Decadal predictability and prediction skill of sea surface temperatures in the South Pacific region

The South Pacific Ocean is a key driver of climate variability within the Southern Hemisphere at different time scales. Previous studies have characterized the main mode of interannual sea surface temperature (SST) variability in that region as a dipolar pattern of SST anomalies that cover subtropical and extratropical latitudes (the South Pacific Ocean Dipole, or SPOD), which is related to precipitation and temperature anomalies over several regions throughout the Southern Hemisphere. Using that relationship and the reported low predictive skill of precipitation anomalies over the Southern Hemisphere, this work explores the predictability and prediction skill of the SPOD in near-term climate hindcasts using a set of state-of-the-art forecast systems. Results show that predictability greatly benefits from initializing the hindcasts beyond the prescribed radiative forcing, and is modulated by known modes of climate variability, namely El Niño-Southern Oscillation and the Interdecadal Pacific Oscillation. Furthermore, the models are capable of simulating the spatial pattern of the observed SPOD even without initialization, which suggests that the key dynamical processes are properly represented. However, the hindcast of the actual phase of the mode is only achieved when the forecast systems are initialized, pointing at SPOD variability to not be radiatively forced but probably internally generated. The comparison with the performance of an empirical prediction based on persistence suggests that initialization may provide skillful information for SST anomalies, outperforming damping processes, up to 2–3 years into the future.     

Risk occurrences of damaging frosts during the growing season of vegetables in the Elbe River lowland,the Czech Republic

This study has, for the first time, analysed in detail the risk occurrences of the last spring frost, first fall frost and the length of the frost-free period during the growing season of vegetable crops at a high horizontal resolution of 10 km in the Elbe River lowland in the Czech Republic. The daily minimum air temperature from 116 grid points throughout the studied area for the period 1961–2011 was used. The daily values of minimum air temperature ranges of 0 to ?1.1 °C, ?1.2 to ?2.2 °C and below ?2.2 °C were considered to constitute mild, moderate and severe frost intensities, respectively. Firstly, the spatiotemporal variability of the date of the last spring frost, the date of the first fall frost and the length of the frost-free period in the Elbe River lowland is provided. Secondly, the estimation of the probability of a later date in the spring and an earlier date in the fall for various severe frost events and the length of the frost-free period is determined. Third, the changes in the timing of the last and first frosts of the three severities, as well as the length of the frost-free period, are evaluated. From 1961 to 2011, the Elbe River lowland has experienced a decrease in the number of frost days, while the length of the frost-free period between the last spring frost and the first fall frost has increased. The temporal evolution of the frost-free period anomalies displays two distinct periods: a shortening of the frost-free period in the 1960s and an intensified lengthening of the frost-free period since the 1980s. Whereas the latest spring frost has ended on an earlier date across the Elbe River lowland, the first frost date in the fall has generally been delayed to a later date. The dates of the last spring frost have advanced by ?0.21 days per year on average. The fall dates are delayed up to 0.18 days per year, whereas the frost-free period is lengthening by up to 0.39 days per year on average. However, regional frost series suggests that the frost-free period exhibits a large amount of inter-annual variability. In terms of the growth of field vegetables, a late spring frost remains a risk factor, but the degree of risk has decreased. There is a 25 % chance of the occurrence of dangerous spring frosts during the planting of field vegetables after 3rd May, but after 15th May, the risk is only 10 %.     

A simple method to model the reduced environment of lake bottom sapropel formation

The Kambala and Barchin brackish lakes(Baraba steppe,southern West Siberia) contain an organic-rich sapropel layer that was formed in oxygen-depleted waters.We measured the bulk sediment elemental composition,the water chemistry and determined the mineralogical composition and predominant biota species(Diatoms and Cyanobacteria in phytoplankton community respectively) in the lakes.The result indicates that the first lake has a siliceous type of sapropel and the second a carbonaceous one.A computer thermodynamic model was developed for chemical interaction in water-bottom sediment systems of the Kambala and Barchin Lakes.The surface sodium bicarbonate waters are supersaturated with respect to calcite,magnesite(or low Mg-calcite),quartz and chlorite with minor strontianite,apatite and goethite(pH8.9-9.3,Eh 0.3 V).Nevertheless,it is shown that during sapropel deposition,deep silt waters should be anoxic(Eh0 V).The virtual component CH_2O has been used to create an anoxic environment suitable for pyrite formation due to the biotic community impact and abiotic reduction.Thermodynamic calculation has shown that silt water is not necessarily euxinic(anoxic and sulfidic).Depending on Eh,sulfate sulfur can dominate in solution,causing the formation of gypsum together with pyrite.An attempt was made to find a reason for solution supersaturation with respect to Ca and Mg ions due to their complexation with humic acids.     

Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi,Uttar Pradesh,India

The area east of Varanasi is one of numerous places along the watershed of the Ganges River with groundwater concentrations of arsenic surpassing the maximum value of 10 parts per billion (ppb) recommended by the World Health Organization in drinking water. Here we apply geostatistics and compositional data analysis for the mapping of arsenic and iron to help in understanding the conditions leading to the occurrence of elevated level of arsenic in groundwater. The methodology allows for displaying concentrations of arsenic and iron as maps consistent with the limited information from 95 water wells across an area of approximately 210 km²; visualization of the uncertainty associated with the sampling; and summary of the findings in the form of probability maps. For thousands of years, Varanasi has been on the erosional side in a meander of the river that is free of arsenic values above 10 ppb. Maps reveal two anomalies of high arsenic concentrations on the depositional side of the valley, which has started seeing urban development. The methodology using geostatistics combined with compositional data analysis is completely general, so this study could be used as a prototype for hydrochemistry mapping in other areas.