Beschreibung: Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017) Amelie Driemel, John Augustine, Klaus Behrens, Sergio Colle, Christopher Cox, Emilio Cuevas-Agulló, Fred M. Denn, Thierry Duprat, Masato Fukuda, Hannes Grobe, Martial Haeffelin, Nicole Hyett, Osamu Ijima, Ain Kallis, Wouter Knap, Vasilii Kustov, Charles N. Long, David Longenecker, Angelo Lupi, Marion Maturilli, Mohamed Mimouni, Lucky Ntsangwane, Hiroyuki Ogihara, Xabier Olano, Marc Olefs, Masao Omori, Lance Passamani, Enio Bueno Pereira, Holger Schmithüsen, Stefanie Schumacher, Rainer Sieger, Jonathan Tamlyn, Roland Vogt, Laurent Vuilleumier, Xiangao Xia, Atsumu Ohmura, and Gert König-Langlo Earth Syst. Sci. Data Discuss., https//doi.org/10.5194/essd-2018-8,2018 Manuscript under review for ESSD (discussion: open, 0 comments) The Baseline Surface Radiation Network (BSRN), collects and centrally archives high quality ground-based radiation measurements in 1-minute resolution. More than 10 300 months, i.e. 〉 850 years, of high radiation data in one-minute resolution from the years 1992 to 2017 are available. The network currently comprises 59 stations collectively representing all seven continents as well as island-based stations in the Pacific, Atlantic, Indian and Arctic Oceans.

Beschreibung: An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative Jean-François Legeais, Michaël Ablain, Lionel Zawadzki, Hao Zuo, Johnny A. Johannessen, Martin G. Scharffenberg, Luciana Fenoglio-Marc, M. Joana Fernandes, Ole Baltazar Andersen, Sergei Rudenko, Paolo Cipollini, Graham D. Quartly, Marcello Passaro, Anny Cazenave, and Jérôme Benveniste Earth Syst. Sci. Data, 10, 281-301, https://doi.org/10.5194/essd-10-281-2018, 2018 Sea level is one of the best indicators of climate change and has been listed as one of the essential climate variables. Sea level measurements have been provided by satellite altimetry for 25 years, and the Climate Change Initiative (CCI) program of the European Space Agency has given the opportunity to provide a long-term, homogeneous and accurate sea level record. It will help scientists to better understand climate change and its variability.

Beschreibung: Mediterranean Sea Hydrographic Atlas: towards optimal data analysis by including time-dependent statistical parameters Athanasia Iona, Athanasios Theodorou, Sylvain Watelet, Charles Troupin, and Jean-Marie Beckers Earth Syst. Sci. Data Discuss., https//doi.org/10.5194/essd-2018-9,2018 Manuscript under review for ESSD (discussion: open, 4 comments) We compute a new, high-resolution hydrographic Atlas for the Mediterranean Sea using the Interpolating Variational Analysis technique and the latest SeaDataNet aggregated data collection in an effort to contribute to the studies of the long term variability of the hydrological characteristics of the Mediterranean region and its climate change.

Beschreibung: Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015) Wei Li, Natasha MacBean, Philippe Ciais, Pierre Defourny, Céline Lamarche, Sophie Bontemps, Richard A. Houghton, and Shushi Peng Earth Syst. Sci. Data, 10, 219-234, https://doi.org/10.5194/essd-10-219-2018, 2018 We evaluated the land cover changes based on plant functional types (PFTs) derived from the newly released annual ESA land cover maps. We addressed the geographical distributions and temporal trends of the translated PFT maps and compared with other datasets commonly used by the land surface model community. Different choices of these datasets for the applications in land surface models are proposed depending on the research purposes.

Beschreibung: Estimating the thickness of unconsolidated coastal aquifers along the global coastline Daniel Zamrsky, Gualbert H. P. Oude Essink, and Marc F. P. Bierkens Earth Syst. Sci. Data Discuss., https//doi.org/10.5194/essd-2017-110,2018 Manuscript under review for ESSD (discussion: open, 0 comments) An increasing number of coastal areas worldwide is facing a threat of groundwater quality degradation by salt water intrusion. Groundwater flow models help to get a better idea about the volumes of fresh groundwater reserves in these areas. Our research provides information on aquifer thickness which is one of the most important parameters for such models. However, we found that geological complexity of coastal aquifer systems is an at least equally important factor for accurate predictions.

Beschreibung: seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day Cristian Lussana, Tuomo Saloranta, Thomas Skaugen, Jan Magnusson, Ole Einar Tveito, and Jess Andersen Earth Syst. Sci. Data, 10, 235-249, https://doi.org/10.5194/essd-10-235-2018, 2018 The observational gridded climate datasets are among the primary sources of information for climate analysis and monitoring. The seNorge2 high-resolution dataset of daily total precipitation (1957–2017) constitutes a valuable meteorological input for snow and hydrological simulations which are routinely conducted over Norway for research and to support operational applications for civil protection purposes. The dataset and the seNorge2 software are publicly available for download.

Beschreibung: Upscaled diurnal cycles of land-atmosphere fluxes: a new global half-hourly data product Paul Bodesheim, Martin Jung, Fabian Gans, Miguel D. Mahecha, and Markus Reichstein Earth Syst. Sci. Data Discuss., https//doi.org/10.5194/essd-2017-130,2018 Manuscript under review for ESSD (discussion: open, 1 comment) Interactions between the biosphere and the atmosphere can be well characterized by fluxes between the two. In particular, carbon and energy fluxes play a major role for understanding biogeochemical processes on ecosystem level or global scale. However, the fluxes can only be measured at individual sites by eddy covariance towers and an upscaling of these local observations is required to analyze global patterns. Previous work focused on upscaling monthly, eight-day, or daily average values and global maps for each flux have been provided accordingly. In this paper, we raise the upscaling of carbon and energy fluxes between land and atmosphere to the next level by increasing the temporal resolution to subdaily scales. We provide continuous half-hourly fluxes for the period from 2001 to 2014 at 0.5◦ spatial resolution, which allows for analyzing diurnal cycles globally. The dataset contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). We propose two prediction approaches for the diurnal cycles based on large-scale regression models and compare them in extensive cross-validation experiments using different sets of predictor variables. We analyze the results for a set of FLUXNET tower sites showing the suitability of our approaches for this upscaling task. Finally, we have selected one approach to calculate the global half- hourly data products based on predictor variables from remote sensing and meteorology at daily resolution as well as half-hourly potential radiation. In addition, we provide a derived product that only contains monthly average diurnal cycles, which is a lightweight version in terms of data storage that still enables to study the important characteristics of diurnal courses globally. We recommend to primarily use these monthly average diurnal cycles, because they are less affected by the impacts of day-to-day variation, observation noise, and short- term fluctuations on subdaily scales compared to the plain half-hourly flux products. The global half-hourly data products are available at https://doi.org/10.17871/BACI.224 .

Beschreibung: A 20-year record (1998–2017) of permafrost, active layer and meteorological conditions at a high Arctic permafrost research site (Bayelva, Spitsbergen) Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann Earth Syst. Sci. Data, 10, 355-390, https://doi.org/10.5194/essd-10-355-2018, 2018 A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.

Beschreibung: Spatial datasets of radionuclide contamination in the Ukrainian Chernobyl Exclusion Zone Valery Kashparov, Sviatoslav Levchuk, Marina Zhurba, Valentyn Protsak, Yuri Khomutinin, Nicholas A. Beresford, and Jacqueline S. Chaplow Earth Syst. Sci. Data, 10, 339-353, https://doi.org/10.5194/essd-10-339-2018, 2018 Spatial datasets of radionuclide contamination in the Ukrainian Chernobyl Exclusion Zone describe data from analysis of samples collected by the Ukrainian Institute of Agricultural Radiology after the Chernobyl nuclear accident between May 1986 and 2014 at sites inside the Chernobyl Exclusion Zone and other areas of interest. The data and supporting documentation are freely available from the Environmental Information Data Centre: https://doi.org/10.5285/782ec845-2135-4698-8881-b38823e533bf .

Beschreibung: Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5 Angeline G. Pendergrass, Andrew Conley, and Francis M. Vitt Earth Syst. Sci. Data, 10, 317-324, https://doi.org/10.5194/essd-10-317-2018, 2018 We document and validate radiative kernels for the surface and top-of-atmosphere calculated with NCAR's CESM1 climate model. A radiative kernel is the change in radiation in response to a small change in a property of the atmosphere or surface, essentially a partial derivative. They are used to quantify temperature, water vapor, surface albedo, and cloud feedbacks. We made these kernels because few are available for the surface. We also validate the kernels against the expected model responses.