Dependence of the Accuracy of Precipitation and Cloud Simulation on Temporal and Spatial Scales

Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associated cloud simulation on temporal and spatial scales becomes an important issue. We report a cloud- resolving modeling analysis on this issue by comparing the control experiment with experiments perturbed by initial temperature, water vapor, and cloud conditions. The simulation is considered to be accurate only if the root-mean-squared difference between the perturbation experiments and the control experiment is smaller than the standard deviation. The analysis may suggest that accurate precipitation and cloud simulations cannot be obtained on both fine temporal and spatial scales simultaneously, which limits quanti- tative precipitation forecasting. The accurate simulation of water vapor convergence could lead to accurate precipitation and cloud simulations on daily time scales, but it may not be beneficial to precipitation and cloud simulations on hourly time scales due to the dominance of cloud processes.

Temporal and Spatial Scale Dependence of Precipitation Analysis over the Tropical Deep Convective Regime

Data from Goddard cumulus ensemble model experiment are used to study temporal and spatial scale dependence of tropical rainfall separation analysis based on cloud budget during Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment （TOGA COARE）. The analysis shows that the calculations of model domain mean or time-mean grid-scale mean simulation data overestimate the rain rates of the two rainfall types associated with net condensation but they severely underestimate the rain rate of the rainfall type associated with net evaporation and hydrometeor convergence.

Wavelet methods reveal big cat activity patterns and synchrony of activity with preys

Appropriate temporal and spatial scales are important prerequisites for obtaining reliable results in studies of wildlife activity patterns and interspecific interactions.The spread of camera-trap technology has increased interest in and feasibility of studying the activity patterns and interspecific interactions of wildlife.However,such studies are often conducted at arbitrary spatial and temporal scales,and the methods used impose scale on the study rather than determining how activity and species interactions change with spatial scale.In this study,we used a waveletbased approach to determine the temporal and spatial scales for activity patterns and interspecific interactions on Amur leopard and their ungulate prey species that were recorded using camera traps in the main Amur leopard occurrence region in northeast China.Wavelets identified that Amur leopards were more active in spring and fall than summer,and fluctuated with periodicities of 9 and 17 days,respectively.Synchronous relationships between leopards and their prey commonly occurred in spring and fall,with a periodicity of about 20 days,indicating the appropriate seasons and temporal scales for interspecific interaction research.The influence of human activities on the activity patterns of Amur leopard or prey species often occurred over longer time periods(60–64 days).Twodimensional wavelet analyses showed that interactions between leopard and prey were more significant at spatial scales of 1 km2.Overall,our study provides a feasible approach to studying the temporal and spatial scales for wildlife activity patterns and interspecific interaction research using camera trap data.