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Knit directory: emlr_obs_v_XXX/
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library(tidyverse)The following local parametrisations (i.e. relevant for this sensitivity run) were defined to run the analysis:
# neutral density thresholds to cut the Atlantic ocean into slabs
slabs_Atl <-
c(
-Inf,
26.00,
26.50,
26.75,
27.00,
27.25,
27.50,
27.75,
27.85,
27.95,
28.05,
28.10,
28.15,
28.20,
Inf
)
# neutral density thresholds to cut the Indo-Pacific ocean into slabs
slabs_Ind_Pac <-
c(-Inf,
26.00,
26.50,
26.75,
27.00,
27.25,
27.50,
27.75,
27.85,
27.95,
28.05,
28.10,
Inf)
# MLR model to be fitted with all predictors taken into account
# Please note that for the mapping step, predictors need to be adjusted manually
MLR_full_model <- "cstar ~
sal +
tem +
aou +
oxygen +
silicate +
phosphate +
phosphate_star"
params_local <-
lst(
# ID of current sensitivity run
Version_ID = "v_XXX",
# f flags accepted for GLODAP data
flag_f = c(2),
# qc flags accepted for GLODAP data
flag_qc = 1,
# Shallowest depth for data to be included in MLR fitting
depth_min = 150,
# Shallowest water depth for data to be included in MLR fitting
bottomdepth_min = 0,
# Lowest neutral density to map Cant with eMLR approach
gamma_min = 26,
# break years for eras, numbers indicate the upper end of the respective era
era_breaks = c(1981, 1999, 2012, Inf),
# see above
MLR_full_model = MLR_full_model,
# Maxmimum number of MLR predictors
predictors_max = 5,
# Minimum number of MLR predictors
predictors_min = 2,
# Total number of MLR fits taken into account
MLR_number = 10,
# see above
slabs_Atl = slabs_Atl,
# see above
slabs_Ind_Pac = slabs_Ind_Pac,
# Stoichiometric ratio of C to P
rCP = 117,
# Stoichiometric ratio of N to P
rNP = 16,
# Stoichiometric ratio of P to O (PO4* calculation)
rPO = 170,
# Offset P to O (PO4* calculation)
rPO_offset = 1.95,
# Preindustrial atmospheric pCO2
preind_atm_pCO2 = 280,
# generate a high number of diagnostic plots while running the analysis (y/n)
plot_all_figures = "n"
)params_local %>%
write_rds(here::here("data/auxillary",
"params_local.rds"))
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.1
Matrix products: default
BLAS: /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/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] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.2 purrr_0.3.4
[5] readr_1.4.0 tidyr_1.1.2 tibble_3.0.4 ggplot2_3.3.2
[9] tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] tidyselect_1.1.0 xfun_0.18 haven_2.3.1 colorspace_2.0-0
[5] vctrs_0.3.5 generics_0.0.2 htmltools_0.5.0 yaml_2.2.1
[9] blob_1.2.1 rlang_0.4.9 later_1.1.0.1 pillar_1.4.7
[13] withr_2.3.0 glue_1.4.2 DBI_1.1.0 dbplyr_1.4.4
[17] modelr_0.1.8 readxl_1.3.1 lifecycle_0.2.0 munsell_0.5.0
[21] gtable_0.3.0 cellranger_1.1.0 rvest_0.3.6 evaluate_0.14
[25] knitr_1.30 httpuv_1.5.4 fansi_0.4.1 broom_0.7.2
[29] Rcpp_1.0.5 promises_1.1.1 backports_1.1.10 scales_1.1.1
[33] jsonlite_1.7.1 fs_1.5.0 hms_0.5.3 digest_0.6.27
[37] stringi_1.5.3 rprojroot_2.0.2 grid_4.0.3 here_0.1
[41] cli_2.2.0 tools_4.0.3 magrittr_2.0.1 crayon_1.3.4
[45] whisker_0.4 pkgconfig_2.0.3 ellipsis_0.3.1 xml2_1.3.2
[49] reprex_0.3.0 lubridate_1.7.9 assertthat_0.2.1 rmarkdown_2.5
[53] httr_1.4.2 rstudioapi_0.13 R6_2.5.0 git2r_0.27.1
[57] compiler_4.0.3