Andrew C. Comrie

The North American Monsoon

The North American monsoon is an important feature of the atmospheric circulation over the continent, with a research literature that dates back almost 100 years. The authors 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 intrase...

Comparing Neural Networks and Regression Models for Ozone Forecasting

Abstract 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 input 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 widely 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 might 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 o...

Climate and dengue transmission: evidence and implications.

Background: Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. Objective: We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. Methods: We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Results and Discussion: Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host–species interactions. Conclusion: Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence. Citation: Morin CW, Comrie AC, Ernst KC. 2013. Climate and dengue transmission: evidence and implications. Environ Health Perspect 121:1264–1272; http://dx.doi.org/10.1289/ehp.1306556

An Epidemic of Coccidioidomycosis in Arizona Associated with Climatic Changes, 1998–2001

BACKGROUND Reports of coccidioidomycosis cases in Arizona have increased substantially. We investigated factors associated with the increase. METHODS We analyzed the National Electronic Telecommunications System for Surveillance (NETSS) data from 1998 to 2001 and used Geographic Information Systems (GIS) to map high-incidence areas in Maricopa County. Poisson regression analysis was performed to assess the effect of climatic and environmental factors on the number of monthly cases; a model was developed and tested to predict outbreaks. RESULTS The overall incidence in 2001 was 43 cases/100,000 population, a significant (P<.01, test for trend) increase from 1998 (33 cases/100,000 population); the highest age-specific rate was in persons > or =65 years old (79 cases/100,000 population in 2001). Analysis of NETSS data by season indicated high-incidence periods during the winter (November-February). GIS analysis showed that the highest-incidence areas were in the periphery of Phoenix. Multivariable Poisson regression modeling revealed that a combination of certain climatic and environmental factors were highly correlated with seasonal outbreaks (R2=0.75). CONCLUSIONS Coccidioidomycosis in Arizona has increased. Its incidence is driven by seasonal outbreaks associated with environmental and climatic changes. Our study may allow public-health officials to predict seasonal outbreaks in Arizona and to alert the public and physicians early, so that appropriate preventive measures can be implemented.

Climate Factors Influencing Coccidioidomycosis Seasonality and Outbreaks

Although broad links between climatic factors and coccidioidomycosis have been established, the identification of simple and robust relationships linking climatic controls to seasonal timing and outbreaks of the disease has remained elusive. Using an adaptive data-oriented method for estimating date of exposure, in this article I analyze hypotheses linking climate and dust to fungal growth and dispersion, and evaluate their respective roles for Pima County, Arizona. Results confirm a strong bimodal disease seasonality that was suspected but not previously seen in reported data. Dispersion-related conditions are important predictors of coccidioidomycosis incidence during fall, winter, and the arid foresummer. However, precipitation during the normally arid foresummer 1.5–2 years before the season of exposure is the dominant predictor of the disease in all seasons, accounting for half of the overall variance. Cross-validated models combining antecedent and concurrent conditions explain 80% of the variance in coccidioidomycosis incidence.

Intraseasonal Variability Associated with Wet Monsoons in Southeast Arizona

The intraseasonal evolution of the North American monsoon in southeast Arizona during the 1980‐93 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 (June‐July‐ August‐September) of the 1980‐93 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 midtropospheric height pattern over the North Pacific‐North American sector, suggesting a largescale 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 northeastwarddisplaced monsoon ridge, large amounts of midtropospheric 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 datasets 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 midtropospheric 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 1980‐93 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) it is shown that the positive SST anomaly pattern along the Pacific coast of Baja California, which characterized wet events during 1980‐93, 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 needs further investigation.

Interactions between antecedent climate and wildfire variability across south-eastern Arizona

Long-term antecedent climate conditions are often overlooked as important drivers of wildfire variability. Fuel moisture levels and fine-fuel productivity are controlled by variability in precipitation and temperature at long timescales (months to years) before wildfire events. This study examines relationships between wildfire statistics (total area burned and total number of fires) aggregated for south-eastern Arizona and antecedent climate conditions relative to 29 fire seasons (April-May-June) between 1973 and 2001. High and low elevation fires were examined separately to determine the influence of climate variability on dominant fuel types (low elevation grasslands with fine fuels v. high elevation forests with heavy fuels). Positive correlations between lagged precipitation and total area burned highlight the importance of climate in regulating fine fuel production for both high and low elevation fires. Surprisingly, no significant negative correlations between precipitation and seasonal wildfire statistics were found at any seasonal lag. Drought conditions were not associated with higher area burned or a greater number of fires. Larger low elevation fires were actually associated with wet antecedent conditions until just before the fire season. Larger high elevation fires were associated with wet conditions during seasons up to 3 years before the fire season.

Applications of Monsoon Research: Opportunities to Inform Decision Making and Reduce Regional Vulnerability

Abstract This article presents ongoing efforts to understand interactions between the North American monsoon and society in order to develop applications for monsoon research in a highly complex, multicultural, and binational region. The North American monsoon is an annual precipitation regime that begins in early June in Mexico and progresses northward to the southwestern United States. The region includes stakeholders in large urban complexes, productive agricultural areas, and sparsely populated arid and semiarid ecosystems. The political, cultural, and socioeconomic divisions between the United States and Mexico create a broad range of sensitivities to climate variability as well as capacities to use forecasts and other information to cope with climate. This paper highlights methodologies to link climate science with society and to analyze opportunities for monsoon science to benefit society in four sectors: natural hazards management, agriculture, public health, and water management. A list of stakeh...

Monsoonal moisture sources revealed using temperature, precipitation, and precipitation stable isotope timeseries

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.

Mapping a Wind-Modified Urban Heat Island in Tucson, Arizona (with Comments on Integrating Research and Undergraduate Learning)

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 30-yr temporal trends in urban and nonurban minimum temperatures across the region shows the rate of urban warming to be about three-quarters of the general regional...