Validation of a Meteosat Second Generation solar radiation dataset over the northeastern Iberian Peninsula

Cristóbal, Jordi; Anderson, Martha C.

doi:10.5194/hess-17-163-2013

Cited by 27 publications

(42 citation statements)

References 47 publications

(52 reference statements)

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“…RS also shows stable results at the monthly scale over the annual cycle, with an average temporal variability in accuracy represented by a standard deviation of 3 %. The rel- atively high accuracy of remotely sensed R s maps already available from geostationary satellites (Otkin et al, 2005;Cristóbal and Anderson, 2013), as well as the fact that no auxiliary information is required for the application of the RS method, provide further motivation for adoption of this technique in large-scale applications.…”

Section: Discussionmentioning

confidence: 99%

Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications

Cammalleri

Anderson

Kustas

2014

Hydrol. Earth Syst. Sci.

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Abstract. Four upscaling methods for estimating daytime actual evapotranspiration (ET) from single time-of-day snapshots, as commonly retrieved using remote sensing, were compared. These methods assume self-preservation of the ratio between ET and a given reference variable over the daytime hours. The analysis was performed using eddy covariance data collected at 12 AmeriFlux towers, sampling a fairly wide range in climatic and land cover conditions. The choice of energy budget closure method significantly impacted performance using different scaling methodologies. Therefore, a statistical evaluation approach was adopted to better account for the inherent uncertainty in ET fluxes using eddy covariance technique. Overall, this approach suggested that at-surface solar radiation was the most robust reference variable amongst those tested, due to high accuracy of upscaled fluxes and absence of systematic biases. Top-of-atmosphere irradiance was also tested and proved to be reliable under near clear-sky conditions, but tended to overestimate the observed daytime ET during cloudy days. Use of reference ET as a scaling flux yielded higher bias than the solar radiation method, although resulting errors showed similar lack of seasonal dependence. Finally, the commonly used evaporative fraction method yielded satisfactory results only in summer months, July and August, and tended to underestimate the observations in the fall/winter seasons from November to January at the flux sites studied. In general, the proposed methodology clearly showed the added value of an intercomparison of different upscaling methods under scenarios that account for the uncertainty in eddy covariance flux measurements due to closure errors.

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Section: Discussionmentioning

confidence: 99%

Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications

Cammalleri

Anderson

Kustas

2014

Hydrol. Earth Syst. Sci.

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“…Knowledge of spatiotemporal distributions of this parameter is essential for understanding numerous processes in the climate system, such the water cycle or plant photosynthesis [2]. In this regard, Rs is crucial in hydrology, playing a key role in the modelling of evapotranspiration (ET) as well as air temperature [3][4][5][6][7][8]. Moreover, it is a critical input parameter to crop monitoring systems that rely on agrometeorologic models [9,10].…”

Section: Introductionmentioning

confidence: 99%

Seasonal Characterization of Solar Radiation Estimates Obtained from a MSG-SEVIRI-Derived Dataset and a RAMS-Based Operational Forecasting System over the Western Mediterranean Coast

2016

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Solar radiation is a key factor in the Earth's energy balance and it is used as a crucial input parameter in many disciplines such as ecology, agriculture, solar energy and hydrology. Thus, accurate information of the global downward surface shortwave flux integration into the grid is of significant importance. From the different strategies used for grid integration of the surface solar radiation estimates, satellite-derived and numerical weather prediction forecasts are two interesting alternatives. In the current work, we present a comprehensive evaluation of the global downward solar radiation forecasts provided by the Regional Atmospheric Modeling System (RAMS) and the Downwelling Surface Shortwave Flux (DSSF) product, derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Both solar radiation estimates are compared to thirteen ground-based weather station measurements for the winter 2010-2011 and the summer 2011 seasons. For these periods, the most recent versions of RAMS (4.4 and 6.0) were running in parallel within the real-time weather forecasting system implemented over the Valencia Region. The solar radiation performance and accuracy are evaluated for these datasets segmented into two atmospheric conditions (clear and cloudy skies) and two terrain classes (flat and hilly). DSSF shows a very good agreement over the study area. Statistical daily evaluations show that corresponding errors vary between seasons, with absolute bias ranging from´30 to 40 W¨m´2, absolute root mean square errors (RMSE) from 25 to 60 W¨m´2, relative bias ranging from´11% to 7% and relative RMSE from 7% to 22%, depending on the sky condition and the terrain location as well, thus reproducing the observations more faithfully than RAMS, which produces higher errors in comparison to the measurements. In this regard, statistical daily evaluations show absolute bias values varying from´50 to 160 W¨m´2, absolute RMSE from 60 to 240 W¨m´2, relative bias ranging from´30% to 40% and relative RMSE from 10% to 80%, also depending on the daily initialization and the forecast horizon. This bias variability demonstrates that there is a different trend in the deviation of the model results in relation to the observations, both for the DSSF product and RAMS forecasts, and considering the summer and the winter seasons independently. In this regard, although there is an overestimation of the observed solar radiation within the summer months, this magnitude is underestimated during the winter. Finally, comparing this solar radiation estimates for different atmospheric conditions and different terrain classes, the best results are found under clear skies over flat terrain. This result is achieved using both methodologies.

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“…Several algorithms are already in practice with different complexity levels to estimate evapotranspiration based on different climatic conditions and land use variability (Elhag et al, 2011;Espadafor et al, 2011;Cristóbal and Anderson, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Weather and wind conditions induce a regional and seasonal variation of evapotranspiration estimation (Hanson, 1991;Cristóbal and Anderson, 2013).…”

Section: Introductionmentioning

confidence: 99%

Realization of daily evapotranspiration in arid ecosystems based on remote sensing techniques

Elhag

Bahrawi

2017

Geosci. Instrum. Method. Data Syst.

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Abstract. Daily evapotranspiration is a major component of water resources management plans. In arid ecosystems, the quest for an efficient water budget is always hard to achieve due to insufficient irrigational water and high evapotranspiration rates. Therefore, monitoring of daily evapotranspiration is a key practice for sustainable water resources management, especially in arid environments. Remote sensing techniques offered a great help to estimate the daily evapotranspiration on a regional scale. Existing open-source algorithms proved to estimate daily evapotranspiration comprehensively in arid environments. The only deficiency of these algorithms is the course scale of the used remote sensing data. Consequently, the adequate downscaling algorithm is a compulsory step to rationalize an effective water resources management plan. Daily evapotranspiration was estimated fairly well using an Advance Along-Track Scanner Radiometer (AATSR) in conjunction with (MEdium Resolution Imaging Spectrometer) MERIS data acquired in July 2013 with 1 km spatial resolution and 3 days of temporal resolution under a surface energy balance system (SEBS) model. Results were validated against reference evapotranspiration ground truth values using standardized Penman-Monteith method with R 2 of 0.879. The findings of the current research successfully monitor turbulent heat fluxes values estimated from AATSR and MERIS data with a temporal resolution of 3 days only in conjunction with reliable meteorological data. Research verdicts are necessary inputs for a well-informed decisionmaking processes regarding sustainable water resource management.

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Validation of a Meteosat Second Generation solar radiation dataset over the northeastern Iberian Peninsula

Cited by 27 publications

References 47 publications

Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications

Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications

Seasonal Characterization of Solar Radiation Estimates Obtained from a MSG-SEVIRI-Derived Dataset and a RAMS-Based Operational Forecasting System over the Western Mediterranean Coast

Realization of daily evapotranspiration in arid ecosystems based on remote sensing techniques

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