Comprehensive Evaluation and Spatio-temporal Analysis of Surface Radiation and Energy Budget Datasets
Surface radiation and energy budget plays a central role in Earth systems. Spatio-termporal variations in the surface radiation and energy budget affect not only the thermal conditions on the planet, but also various other climate elements, such as atmospheric and oceanic circulations, the components of the hydrological cycle, glaciers, plant productivity, terrestrial carbon uptake, and so on.
Over the past several decades, technological advances in remote sensing, modern numerical weather modelling and assimilation have provided an unprecedented wealth of data sets relevant to surface radiation and energy budget over a global scale. However, the discrepancies among various datasets at this global level, particularly the substantial uncertainties in their quantification and mechanisms at various tempo-spatial scales, have not been explored thoroughly in previous studies; even the magnitude in the components of surface radiation and energy budget is currently debated. Therefore, further progress is required for comprehensive evaluation of these datasets in terms of improving retrieval accuracy, refining modelling approaches, and better knowledge of surface radiation and energy budget and its distribution within Earth systems.
Along these lines, this collection on “Comprehensive Evaluation and Spatio-temporal Analysis of Surface Radiation and Energy Budget Datasets” in the International Journal of Digital Earth aims to capture recent advancements in comparison and evaluation and spatio-temporal analysis of surface radiation and energy budget datasets regarding a variety of components, such as shortwave/longwave radiation, all-wave net radiation, albedo, latent/sensible heat flux, and surface temperature.
Edited by
Dr Bo Jiang(State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University)
Dr Xiaotong Zhang(State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University)
Dr Dongdong Wang(Department of Geographical Sciences, University of Maryland)