Proxy data and model simulations of sediment core GeoB7920-2

The evolution of the northwest African hydrological balance throughout the Pleistocene epoch influenced the migration of prehistoric humans**1. The hydrological balance is also thought to be important to global teleconnection mechanisms during Dansgaard-Oeschger and Heinrich events**2. However, most high-resolution African climate records do not span the millennial-scale climate changes of the last glacial-interglacial cycle**1, 3, 4, 5, or lack an accurate chronology**6. Here, we use grain-size analyses of siliciclastic marine sediments from off the coast of Mauritania to reconstruct changes in northwest African humidity over the past 120,000 years. We compare this reconstruction to simulations of palaeo-humidity from a coupled atmosphere-ocean-vegetation model. These records are in good agreement, and indicate the reoccurrence of precession-forced humid periods during the last interglacial period similar to the Holocene African Humid Period. We suggest that millennial-scale arid events are associated with a reduction of the North Atlantic meridional overturning circulation and that millennial-scale humid events are linked to a regional increase of winter rainfall over the coastal regions of northwest Africa.

E-RUN version 1.1: Observational gridded runoff estimates for Europe, link to data in NetCDF format (69 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950 - December 2015) on a 0.5° x 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

E-RUN version 1.0: Observational gridded runoff estimates for Europe, link to data in NetCDF format (68 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.

Oil viscosity from experiments and model calculations

Five frequently-used models were chosen and evaluated to calculate the viscosity of the mixed oil. Totally twenty mixed oil samples were prepared with different ratios of light to crude oil from different oil wells but the same oil field. The viscosities of the mixtures under the same shear rates of 10 s**-1 were measured using a rotation viscometer at the temperatures ranging from 30°C to 120°C. After comparing all of the experimental data with the corresponding model values, the best one of the five models for this oil field was determined. Using the experimental data, one model with a better accuracy than the existing models was developed to calculate the viscosity of mixed oils. Another model was derived to predict the viscosity of mixed oils at different temperatures and different values of mixing ratio of light to heavy oil.

Mapped cetacean habitat suitability and richness in the Azores, links to ArcGIS files

Marine spatial planning and ecological research call for high-resolution species distribution data. However, those data are still not available for most marine large vertebrates. The dynamic nature of oceanographic processes and the wide-ranging behavior of many marine vertebrates create further difficulties, as distribution data must incorporate both the spatial and temporal dimensions. Cetaceans play an essential role in structuring and maintaining marine ecosystems and face increasing threats from human activities. The Azores holds a high diversity of cetaceans but the information about spatial and temporal patterns of distribution for this marine megafauna group in the region is still very limited. To tackle this issue, we created monthly predictive cetacean distribution maps for spring and summer months, using data collected by the Azores Fisheries Observer Programme between 2004 and 2009. We then combined the individual predictive maps to obtain species richness maps for the same period. Our results reflect a great heterogeneity in distribution among species and within species among different months. This heterogeneity reflects a contrasting influence of oceanographic processes on the distribution of cetacean species. However, some persistent areas of increased species richness could also be identified from our results. We argue that policies aimed at effectively protecting cetaceans and their habitats must include the principle of dynamic ocean management coupled with other area-based management such as marine spatial planning.