Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga) in the North Atlantic for the period 1967-2008, compiled from statistics about ICCAT fishery region T10

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

Precipitation over sea: Validation against shipboard in-situ measurements

The satellite derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data) and ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis data sets have been validated against in-situ precipitation measurements from ship rain gauges and optical disdrometers over the open-ocean by applying a statistical analysis for binary forecasts. For this purpose collocated pairs of data were merged within a certain temporal and spatial threshold into single events, according to the satellites' overpass, the observation and the forecast times. HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially in the tropics and subtropics. Although precipitation rates are difficult to compare because along-track point measurements are collocated with areal estimates and the numbers of available data are limited, we find that HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide average precipitation rate is close to measurements. However, regionally averaged over latitudinal belts, there are deviations between the observed mean precipitation rates and ERA-Interim. The most obvious ERA-Interim feature is an overestimation of precipitation in the area of the intertropical convergence zone and the southern sub-tropics over the Atlantic Ocean. For a limited number of snow measurements by optical disdrometers it can be concluded that both HOAPS and ERA-Interim are suitable to detect the occurrence of solid precipitation.

High-resolution digital elevation model (DEM) of a thermokarst depression in Siberian ice-rich permafrost deposits

This data set provides a high-resolution digital elevation model (DEM) of a thermokarst depression (~7 km²) on ice-complex deposits in the Arctic Lena Delta, Siberia. The DEM based on a geodetic field survey and was used for quantitative land surface analyses and detailed description of the thermokarst depression morphology. Detailed morphometrical analyses, volume calculations, and solar radiation modeling were performed and statistically analyzed by Ulrich et al. (2010) to investigate the asymmetrical thermokarst depression development and directed lake migration previously proposed by Morgenstern et al. (2008). Furthermore, the high-resolution DEM in combination with satellite data allowed detailed analyses of spatial and temporal landscape changes due to thermokarst development (Günther, 2009).