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@ARTICLE{Bayat:1020234,
      author       = {Bayat, Bagher and Raj, Rahul and Graf, Alexander and
                      Vereecken, Harry and Montzka, Carsten},
      title        = {{C}omprehensive accuracy assessment of long-term
                      geostationary {SEVIRI}-{MSG} evapotranspiration estimates
                      across {E}urope},
      journal      = {Remote sensing of environment},
      volume       = {301},
      issn         = {0034-4257},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2023-05901},
      pages        = {113875 -},
      year         = {2024},
      abstract     = {This study quantifies the accuracy of evapotranspiration
                      (ET) estimates from the Spinning Enhanced Visible and
                      Infrared Imager (SEVIRI) geostationary sensor onboard the
                      Meteosat Second Generation (MSG) satellites, along seven key
                      dimensions, i.e., diurnal cycle, daily, intra-annual,
                      inter-annual, ecosystem, climate zone, and products
                      intercomparison. In situ measurements were collected at 54
                      eddy covariance (EC) sites to evaluate the accuracy of
                      SEVIRI actual ET products (diurnal and daily SEVIRI-ETa) as
                      well as reference ET (daily SEVIRI-ET0) covering the period
                      from 2004 to 2018 across Europe. SEVIRI-ETa is produced by
                      the Tiled ECMWF Surface Scheme of Exchange processes at the
                      Land surface (TESSEL) model, while SEVIRI-ET0 is estimated
                      by a combination of a thermodynamically-based and an
                      atmospheric boundary layer model. This evaluation is further
                      separated according to the land cover heterogeneity of the
                      SEVIRI pixels across all 54 EC sites, using MODIS land cover
                      data. The Root Mean Squared Error (RMSE), along with the
                      Kling-Gupta efficiency (KGE) and their respective
                      decompositions, were employed to quantify the errors.For
                      diurnal SEVIRI-ETa estimates, we found that the KGE (RMSE
                      [mm hour−1]) varied between −1.6 (0.04) to 0.8 (0.14),
                      with a median value of 0.26 (0.07). Higher accuracy for
                      diurnal SEVIRI-ETa was obtained in the summer and during the
                      mid-day time. For daily SEVIRI-ETa, the KGE (RMSE [mm
                      day−1]) varied between −0.88 (0.43) to 0.93 (1.79), with
                      a median value of 0.6 (0.77) and for daily SEVIRI-ET0 the
                      KGE (RMSE [mm day−1]) varied between 0.51 (0.40) to 0.94
                      (1.50), with a median value of 0.77 (0.57). For daily
                      SEVIRI-ETa, intra-annual accuracy was low from January to
                      March, increased in the mid-year, and then began to decline
                      from November to December. Although accuracy remained
                      relatively stable during the middle of the year, it varied
                      considerably in the winter period. In the inter-annual
                      dimension, the mid-year positive KGE values and
                      distributions changed over time from 2004 to 2018. In
                      spatial dimensions, the highest accuracy was in peat and
                      grassland ecosystems, and the lowest in cropland ecosystem,
                      with similar patterns observed in the boreal snow fully
                      humid warm summer and warm temperate fully humid hot summer
                      climate zones. Regarding SEVIRI-ET0 results, similar to
                      SEVIRI-ETa, intra-annual accuracy was low in the first
                      quarter of the year and the last one but high in the
                      mid-year. In the inter-annual dimension, unlike SEVIRI-ETa,
                      almost an identical pattern was observed for the mid-year
                      positive KGE values, demonstrating only a slight change in
                      SEVIRI-ET0 accuracy during 2004–2018. However, the highest
                      accuracy was found in crop ecosystem, while the lowest was
                      in forest ecosystem, reflecting similar trends in the warm
                      temperate fully humid hot summer and warm temperate summer
                      dry hot summer climate zones. The observed range of median
                      RMSE changed between 0.4 and 1.5 mm day−1, also suggests a
                      reasonable accuracy for SEVIRI-ET estimates in all spatial
                      domains.Our results showed that the main trends in the
                      accuracies (median KGEs) of SEVIRI-ET (both ETa and ET0)
                      remained similar in separated homogeneous and heterogeneous
                      sites and were comparable to combined sites among the
                      dimensions. Through error decomposition, we discerned that
                      SEVIRI-ET estimates performed particularly well in
                      explaining inter-annual and spatial variabilities.
                      Furthermore, the intercomparison of ET products revealed
                      that SEVIRI satellite-derived ETa exhibited the strongest
                      correlation with in situ ET measurements across all
                      ecosystem types and climate zones, outperforming other
                      products (such as MODIS, PML, GLEAM, and BESS). The ET
                      estimates from other products exhibited lower standard
                      deviation errors and were in closer agreement with the in
                      situ measurements. This study provides the first
                      comprehensive evaluation of the accuracy of SEVIRI diurnal
                      and daily ET products across Europe, which may serve as a
                      stimulus for further optimized selection of these products
                      by potential users for various applications.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217) / ERA-PLANET - The European network for observing
                      our changing planet (689443) / Verbundvorhaben H2-Atlas:
                      Potentialatlas Grüner Wasserstoff in Afrika - Eine
                      technologische, ökologische und sozioökonomische
                      Machbarkeitsstudie (03EW0001A)},
      pid          = {G:(DE-HGF)POF4-2173 / G:(EU-Grant)689443 /
                      G:(BMBF)03EW0001A},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001134603000001},
      doi          = {10.1016/j.rse.2023.113875},
      url          = {https://juser.fz-juelich.de/record/1020234},
}