Basic and other measurements of radiation from the Baseline Surface Radiation Network (BSRN) Station Ny-Ålesund in the years 1992 to 2013, reference list of 253 datasets

At Ny-Ålesund (78.9° N), Svalbard, surface radiation measurements of up- and downward short- and longwave radiation are operated since August 1992 in the frame of the Baseline Surface Radiation Network (BSRN), complemented with surface and upper air meteorology since August 1993. The long-term observations are the base for a climatological presentation of the surface radiation data. Over the 21-year observation period, ongoing changes in the Arctic climate system are reflected. Particularly, the observations indicate a strong seasonality of surface warming and related changes in different radiation parameters. The annual mean temperature at Ny-Ålesund has risen by +1.3 ± 0.7 K per decade, with a maximum seasonal increase during the winter months of +3.1 ± 2.6 K per decade. At the same time, winter is also the season with the largest long-term changes in radiation, featuring an increase of +15.6 ± 11.6 W/m**2 per decade in the downward longwave radiation. Furthermore, changes in the reflected solar radiation during the months of snow melt indicate an earlier onset of the warm season by about 1 week compared to the beginning of the observations. The online available dataset of Ny-Ålesund surface radiation measurements provides a valuable data source for the validation of satellite instruments and climate models.

Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study

The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

Digital elevation model (DEM), surveyed stream network (SSN), mask and stream sampling points (SSP)

These data are provided to allow users for reproducibility of an open source tool entitled 'automated Accumulation Threshold computation and RIparian Corridor delineation (ATRIC)'

Snow height on sea ice and sea ice drift from autonomous measurements from buoy 2013S1, deployed during Antarctic Fast Ice Network 2013 (AFIN 2013)

Snow height was measured by the Snow Depth Buoy 2013S1, an autonomous platform, installed close to Neumayer III Base, Antarctic during Antarctic Fast Ice Network 2013 (AFIN 2013). The resulting time series describes the evolution of snow height as a function of place and time between 2013-02-11 and 2013-04-29 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The buoy was installed on the ice shelf. In addition to snow height, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Negative values of snow height occur if surface ablation continues into the sea ice. Thus, these measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). Records without any snow height may still be used for sea ice drift analyses. Note: This data set contains only relative changes in snow height, because no initial readings of absolute snow height are available.

Snow height on sea ice and sea ice drift from autonomous measurements from buoy 2014S24, deployed during Antarctic Fast Ice Network 2014 (AFIN 2014)

Snow height was measured by the Snow Depth Buoy 2014S24, an autonomous platform, installed close to Neumayer III Base, Antarctic during Antarctic Fast Ice Network 2014 (AFIN 2014). The resulting time series describes the evolution of snow depth as a function of place and time between 2014-03-07 and 2014-05-16 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The buoy was installed on the ice shelf. In addition to snow depth, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Negative values of snow depth occur if surface ablation continues into the sea ice. Thus, these measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). Records without any snow depth may still be used for sea ice drift analyses. Note: This data set contains only relative changes in snow depth, because no initial readings of absolute snow depth are available.

Basic measurements of radiation from the Baseline Surface Radiation Network (BSRN) in the years 1992 to 2012, reference list of 6378 datasets

In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm**-2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 Wm**-2 and 397 Wm**-2, respectively, this leaves 106 Wm**-2 of surface net radiation available for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85 Wm**-2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates.