Rainfall Speed Research Articles

Integration of GIS-Based Multicriteria Decision Analysis and Analytic Hierarchy Process to Assess Flood Hazard on the Al-Shamal Train Pathway in Al-Qurayyat Region, Kingdom of Saudi Arabia

Understanding the dynamics of floods in dry environments and predicting an accurate flood hazard map considering multiple standards and conflicting objectives is of great political and planning importance in the Kingdom of Saudi Arabia’s vision for the year 2030, in order to reduce losses in lives, property, and infrastructure. The objectives of this study are (1) to develop a flood vulnerability map identifying flood-prone areas along the Al-Shamal train railway pathway; (2) to forecast the vulnerability of urban areas, agricultural land, and infrastructure to possible future floods hazard; and (3) to introduce strategic solutions and recommendations to mitigate and protect such areas from the negative impacts of floods. In order to achieve these objectives, multicriteria decision analysis based on geographic information systems (GIS-MCDA) is used to build a flood hazard map of the study area. The analytic hierarchy process (AHP) is applied to extract the weights of eight criteria which affect the areas which are prone to flooding hazards, including flow accumulation, distance from the wadi network, slope, rainfall density, drainage density, and rainfall speed. Furthermore, the receiver operating characteristic (ROC Curve) method is used to validate the presented flood hazard model. The results of the study reveal that there are five degrees of flooding hazard along the Al-Shamal train path, ranging from very high to very low. The high and very high hazard zones comprise 19.2 km along the path, which constitutes about 26.45% of the total path length, and are concentrated at the intersections of the Al-Shamal train pathway with the Bayer and Al-Makhrouk wadis. Moderate, low, and very low flood severity areas constitute nearly 53.39 km, representing 73.55% of the total length (72.59 km) of the track. These areas are concentrated at the intersection of the Al-Shamal train track with the Haseidah Al-Gharbiyeh and Hsaidah Umm Al-Nakhleh wadis. Urban and agricultural areas that are vulnerable to high and very high flooding hazards are shown to have areas of 29.23 km2 (22.12%) and 59.87 km2 (46.39%), respectively.

Spectra of atmospheric water in precipitating quasi-geostrophic turbulence

Atmospheric water has a complex behaviour partly due to the influence of precipitation. Consequently, it is challenging to explain properties of water such as the scale-dependence of its variance, for which a range of spectral exponents has been identified in observational data. Here, a precipitating quasi-geostrophic (PQG) model is explored as a possible prototype for contributing to understanding of water spectra, in an idealised setting. Geostrophic turbulence is examined in numerical simulations, where precipitation is included to explore its effect on the water spectrum, but where phase changes are neglected to allow corresponding theoretical analysis. The water spectral exponent is seen to range from approximately −1.4 to approximately −5 depending on the rainfall speed parameter, , which indicates a significant influence of precipitation on the water spectrum. The limiting values of this range are explained through asymptotic analyses for large and small values of . To obtain this theoretical understanding of the model, a key observation is that water can be written as a linear combination of two other tracers (equivalent potential temperature and a moist variable M), which themselves have theoretically tractable spectra. These two other tracers are linked to distinct modes of the PQG equations–the vortical mode and a moist mode – and the analysis here highlights the usefulness of wave or mode decompositions for understanding water in a saturated domain.

Simultaneous wind and rainfall detection by power spectrum analysis using a VAD scanning coherent Doppler lidar.

Doppler wind lidar is an effective tool for wind detection with high temporal and spatial resolution. However, precise wind profile measurement under rainy conditions is a challenge, due to the interfering signals from raindrop reflections. In this work, a compact all-fiber coherent Doppler lidar (CDL) at working wavelength of 1.5 µm is applied for simultaneous wind and precipitation detection. The performance of the lidar is validated by comparison with the weather balloons. Thanks to the ability of precise spectrum measurement, both aerosol and rainfall signals can be detected by the CDL under rainy conditions. The spectrum width is used to identify the precipitation events, during which the two-peak Doppler spectrum is observed. The spectrum is fitted by a two-component Gaussian model and two velocities are obtained. By using the velocity-azimuth display (VAD) scanning technique, wind speed and rainfall speed are simultaneously retrieved. The false detection probability of wind speed in the rainy conditions is thus reduced.

Moisture Transport due to Baroclinic Waves: Linear Analysis of Precipitating Quasi-Geostrophic Dynamics

AbstractThe effects of rainfall speed, V

Modeling convective‐stratiform precipitation processes on a Mei‐Yu front with the Weather Research and Forecasting model: Comparison with observations and sensitivity to cloud microphysics parameterizations

Deep convective‐scale simulations of the linear mesoscale convective systems (MCSs) formed on a Mei‐Yu front over the Huai River basin in China on 7–8 July 2007 were conducted using the Advanced Research Weather Research and Forecasting model to investigate impacts of cloud microphysics parameterizations on simulated convective‐stratiform precipitation processes. Eight simulations were performed with identical configurations, except for differences in the cloud microphysics parameterizations. Measurements from rain gauges, ground‐based weather radars, and the Tropical Rainfall Measuring Mission satellite Precipitation Radar were used to quantitatively evaluate the model results. While all of the simulations largely capture the observed large‐scale characteristics of the precipitation event, notable differences among the simulations are found in the morphology and evolution of the MCSs at mesoscale and cloud scale. Significant influences on the coupling between dynamical and microphysical processes at the resolved deep convective scale by the various microphysical parameterizations are evident. On the one hand, the different microphysical schemes produce not only substantial differences in intensity of convective precipitation but also distinguishable vertical distributions of latent heating and condensate loading in the deep convective regions, which in turn results in significant differences in the vertical distributions of vertical air velocity and in the heights and strength of detrainment from deep convective regions. Consequently, detrainment of hydrometeors and positively buoyant air from the deep convective regions to the stratiform regions is significantly different, which impacts the formation and growth of ice‐phase hydrometeors at the upper levels and thus surface rainfall rates in the stratiform regions. On the other hand, prediction of rain size distribution significantly impacts the simulated rain evaporation rates and mass‐weighted rain fall speeds, and hence rain flux. Improper determination of the intercept parameter of rain size distribution can result in unrealistic features in the morphology of the storm and can have substantial impacts on precipitation distribution and evolution.