Sentences with phrase «global ocean temperature data»

Near - global ocean temperature data sets made available in recent years allow a direct calculation of thermal expansion.

Not exact matches

Average global land and ocean temperatures have climbed at a rate of 0.2 °C per decade since 1976, according to data compiled by the National Climatic Data Center (NCDC) in Asheville, North Carolina, and the World Meteorological Organization (WMO) in Geneva, Switzerldata compiled by the National Climatic Data Center (NCDC) in Asheville, North Carolina, and the World Meteorological Organization (WMO) in Geneva, SwitzerlData Center (NCDC) in Asheville, North Carolina, and the World Meteorological Organization (WMO) in Geneva, Switzerland.

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.

However, comparison of the global, annual mean time series of near - surface temperature (approximately 0 to 5 m depth) from this analysis and the corresponding SST series based on a subset of the International Comprehensive Ocean - Atmosphere Data Set (ICOADS) database (approximately 134 million SST observations; Smith and Reynolds, 2003 and additional data) shows a high correlation (r = 0.96) for the period 1955 to 2Data Set (ICOADS) database (approximately 134 million SST observations; Smith and Reynolds, 2003 and additional data) shows a high correlation (r = 0.96) for the period 1955 to 2data) shows a high correlation (r = 0.96) for the period 1955 to 2005.

A new analysis of nearly five decades of data has revealed the oceans» dissolved oxygen levels started dropping in the 1980s as global temperatures began to climb.

«In the global [land and ocean] temperature anomaly data series of 1880 to 2010, the trend presented an increase of 0.6 oC per Century.

can point me to the data that show that global ocean temperatures are decreasing (if they are?)

The objective of our study was to quantify the consistency of near - global and regional integrals of ocean heat content and steric sea level (from in situ temperature and salinity data), total sea level (from satellite altimeter data) and ocean mass (from satellite gravimetry data) from an Argo perspective.

From what I see from the Global Historical Climatology Network (GHCN) of land temperatures and the Comprehensive Ocean - Atmosphere Data Set (COADS) of SST data, temperatures there were higher around the 1930's than now, and there is not much long term warming trend, except for the past few yeData Set (COADS) of SST data, temperatures there were higher around the 1930's than now, and there is not much long term warming trend, except for the past few yedata, temperatures there were higher around the 1930's than now, and there is not much long term warming trend, except for the past few years.

But I would suppose that equilibrium climate sensitivity [background] and even global mean surface temperature on a decadal scale could be better nailed down by model pruning and better ocean data.

«The average global temperature anomaly for combined land and ocean surfaces for July (based on preliminary data) was 1.1 degrees F (0.6 degrees C) above the 1880 - 2004 long - term mean.

Global hurricane frequency versus global ocean temperatures - Top image from FSU ACE, bottom image from GISS ocean data plotted by WUWT - click for largerGlobal hurricane frequency versus global ocean temperatures - Top image from FSU ACE, bottom image from GISS ocean data plotted by WUWT - click for largerglobal ocean temperatures - Top image from FSU ACE, bottom image from GISS ocean data plotted by WUWT - click for larger image

«Another recent paper used a different NOAA ocean surface temperature data set to find that since 2003 the global average ocean surface temperature has been rising at a rate that is an order of magnitude smaller than the rate of increase reported in Karl's paper.»

If scientists need to rely on bucket samples of water to prove the historic global temperature of our oceans, perhaps it is time to recognise that there are some aspects of our climate data that are not worth relying on.

We can look at the impacts of the GISS infilling method by subtracting the global GISS land - ocean temperature index data with 250 km smoothing from the GISS data with 1200 km smoothing.

A global - scale instrumental temperature record that has not been contaminated by (a) artificial urban heat (asphalt, machines, industrial waste heat, etc.), (b) ocean - air affected biases (detailed herein), or (c) artificial adjustments to past data that uniformly serve to cool the past and warm the present... is now available.

Forest 2006, along with several other climate sensitivity studies, used simulations by the MIT 2D model of zonal surface and upper - air temperatures and global deep - ocean temperature, the upper - air data being least influential.

The Group for High Resolution SST (GHRSST) is a follow on activity form the Global Ocean Data Assimilation Experiment (GODAE) high - resolution sea surface temperature pilot project (GHRSST - PP) provides a new generation of global high - resolution (< 10 km) SST data products to the operational oceanographic, meteorological, climate and general scientific community, in real time and delayedGlobal Ocean Data Assimilation Experiment (GODAE) high - resolution sea surface temperature pilot project (GHRSST - PP) provides a new generation of global high - resolution (< 10 km) SST data products to the operational oceanographic, meteorological, climate and general scientific community, in real time and delayed mData Assimilation Experiment (GODAE) high - resolution sea surface temperature pilot project (GHRSST - PP) provides a new generation of global high - resolution (< 10 km) SST data products to the operational oceanographic, meteorological, climate and general scientific community, in real time and delayedglobal high - resolution (< 10 km) SST data products to the operational oceanographic, meteorological, climate and general scientific community, in real time and delayed mdata products to the operational oceanographic, meteorological, climate and general scientific community, in real time and delayed mode.

When he presented his misleading graph, when he said 97 % of climate scientists agree, (knowing full well the actual situation that the number is bogus and misleading,) when he mentions adjustments to satellite data but not to surface temperatures with major past cooling and absurd derived precision to.005 * C, when he defends precision in surface global averages but ignores major estimates of temps and krigging in Arctic, Africa, Asia and oceans or Antarctica, he forfeits credibility.

However, comparison of the global, annual mean time series of near - surface temperature (approximately 0 to 5 m depth) from this analysis and the corresponding SST series based on a subset of the International Comprehensive Ocean - Atmosphere Data Set (ICOADS) database (approximately 134 million SST observations; Smith and Reynolds, 2003 and additional data) shows a high correlation (r = 0.96) for the period 1955 to 2Data Set (ICOADS) database (approximately 134 million SST observations; Smith and Reynolds, 2003 and additional data) shows a high correlation (r = 0.96) for the period 1955 to 2data) shows a high correlation (r = 0.96) for the period 1955 to 2005.

Surface warming / ocean warming: «A reassessment of temperature variations and trends from global reanalyses and monthly surface climatological datasets» «Estimating changes in global temperature since the pre-industrial period» «Possible artifacts of data biases in the recent global surface warming hiatus» «Assessing the impact of satellite - based observations in sea surface temperature trends»

According to data from the reanalysis produced by the European Centre for Medium - Range Weather Forecasts, the January to October combined land and ocean global average temperature would place 2014 as third or fourth highest for this dataset, which runs from 1958.

Previous large natural oscillations are important to examine: however, 1) our data isn't as good with regards to external forcings or to historical temperatures, making attribution more difficult, 2) to the extent that we have solar and volcanic data, and paleoclimate temperature records, they are indeed fairly consistent with each other within their respective uncertainties, and 3) most mechanisms of internal variability would have different fingerprints: eg, shifting of warmth from the oceans to the atmosphere (but we see warming in both), or simultaneous warming of the troposphere and stratosphere, or shifts in global temperature associated with major ocean current shifts which for the most part haven't been seen.

In the present study, satellite altimetric height and historically available in situ temperature data were combined using the method developed by Willis et al. [2003], to produce global estimates of upper ocean heat content, thermosteric expansion, and temperature variability over the 10.5 - year period from the beginning of 1993 through mid-2003...

To conduct the research, a team of scientists led by John Fasullo of the US National Center for Atmospheric Research in Boulder, Colorado, combined data from three sources: NASA's GRACE satellites, which make detailed measurements of Earth's gravitational field, enabling scientists to monitor changes in the mass of continents; the Argo global array of 3,000 free - drifting floats, which measure the temperature and salinity of the upper layers of the oceans; and satellite - based altimeters that are continuously calibrated against a network of tide gauges.

So, if we could reduce the ocean blip by, say 0.15 deg C, then this would be significant for the global mean — but we'd still have to explain the land blip...» — Dr. Tom Wigley, University Corporation for Atmospheric Research, on adjusting global temperature data, disclosed Climategate e-mail to Phil Jones, Sep. 28, 2008

You seem to be leaving out the ocean temperature data, as additional evidence for global warming independent of the urban heating effect: http://www.john-daly.com/mobydick/oceans.htm

C: increase in atmospheric CO2 from pre-industrial to present is anthropogenic (D / A) S: best guess for likely climate sensitivity (NUM) s: 2 - sigma range of S (NUM) a: ocean acidification will be a problem (D / A) L: expected sea level rise by 2100 in cm (all contributions)(NUM) B: climate change will be beneficial (D / A) R: CO2 emissions need to be reduced drastically by 2050 (D / A) T: technical advances will take care of any problems (D / A) r: the 20th century global temperature record is reliable (D / A) H: over the last 1000 years global temperature was hockey stick shaped (D / A) D: data has been intentionally distorted by scientist to support the idea of anthropogenic climate change (D / A) g: the CRU - mails are important for the science (D / A) G: the CRU - mails are important otherwise (D / A)

The tiny, close - knit clique of climate scientists who invented and now drive the «global warming» fraud — for fraud is what we now know it to be — tampered with temperature data so assiduously that, on the recent admission of one of them, land temperatures since 1980 have risen twice as fast as ocean temperatures.

C. warmer than it was with respect to the start of the industrial revolution, I believe that it would be necessary to use actual average global land - ocean surface temperature data (which would be imperfectly known that far back).

Unfortunately, we don't have good ocean heat content data for this period, while the data we do have — global mean atmospheric surface temperature — is dominated by ocean oscillations.

Both NASA GISS and NOAA NCEI use NOAA's ERSST.v4 «pause buster» data for the ocean surface temperature components of their combined land - ocean surface temperature datasets, and, today, both agencies are holding a multi-agency press conference to announce their «warmest ever» 2016 global surface temperature findings.

As noted above, the ERSST.v4 data make up the ocean portion of the NOAA and GISS global land + ocean surface temperature products.

Why on earth did we pay so much money for the ARGO floats, the only instrumentation actually designed for the task of measuring global ocean temperature accurately to hundredths of a degree, if we don't use the data?

Where admitted very poor and very dodgy data from ships buckets and engine inlets is used to adjust reliable ocean buoy data upwards and then the adjusted data is promoted as the new global temperature data.

Because the GISS analysis combines available sea surface temperature records with meteorological station measurements, we test alternative choices for the ocean data, showing that global temperature change is sensitive to estimated temperature change in polar regions where observations are limited.

The National Climatic Data Center (NCDC), which is part of the National Oceanic and Atmospheric Administration (NOAA), has maintained global average monthly and annual records of combined land and ocean surface temperatures for more than 130 years.

The feedbacks, including subsurface ocean warming, help explain paleoclimate data and point to a dominant Southern Ocean role in controlling atmospheric CO2, which in turn exercised tight control on global temperature and sea locean warming, help explain paleoclimate data and point to a dominant Southern Ocean role in controlling atmospheric CO2, which in turn exercised tight control on global temperature and sea lOcean role in controlling atmospheric CO2, which in turn exercised tight control on global temperature and sea level.

This is consistent with the comparison by Roemmich and Gilson (2009) of Argo data with the global temperature time - series of Levitus et al (2005), finding a warming of the 0 - 2000 m ocean by 0.06 °C since the (pre-XBT) early 1960's.»

The near - linear rate of anthropogenic warming (predominantly from anthropogenic greenhouse gases) is shown in sources such as: «Deducing Multidecadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis» «The global warming hiatus — a natural product of interactions of a secular warming trend and a multi-decadal oscillation» «The Origin and Limits of the Near Proportionality between Climate Warming and Cumulative CO2 Emissions» «Sensitivity of climate to cumulative carbon emissions due to compensation of ocean heat and carbon uptake» «Return periods of global climate fluctuations and the pause» «Using data to attribute episodes of warming and cooling in instrumental records» «The proportionality of global warming to cumulative carbon emissions» «The sensitivity of the proportionality between temperature change and cumulative CO2 emissions to ocean mixing&Global Warming Trends Using Multiple Regression Analysis» «The global warming hiatus — a natural product of interactions of a secular warming trend and a multi-decadal oscillation» «The Origin and Limits of the Near Proportionality between Climate Warming and Cumulative CO2 Emissions» «Sensitivity of climate to cumulative carbon emissions due to compensation of ocean heat and carbon uptake» «Return periods of global climate fluctuations and the pause» «Using data to attribute episodes of warming and cooling in instrumental records» «The proportionality of global warming to cumulative carbon emissions» «The sensitivity of the proportionality between temperature change and cumulative CO2 emissions to ocean mixing&global warming hiatus — a natural product of interactions of a secular warming trend and a multi-decadal oscillation» «The Origin and Limits of the Near Proportionality between Climate Warming and Cumulative CO2 Emissions» «Sensitivity of climate to cumulative carbon emissions due to compensation of ocean heat and carbon uptake» «Return periods of global climate fluctuations and the pause» «Using data to attribute episodes of warming and cooling in instrumental records» «The proportionality of global warming to cumulative carbon emissions» «The sensitivity of the proportionality between temperature change and cumulative CO2 emissions to ocean mixing&global climate fluctuations and the pause» «Using data to attribute episodes of warming and cooling in instrumental records» «The proportionality of global warming to cumulative carbon emissions» «The sensitivity of the proportionality between temperature change and cumulative CO2 emissions to ocean mixing&global warming to cumulative carbon emissions» «The sensitivity of the proportionality between temperature change and cumulative CO2 emissions to ocean mixing»

«Causes of differences in model and satellite tropospheric warming rates» «Comparing tropospheric warming in climate models and satellite data» «Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures» «Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends» «Reconciling warming trends» «Natural variability, radiative forcing and climate response in the recent hiatus reconciled» «Reconciling controversies about the «global warming hiatus»»

So, perhaps, it should be no surprise that in a June 2015 article in Science magazine, National Oceanic and Atmospheric Administration (NOAA) authors attempted to eliminate the pause in warming by ignoring their own satellite data and introducing new global ocean surface temperature sets whose readings are taken from buoys and engine - intakes on vessels.

This is consistent with the comparison by Roemmich and Gilson (2009) of Argo data with the global temperature time - series of Levitus et al (2005), finding a warming of the 0 — 2000 m ocean by 0.06 °C since the (pre-XBT) early 1960's.

The global ocean temperature analysis is primarily based on buoy and ship observations from the International Comprehensive Ocean Atmosphere Dataset (ICOADS), while monthly data updates come from the Global Telecommunications System global ocean temperature analysis is primarily based on buoy and ship observations from the International Comprehensive Ocean Atmosphere Dataset (ICOADS), while monthly data updates come from the Global Telecommunications System (ocean temperature analysis is primarily based on buoy and ship observations from the International Comprehensive Ocean Atmosphere Dataset (ICOADS), while monthly data updates come from the Global Telecommunications System (Ocean Atmosphere Dataset (ICOADS), while monthly data updates come from the Global Telecommunications System Global Telecommunications System (GTS).

All of these characteristics (except for the ocean temperature) have been used in SAR and TAR IPCC (Houghton et al. 1996; 2001) reports for model - data inter-comparison: we considered as tolerable the following intervals for the annual means of the following climate characteristics which encompass corresponding empirical estimates: global SAT 13.1 — 14.1 °C (Jones et al. 1999); area of sea ice in the Northern Hemisphere 6 — 14 mil km2 and in the Southern Hemisphere 6 — 18 mil km2 (Cavalieri et al. 2003); total precipitation rate 2.45 — 3.05 mm / day (Legates 1995); maximum Atlantic northward heat transport 0.5 — 1.5 PW (Ganachaud and Wunsch 2003); maximum of North Atlantic meridional overturning stream function 15 — 25 Sv (Talley et al. 2003), volume averaged ocean temperature 3 — 5 °C (Levitus 1982).

A slight change of ocean temperature (after a delay caused by the high specific heat of water, the annual mixing of thermocline waters with deeper waters in storms) ensures that rising CO2 reduces infrared absorbing H2O vapour while slightly increasing cloud cover (thus Earth's albedo), as evidenced by the fact that the NOAA data from 1948 - 2008 shows a fall in global humidity (not the positive feedback rise presumed by NASA's models!)

Figure 2: Impact of SST bias on the global (i.e. land / ocean) temperature record estimated from the HadSST3 data.

One of the main limitations of Cowtan and Way (in press), which we highlighted in the paper and has been echoed by others, is that the global temperature reconstruction was performed on the blended land - ocean data.

OWASLT = Sum (Temp x Mass x Heat Capacity) / Sum (Mass x Heat Capacity), and looking at all pieces of mass components in the atmosphere + mass in the ocean (say down to 2000m or whatever depth would appropriate with respect to available global data & that should rightfully be included for an all inclusive weighted average temperature like this).

Mosh, I asked you on a previous thread what your estimate of the accuracy of the global mean temperature is, given the sparse data on the Arctic, Anarctic, Africa, Asia, South Atlantic ocean and Pacific ocean?