CHAPTER 11

MINTMP Correlation With Dew Point Temperature

T

his chapter reviews climate data, collected from 303 U.S. cities, that indicate a relatively strong correlation between MINTMP and dew point temperature. This correlation is more obvious if cities whose average monthly precipitation (PRECIP) is less than 3.5 inches* are excluded from the database.

Influence of PRECIP on Dew Point and MINTMP Temperature Correlations

Table 11-1, page 195, shows two correlations between dew point temperature and MINTMP (average monthly minimum temperature).

The first correlation within this table disregards PRECIP as a variable; nevertheless, the sample linear correlation coefficient for July (lowest correlation of all months) is about 80%.

The second correlation reduces the statistical database by omitting cities whose PRECIP is less than 3.5 inches; the sample linear correlation coefficient for July then rises to about 96%.

The correlation for July is consistently the lowest of the twelve months. Perhaps this observation relates to the fact that July is the hottest month in the United States. The sample linear correlation coefficient tends to increase on either side of July.

Another Look at PRECIP Influence

Table 11-2, pages 196-205, shows climate data for July, sorted by PRECIP. In this table, monthly PRECIP values range from “0.0” to “10.2.” By comparing the PRECIP and dew point temperature columns (highlighted by grayscale), while moving down the table, two trends become obvious, namely:

• From the top of Table 11-2 (at 0.0 inches of PRECIP) to the middle of the table (at PRECIP just short of 3.5 inches), we see an inconsistent matching relationship between dew point and average monthly minimum temperature.

• For PRECIP of 3.5 inches or more, we see agreement between dew point temperature and MINTMP.

The table suggests that PRECIP, when above a certain threshold, is a synergistic factor that improves the correlation between dew point temperature and monthly PRECIP.

Dew Point Temperature and MINTMP

Are Analyzed for 303 Cities of the U.S.

Table 11-3, pages 206-215, displays the arithmetic differences between MINTMP (average monthly minimum temperature) and dew point temperature, the latter subtracted from the former, for each month. This table is sorted by city and state.

This table shows many instances when differences between dew point temperature and average monthly minimum temperature are close to zero.

Accordingly, we may cautiously use Table 11-3, usually as a last resort, to estimate dew point temperature from an independently reported MINTMP. Not all weather stations report dew point temperature, but most weather stations report the MINTMP. In Chapter 10 (pages 186-187) we illustrate application of Table 11-3 to substitute MINTMP for dew point temperature while estimating PMV_SHADE. ■

	TABLE 11-1: INFLUENCE OF PRECIP ON DEW POINT TEMPERATURE AND MINTMP CORRELATIONS
PRECIPI-TATION	CORREL- ATION
THRESHOLD	MEASURES	JAN	FEB	MAR	APR	MAY	JUN	JUL	AUG	SEP	OCT	NOV	DEC
None	R^2	0.952	0.936	0.926	0.870	0.785	0.673	0.647	0.700	0.802	0.876	0.998	0.930
	rxy	0.976	0.968	0.962	0.933	0.886	0.820	0.804	0.835	0.895	0.936	0.999	0.964
3.5 Inches	R^2	0.962	0.958	0.955	0.942	0.950	0.942	0.916	0.942	0.971	0.971	0.947	0.961
	rxy	0.981	0.979	0.977	0.971	0.975	0.971	0.957	0.971	0.985	0.985	0.973	0.980

R² implies the fraction of variation in the dependent variable that is explained by the independent variable(s).

In July, for example, 65% of variation in average monthly minimum temperature is explained by dew point temperature – regardless of average monthly precipitation (see first row of table, above).

But, if average monthly precipitation is at least 3.5 inches, then R² increases to about 92% (see threshold equal to 3.5 inches in table above).

r_xy, the Sample Linear Correlation Coefficient, is the square root of R².

“+1” represents strong positive correlation

“-1” represents strong negative correlation

	TABLE 11-2: JULY AT A GLANCE – SORTED BY PRECIP
		PRECIP	TEMPERATURE °F			THERMAL COMFORT INDICES
STATE	CITY		DEWPNT	MAXTMP	MINTMP	MAXTMP	MINTMP	AVETMP
CA	ALAMEDA NAS	0.0	54	71	56	-1.61	-4.64	-3.12
CA	BAKERSFIELD WSO AP	0.0	51	98	69	3.55	-2.05	0.75
CA	CHINA LAKE NAF	0.0	42	103	70	.	-1.95	1.25
CA	EL TORO MCAS	0.0	59	82	61	0.65	-3.55	-1.45
CA	FRESNO WSO AP	0.0	53	98	65	3.58	-2.83	0.37