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Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?

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  • Pelosi, A.
  • Chirico, G.B.

Abstract

This study evaluates the accuracy of daily reference evapotranspiration (ETo), computed according to the FAO Penman-Monteith equation by using a set of input weather variables obtained by blending ERA5-Land (ERA5L) reanalysis data with surface incoming solar radiation (Rs) provided by the instruments on board the Meteosat geostationary satellites, operationally delivered by the Satellite Applications Facility on Climate Monitoring (CM-SAF). Performance assessment was carried out in Sicily (southern Italy) by using data from 38 automatic ground weather stations (AWSs) for years 2003–2020. ERA5L and CM-SAF data were first downscaled and bias-corrected with a calibration dataset; ERA5L air temperature data were also downscaled by lapse-rate correction. ETo estimates obtained with the blended ERA5L and CM-SAF validation dataset (ERA5L+CM-SAF) were compared with two other ETo estimates respectively obtained by using ERA5L and interpolated ground weather data (IGD). Performance indicators of the IGD dataset were evaluated by recursively applying universal kriging or ordinary kriging to the observed weather data, according to a cross-validation procedure. Rs provided by CM-SAF outperformed Rs obtained by ground interpolation, thus confirming the convenience of using bias-corrected CM-SAF data even when ground observations are available in the study area. ETo estimates with ERA5L+CM-SAF showed a normalized RMSE of 12%, outperforming ERA5L ETo estimates while performing comparably to ETo estimates obtained with the IGD dataset. The results suggested that the proposed blended dataset is a good proxy for interpolated ground weather observations in the assessment of ETo at regional scale when weather measurements cannot be easily gathered or in data-sparse regions.

Suggested Citation

  • Pelosi, A. & Chirico, G.B., 2021. "Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?," Agricultural Water Management, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:agiwat:v:258:y:2021:i:c:s0378377421004467
    DOI: 10.1016/j.agwat.2021.107169
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    1. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).
    2. Frances C. Moore & David B. Lobell, 2014. "Adaptation potential of European agriculture in response to climate change," Nature Climate Change, Nature, vol. 4(7), pages 610-614, July.
    3. Paredes, P. & Pereira, L.S. & Almorox, J. & Darouich, H., 2020. "Reference grass evapotranspiration with reduced data sets: Parameterization of the FAO Penman-Monteith temperature approach and the Hargeaves-Samani equation using local climatic variables," Agricultural Water Management, Elsevier, vol. 240(C).
    4. Peter Bauer & Alan Thorpe & Gilbert Brunet, 2015. "The quiet revolution of numerical weather prediction," Nature, Nature, vol. 525(7567), pages 47-55, September.
    5. Consoli, S. & Vanella, D., 2014. "Mapping crop evapotranspiration by integrating vegetation indices into a soil water balance model," Agricultural Water Management, Elsevier, vol. 143(C), pages 71-81.
    6. Prashant Srivastava & Tanvir Islam & Manika Gupta & George Petropoulos & Qiang Dai, 2015. "WRF Dynamical Downscaling and Bias Correction Schemes for NCEP Estimated Hydro-Meteorological Variables," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2267-2284, May.
    7. Pelosi, A. & Medina, H. & Villani, P. & D’Urso, G. & Chirico, G.B., 2016. "Probabilistic forecasting of reference evapotranspiration with a limited area ensemble prediction system," Agricultural Water Management, Elsevier, vol. 178(C), pages 106-118.
    8. Longo-Minnolo, G. & Vanella, D. & Consoli, S. & Intrigliolo, D.S. & Ramírez-Cuesta, J.M., 2020. "Integrating forecast meteorological data into the ArcDualKc model for estimating spatially distributed evapotranspiration rates of a citrus orchard," Agricultural Water Management, Elsevier, vol. 231(C).
    9. Pereira, Luis S. & Cordery, Ian & Iacovides, Iacovos, 2012. "Improved indicators of water use performance and productivity for sustainable water conservation and saving," Agricultural Water Management, Elsevier, vol. 108(C), pages 39-51.
    10. Iglesias, Ana & Garrote, Luis, 2015. "Adaptation strategies for agricultural water management under climate change in Europe," Agricultural Water Management, Elsevier, vol. 155(C), pages 113-124.
    11. Paredes, Paula & Martins, Diogo S. & Pereira, Luis Santos & Cadima, Jorge & Pires, Carlos, 2018. "Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes," Agricultural Water Management, Elsevier, vol. 210(C), pages 340-353.
    12. Xiaodong Ren & Zhongyi Qu & Diogo S. Martins & Paula Paredes & Luis S. Pereira, 2016. "Daily Reference Evapotranspiration for Hyper-Arid to Moist Sub-Humid Climates in Inner Mongolia, China: I. Assessing Temperature Methods and Spatial Variability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 3769-3791, September.
    13. Luis Santos Pereira, 2017. "Water, Agriculture and Food: Challenges and Issues," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2985-2999, August.
    14. Rehman, Shafiqur & Ghori, Saleem G, 2000. "Spatial estimation of global solar radiation using geostatistics," Renewable Energy, Elsevier, vol. 21(3), pages 583-605.
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    4. Pelosi, A., 2023. "Performance of the Copernicus European Regional Reanalysis (CERRA) dataset as proxy of ground-based agrometeorological data," Agricultural Water Management, Elsevier, vol. 289(C).

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