We consider modelling time series using a generalized additive model with first-order Markov structure and mixed transition density having a discrete component at zero and a continuous component with positive sample space. Such models have application, for example, in modelling daily occurrence and intensity of rainfall, and in modelling the number and size of insurance claims. We show how thes...

[1] Positive feedbacks between vegetation and soil moisture may induce, in arid ecosystems, the emergence of two alternative stable states, corresponding to bare and completely vegetated soil. A new analytical model is developed to investigate this behavior and to study the effects of interannual rainfall variability on the dynamics of bistable ecosystems. When dichotomic Markov noise is used t...

Fluvial sediment export from small mountainous rivers in Oceania has global biogeochemical significance affecting the turnover rate and export of terrestrial carbon, which might be speeding up at the recognized conditions of increased rainfall intensity. In this study, the historical runoff and sediment export from 16 major rivers in Taiwan are investigated and separated into an early stage (19...

A scale-invariance analysis of space and time rainfall events monitored by meteorological radar over the area of Rome (Italy) is proposed. The study of the scale-invariance properties of intense precipitation storms, particularly important in flood forecast and risk mitigation, allows to transfer rainfall information from the large scale predictive meteorological models to the small scale hydro...

BACKGROUND AND OBJECTIVES: Very low grid power penetration in some urban areas has led to telecoms companies investing massively in the deployment of diesel generators (DGs). These deployments have led to diesel and waste oil spill at base transceiver station (BTS) sites during maintenance cycles, impacting the environment and human activities. The objective of this study is to...

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such ...

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of sufficient ground-based observing network in many parts of th...

Many investigators have used satellite data to derive rainfall intensity and to compare them with rain gauge data. However, there has always been a problem: what is the optimal time period for the two different types of data? A set of well-controlled data collected by ground-based dual-frequency microwave radiometers at the National Central University (24.98N, 121.18E) in Taiwan between January...

Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation recor...

Satellite-based rainfall products have extensive applications in global change studies, but they are known to contain deviations that require comprehensive verification at different scales. In this paper, we evaluated the accuracies of two high-resolution satellite-based rainfall products: the Tropical Rainfall Measurement Mission (TRMM) rainfall product 3B42V7 and the Climate Prediction Center...