Evaluation of MSG-derived global radiation estimates for application in a regional crop model

Roerink, G.J.; Bojanowski, Jędrzej S.; Wit, Allard de; Eerens, Herman; Supit, Iwan; Léo, Oberdan; Boogaard, H.L.

doi:10.1016/j.agrformet.2012.02.006

Cited by 33 publications

(32 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…in Belgium determined RMSE equals to 104 W m −2 (about 9 MJ m −2 d −1 ),Roerink et al (2012) also determined accurate and unbiased errors with standard deviations between 30 and 51 W m −2 (about 2.5-4.5 MJ m −2 d −1 ), Annual solar radiation (Rs) assessment for 2007 obtained with LSA SAF tool using the MSG satellite for the region of Andalusia, Southern Spain. Below, curve of cumulative frequency of the Rs values obtained from LSA SAF tool.…”

mentioning

confidence: 99%

Assessment of reference evapotranspiration using remote sensing and forecasting tools under semi-arid conditions

Cruz-Blanco

Jiménez-Gavilán

Santos

et al. 2014

International Journal of Applied Earth Observation and Geoinfor

View full text Add to dashboard Cite

mentioning

confidence: 99%

Assessment of reference evapotranspiration using remote sensing and forecasting tools under semi-arid conditions

Cruz-Blanco

Jiménez-Gavilán

Santos

et al. 2014

International Journal of Applied Earth Observation and Geoinfor

View full text Add to dashboard Cite

“…The R s performance and accuracy are then evaluated for these datasets segmented based on terrain classes (flat or hilly), and taking into Remote Sens. 2016, 8,46 4 of 28 account the corresponding sky condition (clear or cloudy) together with considering all sky conditions. Additionally, the evaluation process is performed for the winter 2010-2011 and the summer 2011, separately.…”

Section: Introductionmentioning

confidence: 99%

“…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

View full text Add to dashboard Cite

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.

show abstract

“…Since 2005 the LSA-SAF method (Geiger et al, 2008b) is used to generate maps of global DSSF using observations from the Meteosat Second Generation (MSG) series of geostationary satellites (Schmetz et al, 2002) and near real time analyses of atmospheric gases from the European Center for Medium-Range Weather Forecasts (ECMWF). Albeit this LSA-SAF product has proved to be highly accurate (Ineichen et al, 2009;Roerink et al, 2012;Moreno et al, 2013), it still shows some limitations under clear sky conditions. For example, the adoption of a static aerosol optical depth (AOD) does not match the variability of aerosols in time and space (Bevan et al, 2012).…”

Section: Ceamanos Et Almentioning

confidence: 99%

Improved retrieval of direct and diffuse downwelling surface shortwave flux in cloudless atmosphere using dynamic estimates of aerosol content and type: application to the LSA-SAF project

2014

View full text Add to dashboard Cite

Abstract. Downwelling surface shortwave flux (DSSF) is a key parameter to addressing many climate, meteorological, and solar energy issues. Under clear sky conditions, DSSF is particularly sensitive to the variability both in time and space of the aerosol load and chemical composition. Hitherto, this dependence has not been properly addressed by the Satellite Application Facility on Land Surface Analysis (LSA-SAF), which operationally disseminates instantaneous DSSF products over the continents since 2005 considering constant aerosol conditions. In the present study, an efficient method is proposed for DSSF retrieval that will overcome the limitations of the current LSA-SAF product. This method referred to as SIRAMix (Surface Incident Radiation estimation using Aerosol Mixtures) is based upon an accurate physical parameterization coupled with a radiative transfer-based look up table of aerosol properties. SIRAMix considers a tropospheric layer composed of several major aerosol species that are conveniently mixed to reproduce real aerosol conditions as best as possible. This feature of SIRAMix allows it to provide not only accurate estimates of global DSSF but also the direct and diffuse DSSF components, which are crucial radiative terms in many climatological applications. The implementation of SIRAMix is tested in the present article using atmospheric analyses from the European Center for Medium-Range Weather Forecasts (ECMWF). DSSF estimates provided by SIRAMix are compared against instantaneous DSSF measurements taken at several ground stations belonging to several radiation measurement networks. Results show an average root mean square error (RMSE) of 23.6, 59.1, and 44.9 W m −2 for global, direct, and diffuse DSSF, respectively. These scores decrease the average RMSE obtained for the current LSA-SAF product by 18.6 %, which only provides global DSSF for the time being, and, to a lesser extent, for the state of the art in the matter of DSSF retrieval (RMSE decrease of 10.9, 6.5, and 19.1 % for global, direct, and diffuse DSSF with regard to the McClear algorithm). The main limitation of the proposed approach is its high sensitivity to the quality of the ECMWF aerosol inputs, which is proved to be sufficiently accurate for reanalyses but not for forecast data. Given the proximity of DSSF retrieval to the modeling of the atmospheric direct effect, SIRAMix is also able to quantify the direct radiative forcing at the surface due to a given atmospheric component (e.g., gases or aerosols).

show abstract

Evaluation of MSG-derived global radiation estimates for application in a regional crop model

Cited by 33 publications

References 27 publications

Assessment of reference evapotranspiration using remote sensing and forecasting tools under semi-arid conditions

Assessment of reference evapotranspiration using remote sensing and forecasting tools under semi-arid conditions

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

Improved retrieval of direct and diffuse downwelling surface shortwave flux in cloudless atmosphere using dynamic estimates of aerosol content and type: application to the LSA-SAF project

Contact Info

Product

Resources

About