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.

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.

Abstract. Small-scale surface heterogeneities can influence land-atmosphere fluxes and therefore carbon, water and energy budgets on a larger scale. This effect is of particular relevance for high-latitude ecosystems, because of the great amount of carbon stored in their soils. We introduce a novel micro-topographic model, the Hummock-Hollow (HH) model, which explicitly represents small-scale surface elevation changes. By computing the water table at the small scale, and by coupling the model with a process-based model for soil methane processes, we are able to model the effects of micro-topography on hydrology and methane emissions in a typical boreal peatland. In order to assess the effect of micro-topography on water the balance and methane emissions of the peatland we compare two versions of the model, one with a representation of micro-topography and a classical single-bucket model version, and show that the temporal variability in the model version with micro-topography performs better if compared with local data. Accounting for micro-topography almost triples the cumulative methane flux over the simulated time-slice. We found that the singlebucket model underestimates methane emissions because of its poor performance in representing hydrological dynamics. The HH model with micro-topography captures the spatial dynamics of water and methane fluxes, being able to identify the hotspots for methane emissions. The model also identifies a critical scale (0.01 km 2 ) which marks the minimal resolution for the explicit representation of micro-topography in larger-scale models.

Abstract. Subgrid processes occur in various ecosystems and landscapes but, because of their small scale, they are not represented or poorly parameterized in climate models. These local heterogeneities are often important or even fundamental for energy and carbon balances. This is especially true for northern peatlands and in particular for the polygonal tundra, where methane emissions are strongly influenced by spatial soil heterogeneities. We present a stochastic model for the surface topography of polygonal tundra using PoissonVoronoi diagrams and we compare the results with available recent field studies. We analyze seasonal dynamics of water table variations and the landscape response under different scenarios of precipitation income. We upscale methane fluxes by using a simple idealized model for methane emission. Hydraulic interconnectivities and large-scale drainage may also be investigated through percolation properties and thresholds in the Voronoi graph. The model captures the main statistical characteristics of the landscape topography, such as polygon area and surface properties as well as the water balance. This approach enables us to statistically relate large-scale properties of the system to the main small-scale processes within the single polygons.