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Merge pull request #170 from ropensci/spatialwarnings
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 More vignette work related to other changes.
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elinw committed Apr 14, 2022
2 parents fae6806 + 6c7fd32 commit cb94a91
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Showing 3 changed files with 9 additions and 6 deletions.
2 changes: 2 additions & 0 deletions vignettes/accumulated_cyclone_energy.Rmd
Expand Up @@ -13,6 +13,7 @@ knitr::opts_chunk$set(echo = TRUE,
```{r, message = FALSE}
library(dplyr)
library(ggplot2)
# library(HURDAT)
library(lubridate)
library(readr)
Expand All @@ -35,6 +36,7 @@ To calculate ACE you would want to use the `fstadv` dataset and apply the follow
* select `Wind`

```{r eval=FALSE}
fstadv <- fstadv %>%
filter(hour(Date) %in% c(3, 9, 15, 21),
Status %in% c("Tropical Storm", "Hurricane"),
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5 changes: 3 additions & 2 deletions vignettes/forecast_advisory.Rmd
Expand Up @@ -26,14 +26,15 @@ key <- "AL092008"
adv <- 42
```

```{r}
```{r eval=FALSE}
fstadv <- fstadv %>% filter(Key == key, Adv <= adv)
```

### GIS Advisory Forecast Track, Cone of Uncertainty, and Watches/Warnings

```{r warning=FALSE}
gis_adv <- gis_advisory(key = key, advisory = adv) %>% gis_download()
gis_adv <- gis_advisory(key = key, advisory = adv) %>%
gis_download()
```

Get bounding box of the forecast polygon.
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8 changes: 4 additions & 4 deletions vignettes/gis_data.Rmd
Expand Up @@ -83,7 +83,7 @@ There are several datasets that are published for active cyclones. The following

## Advisory Package

```{r}
```{r warning=FALSE}
gis_advisory(key = "AL182012", advisory = "18")
```

Expand Down Expand Up @@ -146,7 +146,7 @@ Each forecast position is also included in the points dataframe. You can access

Forecast cone data is contained in the polygon dataset. To deal with this dataset you can use the `shp_to_df` function again or take the slightly longer way:

```{r}
```{r warning=FALSE}
fcst_cone <- df.gis_adv$al182012.018_5day_pgn
fcst_cone@data$id <- rownames(fcst_cone@data)
fcst_cone.points <- broom::tidy(fcst_cone, region = "id")
Expand Down Expand Up @@ -184,13 +184,13 @@ In the example above you can see tropical storm warnings issued for the Bahamas,

The Tropical Cyclone Storm Surge Probabilities data shows the probability, in percent, of a specified storm surge occurring during the forecast period indicated. The product is based upon an ensemble of Sea, Lake, and Overland Surge from Hurricanes (SLOSH) model runs using the National Hurricane Center (NHC) official advisory and accounts for track, size, and intensity errors based on historical errors.

```{r}
```{r warning=FALSE}
gis_prob_storm_surge(key = "AL142016",
products = list(psurge = 0),
datetime = "20161006")
```

```{r, eval = FALSE}
```{r, warning=FALSE}
df.gis_storm_surge <-
gis_prob_storm_surge(key = "AL142016",
products = list(psurge = 0),
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