Global Weather Sensitivity: A Comparative Study - albertotroccoli.org

least 10 years of data history were included. Data reporting an unusual number
of repeated zeroes, extremely low precipitation values, or highly erratic and
improbable precipitation values were excluded. Finally, where data was missing,
it was replaced with the average value for that day over all of the available years.
These data cleansing techniques led to some countries having very few reliable
weather stations, which may bias results in data scarce environments.
Weather data was gathered in the form of daily observations of temperature
and precipitation for as many years as records were readily available. To
make this easily interpretable, data was translated into three categories: annual
totals of heating-degree-days (HDDs), cooling-degree-days (CDDs), and
precipitation. HDDs and CDDs are quantitative indices that demonstrate daily
deviations of daily average temperature from 65 degrees Fahrenheit, considered
to be the lowest point for heating and cooling demand in commercial and residential
buildings. For example, a day with an average temperature of 75 degrees
would represent 10 CDDs. For each weather data type, the mean and standard
deviation were calculated, from which the coefficient of variance (CV), or the
STDEV/MEAN, was found.
Each country’s CV value was calculated as the
average of all of the weather stations in that country. CV data for each weather
variable can be found in Table 7.
Weather sensitivity coefficients, presented as elasticity scores by sector and
weather variable, were calculated by Larsen [6]. Elasticities are defined as the
estimated change in output to a given sector given a 1% change in a given
weather variable (HDD, CDD, or Total Precipitation), and are found by taking
the partial derivative of a fitted production model with respect to each weather
variable. Though Larsen’s coefficients are sign-specific, representing positive and
negative impacts on output due to weather behavior, all elasticity values were
made positive to represent the total range of weather sensitivity. For example,
7