General circulation models (GCMs), used to predict rainfall at a seasonal lead-time, tend to simulate too many rainfall events of too low intensity relative to individual stations within a GCM grid cell. Even if bias in total rainfall is corrected relative to a target location, this distortion of frequency and intensity is expected to adversely affect simulations of crop growth and yield. We pr...

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products...

[1] Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) is a satellite infrared-based algorithm that produces global estimates of rainfall at resolutions of 0.25 0.25 and a half-hour. In this study the model parameters of PERSIANN are routinely adjusted using coincident rainfall derived from the Tropical Rainfall Measurement Mission Microwave Im...

BACKGROUND AND OBJECTIVES An investigation was carried out in Thailand to study the correlation between rainfall and prevalence of dengue infection during 2002-03, which can be used for prevention and control of the disease. METHODS Rainfall data (2002-03) collected from Ministry of Public Health were utilised for transformation of the infection and the rainfall data were derived from Royal I...

7 The hydrological budget of Himalayan rivers is dominated by monsoonal rainfall and 8 snowmelt, but their relative impact is not well established. Current knowledge of rainfall and 9 snow-cover distribution is unreliable because this remote region lacks a dense gauge network. 10 Here, we use a combination of remotely-sensed climate parameters that have been both 11 calibrated and validated to ...

7 The hydrological budget of Himalayan rivers is dominated by monsoonal rainfall and 8 snowmelt, but their relative impact is not well established. Current knowledge of rainfall and 9 snow-cover distribution is unreliable because this remote region lacks a dense gauge network. 10 Here, we use a combination of remotely-sensed climate parameters that have been both 11 calibrated and validated to ...

Topography is a significant factor influencing the spatial distribution of precipitation. This study developed a new methodology to evaluate and calibrate the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) products by merging geographic and topographic information. In the proposed method, firstly, the consistency rule was introduced to evaluate the fitness of ...

The rainfall input is one of the main factors influencing the magnitude of the runoff response during a flood event. Its temporal and spatial distribution significantly contributes to the formation of hydrograph shape, peak discharge and flood volume. a novel approach to the evaluation of the role of the temporal rainfall pattern of hydrograph is presented in this contribution. The methodology ...

Radar rainfall data are affected by several types of error. Beside the error in the measurement of the rainfall reflectivity and its transformation into rainfall intensity, random errors can be generated by the temporal spacing of the radar scans. The aim of this work is to analize the sensitivity of the estimated rainfall maps to the radar sampling interval, i.e. the time interval between two ...

Pore water pressure, build up by recharge of hydrosystems, is one of the main triggering factors of deep seated landslides. Effective rainfall, which is the part of the rainfall which recharges the aquifer, is a significant parameter. Soil-water balance is an accurate way to estimate effective rainfall. Nevertheless this approach requires evapo5 transpiration, soil water storage and runoff char...