Considerable rainfall occurs in India during the post-monsoon period from October to December, particularly over north-eastern, eastern and southern regions, and this is of great significance in agricultural and allied sectors. For the first time, we have attempted to provide detailed information on the variability and predictability of the post-monsoon rainfall (PMR) of the country. Details on...

This article reviews some of the recent advances in the analysis of extreme flood events in Malaysia. First, a detailed analysis of daily rainfall precipitation measurements leads to new understanding regarding Malaysian monsoons: the conditional probability of rainfall steadily increases as a function of the number of successive rainy days. The probability of multi-day rainfall events has also...

Savanna ecosystems are water limited and responsive to rainfall on short time scales, characteristics that can be exploited to estimate fractional cover of trees, grass, and bare soil over large-scale areas from synthesis of remote sensing and rainfall measurements. A method is presented to estimate fractional cover based upon the differing ways in which grasses and trees respond to rainfall, a...

Wildfires are often governed by rapid changes in seasonal rainfall. Therefore, measuring seasonal rainfall on a temporally finescale should facilitate the prediction of wildfire regimes. To explore this hypothesis, daily rainfall data over a 58-yr period (1950–2007) in south-central Florida were transformed into cumulative rainfall anomalies (CRAs). This transformation allowed precise estimatio...

[1] A sudden reduction in rainfall occurred in the southwest of Western Australia in the mid-20th century. This reduced inflows to the Perth water supply by about 120 GL (42%) and led to an acceleration of projects to develop new water sources at a cost of about $300 million. The reduction in rainfall was coincident with warmer temperatures. A major analysis of these changes indicated that the ...

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Rainfall is the driving force behind all hydrologic processes in a watershed, and therefore the driving force in hydrologic modeling. In the past, raingauge data has been used as the primary input for these models. However, raingauge networks are generally sparse and insufficient to capture the spatial variability across large watersheds. A relatively new alternative is high−resolution radar ra...

Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolu...

[1] A quantitative definition of and ability to predict the onset and duration of the dominant rainfall season in a region are important for agricultural and natural resources management. In this paper, a methodology based on an analysis of daily rainfall occurrence is proposed and applied to define the onset and end of the rainfall season in northeast Brazil. Multiple rainfall gauges are consi...

Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency...