ASHRAE Journal - June 2019 - 67

COLUMN ENGINEER'S NOTEBOOK

¥ Relative humidity.
While averages and bin data have their uses, each format has certain limitations. Averages, whether monthly
or annually, typically do not show the range of variation
of the speciﬁc parameter, nor the relationship between
multiple parameters. Bin data captures the range of
variation of a speciﬁc parameter, but, typically shows, at
most, a minimal correlation between parameters (e.g.,
mean wet-bulb temperature for a speciﬁc dry-bulb
temperature bin). For most advanced weather analytic
studies, hourly data is the best primary resource as it
captures both simultaneous occurrences of multiple
parameters along with time of day correlation. A body
of hourly observations of simultaneous weather parameter observations can be processed to provide time of
day related analyses, i.e., monthly heating degree hours
during the ofﬁce occupancy period. The most common
form of portraying the simultaneous occurrences of
dry-bulb temperature and moisture content of the air is
hourly frequency bin diagram portrayed on a psychrometric chart, as shown in Figure 2 for New York City, with
comfort zones shown for two levels of clothing in still
air and for airﬂow across the body at 236 fpm (1.2 m/s)
velocity. This graphic gives insight into the feasibility of
natural ventilation in that location. Although the comfort zone is determined, in ASHRAE Standard 55-2016,1
by the operative temperature, a function of both the air
temperature and mean radiant temperature, a good
presumption would be that, barring excessive solar
irradiation, interior surface temperatures are likely to
approximate air temperature when conditioning is by
natural ventilation.
Another useful climate graphic portrays diurnal temperature variation, in this case for a California location.
The graphic demonstrates that in all months, the diurnal swing for almost all days traverses the comfort zone
(in this case, determined by the software package and
not necessarily related to ASHRAE Standard 55-20161).
Portrayal of weather data in this format strongly suggests that a thermally massive building with adequate
controlled outdoor ventilation could maintain comfort
without recourse to refrigerated cooling.

Psychrometric Climate Analysis
Packages of psychrometric functions that can be
embedded in the most common spreadsheet platforms
are available from several vendors. These packages are

FIGURE 1 Simple representation of climate data (image courtesy WSP Group).

Hourly Average Dry-Bulb Temperature

Dry-Bulb
Temperature (°F)
0%
<32
51%
32 to 70
11%
70 to 75
36%
75 to 100
0%
>100

Max
92.15
Min
44.51

Midnight
0.00

Nov

6 p.m.

Sep
Noon

Jul
May

6 a.m.

Mar
Jan
Annual Relative Humidity

Relative
Humidity (%)
<20
0%
0%
20 to 40
24%
40 to 60
31%
60 to 80
43%
>80

Max
95.65
Min
45.90
0.00

Midnight
6 p.m.

Nov
Sep
Noon

Jul
May

6 a.m.

Mar
Jan
Annual Solar Radiation

Global Horizon
Radiation (Btu/h·ft2)
47% <1
14% 1 to 50
9%
50 to 100
12% 100 to 150
17% >150

Max
254.11
Min
0.00

Midnight
Nov

6 p.m.

Sep
Jul

Noon
May

6 a.m.

Mar
Jan

extremely valuable for processing annual weather data
consisting of 8,760 sets of hourly weather observations of
multiple weather parameters. While the typical Typical
Meteorological Year (TMY) weather data format includes
all common parameters that describe moisture content
related metrics, dry-bulb, wet-bulb, dew-point, humidity ratio, vapor pressure and enthalpy, some hourly data
sources are not this complete, and will require processing at least two of the non-parallel psychrometric
J U N E 2 0 19

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ASHRAE Journal - June 2019

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