Abstract. Most of the world's permafrost is located in the Arctic, where its frozen organic carbon content makes it a potentially important influence on the global climate system. The Arctic climate appears to be changing more rapidly than the lower latitudes, but observational data density in the region is low. Permafrost thaw and carbon release into the atmosphere, as well as snow cover changes, are positive feedback mechanisms that have the potential for climate warming. It is therefore particularly important to understand the links between the energy balance, which can vary rapidly over hourly to annual timescales, and permafrost conditions, which changes slowly on decadal to centennial timescales. This requires long-term observational data such as that available from the Samoylov research site in northern Siberia, where meteorological parameters, energy balance, and subsurface observations have been recorded since 1998. This paper presents the temporal data set produced between 2002 and 2017, explaining the instrumentation, calibration, processing, and data quality control. Furthermore, we present a merged data set of the parameters, which were measured from 1998 onwards. Additional data include a high-resolution digital terrain model (DTM) obtained from terrestrial lidar laser scanning. Since the data provide observations of temporally variable parameters that influence energy fluxes between permafrost, active-layer soils, and the atmosphere (such as snow depth and soil moisture content), they are suitable for calibrating and quantifying the dynamics of permafrost as a component in earth system models. The data also include soil properties beneath different microtopographic features (a polygon centre, a rim, a slope, and a trough), yielding much-needed information on landscape heterogeneity for use in land surface modelling. For the record from 1998 to 2017, the average mean annual air temperature was −12.3 ∘C, with mean monthly temperature of the warmest month (July) recorded as 9.5 ∘C and for the coldest month (February) −32.7 ∘C. The average annual rainfall was 169 mm. The depth of zero annual amplitude is at 20.75 m. At this depth, the temperature has increased from −9.1 ∘C in 2006 to −7.7 ∘C in 2017. The presented data are freely available through the PANGAEA (https://doi.org/10.1594/PANGAEA.891142) and Zenodo (https://zenodo.org/record/2223709, last access: 6 February 2019) websites.

Abstract. Most permafrost is located in the Arctic, where frozen organic carbon makes it an important component of the global climate system. Despite the fact that the Arctic climate changes more rapidly than the rest of the globe, observational data density in the region is low. Permafrost thaw and carbon release to the atmosphere are a positive feedback mechanism that can exacerbate global warming. This positive feedback functions via changing land–atmosphere energy and mass exchanges. There is thus a great need to understand links between the energy balance, which can vary rapidly over hourly to annual timescales, and permafrost, which changes slowly over long time periods. This understanding thus mandates long-term observational data sets. Such a data set is available from the Bayelva site at Ny-Ålesund, Svalbard, where meteorology, energy balance components and subsurface observations have been made for the last 20 years. Additional data include a high-resolution digital elevation model (DEM) that can be used together with the snow physical information for snowpack modeling and a panchromatic image. This paper presents the data set produced so far, explains instrumentation, calibration, processing and data quality control, as well as the sources for various resulting data sets. The resulting data set is unique in the Arctic and serves as a baseline for future studies. The mean permafrost temperature is −2.8 °C, with a zero-amplitude depth at 5.5 m (2009–2017). Since the data provide observations of temporally variable parameters that mitigate energy fluxes between permafrost and atmosphere, such as snow depth and soil moisture content, they are suitable for use in integrating, calibrating and testing permafrost as a component in earth system models.The presented data are available in the Supplement for this paper (time series) and through the PANGAEA and Zenodo data portals: time series (https://doi.org/10.1594/PANGAEA.880120, https://zenodo.org/record/1139714) and HRSC-AX data products (https://doi.org/10.1594/PANGAEA.884730, https://zenodo.org/record/1145373).

The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing in Central Siberia. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS-derived NASA products (250-1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. This area experienced both large scale wetting and large scale drying during the study period probably related to the nature of the substrate conditions. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year, but ranged up to 0.49 °C/year during September-October. This is about ten times higher than the global warming rate of 0.0116 °C/year (2000 to 2014) estimated by Karl et al. (2015). The spring warming trend is very likely to be due to changes in the area covered by snow: 80% of the area showed reduction in snow coverage in spring. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the proportion of the land surface that is covered by water (i.e., to wetting and drying). The study area (315,000 km 2 ) covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. The area has a high population density compared to other permafrost regions and can therefore be important for the study of rapid land surface changes and the resulting socio-economic effects. Landscape characteristics (Fedorov et al., 1989) land surface temperature

Abstract. Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1.0 × 10 4 m 2 , have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of Published by Copernicus Publications. S. Muster et al.: A circum-Arctic PeRL1.4 × 10 6 km 2 across the Arctic, about 17 % of the Arctic lowland (< 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1.0 × 10 6 m 2 down to 1.0 × 10 2 m 2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1.0 × 10 to 9.4 × 10 1 km −2 . Ponds are the dominant waterbody type by number in all landscapes representing 45-99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349.

Abstract. Most of the world's permafrost is located in the Arctic, where its frozen organic carbon con-tent makes it a potentially important influence on the global climate system. The Arctic climate appears to be changing more rapidly than the lower latitudes, but observational data density in the region is low. Permafrost thaw and carbon release into the atmosphere is a positive feed-back mechanism that has the potential for climate warming. It is therefore particularly im-portant to understand the links between the energy balance, which can vary rapidly over hour-ly to annual time scales, and permafrost condition, which changes slowly on decadal to cen-tennial timescales. This requires long-term observational data such as that available from the Samoylov research site in northern Siberia, where meteorological parameters, energy balance, and subsurface observations have been recorded since 1998. This paper presents the temporal data set produced between 2002 and 2017, explaining the instrumentation, calibration, pro-cessing and data quality control. Additional data include a high-resolution digital terrain mod-el (DTM) obtained from terrestrial LiDAR laser scanning. Since the data provide observations of temporally variable parameters that influence energy fluxes between permafrost, active lay-er soils, and the atmosphere (such as snow depth and soil moisture content), they are suitable for calibrating and quantifying the dynamics of permafrost as a component in earth system models. The data also include soil properties beneath different microtopographic features (a polygon center, a rim, a slope, and a trough), yielding much-needed information on landscape heterogeneity for use in land surface modeling. For the record from 1998 to 2017, the average mean annual air temperature was − 12.3 °C, with mean monthly temperature of the warmest month (July) recorded as 9.5 °C and for the coldest month (February) − 32.7 °C. The average annual rainfall was 169 mm. The depth of zero annual amplitude niveau is at 20.8 m, and has warmed from − 9.1 °C in 2006 to − 7.7 °C in 2017. The presented data are available in the supplementary material of this paper and through the PANGAEA website (https://doi.org/10.1594/PANGAEA.891142).

Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km 2 (100 m 2 ) to 1 km 2 . We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R 2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.

Most permafrost is located in the Arctic, where frozen organic carbon makes it an important component of the global climate system. Despite the fact that the Arctic climate changes more rapidly than the rest of the globe, observational data density in the region is low. Permafrost thaw and carbon release to the atmosphere are a positive feedback mechanism that can exac-35 erbate climate warming. This positive feedback functions via changing land-atmosphere energy and mass exchanges. There is thus a great need to understand links between the energy balance, which can vary rapidly over hourly to annual time scales, and permafrost, which changes slowly over long time periods. This understanding thus mandates long-term observational data sets. 40Such a data set is available from the Bayelva Site at Ny-Ålesund, Svalbard, where meteorology, energy balance components and subsurface observations have been made for the last 20 years. Additional data include a high resolution digital elevation model and a panchromatic image. This paper presents the data set produced so far, explains instrumentation, calibration, processing and data quality control, as well as the sources for various resulting data sets. The 45 resulting data set is unique in the Arctic and serves a baseline for future studies. Since the data provide observations of temporally variable parameters that mitigate energy fluxes between permafrost and atmosphere, such as snow depth and soil moisture content, they are suitable for use in integrating, calibrating and testing permafrost as a component in Earth System Models. The data set also includes a high resolution digital elevation model that can be used can blanket the permafrost surface for many months of the year and has an important effect on the thermal regime of permafrost (Langer et al., 2013;López-Moreno et al., 2016). The soil's water content determines not only its hydrologic and thermal properties, but also the amount of latent heat that is either required for the seasonal thaw in spring, or produced during fall. In view of these dependencies, the resulting datasets (including snow cover and the thermal state 75 of the soil and permafrost), ideally at the same resolution as any meteorological input data, will be of great value for evaluating permafrost models (or land surface models intended for Earth Syst. Sci. Data Discuss., https://doi

Hydraulic roughness, which quantifies the resistance to flow by objects protruding into the water column (Chow, 1959), is a fundamental property in hydraulics. Due to its influence on water levels, flow structure and the associated sediment transport, understanding roughness is crucial to comprehend river dynamics. Quantification of hydraulic roughness is challenging, since it is not directly measurable in the field.Hydraulic roughness at the bed of a main channel with abundant bedforms, consists of grain-friction drag and form drag. In lowland rivers, bedforms (bars, dunes, ripples) are typically the major cause of form roughness (Gates & Al-Zahrani, 1996;Julien et al., 2002). Form drag induced by dunes is estimated with predictors based on dune height and length (