Spatial-temporal change of climate in relation to urban fringe development in central Arizona-Phoenix
Author(s):
- Anthony Brazel, Department of Geography, Arizona State University
- Brent Hedquist, Department of Geography, Arizona State University
Abstract:
Not many studies have documented climate and air quality changes of settlements at early stages of development. This is because high quality climate and air quality records are deficient for the periods of the early 18th century to mid 20th century when many U.S. cities were formed and grew. Dramatic landscape change induces substantial local climate change during the incipient stage of development. Rapid growth along the urban fringe in Phoenix, coupled with a fine-grained climate monitoring system, provide a unique opportunity to study the climate impacts of urban development as it unfolds.
Generally, heat islands form, particularly at night, in proportion to city population size and morphological characteristics. Drier air is produced by replacement of the countryside's moist landscapes with dry, hot urbanized surfaces. Wind is increased due to turbulence induced by the built-up urban fabric and its morphology; although, depending on spatial densities of buildings on the land, wind may also decrease. Air quality conditions are worsened due to increased city emissions and surface disturbances. Depending on the diversity of microclimates in pre-existing rural landscapes and the land-use mosaic in cities, the introduction of settlements over time and space can increase or decrease the variety of microclimates within and near urban regions. These differences in microclimatic conditions can influence variations in health, ecological, architectural, economic, energy and water resources, and quality-of-life conditions in the city. Therefore, studying microclimatic conditions which change in the urban fringe over time and space is at the core of urban ecological goals as part of LTER aims.
In analyzing Phoenix and Baltimore long-term rural/urban weather and climate stations, Brazel et al. (In progress) have discovered that long-term (i.e., 100 years) temperature changes do not correlate with populations changes in a linear manner, but rather in a third-order nonlinear response fashion. This nonlinear temporal change is consistent with the theories in boundary layer climatology that describe and explain the leading edge transition and energy balance theory. This pattern of urban vs. rural temperature response has been demonstrated in relation to spatial range of city sizes (using population data) for 305 rural vs. urban climate stations in the U.S. Our recent work on the two urban LTER sites has shown that a similar climate response pattern also occurs over time for climate stations that were initially located in rural locations have been overrun bu the urban fringe and subsequent urbanization (e.g., stations in Baltimore, Mesa, Phoenix, and Tempe).
Lack of substantial numbers of weather and climate stations in cities has previously precluded small-scale analyses of geographic variations of urban climate, and the links to land-use change processes. With the advent of automated weather and climate station networks, remote-sensing technology, land-use history, and the focus on urban ecology, researchers can now analyze local climate responses as a function of the details of land-use change.
Therefore, the basic research question of this study is: How does urban climate change over time and space at the place of maximum disturbance on the urban fringe?
Hypotheses
1. Based on the leading edge theory of boundary layer climate change, largest changes should occur during the period of peak development of the land when land is being rapidly transformed from open desert and agriculture to residential, commercial, and industrial uses.
2. One would expect to observe, on average and on a temporal basis (several years), nonlinear temperature and humidity alterations across the station network at varying levels of urban development.
3. Based on past research on urban climate, one would expect to see in areas of the urban fringe, rapid changes in temperature (increases at night particularly), humidity (decreases in areas from agriculture to urban; increases from desert to urban), and wind speed (increases due to urban heating).
4. Changes of the surface climate on the urban fringe are expected to be altered as a function of various energy, moisture, and momentum control parameters, such as albedo, surface moisture, aerodynamic surface roughness, and thermal admittance. These parameters relate directly to population and land-use change (Lougeay et al. 1996).
Keywords:
Temporal Coverage:
2001-08-18 to 2002-05-01Geographic Coverage:
Geographic Description: southeast Phoenix metropolitan area, cities of Tempe, Chandler, MesaBounding Coordinates:
Longitude:-111.93424 to -111.628721
Latitude:33.401989 to 33.259363
Contact:
Information Manager, Arizona State University,Global Institute of Sustainability,POB 875402,TEMPE
caplter.data@asu.edu
Methods used in producing this dataset: Show
Data Files (8) :
Tabular: 37_mean_savi_1.csv
Description: Mean values for soil adjusted vegestation index
Column | Description | Type | Units |
---|---|---|---|
site_id | unique identifier used to distinguish sites. |
string | |
radius | The radius of the area around the instruments. |
integer | meter |
year | The year the data was collected. |
integer | nominalYear |
Pixels | number of pixels in circle |
integer | dimensionless |
AREA | Area of the circle |
float | squareMeter |
MIN | minimum value for SAVI within circle |
float | dimensionless |
MAX | maximum value for SAVI within circle |
float | dimensionless |
RANGE | range values for SAVI within circle |
float | dimensionless |
MEAN | mean value for SAVI within circle |
float | dimensionless |
STD | standard deviation for SAVI within circle |
float | dimensionless |
SUM | sum of SAVI for all pixels within circle |
float | dimensionless |
Tabular: 37_sites_1.csv
Description: site description for the HOBO station locations
Column | Description | Type | Units |
---|---|---|---|
site_id | Unique identification used to distinguish sites. |
string | |
description | Descriptions of the sites used in this study. |
string |
Tabular: 37_weatherstaa201_1.csv
Description: weatherstation data at site AA201
Column | Description | Type | Units |
---|---|---|---|
id | sample Id |
integer | |
site_id | Unique identification number |
string | |
Date | date the sample was taken |
datetime | Format: YYYY-MM-DD |
time | time the sample was taken |
datetime | Format: HH:MM:SS A/P |
Temperature | temperature at the time of sampling |
float | celsius |
Dew Point | dew point at the time of sampling |
float | celsius |
RH | relative humidity |
float | dimensionless |
Tabular: 37_weatherstab201_1.csv
Description: weatherstation data at site AB201
Column | Description | Type | Units |
---|---|---|---|
site_id | Unique identification used to distinguish sites. |
string | |
id | Sequential whole numbers used to identify the data collected from the weather station AB201. |
integer | |
Date | Date the data was taken. |
datetime | Format: YYYY-MM-DD |
time | Time the reading was taken. |
datetime | Format: HH:MM:SS A/P |
Temperature | Temperature at the time the reading was taken. |
float | celsius |
Dew Point | The dew point at the time the reading was taken. |
float | celsius |
RH | relative humidity |
float | dimensionless |
Tabular: 37_weatherstab221_1.csv
Description: weatherstation data at site AB221
Column | Description | Type | Units |
---|---|---|---|
id | Sequential unique whole numbers used to identify data taken from weather station AB221 |
integer | |
site_id | Unique identification used to distinguish sites. |
string | |
Date | Date the reading was taken |
datetime | Format: YYYY-MM-DD |
time | Time the reading was taken |
datetime | Format: HH:MM:SS A/P |
Temperature | Temperature at the time the reading was taken |
float | celsius |
Dew Point | Dew point at the time the reading was taken |
float | celsius |
RH | relative humidity |
float | dimensionless |
Tabular: 37_weatherstac201_1.csv
Description: weatherstation data at site AC201
Column | Description | Type | Units |
---|---|---|---|
id | Sequential unique whole numbers used to identify readings taken by the weatherstation AC201 |
integer | |
site_id | Unique identification used to distinguish sites. |
string | |
Date | Date the reading was taken |
datetime | Format: YYYY-MM-DD |
time | Time at which the reading was taken |
datetime | Format: HH:MM:SS A/P |
Temperature | Temperature at which the reading was taken |
float | celsius |
Dew Point | Dew point at which the reading was taken. |
float | celsius |
RH | relative humidity in percent |
float | dimensionless |
Tabular: 37_weatherstad211_1.csv
Description: weatherstation data at site AD211
Column | Description | Type | Units |
---|---|---|---|
id | Sequential unique whole numbers used to identify readings taken by the weather station AC211 |
integer | |
site_id | Unique identification used to distinguish sites. |
string | |
Date | Date the reading was taken. |
datetime | Format: YYYY-MM-DD |
time | Time the reading was taken |
datetime | Format: HH:MM:SS A/P |
Temperature | Temperature at the time the reading was taken |
float | celsius |
Dew Point | Dew point at the time the reading was taken |
float | celsius |
RH | relative humidity |
float | dimensionless |
Tabular: 37_weatherstcorbell_1.csv
Description: weatherstation data at site Corbell
Column | Description | Type | Units |
---|---|---|---|
id | Sequential unique whole numbers used to identify readings taken by the weatherstation at Corbell |
integer | |
site_id | Unique identification used to distinguish sites. |
string | |
Date | Date the reading was taken |
datetime | Format: YYYY-MM-DD |
time | TIme the reading was taken |
datetime | Format: HH:MM:SS A/P |
Temperature | Temperature at the time the reading was taken |
float | celsius |
Dew Point | Dew point at the time the reading was taken. |
float | celsius |
RH | relative humidity |
float | dimensionless |