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ChaptersComrie, A.C., 1990: The climatology of surface ozone in rural areas: a conceptual model. Progress in Physical Geography 14, 295-316.
Ozone occurs both naturally and anthropogenically in the atmosphere, and several processes result in temporal and spatial variations in its concentration. Concern here is principally with surface ozone concentrations, although effects of ozone at other levels in the atmosphere are included where appropriate. The ozone problem will be approached via three phases of examination: firstly, the basic behavior of ozone, which comprises photochemical formation processes and relationships to meteorological variables; secondly, the sources of ozone, both background sources in the stratosphere and free troposphere, and anthropogenic sources in the planetary boundary layer (PBL) from urban and industrial plumes; thirdly, the transport of ozone within the PBL, not only the long range transport and accumulation of ozone in synoptic high pressure systems, but also subsynoptic local effects at the mesoscale. A conceptual model of the formation and transport of surface ozone in rural areas is formulated, and presented by way of a summary, with a brief discussion of promising research approaches and techniques. (from the introduction to the paper)
Comrie, A.C., 1992: A procedure for removing the synoptic climate signal from environmental data. International Journal of Climatology 12, 177-183.
Using weather-type frequencies from a synoptic climatology, a technique is presented that discriminates between within-type and between-type variations in a time series of climate-related environmental data. The removal of the synoptic climate signal, or declimatizing, is based on normalizing the data by the mean annual weather-type frequencies for the study period. Declimatizing is illustrated symbolically and with a worked hypothetical example. An application of the procedure to visibility data from Pittsburgh, Pennsylvania demonstrates its utility in decomposing complex climate-related environmental data into its component synoptic and non-synoptic influences. The methodology can also distinguish the relative importance of between-type and within-type changes in a synoptic climatology.
Comrie, A.C., 1992: An enhanced synoptic climatology of ozone using a sequencing technique. Physical Geography 13, 53-65.
A synoptic classification scheme is derived to examine basic associations between surface ozone pollution and the atmospheric circulation. Nine weather types are related to the daily maximum ozone concentration in Pittsburgh, Pennsylvania for the years 1978-1987. A sequencing technique is developed to extract the maximum utility from the classification scheme. An analysis of the sequences of synoptic weather types highlights additional spatial and temporal information, such as air mass origins, system speed and seasonal variations. Low concentrations of ozone are experienced in winter during lake-effect and cyclonic storms, which move in rapidly from the northwest bringing cold, cloudy, windy conditions with precipitation. High concentrations occur during summer in slow-moving anticyclones, with southwesterly transport and warm, sunny conditions that are favorable for photochemical formation of ozone. The study demonstrates that the use of a sequencing technique in conjunction with a synoptic classification scheme enables a more thorough analysis of the data.
Comrie, A.C. and Yarnal, B., 1992: Relationships between synoptic-scale atmospheric circulation and ozone concentrations in metropolitan Pittsburgh, Pennsylvania. Atmospheric Environment 26B, 301-312.
A synoptic climatology demonstrates the relationships between the atmospheric circulation and surface ozone (O3) concentrations. To deduce these associations, a subjective synoptic classification scheme is applied to ten years' O3 data from the Pittsburgh metropolitan area. The results focus on four aspects of the atmospheric circulation-O3 relationship: average, extreme-event, between-season, and year-to-year conditions. On average, each of the nine circulation types is related to a characteristic O3 concentration level and cumulative O3 dose. Extreme high-O3 events are associated with either the western side of a slowly-migrating anticyclone or a stagnating extended high-pressure ridge; low-O3 events are experienced under cool and cloudy cyclonic conditions. Between-season variations in the average and extreme circulation-O3 relationships are observed: the high-pressure features that produce the highest O3 levels in summer are related to low levels in winter, while circulation patterns that contribute very little to summertime O3 buildup are associated with the highest levels of wintertime O3. The latter situation could be caused by tropopause folding and the introduction of stratospheric ozone in winter months. While zonal (meridional) circulation regimes tend to produce lower (higher) mean annual O3 levels, such year-to-year changes in synoptic-type frequencies do not appear to be strongly related to interannual variations in O3, and other non-climatic factors appear to be of greater importance.
Comrie, A.C., 1994: A synoptic climatology of rural ozone pollution at three forest sites in Pennsylvania. Atmospheric Environment 28A, 1601-1614.
An analysis reveals strong relationships between ozone (O3) concentrations at three rural forest sites in north-central Pennsylvania and the synoptic-scale atmospheric circulation. To identify these associations, a synoptic classification scheme is applied to daily maximum 1h ambient surface O3 measurements for the growing seasons of 1988, 1989 and 1990. The results cover five aspects of the atmospheric circulationrural O3 relationship: overall conditions, O3 extremes, key weather sequences, the seasonal cycle and interannual differences. Overall, high rural O3 concentrations occur with southwesterly transport conditions on the western sides of anticyclones, while low values are found in post-frontal and cyclonic conditions. While slow-moving or stagnant anticyclones are occasionally associated with high-O3 episodes, these situations are most frequent in the same southwesterly transport regime. This behavior is the inverse of that found in Pittsburgh in a closely related study by Comrie and Yarnal (Atmospheric Environment Vol. 26B, No. 3, pp. 301-312, 1992). Unlike urban environments where air-mass stagnation leads to an episode, an episode in a non-urban environment requires transport of a polluted air mass from a source region. In this latter scenario, forest O3 levels are critically dependent on the air-mass history and trajectory. Key weather-pattern sequences show that the southwesterly transport must be preceded by stagnation of the air mass over an upwind polluted region, with stagnation and transport each lasting one to two days. The relative importance of these complementary mechanisms in the O3 climatology remains the same through the growing season. The unusually hot and dry conditions of the summer of 1988 were more favorable for O3 formation across all synoptic patterns, as compared to 1989 and 1990.
Comrie, A.C., 1994: Tracking ozone: air-mass trajectories and pollutant source regions influencing ozone in Pennsylvania forests. Annals of the Association of American Geographers 84 (4), 635-651.
Ground-level ozone pollution is causing measurable damage to the forests of the eastern United States, including those in Pennsylvania's Allegheny Plateau region. This area is surrounded by many urban and industrial pollution sources in the Midwest, Southeast, and Northeast United States and in southeast Canada. Any of these may play critical roles as source regions from which ozone and its precursor pollutants are carried toward the forests. This study identifies those geographic regions with the greatest potential influence on forest ozone concentrations via a climatological analysis of air-mass trajectories. In this analysis, observed meteorological data and a trajectory model are used to calculate the spatial history of polluted air-masses. Multiple trajectories are examined using a newly adapted methodology of ensemble trajectory analysis in combination with ozone data and key synoptic weather patterns from a related climatology. Results indicate a critical region of influence centered on the junction of the Ohio and Mississippi River Valleys, and extending eastward up the Ohio River Valley. These parts of Indiana, Ohio, Kentucky, Illinois and Missouri have the greatest likelihood of influencing high-ozone air masses arriving in Pennsylvania, and they coincide with some of the highest emission regions in the country. In the worst cases, air masses accumulate pollutants for several days as they stagnate over this region, and then continue accumulating pollutants as they move slowly toward Pennsylvania. Brief comments regarding the research and policy implications of these results are provided.
Comrie, A.C., 1996: An All-Season Synoptic Climatology of Air Pollution in the U.S.-Mexico Border Region.Professional Geographer 48 (3), 237-251.
The potential exists for widespread air quality problems in the U.S.-Mexico borderlands. Climate and weather are major factors governing the behavior of air pollution, and thus there is a need for greater understanding of border-region air pollution climatology. This paper presents a synoptic climatology of the 850 mb atmospheric circulation for the U.S.-Mexico border region, and an accompanying analysis of relationships between synoptic conditions and ground-level ozone. The synoptic methodology employs high-pass filtering to enable comparisons of all seasons, and it uses modified multiple k means clustering to identify six characteristic circulation patterns. The climatology succinctly summarizes important spatial and temporal complexities of border region circulation, including various pressure configurations, the seasonality of those patterns, and associated weather conditions across the region. These results are linked with ozone data for four border-region cities, and the subsequent findings highlight systematic seasonal and region-wide variations in ozone pollution corresponding to patterns of controlling climatic factors. Three high-ozone scenarios are identified, each of which selectively affects a different area or time of year.
Comrie, A.C., 1997: Comparing Neural Networks and Regression Models for Ozone Forecasting. Journal of the Air and Waste Management Association 47, 653-663. (Full paper available in pdf format at AWMA website -- 795K file)
Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season.” Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for inp ut into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been w idely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear, especially for ozone -- properties that may be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.
Adams, D.K. and Comrie, A.C., 1997: The North American Monsoon. Bulletin of the American Meteorological Society, 78(10), 2197-2213. (Full text version available in pdf format from AMS journal website -- 736K file)
The North American monsoon is an important feature of the atmospheric circulation over the continent, with a research literature that dates back almost one hundred years. We review the wide range of past and current research dealing with the meteorological and climatological aspects of the North American monsoon, highlighting historical development and major research themes. The domain of the North American monsoon is large, extending over much of the western United States from its region of greatest influence in northwestern Mexico. Regarding the debate over moisture source regions and water vapor advection into southwestern North America, there is general agreement that the bulk of monsoon moisture is advected at low-levels from the eastern tropical Pacific Ocean and the Gulf of California, while the Gulf of Mexico may contribute some upper-level moisture (although mixing occurs over the Sierra Madre Occidental). Surges of low-level moisture from the Gulf of California are a significant part of intra-seasonal monsoon variability, and they are associated with the configuration of upper-level mid-latitude troughs and tropical easterly waves at the synoptic scale, as well as the presence of low-level jets, a thermal low, and associated dynamics (including the important effects of local topography) at the mesoscale. Seasonally, the gulf surges and the latitudinal position of the mid-tropospheric subtropical ridge over southwestern North America appear to be responsible for much spatial and temporal variability in precipitation. Interannual variability of the North American monsoon system is high, but it is not strongly linked to El Niño or other common sources of interannual circulation variability. Recent mesoscale field measurements gathered during the South-West Area Monsoon Project (SWAMP) have highlighted the complex nature of the monsoon-related severe storm environment and associated difficulties in modeling and forecasting.
Comrie, A.C., 1998: Mapping the climatology of ozone potential for the U.S.-Mexico border region. Journal of the Arizona-Nevada Academy of Science 31(1), 1-12.
Concerns have arisen regarding the potential for ozone formation in the rapidly growing small and medium cities of the United States-Mexico border region. Most of these locations have limited or nonexistent ozone monitoring records, and yet for air quality planning purposes it would be very useful to know the susceptibility of such locations to urban ozone pollution. This paper presents estimates of susceptibility using two statistical measures, percentile rank and z-scores. Ozone potential is defined as the weather-related potential for ozone pollution, assuming a typically polluted urban atmosphere in the region. Ozone potential depends on the range of weather patterns that move over the area in question, and this study examines ozone potential using an existing synoptic climatology of six characteristic circulation patterns based on gridded 850 mb pressure-height data from 1963 to 1994. The synoptic catalog is augmented with matching 850 mb temperature data over the region. Ozone data for long periods of record (extending back to the mid-1970’s) are available for nine monitoring sites across the border region. Percentile rank and z-scores are used as relative measures of ozone concentration to determine ozone potential for each synoptic pattern, thus linking susceptibility to ozone pollution with the controlling atmospheric conditions. Maps of the results show that the border region is differentially susceptible to high-ozone weather conditions, leading to spatially and temporally distinct ozone patterns over the region. The spatial differences in susceptibility to urban ozone pollution are large, and are roughly equal to seasonal differences. Thus, the relative measures of ozone concentration applied in this study allow climate-related potentials for ozone pollution to be inferred for growing urban areas in the U.S.-Mexico border region that currently have sparse air quality data.
Comrie, A.C. and Glenn, E.C. 1998: Principal components-based regionalization of precipitation regimes across the Southwest United States and Northern Mexico, with an application to monsoon precipitation variability. Climate Research 10, 201-215. (Full paper available in pdf format at CR website -- 1325K file)
We determine precipitation regions for the United States-Mexico border region based on seasonality and variability of monthly precipitation at 309 stations for the period 1961 to 1990. Using a correlation matrix of input data to avoid the effect of elevation on precipitation, we apply principal components analysis with oblique rotation to regionalize this large, climatologically complex study area. We examine the applicability of the method, two rules for defining region boundaries, the various defined regions themselves, and the effects of transforming input data and changing obliquity of component rotation. We obtain 9 consistent and largely contiguous regions from each of the analyses, including regions for the North American monsoon, the low deserts, the California Mediterranean region, and for summer precipitation regimes adjoining the Gulf of Mexico. The derived regions and associated boundaries make physical sense in terms of the driving atmospheric processes, and they are robust to transformed input data and changes in rotation procedures. The central border regions are remarkably consistent across analyses, with small changes to peripheral regions. We also identify 4 monsoon sub-regions, and we illustrate the applicability of the regionalization via an analysis of relationships between monsoon precipitation variability and 500 mb pressure heights. Significantly different 500 mb circulation patterns are associated with wet and dry monsoon seasons in each of the sub-regions, and it appears that shifts in 500 mb circulation relative to the geographic position of each sub-region influence seasonal precipitation variability, directly or indirectly. There are important differences between some sub-regions, but in general wet monsoons are associated with northward meridional bulging of the subtropical anticyclone over the continental monsoon areas, while dry monsoons are associated with zonal stretching of the subtropical anticyclone over adjacent oceans with slightly higher pressure-heights. Overall, the study provides a clear regionalization of the precipitation climatology for the southwest United States and northern Mexico, and shows its utility for studies of climate variability.
We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-hour ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.
Tucson, Arizona
is an example of the many cities in the southwestern United States experiencing
rapid growth and urban sprawl over the last several decades. The accompanying
extensive modification of land use and land cover leads to many environmental
impacts, including urban heat islands. The primary aim of this paper is to
expand knowledge of the phenomenon for Tucson, by quantifying the amount of
urban warming, and by mapping temperature patterns over the city and examining
related aspects of the local scale atmospheric circulation. The secondary aim is
to document how an applied empirical research project was integrated into an
introductory undergraduate climatology class via active learning. The paper
begins and concludes with general and practical comments on combining the
research and educational aspects of the project.
An analysis of thirty-year
temporal trends in urban and non-urban minimum temperatures across the region
shows the rate of urban warming to be about three-quarters of the general
regional warming. Tucson’s urban heat island is ~3°C over the last century, with
>2°C of this warming in the last thirty years. The annual average urban
warming trend over the last three decades is 0.071°C yr-1 with the
strongest effect in March and the weakest effect in November. There is evidence
that the latter is caused by strong, near-surface winds under stable conditions.
A case study is presented comprising field measurements and map analysis of
urban temperatures and supporting variables for February 13, 1999. Measurements
include comprehensive mapping using vehicle-mounted thermistors and numerous
local meteorological observations from around the city. Wind speeds during the
field measurements were somewhat stronger than is typical of heat island
studies, up to 12 m s-1. Nonetheless, because of terrain-induced
flows and land surface heterogeneity, complex temperature patterns were
observed. Several transient katabatic flows off surrounding mountain ranges were
detected, leading to localized cold pockets. Locally warm areas in other parts
of the city are associated with terrain sheltering or local land-surface
heating. The central city showed a possible urban heating pattern with
temperatures ~2°C higher than upwind rural air.
This paper
presents a methodology for the development of a high resolution (30 m),
standardized biogenic volatile organic compound (BVOC) emissions inventory and a
subsequent application of the methodology to Tucson, Arizona. The region's
heterogeneous vegetation cover cannot be modeled accurately with low resolution
(e.g., 1 km) land cover and vegetation information. Instead, local
vegetation data are used in conjunction with multi-spectral satellite data to
generate a detailed vegetation-based land cover database of the region. A high
resolution emissions inventory is assembled by associating the vegetation data
with appropriate emissions factors. The inventory reveals a substantial
variation in BVOC emissions across the region resulting from the region's
diversity of both native and exotic vegetation. The importance of BVOC emissions
from forest lands, desert lands, and the urban forest changes according to
regional, metropolitan, and urban scales. Within the entire Tucson region, the
average isoprene, monoterpenes, and OVOC fluxes are 454, 248, and 91 µg m
-2 hr-1, respectively, with forest and desert lands emitting
nearly all of the BVOCs. Within the metropolitan area, which does not include
the forest lands, the average fluxes are 323, 181, and 70 µg m -2
hr-1, respectively. Within the urban area, the average fluxes are
801, 100, and 100 µg m-2 hr-1, respectively, with exotic
trees such as eucalyptus, pine, and palm emitting most of the urban BVOCs. The
methods presented in this paper can be modified to create detailed, standardized
BVOC emissions inventories for other regions, especially those with spatially
complex vegetation patterns.
Coccidioidomycosis (valley fever) is a disease endemic to arid regions
in the western hemisphere, and is caused by the soil-dwelling fungus
Coccidioides immitis (C. immitis). In this paper, we provide an overview of the
current state of knowledge regarding valley fever and C. immitis as related to
climatic conditions and habitat requirements. Previous research shows there is a
relationship between temperature and precipitation, and outbreaks of
coccidioidomycosis. Incidence of the disease varies seasonally as well as
annually due to changing climatic conditions. However, the specific
environmental conditions that may produce an outbreak of coccidioidomycosis are
not well understood in space and time. Previous studies have attempted to
characterize C. immitis’ habitat. Temperature, moisture, salinity, and pH of the
soil have all been considered separately in the geographic distribution of the
fungus. Medical and proactive intervention are served best, however, by an
integrative strategy that folds climate and surface variables into
spatially-explicit models. We conclude with recommendations for future research
directions.
Results of
analyses using timeseries of mean temperature, precipitation amount, and stable
isotopes from precipitation from July-August in Tucson, Arizona, have revealed
atmospheric circulation patterns related to the North American monsoon in the
U.S. Southwest. The isotope timeseries and Tucson air temperatures and
precipitation amount are significantly correlated. The temperature and isotope
timeseries also correlate significantly with regional and extra-regional
specific humidity, and with eastern Pacific SSTs near the Mexican coast,
evidence for a dominantly Pacific/Gulf of California summer moisture source for
the period 1983-1999. Separation of extra-regional wind vector datasets into
groups of years matching relative isotopic depletion or enrichment of the Tucson
July-August precipitation seasonal means for the stable isotope timeseries
(usually the extreme years in the Tucson seasonal temperature means) suggest
circulation patterns entraining more tropical moisture in cooler/isotopically
depleted years, and entraining less tropical moisture in hotter/isotopically
enriched years.
This article
addresses the need to better understand the complex interactions between
climate, human activities, vegetation responses, and surface ozone so that more
informed air-quality policy recommendations can be made. The impacts of
intraseasonal climate variations on ozone levels in Tucson, Arizona from April
through September of 1995 to 1998 are determined by relating variations in ozone
levels to variations in atmospheric conditions and emissions of ozone’s
precursor chemicals, volatile organic compounds (VOCs) and nitrogen oxides
(NOx), and by determining month-specific atmospheric conditions that are
conducive to elevated ozone levels. Results show that the transport of ozone and
its precursor chemicals within the Tucson area causes the highest ozone levels
to be measured at a downwind monitor. The highest ozone levels occur in August,
due in part to the presence of the North American monsoon. Atmospheric
conditions conducive to elevated ozone concentrations differ substantially
between the arid foresummer (May and June) and the core monsoon months ( July
and August). Transport of pollution from Phoenix may have a substantial impact
on elevated ozone concentrations during April, May, and June, while El
Paso/Ciudad Juarez –derived pollution may contribute significantly to elevated
ozone concentrations in August and September. Two broad policy implications
derive from this work. Regional pollutant transport, both within the U.S. and
between the U.S. and Mexico, is a potential issue that needs to be examined more
intensively in future studies. In addition, spatiotemporal variations in
sensitivities of ozone production require the adoption of both NOx and VOC
control measures to reduce ozone levels in the Tucson area.
Developments in
synoptic climatology in the 1990s included advances in traditional synoptic
climatology, empirical downscaling, and dynamical downscaling (i.e. regional
climate modelling). The research emphasis in traditional, empirical–statistical
approaches to synoptic climatology shifted from methodological development to
applications of widely accepted classification techniques, including manual,
correlation-based, eigenvector-based, compositing and indexing schemes. In
contrast, most efforts in empirical downscaling, which became a well-established
field of synoptic climatology during the 1990s, were directed to model
development; applications were of secondary concern. Similarly, regional climate
models (RCMs) burst onto the scene during the decade and focused on model
development, although important progress was made in linking or coupling RCMs to
regional or local surface climate systems. This paper discusses prospects for
the future of traditional synoptic climatology, empirical downscaling and
regional climate modelling. It concludes by looking at the present role of
geographic information system (GIS) concepts in synoptic climatology and the
potential future role of GIS to the field.
An inventory of
volatile organic compound (VOC) and nitrogen oxides (NOx) emissions is an
important tool for the management of ground-level ozone pollution. This paper
has two broad aims: it illustrates the potential of a geographic information
system (GIS) for enhancing an existing spatially-aggregated, anthropogenic
emissions inventory (EI) for Tucson, AZ, and it discusses the ozone-specific
management implications of the resulting spatially-disaggregated EI. The main
GIS-related methods include calculating emissions for specific features,
spatially disaggregating region-wide emissions totals for area sources, and
adding emissions from various point sources. In addition, temporal allocation
factors enable the addition of a multi-temporal component to the inventory. The
resulting inventory reveals that on-road motor vehicles account for
approximately 50% of VOC and NOx emissions annually. On-road motor vehicles and
residential wood combustion are the largest VOC sources in the summer and winter
months, respectively. On-road motor vehicles are always the largest NOx sources.
The most noticeable weekday vs. weekend VOC emissions differences are triggered
by increased residential wood combustion and increased lawn and garden equipment
use on weekends. Concerning the EI’s uncertainties and errors, on-road mobile,
construction equipment, and lawn and garden equipment are identified as sources
in the most need of further investigation. Overall, the EIs spatial component
increases its utility as a management tool, which might involve
visualization-driven analyses and air quality modeling.
We present a
unique new set of high spatial resolution precipitation data from a storage
gauge network, for the sparsely observed northern Sonoran desert in southwest
Arizona. We examine the nature and causes of the highly complex seasonal and
spatial variability in the data, using fine-scale maps developed via spatial
modeling and interpolation. These high-resolution maps had explained variances
approaching 1.00, and precipitation errors of about 1 percent in winter and
about 10 percent in summer. Seasonal precipitation ranges from near zero to
almost 15 inches across the area, and shows high interannual variability.
Localized convectional processes lead to summer anomalies that are more
spatially complex than in winter when broad-scale synoptic and frontal processes
cause precipitation. In general, summer and winter precipitation variability are
tied to meridional-zonal shifts and east-west movement of the respective
anticyclone or trough pattern over the region. Statistical links between major
weather stations in the region and precipitation across the area are spatially
inconsistent, especially in the west.
A limited
number of sample points greatly reduces the availability of appropriate spatial
interpolation methods.This is a common problem when one attempts to accurately
predict air pollution levels across a metropolitan area. Using ground-level
ozone concentrations in the Tucson,Arizona,region as an example, this paper
discusses the above problem and its solution, which involves the use of linear
regression. A large range of temporal variability is used to compensate for
sparse spatial observations (i.e. few ozone monitors). Gridded estimates of
emissions of ozone precursor chemicals, which are developed,stored,and
manipulated within a geographic information system,are the core predictor
variables in multiple linear regression models. Cross-validation of the pooled
models reveals an overall R2 of 0.90 and approximately 7% error.
Composite ozone maps predict that the highest ozone concentrations occur in a
monitor-less area on the eastern edge of Tucson. The maps also reveal the need
for ozone monitors in industrialized areas and in rural, forested areas.
This paper summarizes the current state of knowledge of the climate of the southwest USA (the 'Southwest'). Low annual precipitation, clear skies, and year-round warm climate over much of the Southwest are due in large part to a quasi-permanent subtropical high-pressure ridge over the region. However, the Southwest is located between the mid-latitude and subtropical atmospheric circulation regimes, and this positioning relative to shifts in these regimes is the fundamental reason for the region's climatic variability. Furthermore, the Southwest's complex topography and its geographical proximity to the Pacific Ocean, the Gulf of California, and the Gulf of Mexico also contribute to this region's high climatic variability. El Niño, which is an increase in sea surface temperature of the eastern equatorial Pacific Ocean with an associated shift of the active center of atmospheric convection from the western to the central equatorial Pacific, has a well developed teleconnection with the Southwest, usually resulting in wet winters. La Niña, the opposite oceanic case of El Niño usually results in dry winters for the Southwest. Another important oceanic influence on winter climate of the Southwest is a feature called the Pacific Decadal Oscillation (PDO), which has been defined as temporal variation in sea surface temperatures for most of the Northern Pacific Ocean. The combined effects of ENSO and PDO can amplify each other, resulting in increased annual variability in precipitation over the Southwest. The major feature that sets climate of the Southwest apart from the rest of the United States is the North American monsoon, which in the US is most noticeable in Arizona and New Mexico. Up to 50% of the annual rainfall of Arizona and New Mexico occurs as monsoonal storms from July through September. Instrumental measurement of temperature and precipitation in the Southwest dates back to the middle to late 1800s. From that record, average annual rainfall of Arizona is 322 mm [12.7 in.] while that of New Mexico is 340 mm [13.4 in.], and mean annual temperature of New Mexico is cooler (12 °C [53 °F]) than Arizona (17 °C [62 °F]). As instrumental meteorological records extend back only about 100–120 years throughout the Southwest, they are of limited utility for studying climate phenomena of long time frames. Hence, there is a need to extend the measured meteorological record further back in time using so-called "natural archive" paleoclimate records. Tree-ring data, which provide annual resolution, range throughout the Southwest, extend back in time for up to 1000 years or more in various forests of the Southwest, and integrate well the influences of both temperature and precipitation, are useful for this assessment of climate of the Southwest. Tree growth of mid elevation forests typically responds to moisture availability during the growing season, and a commonly used climate variable in paleo-precipitation studies is the Palmer Drought Severity Index (PDSI), which is a single variable derived from variation in precipitation and temperature. June–August PDSI strongly represents precipitation and, to a lesser extent, temperature of the year prior to the growing season (prior September through current August). The maximum intra-ring density of higher elevation trees can yield a useful record of summer temperature variation. The combined paleo-modern climate record has at least three occurrences of multi-decadal variation (50–80 years) of alternating dry (below average PDSI) to wet (above average PDSI). The amplitude of this variation has increased since the 1700s. The most obvious feature of the temperature record is its current increase to an extent unprecedented in the last four hundred years. Because this warming trend is outside the variation of the natural archives, it is possible that anthropogenic impacts, such as increased atmospheric concentrations of greenhouse trace gases, are playing a role in climate of the Southwest. Accordingly, this pattern merits further research in search of its cause or combination of causes.
The
intraseasonal evolution of the North American monsoon in southeast Arizona
during the 1980-1993 period is investigated using a neural network-based
nonlinear classification technique known as the self-organizing map (SOM). The
goal of the SOM algorithm is to discover meaningful low-dimensional structures
hidden in the high-dimensional observations. Various daily lagged atmospheric
fields (850-hPa meridional winds, 700-hPa specific humidity, 500-hPa
geopotential heights, and 850-500-hPa thickness) for the summer season
(Jun-Jul-Aug-Sep) of the 1980-1993 period are used in the nonlinear
classification of monsoon modes. Special emphasis is given to the wettest
monsoon modes. The neural network classification successfully captures the
multidimensional interaction of the atmospheric variables during the monsoon
evolution, and shows monsoon “bursts” and “breaks” in a given year. Spectral
analysis of daily summer rainfall in the study area reveals a significant peak
in the 12-18-day band; a secondary and significant peak is also found near 40
days. Thus, monsoon bursts and breaks seem to be modulated by low frequency
variability.
The SOM nonlinear classification shows that the mature phase of
the monsoon is associated with two distinct intraseasonal (>10 days) wet
monsoon modes. The signature of the wettest monsoon mode is a zonal three-cell
anomalous mid-tropospheric height pattern over the North Pacific-North American
sector, suggesting a large-scale dynamical mechanism, possibly linked to sea
surface temperature (SST) anomalies in the North Pacific. This zonal mode, which
is most frequent in July and August, is characterized by an enhanced and
northeastward-displaced monsoon ridge, large amounts of mid-tropospheric
moisture over the study area, and an out of phase relationship between
precipitation in the Southwest United States and precipitation in the Great
Plains. The zonal mode has been recognized in longer data sets and it is the
most typical mode that characterizes the mature phase of the monsoon in the
Southwest United States. In contrast, the second wettest intraseasonal monsoon
mode does not show a monsoon ridge, but a meridional three-cell anomalous
mid-tropospheric height pattern along the West coast of North America, weak
height anomalies over the rest of North America, and large amounts of moisture
over the study area. Importantly, this meridional mode, which is most frequent
in August and September, does not show out of phase links to Great Plains
precipitation. The meridional wet mode also shows an anomalous low-level
cyclonic circulation off the west coast of central-south Mexico suggesting that
convective activity off the southern Mexican coast – possibly associated with
the intertropical convergence zone – may cross over the Isthmus of Tehuantepec
toward the Gulf of Mexico and the southern United States. This would explain the
weak link between precipitation in the Southwest and precipitation in the Great
Plains during August and September of the 1980-1993 period.
At more regional
scales, the zonal wet mode is also characterized by a latitudinal gradient of
SST anomalies between Baja California and southern Mexico and reversed low-level
flow over the Gulf of California. Looking at extreme wet monsoons outside of the
study period (e.g., 1955, 1959, 1999) indicate that the positive SST anomaly
pattern along the Pacific coast of Baja California, which characterized wet
events during 1980-1993, can be completely reversed during other extreme wet
events. These contrasting results suggest that interaction between local and
remote forcing mechanisms over the study area are complex during extreme events
and need further investigation.
The development
of a statistical modeling technique suitable for producing mean and interannual
gridded climate datasets for a topographically varying domain is
undertaken. Stepwise regression models at 1x1 km resolution are generated
to estimate mean winter temperature and precipitation for the Southwest United
States for the years 1961 to 1990. Topographic predictor variables are
used to explain spatial variance in the datasets. Kriging and inverse
distance weighting interpolation algorithms are utilized to account for model
residuals. The final regression models show a high degree of explained
variance for temperature (R2 = 0.98, MBE = -0.15° C, RMSE = 0.74° C) and a
moderate degree of explained variance for precipitation (R2 = 0.63, MBE = -1.4
mm, RMSE = 27.0 mm). Several smaller-scale precipitation regression models
are developed for comparison to the domain-wide model, but do not show marked
accuracy improvements. Observed values of winter temperature and
precipitation from the years 1961 to 1999 are compared to the 30-year modeled
means, and the differences are interpolated using kriging (temperature) and
inverse distance weighting (precipitation). The result is a 39-year time
series of maps and datasets of winter temperature and precipitation at 1x1 km
resolution for the Southwest United States.
A 1000-year
reconstruction of cool-season (November-April) precipitation was developed for
each climate division in Arizona and New Mexico from a network of 19 tree-ring
chronologies in the Southwestern United States. Linear regression (LR) and
artificial neural networks (NN) models were used to compare the response of tree
growth to cool-season precipitation. The stepwise LR model was cross-validated
with a leave-one-out procedure while the NN was validated with a bootstrap
technique using 1931-1988 records. The final models were also independently
validated using the 1896-1930 precipitation data. In most of the climate
divisions both techniques can successfuly simulate dry and normal years, and the
NN seems to better capture large precipitation events and more variability than
the LR. In the 1000-year reconstructions the NN also produces more distinctive
wet events and more variability, while the LR produces more distinctive dry
events. The 1000-year reconstructed precipitation from the two models shows
several sustained dry and wet periods comparable to the 1950s drought (e.g.,
16th century megadrought) and the post-1976 wet periods (e.g., 1330s, 1610s).
The impact of extreme periods on the environment may be stronger during sudden
reversals from dry to wet, which were not uncommon throughout the millennium,
such as the 1610s wet interval that followed the 16th century megadrought. The
instrumental records suggest that strong dry to wet precipitation reversals in
the past 1000 years might be linked to strong shifts from cold to warm El
Nino/Southern Oscillation (ENSO) events and from negative to positive Pacific
Decadal Oscillation (PDO).
This paper
highlights the relationship between precipitation variability at the
sub-regional level in the Southwest United States and the SOI and PDO climate
teleconnection indices during the period 1950 – 2000. Statistical
correlations at the a = 0.05 and a = 0.01 levels are calculated for fall,
winter, and spring precipitation in the Southwest, and contemporaneous and
antecedent seasonal SOI and PDO index values. A strong SOI-winter
precipitation signal is seen to progress across Arizona and New Mexico from
southwest to northeast over a three-season lagged period. The PDO also
exhibits a strong relationship with winter and spring precipitation in New
Mexico; however, the PDO is not well correlated with precipitation in
Arizona. The results underscore the non-uniform spatio-temporal
relationships of the SOI and PDO indices as they relate to the precipitation
regime of the Southwest, and provide a framework for future diagnostic analyses
of these relationships.
(Summary from introduction – no abstract) Coccidioidomycosis is a
systemic infection caused by inhalation of airborne spores from Coccidioides
immitis, a fungus found in soil in the southwestern