Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant an...

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the nat...

BACKGROUND In the tropics, rainfall data are seldom accurately recorded, and are often discontinuous in time. In the scope of plague-research in northeast Tanzania, we adapted previous research to reconstruct rainfall patterns at a suitable resolution (1 km), based on time series of NDVI: more accurate satellite imagery was used, in the form of MODIS NDVI, and rainfall data were collected from ...

In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinski...

The Tibetan Plateau (TP) has long been regarded as a key driver for the formation and variations of the Indian summer monsoon (ISM). Recent studies, however, have indicated that the ISM also exerts a considerable impact on rainfall variations in the TP, suggesting that the ISM and the TP should be considered as an interactive system. From this perspective, the covariability of the July–August m...

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 ...