Extreme floods and their relationship with tropical cyclones in Puerto Rico

An extreme value analysis (EVA) point process approach has been implemented to examine the flood characteristics of Puerto Rico when tropical cyclones (TCs) are present in the discharge series and when they are removed from it. Mean daily discharge values that exceeded the 99th percentile thresholds were used in both the TC and non-TC data series. In nine of the 12 stations the maximum discharge was associated with a TC, with hurricanes Hortense (1996), Georges (1998) and Eloise (1975) responsible for most of the maximum peaks at each site. Percentage changes in the generalized extreme value parameters, which include location (central tendency), scale (variance) and shape (skewness), between the TC and non-TC data exhibited a decrease in the majority of stations. Stations in the eastern interior and central region of the island showed the largest decrease in all parameters, in flood occurrences and in return periods when TCs were removed from the series.     

Cognitive and affective responses of Florida tourists after exposure to hurricane warning messages

Tourists are particularly vulnerable to natural disasters such as hurricanes since they might be less informed and prepared than residents of disaster-prone areas. Thus, understanding how the traits of a tropical cyclone as well as specific characteristics of tourists influence affective and cognitive responses to a hurricane warning message is a critical component in disaster planning. Using scenarios that presented tropical cyclones with different relevant characteristics (such as category at landfall), tourists’ knowledge, experience with hurricanes, trip traits, and the location of the survey (coastal or inland), this study contributes to the literature on sociological issues related to natural disasters. The findings suggest that risk perceptions and fear are influenced differently by the traits of the hurricanes and tourists’ knowledge and experience. Risk is strongly influenced by the projected category of the hurricane at landfall, while fear is not as sensitive to this extremely relevant trait of cyclones. The results also suggest that the influence of risk and fear on evacuation likelihood is strong and positive. This study shows the value of studying cognitive and affective responses to uncertain events.     

Associations between the size of hurricane rain fields at landfall and their surrounding environments

This study examines relationships between the extent of hurricane rain fields, storm size, and the environment surrounding the storm. A Geographic Information System is employed to measure the extent of the rain fields in each quadrant of 31 hurricanes at landfall-time. After correlating the extents with measures of storm size, multiple linear regression models are developed to determine which atmospheric forcing(s) at 0, 12, and 24 h prior to landfall are most highly related to rain field size in each quadrant. Results show that the radius of the outermost closed isobar encompasses the rain fields in 90% of the observations. Strong vertical wind shear from the southwest correlates with a larger (smaller) rain field extent toward the northeast (southwest), while higher relative humidity values correlate with a larger extent toward the northwest, southwest, and southeast. Storm intensity and location also exhibit statistically significant correlations with rain field size.     

Statistical aspects of flow in a random network of channels

This paper presents a detailed statistical analysis of Hagen-Poiseuille flow in plane random isotropic networks of interconnected channels. The emphasis is on statistico-geometrical features of networks that affect macroscopic permeability. It is shown that permeability of a network depends on its average co-ordination number, the first two moments of the channel length distribution and other explicitly identifiable geometrical features. Distributions of flow rates in channels and average flow rates are established by minimization of the rate of energy dissipation. Theoretical developments are interpreted in the context of classical statistical mechanics. Analytical results are illustrated and verified using numerical analysis of flow in a simulated random network.     

Spatial distribution of tropical cyclone rainfall and its contribution to the climatology of Puerto Rico

This study explores two different tropical cyclone rainfall (TCR) problems: first, the identification of areas where TCR is highly concentrated and, second, the contribution of tropical cyclones (TCs) to the climatology of Puerto Rico for the period 1970–2010. A total of 86 storms within a 500-km radius of Puerto Rico were analyzed. Daily and monthly rainfall data from 32 weather stations were used to generate interpolated surfaces. Two geostatistical interpolation techniques were implemented: ordinary kriging and ordinary cokriging. Results show that rainfall from most TCs tends to be clustered in the eastern, southeastern, and central regions of the island, with a decrease in values toward the west. TCs closer to Puerto Rico (≤230 km) and embedded in high moisture environments (≥44.5 mm) exhibited the highest rainfall values, with most concentrated in the high elevation areas of the southeastern region of the island. Months with the largest TC contributions to rainfall (20–30%) were August and September, while the lowest contributions were found in June and November. For August, stations in the southern and eastern portions of the island had TCR contributions of >20%, with some stations in the southern coastal plains exhibiting 30%.     

Extreme weather and economic well-being in rural Mozambique

Societies dependent on rain-fed agriculture are highly vulnerable to weather extremes; thus, linkages between rainfall variability and economic well-being merit close attention. The hypothesis of this paper is that rainfall patterns impact changes in income within our study region of central and northern Mozambique. Utilizing satellite-based estimates of rainfall analyzed within a GIS, we establish a 12-year rainfall climatology and calculate monthly rainfall anomalies for 419 villages during three growing seasons. We also approximate storm-total rainfall from tropical cyclones entering the Mozambique Channel. Hierarchical cluster analysis groups the villages according to the monthly rainfall anomalies and rainfall received from Cyclones Delfina and Japhet. Then, using data from the National Agricultural Survey of Mozambique conducted in 2002 and 2005, we relate rainfall and change in income through the calculation of Pearson’s correlation coefficients and independent-samples t tests using village-groups produced by the cluster analysis. We find that no season closely approximates the 12-year climatology and that rainfall varied among the three seasons. Although most villages experience income declines, those affected by Delfina exhibit the worst economic performance, indicating that heavy rainfall from some tropical cyclones can have long-lasting negative effects on income. Additionally, receiving above-normal rainfall may hinder economic well-being more than below-normal rainfall. Our study identifies patterns in sub-national rainfall variability and economic well-being that enable a more detailed understanding of weather-related effects on socio-economic outcomes.     

Risk perception and evacuation decisions of Florida tourists under hurricane threats: a stated preference analysis

Though most hurricane evacuation studies have focused on residents, tourists are also a vulnerable population. To assess their perceptions of risk and evacuation likelihood under different hurricane conditions, we surveyed 448 tourists visiting central Florida. Respondents viewed four maps emulating track forecast cones produced by the National Hurricane Center and text information featuring variations of storm intensity, coast of landfall, centerline position relative to the survey site, time until landfall, and event duration. We performed chi-square tests to determine which hurricane conditions, and aspects of tourists such as their demographics and previous hurricane experience, most likely influenced their ratings of risk and evacuation likelihood for respondents located on Pinellas County beaches or inland near Orlando, FL. Highly rated scenarios featured a Category 4 hurricane making landfall along the Gulf Coast with the centerline passing over the sampling site. Overall, tourists that indicated the highest risk and evacuation ratings were not previously affected by a hurricane, had a trip duration of less than 6 days, and had checked for the possibility of a hurricane strike before departure. However, results for other tourist attributes differed between tourists in coastal and inland locations. We found that although somewhat knowledgeable about hurricanes, tourists misinterpreted the track forecast cone and hurricane conditions, which led to a lower perception of risk and subsequent likelihood to evacuate. Tourists, particularly those from outside of Florida, need to be better educated about the risks they face from hurricanes that make landfall.     

Assessing links between upper atmospheric vorticity patterns and directional changes in hurricane tracks

Links between hurricane track changes and upper atmospheric potential vorticity (PV) anomaly patterns were identified qualitatively and analytically between 1990 and 2005 in the Western Atlantic. Strong track changes of hurricanes, particularly the constellations that triggered northward acceleration of the storm systems, were associated with upper-air PV patterns characterized by strongly positive anomalies to the northeast in combination with weak PV to the north of the system center. Constellations that triggered eventual eastward acceleration were associated with strongly positive PV anomalies to the northwest in combination with weak PV to the northeast of the system center. These results may assist hurricane forecasters and modelers in identifying possible signatures of future tropical cyclone tracks.     

Surface radar-derived convective rainfall associations with Midwest US land surface conditions in summer seasons 1999 and 2000

Previous research has suggested that spatial heterogeneities in soil moisture and/or vegetation cover promote the development of convective clouds. We examine the intensity of convective precipitation for the Midwest US Corn Belt in the summers of 1999 and 2000, which had contrasting synoptic circulation, atmospheric humidity, and soil moisture conditions. For days when synoptic scale atmospheric forcing is weak, we calculate a convective severity index (CSI) based on radar reflectivity composite values. Our results suggest that boundaries between soil types, and cropland and forest vegetation types in the western portion of the Corn Belt, enhance the development of convective precipitation. In the eastern part of the Corn Belt, less convection occurs, but we find a positive correlation between the intensity of convection and soil moisture conditions. Our results also demonstrate that the CSI is a simple yet effective technique for identifying where deep convection occurs relative to lighter precipitation.