scholarly journals Recent changes in the Norske Øer Ice Barrier, coastal Northeast Greenland

2016 ◽  
Vol 57 (73) ◽  
pp. 47-55 ◽  
Author(s):  
William A. Sneed ◽  
Gordon S. Hamilton
Keyword(s):  
Logistic Regression ◽  
Sea Ice ◽  
Statistical Model ◽  
20Th Century ◽  
Rare Event ◽  
Complex Interaction ◽  
Weather Station ◽  
Degree Days ◽  
Wind Speeds ◽  
Extensive Region

ABSTRACTIn Northeast Greenland, the Norske Øer Ice Barrier (NØIB) abuts Nioghalvfjerdsfjorden (79N) and Zachariae Isstrøm (ZI), two floating outlets of the Northeast Greenland Ice Stream. NØIB is an extensive region of perennially fast sea ice, which varies in size from year to year, but with complete breakup a rare event in the 20th century. It reportedly broke up in the 1950s and was seen to break up in 1997. Since 2000 the NØIB has broken up during 11 of the last 14 summers. The forcings driving the increased frequency of ice barrier breakup are poorly understood, and it is not clear if the breakup is a purely local phenomenon or an indicator of regional changes in the ocean and atmosphere. Here we use a logistic regression statistical model to show that the odds of breakup are linked to June positive degree days and July wind speeds at a nearby weather station. It is too soon to know if subtle changes detected on 79N and ZI in the last decade are connected to breakups of the NØIB but, if they are, it suggests a complex interaction between the atmosphere, ocean and outlet glaciers in this part of Greenland.

scholarly journals The importance of wind-blown snow redistribution to snow accumulation on Bellingshausen Sea ice

2011 ◽  
Vol 52 (57) ◽  
pp. 271-278 ◽  
Author(s):  
Katherine C. Leonard ◽  
Ted Maksym
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Wind Speeds ◽  
Antarctic Sea Ice ◽  
Drifting Snow ◽  
Bellingshausen Sea ◽  
Ice Mass Balance ◽  
High Winds

AbstractSnow distribution is a dominating factor in sea-ice mass balance in the Bellingshausen Sea, Antarctica, through its roles in insulating the ice and contributing to snow-ice production. the wind has long been qualitatively recognized to influence the distribution of snow accumulation on sea ice, but the relative importance of drifting and blowing snow has not been quantified over Antarctic sea ice prior to this study. the presence and magnitude of drifting snow were monitored continuously along with wind speeds at two sites on an ice floe in the Bellingshausen Sea during the October 2007 Sea Ice Mass Balance in the Antarctic (SIMBA) experiment. Contemporaneous precipitation measurements collected on board the RVIB Nathaniel B. Palmer and accumulation measurements by automated ice mass-balance buoys (IMBs) allow us to document the proportion of snowfall that accumulated on level ice surfaces in the presence of high winds and blowing-snow conditions. Accumulation on the sea ice during the experiment averaged <0.01 m w.e. at both IMB sites, during a period when European Centre for Medium-Range Weather Forecasts analyses predicted >0.03 m w.e. of precipitation on the ice floe. Accumulation changes on the ice floe were clearly associated with drifting snow and high winds. Drifting-snow transport during the SIMBA experiment was supply-limited. Using these results to inform a preliminary study using a blowing-snow model, we show that over the entire Southern Ocean approximately half of the precipitation over sea ice could be lost to leads.

scholarly journals Effect of Glaciers on Annual Run-Off, Johan Dahl Land, South Greenland

1988 ◽  
Vol 34 (117) ◽  
pp. 200-207 ◽  
Author(s):  
R. J. Braithwaite ◽  
Ole B. Olesen
Keyword(s):  
Statistical Model ◽  
Negative Correlation ◽  
Seasonal Variations ◽  
Data Sets ◽  
Weather Station ◽  
Moderate Amount ◽  
Run Off ◽  
Few Data

AbstractRun-off data for two basins in south Greenland, one of which contains glaciers, are compared with precipitation at a nearby weather station and with ablation measured in the glacier basin. Seasonal variations of run-off for the two basins are broadly similar while run-off from the glacier basin has smaller year-to-year variations. A simple statistical model shows that this is the result of a negative correlation between ablation and precipitation, which has the effect of reducing run-off variations in basins with a moderate amount of glacier cover although run-off variations may become large again for highly glacierized basins. The model also predicts an increasing run-off with ablation correlation and a decreasing run-off with precipitation correlation as the amount of glacier cover increases. Although there are still too few data sets from other parts of Greenland for final conclusions, there are indications that the present findings may be applicable to other Greenland basins.

Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

2021 ◽  
Author(s):  
Vladimir Semenov ◽  
Tatiana Matveeva
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
The North ◽  
Arctic Sea ◽  
Ice Concentration

&lt;p&gt;Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20&lt;sup&gt;th&lt;/sup&gt; century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model&amp;#8217;s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20&lt;sup&gt;th&lt;/sup&gt; century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km&lt;sup&gt;2&lt;/sup&gt; in September and 0.7 million km&lt;sup&gt;2&lt;/sup&gt; in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21&lt;sup&gt;st&lt;/sup&gt; century.&lt;/p&gt;

Meteorological and hydrological conditions triggering rockfall events in Germany

2021 ◽  
Author(s):  
Katrin Nissen ◽  
Stefan Rupp ◽  
Björn Guse ◽  
Uwe Ulbrich ◽  
Sergiy Vorogushyn ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Soil Moisture ◽  
Statistical Model ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Daily Precipitation ◽  
Hydrologic Model ◽  
Data Set ◽  
Hydrological Conditions ◽  
Landslide Database

&lt;p&gt;In this study we present the results of a logistic regression model aimed at describing changes in probabilities for rockfall events in Germany in response to changes in meteorological and hydrological conditions.&lt;/p&gt;&lt;p&gt;The rockfall events for this study are taken from the landslide database for Germany (Damm and Klose, 2015). The meteorological variables we tested as predictors for the logistic regression model are daily precipitation from the REGNIE data set (Rauthe et al. 2013), hourly precipitation from the RADKLIM radar climatology (Winterrath et al., 2018) and temperature from the E-OBS data set (Cornes et al., 2018). As there is no observational soil moisture data set covering the entire country, we used soil moisture modelled with the state-of-the-art hydrological model mHM (Samaniego et al. 2010), which was calibrated using gauge measurements.&lt;/p&gt;&lt;p&gt;In order to select the best statistical model we tested a large number of physically plausible combinations of meteorological and hydrological predictors. Each model was checked using cross-validation. The decision on the final model was based on the value of the logarithmic skill score and on expert judgement.&lt;/p&gt;&lt;p&gt;The final statistical model includes the local percentile of daily precipitation, total relative soil moisture and freeze-thawing cycles in the previous weeks as predictors. It was found that daily precipitation is the most important parameter in the model. An increase of daily precipitation from its median to its 80th percentile approximately doubles the probability for a rockfall event. Higher soil moisture and the occurrence of freeze-thaw cycles also increase the probability for rockfall events.&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;br&gt;Cornes, R. C. et al., 2018: An ensemble version of the E&amp;#8208;OBS temperature and precipitation data sets. Journal of Geophysical Research: Atmospheres, 123, 9391&amp;#8211; 9409.&lt;/p&gt;&lt;p&gt;Damm, B., Klose, M., 2015. The landslide database for Germany: Closing the gap at national level. Geomorphology 249, 82&amp;#8211;93&lt;/p&gt;&lt;p&gt;Rauthe, M. et al., 2013: A Central European precipitation climatology &amp;#8211; Part I: Generation and validation of a high-reso-lution gridded daily data set (HYRAS), Vol. 22(3), p 235&amp;#8211;256.&lt;/p&gt;&lt;p&gt;Samaniego, L. et al., 2010: Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46,W05523&lt;/p&gt;&lt;p&gt;Winterrath, T. et al., 2018: RADKLIM Version 2017.002: Reprocessed gauge-adjusted radar data, one-hour precipitation sums (RW), DOI: 10.5676/DWD/RADKLIM_RW_V2017.002.&lt;/p&gt;

scholarly journals Early start of 20th-century Arctic sea-ice decline recorded in Svalbard coralline algae

Geology ◽  
2019 ◽  
Vol 47 (10) ◽  
pp. 963-967 ◽  
Author(s):  
Steffen Hetzinger ◽  
Jochen Halfar ◽  
Zoltán Zajacz ◽  
Max Wisshak
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Global Climate ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Coralline Algae ◽  
Sea Ice Extent ◽  
Early 19Th Century ◽  
Arctic Sea ◽  
Annual Resolution

Abstract The fast decline of Arctic sea ice is a leading indicator of ongoing global climate change and is receiving substantial public and scientific attention. Projections suggest that Arctic summer sea ice may virtually disappear within the course of the next 50 or even 30 yr with rapid Arctic warming. However, limited observational records and lack of annual-resolution marine sea-ice proxies hamper the assessment of long-term changes in sea ice, leading to large uncertainties in predictions of its future evolution under global warming. Here, we use long-lived encrusting coralline algae that strongly depend on light availability as a new in situ proxy to reconstruct past variability in the duration of seasonal sea-ice cover. Our data represent the northernmost annual-resolution marine sea-ice reconstruction to date, extending to the early 19th century off Svalbard. Algal records show that the decreasing trend in sea-ice cover in the high Arctic had already started at the beginning of the 20th century, earlier than previously reported from sea-ice reconstructions based on terrestrial archives. Our data further suggest that, although sea-ice extent varies on multidecadal time scales, the lowest sea-ice values within the past 200 yr occurred at the end of the 20th century.

Input Attribution for Statistical Model Checking Using Logistic Regression

2016 ◽  
pp. 185-200 ◽  
Author(s):  
Jeffery P. Hansen ◽  
Sagar Chaki ◽  
Scott Hissam ◽  
James Edmondson ◽  
Gabriel A. Moreno ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Model Checking ◽  
Statistical Model ◽  
Statistical Model Checking

Effect of weather station logging interval on the precision of degree-day estimates

1995 ◽  
Vol 35 (6) ◽  
pp. 795 ◽  
Author(s):  
DM Watson ◽  
GAC Beattie
Keyword(s):  
Weather Station ◽  
Data Logging ◽  
Degree Days ◽  
Degree Day ◽  
The Relationship

The relationship between data-logging intervals and degree-day estimates was examined to determine the longest interval giving equivalent information to estimates based on 12-min intervals and, so, the most efficient interval for estimation of degree-days

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