Article
Environmental Studies
Sailesh Acharya, Patrick A. Singleton
Summary: Inclement weather and poor air quality have negative effects on non-motorized travel, especially in recreational locations. A study conducted in two trail locations in northern Utah found that non-motorized travel significantly reduced during inclement weather. The impact of rainfall and cold temperatures on non-motorized travel was smaller for utilitarian sites compared to recreational sites. Non-motorized counts at the recreational site were higher on holidays, weekends, and days with greater snow depth.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Environmental Sciences
Wenyue Wang, Klemens Hocke
Summary: In this study, the characteristics of atmospheric parameters before, during, and after rain events in Bern, Switzerland were investigated. The study found that the air density can be used as a precursor to predict rainfall with a true detection rate of 60%.
Article
Multidisciplinary Sciences
Jing Gao, Melissa S. Bukovsky
Summary: The study finds that urban land patterns can sometimes decrease rather than increase population exposure to climate extremes, even heat extremes, and that spatial patterns, rather than total quantities of urban land, have a greater influence on population exposures. This provides preliminary suggestions for incorporating long-term climate resilience in urban and regional land-use system designs, and motivates the search for optimal spatial urban land patterns that can consistently moderate population exposures to climate extremes throughout the 21st century.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Lyuchao Liao, Zhengrong Li, Shukun Lai, Wenxia Jiang, Fumin Zou, Xiang Yu, Zhiyu Xu
Summary: This study proposes a traffic congestion measurement method considering the influence of service areas, and it is implemented by merging ETC transaction datasets and service area entrance data. The experiments show that this method can be applied to measure the effect caused by service areas in the absence of service area entry data. The model can also provide references for measuring other traffic indicators under the influence of service areas.
Article
Engineering, Civil
Sophie Louise Ullrich, Mark Hegnauer, Dung Viet Nguyen, Bruno Merz, Jaap Kwadijk, Sergiy Vorogushyn
Summary: Stochastic modeling of precipitation is crucial for flood risk assessment. Two weather generators were evaluated for their ability to simulate precipitation fields, with the station-based generator overestimating areal extreme precipitation. The auto-regressive model tends to generate larger rainfall fields while the nearest-neighbor resampling generator reproduces extreme events well.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Civil
Binliang Li, Haiming Cai, Dan Xiao
Summary: This study analyzes the persistent effect of snowfall on taxi operation using GPS trajectory data collected in Harbin, China. The research proposes an autoregressive distribution lag model (ARDL) and finds that snowfall has a lag effect on taxi operation lasting about 3 days. The study also highlights the positive effect of weekends on taxi operation.
JOURNAL OF ADVANCED TRANSPORTATION
(2022)
Article
Environmental Sciences
Yawen Wang, Yuchen Wei, Kehang Li, Xiaoting Jiang, Conglu Li, Qianying Yue, Benny Chung-ying Zee, Ka Chun Chong
Summary: The study investigated the short-term associations between extreme temperatures, extreme rainfall, and DF infection risk in South and Southeast Asia. Results showed an increased risk of DF infection within 1-3 weeks after extremely high temperatures, while extreme rainfall was associated with a decreased DF risk.
ENVIRONMENT INTERNATIONAL
(2022)
Article
Geosciences, Multidisciplinary
Steven P. Chavez, Ana P. Barros
Summary: This study investigates the sensitivity of warm orographic cloud development to aerosol indirect effects. By using regional aerosol measurements and default aerosol, the study compares aerosol-cloud-precipitation interactions in three rainfall events: enhanced local convection, a frontal system, and a tropical system. The results show that the impact of aerosol-cloud-precipitation interactions on orographic rainfall spatial variability is conditional on weather regime.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Geosciences, Multidisciplinary
Wenting Wang, Shuiqing Yin, Bofu Yu, Shaodong Wang
Summary: The study developed a set of site-specific parameter values for the CLIGEN stochastic weather generator in mainland China using interpolation methods, showing that universal kriging (UK) generally outperformed ordinary kriging (OK). The interpolated parameter values exhibited good accuracy and efficiency, with interpolated temperature-related parameters having a root mean square error of <= 0.88 degrees C and precipitation- and solar-radiation-related parameters showing a Nash-Sutcliffe efficiency coefficient of >= 0.87.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Computer Science, Interdisciplinary Applications
Achraf Tounsi, Marouane Temimi, Mohamed Abdelkader, Jonathan J. Gourley
Summary: This study evaluates the performance of deterministic and probabilistic precipitation nowcasting models over the greater New York City area. The results show that the LINDA-P method has the highest correlation and longest decorrelation times. It also performs better for moderate and heavy rainfall compared to other Lagrangian Persistence-based approaches. However, it has a higher average runtime cost compared to the STEPS method.
ENVIRONMENTAL MODELLING & SOFTWARE
(2023)
Article
Economics
Xiaobao Yang, Xianfei Yue, Huijun Sun, Ziyou Gao, Wencheng Wang
Summary: Research shows that intercity travel demand is sensitive to adverse weather conditions, especially fog, heavy rain, and snow. Differences in rainfall and snowfall between OD points, as well as adverse weather on weekends and in the afternoon, have significant impacts on intercity travel demand. Travelers with less experience are more sensitive to adverse weather.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2021)
Article
Astronomy & Astrophysics
Sandeep Chinta, J. Yaswanth Sai, C. Balaji
Summary: This study aims to identify the parameters that most strongly influence the model output variables in the WRF model using Global Sensitivity Analysis (GSA) method. Morris One-At-a-Time (MOAT) is used to evaluate sensitivity of 23 chosen tunable parameters corresponding to seven physical parameterization schemes. The study considers high-intensity 4-day precipitation events during the Indian summer monsoon, and assesses the consistency of sensitivity analysis results with different initial and lateral boundary conditions.
EARTH AND SPACE SCIENCE
(2021)
Article
Public, Environmental & Occupational Health
Javadreza Vahedi, Zhaleh Shams, Milad Mehdizadeh
Summary: This study examined the direct and indirect effects of background variables on active commuting among university students. The results revealed that psychological aspects of travel, such as satisfaction and attitudes, played a mediating role in the relationship between background variables and active commuting. Factors like gender, employment status, and mode of transportation influenced students' attitudes and satisfaction towards walking and cycling, consequently impacting their choice of active modes of transportation.
JOURNAL OF TRANSPORT & HEALTH
(2021)
Article
Meteorology & Atmospheric Sciences
Philipp Hess, Niklas Boers
Summary: The accurate prediction of heavy rainfall events remains challenging for numerical weather prediction models. In this study, a U-Net-based deep neural network is used to learn heavy rainfall events from a NWP ensemble. A frequency-based weighting method is proposed to enable the learning of heavy rainfall events in the distributions' tails. Applying this method in post-processing improves the forecast skill of heavy rainfall events.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Environmental Sciences
Yingjie Wang, Jianping Wu, Xiangrong Yang, Jun Peng, Xiaotian Pan
Summary: Numerical weather prediction (NWP) is an important method for predicting extreme weather events. This paper investigates a method for constructing a global orographic dataset suitable for NWP spectral models based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) elevation data. The effectiveness and superiority of the proposed orographic construction method are verified through simulations of extreme rainfall events in Henan Province and Beijing. The results show that the bidirectional one-dimensional filter is better than the direct two-dimensional filter in orographic processing, and the new global orographic dataset improves the simulation results for heavy rainfall events.