Sentences with phrase «sea level pressure data»

I need hourly mean sea level pressure data for the recent years.

This updated dataset includes more data sources than the HadSLP v1.0 and is updated to April 2006, this dataset is documented in an upcoming J. Climate manuscript (Allan, R. and T. Ansell: A new globally - complete monthly historical gridded mean sea level pressure data set (HadSLP2): 1850 - 2004.

Not exact matches

The analysis of high - frequency surface air temperature, mean sea - level pressure, wind speed and direction and cloud - cover data from the solar eclipse of 20 March 2015 from the UK, Faroe Islands and Iceland, published today (Monday 22 August 2016), sheds new light on the phenomenon.

Here we analyze a series of climate model experiments along with observational data to show that the recent warming trend in Atlantic sea surface temperature and the corresponding trans - basin displacements of the main atmospheric pressure centers were key drivers of the observed Walker circulation intensification, eastern Pacific cooling, North American rainfall trends and western Pacific sea - level rise.

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 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.

Given the increased levels of certainty regarding human - induced global warming (from 90 to 95 %), more robust projections on sea - level rise and data on melting of ice sheets, and the «carbon budget» for staying below the 2 °C target, the WGI conclusions together with other AR5 component reports are likely to put more pressure on the UNFCCC parties to deliver by 2015 an ambitious agreement that is capable of preventing dangerous anthropogenic interference with the climate system.

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 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.

I challege you to find the sea level data at UCB that haven't been corrected for basin movement, seaonality, salinity, barometric pressure, etc..

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.

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 E-OBS holds gridded data for daily values of the precipitation amount, the daily mean - sea - level pressure and the daily maximum, mean and minimum temperatures from January 1950 onward.

While derived from sea surface temperature data, the PDO index is well correlated with many records of North Pacific and Pacific Northwest climate and ecology, including sea level pressure, winter land — surface temperature and precipitation, and stream flow.

Anyway, one of the things on my todo list is to look into where the pressures used to adjust sea level data come from.

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

There's also a barometer inside just incase you want to check atmospheric pressure — or eventually calculate your height above sea level, just as soon as you grab an app that's able to read the data.