CrawlModels: Get Available Model Runs

In rNOMADS: An R Interface to the NOAA Operational Model Archive and Distribution System

Get Available Model Runs

Description

This function determine which instances of a given model are available for download.

Usage

CrawlModels(abbrev = NULL, model.url = NULL, depth = NULL, verbose = TRUE)

Arguments

abbrev	The model abbreviation, see NOMADSRealTimeList. Defaults to NULL.
model.url	A URL to use instead of using the abbreviations in NOMADSRealTimeList. Defaults to NULL.
depth	How many model instances to return. This avoids having to download the entire model list (sometimes several hundred) if only the first few instances are required. Defaults to NULL, which returns everything.
verbose	Print out each link as it is discovered. Defaults to TRUE.

Details

This function calls WebCrawler, a recursive algorithm that discovers each link available in the URL provided. It then searches each link in turn, and follows those links until it reaches a dead end. At that point, it returns the URL. For the model pages on the NOMADS web site, each dead end is a model instance that can be examined using ParseModelPage or have data retrieved from it using GribGrab.

Value

urls.out

A list of web page addresses, each of which corresponds to a model instance.

Note

It is a good idea to set depth to a small number rather than leave it at the default value. Some models (such as the Global Forecast System) have a large number of instances, and crawling each one can take a lot of time. I recommend depth = 2, since the first URL may not have an active model on it yet if the model is still being uploaded to the server. In that case,the first URL will contain no data, and the second URL can be used instead.

Author(s)

Daniel C. Bowman [e-mail]

See Also

WebCrawler, ParseModelPage, NOMADSRealTimeList, GribGrab

Examples

#Get the latest 5 instances
#for the Global Forecast System 0.5 degree model

## Not run: urls.out <- CrawlModels(abbrev = "gfs_0p50", depth = 5)

rNOMADS documentation built on May 29, 2024, 6:44 a.m.