Weather conditions and phosphorus speciation in waters of the Western Sargasso Sea in October-November 1977

Forms of phosphorus were determined for the first time in the area under study. Based on the ratio between organic and inorganic forms of phosphorus, it is concluded that sorption processes in the thin surface layer and photosynthetic processes in surface water are of the same intensity. Extremely high values of total phosphorus in the thin layer may be indicators of water pollution.

Discharge measurements and storm event chemistry at the San Francisco River station (Planta) in 2007-2008

To improve our knowledge of the influence of land-use on solute behaviour and export rates in neotropical montane catchments we investigated total organic carbon (TOC), Ca, Mg, Na, K, NO3 and SO4 concentrations during April 2007-May 2008 at different flow conditions and over time in six forested and pasture-dominated headwaters (0.7-76 km2) in Ecuador. NO3 and SO4 concentrations decreased during the study period, with a continual decrease in NO3 and an abrupt decrease in February 2008 for SO4. We attribute this to changing weather regimes connected to a weakening La Niña event. Stream Na concentration decreased in all catchments, and Mg and Ca concentration decreased in all but the forested catchments during storm flow. Under all land-uses TOC increased at high flows. The differences in solute behaviour during storm flow might be attributed to largely shallow subsurface and surface flow paths in pasture streams on the one hand, and a predominant origin of storm flow from the organic layer in the forested streams on the other hand. Nutrient export rates in the forested streams were comparable to the values found in literature for tropical streams. They amounted to 6-8 kg/ha/y for Ca, 7-8 kg/ha/y for K, 4-5 kg/ha/y for Mg, 11-14 kg/ha/y for Na, 19-22 kg/ha/y for NO3 (i.e. 4.3-5.0 kg/ha/y NO3-N) and 17 kg/ha/y for SO4. Our data contradict the assumption that nutrient export increases with the loss of forest cover. For NO3 we observed a positive correlation of export value and percentage forest cover.

Event layer chronology from Lake Suigetsu (Japan, SG06 Project) for the last 40 kyr

Event layers in lake sediments are indicators of past extreme events, mostly the results of floods or earthquakes. Detailed characterisation of the layers allows the discrimination of the sedimentation processes involved, such as surface runoff, landslides or subaqueous slope failures. These processes can then be interpreted in terms of their triggering mechanisms. Here we present a 40 kyr event layer chronology from Lake Suigetsu, Japan. The event layers were characterised using a multi-proxy approach, employing light microscopy and µXRF for microfacies analysis. The vast majority of event layers in Lake Suigetsu was produced by flood events (362 out of 369), allowing the construction of the first long-term, quantitative (with respect to recurrence) and well dated flood chronology from the region. The flood layer frequency shows a high variability over the last 40 kyr, and it appears that extreme precipitation events were decoupled from the average long-term precipitation. For instance, the flood layer frequency is highest in the Glacial at around 25 kyr BP, at which time Japan was experiencing a generally cold and dry climate. Other cold episodes, such as Heinrich Event 1 or the Late Glacial stadial, show a low flood layer frequency. Both observations together exclude a simple, straightforward relationship with average precipitation and temperature. We argue that, especially during Glacial times, changes in typhoon genesis/typhoon tracks are the most likely control on the flood layer frequency, rather than changes in the monsoon front or snow melts. Spectral analysis of the flood chronology revealed periodic variations on centennial and millennial time scales, with 220 yr, 450 yr and a 2000 yr cyclicity most pronounced. However, the flood layer frequency appears to have not only been influenced by climate changes, but also by changes in erosion rates due to, for instance, earthquakes.

Towards convection-resolving, global atmospheric simulations with the Model for Prediction Across Scales (MPAS) v3.1: an extreme scaling experiment, links to sourcecode of model and grides

The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This concept allows one to include the feedback of regional land use information on weather and climate at local and global scales in a consistent way, which is impossible to achieve with traditional limited area modelling approaches. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different high-performance computing (HPC) sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African monsoon (WAM) and its associated precipitation in a pilot study. Constrained by available computational resources, we compare 11-month runs for two meshes with observations and a reference simulation from the Weather Research and Forecasting (WRF) model. We show that MPAS can reproduce the atmospheric dynamics on global and local scales in this experiment, but identify a precipitation excess for the West African region. Finally, we conduct extreme scaling tests on a global 3?km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70?% parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3?km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.