yeshancqcq / deglaciation

Deglaciation

Step 1. Extract data from the LipD:

Use: lipd.R to get temperature data; https://github.com/yeshancqcq/deglaciation/blob/master/lipd.R Get datafiles in the lipd2csv folder; lipd_meta.R to get metadata from LipD; https://github.com/yeshancqcq/deglaciation/blob/master/lipd_meta.R Get the metadata.csv file; lipd_depth_et.R to get geochronological data from LipD; https://github.com/yeshancqcq/deglaciation/blob/master/lipd_depth_et.R Get datafiles in the lipd_chron folder;

https://github.com/yeshancqcq/GEO420_data Previous data (Shakun and Marcott papers) are in the GEO_420 repository.

Step 2. Interpolation / Anomaly construction

Use interpolation_anomaly.R to generate the interpolated datasets, and calculate the anomaly (base: 8000 - 12000 bp). Data files in the anomaly_interpolated folder https://github.com/yeshancqcq/deglaciation/blob/master/interpolation_anomaly.R

Step 3. Join interpolated temperature and anomaly to metadata -- prepare for the spatiotemporal reconstruction

Use join.R

Better to have a helper.csv file prepared from excel.

This file should only contains fieldnames from t0 to t22000

Results: 2 metadata files (anomaly_metadata.csv and temperature_metadata.csv) https://github.com/yeshancqcq/deglaciation/blob/master/join.R

Step 4. Spatiotemporal reconstruction.

If using ArcGIS: Import the csv metadata and convert it into a point shapefile

Preparing girds with Grid_Index_Feature, Then

Point To Raster --> Zonal Statistics as table--> Join back to the shapefile

If using ArcPy: https://github.com/yeshancqcq/paleo_data_spatial/blob/master/arcgis.py

Without ArcPy: https://github.com/yeshancqcq/deglaciation/blob/master/spatiotemporal_reconstruction.R

and then: hemispheric reconstruction and plotting: https://github.com/yeshancqcq/deglaciation/blob/master/hemisphere_construction.R

Step 5. Regional average

With or without model https://github.com/yeshancqcq/paleo_data_spatial/blob/master/regional_construction.R

Step 6. Data model comparison

Generating coordinates for model outputs (.nc files) https://github.com/yeshancqcq/paleo_data_spatial/blob/master/coor_gen.R

Visualization

Regional plots: https://github.com/yeshancqcq/paleo_data_spatial/blob/master/plot_regional.R

Plot LipD metadata: https://github.com/yeshancqcq/paleo_data_spatial/blob/master/meta_plot.R

Plot maps in R: https://github.com/yeshancqcq/paleo_data_spatial/blob/master/map.R

Automatically plot spatiotemporal reconstructions in ArcPy/ArcGIS (need to set up the mxd and symbol layer in the desktop) https://github.com/yeshancqcq/paleo_data_spatial/blob/master/symbol.lyr https://github.com/yeshancqcq/paleo_data_spatial/blob/master/Untitled.mxd https://github.com/yeshancqcq/paleo_data_spatial/blob/master/paleo_process1.mxd https://github.com/yeshancqcq/paleo_data_spatial/blob/master/mapping_series.py

Latest files to use

Gridded data: model_sealand.csv and proxy_sealand.csv

Package data: model_lat_band3.csv and proxy_lat_band3.csv

Regional packages: model_region.csv and proxy_region.csv