Chapter IIC. Historical Analysis of the Urban Climate of Los Angeles: Analysis and results
Analysis and results
We first examined yearly maxima at each of the eleven stations over the period of record available. Linear regressions were performed to discern overall trends in the data. The statistical significance of these trends were assessed using a t-statistic to determine the probability p that these trends could be obtained from a population satisfying the one-sided null hypothesis (in this case, slope = 0 or of the opposite sign). Table 5 summarizes characteristics of the data and the regression analysis. Significant trends, using a 95% confidence level (p < 5%), are observed at Burbank, Culver City, and the Civic Center weather stations. The rate of increase in yearly maximum temperatures at the Civic Center, discussed in Akbari et al. (1990), is the largest observed of all stations. The warming effect experienced by the Civic Center area may be compounded by increasing microclimate influences. The Civic Center data record is not representative of the entire Los Angeles region; at most stations, a more modest rate of change is found or the trends are not statistically significant. In similar fashion, we examined monthly averages of daily maximum and minimum temperatures for linear trends at the eleven stations selected. Again, a t-statistic is used to assess the significance of the trends. We present the regression results for the months of March, June, September, and December in Table 6.
The three stations at which large, statistically significant trends were found in yearly temperature maxima--Burbank, Culver City, and the Civic Center--and UCLA show June rates between 0.05 and 0.09K (0.09 and 0.16°F) per year. Milder increases are observed in March and September averages. These increases suggest that the daytime warming is becoming more important over time at these stations during the summer months. However, whether this rise in daily maxima is caused by local-scale heat island effects or simply by changes in microclimate below canopy height is uncertain. Other significant increases in daily maximum temperatures are detected at Pasadena (June, 0.04 ± 0.01K per year), Pomona (December, 0.01 ± 0.01K per year), and Torrance (June, 0.05 ± 0.02°F per year).
On the other hand, significant increases in monthly averages of daily minimum temperatures are present for most months at all stations. The timing of the warming trends is different also; in many cases, the March and September trends are comparable in size to those for June. Stations which showed no tendency for daytime warming trends--L.A. International Airport, Pomona, Santa Ana, and Santa Monica--show large trends in their monthly mean minima. The largest increase is seen for Santa Ana. The increase in the number and size of the trends over those for daytime indicates the general tendency for urban warming to be most prevalent at night.
The analysis confirms the presence of historical increases in daytime and nighttime temperatures at Burbank, Culver City, the Civic Center, and UCLA. These four stations are all located within areas of dense urban development, and the findings are consistent with the presence of strong heat island effects. However, this level of analysis is inadequate to discern among the various causes for these temperature increases, such as heat island effects, microclimate changes, and long-term synoptic climate variations.
Climate records from other cooperative network stations show milder increases in yearly and daily maximum temperatures. These differences must be kept in mind when estimating, for example, the energy and air pollution costs of heat island effects in the Los Angeles area. If one assumes that the microclimate changes at the less densely developed urban areas outside of the city center are relatively small, then findings from Pasadena, Pomona, or Santa Ana should be more representative of local-scale effects. Synoptic climate variations may be assessed by expanding the analysis to include more historical climate records from non-urban areas, although this task is complicated by the expansive scale of urban development in the Los Angeles region. Continue to: Chapter III. Analysis of Short-Term Data
| Monthly Average of Daily Maxima | Monthly Average of Daily Minima | |||||||||
| Mean | Std. Dev. | Slope | Mean | Std. Dev. | Slope | |||||
| Month | (°C) | (°F) | (Kelvin) | (K/yr) | p(Slope=0) | (°C) | (°F) | (Kelvin) | (K/yr) | p(Slope=0) |
| March | 21.3 | 70.3 | 1.9 | 0.04 ± 0.02 | 0.03 | 7.4 | 45.4 | 1.6 | 0.01 ± 0.02 | 0.84 |
| June | 27.7 | 81.9 | 2.6 | 0.09 ± 0.02 | 0.00 | 13.8 | 56.8 | 1.2 | 0.04 ± 0.01 | 0.00 |
| September | 30.7 | 87.3 | 2.2 | 0.02 ± 0.02 | 0.28 | 14.9 | 58.8 | 1.7 | 0.03 ± 0.01 | 0.03 |
|
December |
19.8 | 67.7 | 2.1 | 0.00 ± 0.02 | 0.93 | 5.4 | 41.7 | 1.4 | -0.03 ± 0.01 | 0.03 |
|
March |
19.9 | 67.9 | 1.4 | 0.04 ± 0.01 | 0.00 | 8.9 | 48.0 | 1.6 | 0.06 ± 0.01 | 0.00 |
|
June |
23.4 | 74.1 | 1.8 | 0.07 ± 0.01 | 0.00 | 14.2 | 57.6 | 1.3 | 0.04 ± 0.01 | 0.00 |
|
September |
26.1 | 78.9 | 1.8 | 0.06 ± 0.01 | 0.00 | 15.8 | 60.4 | 1.6 | 0.05 ± 0.01 | 0.00 |
|
December |
20.1 | 68.1 | 1.8 | -0.03 ± 0.02 | 0.07 | 7.8 | 46.0 | 1.3 | 0.03 ± 0.01 | 0.02 |
| March | 20.6 | 69.1 | 1.8 | 0.04 ± 0.02 | 0.06 | 10.7 | 51.3 | 1.5 | 0.06 ± 0.02 | 0.00 |
|
June |
25.6 | 78.1 | 2.1 | 0.05 ± 0.02 | 0.05 | 15.9 | 60.6 | 1.4 | 0.07 ± 0.02 | 0.00 |
|
September |
28.3 | 82.9 | 1.8 | 0.01 ± 0.02 | 0.78 | 17.8 | 64.0 | 1.6 | 0.06 ± 0.02 | 0.00 |
|
December |
19.9 | 67.8 | 2.0 | 0.03 ± 0.02 | 0.19 | 9.4 | 48.9 | 1.5 | 0.02 ± 0.02 | 0.32 |
|
March |
18.4 | 65.2 | 1.6 | 0.01 ± 0.02 | 0.50 | 10.1 | 50.1 | 1.4 | 0.06 ± 0.01 | 0.00 |
|
June |
22.2 | 72.0 | 1.6 | 0.02 ± 0.02 | 0.41 | 15.3 | 59.5 | 1.0 | 0.03 ± 0.01 | 0.02 |
|
September |
24.6 | 76.3 | 1.6 | 0.01 ± 0.02 | 0.50 | 16.9 | 62.5 | 1.4 | 0.06 ± 0.02 | 0.00 |
|
December |
18.9 | 66.1 | 1.8 | 0.01 ± 0.02 | 0.58 | 8.7 | 47.7 | 1.3 | 0.04 ± 0.01 | 0.01 |
|
March |
21.1 | 70.0 | 2.1 | 0.02 ± 0.01 | 0.20 | 7.7 | 45.8 | 1.3 | 0.03 ± 0.01 | 0.00 |
|
June |
27.3 | 81.1 | 2.1 | 0.04 ± 0.01 | 0.01 | 13.3 | 55.9 | 1.2 | 0.04 ± 0.01 | 0.00 |
|
September |
30.6 | 87.0 | 1.9 | 0.02 ± 0.01 | 0.07 | 14.9 | 58.9 | 1.6 | 0.04 ± 0.01 | 0.00 |
|
December |
19.9 | 67.9 | 2.0 | 0.01 ± 0.01 | 0.62 | 6.3 | 43.3 | 1.3 | 0.02 ± 0.01 | 0.06 |
|
March |
21.0 | 69.8 | 2.0 | -0.01 ± 0.01 | 0.77 | 5.6 | 42.1 | 1.8 | 0.06 ± 0.01 | 0.00 |
|
June |
28.5 | 83.3 | 1.8 | 0.00 ± 0.01 | 0.98 | 11.7 | 53.1 | 1.3 | 0.04 ± 0.01 | 0.00 |
|
September |
31.2 | 88.2 | 2.0 | -0.01 ± 0.01 | 0.62 | 13.1 | 55.6 | 1.9 | 0.07 ± 0.01 | 0.00 |
|
December |
19.3 | 66.8 | 2.4 | 0.04 ± 0.02 | 0.00 | 3.5 | 38.3 | 1.8 | 0.06 ± 0.01 | 0.00 |
|
March |
21.1 | 70.0 | 1.5 | 0.02 ± 0.02 | 0.22 | 8.5 | 47.3 | 2.0 | 0.12 ± 0.02 | 0.00 |
|
June |
25.6 | 78.0 | 1.7 | 0.01 ± 0.02 | 0.80 | 14.5 | 58.1 | 1.6 | 0.09 ± 0.02 | 0.00 |
|
September |
28.8 | 83.8 | 1.7 | -0.02 ± 0.02 | 0.24 | 15.9 | 60.7 | 1.8 | 0.11 ± 0.02 | 0.00 |
|
December |
20.3 | 68.6 | 1.8 | 0.01 ± 0.02 | 0.67 | 6.8 | 44.3 | 1.8 | 0.08 ± 0.02 | 0.00 |
|
March |
17.4 | 63.3 | 1.4 | -0.01 ± 0.02 | 0.56 | 10.3 | 50.6 | 1.3 | 0.06 ± 0.02 | 0.00 |
|
June |
19.9 | 67.8 | 2.1 | -0.05 ± 0.03 | 0.07 | 14.6 | 58.3 | 0.9 | 0.03 ± 0.01 | 0.01 |
|
September |
22.3 | 72.2 | 1.7 | -0.02 ± 0.02 | 0.42 | 16.3 | 61.4 | 1.4 | 0.06 ± 0.01 | 0.00 |
|
December |
18.4 | 65.1 | 1.7 | 0.01 ± 0.02 | 0.53 | 9.8 | 49.6 | 1.4 | 0.04 ± 0.02 | 0.04 |
|
March |
19.8 | 67.6 | 1.4 | 0.03 ± 0.02 | 0.09 | 8.3 | 47.0 | 1.4 | 0.08 ± 0.01 | 0.00 |
|
June |
23.6 | 74.5 | 1.6 | 0.05 ± 0.02 | 0.02 | 13.8 | 56.9 | 1.1 | 0.05 ± 0.01 | 0.00 |
|
September |
26.1 | 79.0 | 1.7 | 0.04 ± 0.02 | 0.08 | 15.5 | 59.9 | 1.4 | 0.06 ± 0.02 | 0.00 |
|
December |
19.8 | 67.6 | 1.9 | -0.01 ± 0.02 | 0.80 | 7.3 | 45.1 | 1.4 | 0.04 ± 0.02 | 0.02 |
|
March |
20.8 | 69.4 | 1.9 | -0.02 ± 0.01 | 0.27 | 6.6 | 43.9 | 1.6 | 0.01 ± 0.01 | 0.40 |
|
June |
26.1 | 79.0 | 1.8 | -0.02 ± 0.01 | 0.19 | 13.1 | 55.5 | 1.3 | 0.02 ± 0.01 | 0.04 |
|
September |
29.1 | 84.3 | 1.8 | -0.02 ± 0.01 | 0.12 | 13.6 | 56.5 | 1.7 | 0.04 ± 0.01 | 0.00 |
|
December |
20.0 | 68.0 | 2.0 | -0.01 ± 0.01 | 0.52 | 4.7 | 40.4 | 1.4 | -0.01 ± 0.01 | 0.34 |
|
March |
18.9 | 66.1 | 1.7 | 0.02 ± 0.02 | 0.26 | 10.0 | 50.0 | 1.2 | 0.03 ± 0.02 | 0.06 |
|
June |
22.2 | 72.0 | 1.7 | 0.05 ± 0.02 | 0.02 | 14.3 | 57.7 | 1.0 | 0.03 ± 0.01 | 0.04 |
|
September |
25.3 | 77.5 | 1.9 | 0.01 ± 0.02 | 0.57 | 16.3 | 61.3 | 1.6 | 0.03 ± 0.02 | 0.18 |
|
December |
19.2 | 66.6 | 1.9 | 0.00 ± 0.02 | 0.99 | 10.4 | 50.7 | 1.4 | 0.00 ± 0.02 | 0.90 |
Table 6: Mean, standard deviation, and regression results against year for monthly averages of daily temperature maxima and minima at various cities over time. Statistically significant slopes at 95% confidence level, for which p(Slope=0) is less than or equal to 0.05, are in gray.