Last updated: 2020-02-20
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Knit directory: MHWNWA/
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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | a3b88a8 | Robert William Schlegel | 2020-02-12 | Working through a full edit of the workflowr site. This will seque into a write up of the draft manuscript. |
| html | a7fbd91 | robwschlegel | 2019-08-28 | Build site. |
| Rmd | 59cf771 | robwschlegel | 2019-08-22 | Polished up the variable prep vignette |
| html | 826c73d | robwschlegel | 2019-08-15 | Build site. |
| html | 143b1a6 | robwschlegel | 2019-08-15 | Build site. |
| Rmd | 78f4977 | robwschlegel | 2019-08-15 | Re-publish entire site. |
| html | 20ae166 | robwschlegel | 2019-08-11 | Build site. |
| html | 19bea26 | robwschlegel | 2019-08-11 | Build site. |
| html | 2652a3a | robwschlegel | 2019-08-11 | Build site. |
| Rmd | adc762b | robwschlegel | 2019-08-08 | Re-worked the GLORYS data and propogated update through to SOM analysis figures for all experiments |
| html | f0d2efb | robwschlegel | 2019-08-07 | Build site. |
| Rmd | ed626bf | robwschlegel | 2019-08-07 | Ran a bunch of figures and had a meeting with Eric. More changes coming to GLORYS data tomorrow before settling on one of the experimental SOMs |
| Rmd | f27c261 | robwschlegel | 2019-08-06 | Working towards pipeline optimised for testing different SOM inputs |
| Rmd | 9a9fa7d | robwschlegel | 2019-08-01 | A more in depth dive into the potential criteria to meet for the SOM model |
| html | aa82e6e | robwschlegel | 2019-07-31 | Build site. |
| Rmd | 498909b | robwschlegel | 2019-07-31 | Re-publish entire site. |
| Rmd | 256a7f1 | robwschlegel | 2019-07-31 | Completed re-run on ERA 5 data. Working on combining anomalies. |
| Rmd | 3b805e4 | robwschlegel | 2019-07-30 | Completed anomaly runs on GLORYS variables |
| Rmd | bd987b4 | robwschlegel | 2019-07-29 | Completed run on anomalies with the exception of the three in the GLORYS product |
| Rmd | 51ed681 | robwschlegel | 2019-07-25 | Completed anoms for OISST |
| Rmd | 0b6f065 | robwschlegel | 2019-07-25 | Push before beginning to write code for loading entire obs/reanalysis products into memory for clim calculations |
| Rmd | 04a6bf3 | robwschlegel | 2019-07-24 | Creating new download script for obs/reanalysis products |
| html | 81e961d | robwschlegel | 2019-07-09 | Build site. |
| Rmd | 7ff9b8b | robwschlegel | 2019-06-17 | More work on the talk |
| html | c23c50b | robwschlegel | 2019-06-10 | Build site. |
| html | 028d3cc | robwschlegel | 2019-06-10 | Build site. |
| html | c61a15f | robwschlegel | 2019-06-06 | Build site. |
| Rmd | 49c6105 | robwschlegel | 2019-06-06 | Finished vector data packet pipeline |
| Rmd | 44ac335 | robwschlegel | 2019-06-06 | Working on inclusion of vectors into SOM pipeline |
| html | 6dd6da8 | robwschlegel | 2019-06-06 | Build site. |
| Rmd | 07137d9 | robwschlegel | 2019-06-06 | Site wide update, including newly functioning SOM pipeline. |
| Rmd | 990693a | robwschlegel | 2019-06-05 | First SOM result visuals |
| Rmd | 4838cc8 | robwschlegel | 2019-06-04 | Working on SOM functions |
| Rmd | 94ce8f6 | robwschlegel | 2019-06-04 | Functions for creating data packets are up and running |
| Rmd | 65301ed | robwschlegel | 2019-05-30 | Push before getting rid of some testing structure |
| Rmd | 0717c84 | robwschlegel | 2019-05-29 | Working towards getting the variable climatologies in order |
| Rmd | 2c3f68c | robwschlegel | 2019-05-28 | Working on the variable prep vignette |
| html | c09b4f7 | robwschlegel | 2019-05-24 | Build site. |
| Rmd | 5dc8bd9 | robwschlegel | 2019-05-24 | Finished initial creation of SST prep vignette. |
This vignette walks through the steps needed to create mean synoptic states during all of the MHWs detected in the previous vignette. These synoptic states consist of the variables in the ocean heat budget equation.
After first going through this entire process with the NAPA model output it became clear that this analysis should actually be run with obs/reanalysis data, and the NAPA model results may be compared against this as desired. To this end we will use the following variables as found in the following data products:
All of these products and variables have a shared daily resolution period from 1993 – 2018. The spatial resolutions for NOAA and ERA 5 are 1/4 degrees and the GLORYS data are 1/12 degree. The coordinates are slightly off between OISST and ERA 5 & GLORYS, with the coordinate system for NOAA being centred per pixel while the other two products have their coordinate system based on the northwest corner. In order to compare the OISST dataset to the other 1/4 degree products the lat values for OISST will have 0.125 added to them, and the longitude values will have 0.125 subtracted from them. The ERA5 data are hourly, so will need to be binned into mean daily values. In order to trade between efficiency and accuracy we will be converting everything to the 1/4 degree grid of the GLORYS/ERA 5 data at a daily temporal resolution.
Rather than go about performing all of the calculations below on piecemeal bits of data, we will load each variable into memory at once. The following code chunk shows how we create functions that load each of the variables from the different data products. We will then create and save this complete dataset for ease of use later on.
# The code used for this step may be seen in the 'code/workflow.R':
# https://github.com/robwschlegel/MHWNWA/blob/master/code/workflow.R
# The sections of the script used are:
# OISST processing, GLORYS processing, and ERA 5 processingThis is the one variable I was not able to source. The OAFlux product does have a net heat flux layer, but it ends in 2009. This is not long enough so we are going to create our own net heat flux layer by adding together the latent & sensible heat flux layers with the shortwave & longwave radiation layers from the ERA 5 product. When doing so we must ensure that the directions of the terms are matched correctly (i.e. that they all represent positive downward flux). Reading through the available meta-data I was not able to verify this, but it appears as though these area all positive downward flux terms.
# The code used to perform these steps may be seen in 'code/workflow.R' sction:
# ERA 5 processingIn the data packets we need to create for the SOM we will need to include anomaly values. In order to do this we need to first create daily climatologies for each variable for each pixel. To do so we will need to load all of the files and then pixel-wise go about getting the seasonal (mean daily) climatologies. This will be done with the same function (ts2clm()) that is used for the MHW climatologies. One-by-one we will load an entire dataset (created above) into memory so that we can perform the necessary calculations. Hold on to your hats, this is going to be RAM heavy…
# The code used to perform these steps may be seen in 'code/workflow.R' sction:
# OISST processing, GLORYS processing, and ERA 5 processingThe last step before we can begin creating our data packets is to subtract our climatology data from our base data for each of the variables used in this study. We then save these large anomaly cubes to allow for easier synoptic state creation later on.
# The code used to perform these steps may be seen in 'code/workflow.R' sction:
# OISST processing, GLORYS processing, and ERA 5 processingThe next step is to create mean synoptic states for each variable during each of the MHWs detected in each region. To do this we simply load the combined anomaly dataset of all of our chosen variables and slice off only the bits we need during each of the observed MHWs. These slices are then meaned, pixel-wise, to create the synoptic states during each event.
# The code used to perform these steps may be seen in 'code/workflow.R' sction:
# OISST processing, GLORYS processing, and ERA 5 processingWith all of our mean synoptic states created it is now time to feed them to the Self-organising map (SOM).
sessionInfo()R version 3.6.2 (2019-12-12)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS
Matrix products: default
BLAS: /usr/lib/openblas-base/libblas.so.3
LAPACK: /usr/lib/libopenblasp-r0.2.18.so
locale:
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[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
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[25] knitr_1.27