hotssea_surface_salinity_min: Load or download the HOTSSea model output

In pbs-assess/PACea: An R package of Pacific ecosystem information to help facilitate an ecosystem approach to fisheries management

Load or download the HOTSSea model output

Description

Loading and/or downloading model output from HOTSsea physical hindcast of the Salish Sea model. Loads it into your R environment from your local cache, and if it has not been previously downloaded will first download it from Zenodo into your local cache. To download all HOTSsea model output in one go (recommended), first use the function [hotssea_all_variables()]. See the hotssea vignette for further explanations.

Usage

hotssea_surface_salinity_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_salinity_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_salinity_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_salinity_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_temperature_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_temperature_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_temperature_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_surface_temperature_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_salinity_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_salinity_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_salinity_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_salinity_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_temperature_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_temperature_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_temperature_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg0to30m_temperature_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_salinity_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_salinity_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_salinity_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_salinity_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_temperature_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_temperature_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_temperature_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg30to150m_temperature_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_salinity_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_salinity_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_salinity_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_salinity_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_temperature_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_temperature_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_temperature_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_avg150toBot_temperature_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_salinity_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_salinity_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_salinity_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_salinity_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_temperature_min(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_temperature_mean(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_temperature_max(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

hotssea_bottom_temperature_std(
  update = FALSE,
  ask = interactive(),
  force = FALSE,
  version = "01",
  cache_subfolder = "hotssea"
)

Arguments

update	Logical. Would you like to check for a newer version of the layer?
ask	Logical. Should the user be asked before downloading the data to local cache? Defaults to the value of interactive().
force	Logical. Should download of data be forced? Overrides 'ask' argument if TRUE.
version	character Version number of data as saved on Zenodo. Only currently works for "01" as that's all that is currently available.
cache_subfolder	character. Subfolder to put or look for the objects; defaults to 'hotssea' and it is best to stick with this. The objects will be put in your 'paste0(pacea::pacea_cache(), cache_subfolder)' directory.

Format

A simple features dataframe.

Details

The Hindcast of the Salish Sea (HOTSSea) is a physical ocean model that recreates conditions throughout the Salish Sea from 1980 to 2018, filling in the gaps in patchy measurements Oldford et al., (in review). The model predicts physical ocean properties with sufficient accuracy to be useful for a variety of applications. It corroborates observed ocean temperature trends and can examine areas with few observations. Results indicate that some seasons and areas are warming faster than others. HOTSSea was developed using the Nucleus for European Modelling of the Ocean (NEMO) engine, and temperature and salinty outputs are included in pacea (from version 1 of HOTSSea).

The HOTSSea outputs in pacea are adapted from results provided by Greig Oldford (Fisheries and Oceans Canada). For model details see Oldford et al., (in review), which should be read and cited if you use the results, and Greig and Andrew Edwards should be consulted for any clarifications and uses of the results.

The following 40 functions serve to download specific individual ocean calculations related to temperature or salinity from the HOTSSea model. If a variable has already been downloaded, the function will load data from the ‘hotssea' subfolder in the user’s ‘pacea_cache()' folder into user’s local R environment. Each file is around 3-9 Mb, but should not take long to download.

The 40 variables available are desribed below as their respective functions. The variables are listed in the object 'hotssea_data'. The variables are stored on Zenodo, with [get_zenodo_data()] automatically taking care of the DOI address for the one-time download. #' #'

hotssea_*depth*_temperature()_*statistic* Temperature in oC
hotssea_*depth*_salinity() Salinity in PSU

NOTE:
*depth* must be replaced by one of the following depth categories:

surfacesea surface, the top model cell at that location
avg0to30mdepth-integrated average over 0-30 m
avg30to150mdepth-integrated average over 30-150 m
150toBot depth-integrated from 150 m to the bottom cell
bottomsea bottom, the bottom model cell at that location

#' *statistic* must be replaced by one of the following statistics:

minminimum daily mean over the month
meanmean daily mean over the month
maxmaximum daily mean over the month
std standard deviation of the daily means for the month

The five permissable depth values for four types of statistics for both temperature and salinity yield the 40 different combinations. For example, 'hotssea_avg0to30m_temperature_max()' refers to the mean (over the top 30 m) of each modelled depths' maximum (over the month) daily mean temperature. See the hotssea vignette for explicit explanation of these calculations; in particular the '*statistic* is calculated for all cells before the depth averaging is performed.

Explicit details of the vertical resolution of the original HOTSSea model results are as follows (also see Oldford et al., in review). The vertical grid for HOTSSea v1 is divided into 40 vertical levels that are gradually stretched to achieve higher resolution at the surface, ranging from 1 m vertical resolution in the upper 10 m to approximately 27 m widths at the deepest level (~420 m). When time-dynamic variation is ignored, the 'surface' '0-4 m' depth range is more precisely the 0-4.0000467 m depth range, the '0-30 m' depth range is more precisely the 0-31.101 m depth range, and the '0-150 m' depth range is more precisely the 0-147.089 m. Although depth interpolation schemes may be used to extract model outputs from precise depths, these schemes introduce biases, are potentially computationally costly, and are unlikely to change the extracted values enough to be worth it when working at monthly time scales. In addition, the thickness of each layer is proportionally scaled at each time-step as sea surface height changes using a nonlinear free-surface scheme referred to as the 'variable volume option' in the NEMO model framework. The datum heights of model outputs therefore vary dynamically in space and time because the NEMO model vertical depth level widths vary dynamically with sea surface height. For example, if sea surface height varies on the order of seconds or minutes due to, say, wind-driven wave action, then hourly, daily, and monthly model depths are time-integrated means for a given grid cells. The 'variable volume option' is another reason why a simpler approach than depth interpolation was used when extracting and wrangling HOTSSea v1 model outputs. 'Surface' is defined in the monthly mean HOTSSea v1 outputs as 0 to ~4 m (rather than, say 0 to ~1 m) because model biases are most pronounced at the shallowest depth (0 to ~1 m). On the monthly scale, conditions throughout the model domain are generally similar between 0.5 m and 4 m (mean depth-integrated differences of approximately < 0.25 Celcius and 0.2 PSU) and biases > 2 m are substantially lower. Vertical averaging of model results from 0 to 4 m was therefore chosen based on analyses of spatial-temporal model performance to lessen the impact of model error - more in-depth analyses are given in Oldford et al. (in review).

Value

'sf' data object requested.

Source

Oldford, G.L., Jarníková, T., Christensen, V., and Dunphy, M. (in review). HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development. Preprint. https://doi.org/10.5194/gmd-2024-58

Examples

## Not run: 
h <- hotssea_bottom_salinity_min()
plot(h)

## End(Not run)

pbs-assess/PACea documentation built on April 17, 2025, 11:36 p.m.