#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