Sentences with phrase «using ice thickness»

We used the ice thickness in December, ice movement from December to April, and ice concentration in June.

Not exact matches

Icing amounts are very general and will vary with consistency, thickness applied and tips used.

Tips and Notes to the crêpe maker: — I use an Ice cream scooper to portion the batter, this allow me to have equal thickness every time.

Frozen bananas are the best with any smoothie because they add that thickness without using ice.

Clean Eating Green Smoothie Credit @dashingdish (check out her blog) 2 cups Fresh spinach 1/4 medium Banana 1/4 cup Strawberries, diced (about 3 - 4 berries) 1/2 cup Low fat cottage cheese 1 1/4 cup Vanilla or plain protein powder (I use Designer Whey, which is 100 calories per scoop) 1 - 3 pkts Packets of stevia or sweetener of choice (or to taste) 5 - 10 Ice cubes (more or less depending on how thick you like it) 1/2 -1 cup Water (again, alter according to desired thickness of shake) 1 You can not taste the cottage cheese at all, it makes for a creamy protein packed shake!

Use the ice to adjust the thickness to your preference.

In Grayslake, the Fire Protection District checks ice thickness, and the Park District uses a colored rating system to warn people about conditions.

Use frozen fruit or ice to help increase smoothie thickness.

Morris uses the information she gathers on these trips to check the accuracy of data collected by a European satellite, Cryosat - 2, that tracks changes in the thickness of polar ice — information that tells scientists how quickly that ice is thawing.

The study uses data from two NASA missions — Operation IceBridge, which measures ice thickness and gravity from aircraft, and Oceans Melting Greenland, or OMG, which uses sonar and gravity instruments to map the shape and depth of the seafloor close to the ice front.

Millan, a UCI graduate student researcher in Earth system science, and his colleagues analyzed 20 major outlet glaciers in southeast Greenland using high - resolution airborne gravity measurements and ice thickness data from NASA's Operation IceBridge mission; bathymetry information from NASA's Oceans Melting Greenland project; and results from the BedMachine version 3 computer model, developed at UCI.

The cores, some as long as 100 - feet, were transported to Dartmouth where the research team used a light table to measure the thickness and frequency of the ice layers.

Scientists used the data to explore Antarctic ice thickness and the distribution of subglacial lakes.

Although CryoSat - 2 is designed to measure changes in the ice sheet elevation, these can be translated into horizontal motion at the grounding line using knowledge of the glacier and sea floor geometry and the Archimedes principle of buoyancy — which relates the thickness of floating ice to the height of its surface.

It will use ice - penetrating radar to measure the thickness of the moon's ice shell, map its internal rifts and faults (clues to the tempo of its geologic activity) and locate pockets of water near the surface.

For their work Maksym and co-investigators Guy Williams from the University of Hobart, Tasmania and Jeremy Wilkinson of the British Antarctic Survey in Cambridge, UK, used a robot known as an autonomous underwater vehicle (AUV) to cruise under ice in three regions near the coast and measure the thickness directly over a much larger area.

Haas and his team, including Stephen Howell of Environment Canada, measured first - year and multiyear ice thickness in the Canadian Arctic Archipelago using an airplane equipped with an electromagnetic induction sounder or EM bird.

Using all available geologic, tectonic and geothermal heat flux data for Greenland — along with geothermal heat flux data from around the globe — the team deployed a machine learning approach that predicts geothermal heat flux values under the ice sheet throughout Greenland based on 22 geologic variables such as bedrock topography, crustal thickness, magnetic anomalies, rock types and proximity to features like trenches, ridges, young rifts, volcanoes and hot spots.

During the past weeks, sea - ice thickness measurements were the main topic of the TIFAX (Thick Ice Feeding Arctic Export) campaign, which involved research aircraft using laser scanners and a towed electromagnetic proice thickness measurements were the main topic of the TIFAX (Thick Ice Feeding Arctic Export) campaign, which involved research aircraft using laser scanners and a towed electromagnetic proIce Feeding Arctic Export) campaign, which involved research aircraft using laser scanners and a towed electromagnetic probe.

We calculate the WD gas age - ice age difference (Delta age) using a combination of firn densification modeling, ice - flow modeling, and a data set of d15N - N2, a proxy for past firn column thickness.

1994 A method for determining ice - thickness change at remote locations using GPS.

Finnish Meteorological Institute has been doing estimates of two essential sea ice parameters — namely, sea ice concentration (SIC) and sea ice thickness (SIT)-- for the Bohai Sea using a combination of a thermodynamic sea ice model and Earth observation (EO) data from synthetic aperture radar (SAR) and microwave radiometer.

NASA and the USGS have used MRO instruments to analyze the vertical structure and thickness of buried ice sheets, which preserve a detailed record of the Red Planet's past and could provide future human explorers with an easily - accessible water supply.

«He has pioneered the use of AUVs (autonomous underwater vehicles) to measure under - ice topography and has worked with the Royal Navy since the 1970s in carrying out ice thickness measurement work from Navy submarines on Arctic deployments.»

The second is electromagnetic (EM) induction ice thickness measurements gathered using a helicopter by the Alfred Wegener Institute in April 2003.

It is argued that uncertainty, differences and errors in sea ice model forcing sets complicate the use of models to determine the exact causes of the recently reported decline in Arctic sea ice thickness, but help in the determination of robust features if the models are tuned appropriately against observations.

Using comprehensive data sets of observations made between 1979 and 2001 of sea ice thickness, draft, extent, and speeds, we find that it is possible to tune model parameters to give satisfactory agreement with observed data, thereby highlighting the skill of modern sea ice models, though the parameter values chosen differ according to the model forcing used.

There is no other reliable method to measure the thickness of snow than to step on the ice and use poles like Marc did.

The steady state average ice thickness at summer's end used to be about 3 meters, and is now around half that.

There are two ways to categorize the amount of ice: by measuring the extent (essentially the area of the ocean covered by ice, though in detail it's a little more complicated) or using volume, which includes the thickness of the ice.

Canadian Ice Service, 4.7, Multiple Methods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Service, 4.7, Multiple Methods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice predictors.

Canadian Ice Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice predictors.

According to the second study, which measured changes in the thickness and height of ice using radar and laser altimetry instruments flown as part of NASA's Operation IceBridge campaign, the glacier lost between 984 and 1,607 feet in thickness from 2002 to 2009.

And the sonar systems on Los Angelos class fast attack submarines, like the one I went under the ice on, that could measure ice thickness, were of the active variety, projecting sound and listening to the echos, and were rarely, if ever used up there.

Corrigendum to «Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness» published in The Cryosphere, 8, 1839 - 1854, 2014.

Scientists from the University of Erlangen - Nuremberg Institute of Geography and from the Laboratoire de Glaciologie et Gophysique de l'Environnement in Grenoble, France, used radar data from satellites such as ESA's Envisat and observations of ice thickness from airborne surveys in a complex model to demonstrate, for the first time, how the buttressing role of the ice shelves is being compromised as the shelves decline.

Although CryoSat - 2 is designed to measure changes in the ice sheet elevation, these can be translated into horizontal motion at the grounding line using knowledge of the glacier and sea floor geometry and the Archimedes principle of buoyancy — which relates the thickness of floating ice to the height of its surface.

Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea - ice thickness initialization using statistical predictors available in real time.

The DM model has been validated using independent estimates of ice type from QuikSCAT (e.g., Nghiem et al. 2007) and in situ observations of ice thickness from submarines, electromagnetic sensors, etc. (e.g., Haas et al. 2008; Rigor 2005).

These were modified from the CFS v2.0 initial conditions by thinning the ice pack by 60 cm — the thickness which we used as a cutoff in making our 2010 SIO estimates.

«Ice thickness is then calculated using a combination of the freeboard measurements and estimates of snow depth and density derived from a climatology [Warren et al., 1999]»

Researchers used data from IceBridge's ice - penetrating radar — the Multichannel Coherent Radar Depth Sounder, or MCoRDS, which is operated by the Center for Remote Sensing of Ice Sheets at the University of Kansas, Lawrence, Kan. — to determine ice thickness and sub-glacial terrain, and images from satellite sources such as Landsat and Terra to calculate velociice - penetrating radar — the Multichannel Coherent Radar Depth Sounder, or MCoRDS, which is operated by the Center for Remote Sensing of Ice Sheets at the University of Kansas, Lawrence, Kan. — to determine ice thickness and sub-glacial terrain, and images from satellite sources such as Landsat and Terra to calculate velociIce Sheets at the University of Kansas, Lawrence, Kan. — to determine ice thickness and sub-glacial terrain, and images from satellite sources such as Landsat and Terra to calculate velociice thickness and sub-glacial terrain, and images from satellite sources such as Landsat and Terra to calculate velocity.

And for years nuclear submarines (Russian, American and British) have been measuring ice thickness from the bottom, using their sonar.

That gives you a profile of ice thickness, and it is straightforward in principle to use it to calculate the ice volume — though in practice it remains an awful lot of numbers to crunch.

The new ice thickness estimates will also be used to improve on - going seasonal predictions of sea ice extent.

The ensemble consists of seven members each of which uses a unique set of NCEP / NCAR atmospheric forcing fields from recent years, representing recent climate, such that ensemble member 1 uses 2005 NCEP / NCAR forcing, member 2 uses 2006 forcing..., and member 7 uses 2011 forcing... In addition, the recently available IceBridge and helicopter - based electromagnetic (HEM) ice thickness quicklook data are assimilated into the initial 12 - category sea ice thickness distribution fields in order to improve the initial conditions for the predictions.

To make use of that potential we would need good estimates of sea ice thickness, such as might be obtained from ICESat or CryoSat (i.e., complete spatial coverage).

Canadian Ice Service, 4.7 (± 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Service, 4.7 (± 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice predictors.

Ice - ocean model simulations, on the other hand, have requirements with respect to data density and quality, e.g., for observed ice thickness fields used in initialization of model runs, that are currently not being met by existing data sources (with the exception of, e.g., satellite - observed ice concentration fieldIce - ocean model simulations, on the other hand, have requirements with respect to data density and quality, e.g., for observed ice thickness fields used in initialization of model runs, that are currently not being met by existing data sources (with the exception of, e.g., satellite - observed ice concentration fieldice thickness fields used in initialization of model runs, that are currently not being met by existing data sources (with the exception of, e.g., satellite - observed ice concentration fieldice concentration fields).

Our method uses estimates of ice thickness from a coupled ice - ocean model as predictors for a statistical forecast of the minimum ice extent in September.