Last updated: 2021-09-21

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Overview

This document contains a summary of the model data made available by Morten Skogen of the FACE-IT project.

Svalbard

Kongsfjorden

Model temperatures. There are many more variables available within the models.

__Figure 1:__ A) Average model temperatures at depths for different RCP projections. Note that the model data are not on a cartesian coordinate grid so the data are shown here as points instead of as a raster. B) Trends in model temperatures at different depths and RCP projections. Straight lines show linear models fitted to each point in panel A.

Figure 1: A) Average model temperatures at depths for different RCP projections. Note that the model data are not on a cartesian coordinate grid so the data are shown here as points instead of as a raster. B) Trends in model temperatures at different depths and RCP projections. Straight lines show linear models fitted to each point in panel A.

Isfjorden

__Figure 2:__ A) Average model temperatures at depths for different RCP projections. Note that the model data are not on a cartesian coordinate grid so the data are shown here as points instead of as a raster. B) Trends in model temperatures at different depths and RCP projections. Straight lines show linear models fitted to each point in panel A.

Figure 2: A) Average model temperatures at depths for different RCP projections. Note that the model data are not on a cartesian coordinate grid so the data are shown here as points instead of as a raster. B) Trends in model temperatures at different depths and RCP projections. Straight lines show linear models fitted to each point in panel A.

Inglefieldbukta

__Figure 3:__ A) Average model temperatures at depths for different RCP projections. Note that the model data are not on a cartesian coordinate grid so the data are shown here as points instead of as a raster. B) Trends in model temperatures at different depths and RCP projections. Straight lines show linear models fitted to each point in panel A.

Figure 3: A) Average model temperatures at depths for different RCP projections. Note that the model data are not on a cartesian coordinate grid so the data are shown here as points instead of as a raster. B) Trends in model temperatures at different depths and RCP projections. Straight lines show linear models fitted to each point in panel A.

Greenland

Young Sound

Disko Bay

Nuup Kangerlua

Norway

Porsangerfjorden


R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.6 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

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

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

other attached packages:
 [1] doParallel_1.0.16  iterators_1.0.13   foreach_1.5.1      pangaear_1.1.0    
 [5] sf_1.0-0           sp_1.4-5           RColorBrewer_1.1-2 ggOceanMaps_1.1.9 
 [9] ggspatial_1.1.5    gtable_0.3.0       gridExtra_2.3      PCICt_0.5-4.1     
[13] tidync_0.2.4       forcats_0.5.1      stringr_1.4.0      dplyr_1.0.6       
[17] purrr_0.3.4        readr_1.4.0        tidyr_1.1.3        tibble_3.1.2      
[21] ggplot2_3.3.3      tidyverse_1.3.1   

loaded via a namespace (and not attached):
 [1] colorspace_2.0-1   ggsignif_0.6.2     ellipsis_0.3.2     class_7.3-19      
 [5] rio_0.5.26         rprojroot_2.0.2    fs_1.5.0           rstudioapi_0.13   
 [9] httpcode_0.3.0     proxy_0.4-26       ggpubr_0.4.0       farver_2.1.0      
[13] fansi_0.5.0        lubridate_1.7.10   xml2_1.3.2         splines_4.1.1     
[17] codetools_0.2-18   ncdf4_1.17         ncdump_0.0.3       knitr_1.33        
[21] jsonlite_1.7.2     workflowr_1.6.2    broom_0.7.7        dbplyr_2.1.1      
[25] rgeos_0.5-5        oai_0.3.2          hoardr_0.5.2       compiler_4.1.1    
[29] httr_1.4.2         backports_1.2.1    Matrix_1.3-4       assertthat_0.2.1  
[33] cli_2.5.0          later_1.2.0        htmltools_0.5.1.1  tools_4.1.1       
[37] glue_1.4.2         rappdirs_0.3.3     Rcpp_1.0.6         carData_3.0-4     
[41] cellranger_1.1.0   jquerylib_0.1.4    RNetCDF_2.4-2      raster_3.4-10     
[45] vctrs_0.3.8        crul_1.1.0         nlme_3.1-152       xfun_0.23         
[49] openxlsx_4.2.3     rvest_1.0.0        lifecycle_1.0.0    ncmeta_0.3.0      
[53] rstatix_0.7.0      scales_1.1.1       hms_1.1.0          promises_1.2.0.1  
[57] yaml_2.2.1         curl_4.3.1         sass_0.4.0         stringi_1.6.2     
[61] highr_0.9          e1071_1.7-7        zip_2.2.0          rlang_0.4.11      
[65] pkgconfig_2.0.3    evaluate_0.14      lattice_0.20-44    labeling_0.4.2    
[69] cowplot_1.1.1      tidyselect_1.1.1   plyr_1.8.6         magrittr_2.0.1    
[73] R6_2.5.0           generics_0.1.0     DBI_1.1.1          mgcv_1.8-36       
[77] pillar_1.6.1       haven_2.4.1        foreign_0.8-81     withr_2.4.2       
[81] units_0.7-2        abind_1.4-5        modelr_0.1.8       crayon_1.4.1      
[85] car_3.0-10         KernSmooth_2.23-20 utf8_1.2.1         rmarkdown_2.8     
[89] sfheaders_0.4.0    readxl_1.3.1       data.table_1.14.0  git2r_0.28.0      
[93] reprex_2.0.0       digest_0.6.27      classInt_0.4-3     httpuv_1.6.1      
[97] munsell_0.5.0      viridisLite_0.4.0  bslib_0.2.5.1