Sentences with phrase «using ocean heat data»

(Wm - 2) This figure is consistent with the calculations in Hansen et al. 2005 using ocean heat data.

Hansen 2005, using ocean heat data, calculated the planet's energy imbalance around 2003 to be 0.85 Wm?

Interestingly, they use the ocean heat data with the erroneous 2003 cooling trend (see Figure 5.1).

Interestingly, they use the ocean heat data with the erroneous 2003 cooling trend (see Figure 5.1).

Not exact matches

The scientists, led by Eric Oliver of Dalhousie University in Canada, investigated long - term heat wave trends using a combination of satellite data collected since the 1980s and direct ocean temperature measurements collected throughout the 21st century to construct a nearly 100 - year record of marine heat wave frequency and duration around the world.

Rather than use a model - based estimate, as did Hansen (2005) and Trenberth (2009), the authors achieve this by calculating it from observations of ocean heat content (down to 1800 metres) from the PMEL / JPL / JIMAR data sets over the period July 2005 to June 2010 - a time period dominated by the superior ARGO - based system.

To calculate the Earth's total heat content, the authors used data of ocean heat content from the upper 700 metres.

This paper uses Argo buoy data to calculate ocean heat down to 2000 metres depth.

A total of 2.3 million salinity profiles were used in this analysis, about one - third of the amount of data used in the ocean heat content estimates in Section 5.2.2.

ECCO model - data syntheses are being used to quantify the ocean's role in the global carbon cycle, to understand the recent evolution of the polar oceans, to monitor time - evolving heat, water, and chemical exchanges within and between different components of the Earth system, and for many other science applications.

The Web GIS tutorial video and the teacher guide also models data exploration and analysis techniques for using the elevation - profile tool to discover that ocean bathymetry is related to both surface heat flow and the age of the ocean floor.

In situ and reanalyzed data are used to trace the pathways of ocean heat uptake.

The RF time series are linked to the observations of ocean heat content and temperature change through an energy balance model and a stochastic model, using a Bayesian approach to estimate the ECS from the data.

This is at least ten additional years compared to the majority of previously published studies that have used the instrumental record in attempts to constrain the ECS.We show that the additional 10 years of data, and especially 10 years of additional ocean heat content data, have significantly narrowed the probability density function of the ECS.

Balmaseda et al. (2013) was a key study on this subject, using ocean heat content data from the European Centre for Medium - Range Weather Forecasts» Ocean Reanalysis System 4 (ORocean heat content data from the European Centre for Medium - Range Weather Forecasts» Ocean Reanalysis System 4 (OROcean Reanalysis System 4 (ORAS4).

DK12 used ocean heat content (OHC) data for the upper 700 meters of oceans to draw three main conclusions: 1) that the rate of OHC increase has slowed in recent years (the very short timeframe of 2002 to 2008), 2) that this is evidence for periods of «climate shifts», and 3) that the recent OHC data indicate that the net climate feedback is negative, which would mean that climate sensitivity (the total amount of global warming in response to a doubling of atmospheric CO2 levels, including feedbacks) is low.

Large and Yeager (2012) examined global ocean average net heat flux variability using the CORE data set over 1984 — 2006 and concluded that natural variability, rather than long - term climate change, dominates heat flux changes over this relatively short, recent period.

26; (2) 0.07 + / - 0.05 Wm - 2 from ocean heat storage at depths below 2,000 m using data from 1981 to 2010 (ref.

The data used in estimating the Levitus et al. (2005a) ocean temperature fields (for the above heat content estimates) do not include sea surface temperature (SST) observations, which are discussed in Chapter 3.

The consistency between these two data sets gives confidence in the ocean temperature data set used for estimating depth - integrated heat content, and supports the trends in SST reported in Chapter 3.

Despite the fact that there are differences between these three ocean heat content estimates due to the data used, quality control applied, instrumental biases, temporal and spatial averaging and analysis methods (Appendix 5.

The US CLIVAR / OCB Southern Ocean Working Group was formed to identify critical observational targets and develop data / model metrics based on the currently available observational data, both physical and tracer, and the assimilative modeling (re) analyses, and evaluate and develop our understanding of the importance of mesoscale eddies in the heat and carbon uptake and of the response of the Southern Ocean to a changing climate, using high - resolution numerical studies and theory.

They did the same with ocean heat storage; that is, they failed to use the raw data but only averaged data.

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...

I would have liked to see mention of uncertainty that inherent in examining short term data, whether the end points used introduces an element of bias, whether the «pause» is on a much higher plateau of warming than in the past, whether decadel cycles in ocean heat displacement may have interacted with the the known minimum levels of solar activity (not modelled) to cause this «pause».

Fred — I don't think that the Gregory 02 lower bound estimate of sensitivity is at all reliable, because it is highly sensitive to the particular values of the ocean heat and forcings data used.

These pieces of empirical data are then used to support mathematical models that correlate CO2 increases to increasing heating of the atmosphere and oceans.

PS I think that it is misleading to claim that I substituted my own input values — the ocean heat data I used came from the main such dataset, and the forcings data from one of the best known forcings datasets.

Dessler (2011) used observational data (such as surface temperature measurements and ARGO ocean temperature) to estimate and corroborate these values, and found that the heating of the climate system through ocean heat transport was 20 times larger than TOA energy flux changes due to cloud cover over the period in question.

Using corrected ocean heat data and the GISS forcings data, the bottom of the 10 % -90 % confidence interval is a sensitivity of about 0.8 C. And using the forcings in AR4 WG1 Fig. 2.23, it would be about 0Using corrected ocean heat data and the GISS forcings data, the bottom of the 10 % -90 % confidence interval is a sensitivity of about 0.8 C. And using the forcings in AR4 WG1 Fig. 2.23, it would be about 0using the forcings in AR4 WG1 Fig. 2.23, it would be about 0.6 C.

If the corrected 2005 Levitus dataset ocean heat flux data and the GISS change in radiative forcings estimates were used, (Q — F) in the Gregory 02 equation (3) would be centred on 0.68 Wm - 2 instead of on 0.20 Wm - 2.

Scientists use Weddell and southern elephant seals to gather data and monitor the way currents move heat around the world's oceans.

«A more accurate comparison of global ocean / land energy imbalances would be GISS (since they use Arctic data), and ocean heat content down to 2000 meters.»

Wong et al used Earth Radiation Budget Experiment data and compared that to more dense XPT data compiled by Joel Norris as annual ocean heat content.

Actually Fielding's use of that graph is quite informative of how denialist arguments are framed — the selected bit of a selected graph (and don't mention the fastest warming region on the planet being left out of that data set), or the complete passing over of short term variability vs longer term trends, or the other measures and indicators of climate change from ocean heat content and sea levels to changes in ice sheets and minimum sea ice levels, or the passing over of issues like lag time between emissions and effects on temperatures... etc..

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»

No, the model result is only used to estimate ocean heat uptake in the base period, which is before observational data was available.

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).

Then about three years ago, those same scientists, using those same data sets, admitted there was a pause, and spent their energy explaining why it didn't matter (ocean heat content being a better proxy was the most popular).

But worse is your paper with Nic Lewis, which seems to go out of its way to get a low ECS by purposely not using the best data available for surface temperatures, ocean heat content, and with no consideration of aerosols at all.

The way I see it, if you get various data points of ocean heat content, you then have to plot a trend to see how that is changing with the other changes in incoming and outgoing radiation and greenhouse gases andland use etc..

«Our results demonstrate how synergistic use of satellite TOA radiation observations and recently improved ocean heat content measurements, with appropriate error estimates, provide critical data for quantifying short - term and longer - term changes in the Earth's net TOA radiation imbalance.

The method preferred by the GWPF report, and that which Lewis has used in his own papers, involves estimating climate sensitivity using a combination of recent instrumental temperature data (including ocean heat content data), less complex climate models, and statistics.

No: that is the beauty of using top of atmosphere radiative balance data — it automatically reflects the flow of heat into the ocean, so thermal inertia of the oceans is irrelevant to the estimate of equilibrium climate sensitivity that it provides, unlike with virtally all other instrumental methods.

NASA's «GISS» temp uses land and ocean - based thermometers which measure «different parts of the system [UHI affected parking lots, asphalt heat sinks, AC exhaust air vents], different signal to noise ratio [we bias toward warm stations], different structural uncertainty [we «homogenise» our data set to cool the past and warm the present to fit the global warming narrative].»

As for lying, I have observed many scientists seem to have no difficulty with lying when they connect, without a shred of evidence, supportive modeling or any data or often even any theory such things as extreme weather is getting worse or is linked to CO2, wet areas will get wetter and dry areas will get drier, that the ocean swallowed the «missing heat», using a proxy upside down doesn't matter, the models are still adequate for policy even after such a huge divergence from reality, coral die - back is due to manmade warming rather than fishing, all warming must be bad rather than beyond a certain threshold, etc, etc, etc..

Using the last 30y of ocean heat data and simply adopting the official IPCC forcing values rather than his modified versions» I agree that would have been a useful addition to my work.

Using 1981 - 2011 ocean heat data (again for 0 - 2000m, from Levitus et al, 2012), rather than the last 10 years, to compute the trend would have reduced the recent - period OHU estimate, scaling up as before to allow for heat uptake in the deeper ocean and elsewhere, by 0.08 W / m.

In a paper, «Heat Capacity, Time Constant, and Sensitivity of Earth's Climate System» soon to be published in the Journal of Geophysical Research (and discussed briefly at RealClimate a few weeks back), Stephen Schwartz of Brookhaven National Laboratory estimates climate sensitivity using observed 20th - century data on ocean heat content and global surface temperatHeat Capacity, Time Constant, and Sensitivity of Earth's Climate System» soon to be published in the Journal of Geophysical Research (and discussed briefly at RealClimate a few weeks back), Stephen Schwartz of Brookhaven National Laboratory estimates climate sensitivity using observed 20th - century data on ocean heat content and global surface temperatheat content and global surface temperature.

The effective climate sensitivity and ocean heat uptake are compared by Raper et al. (2001b) using the CMIP2 data set (1 % / yr CO2 increase to doubling).