EDS222_delta-turbidity/wind_analysis.Rmd at main · cognack/EDS222_delta-turbidity · GitHub

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---
title: "wind_analysis"
author: "Steven Cognac"
date: "11/28/2021"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

library(dataRetrieval)
library(tidyverse)
library(here)
library(patchwork)
library(readr)
library(feasts)
#library(smooth)
#library(slider)
library(lubridate)
library(tibbletime)
library(tsibble)
```

Data downloaded from the NOAA National Centers for Environmental Information (NCEI) Climate Data Online search tool for Local Climatological Data (LCD) - (https://www.ncdc.noaa.gov/cdo-web/datatools/lcd)

https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc:C00684/html

10-year Date Range
Start:	2011-10-01
End: 	2021-09-30

Stations
 - VACAVILLE NUT TREE AIRPORT ASOS, CA US (Station No: WBAN:93241)
 - SACRAMENTO AIRPORT ASOS, CA US (Station No: WBAN:23232)
 - CONCORD BUCHANAN FIELD, CA US (WBAN:23254)


sacramento airport metadata - https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USW00023232/detail

# Read in Data
```{r}
wind_vaca_raw <- read_csv(here("data", "2805190_vacaville.csv")) %>%
  select(2,56:58) %>%
  filter(DATE > "2014-12-31 23:59:00")

wind_sac_raw <- read_csv(here("data", "2805192_sacramento.csv")) %>%
  select(2,56:58) %>%
  filter(DATE > "2014-12-31 23:59:00")

wind_concord_raw <- read_csv(here("data", "2805195_concord.csv")) %>%
  select(2,56:58) %>%
  filter(DATE > "2014-12-31 23:59:00")

```

```{r}
# vacaville nut tree airport
wind_vaca <- wind_vaca_raw %>%
  mutate(station = "vacaville",
         DATE = lubridate::floor_date(DATE, "hours")) %>%
  group_by(DATE, station) %>%
  summarise(HourlyWindSpeed)

wind_vaca <- wind_vaca[!duplicated(wind_vaca$DATE), ]

# sacramento airport
wind_sac <- wind_sac_raw %>%
  mutate(station = "sacramento",
         DATE = lubridate::floor_date(DATE, "hours")) %>%
  group_by(DATE, station) %>%
  summarise(HourlyWindSpeed)

wind_sac <- wind_sac[!duplicated(wind_sac$DATE), ]

# concord airport
wind_concord <- wind_concord_raw %>%
  mutate(station = "concord",
         DATE = lubridate::floor_date(DATE, "hours")) %>%
  group_by(DATE, station) %>%
  summarise(HourlyWindSpeed)

wind_concord <- wind_concord[!duplicated(wind_concord$DATE), ]


# combine dataframes
wind <- rbind(wind_vaca, wind_sac, wind_concord)

rm(wind_concord_raw, wind_concord, wind_sac_raw,wind_sac, wind_vaca_raw, wind_vaca)
```


```{r}
wind
class(wind)
lapply(wind, class)
```

## Calcualte average hourly wind speed for three stations
```{r}
wind_all <- wind %>%
  group_by(DATE) %>%
  summarize(HourlyWindSpeed = mean(HourlyWindSpeed)) %>%
  mutate(station = "vaca_sac_concord")

# combine datasets
wind_join <- rbind(wind, wind_all)
wind_tsbl <- wind_join %>% as_tsibble(key = station)

```


https://blog.earo.me/2018/02/06/tsibble-or-tibbletime/

```{r}

# time period options: as.Date(.), yearweek(.), yearmonth(.), yearquarter(.), lubridate::floor_date(., "4 hour")

# interval = lubridate::floor_date(., "4 hours")

wind_avg <- wind_tsbl %>%
  group_by_key() %>%

  # every 2 hours
  index_by(time = ~yearweek(.)) %>%
  summarise(wind_speed = mean(HourlyWindSpeed, na.rm = TRUE)) %>%
  na.omit()

wind_avg
```

```{r}
wind_avg %>%
  filter(station == "vaca_sac_concord") %>%

ggplot(aes(x = time, y = wind_speed)) +
  geom_line(color = "firebrick2", alpha = 0.5) +
  geom_smooth() +
  labs(title = "Average Hourly Wind Speed",
       subtitle = "Cache Slough Complex, Solano County, California",
       x = "Date",
       y = "Wind Speed (mph)",
       caption = "Source: NOAA NCEI. Station WBAN No. 93241, 23232, & 23254")

```


```{r}
decomp <- wind_avg %>%
  filter(station == "vaca_sac_concord") %>%
  model(classical_decomposition(wind_speed, type = "additive")) %>%
  components() %>%
  autoplot()
decomp

```