In most situations, theseaice covers only a part ofthe total water surface and is a mixture ofice types differing in structure and properties – level, rafted and ridged ice, possibly with cracks and leads (Lepp¨aranta and Myrberg, 2009). Thenumericalsea-ice models operating on the scale of tens up to thousands of kilometers reduce this informa- tion to a few parameters, typically to the concentration and mean thickness ofthe specified ice (and snow) classes in a given grid cell (for studies concerning theBalticSea see, e.g., Haapala and Lepp¨aranta, 1996; Meier et al., 1999; Haa- pala, 2000; Lehmann and Hinrichsen, 2000a; Zhang, 2000). As described below, the model used in this study belongs to that class of models. Modelling studies oftheBalticSeaicethermodynamicsanddynamics can be broadly divided into two categories. One concentrates on problems of climate and climate change, seasonal and interannual sea-ice variability, andthe influence of large-scale atmospheric circulation pat- terns on thesea-ice processes intheBalticSea (e.g., Haapala and Lepp¨aranta, 1996; Omstedt and Nyberg, 1996; Lehmann and Hinrichsen, 2000a,b; Schrum et al., 2003). These studies are based on medium- and long-term simulations and mostly involve variables such as the maximum annual ice extent or the length oftheice season, i.e., parameters which can be understood as proxies of winter severity and which are there- fore good indicators of a climate change. The other category consists of studies which tackle smaller spatial and tempo- ral scales with the aim of analyzing effects of synoptic-scale weather patterns on thethermodynamicsanddynamicsoftheseaice. Good examples are provided by Uotila (2001), Br¨ummer et al. (2002), Rudolph and Lehmann (2006), Wang et al. (2006) or Bj¨ork et al. (2008). The need for more ex- tensive observational andnumerical research is widely rec- ognized, particularly with respect to short- and medium-term icedynamicsintheBalticSea.
field ratios are feasible in interpreting the spatial and temporal dynamicsin nutrient concentration. For example, Osterroht and Thomas (2000) noticed that the N/P ratio of nutrient alteration fore and after the growing season was much different from Red- field ratios, they explained that the elemental ratios of nutrient uptake were consistent with Redfield ratios, but the nutrient mineralized from freshly produced organic material
algae, i.e. diatoms, generally dominant intheseaice habitat , detritus and gases for totally 9 state variables. A schematic diagram ofthe model is presented in Fig. 6, model’s variables and parameters are reported in Table S2 and Table S3 in File S1, while a mathematical description ofthe model is given in section S2 in File S1. The limiting nutrient is silicate, but any other nutrient can be chosen as model’s currency. Silicon was chosen because the functional group of algae is made of diatoms that require silicate uptake. If the model must have one single chemical component as currency, then silicon is likely to be the most appropriate for theseaice system. However, many oceanic models use nitrogen as model’s currency since it often the most limiting inthe oceans. In this latter case, modellers can choose if either increasing the number of state of variables of their model including both silicon and nitrogen components, either if using a N:Si conversion factor. Silicate dynamics differentiate from nitrate and phosphate dynamics as silicate does not accumulate inthe cell and it is more likely to be parameterized with a simple Michaelis- Menten function (e.g ) and thus directly controls carbon photosynthesis. If nitrate or phosphate are instead chosen as most limiting nutrient, those are decoupled from carbon uptake because ofthe existence of cellular storage capabilities. The co-limitation from all nutrients can be done with a threshold method, as in , and it is considered inthe parameterization of some processes such as chlorophyll synthesis and sinking. Multiple nutrient limitation is different for nutrients that can be stored inthe cell (nitrate and
Recent advances in network science have encouraged ecologists to study food-webs through network indices [14,67,68]. The estimations of species interactions often benefit the understanding of ecosystem response to perturbations [10,69], but it must be kept in mind that the impact of network structure on community may differ between different interaction types . Consequently, the ENA analysis depends strongly on model quality and structure. As explained by Abarca-Arenas and Ulanowicz  and Pinnegar et al.  the number of functional groups and model structure have an impact on the number of flows and system properties. This has to be taken into account when comparing our results to other system outputs and other BalticSea models. Ecopath with Ecosim  is a commonly used approach that has been broadly discussed. Plaga´nyi and Butterworth , Aydin , Coll et al.  and Walters et al.  described the pros and cons ofthe methodology, which has been taken into account during model building, fitting and evaluation [39,78]. Niiranen et al.  found that data uncertainties may translate to uncertainties in modelled trophic control and hence results. However in this study the model was well fitted for several trophic levels and we have confidence inthe model and data , which represent changes in biomasses and ecosystem dynamics well (see Fig. S1 in File S1).
ure ofthe model to capture the observed late fall-winter min- ima (Fig. 4b). At the annual scale, Atlantic waters bring 96% of TA in BCZ and river loads and biological processes con- tribute 3.9% and 0.1%, respectively. Sensitivity tests with varying initial TA corresponding to the range of observed values in WCH (Borges and Frankignoulle, 2003) indicate that a reduction of WCH initial conditions of TA by less than 2% improves significantly model simulations of DIC (Fig. 4a) and TA (Fig. 4b) in winter while fall observations remain overestimated by the model (Fig. 4a, b). Elevated modelled TA in fall could result from an overestimation of river inputs during this period. At that time ofthe year (Oc- tober to January), river discharge is high and inputs of TA ac- count for 45% of annual river loads. Due to the importance of biological processes on magnitude and seasonal variability of DIC, modification of DIC initial value inthe Western Chan- nel has no impact on DIC magnitude inthe Belgian coastal zone.
Theice-drift inthe Arctic Ocean is driven, mainly, by the wind forcing (Lewis et al., 1994; Richter-Menge and Elder, 1998), andthe variability ofthe weather pattern causes cy- cles of redistribution of stresses and deformations with ice breaking (Hopkins et al., 2004) followed by refreezing (Ko- rsnes et al., 2004). On 10 February 2004, a basin-wide sea- ice fragmentation occurred, and it was detected inthe satel- lite images. Figure 4 shows the NOAA satellite images ofthe region of drift obtained on 9 February and 10 Febru- ary 2004. In Fig. 4b one can see large-scale leads (up to 400 km in length), which formed in one day between two subsequent images and a position ofthe research station NP 32 that drifted on the pack during that period of time. The displacements and fragmentation oftheice-cover lasted dur- ing the whole February; on 2 March 2004 the research station NP 32 was abandoned in connection with multiple breakage oftheice-field on which the observations were carried out.
Since seaice potentially hinders winter navigation, de- tailed forecasts oftheice conditions are in demand and reg- ularly provided by the local weather services. A typical ice forecast contains several prognostic variables, for instance ice concentration, thickness and prognosticated ice drift. Ad- ditional variables are occasionally included, e.g., ridged ice fraction, which refers to the most important deformed ice type. Ridges can form substantial obstacles to winter nav- igation and thus receive increasing attention from the re- search community (e.g., Haapala, 2000; Kankaanpää, 1988; Leppäranta and Hakala, 1992; Leppäranta et al., 1995; Löp- tien et al., 2013). The forecast ofthe Swedish Meteorolog- ical and Hydrological Institute (SMHI) provides additional information about convergence oftheice drift field (i.e., re- gions where theice is compacting are marked). In regions with convergent ice motion, large ice stresses can occur, the ships might get stuck and, inthe worst case, even damaged (e.g., Suominen and Kujala, 2014; Pärn et al., 2007).
Abstract. TheBalticSea is a seasonally ice-covered, marginal seain central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by seaice, the local weather services have been monitoring seaice conditions for decades. Inthe present study we revisit a historical monitoring data set, covering the winters 1960/1961 to 1978/1979. This data set, dubbed Data Bank for BalticSeaIceandSea Surface Temperatures (BASIS) ice, is based on hand-drawn maps that were collected and then digitised in 1981 in a joint project ofthe Finnish Institute of Marine Research (today the Finnish Meteorological Institute (FMI)) andthe Swedish Meteorological and Hydrological Institute (SMHI). BASIS ice was designed for storage on punch cards and all ice information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard ice quantities (including information on ice types), which we distribute inthe current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numericalice models and provide easy-to-access unique historical reference material for seaiceintheBalticSea. In addition we provide statistics showcasing the data quality. The website www.baltic-ocean.org hosts the post-processed data andthe conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science, PANGAEA (doi:10.1594/PANGAEA.832353).
In Russia, the Triple Helix is still being at a very early stage of formation — not yet a system, but mostly pairwise relationships, such as: science — busi- ness, the state — science andthe state — business. The specificity ofthe Russian Triple Helix model consists, inthe first place, inthe supremacy ofthe state over science and business. Secondly, unlike most countries ofthe world, Russia does not trust most ofthe fundamental research to universities, but delegates it to the institutes ofthe Russian Academy of Sciences . The intensity of research and development (R & D), is measured by the ratio of R & D expenditure to GDP. In Europe, there is a direct dependence between economic growth andthe size of national and regional resources allocated to research and development . In 2010, total R & D expenditure inthe EU-27 states was an average of 2 % of GDP, below the target of 3 % set by the 2010 recommendations ofthe Lisbon Strategy for the EU . Among the EU countries only Finland (3.87 %), Sweden (3.42 %) and Denmark (3.06 %) exceed the 3 % of GDP . In per capita terms, these states fall behind Lux- embourg. It is important to note that Finland and Denmark still are still showing growth, while Sweden has been in decline for 5 years now. Ger- many spends 2.82 % of GDP on research and development, which is lower than that ofthe Nordic countries, but higher than the average inthe EU andthe U. S.
To get more robust results on long term trends, further evaluation ofthe radar altime- ter on board CryoSat-2 is needed, and more reliable estimates ofseaice density and snow depth on the Arctic seaice are necessary. Our results indicate a less dramatic decline of Arctic seaice volume than reported in previous studies, but it is not possible to draw quantitative conclusions about changes inseaice volume between the ICESat
Thus, over many years, Russia-EU cooperation inthe field of energy ef- ficiency has been developing in several parallel and mutually supportive forms. However, the achieved results are still modest: technology transfer has been faced with certain problems, andthe number of joint projects — especially those inthe Russian regions bordering on the EU — is rather lim- ited. One ofthe most commonly mentioned reasons behind it  is an in- sufficiently favourable investment climate in Russia, which is partially a re- sult of lacking clearly defined legal conditions. Another obstacle is limited financial incentives for companies operating inthe field of energy efficiency. Of course, clearly defined legal conditions and predictability of political leadership’s actions are more important in this field compared to oil and gas trade, where an alliance of giant corporations andthe political leadership of countries or the EU can remove any obstacles.
7. Mezhevich, N. M. 2000, Mezhdunarodnye organizacii Baltijskogo morja: os- novnye napravlenija i rol' v formirovanii sistemy mezhdunarodnyh otnoshenij [In- ternational organizations oftheBalticSea: the main directions and role inthe sys- tem of international relations], St. Petersburg, p. 3.
The structure ofthe remelting zone ofthe steel C90 steel be- fore conventional tempering consitute cells, dendritic cells, sur- rounded with the cementite, inside of which there is a plate mar- tensite and retained austenite, whereas the structure HS 6-5-2 steel consititute cells, dendritic cells and dendrites surrounded with the eutectic, inside of which there is a plate martensite and retained austenite. Such a structure is characterized with the similar micro- hardness (790-800 HV0,065) and intensity ofthe tribilogical wear.
18 cm thick young seaice grown in an outdoor seaice pool from experimental seawa- ter under ambient weather conditions. It is surmised that this brine drainage channel feature is a first generation one, having been formed during seaice growth inthe week previous to the sampling date, and not as result of melting processes, given the temper- ature history oftheseaice volume over the growth period of that section. The speed
have been performed on solid surfaces (with a few exceptions, M ¨ohler et al., 2007). We find low-temperature INA for the isolates observed in this study and these isolates are therefore not likely to be important for polar atmospheric processes. Overall, knowl- edge of bacterial diversity and activity is essential to predict potential bacterial impact on cloud formation processes and air chemistry if metabolically active bacteria process
Nowadays, magnesium alloys are used for casting into sand moulds of huge dimensional castings, high-pressure castings and precise casings. In castings of magnesium alloys defects or inconsistencies often appear (like casting misrun, porosities and cracks) particularly inthe huge dimensional castings. Such defects are mended with the use of padding and welding. The welding techniques can be applied by using weld material consisting of magnesium alloy, as well as for regeneration of alloys after excessive wear. Nevertheless, the number ofthe repaired castings, which were permitted for use, is not satisfactory for a profitable production. The main reasons for wear are the cracks appearing during welding in brittleness high-temperature range.
Zimmerman (1999) in his article titled ―Mobile Computing: Characteristics, Benefits, andthe Mobile fra mework‖ defined mobile computing as ―the use of computing devices, which usually interact in some way with a centralised information system while away from the normal fixed workplace‖. He went on to say that, Mobile computing technology enables the mobile person to create, access, process, store and communicate information without being constrained to a single location. It is on the above basis that this researcher views mobile computing as embracing a host of portable technologies the can access internet using wireless fidelity (WIFI). These range from notebook computers to tablets, to smartphones and e-book readers. Such devices have brought about Mobile learning (m-Learning) in Zimbabwe Polytechnics, enabling staff and students to share academic resources, be able to research and develop applications from wherever they are. Zimmerman (1999) went on to identify mobile computing hardware, software and communications in use then. He identified hardware as palmtops, clamshells, handheld Pen Keys, pen slates, and laptops. The characteristics of such devices in terms of screen size was small, processing capability was limited and supported a few mobile applications. Over the years mobile devices have improved in such characteristics to make mobile computing easy, fast and user friendly. Great improvements also came with the associated systems software, with the modern devices now running on Android, Symbian and windows 8 mobile, as compared to then when MS DOS, Windows 3.1, Pen DOS were used. In communications Zimmerman talked of internet speeds in kilobytes per second (Kbps), while today’s communications devices have speeds of gigabytes per second (Gbps
the countries in Asia as Malaysia had more intentions of organic products from the customers in view ofthe importance of health on environmental issues (Saleki et al., 2012:99). This shows that attentions to organic products are already quite well received by the community. However, there needs to be studied perception of organic products in Indonesia, because Indonesia is a developing country which has a population density is quite high compared from Malaysia. And consumption of vegetable, especially organic vegetable products is still low in Indonesia (Amin, 2014:13), in particularly the province of West Java. An organic vegetable product offered by retail supermarket is assessed by consumers in both of sides, quality and risk. Price is a risk that should be accepted by consumers when buying organic vegetables. Hence, price of organic vegetables is more expensive than conventional vegetable products (Radman, 2005:263). Value ofthe risk products is very important for customer, which has an impact on consumer purchasing decisions (Yee et al., 2011:55). Nowadays consumers buy organic products is not as aware ofthe health and environmental effects but because of advised and habit of surroundings (Guido et al., 2010:99). In addition, not all consumers considered that by buying organic products, have been keeping or help conserve the environment (Arvola, 2008:449). It is alleged lack of consumer understanding of product quality organic vegetables. On last study it was discovered that the perceived quality is strong relationship with consumer purchasing decisions (Yee et al., 2011:55). Consumer’s had perception of organic products is because of quality and safety, in addition to some other benefits (Zanoli et al., 2012:70). Customer value of product influenced purchase decision of products (Shareef, 2008:105). Organic vegetable products have value in consumer where quality and satisfactions become value for consumers (Ying & Chiu, 2012:125). Higher value of consumer product quality of organic vegetables is more possibility to purchase decisions of organic vegetable products who offered in retail supermarkets. Based on previously phenomenon, this study examines the level of consumer perceptions of quality and risk in organic vegetables, as well as the impact on consumer purchasing decisions.
The most pronounced IRD layers caused by the collapses ofthe Laurentide (H5 and H4) and Eurasian (H6 and H3) ice sheets were discovered inthe Ruddiman belt (Bond et al., 1993; Grousset et al., 1993; Grousset et al., 2001; Hemming, 2004; Ruddiman, 1977). It is often assumed that thesea‐ice cover extended to the northern edge of that belt at 55°N (Dokken et al., 2013; Vettoretti & Peltier, 2016) because thesea‐ice edge would have blocked potential northward iceberg movement as well as northward oceanic heat transport making the Ruddiman belt the most suitable region for melting. During H‐events the over- turning circulation was reduced (e.g. Böhm et al., 2015; Henry et al., 2016; Rahmstorf, 2002) andthe restart ofthe overturning circulation is observed in North Atlantic proxy records as a temperature over- shoot indicating the increased advection of warm water (e.g. Dokken et al., 2013; Knutz et al., 2011; Rasmussen & Thomsen, 2004; Sadatzki et al., 2019; Sessford et al., 2018; van Kreveld et al., 2000; Voelker et al., 1998). The glacial surface hydrography ofthe northeastern Labrador Sea was inﬂuenced by Arctic freshwater and Atlantic water and probably iceberg transport and melt from the Laurentide, Eurasian and Greenland ice sheets (Death et al., 2006; Hemming, 2004; Stoner et al., 1998). Consequently, we would expect to observe H‐related meltwater peaks associated with increased IRD ﬂuxes and low foraminifer ﬂuxes, followed by a signal of subsurface warming indicating an active surface and deep water circulation. Instead, the only proxy inthe analyzed core sections of 22CC that shows clear evidence of all H ‐events is δ 18 O, indicating each H ‐related meltwater event. Only H6, H5 and H3 are asso- ciated with low foraminifer ﬂuxes, H4 and H3 with pronounced IRD peaks and H5 and H4 are followed by subsurface warming (Table 3). Following the interpretations ofthe proxy records from this site, these differences can largely be explained by the speci