Sentences with phrase «in sea surface temperature data»

And of course the new paper by Hausfather et al, that made quite a bit of news recently, documents how meticulously scientists work to eliminate bias in sea surface temperature data, in this case arising from a changing proportion of ship versus buoy observations.

In the new study, the researchers searched for such events recorded in sea surface temperature data recorded as far back as 1900 and in satellite data since 1982.

Not exact matches

Their data showed that the difference between polar and equatorial sea surface temperatures in the Eocene was an estimated 20 degrees Celsius, about 36 degrees Fahrenheit.

Using different calibration and filtering processes, the two researchers succeeded in combining a wide variety of available data from temperature measurements and climate archives in such a way that they were able to compare the reconstructed sea surface temperature variations at different locations around the globe on different time scales over a period of 7,000 years.

One of the subtle changes visible in the new data - set is how the Amazon's greenness corresponds to one of the long - known causes of rainfall or drought to the Amazon basin: changes in sea surface temperatures in the eastern Pacific Ocean, called the El Nino Southern Oscillation.

«The data showed that both greenhouse gases and sea surface temperature anomalies contributed strongly to the risk of snow drought in Oregon and Washington,» said Mote, a professor in OSU's College of Earth, Ocean, and Atmospheric Sciences.

In the new set - up, a real - world seasonal forecast driven by data on current sea - surface temperatures will be run alongside a simulated «no global warming» seasonal forecast, in which greenhouse gas emissions have been stripped ouIn the new set - up, a real - world seasonal forecast driven by data on current sea - surface temperatures will be run alongside a simulated «no global warming» seasonal forecast, in which greenhouse gas emissions have been stripped ouin which greenhouse gas emissions have been stripped out.

Analyzing data collected over a 20 - month period, scientists from NASA's Goddard Space Flight center in Greenbelt, Md., and the Massachusetts Institute of Technology found that the number of cirrus clouds above the Pacific Ocean declines with warmer sea surface temperatures.

«In our study we used satellite data for sea ice and sea surface temperatures to run some coordinated hindcast experiments with five different atmospheric models,» Ogawa says.

Nathaniel Johnson and Shang - Ping Xie at the University of Hawaii studied satellite and rain - gauge data from the last 30 years and found that sea surface temperatures in the tropics now need to be about 0.3 °C higher than they did in 1980 before the air above rises and produces rain (Nature Geoscience, DOI: 10.1038 / ngeo1008).

The evaluation of the data show a clear correlation between the sea surface temperatures in the Irminger Sea in summer, the amount of surface freshwater in this region and the atmospheric conditions and onset of convection in the following wintsea surface temperatures in the Irminger Sea in summer, the amount of surface freshwater in this region and the atmospheric conditions and onset of convection in the following wintSea in summer, the amount of surface freshwater in this region and the atmospheric conditions and onset of convection in the following winter.

To develop the model, they compared historic fire data from NASA's Terra satellite with sea surface temperature data in the tropical Pacific and North Atlantic oceans from buoys and satellite images compiled by the National Oceanic and Atmospheric Administration.

The data, in the form of infrared images of the Earth's surface, is used to detect changes in sea surface temperatures for research -LSB-...]

Sea surface temperature data since 1882 document large El Niño - like patterns following four out of five big eruptions: Santa María (Guatemala) in October 1902, Mount Agung (Indonesia) in March 1963, El Chichón (Mexico) in April 1982 and Pinatubo in June 1991.

The first image, based on data from January 1997 when El Nio was still strengthening shows a sea level rise along the Equator in the eastern Pacific Ocean of up to 34 centimeters with the red colors indicating an associated change in sea surface temperature of up to 5.4 degrees C.

The reason could be linked to rising sea surface temperatures — fueled in part by global warming — as seen in ocean buoy data collected along the U.S. coast.

Climatology data from the historical record give a picture of the fluctuations in sea - surface temperature over the last 160 years.

I found problems with the data including: ««⠉ NOAA buoys measuring near - to - sea - surface air temperature — e.g. inadequate shielding of direct solar heating ««⠉ ship - based sea surface temperature — e.g. variable points in cooling systems for diesel versus steam ship propulsion

It is widely realized that WWii saw changes in the construction of sampling buckets for sea surface temperature measurement, and many navies switching to water intake temperatures in compiling data from ships at sea.

Like almost all historical climate data, ship - board sea surface temperatures (SST) were not collected with long term climate trends in mind.

In addition, the early data for sea surface temperatures is not global, which further limits the usefulness of these data for long period harmonic analysis.

«The treatment of the buoy sea - surface temperature (SST) data was guaranteed to put a warming trend in recent data.

------------ PS: The Global Coral Reef Alliance has documented dramatic declines in coral reefs caused by global warming of surface waters, using satellite data of of global coral reefs and sea surface temperatures.

(1) In addition to the data of the near - surface temperatures, which are composed of measurements from weather stations and sea surface temperatures, there is also the microwave data from satellites, which can be used to estimate air temperatures in the troposphere in a few kilometers altitudIn addition to the data of the near - surface temperatures, which are composed of measurements from weather stations and sea surface temperatures, there is also the microwave data from satellites, which can be used to estimate air temperatures in the troposphere in a few kilometers altitudin the troposphere in a few kilometers altitudin a few kilometers altitude.

For instance, for the Last Glacial Maximum, model - data mis - matches highlighted by Rind and Peteet (1985) for the tropical sea surface temperatures, have subsequently been more or less resolved in favour of the models.

Using monthly - averaged global satellite records from the International Satellite Cloud Climatology Project (ISCCP [5]-RRB- and the MODerate Resolution Imaging Spectroradiometer (MODIS) in conjunction with Sea Surface Temperature (SST) data from the National Oceanic and Atmospheric (NOAA) extended and reconstructed SST (ERSST) dataset [7] we have examined the reliability of long - term cloud measurements.

There is good evidence that the answer to both these question is no: (The insensitivy of the results to methodology of selecting rural stations, the Parker et al windy days study, and the fact that data from satellite skin surface measurements, from sea surface temperatures, deep ocean temps as we as tropospheric temps are all in good agreement).

One thing I would have liked to see in the paper is a quantitative side - by - side comparison of sea - surface temperatures and upper ocean heat content; all the paper says is that only «a small amount of cooling is observed at the surface, although much less than the cooling at depth» though they do report that it is consistent with 2 - yr cooling SST trend — but again, no actual data analysis of the SST trend is reported.

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.

But while the graph was only for SST (sea surface temperature, something different of SAT — surface air temperature, even at sea), the influence of the solar cycle and volcanic episodes (El Chicon and Pinatubo) is visible globally in the oceans until a depth of 300 m in the Levitus data.

The first data series — from calcareous shells of marine organisms that live 50 to 200 metres below the sea surface in the northern Atlantic — shows the temperature conditions there.

The AARI data include drifting stations and ice information, although not the majority (my fault to see that as «main»), that means that the difference between only land based and total is in warmer sea surface temperatures.

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.

The gridded field is produced from ship and buoy sea surface temperatures in the ICOADS release 2.5 data set (29) using bias correction and Empirical Orthogonal Teleconnection methodologies as described in (13).

In a study published in the journal Nature the researchers say analysis of sea surface temperature data shows that the AMOC has slowed down by roughly 15 % since the middle of the 20th century, with human - made climate change a prime suspecIn a study published in the journal Nature the researchers say analysis of sea surface temperature data shows that the AMOC has slowed down by roughly 15 % since the middle of the 20th century, with human - made climate change a prime suspecin the journal Nature the researchers say analysis of sea surface temperature data shows that the AMOC has slowed down by roughly 15 % since the middle of the 20th century, with human - made climate change a prime suspect.

In our analysis we use eight well - known datasets: 1) globally averaged well - mixed marine boundary layer CO2 data, 2) HadCRUT3 surface air temperature data, 3) GISS surface air temperature data, 4) NCDC surface air temperature data, 5) HadSST2 sea surface temperature data, 6) UAH lower troposphere temperature data series, 7) CDIAC data on release of anthropogene CO2, and 8) GWP data on volcanic eruptions.

The NINO3.4 data represent the Sea Surface Temperature of a region in the central equatorial Pacific bound by the coordinates of 5S - 5N, 170W - 120W.

The hybrid method used by Cowtan and Way (2013) fills in missing data (both land air and sea surface temperature) using lower troposphere temperature data from UAH.

In the case of ORAS4, this includes ocean temperature measurements from bathythermographs and the Argo buoys, and other types of data like sea surface height and surface temperatures.

«In regards to sea surface temperature, scientists have shown that across the board, data collected from buoys are cooler than ship - based data,» one of the study's co-authors wrote, adding, «Scientists have developed a method to correct the difference between ship and buoy measurements, and we are using this in our trend analysis.&raquIn regards to sea surface temperature, scientists have shown that across the board, data collected from buoys are cooler than ship - based data,» one of the study's co-authors wrote, adding, «Scientists have developed a method to correct the difference between ship and buoy measurements, and we are using this in our trend analysis.&raquin our trend analysis.»

GISS also masks sea surface temperature wherever sea ice has existed so there is little data in the Arctic Ocean.

In the main part of the paper, for China, we compare a new homogenized station data set with gridded temperature products and attempt to assess possible urban influences using sea surface temperature (SST) data sets for the area east of the Chinese mainland.

I also suspect that a good portion of the additional warming shown in the hybrid version of the Cowtan and Way (2013) data (versus their Krig data) comes from the Southern Ocean surrounding Antarctica, where sea surface temperatures are cooling and lower troposphere temperatures are warming.

The basic assumption behind the Cowtan and Way (2013) paper appears to be, because the HADCRUT4 data doesn't capture the Arctic Ocean (there are no temperature measurements there other than sea surface temperatures when sea ice melts seasonally), the warming in the Arctic is underreported.

As a result, directly comparing the Sea Surface Temperature data from the early 20th century to the current Sea Surface Temperature data is like «comparing apples and oranges» — there have been too many changes in the data sources for such comparisons to have much meaning.

Investigators outside NOAA are finding interesting trends and showing that they seem to be correlated with trends in such variables as SST [Sea Surface Temperature] in key regions, the changes of which almost certainly are due to human - induced changes in the climate, though having enough data to get all the statistics right is often problematic.

Give the students the graph below from Johnstone 2014 and ask them to compare changes in sea surface temperatures (SST in red) with the raw and recently homogenized temperature data from southern California.

In summary, the historical [Sea Surface Temperature] record... may well contain instrumental bias effects that render the data of questionable value in determining long period trends in ocean surface temperatures... Investigators that use the data [to try this] bear a heavy, perhaps impossible, responsibility for ensuring that the potential instrument bias has not contaminated their resultIn summary, the historical [Sea Surface Temperature] record... may well contain instrumental bias effects that render the data of questionable value in determining long period trends in ocean surface temperatures... Investigators that use the data [to try this] bear a heavy, perhaps impossible, responsibility for ensuring that the potential instrument bias has not contaminated their rSurface Temperature] record... may well contain instrumental bias effects that render the data of questionable value in determining long period trends in ocean surface temperatures... Investigators that use the data [to try this] bear a heavy, perhaps impossible, responsibility for ensuring that the potential instrument bias has not contaminated their resultin determining long period trends in ocean surface temperatures... Investigators that use the data [to try this] bear a heavy, perhaps impossible, responsibility for ensuring that the potential instrument bias has not contaminated their resultin ocean surface temperatures... Investigators that use the data [to try this] bear a heavy, perhaps impossible, responsibility for ensuring that the potential instrument bias has not contaminated their rsurface temperatures... Investigators that use the data [to try this] bear a heavy, perhaps impossible, responsibility for ensuring that the potential instrument bias has not contaminated their results.

When sceptics look at statistical data, whether it is recent ice melt, deep sea temperatures, current trend in global surface temperatures, troposphere temperatures, ice core records etc. they look at the data as it is without any pre-conceptions and describe what it says.

In this data analysis activity, students explore how hurricanes extract heat energy from the ocean surface by tracking Hurricane Rita and sampling sea surface temperatures along its path.