Last updated: 2024-04-22

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Knit directory: bgc_argo_r_argodata/analysis/

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Rmd 86f2f02 mlarriere 2024-04-22 Adding SST anomaly subsection

Task

Dependencies

Outputs

path_emlr_utilities <- "/nfs/kryo/work/jenmueller/emlr_cant/utilities/files/"
path_basin_mask <- "/nfs/kryo/work/datasets/gridded/ocean/interior/reccap2/supplementary/"
path_argo <- '/nfs/kryo/work/datasets/ungridded/3d/ocean/floats/bgc_argo'
path_argo_core <- '/nfs/kryo/work/datasets/ungridded/3d/ocean/floats/core_argo_r_argodata_2024-03-13'

path_argo_core_preprocessed <- paste0(path_argo_core, "/preprocessed_core_data")
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")

# path_mhw<- '/net/kryo/work/datasets/gridded/ocean/2d/obs/mhw'
path_basin_mask <- "/nfs/kryo/work/datasets/gridded/ocean/interior/reccap2/supplementary/"

path_pCO2_products <- "/nfs/kryo/work/datasets/gridded/ocean/2d/observation/pco2/"

SST

Load data and create climatology 2004-2019 (mean value)

pco2_product <- read_ncdf(paste0(path_pCO2_products, "VLIZ-SOM_FFN/VLIZ-SOM_FFN_inputs.nc"),
                          var = "sst",
                          ignore_bounds = TRUE,
                          make_units = FALSE)
 
pco2_product <- pco2_product %>%
  as_tibble()

pco2_product <- pco2_product %>%
  mutate(across(-c(lon, lat, time), ~ replace(., . >= 1e+19, NA)))

pco2_product <-  pco2_product %>%
  mutate(year = year(time),
         month = month(time))
  
sst_2004_2019_natlantic<- pco2_product %>% 
  filter(year>2004, year<2019, !is.na(sst), lat > 0, lon <30, lon >-100)

climato_2004_2019<-sst_2004_2019_natlantic %>% 
  group_by(month, lat, lon) %>% 
  summarize(mean_temp=mean(sst, na.rm=TRUE))

SST map

#Base map 
world_coordinates <- map_data("world") 
  
base_map <-ggplot() +  
  geom_map(data = world_coordinates, map = world_coordinates, 
    aes(long, lat, map_id = region))

#Restrict base map to North Atlantic Ocean
base_map <- base_map + lims(x= c(-100, 50), y = c(0, 80))


mean_temperature_map<- base_map +
  geom_tile(data=climato_2004_2019, aes(x = lon, y = lat, fill = mean_temp)) +
  scale_fill_viridis_c() +
  labs(title= "Mean temperature in North atlantic", 
       subtitle= "Period: 2004 - 2019", 
       x = "Longitude", y = "Latitude", fill = "Mean SST (°C)") +
  theme(legend.position = 'right')

print(mean_temperature_map)

SST anomaly map

sst_2023_natlantic<- pco2_product %>% 
  filter(year==2023, !is.na(sst), lat > 0, lon <30, lon >-100)

merged_data <- merge(sst_2023_natlantic, climato_2004_2019, by = c("month", "lat", "lon")) %>% 
  as.tibble()
merged_data$anomaly<- merged_data$sst - merged_data$mean_temp

sst_anomaly_2023_natlantic<-merged_data %>% 
  select(lat,lon,month, time, anomaly)

anomaly_sst_2023_map <- 
  base_map + 
  geom_tile(data=sst_anomaly_2023_natlantic, aes(x = lon, y = lat, fill = anomaly)) +
  scale_fill_distiller(palette = "RdBu", direction = -1) +
  labs(title = "Temperature Anomaly per month in North Atlantic (2023)", 
       subtitle = "climatology 2004-2019",
       x = "Longitude", y = "Latitude") +
  theme(legend.position = 'right') +
  facet_wrap(~ month, ncol=2) 

print(anomaly_sst_2023_map)

Write file

write_rds(sst_anomaly_2023_natlantic, 
          file = paste0(path_argo_core_preprocessed,"/", "SST_anomaly2023_clim2004-2019.rds"))

sessionInfo()
R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.5

Matrix products: default
BLAS:   /usr/local/R-4.2.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.2.2/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] RColorBrewer_1.1-3   stars_0.6-0          sf_1.0-9            
 [4] abind_1.4-5          broom_1.0.5          paletteer_1.6.0     
 [7] cluster_2.1.6        gridExtra_2.3        scatterplot3d_0.3-44
[10] viridis_0.6.2        viridisLite_0.4.1    ggOceanMaps_1.3.4   
[13] ggspatial_1.1.7      oce_1.7-10           gsw_1.1-1           
[16] lubridate_1.9.0      timechange_0.1.1     forcats_0.5.2       
[19] stringr_1.5.0        dplyr_1.1.3          purrr_1.0.2         
[22] readr_2.1.3          tidyr_1.3.0          tibble_3.2.1        
[25] ggplot2_3.4.4        tidyverse_1.3.2      workflowr_1.7.0     

loaded via a namespace (and not attached):
 [1] googledrive_2.0.0   colorspace_2.0-3    ellipsis_0.3.2     
 [4] class_7.3-20        rprojroot_2.0.3     fs_1.5.2           
 [7] rstudioapi_0.15.0   proxy_0.4-27        farver_2.1.1       
[10] fansi_1.0.3         xml2_1.3.3          codetools_0.2-18   
[13] cachem_1.0.6        knitr_1.41          jsonlite_1.8.3     
[16] dbplyr_2.2.1        rgeos_0.5-9         compiler_4.2.2     
[19] httr_1.4.4          backports_1.4.1     assertthat_0.2.1   
[22] fastmap_1.1.0       gargle_1.2.1        cli_3.6.1          
[25] later_1.3.0         htmltools_0.5.8.1   tools_4.2.2        
[28] gtable_0.3.1        glue_1.6.2          maps_3.4.1         
[31] Rcpp_1.0.10         cellranger_1.1.0    jquerylib_0.1.4    
[34] RNetCDF_2.6-1       raster_3.6-11       vctrs_0.6.4        
[37] lwgeom_0.2-10       xfun_0.35           ps_1.7.2           
[40] rvest_1.0.3         lifecycle_1.0.3     ncmeta_0.3.5       
[43] googlesheets4_1.0.1 terra_1.7-65        getPass_0.2-2      
[46] scales_1.2.1        hms_1.1.2           promises_1.2.0.1   
[49] parallel_4.2.2      rematch2_2.1.2      yaml_2.3.6         
[52] sass_0.4.4          stringi_1.7.8       highr_0.9          
[55] e1071_1.7-12        rlang_1.1.1         pkgconfig_2.0.3    
[58] evaluate_0.18       lattice_0.20-45     labeling_0.4.2     
[61] processx_3.8.0      tidyselect_1.2.0    magrittr_2.0.3     
[64] R6_2.5.1            generics_0.1.3      DBI_1.2.2          
[67] pillar_1.9.0        haven_2.5.1         whisker_0.4        
[70] withr_2.5.0         units_0.8-0         sp_1.5-1           
[73] modelr_0.1.10       crayon_1.5.2        KernSmooth_2.23-20 
[76] utf8_1.2.2          tzdb_0.3.0          rmarkdown_2.18     
[79] grid_4.2.2          readxl_1.4.1        callr_3.7.3        
[82] git2r_0.30.1        reprex_2.0.2        digest_0.6.30      
[85] classInt_0.4-8      httpuv_1.6.6        munsell_0.5.0      
[88] bslib_0.4.1