Acclimation's influence on physically-fit individuals: marathon race results as a function of meteorological variables and indices

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Description
While there are many elements to consider when determining one's risk of heat or cold stress, acclimation could prove to be an important factor to consider. Individuals who are participating in more strenuous activities, while being at a lower

While there are many elements to consider when determining one's risk of heat or cold stress, acclimation could prove to be an important factor to consider. Individuals who are participating in more strenuous activities, while being at a lower risk, will still feel the impacts of acclimation to an extreme climate. To evaluate acclimation in strenuous conditions, I collected finishing times from six different marathon races: the New York City Marathon (New York City, New York), Equinox Marathon (Fairbanks, Alaska), California International Marathon (Sacramento, California), LIVESTRONG Austin Marathon (Austin, Texas), Cincinnati Flying Pig Marathon (Cincinnati, Ohio), and the Ocala Marathon (Ocala, Florida). Additionally, I collected meteorological variables for each race day and the five days leading up to the race (baseline). I tested these values against the finishing times for the local runners, those from the race state, and visitors, those from other locations. Effects of local acclimation could be evaluated by comparing finishing times of local runners to the change between the race day and baseline weather conditions. Locals experienced a significant impact on finishing times for large changes between race day and the baseline conditions for humidity variables, dew point temperature, vapor pressure, relative humidity, and temperature based variables such as the heat index, temperature and the saturation vapor pressure. Wind speed and pressure values also marked a change in performance, however; pressure was determined to be a larger psychological factor than acclimation factor. The locals also demonstrated an acclimation effect as performance improved when conditions were similar on race day to baseline conditions for the three larger races. Humidity variables had the largest impact on runners when those values increased from training and acclimation values; however increased wind speed appeared to offset increased humidity values. These findings support previous acclimation research stating warm wet conditions are more difficult to acclimate to than warm dry conditions. This research while primarily pertaining to those participating physically demanding activities may also be applied to other large scale events such as festivals, fairs, or concerts.
Date Created
2011
Agent

Reconstruction of a tornado disaster employing remote sensing techniques: a case study of the 1999 Moore, Oklahoma tornado

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Description

Remote sensing has demonstrated to be an instrumental tool in monitoring land changes as a result of anthropogenic change or natural disasters. Most disaster studies have focused on large-scale events with few analyzing small-scale disasters such as tornadoes. These studies

Remote sensing has demonstrated to be an instrumental tool in monitoring land changes as a result of anthropogenic change or natural disasters. Most disaster studies have focused on large-scale events with few analyzing small-scale disasters such as tornadoes. These studies have only provided a damage assessment perspective with the continued need to assess reconstruction. This study attempts to fill that void by examining recovery from the 1999 Moore, Oklahoma Tornado utilizing Landsat TM and ETM+ imagery. Recovery was assessed for 2000, 2001 and 2002 using spectral enhancements (vegetative and urban indices and a combination of the two), a recovery index and different statistical thresholds. Classification accuracy assessments were performed to determine the precision of recovery and select the best results. This analysis proved that medium resolution imagery could be used in conjunction with geospatial techniques to capture recovery. The new indices, Shortwave Infrared Index (SWIRI) and Coupled Vegetation and Urban Index (CVUI), developed for disaster management, were the most effective at discerning reconstruction using the 1.5 standard deviation threshold. Recovery rates for F-scale damages revealed that the most incredibly damaged areas associated with an F5 rating were the slowest to recover, while the lesser damaged areas associated with F1-F3 ratings were the quickest to rebuild. These findings were consistent for 2000, 2001 and 2002 also exposing that complete recovery was never attained in any of the F-scale damage zones by 2002. This study illustrates the significance the biophysical impact has on recovery as well as the effectiveness of using medium resolution imagery such as Landsat in future research.

Date Created
2011
Agent

Snow level elevation over the western United States: an analysis of variability and trend

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Description
Many previous investigators highlight the importance of snowfall to the water supply of the western United States (US). Consequently, the variability of snowpack, snowmelt, and snowfall has been studied extensively. Snow level (the elevation that rainfall transitions to snowfall) directly

Many previous investigators highlight the importance of snowfall to the water supply of the western United States (US). Consequently, the variability of snowpack, snowmelt, and snowfall has been studied extensively. Snow level (the elevation that rainfall transitions to snowfall) directly influences the spatial extent of snowfall and has received little attention in the climate literature. In this study, the relationships between snow level and El Niño-Southern Oscillation (ENSO) as well as Pacific Decadal Oscillation (PDO) are established. The contributions of ENSO/PDO to observed multi-decadal trends are analyzed for the last ~80 years. Snowfall elevations are quantified using three methods: (1) empirically, based on precipitation type from weather stations at a range of elevations; (2) theoretically, from wet-bulb zero heights; (3) theoretically, from measures of thickness and temperature. Statistically significant (p < 0.05) results consistent between the three datasets suggest snow levels are highest during El Niño events. This signal is particularly apparent over the coastal regions and the increased snow levels may be a result of frequent maritime flow into the western US during El Niño events. The El Niño signal weakens with distance from the Pacific Ocean and the Southern Rockies display decreased snow level elevations, likely due to maritime air masses within the mid-latitude cyclones following enhanced meridional flow transitioning to continental air masses. The modulation of these results by PDO suggest that this El Niño signal is amplified (dampened) during the cold (warm) phase of the PDO particularly over Southern California. Additionally, over the coastal states, the La Niña signal during the cold PDO is similar to the general El Niño signal. This PDO signal is likely due to more zonal (meridional) flow throughout winter during the cold (warm) PDO from the weakening (strengthening) of the Aleutian low in the North Pacific. Significant trend results indicate widespread increases in snow level across the western US. These trends span changes in PDO phase and trends with ENSO/PDO variability removed are significantly positive. These results suggest that the wide spread increases in snow level are not well explained by these sea surface temperature oscillations.
Date Created
2011
Agent