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Oceanic, atmospheric, and climate data in Python and R.

Welcome to my portafolio

Roger Revelle

Oceanographer

https://rpubs.com/emeneses/937382

Notes of Waves in Oceanic and Coastal Waters book by Holthuijsen 2007 made with R-markdown

Inter-islands maritime traffic disruption in Las Palmas: Meteoceanic conditions and economic impacts

### Python Script and repository

Data here:

[https://github.com/estebanmeneses/python-dashboard ](https://github.com/estebanmeneses/python-dashboard)

(This dashboard was made originally by Thu Vu) you can see her youtube channel here: (<https://www.youtube.com/watch?v=uhxiXOTKzfs&t=26s>)





Nowadays is highly useful to show your data interactively.

Interactive dashboard in Python of CO2 emissions

# Sea Surface Mean Temperature

Data donwloaded from here:

<https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-oras5?tab=form>

First, create an account, then sign in and get it

upload r packages

```
library(ncdf4)
library(raster)
```

open your netcdf files from your directory and make it writable

```
nc <- nc_open("Inputs_and_Data/sst_1958_2022.nc", write = T)

```

Explore the dataset

```
nc$var$sosstsst
tail(nc$var$nav_lat)
nc$dim$time_counter
tail(nc$dim$lon$vals) # -179.98 to 179
tail(nc$dim$lat$vals) # -89.98 to -89.98
nc$dim$time$vals 
nc2$dim$time
nc2$var$time
```

Get some variables

```
lon <- ncvar_get(nc, 'lon')
lat <- ncvar_get(nc, 'lat')
temp <- ncvar_get(nc, 'sosstsst')
time <- ncvar_get(nc, 'time_counter')
head(time)
```

Transform date variable

```
library(chron)


month.day.year(time, c(month = 1, day = 1, year = 2011))
time2 <- month.day.year(time/86400, c(month = 1, day = 1, year = 1981))
month <- time2$month
day <- time2$day
year <- time2$year
dates_df <- cbind(year, month, day)
dates_df <- as.data.frame(dates_df)
vec_time <- paste(dates_df$year, dates_df$month, dates_df$day, sep = '-')
vec_time
```

### rasters from netcdf files

```
library(oceanmap)


sst <- nc2raster(nc, varname = 'sosstsst')
```

Calculate the mean of all layers of sea surface temperature

```
mean_nc2 <- calc(sst, fun = mean)
```

Map mean sea surface temperature

```


extent(mean_nc2) <- extent(-180, 180, -77, 90)

v(mean_nc2,  replace.na= F, v_contour = T, fill = T, 
  cb.title = "(\u00B0C)", cbpos='r', )#cb= colorbar|RasterStack object
```



Sunset fishing is a beautiful time of day to relax and get in touch with nature

Mean Sea Surface Temperature 1958 - 2022

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Towards a better understanding of climate and its upcoming challenges

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