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Initial commit of NODC Ocean Heat Content
This project forked from larrybelcher/nodc_ocean_heat_content
Initial commit of NODC Ocean Heat Content
#This document describes the data and associated code used to create the NODC Ocean Heat Content maps. Data used are 0-700m seasonal (3-month periods) and yearly from NODC globally analyzed fields at the following url: http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/heat_global.html Methodology described in Levitus et al.: http://data.nodc.noaa.gov/woa/PUBLICATIONS/grlheat12.pdf An excerpt from above paper regarding the technique for calculating anomaly: "From every observed one-degree mean temperature value at every standard depth level we subtract off a climatological value. For this purpose we use the monthly climatological fields of temperature from Locarnini et al. [2010]." The Locarnini work described in the 2009 World Ocean Atlas (ftp://ftp.nodc.noaa.gov/pub/WOA09/DOC/woa09_vol1_text.pdf) states: "Temperature and salinity climatologies are the average of five decadal climatologies for the following time periods: 1955-1964, 1965-1974, 1975-1984, 1985-1994, and 1995-2006". Abstract: This project consists of a suite of python scripts that generate maps of the NODC Ocean Heat Content (OHC) data. These data are obtained from the NODC globally analyzed fields at the url mentioned above. The scripts create several different map projections (Hammer-Aitoff, cylindrical equidistant, or Robinson) based on the image size. The image sizes and style are based on the Data Snapshots style guide developed for the NNVL global temperature anomaly scripts (https://github.com/LarryBelcher/GHCN_Global/blob/master/README). The basic methodology used here is to download the NODC data in netcdf format. These files are continually updated following a given seasonal period and/or year. Once downloaded, the data are projected onto a cylindrical equidistant (CE) map with no additional layers (e.g., coastlines, borders...). Once the CE map for a given year or seasonal period has been created, the data are projected onto a “final” map that includes coastlines, shaded continents, legend, and other relevant map layers. Before creating new maps, update the data using the c-shell script: update_data.csh Python script listing: SeasonalOHCcdf2cyl.py – Routine to create the “initial” seasonal CE map with no additional layers SeasonalOHCcdf2cylBlank.py - Routine to create the “initial” seasonal CE map for the “no data” image YearlyOHCcdf2cyl.py - Routine to create the “initial” annual CE map with no additional layers YearlyOHCcdf2cylBlank.py - Routine to create the “initial” annual CE map for the “no data” image nodc_seasonal_driver.py nodc_seasonal_map.py nodc_seasonal_colorbar.py nodc_yearly_driver.py nodc_yearly_map.py nodc_yearly_colorbar.py
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