From: phred@well.sf.ca.us (Fred Heutte)
Subject: Re: Weather Nuts: Degree Days?
Organization: Whole Earth 'Lectronic Link
Date: Tue, 29 Sep 1992 05:16:13 GMT

In <burton.21@bobcat.lmc.edu> burton@bobcat.lmc.edu writes:

>The manager of our Physical Plant is looking for a source of degree day
>(one or two words?) data to be analyzed for budgeting purposes.

>Anyone know where we can find that data?

>Kathy Burton
>burton@bobcat.lmc.edu

>Harry Peterson (Physical Plant Director)
>petersh@bobcat.lmc.edu
>***********************************************************************
>Kathy Burton
>Computer Services
>Lees-McRae College                                704-898-5241
>Banner Elk, NC  28604                          burton@bobcat.lmc.edu
>***********************************************************************


My experience with degree-days is focused on energy analysis, but perhaps
these comments can help.

In designing a building for energy efficiency, or alternatively, for
measuring the effect of energy conservation measures, the calculation of
degree days plays an important role.

Although more stringent definitions are possible, the usual approach is
to define a balance or reference temperature, and then take the difference
between that and the average daily temperature (average defined here as
the simple average of the high and low for the day, not the mean of
hourly temperatures or another such approach).  For example, if the
reference temperature is 60 degrees and the high/low daily average is
70, that translates into 10 cooling degree days.  Likewise, if the
high/low average is 35, that means 25 heating degree days.

The model I'm most familiar with, the Princeton Scorekeeping Model (PRISM),
is the standard one used to normalize (remove the effects of) weather from
the observation of electric or gas billing histories.  It's primarily used
to gauge the effect of energy conservation programs, where daily or seasonal
changes in weather might mask the actual effect of conservation measures.
PRISM calculates the reference temperature (tau) using a somewhat complex
iterative algorithm.  Some of my colleagues have discovered that assigning
a reasonable rule-of-thumb reference temperature, like 60 degrees F, works
nearly as well and allows a spreadsheet-based approach to be used for this
sort of analysis with a somewhat but not unreasonably increased error term
in the results.

In using PRISM, we need at least a year of billing data before and after
installation of conservation measures, *plus* weather data for that period
and up to ten previous years.  The complete weather record is used to
establish a baseline for annual or monthly degree days, and then the
results are compared to the weather for the pre- and post-installation
periods.  That way, if it was 5% warmer than average for the year before
conservation measures were installed, but 10% colder than average the
year after, we can adjust actual usage by the ratio of actual to long-term
average degree days and not get fooled by the swings in actual results
into thinking that conservation works better or worse than it actually
does.

The same sort of thinking could be applied to overall energy budgets.
All other things being equal -- but of course, they never are, because
building usage patterns also vary quite a bit from year to year --
if you can apply this kind of degree-day based weather adjustment to
your energy bills, you can predict what will happen to usage, and your
future bill, given either a colder or milder winter (or a hotter or
cooler summer, if you're looking at cooling degree-days).

As for degree-day data itself, you'll probably end up having to calculate
it based on available weather data.  The NOAA national weather data center
is in Asheville, North Carolina.  They can provide 10 to 20 years of
high/low temperature data for any major weather station in the country,
and a lot of the smaller ones as well (although the data there tends to
be spottier).  It can be provided either on paper or ASCII files on
regular ole diskettes for a fairly minimal charge and rapid turnaround.

Hope this helps.  I can't pass myself off as a meteorologist or energy
engineer, but perhaps this info will be of use.

Fred Heutte
Sunlight Data Systems
PO Box 40308
Portland, Oregon  97204
503/222-9572
sunlight@well.sf.ca.us

"Why make it simple and easy
 When you can make it complex and wonderful"
Newsgroups: alt.wais