Comprehensive Assessment of Global Surface Net Radiation Products and Uncertainty Analysis

Abstract

Earth surface net radiation (Rn) characterizes the surface radiation budget and plays a critical role in ecological, biogeochemical, and hydrological processes. The Rn products from remote sensing and reanalysis have not been validated comprehensively. In this study, four Rn products (Clouds and the Earth's Radiant Energy System [CERES], ERA‐Interim, Modern‐Era Retrospective analysis for Research and Applications version 2, and Japanese 55‐year Reanalysis) were validated using global ground measurements on monthly (255 sites) and annual (172 sites) timescales. These products have similar accuracies, with average root‐mean‐square error (RMSE) ranges of 5.35 W m−2 (monthly) and 2.30 W m−2 (annually). However, varying accuracies and systemic biases exist across different climatic zones. The annual land Rn intercomparison illustrates that large uncertainty exists over polar regions and deserts. A significantly negative annual anomaly in the CERES product for the 2001–2008 period is identified when examining annual Rn anomalies over the global land surface. Detailed uncertainty analysis indicates that the global CERES Rn anomaly is mainly due to different versions of input data such as aerosol optical thickness and atmospheric profiles (in 2006 and 2008) and cloud properties (in 2002). This work demonstrates that temporal analysis provides powerful quality control for global time series satellite products when the validation using ground measurements fails to capture potential issues.

Determining Factors of Monthly to Decadal Variability in Surface Solar Radiation in China: Evidences From Current Reanalyses

“…Our previous study also suggests that CERES EBAF R s retrievals have 9.9 W/m 2 mean absolute biases comparing with BSRN sites data (Feng & Wang, ). Existing study suggest that changing the MODIS AOD from Collections 4 to 5 resulted in the discontinuity in the CERES EBAF global land R s in 2006 (Jia et al, ). Moreover, satellite AOD retrievals are only available under cloud‐free conditions, which cannot fully represent AOD trend in the all‐weather situation.…”

Validation of Earth Observation Time-Series: A Review for Large-Area and Temporally Dense Land Surface Products

“…The majority of reviewed studies (61) facilitated more than one validation method. Hereby, a variety of studies showed, in particular, the combination of an intercomparison of products with a comparison to reference data [9,21,35,48,53,54,57,59,84,97,[120][121][122][123][124]129,133,135,139,[141][142][143][144][145]. This dual approach can provide an indication of general remote sensing performance for a particular research area or, on the other hand, illustrate improvements of novel methods in relation to existing products [35,71,136].…”

“…Along with similar remote sensing products for this type of validation, products in the form of model outcomes featuring the same target variable are also considered [120][121][122]. For instance, Albergel et al [123] intercompared a fused radar soil moisture product with two reanalysis datasets.…”

Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil

“…Overall, MERRA-2 provides more self-consistent meteorological data than its previous versions at large scale [68,99]. Although some validations of the recent MERRA-2 surface and atmospheric reanalysis have been published [100,101], there is a lack of comprehensive assessment at regional scales.…”