Hiatal surfaces from the Miocene Globigerina Limestone Formation of Malta: Biostratigraphy, sedimentology, trace fossils and early diagenesis

The Miocene Globigerina Limestone of the Maltese islands contains widespread omission surfaces with very different characteristics and origins. The terminal Lower Globigerina Limestone hardground (TLGLHg) formed during a period of falling sea level. Coccolith assemblages suggest shallowness. Sedimentary structures and trace fossil assemblages, indicate increasing frequency of storm events and erosional episodes, towards the surface. Calcite cementation which took place around Thalassinoides burrows and formed irregular nodules was followed by dissolution of aragonite. It is suggested that lithification was linked to microbial reactions involving organic matter. In contrast two later surfaces, the terminal Middle Globigerina Limestone omissionground (TMGLOg), which marks the Lower to Middle Miocene boundary, and the Fomm-ir-Rih local hardground (FiRLHg) both contain early diagenetic dolomite. Lithification took place in two phases. The dolomite is interpreted to have formed beneath the sea floor: it was subsequently exhumed and partially corroded as the precipitation of calcitic and phosphatic cements took place around burrows open to the circulation of sea water. (C) 2008 Elsevier B.V. All rights reserved.

Forecast convergence score: a forecaster's approach to analysing hydro-meteorological forecast systems.

In this paper the properties of a hydro-meteorological forecasting system for forecasting river flows have been analysed using a probabilistic forecast convergence score (FCS). The focus on fixed event forecasts provides a forecaster's approach to system behaviour and adds an important perspective to the suite of forecast verification tools commonly used in this field. A low FCS indicates a more consistent forecast. It can be demonstrated that the FCS annual maximum decreases over the last 10 years. With lead time, the FCS of the ensemble forecast decreases whereas the control and high resolution forecast increase. The FCS is influenced by the lead time, threshold and catchment size and location. It indicates that one should use seasonality based decision rules to issue flood warnings.

Bis amide-aromatic-ureasd - highly effective hydro- and organogelator systems

A series of hydro- and organo-supergelators have been synthesised via coupling of simple bis aromaticureas via alkyl amide linkages. These bis amide-aromatic-ureas exhibited reduced critical gelator concentrations, improved gelator stability, mechanical and dye removal properties for potential use in water purification, in comparison to related bis aromatic-ureas. Systematic structure studies via variation of the bis amide-aromatic-urea linker length as well as functionalization of the terminal aromatic moieties have enabled control over the gel properties.

Bis amide-aromatic-ureasd highly effective hydro- and organogelator systems

A series of hydro- and organo-supergelators have been synthesised via coupling of simple bis aromaticureas via alkyl amide linkages. These bis amide-aromatic-ureas exhibited reduced critical gelator concentrations, improved gelator stability, mechanical and dye removal properties for potential use in water purification, in comparison to related bis aromatic-ureas. Systematic structure studies via variation of the bis amide-aromatic-urea linker length as well as functionalization of the terminal aromatic moieties have enabled control over the gel properties.

HESS Opinions: On forecast (in)consistency in a hydro-meteorological chain: curse or blessing?

Flood forecasting increasingly relies on numerical weather prediction forecasts to achieve longer lead times. One of the key difficulties that is emerging in constructing a decision framework for these flood forecasts is what to dowhen consecutive forecasts are so different that they lead to different conclusions regarding the issuing of warnings or triggering other action. In this opinion paper we explore some of the issues surrounding such forecast inconsistency (also known as "Jumpiness", "Turning points", "Continuity" or number of "Swings"). In thsi opinion paper we define forecast inconsistency; discuss the reasons why forecasts might be inconsistent; how we should analyse inconsistency; and what we should do about it; how we should communicate it and whether it is a totally undesirable property. The property of consistency is increasingly emerging as a hot topic in many forecasting environments.