Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Ice Data

BalticIceTime.nc coverage.pdf ice chartl.jpg ice chart2.jpg ice cliinate. asc Ice Fre iuency. txt ice inonthly. asc duratlon.pdf Max ice cover.asc thlckness.pdf [Pg.645]

The annual maximum extend 1720-2005 of the Baltic Sea ice cover is available from the Finnish Institute of Marine Research (FIMR), provided with the file Max ice cover.asc. [Pg.645]

BalticIceTime.nc is a netcdf file giving the same data as in ice monthly.asc, but on a longitude/latitude grid. [Pg.645]

The source material consists of the ice charts (e.g., see ice chartl.jpg and ice chart2. jpg) issued routinely in winter by the Ice Service of Deutsches Hydrographisches Institut (DHl, German Hydrographic Institute, until 1990) and its successor, Bundesamt fiir Seeschifffahrt und Hydrographie (BSH, Federal Maritime and Hydrographic Agency)  [Pg.645]

The ice data were evaluated to obtain the ice concentration and thickness on a regular geographic grid. The size of each grid cell is 0.5° X 0.5°. The ice concentration (data is available for the complete period) has been indicated in percent (between 10 and 100) for each grid point. Ice thickness was not included regularly in the charts prior to the winter of 1981/1982, that is, ice thickness at the grid points is available only for the period 1982-2005. [Pg.646]

Rommelaere, V., L. Arnaud, and J.-M. Barnola, Reconstructing Recent Atmospheric Trace Gas Concentrations from Polar Firn and Bubbly Ice Data by Inverse Methods, J. Geophys. Res., 102, 30069-30083 (1997). [Pg.840]

QDT provides a framework which relates a few energy independent parameters to a wealth of spectroscopic data. It is used both as an efficient way to parametrize data and as a way of comparing theoretical results to experimental data. Which of the several parametrizations to use is usually unimportant for comparing theoretical results to experimental observations, since all the parametrizations are equivalent. On the other hand, if a set of data is to be represented by QDT parameters, it is useful to use the set of parameters which allows the experimental data to be fit with the minimum number of free parameters. For example, to fit ICE data, the phase shifted R matrix approach is by far the most convenient, for the absolute continuum phase does not enter. [Pg.427]

Table 1.12.2 Extracts of 7"ice data measured in a plant with a valve of 1.1 m diameter between the chamber and condenser (Measurement Steris GmbH)... Table 1.12.2 Extracts of 7"ice data measured in a plant with a valve of 1.1 m diameter between the chamber and condenser (Measurement Steris GmbH)...
A Tour of the Life of a Glacier. National Snow and Ice Data Center Web Site. Available online. URL http //nsidc.org/ glaciers/story/. Accessed November 16,2006. [Pg.102]

Figure 6 GISP2 volcanic sulfate markers for the past 2,000yr based on statistical analysis (Zielinski et ah, 1994). Several large anomalies have not been traced to the responsible volcanoes, including the prominent AD 640 and 1259 peaks. Data provided by the National Snow and Ice Data Center, University of Colorado at Boulder, and the WDC-A... Figure 6 GISP2 volcanic sulfate markers for the past 2,000yr based on statistical analysis (Zielinski et ah, 1994). Several large anomalies have not been traced to the responsible volcanoes, including the prominent AD 640 and 1259 peaks. Data provided by the National Snow and Ice Data Center, University of Colorado at Boulder, and the WDC-A...
TABLE 8.2 Mean and Extreme Ice Data (Only for Winters with Ice Representative)... [Pg.208]

BALTIC contains all public ICES data from 1900 to 2005 including the Restricted Data FIMR 1996-2004 with permission of FIMR but excluding those that failed the additional plausibility tests or were outside the area of interest. [Pg.325]

Discrete seasonal chi a data (0-10 m depth) from the HELCOM monitoring, supplemented by data from the ICES data bank and from different lOW projects, are depicted in Fig. 15.9 for selected stations. It shows that the separate treatment of the seasons (cf. Table 15.2) is much more interesting than the pooled annual data. The simple linear regression lines reveal strong trends in spring data, but no trends in summer data. A new... [Pg.465]

Armstrong RL, Knowles KW, Biodzik MJ, Hardman MA (2003) DMSP SSM/I Pathfinder daily EASE-Grid brightness temperatures. National Snow and Ice Data Center. Digital media and CD-ROM, Boulder, CO... [Pg.218]

NSIDC (National Snow and Ice Data Center) (1997) The Greenland Ice Cores CD-ROM. Available from the National Snow and Ice Data Center, University of Colorado at Bonlder, and the World Data Center-A for Paleoclimatology, National Geophysical Data Center, Boulder Colorado, http //www.ngdc.noaa.gov/paleo/icecore/greenland/summit/index.html Nye IF (1963) Correction factor for accnmnlation measnred by the thickness of annual layers in an ice sheet. J Glaciol 4 785-788... [Pg.552]

Fig. 17.24 The values of freshly fallen snow at South Pole Station during the 12-month period from November 1964 to October 1965 are approximately correlated with surface temperatures (line A, equation 17.5) and with atmospheric temperatures (line B, equation 17.6). Only the condensation temperature at which snow flakes formed in the atmosphere above South Pole Station were plotted. Note that the data points based on surface temperatures are not shown. Line C (equation 17.7) is from Aldaz and Deutsch (1967) and is based on atmospheric temperatures. These quasi-linear relationships provide a basis for estimating surface temperatures as well as condensation temperatures from the 6 0 values of snow, fim, and ice (Data from Aldaz and Deutsch 1967)... Fig. 17.24 The values of freshly fallen snow at South Pole Station during the 12-month period from November 1964 to October 1965 are approximately correlated with surface temperatures (line A, equation 17.5) and with atmospheric temperatures (line B, equation 17.6). Only the condensation temperature at which snow flakes formed in the atmosphere above South Pole Station were plotted. Note that the data points based on surface temperatures are not shown. Line C (equation 17.7) is from Aldaz and Deutsch (1967) and is based on atmospheric temperatures. These quasi-linear relationships provide a basis for estimating surface temperatures as well as condensation temperatures from the 6 0 values of snow, fim, and ice (Data from Aldaz and Deutsch 1967)...
The annual ablation rate of the ice on Lake Vanda has also varied from 12.1 cm/year in 1985/86 to 68.8 cm/year in 1970/71 for an average of 32.6 12.5 cm/ year. The rise of the level of Lake Vanda implies that the volume of water that enters the lake is larger than the volume lost by sublimation of ice. Data published by Chinn (1993) indicate that the levels of all closed-basin lakes in the ice-free vaUeys have increased between 1971 and 1990, although the levels of lakes Vanda and Bonney have increased more than those of the others. [Pg.729]

Fig. 19.40 The Sr/ Sr ratios of strontium in Lake Vanda vary only between 0.7146 and 0.7150 and are essentially independent of depth in the water. These ratios are different from the Sr/ Sr ratios of basalt (0.7043) and seawater (0.7094) which indicates that the strontium in Lake Vanda did not originate from these sources. The concentrations of strontium range from 0.141 ppm at 4 m to 67.1 ppm at 60 m and were plotted as the logarithms to the base 10 in order to accommodate the wide range of variation. The concentration profile identifies chemoclines at depth of about 15 and 50 m below the surface of the ice (Data from Jones and Faure 1967)... Fig. 19.40 The Sr/ Sr ratios of strontium in Lake Vanda vary only between 0.7146 and 0.7150 and are essentially independent of depth in the water. These ratios are different from the Sr/ Sr ratios of basalt (0.7043) and seawater (0.7094) which indicates that the strontium in Lake Vanda did not originate from these sources. The concentrations of strontium range from 0.141 ppm at 4 m to 67.1 ppm at 60 m and were plotted as the logarithms to the base 10 in order to accommodate the wide range of variation. The concentration profile identifies chemoclines at depth of about 15 and 50 m below the surface of the ice (Data from Jones and Faure 1967)...
Figure 6. Model 2 in Specific Heat, Heat Transfer and Climate Change Modeling activity. Arctic sea ice coverage in 2015 compared to median extent from 1981 to 2000. (Source National Snow and Ice Data Center data from (19)). (see... Figure 6. Model 2 in Specific Heat, Heat Transfer and Climate Change Modeling activity. Arctic sea ice coverage in 2015 compared to median extent from 1981 to 2000. (Source National Snow and Ice Data Center data from (19)). (see...
What is the precision of the information provided by each sea ice data source ... [Pg.181]

Is the usefulness of particular sea ice data sources the same for each ice class of vessels ... [Pg.181]

Could vessel determine more favourable route if the content of sea ice data sources was taken into account ... [Pg.181]

Verification of ice data presented by remote sensing sourcesNIS maps named c map3... [Pg.188]

See other pages where Ice Data is mentioned: [Pg.110]    [Pg.424]    [Pg.55]    [Pg.133]    [Pg.503]    [Pg.227]    [Pg.579]    [Pg.49]    [Pg.200]    [Pg.202]    [Pg.315]    [Pg.645]    [Pg.671]    [Pg.202]    [Pg.390]    [Pg.183]    [Pg.191]    [Pg.192]    [Pg.202]   


SEARCH



Ice core data

© 2024 chempedia.info