This page describes and gives options for manipulating the IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface dataset. We start with the options for manipulating, because once you are comfortable with the system, they are the most useful.


Dataset Options


IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface options Help Expert Mode
Help/Terse
switches back and forth between this relatively descriptive page that contains extended explanations, and the page that just has the information.
Expert Mode
switches into a mode that lets you access several datasets at the same time, and enter data-manipulating commands directly as text rather than clicking on a series of pages.

When in Expert Mode there is a list of active datasets at the top of the page, followed by a text window containing the command equivalent of the current page. These commands can be edited or extended.

Note that there will be many more options once you have picked a particular variable, because the server is currently more adept at manipulating single variables than it is at manipulating datasets (e.g. collections of variables).

Dataset Description

We start with a quick reminder of where you are in the collection of datasets.

...RESEARCHATMOSPHEREGLOBALECHAM4EAfrSSTEAfr_goga.DMonthlySurface

As you go from left to right, the datasets listed get more and more specific, ending with the current dataset, IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface. Datasets with documentation are marked (*): the * links to the documentation directly.

IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface

IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface.

Documents

give additional information about the current dataset.
overview
shows an overview of the different parts of this dataset (the parts shown are sub-datasets, see below).

Datasets and variables

Variables (also called data or dependent variables) are sets of numbers, along with the grids (independent variables) that place those numbers in space and time, and the additional information (such as units) that render the data meaningful. Datasets are collections of variables and datasets. This will become clearer once you look at the outline.

total cloud cover IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface cld[ X Y | T]
evaporation IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface evap[ X Y | T]
surface latent heat flux IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface lh[ X Y | T]
net longwave at ground IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface nlwg[ X Y | T]
net shortwave at ground IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface nswg[ X Y | T]
net shortwave at toa IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface nswt[ X Y | T]
out long wave radiation IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface olr[ X Y | T]
total precipitation IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface prec[ X Y | T]
surface sensible heat flux IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface sh[ X Y | T]
sea level pressure IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface slp[ X Y | T]
surface temperature IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface st[ X Y | T]
temperature at 2m IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface t2m[ X Y | T]
surface zonal wind stress IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface taux[ X Y | T]
surface meridional wind stress IRI MP RESEARCH ATMOSPHERE GLOBAL ECHAM4 EAfrSST EAfr_goga.D Monthly Surface tauy[ X Y | T]