Dormant stages of crustaceans as a mechanism of propagation in the extreme and unpredictable environment in the Crimean hypersaline lakes

A pool of dormant stages of planktonic organisms in saline lakes is a substantial component in the plankton communities;we need to take it into account to understand plankton dynamics.Hypersaline water bodies in Crimea,the largest peninsula in the Black Sea,constitute a very characteristic and peculiar habitat type in the region.We examined the presence of crustacean resting stages in sediments of dried up sites of the Crimean hypersaline lakes.Sediment samples were taken in 9 different lakes.Experiments performed on the hatching of these resting stages showed the presence of Moina salina(Cladocera),parthenogenetic Artemia and Artemia urmiana(Anostraca),Eucypris mareotica( inflata)(Ostracoda),and Cletocamptus retrogressus(Harpacticoida).Comparing the experimental results obtained with clean dried brine shrimp cysts and those kept in sediment samples,it was noted that clean cysts hatched much faster than those from sediments did.Some components in bottom sediments slow down and desynchronize hatching from resting eggs in different groups of crustaceans.The sediments of different lakes inhibited the nauplii output from Artemia and ostracod resting eggs to different degrees.More data are needed before we can discuss the reasons of this inhibition.The nonsynchronous output of active stages from the bottom resting ones may be an adaptation that allows crustacean species to exist in extreme and unpredictably changing environments,avoiding the risk that all may emerge at once under unsuitable conditions.     

Development of the ElarmS methodology for earthquake early warning: Realtime application in California and offline testing in Japan

In July 2009, the California Integrated Seismic Network concluded a three-year study of earthquake early warning systems in California. Three algorithms were expanded and examined during the study. Here we discuss the history, methodology, and performance of one of the algorithms, ElarmS. Earthquake Alarm Systems, or ElarmS, uses peak displacement and maximum predominant frequency of the P-wave to detect earthquakes and quantify their hazard in the seconds after rupture begins. ElarmS was developed for Northern and Southern California, and now processes waveforms in realtime from 603 seismic sensors across the state. We outline the methodology as currently implemented, present several example events from different regions of California, and summarize the performance in terms of false and missed alarms. ElarmS was also tested offline with a dataset of 84 large magnitude earthquakes from Japan. The results from the Japan dataset were used to create a statistical error model for the algorithm. The model can be used to provide realtime uncertainty estimates at any stage in processing. In August 2009 the CISN embarked on a second three-year study of earthquake early warning. As part of this ongoing research, we identify the technological and methodological challenges facing ElarmS. Telemetry latencies and false alarm rates are two key opportunities for improvement.     

Seasonal Cycle of the Near-Surface Diurnal Wind Field Over the Bay of La Paz,Mexico

The results of numerical simulations of the troposphere over the Bay of La Paz, calculated for the months of January, April, July and October during the period 2006–2010 with the Weather Research and Forecast (WRF v3.5) regional model, are used to describe the seasonal features of the diurnal cycle of planetary boundary-layer winds. Two distinct near-surface diurnal flows with strong seasonal variability were identified: (1) a nocturnal and matutinal breeze directed from the subtropical Pacific Ocean, over the Baja California peninsula and the Bay of La Paz, into the Gulf of California that is associated with the regional sea-surface temperature difference between those two major water bodies; and (2) a mid to late afternoon onshore sea-breeze related to the peninsula’s daily cycle of insolation heating that evolves with counter-clockwise rotation over the Bay of La Paz. The model results reveal the interaction over Baja California of opposing afternoon sea-breeze fronts that originate from the subtropical Pacific Ocean and the Gulf of California, with a convergence line forming over the peaks of the peninsula’s topography and the associated presence of a closed vertical circulation cell over the Bay of La Paz and the adjacent Gulf. The collision of the opposing sea-breeze fronts over the narrow peninsula drives convection that is relatively weak due to the reduced heat source and only appears to produce precipitation sporadically. The spatial structure of the sea-breeze fronts over the Bay of La Paz region is complex due to shoreline curvature and nearby topographic features. A comparison of the numerical results with available meteorological near-surface observations indicates that the modelling methodology adequately reproduced the observed features of the seasonal variability of the local planetary boundary-layer diurnal wind cycle and confirms that the low-level atmospheric circulation over the Bay of La Paz is dominated by kinetic energy in the diurnal band. The strongest (weakest) diurnal flows occur during the summer (winter) in response to the seasonally varying magnitudes of the daily land–sea thermal contrast and the regional subtropical Pacific Ocean–Gulf of California sea-surface temperature difference.     

WSO-UV progress and expectations

The World Space Observatory Ultraviolet (WSO-UV) is the space mission that will grant access to the ultraviolet (UV) range in the post Hubble epoch. WSO-UV is equipped with instrumentation for imaging and spectroscopy and it is fully devoted to UV astronomy. In this article, we outline the WSO-UV mission model and present the current status of the project.     

Deuterated water: partition functions and equilibrium constants

HDO and D₂O are thought to be present in significant quantities in the coldest regions of the Universe. Partition functions are calculated for these species and used to calculate temperature dependent equilibrium constants for the most important fractionation reactions involving water. HDO may also be a key indicator of the absence of deuterium burning in very low mass stars. The HDO partition function calculation is extended to high  ( T ≤ 6000 K)  temperatures for this purpose.     

Quantifying barriers to decarbonization of the Russian economy: real options analysis of investment risks in low-carbon technologies

Russia has significant potential for reducing its carbon emissions. However, investment in new low-carbon technologies has significant risks. Ambiguous energy and climate policy in Russia, along with deterioration of the country's investment climate, create investment barriers that are well described in qualitative terms in the literature. This paper attempts to provide a quantitative analysis of these barriers. For this numerical experiment, we apply the RU-TIMES model. Using a real options methodology, we estimate the risk-adjusted cost of capital in the Russian energy sector (including energy production and consumption technologies represented in the TIMES framework) to be approximately 43% (including a risk-free interest rate) and demonstrate the high risk of investment into energy-efficient and low-carbon technologies. Any future low-carbon emissions pathway depends on the ability of the Russian government to reduce climate and energy policy uncertainties, and to reduce financial risks through improvements of the general investment climate.

Key policy insights

• The high cost of capital investment into Russian energy production and consumption may prevent the adoption of new energy-efficient and low-carbon technologies.

• These investment risks, if not addressed, will delay Russia's low-carbon transition for the coming decades.

• Adopting a clear and unambiguous long-term climate and energy policy is important to reduce these risks and alleviate some of the barriers to the new technologies.

• The first step could be ratification of the Paris Agreement and adoption of a long-term emission target for the period up to 2050.

     

Predicting Patterns of Near-Surface Air Temperature Using Empirical Data

The signal of recent global warming has been detected in meteorological records, borehole temperatures and by several indirect climate indicators. Anthropogenic warming continues to evolve, and various methods are used to study and predict the changes of the global and regional climate. Results derived from GCMs, palaeoclimate reconstructions, and regional climate models differ in detail. An empirical model could be used to predict the spatial pattern of the near-surface air temperature and to narrow the range of regional uncertainties. The idea behind this approach is to study the correlations between regional and global temperature using century-scale meteorological records, and to evaluate the regional pattern of the future climate using regression analysis and the global-mean air temperature as a predictor. This empirical model, however, is only applicable to those parts of the world where regional near-surface air temperature reacts linearly to changes of the global thermal regime. This method and data from a set of approximately 2000 weather stations with continuous century-scale records of the monthly air temperature was applied to develop the empirical map of the regional climate sensitivity. Data analysis indicated that an empirical model could be applied to several large regions of the World, where correlations between local and global air temperature are statistically significant. These regions are the western United States, southern Canada, Alaska, Siberia, south-eastern Asia, southern Africa and Australia, where the correlation coefficient is typically above 0.9. The map of regional climate sensitivity has been constructed using calculated coefficients of linear regression between the global-mean and regional annual air temperature. As long as the correlations between the local and global air temperature are close to those in the last several decades, this map provides an effective tool to scale down the projection of the global air temperature to regional level. According to the results of this study, maximum warming at the beginning of the 21st century will take place in the continental parts of North America and Eurasia. The empirical regional climate sensitivity defined here as the response of the mean-annual regional temperature to 1 °C global warming was found to be 5–6 °C in southern Alaska, central Canada, and over the continental Siberia, 3–4 °C on the North Slope of Alaska and western coast of the U.S.A., and 1–2 °C in most of the central and eastern U.S.A. and eastern Canada. Regions with negative sensitivity are located in the southeastern U.S.A., north-western Europe and Scandinavia. The local tendency towards cooling, although statistically confirmed by modern data, could, however, change in the near future.     

Relationship between MODIS based Aerosol Optical Depth and PM10 over Croatia

This study analyzes the relationship between Aerosol Optical Depth (AOD) obtained from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based PM10 mass concentration distribution over a period of 5 years (2008–2012), and investigates the applicability of satellite AOD data for ground PM10 mapping for the Croatian territory. Many studies have shown that satellite AOD data are correlated to ground-based PM mass concentration. However, the relationship between AOD and PM is not explicit and there are unknowns that cause uncertainties in this relationship. The relationship between MODIS AOD and ground-based PM10 has been studied on the basis of a large data set where daily averaged PM10 data from the 12 air quality stations across Croatia over the 5 year period are correlated with AODs retrieved from MODIS Terra and Aqua. A database was developed to associate coincident MODIS AOD (independent) and PM10 data (dependent variable). Additional tested independent variables (predictors, estimators) included season, cloud fraction, and meteorological parameters — including temperature, air pressure, relative humidity, wind speed, wind direction, as well as planetary boundary layer height — using meteorological data from WRF (Weather Research and Forecast) model. It has been found that 1) a univariate linear regression model fails at explaining the data variability well which suggests nonlinearity of the AOD-PM10 relationship, and 2) explanation of data variability can be improved with multivariate linear modeling and a neural network approach, using additional independent variables.     

Primary Production and the Hydrochemical Parameters of the Salt Lakes in the North-Western Part of the Crimea(Russia)

正1 Introduction It is known that more than 300 lakes and lagoons are present in the Crimean Peninsula,which are divided depending on position to 7 groups:Perekop,Tarkhankut,Evpatoriyskaya,Khersonesskaya,lake on the mountainpastures,Kerch and Genicheskaya.Almost the all lakes,with the exception of the small freshwater lakes,which situated on mountain pastures of the Main ridge of