Leigh Orf
Assistant Professor
of Atmospheric Sciences
Department of
Geography
Central
Michigan University
Mount
Pleasant, MI 48859
The Geography Department at Central
Michigan University
contains an undergraduate meteorology concentration supported by three
meteorology faculty. In summer 2003 the meteorology lab upgraded its ten
computers to Red Hat Linux PCs running GEMPAK, McIDAS, and Vis5d. The system
received its heaviest use during class time and for homework assignments and
case studies. Several problems became evident with the new system as it became
more heavily used: There was a lack of server storage space, data throughput
from the lab to the server running the LDM and serving data was slow; and the
system did not have a regular backup strategy in place. In the summer of 2004
we received a Unidata equipment award. The funds from this award were used to
purchase a dual processor Dell RAID server containing six gigabit Ethernet
ports running Red Hat Enterprise Linux, a SDLT tape drive, 20 tapes and backup software.
This upgrade has led to a significant improvement in our lab. Students are able
to download large amounts of data for case studies (mostly COMET case studies
containing data viewable by GEMPAK) and undergraduate research programs without
worrying about running out of server space. In addition, student data, which is
NFS mounted to the new server machine, is automatically backed up frequently.
Being able to split Ethernet connections between several interfaces has
improved throughput noticeably, especially when it comes to accessing large
amounts of GEMPAK data via NFS.
The new Dell server handles data ingestion and decoding
without breaking a sweat, and allows us to keep data around for weeks rather
than days before scouring. This is useful for the analysis of timely weather
events in the classroom.
Since the upgrade students heavily utilized GEMPAK
(specifically GARP) for their case studies in Mesoscale Meteorology, and for
analyzing model data in Numerical Weather Prediction. Efforts are underway to
get students trained on the IDV software which we believe has the potential to
become the main data analysis tool used in the classroom.