Satellite Identification of Rain Days over the Upper Nile River Basin Using an Optimum Infrared Rain/No-Rain Threshold Temperature Model

Todd, Martin C.; Barrett, EC; Beaumont, M.J.; Green, Joanna L.

doi:10.1175/1520-0450(1995)034<2600:siordo>2.0.co;2

Cited by 47 publications

(36 citation statements)

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“…Cloud type, season and regions may affect the relationships and the calibration in Ethiopia is also highly dependent on orography and affected by height above sea level, slopes and rain shadows. Todd et al (1995), however, show that marked improvements in rainarea classification may be obtained using an optimum infrared rain/no-rain threshold temperature variation. The method does represent probably the best means available of deriving a spatially distributed time series of rainfall for the Blue Nile basin.…”

Section: Potential For Developing the Modelmentioning

confidence: 99%

“…An 11 region distributed model of the Blue Nile was developed, based on the Sacramento Watershed model (Grijsen et al, 1992). Similar work is also in progress at the National Oceanic and Atmospheric Administration in Washington, USA, in association with the Egyptian Ministry of Public Works, who are developing a comprehensive model of the Nile river in order to predict the inflows to the High Aswan Dam reservoir (Barrett, 1993;Schaake et al, 1993;Johnson & Curtis, 1994;Todd et al, 1995). Johnson & Curtis (1994) describe the application of a monthly water balance model to a number of sub-catchments in the Blue Nile basin with available data.…”

Section: Introductionmentioning

confidence: 99%

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A water balance model of the Upper Blue Nile in Ethiopia

Conway

1997

Hydrological Sciences Journal

151

135

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This paper describes the development and validation of a water balance model of the Upper Blue Nile in Ethiopia. A major requirement of any modelling attempt is the availability of climatic and hydrological data. However, for the Upper Blue Nile, only a limited number of observation sites are available over a very large area. As a result, the model described here is a grid-based water balance model which requires limited data inputs, few parameters and runs on a monthly time-step. Climate is dominated by the influence of elevation in the river basin. Estimates of potential évapotranspiration (PE) and rainfall are predicted for 10-minute resolution grid cells for input to the model. These estimates are based on multiple regression models using latitude, longitude and elevation. In the basin, annual mean PE and rainfall range, with increasing elevation, from 1800 mm to 1200 mm and 924 mm to 1845 mm, respectively. In the model, vegetation cover is not explicitly treated and soil characteristics are spatially invariant. The model is calibrated to reproduce mean monthly runoff over a 37-year period , and validated by its ability to simulate sub-catchment runoff and historical variations in Blue Nile runoff. The key factor that determines model performance is the quality of the rainfall inputs, with the best results obtained with a time series comprised of long, good quality station data. Over a 76-year period the correlation between observed and simulated annual flows was 0.74 and the mean error was 14%, although fairly large errors occurred in individual years. Considering the paucity of data for the basin, these results are encouraging. The model is used to investigate spatial variability in the sensitivity of runoff to changes in rainfall and PE. The sensitivity is greatly affected by the runoff ratio of the model grid cells and it increases as grid cell runoff ratio decreases. The sensitivity is also affected by the seasonal distribution of rainfall. The paper ends with a discussion of the model's performance and its potential for future development.

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Section: Potential For Developing the Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A water balance model of the Upper Blue Nile in Ethiopia

Conway

1997

Hydrological Sciences Journal

151

135

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“…The method uses thresholds that vary from pixel to pixel depending on an ongoing calibration against synoptically reported rainfall, then deploys a weighting for mean rain per rain day at nearby rain gauges, rather than assuming that the association between cold cloud and rainfall is constant (Barrett, 1993). This B4 method has been used for rainfall estimation in the upper Nile River basin, including the Ethiopia highlands (Todd et al, 1995) and has been applied operationally to several other areas of the tropics for several years (Barrett et al, 1996). The Todd et al study modelled spatial variations in optimum cold cloud rain/no rain thresholds in relation to latitude, longitude and elevation.…”

Section: Introductionmentioning

confidence: 99%

“…Menz concluded that there was little variation in linear correlation coefficients for precipitation threshold temperatures between 223 K and 285 K with maximum values at 252 K for September and 280 K for April. This contradicts the conclusion of Todd et al (1995) that variations in threshold temperature are of crucial importance. However, 280 K does not represent 'cold' cloud, though it may distinguish warm stratus from ground surface temperatures, and since the MPI (Cold Cloud) method was developed for convective rainfall, we consider the results presented by Menz to be of doubtful validity.…”

Section: Introductionmentioning

confidence: 99%

A comparison of Meteosat rainfall estimation techniques in Kenya

Tucker¹,

Sear²

2001

Meteorological Applications

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Two methods for estimating ten‐day rainfall totals from Meteosat infra‐red imagery were compared for the April–June 1996 ‘long rains’ of Kenya in an area covering the eastern highlands and the Tana and Athi river basins. One of these (the Bristol ‘B4’ method) was then used for rainfall estimation for the whole of Kenya, for November 1996 and the other, the TAMSAT ‘Cold Cloud Duration’ (CCD) method was used to estimate rainfall for the whole of Kenya for November 1997 to April 1998. April–June 1996 was an unusual season with very few large rainstorms. For this comparison period the B4 method gave better estimates of actual rainfall than the TAMSAT method because it used a variable cold cloud threshold temperature and ongoing calibration against rain gauge data. Comparison of ten‐day CCD totals with rainfall for the 1997–1998 period indicated that using the TAMSAT method gave best rainfall estimates for the arid and semi‐arid areas of eastern and northern Kenya and for months other than the main rainy season months of November and April. Both methods could be used successfully to identify periods with well below or well above average rainfall even over highland areas, and they are therefore useful for providing food security early warnings. Copyright © 2001 Royal Meteorological Society

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“…Among others we recall the Griffith-Woodley technique (Griffith et al, 1978), the Negri-Adler-Wetzel technique (NAW) (Negri et al, 1984), and the convective stratiform technique (CST) (Adler & Negri, 1988). Thresholding methods were also applied to produce rain estimations for periods of ten days or more: see, for example, the application to the River Nile catchment by Todd et al (1995).…”

Section: Introductionmentioning

confidence: 99%