Validation of satellite rainfall products over Greece

Feidas, H.

doi:10.1007/s00704-009-0135-8

Cited by 86 publications

(53 citation statements)

References 26 publications

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“…Several studies on the validation and comparisons of these products with ground measurements have been conducted at different scales (e.g. Dinku et al, 2007;Feidas, 2010;Guo & Liu, 2016;Hessels, 2015;Hu et al, 2014;Jiang et al, 2012;Thiemig et al, 2012;Worqlul et al, 2014).…”

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confidence: 99%

“…This indicates that the performance of satellite 6 products largely depends on the location, topography, season, and hydro-climatic characteristics of the study area. Therefore, the reliability of satellite rainfall needs to be 8 validated and compared against ground measurements to a specific area and temporal scales before it can be used in any subsequent application (Feidas, 2010;Ouma et al, 2012).…”

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confidence: 99%

“…CMAP products include monthly and pentad (5-day) mean rainfall estimates at 2.5 o spatial resolution (Feidas, 2010). These techniques produce rainfall estimates by merging ground 22 station data with rainfall estimates from several satellite-based algorithms (Xie & Arkin, 1997).…”

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confidence: 99%

“…First, the IR and PM rain estimates are merged using a maximum likelihood approach where the 26 estimate with weights are derived by comparison to the gauge analysis. Then, the gauge analysis is used to obtain an absolute value of the merged product (Feidas, 2010). …”

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confidence: 99%

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Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales

Gebremicael

Mohamed

Zaag

et al. 2017

Preprint

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16Satellite rainfall products are considered important options for acquiring rainfall estimates in the absence of ground measurements. However, estimates from these products need to be 18 validated as their accuracy can be affected by geographical position, topography, and climate, as well as by the algorithms used to derive rainfall from satellite measurements. Eight Results show thatCHIRPS, TRMM,and RFEv2 performed well and wereable to capture the 26 rainfall measured by rain gauges. The BIASand correlation of these products were within ±25% and >0.5over different time steps.The remaining products poorly performed at daily 28 time step with higher BIAS (up to ±200%) and lower correlation (<0.5). CMORPH, PERSIANN, and ARCv2 were relatively better while CMAP and GPCP performed poorly 30 (r<0.4) in all conditions. The overall performance of all products was lower in the mountainous areas of the basin with station elevation>2500 m.a.s.l. Compared to the 32 lowlands, the BIAS at highlands increased by 35% whilst the correlation dropped by 28%. Underestimation and overestimation of rainfall dominated in the mountainous and lowland 34 areas, respectively.CMORPH and TRMM overestimated while the remaining products underestimated the rainfall at all spatiotemporal scales. CMAP, ARC2, and GPCP estimates 36 were the most affected by large underestimation. Unlike in temporal scale, the performance of the products did not show a uniform pattern with respect to spatial scale.Their performance 38 improved from point to aerial comparisons in the lowlandswhereas it slightly reduced athighland areas. Poor performance in the highlands contributed to a slightly lower

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confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales

Gebremicael

Mohamed

Zaag

et al. 2017

Preprint

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“…Level 3 data of surface rain rates from the TRMM Microwave Imager (TMI) were used here, available on a monthly mean basis and at 0.5˝ˆ0.5˝spatial resolution (product code: 3A12). This product has been validated in the past, in regions included in the study area [23,24]. These rainfall data come with a quality flag which can obtain three values, 0, 1 and 2, with the zero value corresponding to the highest confidence in rain retrieval.…”

Section: Estimation Of Surface Albedo Changesmentioning

confidence: 99%

Estimation of the Land Surface Albedo Changes in the Broader Mediterranean Area, Based on 12 Years of Satellite Observations

Benas

Chrysoulakis

2015

Remote Sensing

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Abstract:The Land Surface Albedo (LSA) was estimated in the broader Mediterranean area, on an 8-day basis, for the period 2001-2012. MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product parameters, at 1 kmˆ1 km spatial resolution, were used. LSA changes during the above study period were also estimated, based on annual average values. Results revealed increasing LSA trends dominating in the Levant region and decreasing in NW Africa, of the order of 3.3% and´6.6%, respectively, while mixed signs were observed in southern Europe. Three factors that can determine the LSA changes were investigated: land cover changes, rainfall changes and Aerosol Optical Thickness (AOT) spatio-temporal variability. The analysis made clear that land cover and rainfall changes affect LSA at local and regional scales, while the effect of AOT was not important. Land cover changes revealed deforestation hot spots, where LSA was increased by 13%-14%, while an increase in rainfall over many areas in NW Africa appears to have caused a corresponding decrease in LSA by over 5%. These findings highlight the importance of a global and continuous LSA monitoring at both regional and local scales, which is necessary for both climate monitoring and modeling studies.

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Investigation of the temporal relation of remotely sensed coastal water quality with GIS modelled upstream soil erosion

et al. 2014

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Hydrological processes at the river basin influence the quality of downstream water bodies by controlling the loads of nutrients and suspended solids. Although their monitoring is important for social, economic and environmental reasons, in-situ measurements are too expensive and thus too sparse to describe their relations. The aim of this study is to investigate the temporal relations of soil erosion in the upstream part of river basins with water quality characteristics in the downstream coastal zone, using satellite remote sensing and GIS modelling. Data from satellite missions of MODIS, SRTM and TRMM were used to describe the soil erosion factors of the Universal Soil Loss Equation in three river basins, and MERIS satellite data was used to estimate chlorophyll-a and total suspended matter concentrations in the coastal zone of northwest Aegean Sea in Greece, where the rivers discharge. The resulting time series showed an average correlation of upstream rainfall with downstream water quality, which increased when soil erosion was introduced. Higher correlations were observed with the use of a time lag, revealing a variable delay between the three test sites. Lower correlation coefficients were observed for chlorophyll-a, due to the sensitivity of algae to environmental conditions. The use of free of charge satellite data and easy to operate GIS models renders the findings of this work useful for coastal zone management bodies, in order to help increase aquaculture productivity, predict algal blooms and predict siltation of ports.

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Validation of satellite rainfall products over Greece

Cited by 86 publications

References 26 publications

Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales

Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales

Estimation of the Land Surface Albedo Changes in the Broader Mediterranean Area, Based on 12 Years of Satellite Observations

Investigation of the temporal relation of remotely sensed coastal water quality with GIS modelled upstream soil erosion

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