | 4 | 0 | 4 | 783718000 | 783718000 | 0 |
| 2008 | WINTER WEATHER | 88 | 11 | 77 | 5973200 | 5973200 | 0 |
| 2009 | ASTRONOMICAL LOW TIDE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2009 | AVALANCHE | 10 | 7 | 3 | 1001000 | 1001000 | 0 |
| 2009 | BLIZZARD | 4 | 3 | 1 | 24061000 | 24061000 | 0 |
| 2009 | COASTAL FLOOD | 0 | 0 | 0 | 53169500 | 53169500 | 0 |
| 2009 | COLD/WIND CHILL | 11 | 11 | 0 | 0 | 0 | 0 |
| 2009 | DENSE FOG | 0 | 0 | 0 | 755000 | 755000 | 0 |
| 2009 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2009 | DROUGHT | 0 | 0 | 0 | 13988000 | 50000 | 13938000 |
| 2009 | DUST DEVIL | 3 | 0 | 3 | 226500 | 226500 | 0 |
| 2009 | DUST STORM | 3 | 3 | 0 | 1410000 | 660000 | 750000 |
| 2009 | EXCESSIVE HEAT | 19 | 7 | 12 | 0 | 0 | 0 |
| 2009 | EXTREME COLD/WIND CHILL | 17 | 17 | 0 | 0 | 0 | 0 |
| 2009 | FLASH FLOOD | 50 | 33 | 17 | 451537970 | 442489970 | 9048000 |
| 2009 | FLOOD | 33 | 23 | 10 | 637512660 | 607782660 | 29730000 |
| 2009 | FREEZING FOG | 0 | 0 | 0 | 2000000 | 2000000 | 0 |
| 2009 | FROST/FREEZE | 0 | 0 | 0 | 65085000 | 85000 | 65000000 |
| 2009 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2009 | HAIL | 70 | 0 | 70 | 1790994550 | 1440000550 | 350994000 |
| 2009 | HEAT | 40 | 26 | 14 | 1510000 | 1510000 | 0 |
| 2009 | HEAVY RAIN | 15 | 6 | 9 | 5811000 | 5651000 | 160000 |
| 2009 | HEAVY SNOW | 2 | 2 | 0 | 18952000 | 18952000 | 0 |
| 2009 | HIGH SURF | 44 | 15 | 29 | 16455000 | 16455000 | 0 |
| 2009 | HIGH WIND | 26 | 4 | 22 | 147056150 | 147026150 | 30000 |
| 2009 | HURRICANE | 1 | 0 | 1 | 30000 | 20000 | 10000 |
| 2009 | ICE STORM | 6 | 3 | 3 | 205154000 | 205154000 | 0 |
| 2009 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 1657000 | 1657000 | 0 |
| 2009 | LANDSLIDE | 9 | 0 | 9 | 43885000 | 43885000 | 0 |
| 2009 | LIGHTNING | 235 | 34 | 201 | 43868350 | 43857350 | 11000 |
| 2009 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2009 | MARINE HIGH WIND | 0 | 0 | 0 | 0 | 0 | 0 |
| 2009 | MARINE STRONG WIND | 3 | 1 | 2 | 20000 | 20000 | 0 |
| 2009 | MARINE THUNDERSTORM WIND | 4 | 2 | 2 | 51500 | 51500 | 0 |
| 2009 | RIP CURRENT | 59 | 39 | 20 | 1000 | 1000 | 0 |
| 2009 | SEICHE | 0 | 0 | 0 | 15000 | 15000 | 0 |
| 2009 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2009 | STORM SURGE/TIDE | 0 | 0 | 0 | 118000 | 118000 | 0 |
| 2009 | STRONG WIND | 34 | 10 | 24 | 5972000 | 5970000 | 2000 |
| 2009 | THUNDERSTORM WIND | 208 | 20 | 188 | 1430389250 | 1397967250 | 32422000 |
| 2009 | TORNADO | 418 | 21 | 397 | 584292100 | 565814100 | 18478000 |
| 2009 | TROPICAL DEPRESSION | 0 | 0 | 0 | 2000 | 2000 | 0 |
| 2009 | TROPICAL STORM | 1 | 1 | 0 | 221000 | 221000 | 0 |
| 2009 | TSUNAMI | 161 | 32 | 129 | 81020000 | 81000000 | 20000 |
| 2009 | WATERSPOUT | 0 | 0 | 0 | 10000 | 10000 | 0 |
| 2009 | WILDFIRE | 70 | 2 | 68 | 93901600 | 92774600 | 1127000 |
| 2009 | WINTER STORM | 35 | 1 | 34 | 21362000 | 20862000 | 500000 |
| 2009 | WINTER WEATHER | 96 | 10 | 86 | 5929000 | 5929000 | 0 |
| 2010 | ASTRONOMICAL LOW TIDE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | AVALANCHE | 42 | 22 | 20 | 201800 | 201800 | 0 |
| 2010 | BLIZZARD | 0 | 0 | 0 | 1138000 | 1138000 | 0 |
| 2010 | COASTAL FLOOD | 0 | 0 | 0 | 5655000 | 5655000 | 0 |
| 2010 | COLD/WIND CHILL | 27 | 26 | 1 | 1929000 | 1829000 | 100000 |
| 2010 | DENSE FOG | 0 | 0 | 0 | 975000 | 975000 | 0 |
| 2010 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | DROUGHT | 0 | 0 | 0 | 5807000 | 0 | 5807000 |
| 2010 | DUST DEVIL | 0 | 0 | 0 | 61100 | 61100 | 0 |
| 2010 | DUST STORM | 0 | 0 | 0 | 140000 | 140000 | 0 |
| 2010 | EXCESSIVE HEAT | 102 | 39 | 63 | 90000 | 90000 | 0 |
| 2010 | EXTREME COLD/WIND CHILL | 1 | 1 | 0 | 0 | 0 | 0 |
| 2010 | FLASH FLOOD | 255 | 67 | 188 | 991720900 | 839040900 | 152680000 |
| 2010 | FLOOD | 168 | 41 | 127 | 4198737540 | 3094028540 | 1104709000 |
| 2010 | FREEZING FOG | 0 | 0 | 0 | 182000 | 182000 | 0 |
| 2010 | FROST/FREEZE | 0 | 0 | 0 | 357415000 | 3175000 | 354240000 |
| 2010 | FUNNEL CLOUD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | HAIL | 42 | 0 | 42 | 3506089950 | 3404109950 | 101980000 |
| 2010 | HEAT | 83 | 44 | 39 | 100000 | 0 | 100000 |
| 2010 | HEAVY RAIN | 7 | 0 | 7 | 9208500 | 5107500 | 4101000 |
| 2010 | HEAVY SNOW | 20 | 2 | 18 | 26015800 | 26015800 | 0 |
| 2010 | HIGH SURF | 37 | 17 | 20 | 49111500 | 49111500 | 0 |
| 2010 | HIGH WIND | 24 | 7 | 17 | 27727920 | 27659920 | 68000 |
| 2010 | HURRICANE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | ICE STORM | 1 | 0 | 1 | 5337800 | 5337800 | 0 |
| 2010 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 6415000 | 6415000 | 0 |
| 2010 | LAKESHORE FLOOD | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | LANDSLIDE | 0 | 0 | 0 | 17399000 | 17399000 | 0 |
| 2010 | LIGHTNING | 211 | 29 | 182 | 71600700 | 71148700 | 452000 |
| 2010 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | MARINE HIGH WIND | 0 | 0 | 0 | 20010 | 20010 | 0 |
| 2010 | MARINE STRONG WIND | 2 | 2 | 0 | 1630 | 1630 | 0 |
| 2010 | MARINE THUNDERSTORM WIND | 2 | 0 | 2 | 11100 | 11100 | 0 |
| 2010 | RIP CURRENT | 94 | 49 | 45 | 0 | 0 | 0 |
| 2010 | SEICHE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2010 | STORM SURGE/TIDE | 0 | 0 | 0 | 795000 | 795000 | 0 |
| 2010 | STRONG WIND | 36 | 8 | 28 | 11491570 | 10959570 | 532000 |
| 2010 | THUNDERSTORM WIND | 338 | 15 | 323 | 227213000 | 216401000 | 10812000 |
| 2010 | TORNADO | 744 | 45 | 699 | 1164565450 | 1136920450 | 27645000 |
| 2010 | TROPICAL STORM | 0 | 0 | 0 | 17719400 | 12709400 | 5010000 |
| 2010 | TSUNAMI | 0 | 0 | 0 | 305000 | 305000 | 0 |
| 2010 | WATERSPOUT | 0 | 0 | 0 | 1000 | 1000 | 0 |
| 2010 | WILDFIRE | 26 | 2 | 24 | 246938670 | 244888670 | 2050000 |
| 2010 | WINTER STORM | 10 | 6 | 4 | 61948000 | 61948000 | 0 |
| 2010 | WINTER WEATHER | 8 | 3 | 5 | 17705300 | 2705300 | 15000000 |
| 2011 | ASTRONOMICAL LOW TIDE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2011 | AVALANCHE | 17 | 9 | 8 | 55000 | 55000 | 0 |
| 2011 | BLIZZARD | 2 | 2 | 0 | 2742000 | 2742000 | 0 |
| 2011 | COASTAL FLOOD | 2 | 1 | 1 | 27274000 | 27274000 | 0 |
| 2011 | COLD/WIND CHILL | 22 | 21 | 1 | 70000 | 70000 | 0 |
| 2011 | DENSE FOG | 0 | 0 | 0 | 162000 | 162000 | 0 |
| 2011 | DENSE SMOKE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2011 | DROUGHT | 0 | 0 | 0 | 31388000 | 114000 | 31274000 |
| 2011 | DUST DEVIL | 8 | 0 | 8 | 33000 | 33000 | 0 |
| 2011 | DUST STORM | 4 | 0 | 4 | 848000 | 848000 | 0 |
| 2011 | EXCESSIVE HEAT | 174 | 36 | 138 | 1143200 | 1143200 | 0 |
| 2011 | EXTREME COLD/WIND CHILL | 3 | 2 | 1 | 7035000 | 7035000 | 0 |
| 2011 | FLASH FLOOD | 98 | 68 | 30 | 1472491700 | 1384044700 | 88447000 |
| 2011 | FLOOD | 68 | 58 | 10 | 7872549450 | 7717677450 | 154872000 |
| 2011 | FREEZING FOG | 0 | 0 | 0 | 0 | 0 | 0 |
| 2011 | FROST/FREEZE | 0 | 0 | 0 | 18950000 | 5540000 | 13410000 |
| 2011 | FUNNEL CLOUD | 0 | 0 | 0 | 40100 | 40100 | 0 |
| 2011 | HAIL | 31 | 0 | 31 | 533663550 | 451329550 | 82334000 |
| 2011 | HEAT | 674 | 63 | 611 | 0 | 0 | 0 |
| 2011 | HEAVY RAIN | 2 | 1 | 1 | 32504000 | 11791000 | 20713000 |
| 2011 | HEAVY SNOW | 0 | 0 | 0 | 16145300 | 16125300 | 20000 |
| 2011 | HIGH SURF | 22 | 11 | 11 | 222000 | 222000 | 0 |
| 2011 | HIGH WIND | 15 | 4 | 11 | 86244000 | 41951000 | 44293000 |
| 2011 | HURRICANE | 0 | 0 | 0 | 21000000 | 10500000 | 10500000 |
| 2011 | ICE STORM | 0 | 0 | 0 | 7917500 | 7837500 | 80000 |
| 2011 | LAKE-EFFECT SNOW | 0 | 0 | 0 | 853000 | 853000 | 0 |
| 2011 | LAKESHORE FLOOD | 0 | 0 | 0 | 7500000 | 7500000 | 0 |
| 2011 | LANDSLIDE | 1 | 1 | 0 | 21153000 | 21136000 | 17000 |
| 2011 | LIGHTNING | 220 | 26 | 194 | 47090920 | 46978920 | 112000 |
| 2011 | MARINE HAIL | 0 | 0 | 0 | 0 | 0 | 0 |
| 2011 | MARINE HIGH WIND | 0 | 0 | 0 | 1010000 | 1010000 | 0 |
| 2011 | MARINE STRONG WIND | 7 | 2 | 5 | 351600 | 351600 | 0 |
| 2011 | MARINE THUNDERSTORM WIND | 17 | 3 | 14 | 158800 | 108800 | 50000 |
| 2011 | RIP CURRENT | 56 | 29 | 27 | 0 | 0 | 0 |
| 2011 | SEICHE | 0 | 0 | 0 | 0 | 0 | 0 |
| 2011 | SLEET | 0 | 0 | 0 | 0 | 0 | 0 |
| 2011 | STORM SURGE/TIDE | 0 | 0 | 0 | 40695000 | 40695000 | 0 |
| 2011 | STRONG WIND | 43 | 10 | 33 | 31604130 | 16545130 | 15059000 |
| 2011 | THUNDERSTORM WIND | 427 | 54 | 373 | 521723410 | 381891410 | 139832000 |
| 2011 | TORNADO | 6750 | 587 | 6163 | 9850961700 | 9819600700 | 31361000 |
| 2011 | TROPICAL STORM | 5 | 4 | 1 | 163243200 | 138742200 | 24501000 |
| 2011 | TSUNAMI | 1 | 1 | 0 | 53554000 | 53554000 | 0 |
| 2011 | WATERSPOUT | 0 | 0 | 0 | 5110000 | 5110000 | 0 |
| 2011 | WILDFIRE | 122 | 6 | 116 | 658115400 | 648318400 | 9797000 |
| 2011 | WINTER STORM | 1 | 1 | 0 | 18227000 | 18157000 | 70000 |
| 2011 | WINTER WEATHER | 2 | 2 | 0 | 1895000 | 1895000 | 0 |
Legend: EVTYPE - type of events, PROPDMG - damages to properties in $, CROPDMG - damages to crops in $, TOTAL.POPULATION - pool of fatalities and injuries, TOTAL.DAMAGE - pool of damages to properties and crops in $.
Table 1 shows that the weather events did not have an impact every year. Some events had an impact only for a year or two. Hence, an average per year would not be representative of the impactness of the events. We will then summarize the total number of fatalities, injuries, damage to properties or damage to crop from 2001 to 2011 in Table 2.
table2 <- dcast(table1_melt, DATE~variable, fun.aggregate = sum)
table2$TOTAL.POPULATION <- table2$FATALITIES + table2$INJURIES
table2$TOTAL.DAMAGE <- table2$PROPDMG + table2$CROPDMG
table2 <- table2 %>% select(DATE, TOTAL.POPULATION, FATALITIES, INJURIES, TOTAL.DAMAGE, PROPDMG, CROPDMG)
knitr::kable(table2, caption = "Table 2: Summary of impact on population and economy over the time")| DATE | TOTAL.POPULATION | FATALITIES | INJURIES | TOTAL.DAMAGE | PROPDMG | CROPDMG |
|---|---|---|---|---|---|---|
| 2001 | 3190 | 469 | 2721 | 11843771770 | 10027043670 | 1816728100 |
| 2002 | 3653 | 498 | 3155 | 5511250590 | 4100882450 | 1410368140 |
| 2003 | 3374 | 443 | 2931 | 11397618590 | 10254548240 | 1143070350 |
| 2004 | 2796 | 370 | 2426 | 26798776720 | 25346598870 | 1452177850 |
| 2005 | 2303 | 469 | 1834 | 100824993470 | 96789791170 | 4035202300 |
| 2006 | 3967 | 599 | 3368 | 125471672890 | 121937434190 | 3534238700 |
| 2007 | 2612 | 421 | 2191 | 7480086160 | 5788934160 | 1691152000 |
| 2008 | 3191 | 488 | 2703 | 17778176080 | 15568383080 | 2209793000 |
| 2009 | 1687 | 333 | 1354 | 5749424130 | 5227204130 | 522220000 |
| 2010 | 2280 | 425 | 1855 | 11031773640 | 9246487640 | 1785286000 |
| 2011 | 8794 | 1002 | 7792 | 21555723960 | 20888981960 | 666742000 |
Interestingly, the total impact on population which includes the number of people injured and killed, independently of the type of events, was relatively stable over the time but surged in 2011 as presented in Figure 1. In contrast, the highest impact on properties and crops were observed in 2005 and 2006. These results suggest that the economical impact and harmfulness on population are not correlated.
Figure 1. Evolution of impact on population and economy over the time
3.2 Tornadoes are the most harmful event on population health
We have observed the evolution of the impact of population and economy over the time. Next, we will investigate which type of events is the most harmful to population health, all years combined since 2001.
Figure 2. Types of events impacting population health
The figure 2 represents all event types recorded since 2001 and their impact on population health, including injuries, fatalities or the pool number of injuries and fatalities. The bar graph is ordered by impact. Tornadoes have the most impact on population, both in terms of fatalities and injuries. The second most impact event is the excessive heat, although markedly lower on injuries compared to tornado. In third position, flash flood led to the highest number of fatalities while thunderstorm winds had more impact on injuries.
These results show that tornadoes are the most harmful event on population health.
3.3 Flood has the most impact on properties and droughts on crops
Similar to the impact on population health, we next evaluate the impact of the events on properties and crops damages.
Figure 3. Types of events impacting properties and crops
The Figure 3 represents all event types recorded since 2001 and their impact on economy, including the cost for property damages, crop damage or the combined cost on properties and crops. The bar graph is ordered by impact. The highest costs are reported for properties. Flood is the event which has the most impact on properties and second highest on crops. Hurricanes have the second highest impact on properties and third highest impact on crops. In contrast, droughts have the most impact on crops but are only in 13th position on properties.
These results show differences between impact on properties and crops with flood being the most impactful on properties while drought had more damages on crops.
4. Conclusions
By analyzing the Storm database from the NOAA we can evaluate the evolution of the weather events over the time and their impact on population health and economy. Interestingly, peak of impact on population and economy was not observed the same years. The peak impact on population was observed in 2011 while on economy, the most expensive damages were observed in 2006. Tornadoes have injured and killed the highest number of person. Interestingly, tornadoes did not have the highest impact on economy. Flood led to the highest cost on properties and droughts on the crops.