Maps (pdf) and raster images (tif) of predicted rural land cover suitability under current (2010) conditions and future climate scenarios

This study projects land cover probabilities under climate change for corn (maize), soybeans, spring and winter wheat, winter wheat-soybean double cropping, cotton, grassland and forest across 16 central U.S. states at a high spatial resolution, while also taking into account the influence of soil characteristics and topography. The scenarios span three oceanic-atmospheric global circulation models, three Representative Concentration Pathways, and three time periods (2040, 2070, 2100). As climate change intensifies, the suitable area for all six crops display large northward shifts. Total suitable area for spring wheat, followed by corn and soybeans, diminish. Suitable area for winter wheat and for winter wheat-soybean double-cropping expand northward, while cotton suitability migrates to new, more northerly, locations. Suitability for forest intensifies in the south while yielding to crops in the north; grassland intensifies in the western Great Plains as crop suitability diminishes. To maintain current broad geographic patterns of land use, large changes in the thermal response of crops such as corn would be required. A transition from corn-soybean to winter wheat-soybean doubling cropping is an alternative adaptation.

3D models created from ROV videos and their corresponding subtransect dimensions

Underwater video transects have become a common tool for quantitative analysis of the seafloor. However a major difficulty remains in the accurate determination of the area surveyed as underwater navigation can be unreliable and image scaling does not always compensate for distortions due to perspective and topography. Depending on the camera set-up and available instruments, different methods of surface measurement are applied, which make it difficult to compare data obtained by different vehicles. 3-D modelling of the seafloor based on 2-D video data and a reference scale can be used to compute subtransect dimensions. Focussing on the length of the subtransect, the data obtained from 3-D models created with the software PhotoModeler Scanner are compared with those determined from underwater acoustic positioning (ultra short baseline, USBL) and bottom tracking (Doppler velocity log, DVL). 3-D model building and scaling was successfully conducted on all three tested set-ups and the distortion of the reference scales due to substrate roughness was identified as the main source of imprecision. Acoustic positioning was generally inaccurate and bottom tracking unreliable on rough terrain. Subtransect lengths assessed with PhotoModeler were on average 20% longer than those derived from acoustic positioning due to the higher spatial resolution and the inclusion of slope. On a high relief wall bottom tracking and 3-D modelling yielded similar results. At present, 3-D modelling is the most powerful, albeit the most time-consuming, method for accurate determination of video subtransect dimensions.

Age models, iron intensity, magnetic susceptibility records and dry bulk density of sediment cores from around the Canary Islands

A set of 43 sediment cores from around the Canary Islands is used to characterise this region, which intersects meridional climatic regimes and zonal productivity gradients in a high spatial resolution. Using rapid and nondestructive core logging techniques we carried out Fe intensity and magnetic susceptibility (MS) measurements and created a stack on the basis of five stratigraphic reference cores, for which a stratigraphic age model was available from d18O and 14C analyses on planktonic foraminifera. By correlation of the stack with the Fe and MS records of the other cores, we were able to develop age depth models at all investigated sites of the region. We present the bulk sediment accumulation rates (AR) of the Canary Islands region as an indicator of shifts in the upwelling-influenced areas for the Holocene (0-12 ky), the deglaciation (12-18 ky) and the last glacial (18-40 ky). General observations are an enhanced productivity during glacial times with highest values during the deglaciation. The main differences between the analysed time intervals we interpret as result of the sea-level effects, changes in the extent of high productivity areas, and current intensity.

Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga) in the North Atlantic for the period 1956-2010, compiled from the International Commission for the Conservation of Atlantic Tunas

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.

Modeled monthly local topographic lapse rates, Pacific Northwest, USA

An emerging approach to downscaling the projections from General Circulation Models (GCMs) to scales relevant for basin hydrology is to use output of GCMs to force higher-resolution Regional Climate Models (RCMs). With spatial resolution often in the tens of kilometers, however, even RCM output will likely fail to resolve local topography that may be climatically significant in high-relief basins. Here we develop and apply an approach for downscaling RCM output using local topographic lapse rates (empirically-estimated spatially and seasonally variable changes in climate variables with elevation). We calculate monthly local topographic lapse rates from the 800-m Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset, which is based on regressions of observed climate against topographic variables. We then use these lapse rates to elevationally correct two sources of regional climate-model output: (1) the North American Regional Reanalysis (NARR), a retrospective dataset produced from a regional forecasting model constrained by observations, and (2) a range of baseline climate scenarios from the North American Regional Climate Change Assessment Program (NARCCAP), which is produced by a series of RCMs driven by GCMs. By running a calibrated and validated hydrologic model, the Soil and Water Assessment Tool (SWAT), using observed station data and elevationally-adjusted NARR and NARCCAP output, we are able to estimate the sensitivity of hydrologic modeling to the source of the input climate data. Topographic correction of regional climate-model data is a promising method for modeling the hydrology of mountainous basins for which no weather station datasets are available or for simulating hydrology under past or future climates.

Standardized geo-referenced catch, fishing effort and length-frequency data for the Indian Ocean Bigeye Tuna, Thunnus obesus (1952-2014)

Geo-referenced catch and fishing effort data of the bigeye tuna fisheries in the Indian Ocean over 1952-2014 were analysed and standardized to facilitate population dynamics modelling studies. During this sixty-two years historical period of exploitation, many changes occurred both in the fishing techniques and the monitoring of activity. This study includes a series of processing steps used for standardization of spatial resolution, conversion and standardization of catch and effort units, raising of geo-referenced catch into nominal catch level, screening and correction of outliers, and detection of major catchability changes over long time series of fishing data, i.e., the Japanese longline fleet operating in the tropical Indian Ocean. A total of thirty fisheries were finally determined from longline, purse seine and other-gears data sets, from which 10 longline and four purse seine fisheries represented 96% of the whole historical catch. The geo-referenced records consists of catch, fishing effort and associated length frequency samples of all fisheries.

Inventory of thermo-erosional valleys and streams in three ice-rich permafrost lowlands adjacent to the Laptev Sea, with links to maps in ArcGIS format

This dataset provides an inventory of thermo-erosional landforms and streams in three lowland areas underlain by ice-rich permafrost of the Yedoma-type Ice Complex at the Siberian Laptev Sea coast. It consists of two shapefiles per study region: one shapefile for the digitized thermo-erosional landforms and streams, one for the study area extent. Thermo-erosional landforms were manually digitized from topographic maps and satellite data as line features and subsequently analyzed in a Geographic Information System (GIS) using ArcGIS 10.0. The mapping included in particular thermo-erosional gullies and valleys as well as streams and rivers, since development of all of these features potentially involved thermo-erosional processes. For the Cape Mamontov Klyk site, data from Grosse et al. [2006], which had been digitized from 1:100000 topographic map sheets, were clipped to the Ice Complex extent of Cape Mamontov Klyk, which excludes the hill range in the southwest with outcropping bedrock and rocky slope debris, coastal barrens, and a large sandy floodplain area in the southeast. The mapped features (streams, intermittent streams) were then visually compared with panchromatic Landsat-7 ETM+ satellite data (4 August 2000, 15 m spatial resolution) and panchromatic Hexagon data (14 July 1975, 10 m spatial resolution). Smaller valleys and gullies not captured in the maps were subsequently digitized from the satellite data. The criterion for the mapping of linear features as thermo-erosional valleys and gullies was their clear incision into the surface with visible slopes. Thermo-erosional features of the Lena Delta site were mapped on the basis of a Landsat-7 ETM+ image mosaic (2000 and 2001, 30 m ground resolution) [Schneider et al., 2009] and a Hexagon satellite image mosaic (1975, 10 m ground resolution) [G. Grosse, unpublished data] of the Lena River Delta within the extent of the Lena Delta Ice Complex [Morgenstern et al., 2011]. For the Buor Khaya Peninsula, data from Arcos [2012], which had been digitized based on RapidEye satellite data (8 August 2010, 6.5 m ground resolution), were completed for smaller thermo-erosional features using the same RapidEye scene as a mapping basis. The spatial resolution, acquisition date, time of the day, and viewing geometry of the satellite data used may have influenced the identification of thermo-erosional landforms in the images. For Cape Mamontov Klyk and the Lena Delta, thermo-erosional features were digitized using both Hexagon and Landsat data; Hexagon provided higher resolution and Landsat provided the modern extent of features. Allowance of up to decameters was made for the lateral expansion of features between Hexagon and Landsat acquisitions (between 1975 and 2000).

The Lena River Delta - Land cover classification of tundra environments based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

GPS linked photos of benthic cover transect surveys in Heron Reef

Underwater photo-transect surveys were conducted on September 23-27, 2007 at different sections of the reef flat, reef crest and reef slope in Heron Reef. This survey was done by swimming along pre-defined transect sites and taking a picture of the bottom substrate parallel to the bottom at constant vertical distance (30cm) every two to three metres. A total of 3,586 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of transect surveys. Approximation of the coordinates for each benthic photo was based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software. Coordinates of each photo were interpolated by finding the the gps coordinates that were logged at a set time before and after the photo was captured. The output of this process was an ArcMap point shapefile, a Google Earth KML file and a thumbnail of each benthic photo taken. The data in the ArcMap shapefile and in the Google Earth KML file consisted of the approximated coordinate of each benthic photo taken during the survey. Using the GPS Photo Link extension within the ArcMap environment, opening the ArcMap shapefile will enable thumbnail to be displayed on the associated benthic cover photo whenever hovering with the mouse over a point on the transect. By downloading the GPSPhotoLink software from the www.geospatialexperts.com, and installing it as a trial version the ArcMap exstension will be installed in the ArcMap environment.

LPJ-LMfire simulations for Europe for the Last Glacial Maximum and preindustrial control, link to netCDF files

This data sets contains LPJ-LMfire dynamic global vegetation model output covering Europe and the Mediterranean for the Last Glacial Maximum (LGM; 21 ka) and for a preindustrial control simulation (20th century detrended climate). The netCDF data files are time averages of the final 30 years of the model simulation. Each netCDF file contains four or five variables: fractional cover of 9 plant functional types (PFTs; cover), total fractional coverage of trees (treecover), population density of hunter-gatherers (foragerPD; only for the "people" simulations), fraction of the gridcell burned on 30-year average (burnedf), and vegetation net primary productivity (NPP). The model spatial resolution is 0.5-degrees For the LGM simulations, LPJ-LMfire was driven by the PMIP3 suite of eight GCMs for which LGM climate simulations were available. Also provided in this archive is the result of an LPJ-LMfire run that was forced by the average climate of all GCMs (the "GCM-mean" files), and the average of each of the individual LPJ-LMfire runs over the eight LGM scenarios individually (the "LPJ-mean" files). The model simulations are provided that include the influence of human presence on the landscape (the "people" files), and in a "world without humans" scenario (the "natural" files). Finally this archive contains the preindustrial reference simulation with and without human influence ("PI_reference_people" and "PI_reference_nat", respectively). There are therefore 22 netCDF files in this archive: 8 each of LGM simulations with and without people (total 16) and the "GCM mean" simulation (2 files) and the "LPJ mean" aggregate (2 files), and finally the two preindustrial "control" simulations ("PI"), with and without humans (2 files). In addition to the LPJ-LMfire model output (netCDF files), this archive also contains a table of arboreal pollen percent calculated from pollen samples dated to the LGM at sites throughout (lgmAP.txt), and a table containing the location of archaeological sites dated to the LGM (LGM_archaeological_site_locations.txt).

Lithofacies distribution in the western Bay of Plenty, New Zealand

Sediment dynamics on a storm-dominated shelf (western Bay of Plenty, New Zealand) were mapped and analyzed using the newly developed multi-sensor benthic profiler MARUM NERIDIS III. An area of 60 km × 7 km between 2 and 35 m water depth was surveyed with this bottom-towed sled equipped with a high-resolution camera for continuous close-up seafloor photography and a CTD with connected turbidity sensor. Here we introduce our approach of using this multi-parameter dataset combined with sidescan sonography and sedimentological analyses to create detailed lithofacies and bedform distribution maps and to derive regional sediment transport patterns. For the assessment of sediment distribution, photographs were classified and their spatial distribution mapped out according to associated acoustic backscatter from a sidescan sonar. This provisional map was used to choose target locations for surficial sediment sampling and subsequent laboratory analysis of grain size distribution and mineralogical composition. Finally, photographic, granulometric and mineralogical facies were combined into a unified lithofacies map and corresponding stratigraphic model. Eight distinct types of lithofacies with seawards increasing grain size were discriminated and interpreted as reworked relict deposits overlain by post-transgressional fluvial sediments. The dominant transport processes in different water depths were identified based on type and orientation of bedforms, as well as bottom water turbidity and lithofacies distribution. Observed bedforms include subaquatic dunes, coarse sand ribbons and sorted bedforms of varying dimensions, which were interpreted as being initially formed by erosion. Under fair weather conditions, sediment is transported from the northwest towards the southeast by littoral drift. During storm events, a current from the southeast to the northweast is induced which is transporting sediment along the shore in up to 35 m water depth. Shorewards oriented cross-shore transport is taking place in up to 60 m water depth and is likewise initiated by storm events. Our study demonstrates how benthic photographic profiling delivers comprehensive compositional, structural and environmental information, which compares well with results obtained by traditional probing methods, but offers much higher spatial resolution while covering larger areas. Multi-sensor benthic profiling enhances the interpretability of acoustic seafloor mapping techniques and is a rapid and economic approach to seabed and habitat mapping especially in muddy to sandy facies.

Downwelling spectral irradiance as measured in different depths, remote sensing reflectance and phytoplankton pigment concentration during POLARSTERN cruises ANT-XXIV/1, ANT-XXIV/4, ANT-XXVI/4 and Maria S. Merian cruise MSM18/3

The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

Circumpolar dataset of Soil Organic Carbon north of treeline derived from ENVISAT ASAR GM, link to GeoTIFF

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

Melt climatology estimates for small to giant Antarctic icebergs, links to NetCDF files

We present four melt climatology estimates based on a simulation of Antarctic iceberg drift and melting that includes small, medium-sized, and giant tabular icebergs with a realistic size distribution. Drift and meltdown is simulated using vertical profiles of ocean currents, temperature, and salinity, which goes beyond the present standard in iceberg modeling. The climatology estimates based on simulations of small (SMA), 'small-to-medium'-sized (MED12 & MED123), and small-to-giant icebergs (ALL) exhibit differential characteristics: successive inclusion of larger icebergs leads to a reduced seasonality of iceberg melt and a shift of the mass input to the area north of 58°S, while less melt water is released into the coastal areas. This highlights the necessity to account for larger and giant icebergs in order to obtain accurate melt climatologies. The four monthly melt climatologies [mm/day] are available as netCDF files with 1°x1° spatial resolution and can be used, e.g., for sensitivity studies with uncoupled sea ice-ocean models, or as spatio-temporal templates for the redistribution of land ice from the Antarctic ice sheet over the Southern Ocean in climate models.

ROCADA: Romanian daily gridded climatic dataset (1961-2013) V1.0

Daily records of nine meteorological variables covering the interval 1961-2013 were used in order to create a state-of-the-art homogenized climatic dataset over Romania at a spatial resolution of 0.1°. All meteorological stations with full data records, as well as stations with up to 30 % missing data, were used for the following variables: air pressure (150 stations); minimum, maximum, and average air temperature (150 stations); soil temperature (127 stations); precipitation (188 stations); sunshine hours (135 stations); cloud cover (104 stations); relative humidity (150 stations). For each parameter, the data series were first homogenized with the software MASH (Multiple Analysis of Series for Homogenization); then, the data series were gridded by means of the software MISH (Meteorological Interpolation based on Surface Homogenized Data).