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Carola Dahlke, Alexander Loew, and Christian Reick

Abstract

The fraction of absorbed photosynthetically active radiation (fAPAR) is an essential diagnostic variable to investigate the temporal and spatial dynamics of the terrestrial biosphere. The present study provides a new method to assess global vegetation greening phase dynamics, derived from fAPAR time series from four different remote sensing products. A robust algorithm is developed to detect intra-annual greening phase patterns and derive seasonality patterns of vegetation dynamics at the global scale. The comparison of four independent remote sensing datasets shows significantly consistent global spatiotemporal patterns at the 95% confidence level. Regions where the remote sensing datasets show consistent results, as well as regions where at least one of the used remote sensing datasets deviates, can be identified. The derived global greening phase dataset and analysis method provides a solid framework for the evaluation of global vegetation models.

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Alexander Loew, Axel Andersson, Jörg Trentmann, and Marc Schröder

Abstract

Earth system models are indispensable tools in climate studies. The Coupled Model Intercomparison Project (CMIP) is a coordinated effort of the Earth system modeling community to intercompare existing models. An accurate simulation of surface solar radiation fluxes is of major importance for the accuracy of simulations of the near-surface climate in Earth system models. The present study provides a quantitative assessment of the accuracy and multidecadal changes of surface solar radiation fluxes for model results from two phases of CMIP. The entire archives of phase 5 of CMIP (CMIP5) and its predecessor phase 3 (CMIP3) are analyzed for present-day climate conditions. A relative model ranking is provided, and its uncertainty is quantified using different global observational records. It is shown that the choice of an observational dataset can have a major influence on relative model ranking between CMIP models. However the multidecadal variability of surface solar radiation fluxes, also known as global “dimming” or “brightening,” is largely underestimated by the CMIP models.

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Paul A. Kucera, Elizabeth E. Ebert, F. Joseph Turk, Vincenzo Levizzani, Dalia Kirschbaum, Francisco J. Tapiador, Alexander Loew, and M. Borsche

Advances to space-based observing systems and data processing techniques have made precipitation datasets quickly and easily available via various data portals and widely used in Earth sciences. The increasingly lengthy time span of space-based precipitation data records has enabled cross-discipline investigations and applications that would otherwise not be possible, revealing discoveries related to hydrological and land processes, climate, atmospheric composition, and ocean freshwater budget and proving a vital element in addressing societal issues. The purpose of this article is to demonstrate how the availability and continuity of precipitation data records from recent and upcoming space missions is transforming the ways that scientific and societal issues are addressed, in ways that would not be otherwise possible.

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Kenneth R. Knapp, Steve Ansari, Caroline L. Bain, Mark A. Bourassa, Michael J. Dickinson, Chris Funk, Chip N. Helms, Christopher C. Hennon, Christopher D. Holmes, George J. Huffman, James P. Kossin, Hai-Tien Lee, Alexander Loew, and Gudrun Magnusdottir

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA's National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

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