Sentences with phrase «as sea level pressure»

However, variables such as sea level pressure or top - of - atmosphere clear - sky shortwave radiation do not cover a sufficiently wide range in some.

Not exact matches

There's often intense local pressure to rebuild communities as they were, he said, even if the future risk from sea - level rise or other climate risks suggests it's not the most prudent path.

For every hurricane in the North Atlantic Basin between 1997 and 2013, they pulled information such as mean sea - level pressure and temperature as well as vertical temperature and humidity profiles, and entered it into a thermodynamic hurricane model that treats each storm as a gigantic heat engine.

These cyclones are characterized by strong localized drops in sea level pressure, and as Arctic - wide decreases in sea level pressure are one of the expected results of climate change, this could increase extreme Arctic cyclone activity, including powerful storms in the spring and fall.

Fisher's pen makes up for a lack of gravity by storing ink in a cartridge pressurized with nitrogen at 35 pounds per square inch — more than twice as much force as sea - level atmospheric pressure on Earth.

As it dove through the gap, Cassini came within about 1,900 miles (3,000 kilometers) of Saturn's cloud tops (where the air pressure is 1 bar — comparable to the atmospheric pressure of Earth at sea level) and within about 200 miles (300 kilometers) of the innermost visible edge of the rings.

The sea level time series is rich in physical phenomena such as tides (caused mostly by the gravitational pull of the Moon and the Sun), meteorological signals (high and low pressure), and signals from climate change.

At 1 bar (the same pressure as at sea level on Earth) Saturn's atmosphere is only 134 K. Saturn has as much mass as 95 Earths would have — and this massive, cold planet rotates fully around every 10.7 hours!

Same as water boiling at sea level at 100C (212F) but at lower temp at high altitudes because pressure is less, same rule applies to refrigerant.

The effects can also be felt as far away as Antarctica where a «dipole» of sea level pressure between the Bellinghausen and Weddell Seas is highly correlated to the ENSO phase and can have important effects on sea ice and Antarctic ecology.

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 predictorAs 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 predictoras 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 predictoras 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 predictoSea 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 predictosea ice 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 predictoSea 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 predictosea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictosea ice predictors.

Reflecting the generally stormy pattern through the month, sea level pressures were well below average (as much as 10 hPa) over the central and eastern Arctic Ocean.

So it sounds like even though at sea level freshwater at 4º or less does not expand when heated, that with the salinity and higher pressure, the deep ocean below 700m is actually expanding as it heats and thus adding a little to searise.

Quadrelli and Wallace (2004) found that many patterns of NH interannual variability can be reconstructed as linear combinations of the first two Empirical Orthogonal Functions (EOFs) of sea level pressure (approximately the NAM and the PNA).

Here we examine how sensitive the SAM (defined as the leading empirical orthogonal function of SH sea level pressure anomalies) is to future GHG concentrations.

The strength of these currents is influenced by the location of the polar fronts as determined by sea level pressures in the Southern and Northern Annular Modes.

The question would seem to be whether the «models of sea level» attempt to correlate regional variation in water depth / mass in production of pressure variation in a «water column», if it is to be understood the limited outline of the question as placed, with relation to regional «surface level» displacement.

Radiation from the atmosphere's greenhouse gases is narrow - band, even at sea level but increasingly so at higher altitudes as the effect of pressure - broadening decreases.

Canadian Ice Service; 5.0; Statistical As with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) 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 predictorAs with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) 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 predictoras 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 predictoras 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 predictoSea 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 predictosea ice predictors.

A negative PDO is a characteristic of a warm Kuroshio - Oyashio Extension — along with ENSO and North Pacific sea level pressure — not vice versa as you stated.

The North Atlantic Oscillation turned positive in spring and can be seen as low sea level pressures over Iceland during May 2011 (Figure 7).

However, if the temperature warms, or the pressure is reduced (for instance if local sea level decreases), the hydrate will break up and release the methane as gas which can bubble up through the ocean and enter the atmosphere.

Daily mean NCEP / NCAR reanalysis data are used as atmospheric forcing, i.e., 10 - m surface winds, 2 - m surface air temperature (SAT), specific humidity, precipitation, evaporation, downwelling longwave radiation, sea level pressure, and cloud fraction.

[Ankh]:» «As for CO2 itself, the old measurements made at sea - level pressure had little to say about the frigid and rarified air in the upper reaches of the atmosphere, where most of the infrared absorption takes place.

The climate shift of 1978 manifests as a strong lift in 200hPa temperature globally with the most extreme change at about 30 ° of latitude in both hemispheres, a pronounced fall in sea level pressure in the south East Pacific, a jump in sea surface temperature in the tropics, the transition between solar cycle 20 and 21 and a hike in the aa index of geomagnetic activity that has slowly sunk along with 200hpa temperature from that time forward.

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 predictoSea 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 predictosea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictosea ice predictors.

The pressure is on climate forecasters to give us more accurate predictions of impacts, such as rising sea levels, but ahead of the Durban climate summit scientists say we still have much to learn

The polar front changes largely in response to sea level pressure difference between the pole and the sub-Antarctic — as measured by the Southern Annular Mode (SAM) index.

And that vast sum of ice melt represents about 220 feet of sea level rise long term so long as the greenhouse gas melt and heat pressure remains.

As warm air rises this leads to the formation of depressions at sea level, or low air pressure weather systems.

This reduces the atmospheric pressure at sea level, leading to what is known as «cyclonic behaviour».

This in turn is influenced by sea level pressure patterns in polar and subpolar regions — as more or less wind and currents are pushed north (Roemmich et al, 2007, Qiu, Bo et al 2006).

The pressure is on climate forecasters to give us more accurate predictions of impacts, such as rising sea levels, but ahead of the Durban climate summit scientists say we still have much to learn When it comes to the environment, how [continue reading...]

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A far as the volume / pressure, in a 30 C saturated volume of air at sea level the specific volume is ~ 0.9 kg / m ^ 3.

It is manifested as strong anomalous easterly trade winds, distinctive sea - level pressure patterns, and large rainfall anomalies in the Pacific, which resemble the Pacific Decadal Oscillation (PDO).

In the ASCII file you are referring to, when a station has reported both surface and sea level pressure, it will coded as type 181 and both reports will be included.

If temperatures are not kept down then Africa faces a range of devastating threats such as crop yield reductions in places of as much 50 % in some countries by 2020; Increased pressure on water supplies for 70 — 250 million people by 2020 and 350 — 600 million by 2050; The cost of adaptation to sea level rises of at least 5 — 10 % of gross domestic product.

SOI data are presented as annual mean sea level pressure anomalies at Tahiti and Darwin.

(Top) Time series of the NPI (sea level pressure during December through March averaged over the North Pacific, 30 ° N to 65 ° N, 160 ° E to 140 ° W) from 1900 to 2005 expressed as normalised departures from the long - term mean (each tick mark on the ordinate represents two standard deviations, or 5.5 hPa).

Note that the ISPD record preserves the original elevation and value (or values if both station and sea level pressure were reported), as well as providing the value as modified to be consistent with the assimilating model's orography.

We examine the annular mode within each hemisphere (defined here as the leading empirical orthogonal function and principal component of hemispheric sea level pressure) as simulated by the Intergovernmental Panel on Climate Change Fourth Assessment Report ensembles of coupled ocean - atmosphere models.

Gillett et al. (2003) compared observed changes in sea level pressure with those predicted by four coupled ocean — atmosphere climate models and concluded as follows.

Atmospheric pressure at sea level rises and falls to some degree as horizontal pressure ridges sweep along but the average pressure remains the same at 1 bar.

As there are numerous techniques for determining sea level pressures from atmospheric observations, all having limitations, we also compared the SLP fields generated in the above way for general consistency with those generated using an independent method.

As discussed in the July Outlook, low sea level pressure (SLP) dominated the Arctic Ocean in July, leading to ice divergence and cooler temperatures that helped to slow the fast pace of ice loss observed in May and June.

Same as Fig 1 but for the rank histogram of the climate variables such as surface air temperature (SAT, red solid), SAT trend (red dotted), precipitation (blue), sea level pressure (green), SW net, cloud radiative forcing, clear - sky radiation (orange solid, dotted, and dashed), and LW net, cloud radiative forcing, and clear - sky radiation (cyan solid, dotted, dashed) at the TOA.

However, during the second half of July, ice loss slowed substantially as the high pressure over the central Arctic and Beaufort Sea was replaced by low sea level pressure (Figure Sea was replaced by low sea level pressure (Figure sea level pressure (Figure 3).

We use the nine climate variables such as surface air temperature, precipitation, sea level pressure, shortwave (SW) and longwave (LW) net flux, cloud radiative forcing, and clear - sky flux