Commuter Cyclist’s Sensitivity to Changes in Weather: Insight from Two Cities with Different Climatic Conditions

This study examines the relationship between various weather conditions and commuter bicyclist volume in two cities (Portland, USA and Brisbane, Australia), which fall into different climatic zones. Investigating the variation in day-to-day bicycle ridership can help to understand factors influencing demand and in particular how base climatic conditions may condition bicyclist’s responsiveness to changes in weather and climate. Temporal variations in bicycle usage and key weather parameters (temperature and rainfall) are analyzed. Ridership counts and weather data are then used to develop an aggregate demand model that provides quantitative insight into the effects of weather on bicyclist volumes. The results indicate that daily bicyclist volume varies across hours of the day as well as days of the week. Both temperature and rainfall are found to have a significant influence on daily bicyclist volume but with different degrees of sensitivity in these two cities which correspond to their base climates. The results are discussed in view of their implications for government strategies that seek to increase the role of bicycle in urban areas. TRB 2012 Annual Meeting Paper revised from original submittal. Ahmed, Rose, Figliozzi & Jacob 3 INTRODUCTION Policy makers are promoting bicycling as a mode of transportation since it reduces traffic congestion, energy consumption and greenhouse gas emissions and enhances health outcomes (1, 2, 3) and therefore offers sustainable economic, environmental and social benefits (4). At the same time, changes in weather are high on the agenda in cities around the world today because the intensity and frequency of extreme weather conditions are expected to increase as a result of climate changes (5). Since cyclists are directly exposed to the weather this paper seeks to quantify the impact of changes in weather on bicyclist’s travel behavior. There are many factors that affect demand for bicycling although research consistently highlights the importance of adequate infrastructure (6). Apart from investing in infrastructure, such as off-road paths and bicycle lanes to accommodate the growing number of cyclists and to facilitate even more growth, governments have regularly sponsored events to encourage bicycle commuting (e.g. ‘Ride to Work Day’ (7)). Seasonal variations in ridership (8, 9) suggest that there are many fair weather utilitarian cyclists and this presents a challenge from the perspective of gaining the maximum benefit from the investments in bicycle infrastructure targeted on promoting this mode of transport. Policies could be undermined by the influence of weather; particularly where the target is to increase women’s cycling (2), if women are more likely to be deterred from riding in adverse weather. Following global policy, Portland, Oregon and Brisbane, Queensland has been encouraging bicycling. Portland is well known for being one of the most bicycle friendly cities in the USA. In 2008 Portland became the first major city in the USA designated as a Platinum-level Bicycle Friendly Community by the League of American Bicyclists (10, 11). Likewise, in Queensland, cycling has been encouraged by allocating funds to develop cycle networks, through supporting various cycle events (12) and developing world-class end-of-trip facilities to promote commuter cycling (13). While bicycle count data has been complied for more than ten years (14), little research has explored the temporal variability in bicycle volume and in particular, how commuter cyclists of Portland and Brisbane are influenced by weather conditions. Portland and Brisbane fall into different climatic zones; Portland’s climate is more temperate mediterranean climate whereas Brisbane experiences a tropical climate (15). As noted earlier, weather and climate has the potential to influence cycling. Thus, this paper seeks to quantify the influence of day to day changes in weather on bicyclist volume in these two cities whose base climatic condition are different. This analysis can also provide insight into weather corrections which could be useful in adjusting counts made at one point in time (e.g. census journey to work data) to account for regional differences in weather/climate. The structure of this paper is as follows. Section two provides a review of the relevant literature. The review focuses on the effect of changing weather conditions on travel behavior and identifies the sources of data and the methodologies which have been used to develop understanding of those relationships. The following section examines temporal variation of bicyclist volume in Portland and Brisbane. It also explores how various weather parameters specifically, temperature and rainfall, vary over the year. Data from Portland and Brisbane are then used to calibrate aggregate bicycle demand models that incorporate a range of explanatory variables including weather. The final section presents the conclusions of the research and identifies future research needs and directions. TRB 2012 Annual Meeting Paper revised from original submittal. Ahmed, Rose, Figliozzi & Jacob 4 INSIGHT FROM THE LITERATURE There is limited research which explores how travel behavior is influenced by weather. Nankervis (16) examined how weather and climate affects bicycle commuters in Melbourne, Australia. He identified a decrease in cycling over the winter months. Heavy rain was the biggest deterrent for the cyclists to ride with 67% of the respondents indicating they would be deterred from riding in heavy rain. Among these respondents who did not ride (67%), almost all of them (90%) indicated that they still made the trip but used an alternative mode. Thomas et al (17) identified that temperature caused greatest variation and wind caused the least variation in bicycling demand in Netherlands. More recently, Lewin (18) confirmed that the impact of temperature on daily bicyclist volume in Boulder, CO was non linear with the optimum riding temperature estimated to be 32.2 0 C. Moreno and Nosal (1) investigated how bicycle usage in Montreal, Canada is impacted by various weather conditions. Their analyses found that precipitation, temperature and humidity influence bicycle ridership. When other factors are controlled, a 100% increase in temperature increases the ridership by 43-50%. However, temperature greater than 28 0 C and humidity greater than 60%, reduced the ridership which confirms a nonlinear effect. Precipitation was also found to have both a direct and a lagged effect on ridership. As a result, bicyclist volume in a particular hour is not only affected by the presence of rain in that hour but also affected if there was rain in previous hours. Other research (19) examined ridership sensitivity to weather in Portland, Oregon, USA. Analyses of six months of data from Portland, Oregon indicated that a 1 0 C rise in temperature increases the volume of daily bicyclists by between 3% to 6% whereas each1mm increase of precipitation decreases the volume by around 4%. Both Richardson (20) and Phung and Rose (21) explored how weather variations affect bicycle ridership in Melbourne, Australia. Rain was identified as the most influential weather parameter which significantly decreased commuting cyclist volumes. Both of these studies found that rainfall has a non-linear effect. Richardson (20) identified that daily rainfall of around 8 mm, reduces cyclist volumes by about 50% compared to days when there is no rain. In contrast, Phung and Rose (21) found that light rain (defined as daily rainfall less than 10 mm) deterred between 8 and 19% of all cyclists while heavy rain (defined as daily rainfall greater than 10 mm) deterred about one-third more (13 to 25%). Air temperature has been identified to have a non-linear and non-symmetrical relationship on commuter cyclist volume with the volume of riders decreasing immediately after the ideal riding temperature (20, 21). Phung and Rose (21) identified the ideal riding air temperature to be about 28 0 C whereas Richardson’s (20) analysis identified the optimal air temperature for riding to be 25 0 C. Wind effects were detected for most of the sites in Melbourne studied by Phung and Rose (21), but ridership on the Bay Trail, which runs along the exposed coast of Port Phillip Bay, was the most sensitive to wind change. Table 1 summarizes the general nature of the conclusions reached from studies focused on different geographic locations which have a range of background climatic conditions. The literature suggests that across the locations which have been examined, cyclists have been found to be sensitive to weather although that sensitivity varies across different weather parameters. Temperature and precipitation are the most important influences on bicyclist volume. Wind was found to be deterrent in some places but mostly identified as being less influential. TRB 2012 Annual Meeting Paper revised from original submittal. Ahmed, Rose, Figliozzi & Jacob 5 TABLE 1 Different Location’s Sensitivity to Weather Parameters Location Weather parameter Climate Reference Temperature Precipitation Wind Melbourne, Australia   Highly influential  Least influential Temperate oceanic climate Nankervis (16) Netherlands  Highly influential   Temperate oceanic climate Thomas et al (17) Boulder, CO  Highly influential  Warm oceanic climate Lewin (18)