Sentences with phrase «comparing ocean data»

These reconstructions are highly relevant when comparing ocean data with model simulations of global and regional climate change.

Not exact matches

The team, led by Dr Kira Rehfeld and Dr Thomas Laepple, compared the Greenland data with that from sediments collected in several ocean regions around the globe, as well as from ice - core samples gathered in the Antarctic.

This estimate was compared with results from an ocean model - data synthesis from ECMWF and a leading atmospheric model - data synthesis produced in the US.

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 new findings on Arctic Ocean salinity conditions in the Eocene were calculated in part by comparing ratios of oxygen isotopes locked in ancient shark teeth found in sediments on Banks Island in the Arctic Circle and incorporating the data into a salinity model.

To better understand the physical mechanisms of rapid ocean adjustment, the data was compared with a climate model simulation which covers the same period.

Comparing disease statistics with climate data, he found that the outbreaks roughly coincided with El Niño, the warm Pacific Ocean current that brings higher temperatures and rainfall to this part of Peru.

They compared existing National Oceanic and Atmospheric Administration (NOAA) records of upper - ocean temperatures in coastal waters for each U.S. ocean coastline with records of actual sea level changes from 1955 to 2012, and data from U.S. / European satellite altimeter missions since 1992.

Figure 3 is the comparison of the upper level (top 700m) ocean heat content (OHC) changes in the models compared to the latest data from NODC and PMEL (Lyman et al (2010), doi).

In order to compare these satellite - based observations with ocean heat content it is necessary to anchor the data to an absolute scale.

Another figure worth updating is the comparison of the ocean heat content (OHC) changes in the models compared to the latest data from NODC.

Rather, their analysis shows that if you compare the LGM land cooling with the model land cooling, then the model that fits the land best has much higher GLOBAL climate sensitivity than you get for best fit if you use ocean data.

Nick Moran of The Millions had interesting prospective, mentioning «The emissions and e-waste for e-Readers could be stretched even further if I went down the resource rabbit hole to factor in: electricity needed at the Amazon and Apple data centers; communication infrastructure needed to transmit digital files across vast distances; the incessant need to recharge or replace the batteries of eReaders; the resources needed to recycle a digital device (compared to how easy it is to pulp or recycle a book); the packaging and physical mailing of digital devices; the need to replace a device when it breaks (instead of replacing a book when it's lost); the fact that every reader of eBooks requires his or her own eReading device (whereas print books can be loaned out as needed from a library); the fact that most digital devices are manufactured abroad and therefore transported across oceans.

The next figure is the comparison of the ocean heat content (OHC) changes in the models compared to the latest data from NODC.

Decadal hindcast simulations of Arctic Ocean sea ice thickness made by a modern dynamic - thermodynamic sea ice model and forced independently by both the ERA - 40 and NCEP / NCAR reanalysis data sets are compared for the first time.

On the frequency of the storms, I note that the weather really didn't change much during Dec 04 and part of Jan 05 such that you had four distinct spots in the oceans at 90 intervals in the Southern hemisphere that showed substantial chilling compared to historical data.

A fingerprinting study of the ocean data, compared to GHG / aerosols, ice volumes, solar variance and volcanic influences may give some more insight...

Sorry, I was comparing heat content (not SST, neither SAT) of different parts of the oceans down to 300 m depth (where most of the variation is visible), based on the data of Levitus e.a. which can be downloaded from the NOAA web site.

The 2005 Jan - Sep land data (which is adjusted for urban biases) is higher than the previously warmest year (0.76 °C compared to the 1998 anomaly of 0.75 °C for the same months, and a 0.71 °C anomaly for the whole year), while the land - ocean temperature index (which includes sea surface temperature data) is trailing slightly behind (0.58 °C compared to 0.60 °C Jan - Sep, 0.56 °C for the whole of 1998).

Then compare that with the known emissions, carbon isotope data and increases in CO2 in the ocean and biosphere.

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.

«Hansen now believes he has an answer: All the climate models, compared to the Argo data and a tracer study soon to be released by several NASA peers, exaggerate how efficiently the ocean mixes heat into its recesses.

The accuracy of the data is questionable, the assumption of the initial conditions questionable and comparing oceans to land plus oceans also would add uncertainty, but decreasing ocean energy imbalance makes sense when you consider the change in the rate of sea level rise.

Let us therefore compare satellite data (UAH6.0) with surface data (GISTEMP Land / Ocean) measured for the Southern Hemisphere (SH), from 1979 till 2015: You hopefully see like me a good correlation between the two, shown by both linear estimates and 60 month running means.

Because of that the ocean temperature data, sparse as it may be is the more reliable and most easily compared to paleo.

We can compare this with Jimmy D's pontifications on both mechanism — anthropogenically warming oceans that itself is minor and highly uncertain — and on absurdly short term data that fails by a vast margin to be definitive.

The second plot shows the calculated Ocean Heat Content from the «Callendar model» fitted with the above parameters, and compares it with the 0 - 700m data held by NOAA, based on Levitus.

If you look at the table of ocean heating rates at various depths as a function of time given in the posting directly below this post, it seems that from 0 - 700 m the rate of heating since 2004 has slowed compared to 1983 - 2004, and we don't have any good data below 700m until the Argo data started flowing in (2005 - 2008?).

Ocean heat content each year since 1993 compared to the 1993 - 2013 average (dashed line) from a variety of data sources.

The study compared a 5,000 - year record of strong storms etched in lagoon mud on the Puerto Rican island of Vieques with data on ocean temperatures and climate and storm patterns.

Compare the SAR and the TAR for example, and since then we have many more proxy reconstructions to consider, the satellite analyses corrected, new data about energy imbalances, better observations of ocean currents and temperature, ice sheet behaviour in Greenland and Antarctica and much much more.

Compare the professionalism of NASA's scientists and programs with that of Spencer and Christy (who told Congress in 2013 that no warming had occurred in 15 years, contradicting his own data and laughably contradicting the trend in atmosphere + ocean heat content).

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.

The researchers compared the GNSS - R satellite measurements with data from other sources, including tropical cyclone best track data from the National Oceanic and Atmospheric Administration's National Centers for Environmental Information; two climate reanalysis products; and a spaceborne scatterometer, a tool that uses microwave radar to measure winds near the surface of the ocean.

«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»»

Using the interactive below, you can compare three different time series data sets collected from Station Mauna Loa and Station Aloha in the Pacific Ocean.

The first part of this thesis compares the seasonal cycle and interannual variability of Advanced Very High Resolution Radiometer (AVHRR) and Total Ozone Mapping Spectrometer (TOMS) satellite retrievals over the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set.

Using precipitation data from the University of East Anglia and ocean temperatures from the Hadley Centre combined with climate models, the researchers were able to add or omit the oceanic temperatures and compare the two sets of results.

My attempts to determine the ratios and differences between the observed ocean air versus ocean SST temperature trends to compare with the model results were limited by the sparseness of the observed data.

Data from an ocean glider equipped with a host of scientific instrumentation and deployed ahead of the storm allowed researchers not only to see how sediment was being redistributed by the hurricane as the storm unfolded but also to compare their real - life observations with forecasts from mathematical models.

The pressure error meant that the temperatures were being associated with a point higher in the ocean column than they should have been, and this (given that the ocean cools with depth) introduced a spurious cooling trend when compared to earlier data.

The observation - based (Global Ocean Data Analysis Project; GLODAP) 1994 saturation horizon (solid white line) is also shown to illustrate the projected changes in the saturation horizon compared to the present.

Indo - Pacific Warm Pool and what limited ocean heat content data (vertical temperature anomaly) we have to compare the rate of warming required for full recovery from the LIA.

The oceans and land temperatures have tracked quite closely until recently where the differences between ocean and land have become very pronounced with increasing divergence as is easily seen by comparing land data with land and ocean data.

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).

More recent documentation (Hansen et al. 2010) compares alternative analyses and addresses questions about perception and reality of global warming; various choices for the ocean data are tested; it is also shown that global temperature change is sensitive to estimated temperature change in polar regions, where observations are limited.

The study authors compared the simulations that were correctly synchronized with the ocean cycles (blue data in the left frame below) and the most out - of - sync (grey data in the right frame) to the observed global surface temperature changes (red) for each 15 - year period.

When comparing climate hindcasts to observed land and ocean data (Figure 3), the early 1940's is the only period where observed data lie above model predictions.