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GettingStarted_Bering10K_ROMSNPZ.tex
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\title{Getting Started with Bering10K Level 2 \& 3 indices}
\author{K. Holsman and K. Aydin (Tutorial), A. Hermann, K. Kearney, W.
Cheng, I. Ortiz (Bering10K)}
\date{}
\begin{document}
\maketitle
{
\setcounter{tocdepth}{2}
\tableofcontents
}
\begin{figure}
\centering
\includegraphics[width=1\textwidth,height=\textheight]{Figs/logos2.jpg}
\caption{The ACLIM2 Repository
\href{https://github.com/kholsman/ACLIM2}{\textbf{github.com/kholsman/ACLIM2}}
is maintained by \textbf{\href{mailto:[email protected]}{Kirstin
Holsman}}, Alaska Fisheries Science Center, NOAA Fisheries, Seattle WA.
Multiple programs and projects have supported the production and sharing
of the suite of Bering10K hindcasts and projections. \emph{Last updated:
Apr 28, 2022}}
\end{figure}
\hypertarget{overview}{%
\section{1. Overview}\label{overview}}
This repository contains R code and Rdata files for working with
netcdf-format data generated from the
\href{https://beringnpz.github.io/roms-bering-sea}{\textbf{downscaled
ROMSNPZ modeling}} of the ROMSNPZ Bering Sea Ocean Modeling team; Drs.
Hermann, Cheng, Kearney, Pilcher,Ortiz, and Aydin. The code and R
resources described in this tutorial are publicly available through the
\href{https://github.com/kholsman/ACLIM2}{\textbf{ACLIM2 github
repository}} maintained by
\href{mailto:[email protected]}{Kirstin Holsman} as part of
NOAA's
\href{https://www.fisheries.noaa.gov/alaska/ecosystems/alaska-climate-integrated-modeling-project}{\textbf{ACLIM
project}} for the Bering Sea. \emph{See
\href{https://www.frontiersin.org/articles/10.3389/fmars.2019.00775/full}{Hollowed
et al.~2020} for more information about the ACLIM project.}
\hypertarget{resources}{%
\subsection{1.1. Resources}\label{resources}}
We \textbf{strongly recommend} reviewing the following documentation
before using the data in order to understand the origin of the indices
and their present level of skill and validation, which varies
considerably across indices and in space and time:
\begin{itemize}
\item
\href{https://zenodo.org/record/4586950/files/Bering10K_dataset_documentation.pdf}{\textbf{The
Bering10K Dataset documentation (pdf)}}: A pdf describing the dataset,
including full model descriptions, inputs for specific results, and a
tutorial for working directly with the ROMS native grid (Level 1
outputs).
\item
\href{https://zenodo.org/record/4586950/files/Bering10K_simulation_variables.xlsx?download=1}{\textbf{Bering10K
Simulaton Variables (xlsx)}}: A spreadsheet listing all simulations
and the archived output variables associated with each, updated
periodically as new simulations are run or new variables are made
available.
\item
A
\href{https://beringnpz.github.io/roms-bering-sea/B10K-dataset-docs/}{\textbf{collection}}
of Bering10K ROMSNPZ model documentation (including the above files)
is maintained by \href{mailto:[email protected]}{Kelly Kearney}
and will be regularly updated with new documentation and publications.
\end{itemize}
\hypertarget{guildlines-for-use-and-citation-of-the-data}{%
\subsection{1.2 Guildlines for use and citation of the
data}\label{guildlines-for-use-and-citation-of-the-data}}
The data described here are published and publicly available for use,
except as explicitly noted. However, for novel uses of the data, it is
\textbf{strongly recommended} that you consult with and consider
including at least one author from the ROMSNPZ team (Drs. Hermann,
Cheng, Kearney, Pilcher, Aydin, Ortiz). There are multiple spatial and
temporal caveats that are best described in discussions with the authors
of these data and inclusion as co-authors will facilitate appropriate
application and interpretation.
\hypertarget{the-bering-10k-model-v.-h16-with-10-depth-layers}{%
\subsubsection{1.2.1. The Bering 10K Model (v. H16) with 10 depth
layers}\label{the-bering-10k-model-v.-h16-with-10-depth-layers}}
The H16 model is the original BSIERP era 10 depth layer model with a 10
Km grid. This version was used in ACLIM1.0 to dynamically downscaled 3
global scale general circulation models (GCMs) under two CMIP
(\href{https://www.wcrp-climate.org/wgcm-cmip}{Coupled Model
Intercomparison Project}{]}) phase 5 representative carbon pathways
(RCP): RCP 4.5 or ``moderate global carbon mitigation'' and RCP 8.5
``high baseline global carbon emissions''. Details of the model and
projections can be found in:
\begin{itemize}
\item
\textbf{Hindcast (1979-2012; updated to 2018 during ACLIM 1.0):}
Hermann, A. J., G. A. Gibson, N. A. Bond, E. N. Curchitser, K.
Hedstrom, W. Cheng, M. Wang, E. D. Cokelet, P. J. Stabeno, and K.
Aydin. 2016. Projected future biophysical states of the Bering Sea.
Deep Sea Research Part II: Topical Studies in Oceanography 134:30--47.
\href{http://dx.doi.org/10.1016/j.dsr2.2015.11.001}{doi:10.1016/j.dsr2.2015.11.001}
\item
\textbf{Projections of the H16 10 layer model using CMIP5 scenarios:}
Hermann, A. J., G. A. Gibson, W. Cheng, I. Ortiz, K. Aydin, M. Wang,
A. B. Hollowed, K. K. Holsman, and S. Sathyendranath. 2019. Projected
biophysical conditions of the Bering Sea to 2100 under multiple
emission scenarios. ICES Journal of Marine Science 76:1280--1304.
\href{https://academic.oup.com/icesjms/article/76/5/1280/5477847?login=true}{doi:10.1093/icesjms/fsz043}
\end{itemize}
\hypertarget{the-bering-10k-model-v.-k20-with-30-depth-layers-and-other-advancements}{%
\subsubsection{1.2.2. The Bering 10K Model (v. K20) with 30 depth layers
and other
advancements}\label{the-bering-10k-model-v.-k20-with-30-depth-layers-and-other-advancements}}
The Bering10K model was subsequently updated by Kearney et al.~2020 (30
layer and other NPZ updates) and Pilcher et al .2019 (OA and O2
dynamics) and this version is used for the projections in ACLIM2.0 under
the most recent CMIP phase 6.
\begin{itemize}
\item
\textbf{Hindcast (1979-2020 hindcast with OA dynamics used in ACLIM
2.0):}
Kearney, K., A. Hermann, W. Cheng, I. Ortiz, and K. Aydin. 2020. A
coupled pelagic-benthic-sympagic biogeochemical model for the Bering
Sea: documentation and validation of the BESTNPZ model (v2019.08.23)
within a high-resolution regional ocean model. Geoscientific Model
Development 13:597--650.
\href{https://doi.org/10.5194/gmd-13-597-2020}{doi:10.5194/gmd-13-597-2020}
Pilcher, D. J., D. M. Naiman, J. N. Cross, A. J. Hermann, S. A.
Siedlecki, G. A. Gibson, and J. T. Mathis. 2019. Modeled Effect of
Coastal Biogeochemical Processes, Climate Variability, and Ocean
Acidification on Aragonite Saturation State in the Bering Sea.
Frontiers in Marine Science 5:1--18.
\href{https://www.frontiersin.org/articles/10.3389/fmars.2018.00508/full}{doi:
10.3389/fmars.2018.00508}
\end{itemize}
\hypertarget{installation}{%
\section{2. Installation}\label{installation}}
\hypertarget{minimal-install}{%
\subsection{2.1 Minimal Install}\label{minimal-install}}
A minimal R install (for Sections 3.2 and 4.1 only) requires installing
the \texttt{ncdf4}, \texttt{devtools} libraries (available on CRAN), and
\texttt{thredds} R library through its github site:
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{install.packages}\NormalTok{(}\StringTok{"devtools"}\NormalTok{)}
\FunctionTok{install.packages}\NormalTok{(}\StringTok{"ncdf4"}\NormalTok{)}
\NormalTok{ devtools}\SpecialCharTok{::}\FunctionTok{install\_github}\NormalTok{(}\StringTok{"bocinsky/thredds"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}
Note that each of these has multiple sub-dependent libraries and may
take several minutes to install. \emph{The full install below includes
installation of these packages, so you don't need to perform this step
if you perform the full install.}
\hypertarget{full-install}{%
\subsection{2.2 Full install}\label{full-install}}
The full install consists of the full directory structure in the ACLIM2
Repo; this includes a substantial set of resource files including shape
files and data for performing Bering Sea spatial analysis in R. This
will eventually become a library package, but currently requires manual
downloading of the full directory structure from github. The full
install may take up to \textbf{1GB of disk space} (initial download
\textasciitilde12MB).
\hypertarget{option-1-clone-the-repository}{%
\subsubsection{Option 1: Clone the
repository}\label{option-1-clone-the-repository}}
If you have git installed and can work with it, this is the preferred
method as it preserves all directory structure and can aid in future
updating. Use this from a \textbf{terminal command line, not in R}, to
clone the full ACLIM2 directory and subdirectories:
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{git}\NormalTok{ clone https://github.com/kholsman/ACLIM2.git}
\end{Highlighting}
\end{Shaded}
\hypertarget{option-2-download-the-repository}{%
\subsubsection{Option 2: Download the
repository}\label{option-2-download-the-repository}}
Download the full zip archive directly from the
\href{https://github.com/kholsman/ACLIM2}{\textbf{ACLIM2 Repo}} using
this link:
\href{https://github.com/kholsman/ACLIM2/archive/main.zip}{\textbf{https://github.com/kholsman/ACLIM2/archive/main.zip}},
and unzip its contents while preserving directory structure.
\textbf{\emph{Important:}} if downloading from zip, please
\textbf{rename the root folder} from \texttt{ACLIM2-main} (in the
zipfile) to \texttt{ACLIM2} (name used in cloned copies) after
unzipping, for consistency in the following examples.
\hypertarget{option-3-use-r-to-download-the-repository}{%
\subsubsection{Option 3: Use R to download the
repository}\label{option-3-use-r-to-download-the-repository}}
This set of commands, run within R, downloads the ACLIM2 repository and
unpacks it, with the ACLIM2 directory structrue being located in the
specified \texttt{download\_path}. This also performs the folder
renaming mentioned in Option 2.
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# Specify the download directory}
\NormalTok{ main\_nm }\OtherTok{\textless{}{-}} \StringTok{"ACLIM2"}
\CommentTok{\# Note: Edit download\_path for preference}
\NormalTok{ download\_path }\OtherTok{\textless{}{-}} \FunctionTok{path.expand}\NormalTok{(}\StringTok{"\textasciitilde{}/desktop"}\NormalTok{)}
\NormalTok{ dest\_fldr }\OtherTok{\textless{}{-}} \FunctionTok{file.path}\NormalTok{(download\_path,main\_nm)}
\NormalTok{ url }\OtherTok{\textless{}{-}} \StringTok{"https://github.com/kholsman/ACLIM2/archive/main.zip"}
\NormalTok{ dest\_file }\OtherTok{\textless{}{-}} \FunctionTok{file.path}\NormalTok{(download\_path,}\FunctionTok{paste0}\NormalTok{(main\_nm,}\StringTok{".zip"}\NormalTok{))}
\FunctionTok{download.file}\NormalTok{(}\AttributeTok{url=}\NormalTok{url, }\AttributeTok{destfile=}\NormalTok{dest\_file)}
\CommentTok{\# unzip the .zip file}
\FunctionTok{setwd}\NormalTok{(download\_path)}
\FunctionTok{unzip}\NormalTok{ (dest\_file, }\AttributeTok{exdir =} \StringTok{"./"}\NormalTok{,}\AttributeTok{overwrite =}\NormalTok{ T)}
\CommentTok{\#rename the unzipped folder from ACLIM2{-}main to ACLIM2}
\FunctionTok{file.rename}\NormalTok{(}\FunctionTok{paste0}\NormalTok{(main\_nm,}\StringTok{"{-}main"}\NormalTok{), main\_nm)}
\FunctionTok{setwd}\NormalTok{(main\_nm)}
\end{Highlighting}
\end{Shaded}
\hypertarget{set-up-envionment-and-get-shapefiles-full-install}{%
\subsection{2.3 Set up envionment and get shapefiles (full
install)}\label{set-up-envionment-and-get-shapefiles-full-install}}
The remainder of this tutorial was tested in RStudio. This may work in
``plain'' R, but is untested. If you are using RStudio, open
\texttt{ACLIM2.Rproj} in Rstudio. If using R, use \texttt{setwd()} to
get to the main ACLIM2 directory. Then run:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\CommentTok{\# SETUP WORKSPACE}
\NormalTok{ tmstp }\OtherTok{\textless{}{-}} \FunctionTok{format}\NormalTok{(}\FunctionTok{Sys.time}\NormalTok{(), }\StringTok{"\%Y\_\%m\_\%d"}\NormalTok{)}
\NormalTok{ main }\OtherTok{\textless{}{-}} \FunctionTok{getwd}\NormalTok{() }\CommentTok{\#"\textasciitilde{}/GitHub\_new/ACLIM2}
\FunctionTok{suppressWarnings}\NormalTok{(}\FunctionTok{source}\NormalTok{(}\StringTok{"R/make.R"}\NormalTok{))}
\FunctionTok{suppressWarnings}\NormalTok{(}\FunctionTok{source}\NormalTok{(}\StringTok{"R/sub\_scripts/load\_maps.R"}\NormalTok{)) }\CommentTok{\# skip this for faster load}
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\end{Highlighting}
\end{Shaded}
The \texttt{R/make.R} command will install missing libraries (including
those listed under the minimal install) and download and process
multiple shapefiles for geographic analysis, it takes several minutes
depending on bandwidth.
\hypertarget{get-romsnpz-data}{%
\section{3. Get ROMSNPZ data}\label{get-romsnpz-data}}
The ROMSNPZ team has been working with
\href{mailto:[email protected]}{Roland Schweitzer} and
\href{mailto:[email protected]}{Peggy Sullivan} to develop the
ACLIM Live Access Server (LAS) to publicly host the published CMIP5
hindcasts and downscaled projections. This server is in beta testing
phase and can be accessed at the following links:
\begin{itemize}
\item
\href{https://data.pmel.noaa.gov/aclim/las/}{LAS custom ROMSNPZ data
exploration, query, mapping, and plotting tool}
\item
\href{https://data.pmel.noaa.gov/aclim/erddap/}{ERDAPP ACLIM data
access tool}
\item
\href{https://data.pmel.noaa.gov/aclim/thredds/}{THREDDS ACLIM direct
data access}
\end{itemize}
Currently, the public data includes hindcasts \& CMIP5 climate
projections.
\hypertarget{available-data}{%
\subsection{3.1 Available data}\label{available-data}}
\begin{itemize}
\tightlist
\item
\texttt{Level1} : (full grid, native ROMS coordinates, full suite of
variables).
\item
\texttt{Level2} : (full grid, rotated to lat lon from the native
ROMSNPZ grid, weekly averages)
\begin{itemize}
\tightlist
\item
\texttt{Bottom\ 5m} : subset of variables from the bottom 5 m of the
water column
\item
\texttt{Surface\ 5m} : subset of variables for the surface 5 m of
the water column
\item
\texttt{Integrated}: watercolumn integrated averages or totals for
various variables
\end{itemize}
\item
\texttt{Level3}: two post-processed datasets
\begin{itemize}
\tightlist
\item
\texttt{ACLIMsurveyrep-x.nc.}: Survey replicated (variables
``sampled'' at the average location and date that each groundfish
survey is sampled)\emph{(Note that the resampling stations need to
be removed before creating bottom temperature maps)}\\
\item
\texttt{ACLIMregion-xnc.}:weekly variables averaged for each survey
strata \emph{(Note that area (km2) weighting should be used to
combine values across multiple strata)}
\end{itemize}
\end{itemize}
For all files the general naming convention of the folders is:
\texttt{B10K-{[}ROMSNPZ\ version{]}\_{[}CMIP{]}\_{[}GCM{]}\_{[}carbon\ scenario{]}}.
For example, the CMIP5 set of indices was downscaled using the H16
(Hermann et al.~2016) version of the ROMSNPZ. Three models were used to
force boundary conditions( MIROC, CESM, and GFDL) under 2 carbon
scenarios RCP 8.5 and RCP 4.5. So to see an individual trajectory we
might look in the level3 (timeseries indices) folder under
\texttt{B10K-H16\_CMIP5\_CESM\_rcp45}, which would be the B10K version
H16 of the CMIP5 CESM model under RCP4.5.
\hypertarget{access-using-minimal-installation}{%
\subsection{3.2 Access using minimal
installation}\label{access-using-minimal-installation}}
The \href{https://data.pmel.noaa.gov/aclim/thredds/}{ACLIM Thredds
server} provides a directory structure and filenames/paths for
individual hindcasts and projections. The latest hindcast, using the
naming scheme described above, is \texttt{B10K-K20\_CORECFS}. Clicking
through the directory shows organization by Level (Levels 1-3), possibly
a subdirectory for variable type (depends on Level), then finally a
catalog page with metadata and the OPENDAP address.
\begin{figure}
\centering
\includegraphics[width=1\textwidth,height=\textheight]{Figs/catalog.jpg}
\caption{Thredds Catalog page.}
\end{figure}
The OPENDAP address (ending in .nc) is used to open a connection between
R and the nc files associated with that data:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# Only required libraries for direct extraction {-} works in plain R}
\FunctionTok{library}\NormalTok{(ncdf4)}
\FunctionTok{library}\NormalTok{(thredds) }
\CommentTok{\# Note: Still ironing out inconsistencies in naming scheme for datasets {-}}
\CommentTok{\# browse to metadata on thredds server to check current names.}
\CommentTok{\# PMEL thredds server (for all available data)}
\NormalTok{ url\_base }\OtherTok{\textless{}{-}} \StringTok{"https://data.pmel.noaa.gov/aclim/thredds/"}
\CommentTok{\# List available runs for whole server}
\FunctionTok{tds\_list\_datasets}\NormalTok{(url\_base)}
\CommentTok{\# Dataset address for hindcast Level2 data}
\NormalTok{ dataset }\OtherTok{\textless{}{-}} \StringTok{"B10K{-}K20\_CORECFS/Level2.html"}
\CommentTok{\# List available data for Level2 hindcast}
\FunctionTok{tds\_list\_datasets}\NormalTok{(}\FunctionTok{paste}\NormalTok{(url\_base,dataset,}\AttributeTok{sep=}\StringTok{""}\NormalTok{))}
\CommentTok{\# Opendap address for bottom 5 meter layer}
\NormalTok{ opendap }\OtherTok{\textless{}{-}} \StringTok{"dodsC/Level2/B10K{-}K20\_CORECFS\_bottom5m.nc"}
\CommentTok{\# Open ncdf4 connection with dataset}
\NormalTok{ nc\_handle }\OtherTok{\textless{}{-}} \FunctionTok{nc\_open}\NormalTok{(}\FunctionTok{paste}\NormalTok{(url\_base,opendap,}\AttributeTok{sep=}\StringTok{""}\NormalTok{)) }
\CommentTok{\# Show metadata from this dataset}
\NormalTok{ nc\_handle}
\CommentTok{\# Close the connection}
\FunctionTok{nc\_close}\NormalTok{(nc\_handle)}
\end{Highlighting}
\end{Shaded}
\hypertarget{access-using-aclim-package}{%
\subsection{3.3 Access using ACLIM
package}\label{access-using-aclim-package}}
The below code will extract variables from the Level 2 and Level 3
netcdf files (\texttt{.nc}) and save them as compressed \texttt{.Rdata}
files on your local Data/in/Newest/Rdata folder.
\hypertarget{setup-up-the-r-worksace}{%
\subsubsection{3.3.1 Setup up the R
worksace}\label{setup-up-the-r-worksace}}
First let's get the workspace set up, will we step through an example
downloading the hindcast and a single projection (CMIP5 MIROC rcp8.5)
but you can loop the code below to download the full set of CMIP5
projections.
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\CommentTok{\# SETUP WORKSPACE}
\CommentTok{\# rm(list=ls())}
\NormalTok{ tmstp }\OtherTok{\textless{}{-}} \FunctionTok{format}\NormalTok{(}\FunctionTok{Sys.time}\NormalTok{(), }\StringTok{"\%Y\_\%m\_\%d"}\NormalTok{)}
\NormalTok{ main }\OtherTok{\textless{}{-}} \FunctionTok{getwd}\NormalTok{() }\CommentTok{\#"\textasciitilde{}/GitHub\_new/ACLIM2}
\FunctionTok{source}\NormalTok{(}\StringTok{"R/make.R"}\NormalTok{)}
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\end{Highlighting}
\end{Shaded}
Let's take a look at the available online datasets:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# preview the datasets on the server:}
\NormalTok{ url\_list }\OtherTok{\textless{}{-}} \FunctionTok{tds\_list\_datasets}\NormalTok{(}\AttributeTok{thredds\_url =}\NormalTok{ ACLIM\_data\_url)}
\CommentTok{\#display the full set of datasets:}
\FunctionTok{cat}\NormalTok{(}\FunctionTok{paste}\NormalTok{(url\_list}\SpecialCharTok{$}\NormalTok{dataset,}\StringTok{"}\SpecialCharTok{\textbackslash{}n}\StringTok{"}\NormalTok{))}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## Constants/
## B10K-H16_CMIP5_CESM_BIO_rcp85/
## B10K-H16_CMIP5_CESM_rcp45/
## B10K-H16_CMIP5_CESM_rcp85/
## B10K-H16_CMIP5_GFDL_BIO_rcp85/
## B10K-H16_CMIP5_GFDL_rcp45/
## B10K-H16_CMIP5_GFDL_rcp85/
## B10K-H16_CMIP5_MIROC_rcp45/
## B10K-H16_CMIP5_MIROC_rcp85/
## B10K-H16_CORECFS/
## B10K-K20_CORECFS/
## files/
\end{verbatim}
\hypertarget{download-level-2-data}{%
\subsubsection{3.3.2 Download Level 2
data}\label{download-level-2-data}}
First we will explore the Level 2 bottom temperature data on the
\href{https://data.pmel.noaa.gov/aclim/thredds/}{ACLIM Thredds server}
using the H16 hindcast and the H16 (CMIP5) projection for MIROC under
rcp8.5. The first step is to get the data urls:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# define the simulation to download:}
\NormalTok{ cmip }\OtherTok{\textless{}{-}} \StringTok{"CMIP5"} \CommentTok{\# Coupled Model Intercomparison Phase}
\NormalTok{ GCM }\OtherTok{\textless{}{-}} \StringTok{"MIROC"} \CommentTok{\# Global Circulation Model}
\NormalTok{ rcp }\OtherTok{\textless{}{-}} \StringTok{"rcp85"} \CommentTok{\# future carbon scenario}
\NormalTok{ mod }\OtherTok{\textless{}{-}} \StringTok{"B10K{-}H16"} \CommentTok{\# ROMSNPZ model}
\NormalTok{ hind }\OtherTok{\textless{}{-}} \StringTok{"CORECFS"} \CommentTok{\# Hindcast}
\CommentTok{\# define the projection simulation:}
\NormalTok{ proj }\OtherTok{\textless{}{-}} \FunctionTok{paste0}\NormalTok{(mod,}\StringTok{"\_"}\NormalTok{,cmip,}\StringTok{"\_"}\NormalTok{,GCM,}\StringTok{"\_"}\NormalTok{,rcp)}
\NormalTok{ hind }\OtherTok{\textless{}{-}} \FunctionTok{paste0}\NormalTok{(mod,}\StringTok{"\_"}\NormalTok{,hind)}
\CommentTok{\# get the url for the projection and hindcast datasets:}
\NormalTok{ proj\_url }\OtherTok{\textless{}{-}}\NormalTok{ url\_list[url\_list}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \FunctionTok{paste0}\NormalTok{(proj,}\StringTok{"/"}\NormalTok{),]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ hind\_url }\OtherTok{\textless{}{-}}\NormalTok{ url\_list[url\_list}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \FunctionTok{paste0}\NormalTok{(hind,}\StringTok{"/"}\NormalTok{),]}\SpecialCharTok{$}\NormalTok{path}
\CommentTok{\# preview the projection and hindcast data and data catalogs (Level 1, 2, and 3):}
\NormalTok{ proj\_datasets }\OtherTok{\textless{}{-}} \FunctionTok{tds\_list\_datasets}\NormalTok{(}\AttributeTok{thredds\_url =}\NormalTok{ proj\_url)}
\NormalTok{ hind\_datasets }\OtherTok{\textless{}{-}} \FunctionTok{tds\_list\_datasets}\NormalTok{(}\AttributeTok{thredds\_url =}\NormalTok{ hind\_url)}
\CommentTok{\# get url for the projection and hindcast Level 2 and Level 3 catalogs}
\NormalTok{ proj\_l2\_cat }\OtherTok{\textless{}{-}}\NormalTok{ proj\_datasets[proj\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \StringTok{"Level 2/"}\NormalTok{,]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ proj\_l3\_cat }\OtherTok{\textless{}{-}}\NormalTok{ proj\_datasets[proj\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \StringTok{"Level 3/"}\NormalTok{,]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ hind\_l2\_cat }\OtherTok{\textless{}{-}}\NormalTok{ hind\_datasets[hind\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \StringTok{"Level 2/"}\NormalTok{,]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ hind\_l3\_cat }\OtherTok{\textless{}{-}}\NormalTok{ hind\_datasets[hind\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \StringTok{"Level 3/"}\NormalTok{,]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ hind\_l2\_cat}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] "https://data.pmel.noaa.gov/aclim/thredds/B10K-H16_CORECFS/Level2.html"
\end{verbatim}
Now that we have the URLs let's take a look at the available Level2
datasets:
\begin{itemize}
\tightlist
\item
\texttt{Bottom\ 5m} : bottom water temperature at 5 meters
\item
\texttt{Surface\ 5m} : surface water temperature in the first 5 meters
\item
\texttt{Integrated} : Integrated water column averages for various NPZ
variables
\end{itemize}
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# preview the projection and hindcast Level 2 datasets:}
\NormalTok{ proj\_l2\_datasets }\OtherTok{\textless{}{-}} \FunctionTok{tds\_list\_datasets}\NormalTok{(proj\_l2\_cat)}
\NormalTok{ hind\_l2\_datasets }\OtherTok{\textless{}{-}} \FunctionTok{tds\_list\_datasets}\NormalTok{(hind\_l2\_cat)}
\NormalTok{ proj\_l2\_datasets}\SpecialCharTok{$}\NormalTok{dataset}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] "Bottom 5m" "Surface 5m" "Integrated"
\end{verbatim}
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# get url for bottom temperature:}
\NormalTok{ proj\_l2\_BT\_url }\OtherTok{\textless{}{-}}\NormalTok{ proj\_l2\_datasets[proj\_l2\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \StringTok{"Bottom 5m"}\NormalTok{,]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ hind\_l2\_BT\_url }\OtherTok{\textless{}{-}}\NormalTok{ hind\_l2\_datasets[hind\_l2\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\SpecialCharTok{==} \StringTok{"Bottom 5m"}\NormalTok{,]}\SpecialCharTok{$}\NormalTok{path}
\NormalTok{ proj\_l2\_BT\_url}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] "https://data.pmel.noaa.gov/aclim/thredds/B10K-H16_CMIP5_MIROC_rcp85/Level2.html?dataset=B10K-H16_CMIP5_MIROC_rcp85_Level2_bottom5m"
\end{verbatim}
We can't preview the Level 3 datasets in the same way but they are
identical to those in the google drive and include two datasets
\begin{itemize}
\tightlist
\item
\texttt{ACLIMsurveyrep\_B10K-H16\_CMIP5\_CESM\_BIO\_rcp85.nc} : NMFS
Groundfish summer NBS and EBS survey replicated values for 60+
variables
\item
\texttt{ACLIMregion\_B10K-H16\_CMIP5\_CESM\_BIO\_rcp85.nc} : weekly
strata averages for 60+ variables
\end{itemize}
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{ weekly\_vars }\CommentTok{\# list of possible variables in the ACLIMregion\_ files }
\end{Highlighting}
\end{Shaded}
Now we can download a subset of the Level2 data (full 10KM Lat Lon
re-gridded data), here with an example of sampling on Aug 1 of each
year:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# Currently available Level 2 variables}
\NormalTok{ dl }\OtherTok{\textless{}{-}}\NormalTok{ proj\_l2\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\CommentTok{\# datasets}
\CommentTok{\# variable list}
\NormalTok{ svl }\OtherTok{\textless{}{-}} \FunctionTok{list}\NormalTok{(}
\StringTok{\textquotesingle{}Bottom 5m\textquotesingle{}} \OtherTok{=} \StringTok{"temp"}\NormalTok{,}
\StringTok{\textquotesingle{}Surface 5m\textquotesingle{}} \OtherTok{=} \StringTok{"temp"}\NormalTok{,}
\StringTok{\textquotesingle{}Integrated\textquotesingle{}} \OtherTok{=} \FunctionTok{c}\NormalTok{(}\StringTok{"EupS"}\NormalTok{,}\StringTok{"Cop"}\NormalTok{,}\StringTok{"NCaS"}\NormalTok{) ) }
\CommentTok{\# preview the variables, timesteps, and lat lon in each dataset:}
\NormalTok{ l2\_info }\OtherTok{\textless{}{-}} \FunctionTok{scan\_l2}\NormalTok{(}\AttributeTok{ds\_list =}\NormalTok{ dl,}\AttributeTok{sim\_list =} \StringTok{"B10K{-}H16\_CORECFS"}\NormalTok{ )}
\FunctionTok{names}\NormalTok{(l2\_info)}
\NormalTok{ l2\_info[[}\StringTok{"Bottom 5m"}\NormalTok{]]}\SpecialCharTok{$}\NormalTok{vars}
\NormalTok{ l2\_info[[}\StringTok{"Surface 5m"}\NormalTok{]]}\SpecialCharTok{$}\NormalTok{vars}
\NormalTok{ l2\_info[[}\StringTok{"Integrated"}\NormalTok{]]}\SpecialCharTok{$}\NormalTok{vars}
\FunctionTok{max}\NormalTok{(l2\_info[[}\StringTok{"Integrated"}\NormalTok{]]}\SpecialCharTok{$}\NormalTok{time\_steps)}
\NormalTok{ l2\_info[[}\StringTok{"Integrated"}\NormalTok{]]}\SpecialCharTok{$}\NormalTok{years}
\CommentTok{\# Simulation list:}
\CommentTok{\# {-}{-}\textgreater{} {-}{-}\textgreater{} Tinker:add additional projection scenarios here}
\NormalTok{ sl }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(hind, proj)}
\CommentTok{\# Currently available Level 2 variables}
\NormalTok{ dl }\OtherTok{\textless{}{-}}\NormalTok{ proj\_l2\_datasets}\SpecialCharTok{$}\NormalTok{dataset }\CommentTok{\# datasets}
\CommentTok{\# variables to pull from each data set}
\CommentTok{\# {-}{-}\textgreater{} {-}{-}\textgreater{} Tinker: try subbing in other Integrated variables }
\CommentTok{\# (l2\_info[["Integrated"]]$vars) into the third list vector }
\NormalTok{ svl }\OtherTok{\textless{}{-}} \FunctionTok{list}\NormalTok{(}
\StringTok{\textquotesingle{}Bottom 5m\textquotesingle{}} \OtherTok{=} \StringTok{"temp"}\NormalTok{,}
\StringTok{\textquotesingle{}Surface 5m\textquotesingle{}} \OtherTok{=} \StringTok{"temp"}\NormalTok{,}
\StringTok{\textquotesingle{}Integrated\textquotesingle{}} \OtherTok{=} \FunctionTok{c}\NormalTok{(}\StringTok{"EupS"}\NormalTok{,}\StringTok{"Cop"}\NormalTok{,}\StringTok{"NCaS"}\NormalTok{) ) }
\CommentTok{\# Let\textquotesingle{}s sample the model years as close to Aug 1 as the model timesteps run:}
\CommentTok{\# {-}{-}\textgreater{} {-}{-}\textgreater{} Tinker {-} try a different date}
\NormalTok{ tr }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"{-}08{-}1 12:00:00 GMT"}\NormalTok{) }
\CommentTok{\# grab nc files from the aclim server and convert to rdatafiles with the ID Aug1}
\FunctionTok{get\_l2}\NormalTok{(}
\AttributeTok{ID =} \StringTok{"\_Aug1"}\NormalTok{,}
\AttributeTok{overwrite =}\NormalTok{ T,}
\AttributeTok{ds\_list =}\NormalTok{ dl,}
\AttributeTok{trIN =}\NormalTok{ tr,}
\AttributeTok{sub\_varlist =}\NormalTok{ svl, }
\AttributeTok{sim\_list =}\NormalTok{ sl )}
\end{Highlighting}
\end{Shaded}
\hypertarget{download-level-3-data}{%
\subsubsection{3.3.3 Download Level 3
data}\label{download-level-3-data}}
Now let's grab some of the Level 3 data and store it in the
Data/in/Newest/Rdata folder. This is comparatively faster because Level
3 files are already post-processed to be in the ACLIM indices format and
are relatively small:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# Simulation list:}
\CommentTok{\# {-}{-}\textgreater{} {-}{-}\textgreater{} Tinker:add additional projection scenarios here}
\NormalTok{ sl }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(hind, proj)}
\CommentTok{\# variable list}
\CommentTok{\# {-}{-}\textgreater{} {-}{-}\textgreater{} Tinker:add additional variables to varlist}
\NormalTok{ vl }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}
\StringTok{"temp\_bottom5m"}\NormalTok{, }\CommentTok{\# bottom temperature,}
\StringTok{"NCaS\_integrated"}\NormalTok{, }\CommentTok{\# Large Cop}
\StringTok{"Cop\_integrated"}\NormalTok{, }\CommentTok{\# Small Cop}
\StringTok{"EupS\_integrated"}\NormalTok{) }\CommentTok{\# Shelf euphausiids}
\CommentTok{\# convert nc files into a long data.frame for each variable}
\CommentTok{\# three options are:}
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\CommentTok{\# opt 1: access nc files remotely (fast, less local storage needed)}
\FunctionTok{get\_l3}\NormalTok{(}\AttributeTok{web\_nc =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{download\_nc =}\NormalTok{ F,}
\AttributeTok{varlist =}\NormalTok{ vl,}\AttributeTok{sim\_list =}\NormalTok{ sl)}
\CommentTok{\# opt 2: download nc files then access locallly:}
\FunctionTok{get\_l3}\NormalTok{(}\AttributeTok{web\_nc =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{download\_nc =}\NormalTok{ T,}
\AttributeTok{local\_path =} \FunctionTok{file.path}\NormalTok{(local\_fl,}\StringTok{"aclim\_thredds"}\NormalTok{),}
\AttributeTok{varlist =}\NormalTok{ vl,}\AttributeTok{sim\_list =}\NormalTok{ sl)}
\CommentTok{\# opt 3: access existing nc files locally:}
\FunctionTok{get\_l3}\NormalTok{(}\AttributeTok{web\_nc =}\NormalTok{ F, }\AttributeTok{download\_nc =}\NormalTok{ F,}
\AttributeTok{local\_path =} \FunctionTok{file.path}\NormalTok{(local\_fl,}\StringTok{"aclim\_thredds"}\NormalTok{),}
\AttributeTok{varlist =}\NormalTok{ vl,}\AttributeTok{sim\_list =}\NormalTok{ sl)}
\end{Highlighting}
\end{Shaded}
\hypertarget{download-level-3-cmip6-aclim-only-for-now}{%
\subsubsection{3.3.4 Download Level 3 CMIP6 (ACLIM only for
now)}\label{download-level-3-cmip6-aclim-only-for-now}}
Go to the shared google drive and dowload the CMIP6 data into your
ACLIM2 local folder:
\href{https://drive.google.com/drive/folders/1ljACM6cgMD7M14lzvozZyTP4tMBnf_S4}{00\_ACLIM\_shared\textgreater02\_Data\textgreater Newest\textgreater roms\_for\_aclim}
and put in your local folder under: \texttt{Data/in/roms\_for\_aclim}
\includegraphics{Figs/filestructure2.jpg}
\hypertarget{explore-indices-plot-the-data}{%
\section{4. Explore indices \& plot the
data}\label{explore-indices-plot-the-data}}
\hypertarget{data-exploration-with-the-minimal-installation}{%
\subsection{4.1. Data exploration with the minimal
installation}\label{data-exploration-with-the-minimal-installation}}
Let's look at some data from the Level 2 bottom temperature records,
using the threadds and ncdf4 libraries:
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{library}\NormalTok{(ncdf4)}
\FunctionTok{library}\NormalTok{(thredds) }
\CommentTok{\# Open connection to Level 2 bottom 5 meter layer}
\NormalTok{ url\_base }\OtherTok{\textless{}{-}} \StringTok{"https://data.pmel.noaa.gov/aclim/thredds/"}
\NormalTok{ opendap }\OtherTok{\textless{}{-}} \StringTok{"dodsC/Level2/B10K{-}K20\_CORECFS\_bottom5m.nc"}
\NormalTok{ nc }\OtherTok{\textless{}{-}} \FunctionTok{nc\_open}\NormalTok{(}\FunctionTok{paste}\NormalTok{(url\_base,opendap,}\AttributeTok{sep=}\StringTok{""}\NormalTok{))}
\CommentTok{\# Examination of the nc object shows variables such as temperature (temp)}
\CommentTok{\# float temp[xi\_rho,eta\_rho,ocean\_time] }
\CommentTok{\# long\_name: time{-}averaged potential temperature, bottom 5m mean}
\CommentTok{\# units: Celsius}
\CommentTok{\# time: ocean\_time}
\CommentTok{\# coordinates: lon\_rho lat\_rho ocean\_time}
\CommentTok{\# field: temperature, scalar, series}
\CommentTok{\# \_FillValue: 9.99999993381581e+36}
\CommentTok{\# cell\_methods: s\_rho: mean}
\CommentTok{\# temp has three dimensions {-} xi\_rho, eta\_rho, and ocean\_time}
\CommentTok{\# Now we make vectors of each axis.}
\NormalTok{ xi\_axis }\OtherTok{\textless{}{-}} \FunctionTok{seq}\NormalTok{(}\DecValTok{1}\NormalTok{,}\DecValTok{182}\NormalTok{) }\CommentTok{\# Hardcoded axis length}
\NormalTok{ eta\_axis }\OtherTok{\textless{}{-}} \FunctionTok{seq}\NormalTok{(}\DecValTok{1}\NormalTok{,}\DecValTok{258}\NormalTok{) }\CommentTok{\# Hardcoded axis length}
\CommentTok{\# time units in GMT: seconds since 1900{-}01{-}01 00:00:00}
\NormalTok{ t\_axis }\OtherTok{\textless{}{-}} \FunctionTok{ncvar\_get}\NormalTok{(nc,}\StringTok{"ocean\_time"}\NormalTok{)}
\NormalTok{ time\_axis }\OtherTok{\textless{}{-}} \FunctionTok{as.POSIXct}\NormalTok{(t\_axis, }\AttributeTok{origin =} \StringTok{"1900{-}01{-}01"}\NormalTok{, }\AttributeTok{tz =} \StringTok{"GMT"}\NormalTok{)}
\CommentTok{\# Make two dates to find in the data}
\NormalTok{ date1 }\OtherTok{\textless{}{-}} \FunctionTok{ISOdate}\NormalTok{(}\AttributeTok{year=}\DecValTok{2010}\NormalTok{, }\AttributeTok{month=}\DecValTok{7}\NormalTok{, }\AttributeTok{day=}\DecValTok{1}\NormalTok{, }\AttributeTok{hour =} \DecValTok{12}\NormalTok{, }\AttributeTok{tz =} \StringTok{"GMT"}\NormalTok{)}
\NormalTok{ date2 }\OtherTok{\textless{}{-}} \FunctionTok{ISOdate}\NormalTok{(}\AttributeTok{year=}\DecValTok{2019}\NormalTok{, }\AttributeTok{month=}\DecValTok{7}\NormalTok{, }\AttributeTok{day=}\DecValTok{1}\NormalTok{, }\AttributeTok{hour =} \DecValTok{12}\NormalTok{, }\AttributeTok{tz =} \StringTok{"GMT"}\NormalTok{)}
\CommentTok{\# Which time index is closest to those dates?}
\NormalTok{ timerec1 }\OtherTok{\textless{}{-}} \FunctionTok{which.min}\NormalTok{(}\FunctionTok{abs}\NormalTok{(time\_axis }\SpecialCharTok{{-}}\NormalTok{ date1))}
\NormalTok{ timerec2 }\OtherTok{\textless{}{-}} \FunctionTok{which.min}\NormalTok{(}\FunctionTok{abs}\NormalTok{(time\_axis }\SpecialCharTok{{-}}\NormalTok{ date2))}
\CommentTok{\# Center time of the closest weekly average}
\NormalTok{ time\_axis[timerec1]}
\NormalTok{ time\_axis[timerec2]}
\CommentTok{\# Get full xi, eta grid (count={-}1) for two time slices}
\CommentTok{\# Get one record starting at desired timerec. }
\CommentTok{\# Careful (easy to grab too much data, if count and start are missing}
\CommentTok{\# it will grab all the data).}
\NormalTok{ temp1 }\OtherTok{\textless{}{-}} \FunctionTok{ncvar\_get}\NormalTok{(nc, }\StringTok{"temp"}\NormalTok{, }\AttributeTok{start=}\FunctionTok{c}\NormalTok{(}\DecValTok{1}\NormalTok{,}\DecValTok{1}\NormalTok{,timerec1), }\AttributeTok{count=}\FunctionTok{c}\NormalTok{(}\SpecialCharTok{{-}}\DecValTok{1}\NormalTok{,}\SpecialCharTok{{-}}\DecValTok{1}\NormalTok{,}\DecValTok{1}\NormalTok{))}
\NormalTok{ temp2 }\OtherTok{\textless{}{-}} \FunctionTok{ncvar\_get}\NormalTok{(nc, }\StringTok{"temp"}\NormalTok{, }\AttributeTok{start=}\FunctionTok{c}\NormalTok{(}\DecValTok{1}\NormalTok{,}\DecValTok{1}\NormalTok{,timerec2), }\AttributeTok{count=}\FunctionTok{c}\NormalTok{(}\SpecialCharTok{{-}}\DecValTok{1}\NormalTok{,}\SpecialCharTok{{-}}\DecValTok{1}\NormalTok{,}\DecValTok{1}\NormalTok{))}
\CommentTok{\# Plot comparison (not checking scale here)}
\FunctionTok{par}\NormalTok{(}\AttributeTok{mfrow=}\FunctionTok{c}\NormalTok{(}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{))}
\FunctionTok{image}\NormalTok{(temp1)}
\FunctionTok{image}\NormalTok{(temp2)}
\CommentTok{\# Get lat/lon for better mapping {-} getting whole variable }
\NormalTok{ lats }\OtherTok{\textless{}{-}} \FunctionTok{ncvar\_get}\NormalTok{(nc,}\StringTok{"lat\_rho"}\NormalTok{)}
\NormalTok{ lons }\OtherTok{\textless{}{-}} \FunctionTok{ncvar\_get}\NormalTok{(nc,}\StringTok{"lon\_rho"}\NormalTok{)}
\CommentTok{\# Visualizing the coordinate transformation }
\FunctionTok{plot}\NormalTok{(lons,lats)}
\CommentTok{\# Let\textquotesingle{}s flag water \textless{}2 degrees C}
\FunctionTok{par}\NormalTok{(}\AttributeTok{mfrow=}\FunctionTok{c}\NormalTok{(}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{))}
\FunctionTok{plot}\NormalTok{(lons,lats,}\AttributeTok{col=}\FunctionTok{ifelse}\NormalTok{(temp1}\SpecialCharTok{\textless{}}\DecValTok{2}\NormalTok{,}\StringTok{"blue"}\NormalTok{,}\StringTok{"green"}\NormalTok{),}\AttributeTok{main=}\StringTok{"2010"}\NormalTok{)}
\FunctionTok{plot}\NormalTok{(lons,lats,}\AttributeTok{col=}\FunctionTok{ifelse}\NormalTok{(temp2}\SpecialCharTok{\textless{}}\DecValTok{2}\NormalTok{,}\StringTok{"blue"}\NormalTok{,}\StringTok{"green"}\NormalTok{),}\AttributeTok{main=}\StringTok{"2019"}\NormalTok{)}
\CommentTok{\# Close the connection}
\FunctionTok{nc\_close}\NormalTok{(nc)}
\end{Highlighting}
\end{Shaded}
\begin{figure}
\centering
\includegraphics[width=1\textwidth,height=\textheight]{Figs/minimal_coldpool.jpg}
\caption{Bottom temperature \textless2 degrees C (blue) and
\textgreater=2 degrees C (green).}
\end{figure}
\hypertarget{level-3-indices}{%
\subsection{4.2. Level 3 indices}\label{level-3-indices}}
Level 3 indices can be used to generate seasonal, monthly, and annual
indices (like those reported in
\href{https://www.frontiersin.org/articles/10.3389/fmars.2020.00124/full}{Reum
et al.~2020)},
\href{http://dx.doi.org/10.1038/s41467-020-18300-3}{Holsman et
al.~2020)}. In the section below we explore these indices in more detail
using R, including using (2) above to generate weekly, monthly, and
seasonal indices (e.g.~Fall Zooplankton) for use in biological models.
In section 3 below we explore these indices in more detail using R,
including using (2) above to generate weekly, monthly, and seasonal
indices (e.g.~Fall Zooplankton) for use in biological models. The
following examples show how to analyze and plot the ACLIM indices from
the .Rdata files created in the previous step 3. Please be sure to
coordinate with ROMSNPZ modeling team members to ensure data is applied
appropriately.
\hypertarget{explore-level-3-data-catalog}{%
\subsubsection{4.2.1 Explore Level 3 data
catalog}\label{explore-level-3-data-catalog}}
Once the base files and setup are loaded you can explore the index
types. Recall that in each scenario folder there are two indices saved
within the \texttt{Level3} subfolders:
\begin{enumerate}
\def\labelenumi{\arabic{enumi})}
\tightlist
\item
\texttt{ACLIMsurveyrep\_B10K-x.nc} contains summer groundfish trawl
``survey replicated'' indices (using mean date and lat lon)
\emph{(Note that the resampling stations need to be removed before
creating bottom temperature maps)}\\
\item
\texttt{ACLIMregion\_B10K-x.nc}: contains weekly ``strata'' values
\emph{(Note that area weighting should be used to combine values
across multiple strata)}
\end{enumerate}
First run the below set of code to set up the workspace:
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\CommentTok{\# SETUP WORKSPACE}
\NormalTok{ tmstp }\OtherTok{\textless{}{-}} \FunctionTok{format}\NormalTok{(}\FunctionTok{Sys.time}\NormalTok{(), }\StringTok{"\%Y\_\%m\_\%d"}\NormalTok{)}
\NormalTok{ main }\OtherTok{\textless{}{-}} \FunctionTok{getwd}\NormalTok{() }\CommentTok{\#"\textasciitilde{}/GitHub\_new/ACLIM2}
\FunctionTok{source}\NormalTok{(}\StringTok{"R/make.R"}\NormalTok{)}
\CommentTok{\# {-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}{-}}
\CommentTok{\# list of the scenario x GCM downscaled ACLIM indices}
\ControlFlowTok{for}\NormalTok{(k }\ControlFlowTok{in}\NormalTok{ aclim)}
\FunctionTok{cat}\NormalTok{(}\FunctionTok{paste}\NormalTok{(k,}\StringTok{"}\SpecialCharTok{\textbackslash{}n}\StringTok{"}\NormalTok{))}
\NormalTok{ embargoed }\CommentTok{\# not yet public or published}
\NormalTok{ public }\CommentTok{\# published runs (CMIP5)}
\CommentTok{\# get some info about a scenario:}
\NormalTok{ all\_info1}
\NormalTok{ all\_info2}
\CommentTok{\# variables in each of the two files:}
\NormalTok{ srvy\_vars}
\NormalTok{ weekly\_vars}
\CommentTok{\#summary tables for variables}
\NormalTok{ srvy\_var\_def}
\NormalTok{ weekly\_var\_def}
\CommentTok{\# explore stations in the survey replicated data:}
\FunctionTok{head}\NormalTok{(station\_info)}
\end{Highlighting}
\end{Shaded}
\hypertarget{level-3-spatial-indices-survey-replicated}{%
\subsubsection{4.2.2 Level 3: Spatial indices (survey
replicated)}\label{level-3-spatial-indices-survey-replicated}}
Let's start b exploring the survey replicated values for each variable.
Previous steps generated the Rdata files that are stored in the
\texttt{ACLIMsurveyrep\_B10K-{[}version\_CMIPx\_GCM\_RCP{]}.Rdata} in
each corresponding simulation folder.
\includegraphics[width=0.5\textwidth,height=\textheight]{Figs/stations_NS.jpg}
\includegraphics[width=0.5\textwidth,height=\textheight]{Figs/stations.jpg}
The code segment below will recreate the above figures.\emph{Note that
if this is the first time through it may take 3-5 mins to load the
spatial packages and download the files from the web (first time through
only).}
\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# if load\_gis is set to FALSE in R/setup.R (default) }
\CommentTok{\# we will need to load the gis layers and packages}
\CommentTok{\# if this is the first time through this would be a good time}
\CommentTok{\# to grab a coffee...}
\FunctionTok{source}\NormalTok{(}\StringTok{"R/sub\_scripts/load\_maps.R"}\NormalTok{)}
\CommentTok{\# first convert the station\_info object into a shapefile for mapping:}
\NormalTok{ station\_sf }\OtherTok{\textless{}{-}} \FunctionTok{convert2shp}\NormalTok{(station\_info)}
\NormalTok{ station\_sf}\SpecialCharTok{$}\NormalTok{stratum }\OtherTok{\textless{}{-}} \FunctionTok{factor}\NormalTok{(station\_sf}\SpecialCharTok{$}\NormalTok{stratum)}
\CommentTok{\# plot the stations:}
\NormalTok{ p }\OtherTok{\textless{}{-}} \FunctionTok{plot\_stations\_basemap}\NormalTok{(}\AttributeTok{sfIN =}\NormalTok{ station\_sf,}
\AttributeTok{fillIN =} \StringTok{"subregion"}\NormalTok{,}
\AttributeTok{colorIN =} \StringTok{"subregion"}\NormalTok{) }\SpecialCharTok{+}
\FunctionTok{scale\_color\_viridis\_d}\NormalTok{(}\AttributeTok{begin =}\NormalTok{ .}\DecValTok{2}\NormalTok{,}\AttributeTok{end=}\NormalTok{.}\DecValTok{6}\NormalTok{) }\SpecialCharTok{+}